Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, G.C.; Martinez, R.F.

1999-05-04

A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

PubMed Central

Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli

2014-01-01

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks. PMID:25014095

Clustering-based ensemble learning for activity recognition in smart homes.

PubMed

Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli

2014-07-10

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

A conserved mechanism for replication origin recognition and binding in archaea.

PubMed

Majerník, Alan I; Chong, James P J

2008-01-15

To date, methanogens are the only group within the archaea where firing DNA replication origins have not been demonstrated in vivo. In the present study we show that a previously identified cluster of ORB (origin recognition box) sequences do indeed function as an origin of replication in vivo in the archaeon Methanothermobacter thermautotrophicus. Although the consensus sequence of ORBs in M. thermautotrophicus is somewhat conserved when compared with ORB sequences in other archaea, the Cdc6-1 protein from M. thermautotrophicus (termed MthCdc6-1) displays sequence-specific binding that is selective for the MthORB sequence and does not recognize ORBs from other archaeal species. Stabilization of in vitro MthORB DNA binding by MthCdc6-1 requires additional conserved sequences 3' to those originally described for M. thermautotrophicus. By testing synthetic sequences bearing mutations in the MthORB consensus sequence, we show that Cdc6/ORB binding is critically dependent on the presence of an invariant guanine found in all archaeal ORB sequences. Mutation of a universally conserved arginine residue in the recognition helix of the winged helix domain of archaeal Cdc6-1 shows that specific origin sequence recognition is dependent on the interaction of this arginine residue with the invariant guanine. Recognition of a mutated origin sequence can be achieved by mutation of the conserved arginine residue to a lysine or glutamine residue. Thus despite a number of differences in protein and DNA sequences between species, the mechanism of origin recognition and binding appears to be conserved throughout the archaea.

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

Optimal wavelength band clustering for multispectral iris recognition.

PubMed

Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

2012-07-01

This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

Infrared spectroscopy of protonated trimethylamine-(benzene)(n) (n = 1-4) as model clusters of the quaternary ammonium-aromatic ring interaction.

PubMed

Shishido, Ryunosuke; Kawai, Yuki; Fujii, Asuka

2014-09-04

The essence of the molecular recognition of the neurotransmitter acetylcholine has been attributed to the attractive interaction between a quaternary ammonium and aromatic rings. We employed protonated trimethylamine-(benzene)n clusters (n = 1-4) in the gas phase as a model to study the recognition mechanism of acetylcholine at the microscopic level. We applied size-selective infrared spectroscopy to the clusters and observed the NH and CH stretching vibrational regions. We also performed density functional theory calculations of stable structures, charge distributions, and infrared spectra of the clusters. It was shown that the methyl groups of protonated trimethylamine are solvated by benzene one at a time in the n > 1 clusters, and the validity of these clusters as a model system of the acetylcholine recognition was demonstrated. The nature of the interactions between a quaternary ammonium and aromatic rings is discussed on the basis of the observed infrared spectra and the theoretical calculations.

Imaging Systems: What, When, How.

ERIC Educational Resources Information Center

Lunin, Lois F.; And Others

1992-01-01

The three articles in this special section on document image files discuss intelligent character recognition, including comparison with optical character recognition; selection of displays for document image processing, focusing on paperlike displays; and imaging hardware, software, and vendors, including guidelines for system selection. (MES)

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-01-01

This report describes a study conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information. The study gathered data from a large number of pilots who conduct all type...

Emotion Recognition Deficits in Schizophrenia-Spectrum Disorders and Psychotic Bipolar Disorder: Findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Study

PubMed Central

Ruocco, Anthony C.; Reilly, James L.; Rubin, Leah H.; Daros, Alex R.; Gershon, Elliot S.; Tamminga, Carol A.; Pearlson, Godfrey D.; Hill, S. Kristian; Keshavan, Matcheri S.; Gur, Ruben C.; Sweeney, John A.

2014-01-01

Background Difficulty recognizing facial emotions is an important social-cognitive deficit associated with psychotic disorders. It also may reflect a familial risk for psychosis in schizophrenia-spectrum disorders and bipolar disorder. Objective The objectives of this study from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were to: 1) compare emotion recognition deficits in schizophrenia, schizoaffective disorder and bipolar disorder with psychosis, 2) determine the familiality of emotion recognition deficits across these disorders, and 3) evaluate emotion recognition deficits in nonpsychotic relatives with and without elevated Cluster A and Cluster B personality disorder traits. Method Participants included probands with schizophrenia (n=297), schizoaffective disorder (depressed type, n=61; bipolar type, n=69), bipolar disorder with psychosis (n=248), their first-degree relatives (n=332, n=69, n=154, and n=286, respectively) and healthy controls (n=380). All participants completed the Penn Emotion Recognition Test, a standardized measure of facial emotion recognition assessing four basic emotions (happiness, sadness, anger and fear) and neutral expressions (no emotion). Results Compared to controls, emotion recognition deficits among probands increased progressively from bipolar disorder to schizoaffective disorder to schizophrenia. Proband and relative groups showed similar deficits perceiving angry and neutral faces, whereas deficits on fearful, happy and sad faces were primarily isolated to schizophrenia probands. Even non-psychotic relatives without elevated Cluster A or Cluster B personality disorder traits showed deficits on neutral and angry faces. Emotion recognition ability was moderately familial only in schizophrenia families. Conclusions Emotion recognition deficits are prominent but somewhat different across psychotic disorders. These deficits are reflected to a lesser extent in relatives, particularly on angry and neutral faces. Deficits were evident in non-psychotic relatives even without elevated personality disorder traits. Deficits in facial emotion recognition may reflect an important social-cognitive deficit in patients with psychotic disorders. PMID:25052782

Emotion recognition deficits in schizophrenia-spectrum disorders and psychotic bipolar disorder: Findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study.

PubMed

Ruocco, Anthony C; Reilly, James L; Rubin, Leah H; Daros, Alex R; Gershon, Elliot S; Tamminga, Carol A; Pearlson, Godfrey D; Hill, S Kristian; Keshavan, Matcheri S; Gur, Ruben C; Sweeney, John A

2014-09-01

Difficulty recognizing facial emotions is an important social-cognitive deficit associated with psychotic disorders. It also may reflect a familial risk for psychosis in schizophrenia-spectrum disorders and bipolar disorder. The objectives of this study from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were to: 1) compare emotion recognition deficits in schizophrenia, schizoaffective disorder and bipolar disorder with psychosis, 2) determine the familiality of emotion recognition deficits across these disorders, and 3) evaluate emotion recognition deficits in nonpsychotic relatives with and without elevated Cluster A and Cluster B personality disorder traits. Participants included probands with schizophrenia (n=297), schizoaffective disorder (depressed type, n=61; bipolar type, n=69), bipolar disorder with psychosis (n=248), their first-degree relatives (n=332, n=69, n=154, and n=286, respectively) and healthy controls (n=380). All participants completed the Penn Emotion Recognition Test, a standardized measure of facial emotion recognition assessing four basic emotions (happiness, sadness, anger and fear) and neutral expressions (no emotion). Compared to controls, emotion recognition deficits among probands increased progressively from bipolar disorder to schizoaffective disorder to schizophrenia. Proband and relative groups showed similar deficits perceiving angry and neutral faces, whereas deficits on fearful, happy and sad faces were primarily isolated to schizophrenia probands. Even non-psychotic relatives without elevated Cluster A or Cluster B personality disorder traits showed deficits on neutral and angry faces. Emotion recognition ability was moderately familial only in schizophrenia families. Emotion recognition deficits are prominent but somewhat different across psychotic disorders. These deficits are reflected to a lesser extent in relatives, particularly on angry and neutral faces. Deficits were evident in non-psychotic relatives even without elevated personality disorder traits. Deficits in facial emotion recognition may reflect an important social-cognitive deficit in patients with psychotic disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

Individual recognition based on communication behaviour of male fowl.

PubMed

Smith, Carolynn L; Taubert, Jessica; Weldon, Kimberly; Evans, Christopher S

2016-04-01

Correctly directing social behaviour towards a specific individual requires an ability to discriminate between conspecifics. The mechanisms of individual recognition include phenotype matching and familiarity-based recognition. Communication-based recognition is a subset of familiarity-based recognition wherein the classification is based on behavioural or distinctive signalling properties. Male fowl (Gallus gallus) produce a visual display (tidbitting) upon finding food in the presence of a female. Females typically approach displaying males. However, males may tidbit without food. We used the distinctiveness of the visual display and the unreliability of some males to test for communication-based recognition in female fowl. We manipulated the prior experience of the hens with the males to create two classes of males: S(+) wherein the tidbitting signal was paired with a food reward to the female, and S (-) wherein the tidbitting signal occurred without food reward. We then conducted a sequential discrimination test with hens using a live video feed of a familiar male. The results of the discrimination tests revealed that hens discriminated between categories of males based on their signalling behaviour. These results suggest that fowl possess a communication-based recognition system. This is the first demonstration of live-to-video transfer of recognition in any species of bird. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition.

PubMed

Bianne-Bernard, Anne-Laure; Menasri, Farès; Al-Hajj Mohamad, Rami; Mokbel, Chafic; Kermorvant, Christopher; Likforman-Sulem, Laurence

2011-10-01

This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. Decision trees are built according to a set of expert-based questions on how characters are written. Questions are divided into global questions, yielding larger clusters, and precise questions, yielding smaller ones. Such clustering enables us to reduce the total number of models and Gaussians densities by 10. We then apply this modeling to the recognition of handwritten words. Experiments are conducted on three publicly available databases based on Latin or Arabic languages: Rimes, IAM, and OpenHart. The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition.

A Survey on Sentiment Classification in Face Recognition

NASA Astrophysics Data System (ADS)

Qian, Jingyu

2018-01-01

Face recognition has been an important topic for both industry and academia for a long time. K-means clustering, autoencoder, and convolutional neural network, each representing a design idea for face recognition method, are three popular algorithms to deal with face recognition problems. It is worthwhile to summarize and compare these three different algorithms. This paper will focus on one specific face recognition problem-sentiment classification from images. Three different algorithms for sentiment classification problems will be summarized, including k-means clustering, autoencoder, and convolutional neural network. An experiment with the application of these algorithms on a specific dataset of human faces will be conducted to illustrate how these algorithms are applied and their accuracy. Finally, the three algorithms are compared based on the accuracy result.

Automated thematic mapping and change detection of ERTS-A images

NASA Technical Reports Server (NTRS)

Gramenopoulos, N. (Principal Investigator)

1975-01-01

The author has identified the following significant results. In the first part of the investigation, spatial and spectral features were developed which were employed to automatically recognize terrain features through a clustering algorithm. In this part of the investigation, the size of the cell which is the number of digital picture elements used for computing the spatial and spectral features was varied. It was determined that the accuracy of terrain recognition decreases slowly as the cell size is reduced and coincides with increased cluster diffuseness. It was also proven that a cell size of 17 x 17 pixels when used with the clustering algorithm results in high recognition rates for major terrain classes. ERTS-1 data from five diverse geographic regions of the United States were processed through the clustering algorithm with 17 x 17 pixel cells. Simple land use maps were produced and the average terrain recognition accuracy was 82 percent.

Cross-cultural emotional prosody recognition: evidence from Chinese and British listeners.

PubMed

Paulmann, Silke; Uskul, Ayse K

2014-01-01

This cross-cultural study of emotional tone of voice recognition tests the in-group advantage hypothesis (Elfenbein & Ambady, 2002) employing a quasi-balanced design. Individuals of Chinese and British background were asked to recognise pseudosentences produced by Chinese and British native speakers, displaying one of seven emotions (anger, disgust, fear, happy, neutral tone of voice, sad, and surprise). Findings reveal that emotional displays were recognised at rates higher than predicted by chance; however, members of each cultural group were more accurate in recognising the displays communicated by a member of their own cultural group than a member of the other cultural group. Moreover, the evaluation of error matrices indicates that both culture groups relied on similar mechanism when recognising emotional displays from the voice. Overall, the study reveals evidence for both universal and culture-specific principles in vocal emotion recognition.

Vocal Affect Recognition and Psychopathy: Converging Findings Across Traditional and Cluster Analytic Approaches to Assessing the Construct

PubMed Central

Bagley, Amy D.; Abramowitz, Carolyn S.; Kosson, David S.

2010-01-01

Deficits in emotion processing have been widely reported to be central to psychopathy. However, few prior studies have examined vocal affect recognition in psychopaths, and these studies suffer from significant methodological limitations. Moreover, prior studies have yielded conflicting findings regarding the specificity of psychopaths’ affect recognition deficits. This study examined vocal affect recognition in 107 male inmates under conditions requiring isolated prosodic vs. semantic analysis of affective cues and compared subgroups of offenders identified via cluster analysis on vocal affect recognition. Psychopaths demonstrated deficits in vocal affect recognition under conditions requiring use of semantic cues and conditions requiring use of prosodic cues. Moreover, both primary and secondary psychopaths exhibited relatively similar emotional deficits in the semantic analysis condition compared to nonpsychopathic control participants. This study demonstrates that psychopaths’ vocal affect recognition deficits are not due to methodological limitations of previous studies and provides preliminary evidence that primary and secondary psychopaths exhibit generally similar deficits in vocal affect recognition. PMID:19413412

An Evaluation and Comparison of Several Measures of Image Quality for Television Displays

DTIC Science & Technology

1979-01-01

vehicles, buildings, or faces , or they may be artificial much as trn-bar patterns, rectangles, or sine waves. The typical objective image quality assessment...Snyder (1974b) wac able to obtain very good correlations with reaction time and correct responses for a face recognition task. Display quality was varied...recognition versus log JUDA for the target recognition study of Chapter 4, 5) graph of angle oubtended by target at recognitio , versus log JNDA for the

Selective Attention in Vision: Recognition Memory for Superimposed Line Drawings.

ERIC Educational Resources Information Center

Goldstein, E. Bruce; Fink, Susan I.

1981-01-01

Four experiments show that observers can selectively attend to one of two stationary superimposed pictures. Selective recognition occurred with large displays in which observers were free to make eye movements during a 3-sec exposure and with small displays in which observers were instructed to fixate steadily on a point. (Author/RD)

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

PubMed

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.

Innate predator recognition in giant pandas.

PubMed

Du, Yiping; Huang, Yan; Zhang, Hemin; Li, Desheng; Yang, Bo; Wei, Ming; Zhou, Yingmin; Liu, Yang

2012-02-01

Innate predator recognition confers a survival advantage to prey animals. We investigate whether giant pandas exhibit innate predator recognition. We analyzed behavioral responses of 56 naive adult captive giant pandas (Ailuropoda melanoleuca), to urine from predators and non-predators and water control. Giant pandas performed more chemosensory investigation and displayed flehmen behaviors more frequently in response to predator urine compared to both non-predator urine and water control. Subjects also displayed certain defensive behaviors, as indicated by vigilance, and in certain cases, fleeing behaviors. Our results suggest that there is an innate component to predator recognition in captive giant pandas, although such recognition was only slight to moderate. These results have implications that may be applicable to the conservation and reintroduction of this endangered species.

Integrated multimodal human-computer interface and augmented reality for interactive display applications

NASA Astrophysics Data System (ADS)

Vassiliou, Marius S.; Sundareswaran, Venkataraman; Chen, S.; Behringer, Reinhold; Tam, Clement K.; Chan, M.; Bangayan, Phil T.; McGee, Joshua H.

2000-08-01

We describe new systems for improved integrated multimodal human-computer interaction and augmented reality for a diverse array of applications, including future advanced cockpits, tactical operations centers, and others. We have developed an integrated display system featuring: speech recognition of multiple concurrent users equipped with both standard air- coupled microphones and novel throat-coupled sensors (developed at Army Research Labs for increased noise immunity); lip reading for improving speech recognition accuracy in noisy environments, three-dimensional spatialized audio for improved display of warnings, alerts, and other information; wireless, coordinated handheld-PC control of a large display; real-time display of data and inferences from wireless integrated networked sensors with on-board signal processing and discrimination; gesture control with disambiguated point-and-speak capability; head- and eye- tracking coupled with speech recognition for 'look-and-speak' interaction; and integrated tetherless augmented reality on a wearable computer. The various interaction modalities (speech recognition, 3D audio, eyetracking, etc.) are implemented a 'modality servers' in an Internet-based client-server architecture. Each modality server encapsulates and exposes commercial and research software packages, presenting a socket network interface that is abstracted to a high-level interface, minimizing both vendor dependencies and required changes on the client side as the server's technology improves.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

PubMed Central

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease. PMID:27977767

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

PubMed

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease.

A Genetic Algorithm That Exchanges Neighboring Centers for Fuzzy c-Means Clustering

ERIC Educational Resources Information Center

Chahine, Firas Safwan

2012-01-01

Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition

PubMed Central

Cui, Zhiming; Zhao, Pengpeng

2014-01-01

A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045

Methods and Systems for Representing, Using and Displaying Time-Varying Information on the Semantic Web

DTIC Science & Technology

2013-11-26

Combination with Simple Features," lEE European Workshop on Handwriting Analysis and Recognition, pp. 6/1-6, Brussels, Jul. 1994. Bock, J., et a...Document Analysis and Recognition, pp. 147-150, Oct. 1993. Starner, T., eta!., "On-Line Cursive Handwriting Recognition Using Speech Recognition Methods

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

PubMed

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

2016-03-01

In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats displayed a significant interaction between the two groups and the number of available objects suggesting impairment in a pattern completion function for object cues. Copyright © 2015 Elsevier Inc. All rights reserved.

Logo image clustering based on advanced statistics

NASA Astrophysics Data System (ADS)

Wei, Yi; Kamel, Mohamed; He, Yiwei

2007-11-01

In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.

Getting the Gist of Events: Recognition of Two-Participant Actions from Brief Displays

PubMed Central

Hafri, Alon; Papafragou, Anna; Trueswell, John C.

2013-01-01

Unlike rapid scene and object recognition from brief displays, little is known about recognition of event categories and event roles from minimal visual information. In three experiments, we displayed naturalistic photographs of a wide range of two-participant event scenes for 37 ms and 73 ms followed by a mask, and found that event categories (the event gist, e.g., ‘kicking’, ‘pushing’, etc.) and event roles (i.e., Agent and Patient) can be recognized rapidly, even with various actor pairs and backgrounds. Norming ratings from a subsequent experiment revealed that certain physical features (e.g., outstretched extremities) that correlate with Agent-hood could have contributed to rapid role recognition. In a final experiment, using identical twin actors, we then varied these features in two sets of stimuli, in which Patients had Agent-like features or not. Subjects recognized the roles of event participants less accurately when Patients possessed Agent-like features, with this difference being eliminated with two-second durations. Thus, given minimal visual input, typical Agent-like physical features are used in role recognition but, with sufficient input from multiple fixations, people categorically determine the relationship between event participants. PMID:22984951

AMOEBA clustering revisited. [cluster analysis, classification, and image display program

NASA Technical Reports Server (NTRS)

Bryant, Jack

1990-01-01

A description of the clustering, classification, and image display program AMOEBA is presented. Using a difficult high resolution aircraft-acquired MSS image, the steps the program takes in forming clusters are traced. A number of new features are described here for the first time. Usage of the program is discussed. The theoretical foundation (the underlying mathematical model) is briefly presented. The program can handle images of any size and dimensionality.

The functional neuroanatomy of verbal memory in Alzheimer's disease: [18F]-Fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) correlates of recency and recognition memory.

PubMed

Staffaroni, Adam M; Melrose, Rebecca J; Leskin, Lorraine P; Riskin-Jones, Hannah; Harwood, Dylan; Mandelkern, Mark; Sultzer, David L

2017-09-01

The objective of this study was to distinguish the functional neuroanatomy of verbal learning and recognition in Alzheimer's disease (AD) using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning task. In 81 Veterans diagnosed with dementia due to AD, we conducted a cluster-based correlation analysis to assess the relationships between recency and recognition memory scores from the CERAD Word Learning Task and cortical metabolic activity measured using [ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET). AD patients (Mini-Mental State Examination, MMSE mean = 20.2) performed significantly better on the recall of recency items during learning trials than of primacy and middle items. Recency memory was associated with cerebral metabolism in the left middle and inferior temporal gyri and left fusiform gyrus (p < .05 at the corrected cluster level). In contrast, recognition memory was correlated with metabolic activity in two clusters: (a) a large cluster that included the left hippocampus, parahippocampal gyrus, entorhinal cortex, anterior temporal lobe, and inferior and middle temporal gyri; (b) the bilateral orbitofrontal cortices (OFC). The present study further informs our understanding of the disparate functional neuroanatomy of recency memory and recognition memory in AD. We anticipated that the recency effect would be relatively preserved and associated with temporoparietal brain regions implicated in short-term verbal memory, while recognition memory would be associated with the medial temporal lobe and possibly the OFC. Consistent with our a priori hypotheses, list learning in our AD sample was characterized by a reduced primacy effect and a relatively spared recency effect; however, recency memory was associated with cerebral metabolism in inferior and lateral temporal regions associated with the semantic memory network, rather than regions associated with short-term verbal memory. The correlates of recognition memory included the medial temporal lobe and OFC, replicating prior studies.

Agent-based method for distributed clustering of textual information

DOEpatents

Potok, Thomas E [Oak Ridge, TN; Reed, Joel W [Knoxville, TN; Elmore, Mark T [Oak Ridge, TN; Treadwell, Jim N [Louisville, TN

2010-09-28

A computer method and system for storing, retrieving and displaying information has a multiplexing agent (20) that calculates a new document vector (25) for a new document (21) to be added to the system and transmits the new document vector (25) to master cluster agents (22) and cluster agents (23) for evaluation. These agents (22, 23) perform the evaluation and return values upstream to the multiplexing agent (20) based on the similarity of the document to documents stored under their control. The multiplexing agent (20) then sends the document (21) and the document vector (25) to the master cluster agent (22), which then forwards it to a cluster agent (23) or creates a new cluster agent (23) to manage the document (21). The system also searches for stored documents according to a search query having at least one term and identifying the documents found in the search, and displays the documents in a clustering display (80) of similarity so as to indicate similarity of the documents to each other.

Strongest Earthquake-Prone Areas in Kamchatka

NASA Astrophysics Data System (ADS)

Dzeboev, B. A.; Agayan, S. M.; Zharkikh, Yu. I.; Krasnoperov, R. I.; Barykina, Yu. V.

2018-03-01

The paper continues the series of our works on recognizing the areas prone to the strongest, strong, and significant earthquakes with the use of the Formalized Clustering And Zoning (FCAZ) intellectual clustering system. We recognized the zones prone to the probable emergence of epicenters of the strongest ( M ≥ 74/3) earthquakes on the Pacific Coast of Kamchatka. The FCAZ-zones are compared to the zones that were recognized in 1984 by the classical recognition method for Earthquake-Prone Areas (EPA) by transferring the criteria of high seismicity from the Andes mountain belt to the territory of Kamchatka. The FCAZ recognition was carried out with two-dimensional and three-dimensional objects of recognition.

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

PubMed

Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.

Social Approach and Emotion Recognition in Fragile X Syndrome

ERIC Educational Resources Information Center

Williams, Tracey A.; Porter, Melanie A.; Langdon, Robyn

2014-01-01

Evidence is emerging that individuals with Fragile X syndrome (FXS) display emotion recognition deficits, which may contribute to their significant social difficulties. The current study investigated the emotion recognition abilities, and social approachability judgments, of FXS individuals when processing emotional stimuli. Relative to…

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

PubMed

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-05-21

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

Repair Rate of Clustered Abasic DNA Lesions by Human Endonuclease: Molecular Bases of Sequence Specificity.

PubMed

Gattuso, Hugo; Durand, Elodie; Bignon, Emmanuelle; Morell, Christophe; Georgakilas, Alexandros G; Dumont, Elise; Chipot, Christophe; Dehez, François; Monari, Antonio

2016-10-06

In the present contribution, the interaction between damaged DNA and repair enzymes is examined by means of molecular dynamics simulations. More specifically, we consider clustered abasic DNA lesions processed by the primary human apurinic/apyrimidinic (AP) endonuclease, APE1. Our results show that, in stark contrast with the corresponding bacterial endonucleases, human APE1 imposes strong geometrical constraints on the DNA duplex. As a consequence, the level of recognition and, hence, the repair rate is higher. Important features that guide the DNA/protein interactions are the presence of an extended positively charged region and of a molecular tweezers that strongly constrains DNA. Our results are on very good agreement with the experimentally determined repair rate of clustered abasic lesions. The lack of repair for one particular arrangement of the two abasic sites is also explained considering the peculiar destabilizing interaction between the recognition region and the second lesion, resulting in a partial opening of the molecular tweezers and, thus, a less stable complex. This contribution cogently establishes the molecular bases for the recognition and repair of clustered DNA lesions by means of human endonucleases.

Recognizing Biological Motion and Emotions from Point-Light Displays in Autism Spectrum Disorders

PubMed Central

Nackaerts, Evelien; Wagemans, Johan; Helsen, Werner; Swinnen, Stephan P.; Wenderoth, Nicole; Alaerts, Kaat

2012-01-01

One of the main characteristics of Autism Spectrum Disorder (ASD) are problems with social interaction and communication. Here, we explored ASD-related alterations in ‘reading’ body language of other humans. Accuracy and reaction times were assessed from two observational tasks involving the recognition of ‘biological motion’ and ‘emotions’ from point-light displays (PLDs). Eye movements were recorded during the completion of the tests. Results indicated that typically developed-participants were more accurate than ASD-subjects in recognizing biological motion or emotions from PLDs. No accuracy differences were revealed on two control-tasks (involving the indication of color-changes in the moving point-lights). Group differences in reaction times existed on all tasks, but effect sizes were higher for the biological and emotion recognition tasks. Biological motion recognition abilities were related to a person’s ability to recognize emotions from PLDs. However, ASD-related atypicalities in emotion recognition could not entirely be attributed to more basic deficits in biological motion recognition, suggesting an additional ASD-specific deficit in recognizing the emotional dimension of the point light displays. Eye movements were assessed during the completion of tasks and results indicated that ASD-participants generally produced more saccades and shorter fixation-durations compared to the control-group. However, especially for emotion recognition, these altered eye movements were associated with reductions in task-performance. PMID:22970227

Recognizing biological motion and emotions from point-light displays in autism spectrum disorders.

PubMed

Nackaerts, Evelien; Wagemans, Johan; Helsen, Werner; Swinnen, Stephan P; Wenderoth, Nicole; Alaerts, Kaat

2012-01-01

One of the main characteristics of Autism Spectrum Disorder (ASD) are problems with social interaction and communication. Here, we explored ASD-related alterations in 'reading' body language of other humans. Accuracy and reaction times were assessed from two observational tasks involving the recognition of 'biological motion' and 'emotions' from point-light displays (PLDs). Eye movements were recorded during the completion of the tests. Results indicated that typically developed-participants were more accurate than ASD-subjects in recognizing biological motion or emotions from PLDs. No accuracy differences were revealed on two control-tasks (involving the indication of color-changes in the moving point-lights). Group differences in reaction times existed on all tasks, but effect sizes were higher for the biological and emotion recognition tasks. Biological motion recognition abilities were related to a person's ability to recognize emotions from PLDs. However, ASD-related atypicalities in emotion recognition could not entirely be attributed to more basic deficits in biological motion recognition, suggesting an additional ASD-specific deficit in recognizing the emotional dimension of the point light displays. Eye movements were assessed during the completion of tasks and results indicated that ASD-participants generally produced more saccades and shorter fixation-durations compared to the control-group. However, especially for emotion recognition, these altered eye movements were associated with reductions in task-performance.

Recognition Is Still a Top Motivator.

ERIC Educational Resources Information Center

Cherrington, David J.; Wixom, B. Jackson, Jr.

1983-01-01

Motivation theories can be generalized to a common principle of human behavior: people do what they are reinforced or rewarded for doing. The most successful motivational recognition programs share five key elements: a recognition symbol, an attractive means of display, a meaningful presentation, effective promotion, and periodic evaluation. (MLF)

Speaker Linking and Applications using Non-Parametric Hashing Methods

DTIC Science & Technology

2016-09-08

clustering method based on hashing—canopy- clustering . We apply this method to a large corpus of speaker recordings, demonstrate performance tradeoffs...and compare to other hash- ing methods. Index Terms: speaker recognition, clustering , hashing, locality sensitive hashing. 1. Introduction We assume...speaker in our corpus. Second, given a QBE method, how can we perform speaker clustering —each clustering should be a single speaker, and a cluster should

Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

Mapping a disordered portion of the Brz2001-binding site on a plant monooxygenase, DWARF4, using a quartz-crystal microbalance biosensor-based T7 phage display.

PubMed

Takakusagi, Yoichi; Manita, Daisuke; Kusayanagi, Tomoe; Izaguirre-Carbonell, Jesus; Takakusagi, Kaori; Kuramochi, Kouji; Iwabata, Kazuki; Kanai, Yoshihiro; Sakaguchi, Kengo; Sugawara, Fumio

2013-04-01

In small-molecule/protein interaction studies, technical difficulties such as low solubility of small molecules or low abundance of protein samples often restrict the progress of research. Here, we describe a quartz-crystal microbalance (QCM) biosensor-based T7 phage display in combination use with a receptor-ligand contacts (RELIC) bioinformatics server for application in a plant Brz2001/DWARF4 system. Brz2001 is a brassinosteroid biosynthesis inhibitor in the less-soluble triazole series of compounds that targets DWARF4, a cytochrome P450 (Cyp450) monooxygenase containing heme and iron. Using a Brz2001 derivative that has higher solubility in 70% EtOH and forms a self-assembled monolayer on gold electrode, we selected 34 Brz2001-recognizing peptides from a 15-mer T7 phage-displayed random peptide library using a total of four sets of one-cycle biopanning. The RELIC/MOTIF program revealed continuous and discontinuous short motifs conserved within the 34 Brz2001-selected 15-mer peptide sequences, indicating the increase of information content for Brz2001 recognition. Furthermore, an analysis of similarity between the 34 peptides and the amino-acid sequence of DWARF4 using the RELIC/MATCH program generated a similarity plot and a cluster diagram of the amino-acid sequence. Both of these data highlighted an internally located disordered portion of a catalytic site on DWARF4, indicating that this portion is essential for Brz2001 recognition. A similar trend was also noted by an analysis using another 26 Brz2001-selected peptides, and not observed using the 27 gold electrode-recognizing control peptides, demonstrating the reproducibility and specificity of this method. Thus, this affinity-based strategy enables high-throughput detection of the small-molecule-recognizing portion on the target protein, which overcomes technical difficulties such as sample solubility or preparation that occur when conventional methods are used.

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

PubMed

Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

2017-05-11

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

Application of unsupervised pattern recognition approaches for exploration of rare earth elements in Se-Chahun iron ore, central Iran

NASA Astrophysics Data System (ADS)

Sarparandeh, Mohammadali; Hezarkhani, Ardeshir

2017-12-01

The use of efficient methods for data processing has always been of interest to researchers in the field of earth sciences. Pattern recognition techniques are appropriate methods for high-dimensional data such as geochemical data. Evaluation of the geochemical distribution of rare earth elements (REEs) requires the use of such methods. In particular, the multivariate nature of REE data makes them a good target for numerical analysis. The main subject of this paper is application of unsupervised pattern recognition approaches in evaluating geochemical distribution of REEs in the Kiruna type magnetite-apatite deposit of Se-Chahun. For this purpose, 42 bulk lithology samples were collected from the Se-Chahun iron ore deposit. In this study, 14 rare earth elements were measured with inductively coupled plasma mass spectrometry (ICP-MS). Pattern recognition makes it possible to evaluate the relations between the samples based on all these 14 features, simultaneously. In addition to providing easy solutions, discovery of the hidden information and relations of data samples is the advantage of these methods. Therefore, four clustering methods (unsupervised pattern recognition) - including a modified basic sequential algorithmic scheme (MBSAS), hierarchical (agglomerative) clustering, k-means clustering and self-organizing map (SOM) - were applied and results were evaluated using the silhouette criterion. Samples were clustered in four types. Finally, the results of this study were validated with geological facts and analysis results from, for example, scanning electron microscopy (SEM), X-ray diffraction (XRD), ICP-MS and optical mineralogy. The results of the k-means clustering and SOM methods have the best matches with reality, with experimental studies of samples and with field surveys. Since only the rare earth elements are used in this division, a good agreement of the results with lithology is considerable. It is concluded that the combination of the proposed methods and geological studies leads to finding some hidden information, and this approach has the best results compared to using only one of them.

The Mucciardi-Gose Clustering Algorithm and Its Applications in Automatic Pattern Recognition.

DTIC Science & Technology

A procedure known as the Mucciardi- Gose clustering algorithm, CLUSTR, for determining the geometrical or statistical relationships among groups of N...discussion of clustering algorithms is given; the particular advantages of the Mucciardi- Gose procedure are described. The mathematical basis for, and the

EMOTION RECOGNITION OF VIRTUAL AGENTS FACIAL EXPRESSIONS: THE EFFECTS OF AGE AND EMOTION INTENSITY

PubMed Central

Beer, Jenay M.; Fisk, Arthur D.; Rogers, Wendy A.

2014-01-01

People make determinations about the social characteristics of an agent (e.g., robot or virtual agent) by interpreting social cues displayed by the agent, such as facial expressions. Although a considerable amount of research has been conducted investigating age-related differences in emotion recognition of human faces (e.g., Sullivan, & Ruffman, 2004), the effect of age on emotion identification of virtual agent facial expressions has been largely unexplored. Age-related differences in emotion recognition of facial expressions are an important factor to consider in the design of agents that may assist older adults in a recreational or healthcare setting. The purpose of the current research was to investigate whether age-related differences in facial emotion recognition can extend to emotion-expressive virtual agents. Younger and older adults performed a recognition task with a virtual agent expressing six basic emotions. Larger age-related differences were expected for virtual agents displaying negative emotions, such as anger, sadness, and fear. In fact, the results indicated that older adults showed a decrease in emotion recognition accuracy for a virtual agent's emotions of anger, fear, and happiness. PMID:25552896

An Evaluation of Imitation Recognition Abilities in Typically Developing Children and Young Children with Autism Spectrum Disorder.

PubMed

Berger, Natalie I; Ingersoll, Brooke

2015-08-01

Previous work has indicated that both typically developing children and children with Autism Spectrum Disorder (ASD) display a range of imitation recognition behaviors in response to a contingent adult imitator. However, it is unknown how the two groups perform comparatively on this construct. In this study, imitation recognition behaviors for children with ASD and typically developing children were observed during periods of contingent imitation imbedded in a naturalistic imitation task. Results from this study indicate that children with ASD are impaired in their ability to recognize being imitated relative to typically developing peers as demonstrated both by behaviors representing basic social attention and more mature imitation recognition. Display of imitation recognition behaviors was independent of length of contingent imitation period in typically developing children, but rate of engagement in imitation recognition behaviors was positively correlated with length of contingent imitation period in children with ASD. Exploratory findings also suggest a link between the ability to demonstrate recognition of being imitated and ASD symptom severity, language, and object imitation for young children with ASD. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

A latent profile analysis of Asian American men's and women's adherence to cultural values.

PubMed

Wong, Y Joel; Nguyen, Chi P; Wang, Shu-Yi; Chen, Weilin; Steinfeldt, Jesse A; Kim, Bryan S K

2012-07-01

The goal of this study was to identify diverse profiles of Asian American women's and men's adherence to values that are salient in Asian cultures (i.e., conformity to norms, family recognition through achievement, emotional self-control, collectivism, and humility). To this end, the authors conducted a latent profile analysis using the 5 subscales of the Asian American Values Scale-Multidimensional in a sample of 214 Asian Americans. The analysis uncovered a four-cluster solution. In general, Clusters 1 and 2 were characterized by relatively low and moderate levels of adherence to the 5 dimensions of cultural values, respectively. Cluster 3 was characterized by the highest level of adherence to the cultural value of family recognition through achievement, whereas Cluster 4 was typified by the highest levels of adherence to collectivism, emotional self-control, and humility. Clusters 3 and 4 were associated with higher levels of depressive symptoms than Cluster 1. Furthermore, Asian American women and Asian American men had lower odds of being in Cluster 4 and Cluster 3, respectively. These findings attest to the importance of identifying specific patterns of adherence to cultural values when examining the relationship between Asian Americans' cultural orientation and mental health status.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

PubMed Central

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-01-01

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. PMID:26007738

Multi-task learning with group information for human action recognition

NASA Astrophysics Data System (ADS)

Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

2018-04-01

Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.

X-ray versus infrared selection of distant galaxy clusters: A case study using the XMM-LSS and SpARCS cluster samples

NASA Astrophysics Data System (ADS)

Willis, J. P.; Ramos-Ceja, M. E.; Muzzin, A.; Pacaud, F.; Yee, H. K. C.; Wilson, G.

2018-04-01

We present a comparison of two samples of z > 0.8 galaxy clusters selected using different wavelength-dependent techniques and examine the physical differences between them. We consider 18 clusters from the X-ray selected XMM-LSS distant cluster survey and 92 clusters from the optical-MIR selected SpARCS cluster survey. Both samples are selected from the same approximately 9 square degree sky area and we examine them using common XMM-Newton, Spitzer-SWIRE and CFHT Legacy Survey data. Clusters from each sample are compared employing aperture measures of X-ray and MIR emission. We divide the SpARCS distant cluster sample into three sub-samples: a) X-ray bright, b) X-ray faint, MIR bright, and c) X-ray faint, MIR faint clusters. We determine that X-ray and MIR selected clusters display very similar surface brightness distributions of galaxy MIR light. In addition, the average location and amplitude of the galaxy red sequence as measured from stacked colour histograms is very similar in the X-ray and MIR-selected samples. The sub-sample of X-ray faint, MIR bright clusters displays a distribution of BCG-barycentre position offsets which extends to higher values than all other samples. This observation indicates that such clusters may exist in a more disturbed state compared to the majority of the distant cluster population sampled by XMM-LSS and SpARCS. This conclusion is supported by stacked X-ray images for the X-ray faint, MIR bright cluster sub-sample that display weak, centrally-concentrated X-ray emission, consistent with a population of growing clusters accreting from an extended envelope of material.

A Method for Determining the Timing of Displaying the Speaker's Face and Captions for a Real-Time Speech-to-Caption System

NASA Astrophysics Data System (ADS)

Kuroki, Hayato; Ino, Shuichi; Nakano, Satoko; Hori, Kotaro; Ifukube, Tohru

The authors of this paper have been studying a real-time speech-to-caption system using speech recognition technology with a “repeat-speaking” method. In this system, they used a “repeat-speaker” who listens to a lecturer's voice and then speaks back the lecturer's speech utterances into a speech recognition computer. The througoing system showed that the accuracy of the captions is about 97% in Japanese-Japanese conversion and the conversion time from voices to captions is about 4 seconds in English-English conversion in some international conferences. Of course it required a lot of costs to achieve these high performances. In human communications, speech understanding depends not only on verbal information but also on non-verbal information such as speaker's gestures, and face and mouth movements. So the authors found the idea to display information of captions and speaker's face movement images with a suitable way to achieve a higher comprehension after storing information once into a computer briefly. In this paper, we investigate the relationship of the display sequence and display timing between captions that have speech recognition errors and the speaker's face movement images. The results show that the sequence “to display the caption before the speaker's face image” improves the comprehension of the captions. The sequence “to display both simultaneously” shows an improvement only a few percent higher than the question sentence, and the sequence “to display the speaker's face image before the caption” shows almost no change. In addition, the sequence “to display the caption 1 second before the speaker's face shows the most significant improvement of all the conditions.

Change blindness and visual memory: visual representations get rich and act poor.

PubMed

Varakin, D Alexander; Levin, Daniel T

2006-02-01

Change blindness is often taken as evidence that visual representations are impoverished, while successful recognition of specific objects is taken as evidence that they are richly detailed. In the current experiments, participants performed cover tasks that required each object in a display to be attended. Change detection trials were unexpectedly introduced and surprise recognition tests were given for nonchanging displays. For both change detection and recognition, participants had to distinguish objects from the same basic-level category, making it likely that specific visual information had to be used for successful performance. Although recognition was above chance, incidental change detection usually remained at floor. These results help reconcile demonstrations of poor change detection with demonstrations of good memory because they suggest that the capability to store visual information in memory is not reflected by the visual system's tendency to utilize these representations for purposes of detecting unexpected changes.

A Parallel Neuromorphic Text Recognition System and Its Implementation on a Heterogeneous High-Performance Computing Cluster

DTIC Science & Technology

2013-01-01

M. Ahmadi, and M. Shridhar, “ Handwritten Numeral Recognition with Multiple Features and Multistage Classifiers,” Proc. IEEE Int’l Symp. Circuits...ARTICLE (Post Print) 3. DATES COVERED (From - To) SEP 2011 – SEP 2013 4. TITLE AND SUBTITLE A PARALLEL NEUROMORPHIC TEXT RECOGNITION SYSTEM AND ITS...research in computational intelligence has entered a new era. In this paper, we present an HPC-based context-aware intelligent text recognition

[Short-term memory characteristics of vibration intensity tactile perception on human wrist].

PubMed

Hao, Fei; Chen, Li-Juan; Lu, Wei; Song, Ai-Guo

2014-12-25

In this study, a recall experiment and a recognition experiment were designed to assess the human wrist's short-term memory characteristics of tactile perception on vibration intensity, by using a novel homemade vibrotactile display device based on the spatiotemporal combination vibration of multiple micro vibration motors as a test device. Based on the obtained experimental data, the short-term memory span, recognition accuracy and reaction time of vibration intensity were analyzed. From the experimental results, some important conclusions can be made: (1) The average short-term memory span of tactile perception on vibration intensity is 3 ± 1 items; (2) The greater difference between two adjacent discrete intensities of vibrotactile stimulation is defined, the better average short-term memory span human wrist gets; (3) There is an obvious difference of the average short-term memory span on vibration intensity between the male and female; (4) The mechanism of information extraction in short-term memory of vibrotactile display is to traverse the scanning process by comparison; (5) The recognition accuracy and reaction time performance of vibrotactile display compares unfavourably with that of visual and auditory. The results from this study are important for designing vibrotactile display coding scheme.

Use of Patterned CNT Arrays for Display Purposes

NASA Technical Reports Server (NTRS)

Delzeit, Lance D. (Inventor); Schipper, John F. (Inventor)

2009-01-01

Method and system for providing a dynamically reconfigurable display having nanometer-scale resolution, using a patterned array of multi-wall carbon nanotube (MWCNT) clusters. A diode, phosphor or other light source on each MWCNT cluster is independently activated, and different color light sources (e.g., red, green, blue, grey scale, infrared) can be mixed if desired. Resolution is estimated to be 40-100 nm, and reconfiguration time for each MWCNT cluster is no greater than one microsecond.

Effects of expected-value information and display format on recognition of aircraft subsystem abnormalities

NASA Technical Reports Server (NTRS)

Palmer, Michael T.; Abbott, Kathy H.

1994-01-01

This study identifies improved methods to present system parameter information for detecting abnormal conditions and to identify system status. Two workstation experiments were conducted. The first experiment determined if including expected-value-range information in traditional parameter display formats affected subject performance. The second experiment determined if using a nontraditional parameter display format, which presented relative deviation from expected value, was better than traditional formats with expected-value ranges included. The inclusion of expected-value-range information onto traditional parameter formats was found to have essentially no effect. However, subjective results indicated support for including this information. The nontraditional column deviation parameter display format resulted in significantly fewer errors compared with traditional formats with expected-value-ranges included. In addition, error rates for the column deviation parameter display format remained stable as the scenario complexity increased, whereas error rates for the traditional parameter display formats with expected-value ranges increased. Subjective results also indicated that the subjects preferred this new format and thought that their performance was better with it. The column deviation parameter display format is recommended for display applications that require rapid recognition of out-of-tolerance conditions, especially for a large number of parameters.

Clustering and classification of infrasonic events at Mount Etna using pattern recognition techniques

NASA Astrophysics Data System (ADS)

Cannata, A.; Montalto, P.; Aliotta, M.; Cassisi, C.; Pulvirenti, A.; Privitera, E.; Patanè, D.

2011-04-01

Active volcanoes generate sonic and infrasonic signals, whose investigation provides useful information for both monitoring purposes and the study of the dynamics of explosive phenomena. At Mt. Etna volcano (Italy), a pattern recognition system based on infrasonic waveform features has been developed. First, by a parametric power spectrum method, the features describing and characterizing the infrasound events were extracted: peak frequency and quality factor. Then, together with the peak-to-peak amplitude, these features constituted a 3-D ‘feature space’; by Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN) three clusters were recognized inside it. After the clustering process, by using a common location method (semblance method) and additional volcanological information concerning the intensity of the explosive activity, we were able to associate each cluster to a particular source vent and/or a kind of volcanic activity. Finally, for automatic event location, clusters were used to train a model based on Support Vector Machine, calculating optimal hyperplanes able to maximize the margins of separation among the clusters. After the training phase this system automatically allows recognizing the active vent with no location algorithm and by using only a single station.

Tie2 and Eph Receptor Tyrosine Kinase Activation and Signaling

PubMed Central

Barton, William A.; Dalton, Annamarie C.; Seegar, Tom C.M.; Himanen, Juha P.

2014-01-01

The Eph and Tie cell surface receptors mediate a variety of signaling events during development and in the adult organism. As other receptor tyrosine kinases, they are activated on binding of extracellular ligands and their catalytic activity is tightly regulated on multiple levels. The Eph and Tie receptors display some unique characteristics, including the requirement of ligand-induced receptor clustering for efficient signaling. Interestingly, both Ephs and Ties can mediate different, even opposite, biological effects depending on the specific ligand eliciting the response and on the cellular context. Here we discuss the structural features of these receptors, their interactions with various ligands, as well as functional implications for downstream signaling initiation. The Eph/ephrin structures are already well reviewed and we only provide a brief overview on the initial binding events. We go into more detail discussing the Tie-angiopoietin structures and recognition. PMID:24478383

A heptadecanuclear Mn(III)9Dy(III)8 cluster derived from triethanolamine with two edge sharing supertetrahedra as the core and displaying SMM behaviour.

PubMed

Langley, Stuart K; Moubarakia, Boujemaa; Murray, Keith S

2010-06-07

A heterometallic, heptadecanuclear cluster of formula [Mn(III)9Dy(III)8O8(OH)8(tea)2(teaH)2(teaH2)4(Ac)4(NO3)2(H2O)4](NO3)7·8H2O (1) is reported. The core of 1 displays two edge sharing Mn(III)5Dy(III)5 supertetrahedra and represents one of the largest Mn/4f cluster compound so far reported. Magnetic studies show that 1 displays probable SMM behaviour as observed via non-zero values in the χM''vs T plot.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

On the three-quarter view advantage of familiar object recognition.

PubMed

Nonose, Kohei; Niimi, Ryosuke; Yokosawa, Kazuhiko

2016-11-01

A three-quarter view, i.e., an oblique view, of familiar objects often leads to a higher subjective goodness rating when compared with other orientations. What is the source of the high goodness for oblique views? First, we confirmed that object recognition performance was also best for oblique views around 30° view, even when the foreshortening disadvantage of front- and side-views was minimized (Experiments 1 and 2). In Experiment 3, we measured subjective ratings of view goodness and two possible determinants of view goodness: familiarity of view, and subjective impression of three-dimensionality. Three-dimensionality was measured as the subjective saliency of visual depth information. The oblique views were rated best, most familiar, and as approximating greatest three-dimensionality on average; however, the cluster analyses showed that the "best" orientation systematically varied among objects. We found three clusters of objects: front-preferred objects, oblique-preferred objects, and side-preferred objects. Interestingly, recognition performance and the three-dimensionality rating were higher for oblique views irrespective of the clusters. It appears that recognition efficiency is not the major source of the three-quarter view advantage. There are multiple determinants and variability among objects. This study suggests that the classical idea that a canonical view has a unique advantage in object perception requires further discussion.

SEAN: SNP prediction and display program utilizing EST sequence clusters.

PubMed

Huntley, Derek; Baldo, Angela; Johri, Saurabh; Sergot, Marek

2006-02-15

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.

Facial emotion recognition, face scan paths, and face perception in children with neurofibromatosis type 1.

PubMed

Lewis, Amelia K; Porter, Melanie A; Williams, Tracey A; Bzishvili, Samantha; North, Kathryn N; Payne, Jonathan M

2017-05-01

This study aimed to investigate face scan paths and face perception abilities in children with Neurofibromatosis Type 1 (NF1) and how these might relate to emotion recognition abilities in this population. The authors investigated facial emotion recognition, face scan paths, and face perception in 29 children with NF1 compared to 29 chronological age-matched typically developing controls. Correlations between facial emotion recognition, face scan paths, and face perception in children with NF1 were examined. Children with NF1 displayed significantly poorer recognition of fearful expressions compared to controls, as well as a nonsignificant trend toward poorer recognition of anger. Although there was no significant difference between groups in time spent viewing individual core facial features (eyes, nose, mouth, and nonfeature regions), children with NF1 spent significantly less time than controls viewing the face as a whole. Children with NF1 also displayed significantly poorer face perception abilities than typically developing controls. Facial emotion recognition deficits were not significantly associated with aberrant face scan paths or face perception abilities in the NF1 group. These results suggest that impairments in the perception, identification, and interpretation of information from faces are important aspects of the social-cognitive phenotype of NF1. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An adolescent suicide cluster and the possible role of electronic communication technology.

PubMed

Robertson, Lindsay; Skegg, Keren; Poore, Marion; Williams, Sheila; Taylor, Barry

2012-01-01

Since the development of Centers for Disease Control's (CDC) guidelines for the management of suicide clusters, the use of electronic communication technologies has increased dramatically. To describe an adolescent suicide cluster that drew our attention to the possible role of online social networking and SMS text messaging as sources of contagion after a suicide and obstacles to recognition of a potential cluster. A public health approach involving a multidisciplinary community response was used to investigate a group of suicides of New Zealand adolescents thought to be a cluster. Difficulties in identifying and managing contagion posed by use of electronic communications were assessed. The probability of observing a time-space cluster such as this by chance alone was p = .009. The cases did not belong to a single school, rather several were linked by social networking sites, including sites created in memory of earlier suicide cases, as well as mobile telephones. These facilitated the rapid spread of information and rumor about the deaths throughout the community. They made the recognition and management of a possible cluster more difficult. Relevant community agencies should proactively develop a strategy to enable the identification and management of suicide contagion. Guidelines to assist communities in managing clusters should be updated to reflect the widespread use of communication technologies in modern society.

YSOVAR: MID-INFRARED VARIABILITY OF YOUNG STELLAR OBJECTS AND THEIR DISKS IN THE CLUSTER IRAS 20050+2720

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

Poppenhaeger, K.; Wolk, S. J.; Hora, J. L.

2015-10-15

We present a time-variability study of young stellar objects (YSOs) in the cluster IRAS 20050+2720, performed at 3.6 and 4.5 μm with the Spitzer Space Telescope; this study is part of the Young Stellar Object VARiability (YSOVAR) project. We have collected light curves for 181 cluster members over 60 days. We find a high variability fraction among embedded cluster members of ca. 70%, whereas young stars without a detectable disk display variability less often (in ca. 50% of the cases) and with lower amplitudes. We detect periodic variability for 33 sources with periods primarily in the range of 2–6 days.more » Practically all embedded periodic sources display additional variability on top of their periodicity. Furthermore, we analyze the slopes of the tracks that our sources span in the color–magnitude diagram (CMD). We find that sources with long variability time scales tend to display CMD slopes that are at least partially influenced by accretion processes, while sources with short variability timescales tend to display extinction-dominated slopes. We find a tentative trend of X-ray detected cluster members to vary on longer timescales than the X-ray undetected members.« less

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

PubMed Central

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

2012-01-01

Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario. PMID:26007727

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

PubMed

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

2015-05-21

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

Exploring the sequence-structure protein landscape in the glycosyltransferase family

PubMed Central

Zhang, Ziding; Kochhar, Sunil; Grigorov, Martin

2003-01-01

To understand the molecular basis of glycosyltransferases’ (GTFs) catalytic mechanism, extensive structural information is required. Here, fold recognition methods were employed to assign 3D protein shapes (folds) to the currently known GTF sequences, available in public databases such as GenBank and Swissprot. First, GTF sequences were retrieved and classified into clusters, based on sequence similarity only. Intracluster sequence similarity was chosen sufficiently high to ensure that the same fold is found within a given cluster. Then, a representative sequence from each cluster was selected to compose a subset of GTF sequences. The members of this reduced set were processed by three different fold recognition methods: 3D-PSSM, FUGUE, and GeneFold. Finally, the results from different fold recognition methods were analyzed and compared to sequence-similarity search methods (i.e., BLAST and PSI-BLAST). It was established that the folds of about 70% of all currently known GTF sequences can be confidently assigned by fold recognition methods, a value which is higher than the fold identification rate based on sequence comparison alone (48% for BLAST and 64% for PSI-BLAST). The identified folds were submitted to 3D clustering, and we found that most of the GTF sequences adopt the typical GTF A or GTF B folds. Our results indicate a lack of evidence that new GTF folds (i.e., folds other than GTF A and B) exist. Based on cases where fold identification was not possible, we suggest several sequences as the most promising targets for a structural genomics initiative focused on the GTF protein family. PMID:14500887

X-ray versus infrared selection of distant galaxy clusters: a case study using the XMM-LSS and SpARCS cluster samples

NASA Astrophysics Data System (ADS)

Willis, J. P.; Ramos-Ceja, M. E.; Muzzin, A.; Pacaud, F.; Yee, H. K. C.; Wilson, G.

2018-07-01

We present a comparison of two samples of z> 0.8 galaxy clusters selected using different wavelength-dependent techniques and examine the physical differences between them. We consider 18 clusters from the X-ray-selected XMM Large Scale Structure (LSS) distant cluster survey and 92 clusters from the optical-mid-infrared (MIR)-selected Spitzer Adaptation of the Red Sequence Cluster survey (SpARCS) cluster survey. Both samples are selected from the same approximately 9 sq deg sky area and we examine them using common XMM-Newton, Spitizer Wide-Area Infrared Extra-galactic (SWIRE) survey, and Canada-France-Hawaii Telescope Legacy Survey data. Clusters from each sample are compared employing aperture measures of X-ray and MIR emission. We divide the SpARCS distant cluster sample into three sub-samples: (i) X-ray bright, (ii) X-ray faint, MIR bright, and (iii) X-ray faint, MIR faint clusters. We determine that X-ray- and MIR-selected clusters display very similar surface brightness distributions of galaxy MIR light. In addition, the average location and amplitude of the galaxy red sequence as measured from stacked colour histograms is very similar in the X-ray- and MIR-selected samples. The sub-sample of X-ray faint, MIR bright clusters displays a distribution of brightest cluster galaxy-barycentre position offsets which extends to higher values than all other samples. This observation indicates that such clusters may exist in a more disturbed state compared to the majority of the distant cluster population sampled by XMM-LSS and SpARCS. This conclusion is supported by stacked X-ray images for the X-ray faint, MIR bright cluster sub-sample that display weak, centrally concentrated X-ray emission, consistent with a population of growing clusters accreting from an extended envelope of material.

Usage of stereoscopic visualization in the learning contents of rotational motion.

PubMed

Matsuura, Shu

2013-01-01

Rotational motion plays an essential role in physics even at an introductory level. In addition, the stereoscopic display of three-dimensional graphics includes is advantageous for the presentation of rotational motions, particularly for depth recognition. However, the immersive visualization of rotational motion has been known to lead to dizziness and even nausea for some viewers. Therefore, the purpose of this study is to examine the onset of nausea and visual fatigue when learning rotational motion through the use of a stereoscopic display. The findings show that an instruction method with intermittent exposure of the stereoscopic display and a simplification of its visual components reduced the onset of nausea and visual fatigue for the viewers, which maintained the overall effect of instantaneous spatial recognition.

Versatile protein recognition by the encoded display of multiple chemical elements on a constant macrocyclic scaffold

NASA Astrophysics Data System (ADS)

Li, Yizhou; De Luca, Roberto; Cazzamalli, Samuele; Pretto, Francesca; Bajic, Davor; Scheuermann, Jörg; Neri, Dario

2018-03-01

In nature, specific antibodies can be generated as a result of an adaptive selection and expansion of lymphocytes with suitable protein binding properties. We attempted to mimic antibody-antigen recognition by displaying multiple chemical diversity elements on a defined macrocyclic scaffold. Encoding of the displayed combinations was achieved using distinctive DNA tags, resulting in a library size of 35,393,112. Specific binders could be isolated against a variety of proteins, including carbonic anhydrase IX, horseradish peroxidase, tankyrase 1, human serum albumin, alpha-1 acid glycoprotein, calmodulin, prostate-specific antigen and tumour necrosis factor. Similar to antibodies, the encoded display of multiple chemical elements on a constant scaffold enabled practical applications, such as fluorescence microscopy procedures or the selective in vivo delivery of payloads to tumours. Furthermore, the versatile structure of the scaffold facilitated the generation of protein-specific chemical probes, as illustrated by photo-crosslinking.

A human performance evaluation of graphic symbol-design features.

PubMed

Samet, M G; Geiselman, R E; Landee, B M

1982-06-01

16 subjects learned each of two tactical display symbol sets (conventional symbols and iconic symbols) in turn and were then shown a series of graphic displays containing various symbol configurations. For each display, the subject was asked questions corresponding to different behavioral processes relating to symbol use (identification, search, comparison, pattern recognition). The results indicated that: (a) conventional symbols yielded faster pattern-recognition performance than iconic symbols, and iconic symbols did not yield faster identification than conventional symbols, and (b) the portrayal of additional feature information (through the use of perimeter density or vector projection coding) slowed processing of the core symbol information in four tasks, but certain symbol-design features created less perceptual interference and had greater correspondence with the portrayal of specific tactical concepts than others. The results were discussed in terms of the complexities involved in the selection of symbol design features for use in graphic tactical displays.

Real-Time Gaze Tracking for Public Displays

NASA Astrophysics Data System (ADS)

Sippl, Andreas; Holzmann, Clemens; Zachhuber, Doris; Ferscha, Alois

In this paper, we explore the real-time tracking of human gazes in front of large public displays. The aim of our work is to estimate at which area of a display one ore more people are looking at a time, independently from the distance and angle to the display as well as the height of the tracked people. Gaze tracking is relevant for a variety of purposes, including the automatic recognition of the user's focus of attention, or the control of interactive applications with gaze gestures. The scope of the present paper is on the former, and we show how gaze tracking can be used for implicit interaction in the pervasive advertising domain. We have developed a prototype for this purpose, which (i) uses an overhead mounted camera to distinguish four gaze areas on a large display, (ii) works for a wide range of positions in front of the display, and (iii) provides an estimation of the currently gazed quarters in real time. A detailed description of the prototype as well as the results of a user study with 12 participants, which show the recognition accuracy for different positions in front of the display, are presented.

InCHlib - interactive cluster heatmap for web applications.

PubMed

Skuta, Ctibor; Bartůněk, Petr; Svozil, Daniel

2014-12-01

Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchical cluster structure of a data matrix, a visualization tool called 'cluster heatmap' is commonly employed. In the cluster heatmap, the data matrix is displayed as a heatmap, a 2-dimensional array in which the colour of each element corresponds to its value. The rows/columns of the matrix are ordered such that similar rows/columns are near each other. The ordering is given by the dendrogram which is displayed on the side of the heatmap. We developed InCHlib (Interactive Cluster Heatmap Library), a highly interactive and lightweight JavaScript library for cluster heatmap visualization and exploration. InCHlib enables the user to select individual or clustered heatmap rows, to zoom in and out of clusters or to flexibly modify heatmap appearance. The cluster heatmap can be augmented with additional metadata displayed in a different colour scale. In addition, to further enhance the visualization, the cluster heatmap can be interconnected with external data sources or analysis tools. Data clustering and the preparation of the input file for InCHlib is facilitated by the Python utility script inchlib_clust . The cluster heatmap is one of the most popular visualizations of large chemical and biomedical data sets originating, e.g., in high-throughput screening, genomics or transcriptomics experiments. The presented JavaScript library InCHlib is a client-side solution for cluster heatmap exploration. InCHlib can be easily deployed into any modern web application and configured to cooperate with external tools and data sources. Though InCHlib is primarily intended for the analysis of chemical or biological data, it is a versatile tool which application domain is not limited to the life sciences only.

Spatial Scale in Image Detection and Recognition.

DTIC Science & Technology

1986-02-01

detail and are important in later visual processing when attention has been focused on a particular aspect of the image. Two experiments investigated the...observers also selected the filter condition to be display on each trial prior to the detection or recognition response.

Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

USDA-ARS?s Scientific Manuscript database

The combination of gas chromatography and pattern recognition (GC/PR) analysis is a powerful tool for investigating complicated biological problems. Clustering, mapping, discriminant development, etc. are necessary to analyze realistically large chromatographic data sets and to seek meaningful relat...

High-Level Event Recognition in Unconstrained Videos

DTIC Science & Technology

2013-01-01

frames per- forms well for urban soundscapes but not for polyphonic music. In place of GMM, Lu et al. [78] adopted spectral clustering to generate...Aucouturier JJ, Defreville B, Pachet F (2007) The bag-of-frames approach to audio pattern recognition: a sufficientmodel for urban soundscapes but not

2007 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2007 National Award for Smart Growth Achievement Booklet displays the winners of the 2007 Smart Growth Report displays the winners of the 2007 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

Possibilistic clustering for shape recognition

NASA Technical Reports Server (NTRS)

Keller, James M.; Krishnapuram, Raghu

1993-01-01

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

Possibilistic clustering for shape recognition

NASA Technical Reports Server (NTRS)

Keller, James M.; Krishnapuram, Raghu

1992-01-01

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, we cast the clustering problem into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We constructed an appropriate objective function whose minimum will characterize a good possibilistic partition of the data, and we derived the membership and prototype update equations from necessary conditions for minimization of our criterion function. In this paper, we show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

PubMed

Alexander, Nathan; Woetzel, Nils; Meiler, Jens

2011-02-01

Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan.

PubMed

Park, Rachel; O'Brien, Thomas F; Huang, Susan S; Baker, Meghan A; Yokoe, Deborah S; Kulldorff, Martin; Barrett, Craig; Swift, Jamie; Stelling, John

2016-11-01

While antimicrobial resistance threatens the prevention, treatment, and control of infectious diseases, systematic analysis of routine microbiology laboratory test results worldwide can alert new threats and promote timely response. This study explores statistical algorithms for recognizing geographic clustering of multi-resistant microbes within a healthcare network and monitoring the dissemination of new strains over time. Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. We explored geographic clustering of multi-resistance phenotypes within the network and changes in clustering over time. Geographic clustering identified from both latitude/longitude and non-parametric facility groupings geographic models were similar, while the latter was offers greater flexibility and generalizability. Iterative application of the clustering algorithms suggested the possible recognition of the initial appearance of invasive E. coli ST131 in the clinical database of a single hospital and subsequent dissemination to others. Systematic analysis of routine antimicrobial resistance susceptibility test results supports the recognition of geographic clustering of microbial phenotypic subpopulations with WHONET and SaTScan, and iterative application of these algorithms can detect the initial appearance in and dissemination across a region prompting early investigation, response, and containment measures.

Broad phonetic class definition driven by phone confusions

NASA Astrophysics Data System (ADS)

Lopes, Carla; Perdigão, Fernando

2012-12-01

Intermediate representations between the speech signal and phones may be used to improve discrimination among phones that are often confused. These representations are usually found according to broad phonetic classes, which are defined by a phonetician. This article proposes an alternative data-driven method to generate these classes. Phone confusion information from the analysis of the output of a phone recognition system is used to find clusters at high risk of mutual confusion. A metric is defined to compute the distance between phones. The results, using TIMIT data, show that the proposed confusion-driven phone clustering method is an attractive alternative to the approaches based on human knowledge. A hierarchical classification structure to improve phone recognition is also proposed using a discriminative weight training method. Experiments show improvements in phone recognition on the TIMIT database compared to a baseline system.

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

PubMed

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.

The face of fear and anger: Facial width-to-height ratio biases recognition of angry and fearful expressions.

PubMed

Deska, Jason C; Lloyd, E Paige; Hugenberg, Kurt

2018-04-01

The ability to rapidly and accurately decode facial expressions is adaptive for human sociality. Although judgments of emotion are primarily determined by musculature, static face structure can also impact emotion judgments. The current work investigates how facial width-to-height ratio (fWHR), a stable feature of all faces, influences perceivers' judgments of expressive displays of anger and fear (Studies 1a, 1b, & 2), and anger and happiness (Study 3). Across 4 studies, we provide evidence consistent with the hypothesis that perceivers more readily see anger on faces with high fWHR compared with those with low fWHR, which instead facilitates the recognition of fear and happiness. This bias emerges when participants are led to believe that targets displaying otherwise neutral faces are attempting to mask an emotion (Studies 1a & 1b), and is evident when faces display an emotion (Studies 2 & 3). Together, these studies suggest that target facial width-to-height ratio biases ascriptions of emotion with consequences for emotion recognition speed and accuracy. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Emotional Processing, Recognition, Empathy and Evoked Facial Expression in Eating Disorders: An Experimental Study to Map Deficits in Social Cognition

PubMed Central

Cardi, Valentina; Corfield, Freya; Leppanen, Jenni; Rhind, Charlotte; Deriziotis, Stephanie; Hadjimichalis, Alexandra; Hibbs, Rebecca; Micali, Nadia; Treasure, Janet

2015-01-01

Background Difficulties in social cognition have been identified in eating disorders (EDs), but the exact profile of these abnormalities is unclear. The aim of this study is to examine distinct processes of social-cognition in this patient group, including attentional processing and recognition, empathic reaction and evoked facial expression in response to discrete vignettes of others displaying positive (i.e. happiness) or negative (i.e. sadness and anger) emotions. Method One hundred and thirty-eight female participants were included in the study: 73 healthy controls (HCs) and 65 individuals with an ED (49 with Anorexia Nervosa and 16 with Bulimia Nervosa). Self-report and behavioural measures were used. Results Participants with EDs did not display specific abnormalities in emotional processing, recognition and empathic response to others’ basic discrete emotions. However, they had poorer facial expressivity and a tendency to turn away from emotional displays. Conclusion Treatments focusing on the development of non-verbal emotional communication skills might be of benefit for patients with EDs. PMID:26252220

Medical Named Entity Recognition for Indonesian Language Using Word Representations

NASA Astrophysics Data System (ADS)

Rahman, Arief

2018-03-01

Nowadays, Named Entity Recognition (NER) system is used in medical texts to obtain important medical information, like diseases, symptoms, and drugs. While most NER systems are applied to formal medical texts, informal ones like those from social media (also called semi-formal texts) are starting to get recognition as a gold mine for medical information. We propose a theoretical Named Entity Recognition (NER) model for semi-formal medical texts in our medical knowledge management system by comparing two kinds of word representations: cluster-based word representation and distributed representation.

DICON: interactive visual analysis of multidimensional clusters.

PubMed

Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

2011-12-01

Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis. © 2011 IEEE

Advanced electronics for the CTF MEG system.

PubMed

McCubbin, J; Vrba, J; Spear, P; McKenzie, D; Willis, R; Loewen, R; Robinson, S E; Fife, A A

2004-11-30

Development of the CTF MEG system has been advanced with the introduction of a computer processing cluster between the data acquisition electronics and the host computer. The advent of fast processors, memory, and network interfaces has made this innovation feasible for large data streams at high sampling rates. We have implemented tasks including anti-alias filter, sample rate decimation, higher gradient balancing, crosstalk correction, and optional filters with a cluster consisting of 4 dual Intel Xeon processors operating on up to 275 channel MEG systems at 12 kHz sample rate. The architecture is expandable with additional processors to implement advanced processing tasks which may include e.g., continuous head localization/motion correction, optional display filters, coherence calculations, or real time synthetic channels (via beamformer). We also describe an electronics configuration upgrade to provide operator console access to the peripheral interface features such as analog signal and trigger I/O. This allows remote location of the acoustically noisy electronics cabinet and fitting of the cabinet with doors for improved EMI shielding. Finally, we present the latest performance results available for the CTF 275 channel MEG system including an unshielded SEF (median nerve electrical stimulation) measurement enhanced by application of an adaptive beamformer technique (SAM) which allows recognition of the nominal 20-ms response in the unaveraged signal.

Impairment in the recognition of emotion across different media following traumatic brain injury.

PubMed

Williams, Claire; Wood, Rodger Ll

2010-02-01

The current study examined emotion recognition following traumatic brain injury (TBI) and examined whether performance differed according to the affective valence and type of media presentation of the stimuli. A total of 64 patients with TBI and matched controls completed the Emotion Evaluation Test (EET) and Ekman 60 Faces Test (E-60-FT). Patients with TBI also completed measures of information processing and verbal ability. Results revealed that the TBI group were significantly impaired compared to controls when recognizing emotion on the EET and E-60-FT. A significant main effect of valence was found in both groups, with poor recognition of negative emotions. However, the difference between the recognition of positive and negative emotions was larger in the TBI group. The TBI group were also more accurate recognizing emotion displayed in audiovisual media (EET) than that displayed in still media (E-60-FT). No significant relationship was obtained between emotion recognition tasks and information-processing speed. A significant positive relationship was found between the E-60-FT and one measure of verbal ability. These findings support models of emotion that specify separate neurological pathways for certain emotions and different media and confirm that patients with TBI are vulnerable to experiencing emotion recognition difficulties.

A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades

PubMed Central

Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean

2017-01-01

The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency−frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency−MARSE, and average frequency−peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes. PMID:29104245

A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades.

PubMed

Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean

2017-11-01

The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency-frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency-MARSE, and average frequency-peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes.

Network analysis of named entity co-occurrences in written texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

Father-infant interaction, paternal ideas about early child care, and their consequences for the development of children's self-recognition.

PubMed

Borke, Jörn; Lamm, Bettina; Eickhorst, Andreas; Keller, Heidi

2007-12-01

In this longitudinal study, the authors addressed intracultural variation on fathers' interactions with their 3-month-old infants, their ideas about parental care, and the timing of their children's self-recognition at the age of 18-20 months. Participants were 24 middle-class German fathers and their firstborn children. Two behavioral clusters emerged: a more proximal parenting style with extensive body contact and a more distal parenting style with extensive object stimulation. Fathers in the distal cluster had significantly more education than did fathers in the proximal cluster. Children who had experienced more distal parenting were more likely to recognize themselves in a mirror than were children with more proximal parenting. The authors discuss the results with respect to fathers' influence on child development and patterns of intracultural variation.

Simulation Test of a Head-Worn Display with Ambient Vision Display for Unusual Attitude Recovery

NASA Technical Reports Server (NTRS)

Arthur, Jarvis (Trey) J., III; Nicholas, Stephanie N.; Shelton, Kevin J.; Ballard, Kathryn; Prinzel, Lawrence J., III; Ellis, Kyle E.; Bailey, Randall E.; Williams, Steven P.

2017-01-01

Head-Worn Displays (HWDs) are envisioned as a possible equivalent to a Head-Up Display (HUD) in commercial and general aviation. A simulation experiment was conducted to evaluate whether the HWD can provide an equivalent or better level of performance to a HUD in terms of unusual attitude recognition and recovery. A prototype HWD was tested with ambient vision capability which were varied (on/off) as an independent variable in the experiment testing for attitude awareness. The simulation experiment was conducted in two parts: 1) short unusual attitude recovery scenarios where the aircraft is placed in an unusual attitude and a single-pilot crew recovered the aircraft; and, 2) a two-pilot crew operating in a realistic flight environment with "off-nominal" events to induce unusual attitudes. The data showed few differences in unusual attitude recognition and recovery performance between the tested head-down, head-up, and head-worn display concepts. The presence and absence of ambient vision stimulation was inconclusive. The ergonomic influences of the head-worn display, necessary to implement the ambient vision experimentation, may have influenced the pilot ratings and acceptance of the concepts.

Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23.

PubMed

Barkan, David T; Cheng, Xiao-Li; Celino, Herodion; Tran, Tran T; Bhandari, Ashok; Craik, Charles S; Sali, Andrej; Smythe, Mark L

2016-11-23

Disulfide-rich peptides (DRPs) are found throughout nature. They are suitable scaffolds for drug development due to their small cores, whose disulfide bonds impart extraordinary chemical and biological stability. A challenge in developing a DRP therapeutic is to engineer binding to a specific target. This challenge can be overcome by (i) sampling the large sequence space of a given scaffold through a phage display library and by (ii) panning multiple libraries encoding structurally distinct scaffolds. Here, we implement a protocol for defining these diverse scaffolds, based on clustering structurally defined DRPs according to their conformational similarity. We developed and applied a hierarchical clustering protocol based on DRP structural similarity, followed by two post-processing steps, to classify 806 unique DRP structures into 81 clusters. The 20 most populated clusters comprised 85% of all DRPs. Representative scaffolds were selected from each of these clusters; the representatives were structurally distinct from one another, but similar to other DRPs in their respective clusters. To demonstrate the utility of the clusters, phage libraries were constructed for three of the representative scaffolds and panned against interleukin-23. One library produced a peptide that bound to this target with an IC 50 of 3.3 μM. Most DRP clusters contained members that were diverse in sequence, host organism, and interacting proteins, indicating that cluster members were functionally diverse despite having similar structure. Only 20 peptide scaffolds accounted for most of the natural DRP structural diversity, providing suitable starting points for seeding phage display experiments. Through selection of the scaffold surface to vary in phage display, libraries can be designed that present sequence diversity in architecturally distinct, biologically relevant combinations of secondary structures. We supported this hypothesis with a proof-of-concept experiment in which three phage libraries were constructed and panned against the IL-23 target, resulting in a single-digit μM hit and suggesting that a collection of libraries based on the full set of 20 scaffolds increases the potential to identify efficiently peptide binders to a protein target in a drug discovery program.

Anomalous subjective experience and psychosis risk in young depressed patients.

PubMed

Szily, Erika; Kéri, Szabolcs

2009-01-01

Help-seeking young people often display depressive symptoms. In some patients, these symptoms may co-exist with clinically high-risk mental states for psychosis. The aim of this study was to determine differences in subjective experience and social perception in young depressed patients with and without psychosis risk. Participants were 68 young persons with major depressive disorder. Twenty-six patients also met the criteria of attenuated or brief limited intermittent psychotic symptoms according to the Comprehensive Assessment of At Risk Mental States (CAARMS) criteria. Subjective experiences were assessed with the Bonn Scale for the Assessment of Basic Symptoms (BSABS). Recognition of complex social emotions and mental states was assessed using the 'Reading the Mind in the Eyes' test. Perplexity, self-disorder, and diminished affectivity significantly predicted psychosis risk. Depressed patients without psychosis risk displayed impaired recognition performance for negative social emotions, whereas patients with psychosis risk were also impaired in the recognition of cognitive expressions. In the high-risk group, self-disorder was associated with impaired recognition of facial expressions. These results suggest that anomalous subjective experience and impaired recognition of complex emotions may differentiate between young depressed patients with and without psychosis risk. 2009 S. Karger AG, Basel.

Good initialization model with constrained body structure for scene text recognition

NASA Astrophysics Data System (ADS)

Zhu, Anna; Wang, Guoyou; Dong, Yangbo

2016-09-01

Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

Data-driven cluster reinforcement and visualization in sparsely-matched self-organizing maps.

PubMed

Manukyan, Narine; Eppstein, Margaret J; Rizzo, Donna M

2012-05-01

A self-organizing map (SOM) is a self-organized projection of high-dimensional data onto a typically 2-dimensional (2-D) feature map, wherein vector similarity is implicitly translated into topological closeness in the 2-D projection. However, when there are more neurons than input patterns, it can be challenging to interpret the results, due to diffuse cluster boundaries and limitations of current methods for displaying interneuron distances. In this brief, we introduce a new cluster reinforcement (CR) phase for sparsely-matched SOMs. The CR phase amplifies within-cluster similarity in an unsupervised, data-driven manner. Discontinuities in the resulting map correspond to between-cluster distances and are stored in a boundary (B) matrix. We describe a new hierarchical visualization of cluster boundaries displayed directly on feature maps, which requires no further clustering beyond what was implicitly accomplished during self-organization in SOM training. We use a synthetic benchmark problem and previously published microbial community profile data to demonstrate the benefits of the proposed methods.

A DDC Bibliography on Optical or Graphic Information Processing (Information Sciences Series). Volume I.

ERIC Educational Resources Information Center

Defense Documentation Center, Alexandria, VA.

This unclassified-unlimited bibliography contains 183 references, with abstracts, dealing specifically with optical or graphic information processing. Citations are grouped under three headings: display devices and theory, character recognition, and pattern recognition. Within each group, they are arranged in accession number (AD-number) sequence.…

Realizing the Full Potential of the Video Disc for Mapping Applications,

DTIC Science & Technology

1985-03-01

symbology, lettering and color usage are all factors that will be tested and evalu- ated for ease of recognition and visual communication when maps are...filmed and displayed on a standard television monitor and the images will then be evaluated for ease of recognition and visual communication . This

Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis.

PubMed

Cohen, Mitchell J; Grossman, Adam D; Morabito, Diane; Knudson, M Margaret; Butte, Atul J; Manley, Geoffrey T

2010-01-01

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Blind equalization and automatic modulation classification based on subspace for subcarrier MPSK optical communications

NASA Astrophysics Data System (ADS)

Chen, Dan; Guo, Lin-yuan; Wang, Chen-hao; Ke, Xi-zheng

2017-07-01

Equalization can compensate channel distortion caused by channel multipath effects, and effectively improve convergent of modulation constellation diagram in optical wireless system. In this paper, the subspace blind equalization algorithm is used to preprocess M-ary phase shift keying (MPSK) subcarrier modulation signal in receiver. Mountain clustering is adopted to get the clustering centers of MPSK modulation constellation diagram, and the modulation order is automatically identified through the k-nearest neighbor (KNN) classifier. The experiment has been done under four different weather conditions. Experimental results show that the convergent of constellation diagram is improved effectively after using the subspace blind equalization algorithm, which means that the accuracy of modulation recognition is increased. The correct recognition rate of 16PSK can be up to 85% in any kind of weather condition which is mentioned in paper. Meanwhile, the correct recognition rate is the highest in cloudy and the lowest in heavy rain condition.

Designing a robust activity recognition framework for health and exergaming using wearable sensors.

PubMed

Alshurafa, Nabil; Xu, Wenyao; Liu, Jason J; Huang, Ming-Chun; Mortazavi, Bobak; Roberts, Christian K; Sarrafzadeh, Majid

2014-09-01

Detecting human activity independent of intensity is essential in many applications, primarily in calculating metabolic equivalent rates and extracting human context awareness. Many classifiers that train on an activity at a subset of intensity levels fail to recognize the same activity at other intensity levels. This demonstrates weakness in the underlying classification method. Training a classifier for an activity at every intensity level is also not practical. In this paper, we tackle a novel intensity-independent activity recognition problem where the class labels exhibit large variability, the data are of high dimensionality, and clustering algorithms are necessary. We propose a new robust stochastic approximation framework for enhanced classification of such data. Experiments are reported using two clustering techniques, K-Means and Gaussian Mixture Models. The stochastic approximation algorithm consistently outperforms other well-known classification schemes which validate the use of our proposed clustered data representation. We verify the motivation of our framework in two applications that benefit from intensity-independent activity recognition. The first application shows how our framework can be used to enhance energy expenditure calculations. The second application is a novel exergaming environment aimed at using games to reward physical activity performed throughout the day, to encourage a healthy lifestyle.

Molecular self-recognition: a chiral [Mn(II)6] wheel via donor-acceptor π···π contacts and H-bonds.

PubMed

Barrios, L A; Salinas-Uber, J; Roubeau, O; Teat, S J; Aromí, G

2015-03-18

A multinucleating ligand capable of establishing different types of intermolecular interactions, when combined with acetate groups leads to the assembly of a chiral [Mn(II)3] cluster poised for a process of self-recognition through a combination of perfectly complementary weak forces.

Phonotactics Constraints and the Spoken Word Recognition of Chinese Words in Speech

ERIC Educational Resources Information Center

Yip, Michael C.

2016-01-01

Two word-spotting experiments were conducted to examine the question of whether native Cantonese listeners are constrained by phonotactics information in spoken word recognition of Chinese words in speech. Because no legal consonant clusters occurred within an individual Chinese word, this kind of categorical phonotactics information of Chinese…

Sub-word image clustering in Farsi printed books

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2015-02-01

Most OCR systems are designed for the recognition of a single page. In case of unfamiliar font faces, low quality papers and degraded prints, the performance of these products drops sharply. However, an OCR system can use redundancy of word occurrences in large documents to improve recognition results. In this paper, we propose a sub-word image clustering method for the applications dealing with large printed documents. We assume that the whole document is printed by a unique unknown font with low quality print. Our proposed method finds clusters of equivalent sub-word images with an incremental algorithm. Due to the low print quality, we propose an image matching algorithm for measuring the distance between two sub-word images, based on Hamming distance and the ratio of the area to the perimeter of the connected components. We built a ground-truth dataset of more than 111000 sub-word images to evaluate our method. All of these images were extracted from an old Farsi book. We cluster all of these sub-words, including isolated letters and even punctuation marks. Then all centers of created clusters are labeled manually. We show that all sub-words of the book can be recognized with more than 99.7% accuracy by assigning the label of each cluster center to all of its members.

Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan

PubMed Central

Park, Rachel; O'Brien, Thomas F.; Huang, Susan S.; Baker, Meghan A.; Yokoe, Deborah S.; Kulldorff, Martin; Barrett, Craig; Swift, Jamie; Stelling, John

2016-01-01

Objectives While antimicrobial resistance threatens the prevention, treatment, and control of infectious diseases, systematic analysis of routine microbiology laboratory test results worldwide can alert new threats and promote timely response. This study explores statistical algorithms for recognizing geographic clustering of multi-resistant microbes within a healthcare network and monitoring the dissemination of new strains over time. Methods Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. We explored geographic clustering of multi-resistance phenotypes within the network and changes in clustering over time. Results Geographic clustering identified from both latitude/longitude and non-parametric facility groupings geographic models were similar, while the latter was offers greater flexibility and generalizability. Iterative application of the clustering algorithms suggested the possible recognition of the initial appearance of invasive E. coli ST131 in the clinical database of a single hospital and subsequent dissemination to others. Conclusion Systematic analysis of routine antimicrobial resistance susceptibility test results supports the recognition of geographic clustering of microbial phenotypic subpopulations with WHONET and SaTScan, and iterative application of these algorithms can detect the initial appearance in and dissemination across a region prompting early investigation, response, and containment measures. PMID:27530311

DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI

NASA Astrophysics Data System (ADS)

He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun

2009-10-01

The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.

Finding Semirigid Domains in Biomolecules by Clustering Pair-Distance Variations

PubMed Central

Schreiner, Wolfgang

2014-01-01

Dynamic variations in the distances between pairs of atoms are used for clustering subdomains of biomolecules. We draw on a well-known target function for clustering and first show mathematically that the assignment of atoms to clusters has to be crisp, not fuzzy, as hitherto assumed. This reduces the computational load of clustering drastically, and we demonstrate results for several biomolecules relevant in immunoinformatics. Results are evaluated regarding the number of clusters, cluster size, cluster stability, and the evolution of clusters over time. Crisp clustering lends itself as an efficient tool to locate semirigid domains in the simulation of biomolecules. Such domains seem crucial for an optimum performance of subsequent statistical analyses, aiming at detecting minute motional patterns related to antigen recognition and signal transduction. PMID:24959586

Structural Analysis of Single Domain Antibodies Bound to a Second Neutralizing Hot Spot on Ricin Toxin's Enzymatic Subunit*

PubMed Central

Rudolph, Michael J.; Cassidy, Michael S.; Rong, Yinghui

2017-01-01

Ricin toxin is a heterodimer consisting of RTA, a ribosome-inactivating protein, and RTB, a lectin that facilitates receptor-mediated uptake into mammalian cells. In previous studies, we demonstrated that toxin-neutralizing antibodies target four spatially distinct hot spots on RTA, which we refer to as epitope clusters I–IV. In this report, we identified and characterized three single domain camelid antibodies (VHH) against cluster II. One of these VHHs, V5E1, ranks as one of the most potent ricin-neutralizing antibodies described to date. We solved the X-ray crystal structures of each of the three VHHs (E1, V1C7, and V5E1) in complex with RTA. V5E1 buries a total of 1,133 Å2 of surface area on RTA and makes primary contacts with α-helix A (residues 18–32), α-helix F (182–194), as well as the F-G loop. V5E1, by virtue of complementarity determining region 3 (CDR3), may also engage with RTB and potentially interfere with the high affinity galactose-recognition element that plays a critical role in toxin attachment to cell surfaces and intracellular trafficking. The two other VHHs, E1 and V1C7, bind epitopes adjacent to V5E1 but display only weak toxin neutralizing activity, thereby providing structural insights into specific residues within cluster II that may be critical contact points for toxin inactivation. PMID:27903650

Graded effects in hierarchical figure-ground organization: reply to Peterson (1999).

PubMed

Vecera, S P; O'Reilly, R C

2000-06-01

An important issue in vision research concerns the order of visual processing. S. P. Vecera and R. C. O'Reilly (1998) presented an interactive, hierarchical model that placed figure-ground segregation prior to object recognition. M. A. Peterson (1999) critiqued this model, arguing that because it used ambiguous stimulus displays, figure-ground processing did not precede object processing. In the current article, the authors respond to Peterson's (1999) interpretation of ambiguity in the model and her interpretation of what it means for figure-ground processing to come before object recognition. The authors argue that complete stimulus ambiguity is not critical to the model and that figure-ground precedes object recognition architecturally in the model. The arguments are supported with additional simulation results and an experiment, demonstrating that top-down inputs can influence figure-ground organization in displays that contain stimulus cues.

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

PubMed

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

2010-09-01

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

Gender Recognition from Point-Light Walkers

ERIC Educational Resources Information Center

Pollick, Frank E.; Kay, Jim W.; Heim, Katrin; Stringer, Rebecca

2005-01-01

Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal…

Augmented reality three-dimensional object visualization and recognition with axially distributed sensing.

PubMed

Markman, Adam; Shen, Xin; Hua, Hong; Javidi, Bahram

2016-01-15

An augmented reality (AR) smartglass display combines real-world scenes with digital information enabling the rapid growth of AR-based applications. We present an augmented reality-based approach for three-dimensional (3D) optical visualization and object recognition using axially distributed sensing (ADS). For object recognition, the 3D scene is reconstructed, and feature extraction is performed by calculating the histogram of oriented gradients (HOG) of a sliding window. A support vector machine (SVM) is then used for classification. Once an object has been identified, the 3D reconstructed scene with the detected object is optically displayed in the smartglasses allowing the user to see the object, remove partial occlusions of the object, and provide critical information about the object such as 3D coordinates, which are not possible with conventional AR devices. To the best of our knowledge, this is the first report on combining axially distributed sensing with 3D object visualization and recognition for applications to augmented reality. The proposed approach can have benefits for many applications, including medical, military, transportation, and manufacturing.

Interactive display/graphics systems for remote sensor data analysis.

NASA Technical Reports Server (NTRS)

Eppler, W. G.; Loe, D. L.; Wilson, E. L.; Whitley, S. L.; Sachen, R. J.

1971-01-01

Using a color-television display system and interactive graphics equipment on-line to an IBM 360/44 computer, investigators at the Manned Spacecraft Center have developed a variety of interactive displays which aid in analyzing remote sensor data. This paper describes how such interactive displays are used to: (1) analyze data from a multispectral scanner, (2) develop automatic pattern recognition systems based on multispectral scanner measurements, and (3) analyze data from nonimaging sensors such as the infrared radiometer and microwave scatterometer.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition.

PubMed

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition

PubMed Central

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation. PMID:28493921

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Single-Domain Antibodies: Rugged Recognition Element

DTIC Science & Technology

2007-01-01

and spiny dogfish shark (60 million representatives), which are displayed on filamentous phage M13 . We selected the llama- derived library for binding...subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE

Promote Your Vocational Office Education Program

ERIC Educational Resources Information Center

Boyd, Daniel R.

1973-01-01

Suggestions for promoting a VOE program within the school include these: bulletin boards and displays, school publications, assemblies, and VOE club activites. Community promotional activities include use of store windows for displays, use of mass media, recognition of local businessmen at the VOE banquet, and programs presented to service clubs.…

A cluster analysis method for identification of subpopulations of cells in flow cytometric list-mode arrays

NASA Technical Reports Server (NTRS)

Li, Z. K.

1985-01-01

A specialized program was developed for flow cytometric list-mode data using an heirarchical tree method for identifying and enumerating individual subpopulations, the method of principal components for a two-dimensional display of 6-parameter data array, and a standard sorting algorithm for characterizing subpopulations. The program was tested against a published data set subjected to cluster analysis and experimental data sets from controlled flow cytometry experiments using a Coulter Electronics EPICS V Cell Sorter. A version of the program in compiled BASIC is usable on a 16-bit microcomputer with the MS-DOS operating system. It is specialized for 6 parameters and up to 20,000 cells. Its two-dimensional display of Euclidean distances reveals clusters clearly, as does its 1-dimensional display. The identified subpopulations can, in suitable experiments, be related to functional subpopulations of cells.

Two-stage color palettization for error diffusion

NASA Astrophysics Data System (ADS)

Mitra, Niloy J.; Gupta, Maya R.

2002-06-01

Image-adaptive color palettization chooses a decreased number of colors to represent an image. Palettization is one way to decrease storage and memory requirements for low-end displays. Palettization is generally approached as a clustering problem, where one attempts to find the k palette colors that minimize the average distortion for all the colors in an image. This would be the optimal approach if the image was to be displayed with each pixel quantized to the closest palette color. However, to improve the image quality the palettization may be followed by error diffusion. In this work, we propose a two-stage palettization where the first stage finds some m << k clusters, and the second stage chooses palette points that cover the spread of each of the M clusters. After error diffusion, this method leads to better image quality at less computational cost and with faster display speed than full k-means palettization.

The Influence of the Phonological Neighborhood Clustering Coefficient on Spoken Word Recognition

ERIC Educational Resources Information Center

Chan, Kit Ying; Vitevitch, Michael S.

2009-01-01

Clustering coefficient--a measure derived from the new science of networks--refers to the proportion of phonological neighbors of a target word that are also neighbors of each other. Consider the words "bat", "hat", and "can", all of which are neighbors of the word "cat"; the words "bat" and…

Human engineer's guide to auditory displays. Volume 1. Elements of perception and memory affecting auditory displays

NASA Astrophysics Data System (ADS)

Mulligan, B. E.; Goodman, L. S.; McBride, D. K.; Mitchell, T. M.; Crosby, T. N.

1984-08-01

This work reviews the areas of auditory attention, recognition, memory and auditory perception of patterns, pitch, and loudness. The review was written from the perspective of human engineering and focuses primarily on auditory processing of information contained in acoustic signals. The impetus for this effort was to establish a data base to be utilized in the design and evaluation of acoustic displays.

Human Consequences of Agile Aircraft (Facteurs humains lies au pilotage des avions de combat tres manoeuvrants)

DTIC Science & Technology

2001-05-01

displays were discussed with the test pilots that we interviewed. The pilots had mixed opinions on tactile and auditory displays. Positive comments...were noted concerning three-dimensional auditory displays, although some stated that the pilot could easily ignore the aural tone. Others complained...recognition technology was not reliable enough and worried about problems with surrounding auditory signals from anti-G straining maneuvers, oxygen

Biomolecular Recognition of Semiconductors and Magnetic Materials to Assemble Nanoparticle Heterostructures

DTIC Science & Technology

2002-01-01

shown that engineered viruses can recognize specific semiconductor surfaces through the selection by combinatorial phage display method. These specific... phage display libraries. The screening method selected for binding affinity of a population of random peptides displayed as part of the pIII minor coat...shorter spacing than expected distance ( M13 phage length: 880 nm) corresponds to the length scale imposed by the phage which formed the tilted

Studies of recognition with multitemporal remote sensor data

NASA Technical Reports Server (NTRS)

Malila, W. A.; Hieber, R. H.; Cicone, R. C.

1975-01-01

Characteristics of multitemporal data and their use in recognition processing were investigated. Principal emphasis was on satellite data collected by the LANDSAT multispectral scanner and on temporal changes throughout a growing season. The effects of spatial misregistration on recognition performance with multitemporal data were examined. A capability to compute probabilities of detection and false alarm was developed and used with simulated distributions for misregistered pixels. Wheat detection was found to be degraded and false alarms increased by misregistration effects. Multitemporal signature characteristics and multitemporal recognition processing were studied to gain insights into problems associated with this approach and possible improvements. Recognition performance with one multitemporal data set displayed marked improvements over results from single-time data.

Automatic speech recognition in air-ground data link

NASA Technical Reports Server (NTRS)

Armstrong, Herbert B.

1989-01-01

In the present air traffic system, information presented to the transport aircraft cockpit crew may originate from a variety of sources and may be presented to the crew in visual or aural form, either through cockpit instrument displays or, most often, through voice communication. Voice radio communications are the most error prone method for air-ground data link. Voice messages can be misstated or misunderstood and radio frequency congestion can delay or obscure important messages. To prevent proliferation, a multiplexed data link display can be designed to present information from multiple data link sources on a shared cockpit display unit (CDU) or multi-function display (MFD) or some future combination of flight management and data link information. An aural data link which incorporates an automatic speech recognition (ASR) system for crew response offers several advantages over visual displays. The possibility of applying ASR to the air-ground data link was investigated. The first step was to review current efforts in ASR applications in the cockpit and in air traffic control and evaluated their possible data line application. Next, a series of preliminary research questions is to be developed for possible future collaboration.

Overlapping Podospora anserina Transcriptional Responses to Bacterial and Fungal Non Self Indicate a Multilayered Innate Immune Response

PubMed Central

Lamacchia, Marina; Dyrka, Witold; Breton, Annick; Saupe, Sven J.; Paoletti, Mathieu

2016-01-01

Recognition and response to non self is essential to development and survival of all organisms. It can occur between individuals of the same species or between different organisms. Fungi are established models for conspecific non self recognition in the form of vegetative incompatibility (VI), a genetically controlled process initiating a programmed cell death (PCD) leading to the rejection of a fusion cell between genetically different isolates of the same species. In Podospora anserina VI is controlled by members of the hnwd gene family encoding for proteins analogous to NOD Like Receptors (NLR) immune receptors in eukaryotes. It was hypothesized that the hnwd controlled VI reaction was derived from the fungal innate immune response. Here we analyze the P. anserina transcriptional responses to two bacterial species, Serratia fonticola to which P. anserina survives and S. marcescens to which P. anserina succumbs, and compare these to the transcriptional response induced under VI conditions. Transcriptional responses to both bacteria largely overlap, however the number of genes regulated and magnitude of regulation is more important when P. anserina survives. Transcriptional responses to bacteria also overlap with the VI reaction for both up or down regulated gene sets. Genes up regulated tend to be clustered in the genome, and display limited phylogenetic distribution. In all three responses we observed genes related to autophagy to be up-regulated. Autophagy contributes to the fungal survival in all three conditions. Genes encoding for secondary metabolites and histidine kinase signaling are also up regulated in all three conditions. Transcriptional responses also display differences. Genes involved in response to oxidative stress, or encoding small secreted proteins are essentially expressed in response to bacteria, while genes encoding NLR proteins are expressed during VI. Most functions encoded in response to bacteria favor survival of the fungus while most functions up regulated during VI would lead to cell death. These differences are discussed in the frame of a multilayered response to non self in fungi. PMID:27148175

Dynamics of fragment formation in neutron-rich matter

NASA Astrophysics Data System (ADS)

Alcain, P. N.; Dorso, C. O.

2018-01-01

Background: Neutron stars are astronomical systems with nucleons subjected to extreme conditions. Due to the longer range Coulomb repulsion between protons, the system has structural inhomogeneities. Several interactions tailored to reproduce nuclear matter plus a screened Coulomb term reproduce these inhomogeneities known as nuclear pasta. These structural inhomogeneities, located in the crusts of neutron stars, can also arise in expanding systems depending on the thermodynamic conditions (temperature, proton fraction, etc.) and the expansion velocity. Purpose: We aim to find the dynamics of the fragment formation for expanding systems simulated according to the little big bang model. This expansion resembles the evolution of merging neutron stars. Method: We study the dynamics of the nucleons with semiclassical molecular dynamics models. Starting with an equilibrium configuration, we expand the system homogeneously until we arrive at an asymptotic configuration (i.e., very low final densities). We study, with four different cluster recognition algorithms, the fragment distribution throughout this expansion and the dynamics of the cluster formation. Results: Studying the topology of the equilibrium states, before the expansion, we reproduced the known pasta phases plus a novel phase we called pregnocchi, consisting of proton aggregates embedded in a neutron sea. We have identified different fragmentation regimes, depending on the initial temperature and fragment velocity. In particular, for the already mentioned pregnocchi, a neutron cloud surrounds the clusters during the early stages of the expansion, resulting in systems that give rise to configurations compatible with the emergence of the r process. Conclusions: We showed that a proper identification of the cluster distribution is highly dependent on the cluster recognition algorithm chosen, and found that the early cluster recognition algorithm (ECRA) was the most stable one. This approach allowed us to identify the dynamics of the fragment formation. These calculations pave the way to a comparison between Earth experiments and neutron star studies.

Improving protein fold recognition by extracting fold-specific features from predicted residue-residue contacts.

PubMed

Zhu, Jianwei; Zhang, Haicang; Li, Shuai Cheng; Wang, Chao; Kong, Lupeng; Sun, Shiwei; Zheng, Wei-Mou; Bu, Dongbo

2017-12-01

Accurate recognition of protein fold types is a key step for template-based prediction of protein structures. The existing approaches to fold recognition mainly exploit the features derived from alignments of query protein against templates. These approaches have been shown to be successful for fold recognition at family level, but usually failed at superfamily/fold levels. To overcome this limitation, one of the key points is to explore more structurally informative features of proteins. Although residue-residue contacts carry abundant structural information, how to thoroughly exploit these information for fold recognition still remains a challenge. In this study, we present an approach (called DeepFR) to improve fold recognition at superfamily/fold levels. The basic idea of our approach is to extract fold-specific features from predicted residue-residue contacts of proteins using deep convolutional neural network (DCNN) technique. Based on these fold-specific features, we calculated similarity between query protein and templates, and then assigned query protein with fold type of the most similar template. DCNN has showed excellent performance in image feature extraction and image recognition; the rational underlying the application of DCNN for fold recognition is that contact likelihood maps are essentially analogy to images, as they both display compositional hierarchy. Experimental results on the LINDAHL dataset suggest that even using the extracted fold-specific features alone, our approach achieved success rate comparable to the state-of-the-art approaches. When further combining these features with traditional alignment-related features, the success rate of our approach increased to 92.3%, 82.5% and 78.8% at family, superfamily and fold levels, respectively, which is about 18% higher than the state-of-the-art approach at fold level, 6% higher at superfamily level and 1% higher at family level. An independent assessment on SCOP_TEST dataset showed consistent performance improvement, indicating robustness of our approach. Furthermore, bi-clustering results of the extracted features are compatible with fold hierarchy of proteins, implying that these features are fold-specific. Together, these results suggest that the features extracted from predicted contacts are orthogonal to alignment-related features, and the combination of them could greatly facilitate fold recognition at superfamily/fold levels and template-based prediction of protein structures. Source code of DeepFR is freely available through https://github.com/zhujianwei31415/deepfr, and a web server is available through http://protein.ict.ac.cn/deepfr. zheng@itp.ac.cn or dbu@ict.ac.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Health monitoring display system for a complex plant

DOEpatents

Ridolfo, Charles F [Bloomfield, CT; Harmon, Daryl L [Enfield, CT; Colin, Dreyfuss [Enfield, CT

2006-08-08

A single page enterprise wide level display provides a comprehensive readily understood representation of the overall health status of a complex plant. Color coded failure domains allow rapid intuitive recognition of component failure status. A three-tier hierarchy of displays provide details on the health status of the components and systems displayed on the enterprise wide level display in a manner that supports a logical drill down to the health status of sub-components on Tier 1 to expected faults of the sub-components on Tier 2 to specific information relative to expected sub-component failures on Tier 3.

The Development of Emotion Recognition in Individuals with Autism

ERIC Educational Resources Information Center

Rump, Keiran M.; Giovannelli, Joyce L.; Minshew, Nancy J.; Strauss, Mark S.

2009-01-01

Emotion recognition was investigated in typically developing individuals and individuals with autism. Experiment 1 tested children (5-7 years, n = 37) with brief video displays of facial expressions that varied in subtlety. Children with autism performed worse than the control children. In Experiment 2, 3 age groups (8-12 years, n = 49; 13-17…

Fluoride-driven 'turn on' ESPT in the binding with a novel benzimidazole-based sensor.

PubMed

Liu, Kai; Zhao, Xiaojun; Liu, Qingxiang; Huo, Jianzhong; Zhu, Bolin; Diao, Shihua

2015-01-01

A novel fluorescence sensor (BIP) bearing NH and OH subunits displayed a highly selective and sensitive recognition property for fluoride over other anions. Fluoride-driven ESPT, poorly used in anion recognition and sensing, was suggested to be responsible for the fluorescence enhancement with a blue shift of 35 nm in the emission spectrum.

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Action and Emotion Recognition from Point Light Displays: An Investigation of Gender Differences

PubMed Central

Alaerts, Kaat; Nackaerts, Evelien; Meyns, Pieter; Swinnen, Stephan P.; Wenderoth, Nicole

2011-01-01

Folk psychology advocates the existence of gender differences in socio-cognitive functions such as ‘reading’ the mental states of others or discerning subtle differences in body-language. A female advantage has been demonstrated for emotion recognition from facial expressions, but virtually nothing is known about gender differences in recognizing bodily stimuli or body language. The aim of the present study was to investigate potential gender differences in a series of tasks, involving the recognition of distinct features from point light displays (PLDs) depicting bodily movements of a male and female actor. Although recognition scores were considerably high at the overall group level, female participants were more accurate than males in recognizing the depicted actions from PLDs. Response times were significantly higher for males compared to females on PLD recognition tasks involving (i) the general recognition of ‘biological motion’ versus ‘non-biological’ (or ‘scrambled’ motion); or (ii) the recognition of the ‘emotional state’ of the PLD-figures. No gender differences were revealed for a control test (involving the identification of a color change in one of the dots) and for recognizing the gender of the PLD-figure. In addition, previous findings of a female advantage on a facial emotion recognition test (the ‘Reading the Mind in the Eyes Test’ (Baron-Cohen, 2001)) were replicated in this study. Interestingly, a strong correlation was revealed between emotion recognition from bodily PLDs versus facial cues. This relationship indicates that inter-individual or gender-dependent differences in recognizing emotions are relatively generalized across facial and bodily emotion perception. Moreover, the tight correlation between a subject's ability to discern subtle emotional cues from PLDs and the subject's ability to basically discriminate biological from non-biological motion provides indications that differences in emotion recognition may - at least to some degree – be related to more basic differences in processing biological motion per se. PMID:21695266

Action and emotion recognition from point light displays: an investigation of gender differences.

PubMed

Alaerts, Kaat; Nackaerts, Evelien; Meyns, Pieter; Swinnen, Stephan P; Wenderoth, Nicole

2011-01-01

Folk psychology advocates the existence of gender differences in socio-cognitive functions such as 'reading' the mental states of others or discerning subtle differences in body-language. A female advantage has been demonstrated for emotion recognition from facial expressions, but virtually nothing is known about gender differences in recognizing bodily stimuli or body language. The aim of the present study was to investigate potential gender differences in a series of tasks, involving the recognition of distinct features from point light displays (PLDs) depicting bodily movements of a male and female actor. Although recognition scores were considerably high at the overall group level, female participants were more accurate than males in recognizing the depicted actions from PLDs. Response times were significantly higher for males compared to females on PLD recognition tasks involving (i) the general recognition of 'biological motion' versus 'non-biological' (or 'scrambled' motion); or (ii) the recognition of the 'emotional state' of the PLD-figures. No gender differences were revealed for a control test (involving the identification of a color change in one of the dots) and for recognizing the gender of the PLD-figure. In addition, previous findings of a female advantage on a facial emotion recognition test (the 'Reading the Mind in the Eyes Test' (Baron-Cohen, 2001)) were replicated in this study. Interestingly, a strong correlation was revealed between emotion recognition from bodily PLDs versus facial cues. This relationship indicates that inter-individual or gender-dependent differences in recognizing emotions are relatively generalized across facial and bodily emotion perception. Moreover, the tight correlation between a subject's ability to discern subtle emotional cues from PLDs and the subject's ability to basically discriminate biological from non-biological motion provides indications that differences in emotion recognition may - at least to some degree - be related to more basic differences in processing biological motion per se.

Association of enhanced limbic response to threat with decreased cortical facial recognition memory response in schizophrenia

PubMed Central

Satterthwaite, Theodore D.; Wolf, Daniel H.; Loughead, James; Ruparel, Kosha; Valdez, Jeffrey N.; Siegel, Steven J.; Kohler, Christian G.; Gur, Raquel E.; Gur, Ruben C.

2014-01-01

Objective Recognition memory of faces is impaired in patients with schizophrenia, as is the neural processing of threat-related signals, but how these deficits interact to produce symptoms is unclear. Here we used an affective face recognition paradigm to examine possible interactions between cognitive and affective neural systems in schizophrenia. Methods fMRI (3T) BOLD response was examined in 21 controls and 16 patients during a two-choice recognition task using images of human faces. Each target face had previously been displayed with a threatening or non-threatening affect, but here were displayed with neutral affect. Responses to successful recognition and for the effect of previously threatening vs. non-threatening affect were evaluated, and correlations with total BPRS examined. Functional connectivity analyses examined the relationship between activation in the amygdala and cortical regions involved in recognition memory. Results Patients performed the task more slowly than controls. Controls recruited the expected cortical regions to a greater degree than patients, and patients with more severe symptoms demonstrated proportionally less recruitment. Increased symptoms were also correlated with augmented amygdala and orbitofrontal cortex response to threatening faces. Controls exhibited a negative correlation between activity in the amygdala and cortical regions involved in cognition, while patients showed a weakening of that relationship. Conclusions Increased symptoms were related to an enhanced threat response in limbic regions and a diminished recognition memory response in cortical regions, supporting a link between two brain systems often examined in isolation. This finding suggests that abnormal processing of threat-related signals in the environment may exacerbate cognitive impairment in schizophrenia. PMID:20194482

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

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H{sub 2}ndc) or 4,4′-(hydroxymethylene)dibenzoic acid (H{sub 2}hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd{sub 2}(2,6-ndc){sub 2}(bpp)(DMF)]·2DMF (1) and [Cd{sub 3}(hmdb){sub 3}(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations inmore » 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process. - Graphical abstract: Compound 1 exhibits a 3D self-penetrating 6-connected framework based on dinuclear cluster, and 2 displays an infinite 3D ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster. The flexible 1,3-bis(4-pyridyl)propane ligand displays different conformations in 1 and 2, which successfully controlled by size-matching mixed ligands during the self-assembly process.« less

Population structure of humpback whales in the western and central South Pacific Ocean as determined by vocal exchange among populations.

PubMed

Garland, Ellen C; Goldizen, Anne W; Lilley, Matthew S; Rekdahl, Melinda L; Garrigue, Claire; Constantine, Rochelle; Hauser, Nan Daeschler; Poole, M Michael; Robbins, Jooke; Noad, Michael J

2015-08-01

For cetaceans, population structure is traditionally determined by molecular genetics or photographically identified individuals. Acoustic data, however, has provided information on movement and population structure with less effort and cost than traditional methods in an array of taxa. Male humpback whales (Megaptera novaeangliae) produce a continually evolving vocal sexual display, or song, that is similar among all males in a population. The rapid cultural transmission (the transfer of information or behavior between conspecifics through social learning) of different versions of this display between distinct but interconnected populations in the western and central South Pacific region presents a unique way to investigate population structure based on the movement dynamics of a song (acoustic) display. Using 11 years of data, we investigated an acoustically based population structure for the region by comparing stereotyped song sequences among populations and years. We used the Levenshtein distance technique to group previously defined populations into (vocally based) clusters based on the overall similarity of their song display in space and time. We identified the following distinct vocal clusters: western cluster, 1 population off eastern Australia; central cluster, populations around New Caledonia, Tonga, and American Samoa; and eastern region, either a single cluster or 2 clusters, one around the Cook Islands and the other off French Polynesia. These results are consistent with the hypothesis that each breeding aggregation represents a distinct population (each occupied a single, terminal node) in a metapopulation, similar to the current understanding of population structure based on genetic and photo-identification studies. However, the central vocal cluster had higher levels of song-sharing among populations than the other clusters, indicating that levels of vocal connectivity varied within the region. Our results demonstrate the utility and value of using culturally transmitted vocal patterns as a way of defining connectivity to infer population structure. We suggest vocal patterns be incorporated by the International Whaling Commission in conjunction with traditional methods in the assessment of structure. © 2015, Society for Conservation Biology.

Multilingual Phoneme Models for Rapid Speech Processing System Development

DTIC Science & Technology

2006-09-01

processes are used to develop an Arabic speech recognition system starting from monolingual English models, In- ternational Phonetic Association (IPA...clusters. It was found that multilingual bootstrapping methods out- perform monolingual English bootstrapping methods on the Arabic evaluation data initially...International Phonetic Alphabet . . . . . . . . . 7 2.3.2 Multilingual vs. Monolingual Speech Recognition 7 2.3.3 Data-Driven Approaches

Exploring Parental Bonding in BED and Non-BED Obesity Compared with Healthy Controls: Clinical, Personality and Psychopathology Correlates.

PubMed

Amianto, Federico; Ercole, Roberta; Abbate Daga, Giovanni; Fassino, Secondo

2016-05-01

Early inadequate attachment experiences are relevant co-factors in the development of obesity and Binge Eating Disorder (BED), which often concurs with obesity. The relationship of parental bonding with personality and psychopathology may influence treatment strategies for obese subjects, either affected or not with BED. In this study, 443 obese women (BMI ≥ 30 kg/m(2)), including 243 with and 200 without BED, and 158 female controls were assessed with regards to attachment, personality and eating psychopathology measures. Clusters obtained using the scores of the Parental Bonding Instrument (PBI) were compared with each other and with a control subjects' group. Lower scores of parental bonding distinguished obese subjects with respect to healthy controls. The cluster analysis revealed two clusters of parenting among obese subjects. The larger one displayed intermediate care and overprotection between controls and the smaller cluster, with the exception of paternal overprotection which is similar to controls. This larger cluster was characterized by low persistence and levels of psychopathology which are intermediate between healthy controls and the smaller cluster. The smaller cluster displayed lower care and higher overcontrol from both parents. It also displays more extreme personality traits (high novelty seeking and harm avoidance, and lower self-directedness and cooperativeness) and more severe eating and general psychopathology. Different parenting dynamics relate to different personality patterns and eating psychopathology of obese subjects, but not to binge eating conducts. Personality differences between parenting clusters are more extensive than those between BED and non-BED subgroups. The two different typologies of obese subjects based on parenting may be relevant for treatment personalization. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Mining a Web Citation Database for Author Co-Citation Analysis.

ERIC Educational Resources Information Center

He, Yulan; Hui, Siu Cheung

2002-01-01

Proposes a mining process to automate author co-citation analysis based on the Web Citation Database, a data warehouse for storing citation indices of Web publications. Describes the use of agglomerative hierarchical clustering for author clustering and multidimensional scaling for displaying author cluster maps, and explains PubSearch, a…

Constitutional chromoanasynthesis: description of a rare chromosomal event in a patient.

PubMed

Plaisancié, Julie; Kleinfinger, Pascale; Cances, Claude; Bazin, Anne; Julia, Sophie; Trost, Detlef; Lohmann, Laurence; Vigouroux, Adeline

2014-10-01

Structural alterations in chromosomes are a frequent cause of cancers and congenital diseases. Recently, the phenomenon of chromosome crisis, consisting of a set of tens to hundreds of clustered genomic rearrangements, localized in one or a few chromosomes, was described in cancer cells under the term chromothripsis. Better knowledge and recognition of this catastrophic chromosome event has brought to light two distinct entities, chromothripsis and chromoanasynthesis. The complexity of these rearrangements and the original descriptions in tumor cells initially led to the thought that it was an acquired anomaly. In fact, a few patients have been reported with constitutional chromothripsis or chromoanasynthesis. Using microarray we identified a very complex chromosomal rearrangement in a patient who had a cytogenetically visible rearrangement of chromosome 18. The rearrangement contained more than 15 breakpoints localized on a single chromosome. Our patient displayed intellectual disability, behavioral troubles and craniofacial dysmorphism. Interestingly, the succession of duplications and triplications identified in our patient was not clustered on a single chromosomal region but spread over the entire chromosome 18. In the light of this new spectrum of chromosomal rearrangements, this report outlines the main features of these catastrophic events and discusses the underlying mechanism of the complex chromosomal rearrangement identified in our patient, which is strongly evocative of a chromoanasynthesis. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Competitive Deep-Belief Networks for Underwater Acoustic Target Recognition

PubMed Central

Shen, Sheng; Yao, Xiaohui; Sheng, Meiping; Wang, Chen

2018-01-01

Underwater acoustic target recognition based on ship-radiated noise belongs to the small-sample-size recognition problems. A competitive deep-belief network is proposed to learn features with more discriminative information from labeled and unlabeled samples. The proposed model consists of four stages: (1) A standard restricted Boltzmann machine is pretrained using a large number of unlabeled data to initialize its parameters; (2) the hidden units are grouped according to categories, which provides an initial clustering model for competitive learning; (3) competitive training and back-propagation algorithms are used to update the parameters to accomplish the task of clustering; (4) by applying layer-wise training and supervised fine-tuning, a deep neural network is built to obtain features. Experimental results show that the proposed method can achieve classification accuracy of 90.89%, which is 8.95% higher than the accuracy obtained by the compared methods. In addition, the highest accuracy of our method is obtained with fewer features than other methods. PMID:29570642

Design of platform for removing screws from LCD display shields

NASA Astrophysics Data System (ADS)

Tu, Zimei; Qin, Qin; Dou, Jianfang; Zhu, Dongdong

2017-11-01

Removing the screws on the sides of a shield is a necessary process in disassembling a computer LCD display. To solve this issue, a platform has been designed for removing the screws on display shields. This platform uses virtual instrument technology with LabVIEW as the development environment to design the mechanical structure with the technologies of motion control, human-computer interaction and target recognition. This platform removes the screws from the sides of the shield of an LCD display mechanically thus to guarantee follow-up separation and recycle.

Differential regulation of ParaHox genes by retinoic acid in the invertebrate chordate amphioxus (Branchiostoma floridae).

PubMed

Osborne, Peter W; Benoit, Gérard; Laudet, Vincent; Schubert, Michael; Ferrier, David E K

2009-03-01

The ParaHox cluster is the evolutionary sister to the Hox cluster. Like the Hox cluster, the ParaHox cluster displays spatial and temporal regulation of the component genes along the anterior/posterior axis in a manner that correlates with the gene positions within the cluster (a feature called collinearity). The ParaHox cluster is however a simpler system to study because it is composed of only three genes. We provide a detailed analysis of the amphioxus ParaHox cluster and, for the first time in a single species, examine the regulation of the cluster in response to a single developmental signalling molecule, retinoic acid (RA). Embryos treated with either RA or RA antagonist display altered ParaHox gene expression: AmphiGsx expression shifts in the neural tube, and the endodermal boundary between AmphiXlox and AmphiCdx shifts its anterior/posterior position. We identified several putative retinoic acid response elements and in vitro assays suggest some may participate in RA regulation of the ParaHox genes. By comparison to vertebrate ParaHox gene regulation we explore the evolutionary implications. This work highlights how insights into the regulation and evolution of more complex vertebrate arrangements can be obtained through studies of a simpler, unduplicated amphioxus gene cluster.

Bioactivation of particles

DOEpatents

Pinaud, Fabien [Berkeley, CA; King, David [San Francisco, CA; Weiss, Shimon [Los Angeles, CA

2011-08-16

Particles are bioactivated by attaching bioactivation peptides to the particle surface. The bioactivation peptides are peptide-based compounds that impart one or more biologically important functions to the particles. Each bioactivation peptide includes a molecular or surface recognition part that binds with the surface of the particle and one or more functional parts. The surface recognition part includes an amino-end and a carboxy-end and is composed of one or more hydrophobic spacers and one or more binding clusters. The functional part(s) is attached to the surface recognition part at the amino-end and/or said carboxy-end.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Automatic face recognition in HDR imaging

NASA Astrophysics Data System (ADS)

Pereira, Manuela; Moreno, Juan-Carlos; Proença, Hugo; Pinheiro, António M. G.

2014-05-01

The gaining popularity of the new High Dynamic Range (HDR) imaging systems is raising new privacy issues caused by the methods used for visualization. HDR images require tone mapping methods for an appropriate visualization on conventional and non-expensive LDR displays. These visualization methods might result in completely different visualization raising several issues on privacy intrusion. In fact, some visualization methods result in a perceptual recognition of the individuals, while others do not even show any identity. Although perceptual recognition might be possible, a natural question that can rise is how computer based recognition will perform using tone mapping generated images? In this paper, a study where automatic face recognition using sparse representation is tested with images that result from common tone mapping operators applied to HDR images. Its ability for the face identity recognition is described. Furthermore, typical LDR images are used for the face recognition training.

Biometric identification

NASA Astrophysics Data System (ADS)

Syryamkim, V. I.; Kuznetsov, D. N.; Kuznetsova, A. S.

2018-05-01

Image recognition is an information process implemented by some information converter (intelligent information channel, recognition system) having input and output. The input of the system is fed with information about the characteristics of the objects being presented. The output of the system displays information about which classes (generalized images) the recognized objects are assigned to. When creating and operating an automated system for pattern recognition, a number of problems are solved, while for different authors the formulations of these tasks, and the set itself, do not coincide, since it depends to a certain extent on the specific mathematical model on which this or that recognition system is based. This is the task of formalizing the domain, forming a training sample, learning the recognition system, reducing the dimensionality of space.

Effective implementation of hierarchical clustering

NASA Astrophysics Data System (ADS)

Verma, Mudita; Vijayarajan, V.; Sivashanmugam, G.; Bessie Amali, D. Geraldine

2017-11-01

Hierarchical clustering is generally used for cluster analysis in which we build up a hierarchy of clusters. In order to find that which cluster should be split a large amount of observations are being carried out. Here the data set of US based personalities has been considered for clustering. After implementation of hierarchical clustering on the data set we group it in three different clusters one is of politician, sports person and musicians. Training set is the main parameter which decides the category which has to be assigned to the observations that are being collected. The category of these observations must be known. Recognition comes from the formulation of classification. Supervised learning has the main instance in the form of classification. While on the other hand Clustering is an instance of unsupervised procedure. Clustering consists of grouping of data that have similar properties which are either their own or are inherited from some other sources.

Phage display of functional αβ single-chain T-cell receptor molecules specific for CD1b:Ac₂SGL complexes from Mycobacterium tuberculosis-infected cells.

PubMed

Camacho, Frank; Huggett, Jim; Kim, Louise; Infante, Juan F; Lepore, Marco; Perez, Viviana; Sarmiento, María E; Rook, Graham; Acosta, Armando

2013-01-01

The development of molecules specific for M. tuberculosis-infected cells has important implications, as these tools may facilitate understanding of the mechanisms regulating host pathogen interactions in vivo. In addition, development of new tools capable to targeting M. tuberculosis-infected cells may have potential applications to diagnosis, treatment, and prevention of tuberculosis (TB). Due to the lack of CD1b polymorphism, M. tuberculosis lipid-CD1b complexes could be considered as universal tuberculosis infection markers. The aim of the present study was to display on the PIII surface protein of m13 phage, a human αβ single-chain T-cell receptor molecule specific for CD1b:2-stearoyl-3-hydroxyphthioceranoyl-2´-sulfate-α-α´-D-trehalose (Ac₂SGL) which is a complex presented by human cells infected with M. tuberculosis. The results showed the pIII fusion particle was successfully displayed on the phage surface. The study of the recognition of the recombinant phage in ELISA and immunohistochemistry showed the recognition of CD1b:Ac₂SGL complexes and cells in human lung tissue from a tuberculosis patient respectively, suggesting the specific recognition of the lipid-CD1b complex.

Recognition and Posing of Emotional Expressions by Abused Children and Their Mothers.

ERIC Educational Resources Information Center

Camras, Linda A.; And Others

1988-01-01

A total of 20 abused and 20 nonabused pairs of children of three-seven years and their mothers participated in a facial expression posing task and a facial expression recognition task. Findings suggest that abused children may not observe as often as nonabused children do the easily interpreted voluntary displays of emotion by their mothers. (RH)

16p11.2 Deletion Mice Display Cognitive Deficits in Touchscreen Learning and Novelty Recognition Tasks

ERIC Educational Resources Information Center

Yang, Mu; Lewis, Freeman C.; Sarvi, Michael S.; Foley, Gillian M.; Crawley, Jacqueline N.

2015-01-01

Chromosomal 16p11.2 deletion syndrome frequently presents with intellectual disabilities, speech delays, and autism. Here we investigated the Dolmetsch line of 16p11.2 heterozygous (+/-) mice on a range of cognitive tasks with different neuroanatomical substrates. Robust novel object recognition deficits were replicated in two cohorts of 16p11.2…

Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Kan, Jianquan

2018-04-01

In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

A fuzzy clustering algorithm to detect planar and quadric shapes

NASA Technical Reports Server (NTRS)

Krishnapuram, Raghu; Frigui, Hichem; Nasraoui, Olfa

1992-01-01

In this paper, we introduce a new fuzzy clustering algorithm to detect an unknown number of planar and quadric shapes in noisy data. The proposed algorithm is computationally and implementationally simple, and it overcomes many of the drawbacks of the existing algorithms that have been proposed for similar tasks. Since the clustering is performed in the original image space, and since no features need to be computed, this approach is particularly suited for sparse data. The algorithm may also be used in pattern recognition applications.

Functional Analytic Psychotherapy (FAP) for Cluster B Personality Disorders: Creating Meaning, Mattering, and Skills

ERIC Educational Resources Information Center

Pankey, Julieann

2012-01-01

There are ten identified personality disorders, broken into three clusters: A, B, and C. Individuals with a cluster B diagnosis may demonstrate marked displays of emotional instability, erratic and disruptive patterns around interpersonal relationships, a myopic and restricted range of affect, a pronounced lack of empathy and insight, barriers…

The application of automatic recognition techniques in the Apollo 9 SO-65 experiment

NASA Technical Reports Server (NTRS)

Macdonald, R. B.

1970-01-01

A synoptic feature analysis is reported on Apollo 9 remote earth surface photographs that uses the methods of statistical pattern recognition to classify density points and clusterings in digital conversion of optical data. A computer derived geological map of a geological test site indicates that geological features of the range are separable, but that specific rock types are not identifiable.

Pattern recognition for Space Applications Center director's discretionary fund

NASA Technical Reports Server (NTRS)

Singley, M. E.

1984-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

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

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

On the clustering of multidimensional pictorial data

NASA Technical Reports Server (NTRS)

Bryant, J. D. (Principal Investigator)

1979-01-01

Obvious approaches to reducing the cost (in computer resources) of applying current clustering techniques to the problem of remote sensing are discussed. The use of spatial information in finding fields and in classifying mixture pixels is examined, and the AMOEBA clustering program is described. Internally, a pattern recognition program, from without, AMOEBA appears to be an unsupervised clustering program. It is fast and automatic. No choices (such as arbitrary thresholds to set split/combine sequences) need be made. The problem of finding the number of clusters is solved automatically. At the conclusion of the program, all points in the scene are classified; however, a provision is included for a reject classification of some points which, within the theoretical framework, cannot rationally be assigned to any cluster.

Dual emissions from MnS clusters confined in the sodalite nanocage of a chalcogenide-based semiconductor zeolite.

PubMed

Hu, Dandan; Zhang, Yingying; Lin, Jian; Hou, Yike; Li, Dongsheng; Wu, Tao

2017-03-21

A new host-guest hybrid system with MnS clusters confined in a chalcogenide-based semiconductor zeolite was for the first time constructed and its photoluminescence (PL) properties were also investigated. The existence of MnS clusters in the nanopores of the semiconductor zeolite was revealed by UV-Vis absorption spectroscopy, steady-state fluorescence analysis, Raman as well as Fourier transform infrared (FTIR) spectroscopy. The aggregation state of the entrapped MnS clusters at different measurement temperatures was probed by electron paramagnetic resonance (EPR) spectroscopy. Of significant importance is the fact that the entrapped MnS clusters displayed dual emissions at 518 nm (2.39 eV) and 746 nm (1.66 eV), respectively, and the long-wavelength emission has never been observed in other MnS-confined host-guest systems. These two emission peaks displayed tunable PL intensity affected by the loading level and measurement temperature. This can be explained by the different morphologies of MnS clusters with different aggregation states at the corresponding loading level or measurement temperature. The current study opens a new avenue to construct inorganic chalcogenide cluster involved host-guest systems with a semiconductor zeolite as the host matrix.

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

NASA Astrophysics Data System (ADS)

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

In recent decades, there has been a great deal of research into the problem of bilingual speech recognition-to develop a recognizer that can handle inter- and intra-sentential language switching between two languages. This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition systems for real world applications are tackled in this paper. One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language**. In order to process the intra-sentential language switching and reduce the amount of data required to robustly estimate statistical models, a compact single set of bilingual acoustic models derived by phone set merging and clustering is developed instead of using two separate monolingual models for each language. In our study, a novel Two-pass phone clustering method based on Confusion Matrix (TCM) is presented and compared with the log-likelihood measure method. Experiments testify that TCM can achieve better performance. Since potential system users' native language is Mandarin which is regarded as a matrix language in our application, their pronunciations of English as the embedded language usually contain Mandarin accents. In order to deal with the matrix language accents in embedded language, different non-native adaptation approaches are investigated. Experiments show that model retraining method outperforms the other common adaptation methods such as Maximum A Posteriori (MAP). With the effective incorporation of approaches on phone clustering and non-native adaptation, the Phrase Error Rate (PER) of MESRS for English utterances was reduced by 24.47% relatively compared to the baseline monolingual English system while the PER on Mandarin utterances was comparable to that of the baseline monolingual Mandarin system. The performance for bilingual utterances achieved 22.37% relative PER reduction.

Cluster-distinguishing genotypic and phenotypic diversity of carbapenem-resistant Gram-negative bacteria in solid-organ transplantation patients: a comparative study.

PubMed

Karampatakis, Theodoros; Geladari, Anastasia; Politi, Lida; Antachopoulos, Charalampos; Iosifidis, Elias; Tsiatsiou, Olga; Karyoti, Aggeliki; Papanikolaou, Vasileios; Tsakris, Athanassios; Roilides, Emmanuel

2017-07-31

Solid-organ transplant recipients may display high rates of colonization and/or infection by multidrug-resistant bacteria. We analysed and compared the phenotypic and genotypic diversity of carbapenem-resistant (CR) strains of Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii isolated from patients in the Solid Organ Transplantation department of our hospital. Between March 2012 and August 2013, 56 CR strains from various biological fluids underwent antimicrobial susceptibility testing with VITEK 2, molecular analysis by PCR amplification and genotypic analysis with pulsed-field gel electrophoresis (PFGE). They were clustered according to antimicrobial drug susceptibility and genotypic profiles. Diversity analyses were performed by calculating Simpson's diversity index and applying computed rarefaction curves.Results/Key findings. Among K. pneumoniae, KP-producers predominated (57.1 %). VIM and OXA-23 carbapenemases prevailed among P. aeruginosa and A. baumannii (89.4 and 88.9 %, respectively). KPC-producing K. pneumoniae and OXA-23 A. baumannii were assigned in single PFGE pulsotypes. VIM-producing P. aeruginosa generated multiple pulsotypes. CR K. pneumoniae strains displayed phenotypic diversity in tigecycline, colistin (CS), amikacin (AMK), gentamicin (GEN) and co-trimoxazole (SXT) (16 clusters); P. aeruginosa displayed phenotypic diversity in cefepime (FEP), ceftazidime, aztreonam, piperacillin, piperacillin-tazobactam, AMK, GEN and CS (9 clusters); and A. baumannii displayed phenotypic diversity in AMK, GEN, SXT, FEP, tobramycin and rifampicin (8 clusters). The Simpson diversity indices for the interpretative phenotype and PFGE analysis were 0.89 and 0.6, respectively, for K. pneumoniae strains (P<0.001); 0.77 and 0.6 for P. aeruginosa (P=0.22); and 0.86 and 0.19 for A. baumannii (P=0.004). The presence of different antimicrobial susceptibility profiles does not preclude the possibility that two CR K. pneumoniae or A. baumannii isolates are clonally related.

WD-repeat instability and diversification of the Podospora anserina hnwd non-self recognition gene family.

PubMed

Chevanne, Damien; Saupe, Sven J; Clavé, Corinne; Paoletti, Mathieu

2010-05-06

Genes involved in non-self recognition and host defence are typically capable of rapid diversification and exploit specialized genetic mechanism to that end. Fungi display a non-self recognition phenomenon termed heterokaryon incompatibility that operates when cells of unlike genotype fuse and leads to the cell death of the fusion cell. In the fungus Podospora anserina, three genes controlling this allorecognition process het-d, het-e and het-r are paralogs belonging to the same hnwd gene family. HNWD proteins are STAND proteins (signal transduction NTPase with multiple domains) that display a WD-repeat domain controlling recognition specificity. Based on genomic sequence analysis of different P. anserina isolates, it was established that repeat regions of all members of the gene family are extremely polymorphic and undergoing concerted evolution arguing for frequent recombination within and between family members. Herein, we directly analyzed the genetic instability and diversification of this allorecognition gene family. We have constituted a collection of 143 spontaneous mutants of the het-R (HNWD2) and het-E (hnwd5) genes with altered recognition specificities. The vast majority of the mutants present rearrangements in the repeat arrays with deletions, duplications and other modifications as well as creation of novel repeat unit variants. We investigate the extreme genetic instability of these genes and provide a direct illustration of the diversification strategy of this eukaryotic allorecognition gene family.

Recognition profile of emotions in natural and virtual faces.

PubMed

Dyck, Miriam; Winbeck, Maren; Leiberg, Susanne; Chen, Yuhan; Gur, Ruben C; Gur, Rurben C; Mathiak, Klaus

2008-01-01

Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications.

Recognition Profile of Emotions in Natural and Virtual Faces

PubMed Central

Dyck, Miriam; Winbeck, Maren; Leiberg, Susanne; Chen, Yuhan; Gur, Rurben C.; Mathiak, Klaus

2008-01-01

Background Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. Methodology/Principal Findings Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. Conclusions/Significance Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications. PMID:18985152

Smartphone-Based Patients' Activity Recognition by Using a Self-Learning Scheme for Medical Monitoring.

PubMed

Guo, Junqi; Zhou, Xi; Sun, Yunchuan; Ping, Gong; Zhao, Guoxing; Li, Zhuorong

2016-06-01

Smartphone based activity recognition has recently received remarkable attention in various applications of mobile health such as safety monitoring, fitness tracking, and disease prediction. To achieve more accurate and simplified medical monitoring, this paper proposes a self-learning scheme for patients' activity recognition, in which a patient only needs to carry an ordinary smartphone that contains common motion sensors. After the real-time data collection though this smartphone, we preprocess the data using coordinate system transformation to eliminate phone orientation influence. A set of robust and effective features are then extracted from the preprocessed data. Because a patient may inevitably perform various unpredictable activities that have no apriori knowledge in the training dataset, we propose a self-learning activity recognition scheme. The scheme determines whether there are apriori training samples and labeled categories in training pools that well match with unpredictable activity data. If not, it automatically assembles these unpredictable samples into different clusters and gives them new category labels. These clustered samples combined with the acquired new category labels are then merged into the training dataset to reinforce recognition ability of the self-learning model. In experiments, we evaluate our scheme using the data collected from two postoperative patient volunteers, including six labeled daily activities as the initial apriori categories in the training pool. Experimental results demonstrate that the proposed self-learning scheme for activity recognition works very well for most cases. When there exist several types of unseen activities without any apriori information, the accuracy reaches above 80 % after the self-learning process converges.

The Development of Facial Emotion Recognition: The Role of Configural Information

ERIC Educational Resources Information Center

Durand, Karine; Gallay, Mathieu; Seigneuric, Alix; Robichon, Fabrice; Baudouin, Jean-Yves

2007-01-01

The development of children's ability to recognize facial emotions and the role of configural information in this development were investigated. In the study, 100 5-, 7-, 9-, and 11-year-olds and 26 adults needed to recognize the emotion displayed by upright and upside-down faces. The same participants needed to recognize the emotion displayed by…

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization and Manipulation of the Pathway-Specific Late Regulator AlpW Reveals Streptomyces ambofaciens as a New Producer of Kinamycins ▿ †

PubMed Central

Bunet, Robert; Song, Lijiang; Mendes, Marta Vaz; Corre, Christophe; Hotel, Laurence; Rouhier, Nicolas; Framboisier, Xavier; Leblond, Pierre; Challis, Gregory L.; Aigle, Bertrand

2011-01-01

The genome sequence of Streptomyces ambofaciens, a species known to produce the congocidine and spiramycin antibiotics, has revealed the presence of numerous gene clusters predicted to be involved in the biosynthesis of secondary metabolites. Among them, the type II polyketide synthase-encoding alp cluster was shown to be responsible for the biosynthesis of a compound with antibacterial activity. Here, by means of a deregulation approach, we gained access to workable amounts of the antibiotics for structure elucidation. These compounds, previously designated as alpomycin, were shown to be known members of kinamycin family of antibiotics. Indeed, a mutant lacking AlpW, a member of the TetR regulator family, was shown to constitutively produce kinamycins. Comparative transcriptional analyses showed that expression of alpV, the essential regulator gene required for activation of the biosynthetic genes, is strongly maintained during the stationary growth phase in the alpW mutant, a stage at which alpV transcripts and thereby transcripts of the biosynthetic genes normally drop off. Recombinant AlpW displayed DNA binding activity toward specific motifs in the promoter region of its own gene and that of alpV and alpZ. These recognition sequences are also targets for AlpZ, the γ-butyrolactone-like receptor involved in the regulation of the alp cluster. However, unlike that of AlpZ, the AlpW DNA-binding ability seemed to be insensitive to the signaling molecules controlling antibiotic biosynthesis. Together, the results presented in this study reveal S. ambofaciens to be a new producer of kinamycins and AlpW to be a key late repressor of the cellular control of kinamycin biosynthesis. PMID:21193612

Molecular Control of Polyene Macrolide Biosynthesis

PubMed Central

Santos-Aberturas, Javier; Vicente, Cláudia M.; Guerra, Susana M.; Payero, Tamara D.; Martín, Juan F.; Aparicio, Jesús F.

2011-01-01

Control of polyene macrolide production in Streptomyces natalensis is mediated by the transcriptional activator PimM. This regulator, which combines an N-terminal PAS domain with a C-terminal helix-turn-helix motif, is highly conserved among polyene biosynthetic gene clusters. PimM, truncated forms of the protein without the PAS domain (PimMΔPAS), and forms containing just the DNA-binding domain (DBD) (PimMDBD) were overexpressed in Escherichia coli as GST-fused proteins. GST-PimM binds directly to eight promoters of the pimaricin cluster, as demonstrated by electrophoretic mobility shift assays. Assays with truncated forms of the protein revealed that the PAS domain does not mediate specificity or the distinct recognition of target genes, which rely on the DBD domain, but significantly reduces binding affinity up to 500-fold. Transcription start points were identified by 5′-rapid amplification of cDNA ends, and the binding regions of PimMDBD were investigated by DNase I protection studies. In all cases, binding took place covering the −35 hexamer box of each promoter, suggesting an interaction of PimM and RNA polymerase to cause transcription activation. Information content analysis of the 16 sequences protected in target promoters was used to deduce the structure of the PimM-binding site. This site displays dyad symmetry, spans 14 nucleotides, and adjusts to the consensus TVGGGAWWTCCCBA. Experimental validation of this binding site was performed by using synthetic DNA duplexes. Binding of PimM to the promoter region of one of the polyketide synthase genes from the Streptomyces nodosus amphotericin cluster containing the consensus binding site was also observed, thus proving the applicability of the findings reported here to other antifungal polyketides. PMID:21187288

Structural Analysis of Single Domain Antibodies Bound to a Second Neutralizing Hot Spot on Ricin Toxin's Enzymatic Subunit.

PubMed

Rudolph, Michael J; Vance, David J; Cassidy, Michael S; Rong, Yinghui; Mantis, Nicholas J

2017-01-20

Ricin toxin is a heterodimer consisting of RTA, a ribosome-inactivating protein, and RTB, a lectin that facilitates receptor-mediated uptake into mammalian cells. In previous studies, we demonstrated that toxin-neutralizing antibodies target four spatially distinct hot spots on RTA, which we refer to as epitope clusters I-IV. In this report, we identified and characterized three single domain camelid antibodies (V H H) against cluster II. One of these V H Hs, V5E1, ranks as one of the most potent ricin-neutralizing antibodies described to date. We solved the X-ray crystal structures of each of the three V H Hs (E1, V1C7, and V5E1) in complex with RTA. V5E1 buries a total of 1,133 Å 2 of surface area on RTA and makes primary contacts with α-helix A (residues 18-32), α-helix F (182-194), as well as the F-G loop. V5E1, by virtue of complementarity determining region 3 (CDR3), may also engage with RTB and potentially interfere with the high affinity galactose-recognition element that plays a critical role in toxin attachment to cell surfaces and intracellular trafficking. The two other V H Hs, E1 and V1C7, bind epitopes adjacent to V5E1 but display only weak toxin neutralizing activity, thereby providing structural insights into specific residues within cluster II that may be critical contact points for toxin inactivation. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Understanding eye movements in face recognition using hidden Markov models.

PubMed

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

2014-09-16

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

Association of enhanced limbic response to threat with decreased cortical facial recognition memory response in schizophrenia.

PubMed

Satterthwaite, Theodore D; Wolf, Daniel H; Loughead, James; Ruparel, Kosha; Valdez, Jeffrey N; Siegel, Steven J; Kohler, Christian G; Gur, Raquel E; Gur, Ruben C

2010-04-01

Recognition memory of faces is impaired in patients with schizophrenia, as is the neural processing of threat-related signals, but how these deficits interact to produce symptoms is unclear. The authors used an affective face recognition paradigm to examine possible interactions between cognitive and affective neural systems in schizophrenia. Blood-oxygen-level-dependent response was examined by means of functional magnetic resonance imaging (3 Tesla) in healthy comparison subjects (N=21) and in patients with schizophrenia (N=12) or schizoaffective disorder, depressed type (N=4), during a two-choice recognition task that used images of human faces. Each target face, previously displayed with a threatening or nonthreatening affect, was displayed with neutral affect. Responses to successful recognition and responses to the effect of previously threatening versus nonthreatening affect were evaluated, and correlations with symptom severity (total Brief Psychiatric Rating Scale score) were examined. Functional connectivity analyses examined the relationship between activation in the amygdala and cortical regions involved in recognition memory. Patients performed the task more slowly than healthy comparison subjects. Comparison subjects recruited the expected cortical regions to a greater degree than patients, and patients with more severe symptoms demonstrated proportionally less recruitment. Increased symptoms were also correlated with augmented amygdala and orbitofrontal cortex response to threatening faces. Comparison subjects exhibited a negative correlation between activity in the amygdala and cortical regions involved in cognition, while patients showed weakening of this relationship. Increased symptoms were related to an enhanced threat response in limbic regions and a diminished recognition memory response in cortical regions, supporting a link between these two brain systems that are often examined in isolation. This finding suggests that abnormal processing of threat-related signals in the environment may exacerbate cognitive impairment in schizophrenia.

Major depressive disorder skews the recognition of emotional prosody.

PubMed

Péron, Julie; El Tamer, Sarah; Grandjean, Didier; Leray, Emmanuelle; Travers, David; Drapier, Dominique; Vérin, Marc; Millet, Bruno

2011-06-01

Major depressive disorder (MDD) is associated with abnormalities in the recognition of emotional stimuli. MDD patients ascribe more negative emotion but also less positive emotion to facial expressions, suggesting blunted responsiveness to positive emotional stimuli. To ascertain whether these emotional biases are modality-specific, we examined the effects of MDD on the recognition of emotions from voices using a paradigm designed to capture subtle effects of biases. Twenty-one MDD patients and 21 healthy controls (HC) underwent clinical and neuropsychological assessments, followed by a paradigm featuring pseudowords spoken by actors in five types of emotional prosody, rated on continuous scales. Overall, MDD patients performed more poorly than HC, displaying significantly impaired recognition of fear, happiness and sadness. Compared with HC, they rated fear significantly more highly when listening to anger stimuli. They also displayed a bias toward surprise, rating it far higher when they heard sad or fearful utterances. Furthermore, for happiness stimuli, MDD patients gave higher ratings for negative emotions (fear and sadness). A multiple regression model on recognition of emotional prosody in MDD patients showed that the best fit was achieved using the executive functioning (categorical fluency, number of errors in the MCST, and TMT B-A) and the total score of the Montgomery-Asberg Depression Rating Scale. Impaired recognition of emotions would appear not to be specific to the visual modality but to be present also when emotions are expressed vocally, this impairment being related to depression severity and dysexecutive syndrome. MDD seems to skew the recognition of emotional prosody toward negative emotional stimuli and the blunting of positive emotion appears not to be restricted to the visual modality. Copyright © 2011 Elsevier Inc. All rights reserved.

Topological side-chain classification of beta-turns: ideal motifs for peptidomimetic development.

PubMed

Tran, Tran Trung; McKie, Jim; Meutermans, Wim D F; Bourne, Gregory T; Andrews, Peter R; Smythe, Mark L

2005-08-01

Beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. Beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi2, psi2, phi3 and psi3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C(alpha)-C(beta) vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C(alpha)-C(beta) vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

Human isolates of Salmonella enterica serovar Typhimurium from Taiwan displayed significantly higher levels of antimicrobial resistance than those from Denmark.

PubMed

Torpdahl, Mia; Lauderdale, Tsai-Ling; Liang, Shiu-Yun; Li, Ishien; Wei, Sung-Hsi; Chiou, Chien-Shun

2013-02-01

Salmonella enterica serovar Typhimurium is a major zoonotic pathogen with a high prevalence of antimicrobial resistance. This pathogen can disseminate across borders and spread far distances via the food trade and international travel. In this study, we compared the genotypes and antimicrobial resistance of 378 S. Typhimurium isolates collected in Taiwan and Denmark between 2009 and 2010. Genotyping revealed that many S. Typhimurium strains were concurrently circulating in Taiwan, Denmark and other countries in 2009 and 2010. When compared to the isolates collected from Denmark, the isolates from Taiwan displayed a significantly higher level of resistance to 11 of the 12 tested antimicrobials. Seven genetic clusters (A-G) were designated for the isolates. A high percentage of the isolates in genetic clusters C, F and G were multidrug-resistant. Of the isolates in cluster C, 79.2% were ASSuT-resistant, characterized by resistance to ampicillin, streptomycin, sulfamethoxazole, and tetracycline. In cluster F, 84.1% of the isolates were ACSSuT-resistant (resistant to ASSuT and chloramphenicol). Cluster G was unique to Taiwan and characterized in most isolates by the absence of three VNTRs (ST20, ST30 and STTR6) as well as a variety of multidrug resistance profiles. This cluster exhibited very high to extremely high levels of resistance to several first-line drugs, and among the seven clusters, it displayed the highest levels of resistance to cefotaxime and ceftazidime, ciprofloxacin and gentamicin. The high prevalence of antimicrobial resistance in S. Typhimurium from Taiwan highlights the necessity to strictly regulate the use of antimicrobials in the agriculture and human health care sectors. Copyright © 2012 Elsevier B.V. All rights reserved.

NeatMap--non-clustering heat map alternatives in R.

PubMed

Rajaram, Satwik; Oono, Yoshi

2010-01-22

The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the detection of hidden structures and relations in the data. However, it is hampered by its use of cluster analysis which does not always respect the intrinsic relations in the data, often requiring non-standardized reordering of rows/columns to be performed post-clustering. This sometimes leads to uninformative and/or misleading conclusions. Often it is more informative to use dimension-reduction algorithms (such as Principal Component Analysis and Multi-Dimensional Scaling) which respect the topology inherent in the data. Yet, despite their proven utility in the analysis of biological data, they are not as widely used. This is at least partially due to the lack of user-friendly visualization methods with the visceral impact of the heat map. NeatMap is an R package designed to meet this need. NeatMap offers a variety of novel plots (in 2 and 3 dimensions) to be used in conjunction with these dimension-reduction techniques. Like the heat map, but unlike traditional displays of such results, it allows the entire dataset to be displayed while visualizing relations between elements. It also allows superimposition of cluster analysis results for mutual validation. NeatMap is shown to be more informative than the traditional heat map with the help of two well-known microarray datasets. NeatMap thus preserves many of the strengths of the clustered heat map while addressing some of its deficiencies. It is hoped that NeatMap will spur the adoption of non-clustering dimension-reduction algorithms.

Controlled Expansion of a Strong-Field Iron Nitride Cluster: Multi-Site Ligand Substitution as a Strategy for Activating Interstitial Nitride Nucleophilicity.

PubMed

Drance, Myles J; Mokhtarzadeh, Charles C; Melaimi, Mohand; Agnew, Douglas W; Moore, Curtis E; Rheingold, Arnold L; Figueroa, Joshua S

2018-05-02

Multimetallic clusters have long been investigated as molecular surrogates for reactive sites on metal surfaces. In the case of the μ 4 -nitrido cluster [Fe 4 (μ 4 -N)(CO) 12 ] - , this analogy is limited owing to the electron-withdrawing effect of carbonyl ligands on the iron nitride core. Described here is the synthesis and reactivity of [Fe 4 (μ 4 -N)(CO) 8 (CNAr Mes2 ) 4 ] - , an electron-rich analogue of [Fe 4 (μ 4 -N)(CO) 12 ] - , where the interstitial nitride displays significant nucleophilicity. This characteristic enables rational expansion with main-group and transition-metal centers to yield unsaturated sites. The resulting clusters display surface-like reactivity through coordination-sphere-dependent atom rearrangement and metal-metal cooperativity. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Isolation of a peptide from Ph.D.-C7C phage display library for detection of Cry1Ab.

PubMed

Wang, Yun; Wang, Qian; Wu, Ai-Hua; Hao, Zhen-Ping; Liu, Xian-Jin

2017-12-15

Traditional ELISA methods of using animal immunity yield antibodies for detection Cry toxin. Not only is this incredibly harmful to the animals, but is also time-intensive. Here we developed a simple method to yield the recognition element. Using a critical selection strategy and immunoassay we confirmed a clone from the Ph.D-C7C phage library, which has displayed the most interesting Cry1Ab-binding characteristics examined in this study (Fig. 1). The current study indicates that isolating peptide is an alternative method for the preparation of a recognition element, and that the developed assay is a potentially useful tool for detecting Cry1Ab. Copyright © 2017. Published by Elsevier Inc.

Multifunctional microcontrollable interface module

NASA Astrophysics Data System (ADS)

Spitzer, Mark B.; Zavracky, Paul M.; Rensing, Noa M.; Crawford, J.; Hockman, Angela H.; Aquilino, P. D.; Girolamo, Henry J.

2001-08-01

This paper reports the development of a complete eyeglass- mounted computer interface system including display, camera and audio subsystems. The display system provides an SVGA image with a 20 degree horizontal field of view. The camera system has been optimized for face recognition and provides a 19 degree horizontal field of view. A microphone and built-in pre-amp optimized for voice recognition and a speaker on an articulated arm are included for audio. An important feature of the system is a high degree of adjustability and reconfigurability. The system has been developed for testing by the Military Police, in a complete system comprising the eyeglass-mounted interface, a wearable computer, and an RF link. Details of the design, construction, and performance of the eyeglass-based system are discussed.

Training a whole-book LSTM-based recognizer with an optimal training set

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Yousefi, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2018-04-01

Despite the recent progress in OCR technologies, whole-book recognition, is still a challenging task, in particular in case of old and historical books, that the unknown font faces or low quality of paper and print contributes to the challenge. Therefore, pre-trained recognizers and generic methods do not usually perform up to required standards, and usually the performance degrades for larger scale recognition tasks, such as of a book. Such reportedly low error-rate methods turn out to require a great deal of manual correction. Generally, such methodologies do not make effective use of concepts such redundancy in whole-book recognition. In this work, we propose to train Long Short Term Memory (LSTM) networks on a minimal training set obtained from the book to be recognized. We show that clustering all the sub-words in the book, and using the sub-word cluster centers as the training set for the LSTM network, we can train models that outperform any identical network that is trained with randomly selected pages of the book. In our experiments, we also show that although the sub-word cluster centers are equivalent to about 8 pages of text for a 101- page book, a LSTM network trained on such a set performs competitively compared to an identical network that is trained on a set of 60 randomly selected pages of the book.

The Development and Evaluation of a Teleprocessed Computer-Assisted Instruction Course in the Recognition of Malarial Parasites. Final Report; May 1, 1967 - June 30, 1968.

ERIC Educational Resources Information Center

Mitzel, Harold E.

A computer-assisted instruction course in the recognition of malarial parasites was developed and evaluated. The course includes stage discrimination, species discrimination, and case histories. Segments developed use COURSEWRITER as an author language and are presented via a display terminal that permits two-way communication with an IBM computer…

78 FR 69931 - Ford Motor Company, Grant of Petition for Decision of Inconsequential Noncompliance

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-21

... indicator within the instrument cluster instead of the word ``BRAKE'' as required in FMVSS No. 101 and FMVSS No. 135. Ford stated its belief that although the instrument cluster telltale symbols are displayed... instrument cluster noting that an important message is stored and can be re-accessed by requesting a System...

Evolution of the properties of Al(n)N(n) clusters with size.

PubMed

Costales, Aurora; Blanco, M A; Francisco, E; Pandey, Ravindra; Martín Pendás, A

2005-12-29

A global optimization of stoichiometric (AlN)(n) clusters (n = 1-25, 30, 35, ..., 95, 100) has been performed using the basin-hopping (BH) method and describing the interactions with simple and yet realistic interatomic potentials. The results for the smaller isomers agree with those of previous electronic structure calculations, thus validating the present scheme. The lowest-energy isomers found can be classified in three different categories according to their structural motifs: (i) small clusters (n = 2-5), with planar ring structures and 2-fold coordination, (ii) medium clusters (n = 6-40), where a competition between stacked rings and globular-like empty cages exists, and (iii) large clusters (n > 40), large enough to mix different elements of the previous stage. All the atoms in small and medium-sized clusters are in the surface, while large clusters start to display interior atoms. Large clusters display a competition between tetrahedral and octahedral-like features: the former lead to a lower energy interior in the cluster, while the latter allow for surface terminations with a lower energy. All of the properties studied present different regimes according to the above classification. It is of particular interest that the local properties of the interior atoms do converge to the bulk limit. The isomers with n = 6 and 12 are specially stable with respect to the gain or loss of AlN molecules.

Aptamer-recognized carbohydrates on the cell membrane revealed by super-resolution microscopy.

PubMed

Jing, Yingying; Cai, Mingjun; Xu, Haijiao; Zhou, Lulu; Yan, Qiuyan; Gao, Jing; Wang, Hongda

2018-04-26

Carbohydrates are one of the most important components on the cell membrane, which participate in various physiological activities, and their aberrant expression is a consequence of pathological changes. In previous studies, carbohydrate analysis basically relied on lectins. However, discrimination between lectins still exists due to their multivalent character. Furthermore, the structures obtained by carbohydrate-lectin crosslinking confuse our direct observation to some extent. Fortunately, the emergence of aptamers, which are smaller and more flexible, has provided us an unprecedented choice. Herein, an aptamer recognition method with high precise localization was developed for imaging membrane-bound N-acetylgalactosamine (GalNAc). By using direct stochastic optical reconstruction microscopy (dSTORM), we compared this aptamer recognition method with the lectin recognition method for visualizing the detailed structure of GalNAc at the nanometer scale. The results indicated that GalNAc forms irregular clusters on the cell membrane with a resolution of 23 ± 7 nm by aptamer recognition. Additionally, when treated with N-acetylgalactosidase, the aptamer-recognized GalNAc shows a more significant decrease in cluster size and localization density, thus verifying better specificity of aptamers than lectins. Collectively, our study suggests that aptamers can act as perfect substitutes for lectins in carbohydrate labeling, which will be of great potential value in the field of super-resolution fluorescence imaging.

Mutual mother-infant recognition in mice: The role of pup ultrasonic vocalizations.

PubMed

Mogi, Kazutaka; Takakuda, Ayaka; Tsukamoto, Chihiro; Ooyama, Rumi; Okabe, Shota; Koshida, Nobuyoshi; Nagasawa, Miho; Kikusui, Takefumi

2017-05-15

The importance of the mother-infant bond for the development of offspring health and sociality has been studied not only in primate species but also in rodent species. A social bond is defined as affiliative behaviors toward a specific partner. However, controversy remains concerning whether mouse pups can distinguish between their own mother and an alien mother, and whether mothers can differentiate their own pups from alien pups. In this study, we investigated whether mutual recognition exists between mother and infant in ICR mice. Furthermore, we studied pup ultrasonic vocalizations (USVs), which are emitted by pups when isolated from their mothers, to determine whether they constituted an individual signature used by the mother for pup recognition. We conducted a variety of two-choice tests and selective-retrieving tests. In a two-choice test for mother recognition by the pup, pups between the ages of 17 and 21days preferred their own mothers to alien mothers. In a two-choice test for pup recognition by its mother, the mothers located their own pups faster than alien pups at the beginning of the test, yet displayed similar retrieving activity for both their own and alien pups in the subsequent selective-retrieving test. Furthermore, after recording USVs from pups from subject and alien mothers, then playing them simultaneously, subject mothers displayed a preference for pup USVs emitted by their own pups. Overall, our findings support the existence of mother-infant bonding in mice and suggest that pup USVs contribute to pup recognition by mothers. Copyright © 2016. Published by Elsevier B.V.

Evaluating Effects of Divided Hemispheric Processing on Word Recognition in Foveal and Extrafoveal Displays: The Evidence from Arabic

PubMed Central

Almabruk, Abubaker A. A.; Paterson, Kevin B.; McGowan, Victoria; Jordan, Timothy R.

2011-01-01

Background Previous studies have claimed that a precise split at the vertical midline of each fovea causes all words to the left and right of fixation to project to the opposite, contralateral hemisphere, and this division in hemispheric processing has considerable consequences for foveal word recognition. However, research in this area is dominated by the use of stimuli from Latinate languages, which may induce specific effects on performance. Consequently, we report two experiments using stimuli from a fundamentally different, non-Latinate language (Arabic) that offers an alternative way of revealing effects of split-foveal processing, if they exist. Methods and Findings Words (and pseudowords) were presented to the left or right of fixation, either close to fixation and entirely within foveal vision, or further from fixation and entirely within extrafoveal vision. Fixation location and stimulus presentations were carefully controlled using an eye-tracker linked to a fixation-contingent display. To assess word recognition, Experiment 1 used the Reicher-Wheeler task and Experiment 2 used the lexical decision task. Results Performance in both experiments indicated a functional division in hemispheric processing for words in extrafoveal locations (in recognition accuracy in Experiment 1 and in reaction times and error rates in Experiment 2) but no such division for words in foveal locations. Conclusions These findings from a non-Latinate language provide new evidence that although a functional division in hemispheric processing exists for word recognition outside the fovea, this division does not extend up to the point of fixation. Some implications for word recognition and reading are discussed. PMID:21559084

The Face of the Chameleon: The Experience of Facial Mimicry for the Mimicker and the Mimickee

PubMed Central

Kulesza, Wojciech Marek; Cisłak, Aleksandra; Vallacher, Robin R.; Nowak, Andrzej; Czekiel, Martyna; Bedynska, Sylwia

2015-01-01

ABSTRACT This research addressed three questions concerning facial mimicry: (a) Does the relationship between mimicry and liking characterize all facial expressions, or is it limited to specific expressions? (b) Is the relationship between facial mimicry and liking symmetrical for the mimicker and the mimickee? (c) Does conscious mimicry have consequences for emotion recognition? A paradigm is introduced in which participants interact over a computer setup with a confederate whose prerecorded facial displays of emotion are synchronized with participants’ behavior to create the illusion of social interaction. In Experiment 1, the confederate did or did not mimic participants’ facial displays of various subsets of basic emotions. Mimicry promoted greater liking for the confederate regardless of which emotions were mimicked. Experiment 2 reversed these roles: participants were instructed to mimic or not to mimic the confederate’s facial displays. Mimicry did not affect liking for the confederate but it did impair emotion recognition. PMID:25811746

Contextual cuing: the effects of stimulus variation, intentionality, and aging.

PubMed

Lyon, John; Scialfa, Charles; Cordazzo, Scheila; Bubric, Katherine

2014-06-01

Three experiments investigated the generalisation of contextual cuing and whether the effect is incidental or intentional in nature. Experiment 1 assessed contextual cuing across variations in display contrast, homogeneity, and spatial separation. Cuing effects were found with all display types and reaction-time disruption was manifested for repeated displays when consistent configurations had their target locations altered. Recognition memory for repeated displays was at chance levels. Experiment 2 showed that contextual cuing was insensitive to instructions to search for and remember repeated displays. Experiment 2A found that there were no age differences in contextual cuing or effects of intentional instructions, and no memory for repeated displays. Future research questions concern the generalisation of contextual cuing to a wider variety of display conditions and naturalistic tasks.

New output improvements for CLASSY

NASA Technical Reports Server (NTRS)

Rassbach, M. E. (Principal Investigator)

1981-01-01

Additional output data and formats for the CLASSY clustering algorithm were developed. Four such aids to the CLASSY user are described. These are: (1) statistical measures; (2) special map types; (3) formats for standard output; and (4) special cluster display method.

Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions.

PubMed

Abe, S

1998-01-01

In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables.

Influence of HLA-DR and -DQ alleles on autoantibody recognition of distinct epitopes within the juxtamembrane domain of the IA-2 autoantigen in type 1 diabetes.

PubMed

Richardson, Carolyn C; McLaughlin, Kerry A; Morgan, Diana; Feltbower, Richard G; Christie, Michael R

2016-02-01

Insulinoma-associated protein 2 (IA-2) is a major target of autoimmunity in type 1 diabetes. When first detected, IA-2-autoantibodies commonly bind epitopes in the juxtamembrane (JM) domain of IA-2 and antibody responses subsequently spread to the tyrosine phosphatase domain. Definition of structures of epitopes in the JM domain, and genetic requirements for autoimmunity to these epitopes, is important for our understanding of initiation and progression of autoimmunity. The aims of this study were to investigate the contribution of individual amino acids in the IA-2 JM domain to antibody binding to these epitopes and the role of HLA genotypes in determining epitope specificity. Regions of the JM domain recognised by autoantibodies were identified by peptide competition and inhibitory effects of alanine substitutions of residues within the JM region. Antibody binding was determined by radioligand binding assays using sera from patients genotyped for HLA-DRB1 and -DQB1 alleles. Patients were categorised into two distinct groups of JM antibody reactivity according to peptide inhibition. Inhibition by substitutions of individual amino acids within the JM domain differed between patients, indicating heterogeneity in epitope recognition. Cluster analysis defined six groups of residues having similar inhibitory effects on antibody binding, with three clusters showing differences in patients affected or unaffected by peptide. One cluster demonstrated significant differences in antibody binding between HLA-DRB1*04 and HLA-DRB1*07 patients and within DRB1*04 individuals; antibody recognition of a second cluster depended on expression of HLA-DQB1*0302. The results identify amino acids contributing to distinct epitopes on IA-2, with both HLA-DR and HLA-DQ alleles influencing epitope specificity.

Clustering of samples and variables with mixed-type data

PubMed Central

Edelmann, Dominic; Kopp-Schneider, Annette

2017-01-01

Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then visualized, while adding further information, like clinical factors, on top. However, a more integrative approach is desirable, where all available data are analyzed jointly, and where also in the visualization different data sources are combined in a more natural way. Here we specifically target integrative visualization and present a heatmap-style graphic display. To this end, we develop and explore methods for clustering mixed-type data, with special focus on clustering variables. Clustering of variables does not receive as much attention in the literature as does clustering of samples. We extend the variables clustering methodology by two new approaches, one based on the combination of different association measures and the other on distance correlation. With simulation studies we evaluate and compare different clustering strategies. Applying specific methods for mixed-type data proves to be comparable and in many cases beneficial as compared to standard approaches applied to corresponding quantitative or binarized data. Our two novel approaches for mixed-type variables show similar or better performance than the existing methods ClustOfVar and bias-corrected mutual information. Further, in contrast to ClustOfVar, our methods provide dissimilarity matrices, which is an advantage, especially for the purpose of visualization. Real data examples aim to give an impression of various kinds of potential applications for the integrative heatmap and other graphical displays based on dissimilarity matrices. We demonstrate that the presented integrative heatmap provides more information than common data displays about the relationship among variables and samples. The described clustering and visualization methods are implemented in our R package CluMix available from https://cran.r-project.org/web/packages/CluMix. PMID:29182671

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

Fully convolutional network with cluster for semantic segmentation

NASA Astrophysics Data System (ADS)

Ma, Xiao; Chen, Zhongbi; Zhang, Jianlin

2018-04-01

At present, image semantic segmentation technology has been an active research topic for scientists in the field of computer vision and artificial intelligence. Especially, the extensive research of deep neural network in image recognition greatly promotes the development of semantic segmentation. This paper puts forward a method based on fully convolutional network, by cluster algorithm k-means. The cluster algorithm using the image's low-level features and initializing the cluster centers by the super-pixel segmentation is proposed to correct the set of points with low reliability, which are mistakenly classified in great probability, by the set of points with high reliability in each clustering regions. This method refines the segmentation of the target contour and improves the accuracy of the image segmentation.

Remote sensing techniques applied to multispectral recognition of the Aranjuez pilot zone

NASA Technical Reports Server (NTRS)

Lemos, G. L.; Salinas, J.; Rebollo, M.

1977-01-01

A rectangular (7 x 14 km) area 40 km S of Madrid was remote-sensed with a three-stage recognition process. Ground truth was established in the first phase, airborne sensing with a multispectral scanner and photographic cameras were used in the second phase, and Landsat satellite data were obtained in the third phase. Agronomic and hydrological photointerpretation problems are discussed. Color, black/white, and labeled areas are displayed for crop recognition in the land-use survey; turbidity, concentrations of pollutants and natural chemicals, and densitometry of the water are considered in the evaluation of water resources.

Control of Lung Inflammation by Microbiome and Peptidoglycan Recognition Protein

DTIC Science & Technology

2017-07-01

AWARD NUMBER: W81XWH-16-1-0230 TITLE: Control of Lung Inflammation by Microbiome and Peptidoglycan Recognition Protein PRINCIPAL INVESTIGATOR...the Army position, policy or decision unless so designated by other documentation. REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188...for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO

DLMS Voice Data Entry.

DTIC Science & Technology

1980-06-01

34 LIST OF ILLUSTRATIONS FIGURE PAGE 1 Block Diagram of DLMS Voice Recognition System .............. S 2 Flowchart of DefaulV...particular are a speech preprocessor and a minicomputer. In the VRS, as shown in the block diagram of Fig. 1, the preprocessor is a TTI model 8040 and...Data General 6026 Magnetic Zo 4 Tape Unit Display L-- - Equipment Cabinet Fig. 1 block Diagram of DIMS Voice Recognition System qS 2. Flexible Disk

DYNAMIC PATTERN RECOGNITION BY MEANS OF THRESHOLD NETS,

DTIC Science & Technology

A method is expounded for the recognition of visual patterns. A circuit diagram of a device is described which is based on a multilayer threshold ...structure synthesized in accordance with the proposed method. Coded signals received each time an image is displayed are transmitted to the threshold ...circuit which distinguishes the signs, and from there to the layers of threshold resolving elements. The image at each layer is made to correspond

Glycoprotein hormone receptors: determinants in leucine-rich repeats responsible for ligand specificity

PubMed Central

Smits, Guillaume; Campillo, Mercedes; Govaerts, Cédric; Janssens, Véronique; Richter, Christine; Vassart, Gilbert; Pardo, Leonardo; Costagliola, Sabine

2003-01-01

Glycoprotein hormone receptors [thyrotropin (TSHr), luteinizing hormone/chorionic gonadotropin (LH/CGr), follicle stimulating hormone (FSHr)] are rhodopsin-like G protein-coupled receptors with a large extracellular N-terminal portion responsible for hormone recognition and binding. In structural models, this ectodomain is composed of two cysteine clusters flanking nine leucine-rich repeats (LRRs). The LRRs form a succession of β-strands and α-helices organized into a horseshoe-shaped structure. It has been proposed that glycoprotein hormones interact with residues of the β-strands making the concave surface of the horseshoe. Gain-of-function homology scanning of the β-strands of glycoprotein hormone receptors allowed identification of the critical residues responsible for the specificity towards human chorionic gonadotropin (hCG). Substitution of eight or two residues of the LH/CGr into the TSHr or FSHr, respectively, resulted in constructs displaying almost the same affinity and sensitivity for hCG as wild-type LH/CGr. Molecular dynamics simulations and additional site-directed mutagenesis provided a structural rationale for the evolution of binding specificity in this duplicated gene family. PMID:12773385

A visual analytics approach for pattern-recognition in patient-generated data.

PubMed

Feller, Daniel J; Burgermaster, Marissa; Levine, Matthew E; Smaldone, Arlene; Davidson, Patricia G; Albers, David J; Mamykina, Lena

2018-06-13

To develop and test a visual analytics tool to help clinicians identify systematic and clinically meaningful patterns in patient-generated data (PGD) while decreasing perceived information overload. Participatory design was used to develop Glucolyzer, an interactive tool featuring hierarchical clustering and a heatmap visualization to help registered dietitians (RDs) identify associative patterns between blood glucose levels and per-meal macronutrient composition for individuals with type 2 diabetes (T2DM). Ten RDs participated in a within-subjects experiment to compare Glucolyzer to a static logbook format. For each representation, participants had 25 minutes to examine 1 month of diabetes self-monitoring data captured by an individual with T2DM and identify clinically meaningful patterns. We compared the quality and accuracy of the observations generated using each representation. Participants generated 50% more observations when using Glucolyzer (98) than when using the logbook format (64) without any loss in accuracy (69% accuracy vs 62%, respectively, p = .17). Participants identified more observations that included ingredients other than carbohydrates using Glucolyzer (36% vs 16%, p = .027). Fewer RDs reported feelings of information overload using Glucolyzer compared to the logbook format. Study participants displayed variable acceptance of hierarchical clustering. Visual analytics have the potential to mitigate provider concerns about the volume of self-monitoring data. Glucolyzer helped dietitians identify meaningful patterns in self-monitoring data without incurring perceived information overload. Future studies should assess whether similar tools can support clinicians in personalizing behavioral interventions that improve patient outcomes.

Expression intensity, gender and facial emotion recognition: Women recognize only subtle facial emotions better than men.

PubMed

Hoffmann, Holger; Kessler, Henrik; Eppel, Tobias; Rukavina, Stefanie; Traue, Harald C

2010-11-01

Two experiments were conducted in order to investigate the effect of expression intensity on gender differences in the recognition of facial emotions. The first experiment compared recognition accuracy between female and male participants when emotional faces were shown with full-blown (100% emotional content) or subtle expressiveness (50%). In a second experiment more finely grained analyses were applied in order to measure recognition accuracy as a function of expression intensity (40%-100%). The results show that although women were more accurate than men in recognizing subtle facial displays of emotion, there was no difference between male and female participants when recognizing highly expressive stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.

The use of a versatile o-vanilloyl hydrazone ligand to prepare SMM-like Dy3 molecular cluster pair.

PubMed

Xue, Shufang; Zhao, Lang; Guo, Yun-Nan; Zhang, Peng; Tang, Jinkui

2012-09-14

A novel lanthanide molecular cluster pair (MCP), displaying single molecule magnet behaviour, was assembled using the novel o-vanilloyl hydrazone ligand, versatile in terms of denticity, tautomerism and the rotatable C-C bond.

Display of adenoregulin with a novel Pichia pastoris cell surface display system.

PubMed

Ren, Ren; Jiang, Zhengbing; Liu, Meiyun; Tao, Xinyi; Ma, Yushu; Wei, Dongzhi

2007-02-01

Two Pichia pastoris cell surface display vectors were constructed. The vectors consisted of the flocculation functional domain of Flo1p with its own secretion signal sequence or the alpha-factor secretion signal sequence, a polyhistidine (6xHis) tag for detection, an enterokinase recognition site, and the insertion sites for target proteins. Adenoregulin (ADR) is a 33-amino-acid antimicrobial peptide isolated from Phyllomedusa bicolor skin. The ADR was expressed and displayed on the Pichia pastoris KM71 cell surface with the system reported. The displayed recombinant ADR fusion protein was detected by fluorescence microscopy and confocal laser scanning microscopy (CLSM). The antimicrobial activity of the recombinant adenoregulin was detected after proteolytic cleavage of the fusion protein on cell surface. The validity of the Pichia pastoris cell surface display vectors was proved by the displayed ADR.

Pattern recognition approach to the subsequent event of damaging earthquakes in Italy

NASA Astrophysics Data System (ADS)

Gentili, S.; Di Giovambattista, R.

2017-05-01

In this study, we investigate the occurrence of large aftershocks following the most significant earthquakes that occurred in Italy after 1980. In accordance with previous studies (Vorobieva and Panza, 1993; Vorobieva, 1999), we group clusters associated with mainshocks into two categories: ;type A; if, given a main shock of magnitude M, the subsequent strongest earthquake in the cluster has magnitude ≥M - 1 or type B otherwise. In this paper, we apply a pattern recognition approach using statistical features to foresee the class of the analysed clusters. The classification of the two categories is based on some features of the time, space, and magnitude distribution of the aftershocks. Specifically, we analyse the temporal evolution of the radiated energy at different elapsed times after the mainshock, the spatio-temporal evolution of the aftershocks occurring within a few days, and the probability of a strong earthquake. An attempt is made to classify the studied region into smaller seismic zones with a prevalence of type A and B clusters. We demonstrate that the two types of clusters have distinct preferred geographic locations inside the Italian territory that likely reflected key properties of the deforming regions, different crustal domains and faulting style. We use decision trees as classifiers of single features to characterize the features depending on the cluster type. The performance of the classification is tested by the Leave-One-Out method. The analysis is performed on different time-spans after the mainshock to simulate the dependence of the accuracy on the information available as data increased over a longer period with increasing time after the mainshock.

Application of affinity propagation algorithm based on manifold distance for transformer PD pattern recognition

NASA Astrophysics Data System (ADS)

Wei, B. G.; Huo, K. X.; Yao, Z. F.; Lou, J.; Li, X. Y.

2018-03-01

It is one of the difficult problems encountered in the research of condition maintenance technology of transformers to recognize partial discharge (PD) pattern. According to the main physical characteristics of PD, three models of oil-paper insulation defects were set up in laboratory to study the PD of transformers, and phase resolved partial discharge (PRPD) was constructed. By using least square method, the grey-scale images of PRPD were constructed and features of each grey-scale image were 28 box dimensions and 28 information dimensions. Affinity propagation algorithm based on manifold distance (AP-MD) for transformers PD pattern recognition was established, and the data of box dimension and information dimension were clustered based on AP-MD. Study shows that clustering result of AP-MD is better than the results of affinity propagation (AP), k-means and fuzzy c-means algorithm (FCM). By choosing different k values of k-nearest neighbor, we find clustering accuracy of AP-MD falls when k value is larger or smaller, and the optimal k value depends on sample size.

Insights into Penicillium roqueforti Morphological and Genetic Diversity

PubMed Central

Gillot, Guillaume; Jany, Jean-Luc; Coton, Monika; Le Floch, Gaétan; Debaets, Stella; Ropars, Jeanne; López-Villavicencio, Manuela; Dupont, Joëlle; Branca, Antoine; Giraud, Tatiana; Coton, Emmanuel

2015-01-01

Fungi exhibit substantial morphological and genetic diversity, often associated with cryptic species differing in ecological niches. Penicillium roqueforti is used as a starter culture for blue-veined cheeses, being responsible for their flavor and color, but is also a common spoilage organism in various foods. Different types of blue-veined cheeses are manufactured and consumed worldwide, displaying specific organoleptic properties. These features may be due to the different manufacturing methods and/or to the specific P. roqueforti strains used. Substantial morphological diversity exists within P. roqueforti and, although not taxonomically valid, several technological names have been used for strains on different cheeses (e.g., P. gorgonzolae, P. stilton). A worldwide P. roqueforti collection from 120 individual blue-veined cheeses and 21 other substrates was analyzed here to determine (i) whether P. roqueforti is a complex of cryptic species, by applying the Genealogical Concordance Phylogenetic Species Recognition criterion (GC-PSR), (ii) whether the population structure assessed using microsatellite markers correspond to blue cheese types, and (iii) whether the genetic clusters display different morphologies. GC-PSR multi-locus sequence analyses showed no evidence of cryptic species. The population structure analysis using microsatellites revealed the existence of highly differentiated populations, corresponding to blue cheese types and with contrasted morphologies. This suggests that the population structure has been shaped by different cheese-making processes or that different populations were recruited for different cheese types. Cheese-making fungi thus constitute good models for studying fungal diversification under recent selection. PMID:26091176

Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

PubMed Central

Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

2013-01-01

Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

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

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

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

2006 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2006 National Award for Smart Growth Achievement Booklet displays the winners of the 2006 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2012 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

012 National Award for Smart Growth Achievement Booklet displays the winners of the 2012 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2010 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2010 National Award for Smart Growth Achievement Booklet displays the winners of the 2010 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2011 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2011 National Award for Smart Growth Achievement Booklet displays the winners of the 2011 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2008 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2008 National Award for Smart Growth Achievement Booklet displays the winners of the 2008 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2003 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2003 National Award for Smart Growth Achievement Booklet displays the winners of the 2003 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2004 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2004 National Award for Smart Growth Achievement Booklet displays the winners of the 2004 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2005 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2005 National Award for Smart Growth Achievement Booklet displays the winners of the 2005 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

2009 National Award for Smart Growth Achievement Booklet

EPA Pesticide Factsheets

2009 National Award for Smart Growth Achievement Booklet displays the winners of the 2009 Smart Growth Achievement Awards along with their projects and accomplishments that earned them this recognition.

Kazakh Traditional Dance Gesture Recognition

NASA Astrophysics Data System (ADS)

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.

Infrared vehicle recognition using unsupervised feature learning based on K-feature

NASA Astrophysics Data System (ADS)

Lin, Jin; Tan, Yihua; Xia, Haijiao; Tian, Jinwen

2018-02-01

Subject to the complex battlefield environment, it is difficult to establish a complete knowledge base in practical application of vehicle recognition algorithms. The infrared vehicle recognition is always difficult and challenging, which plays an important role in remote sensing. In this paper we propose a new unsupervised feature learning method based on K-feature to recognize vehicle in infrared images. First, we use the target detection algorithm which is based on the saliency to detect the initial image. Then, the unsupervised feature learning based on K-feature, which is generated by Kmeans clustering algorithm that extracted features by learning a visual dictionary from a large number of samples without label, is calculated to suppress the false alarm and improve the accuracy. Finally, the vehicle target recognition image is finished by some post-processing. Large numbers of experiments demonstrate that the proposed method has satisfy recognition effectiveness and robustness for vehicle recognition in infrared images under complex backgrounds, and it also improve the reliability of it.

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

Partitioning of the degradation space for OCR training

NASA Astrophysics Data System (ADS)

Barney Smith, Elisa H.; Andersen, Tim

2006-01-01

Generally speaking optical character recognition algorithms tend to perform better when presented with homogeneous data. This paper studies a method that is designed to increase the homogeneity of training data, based on an understanding of the types of degradations that occur during the printing and scanning process, and how these degradations affect the homogeneity of the data. While it has been shown that dividing the degradation space by edge spread improves recognition accuracy over dividing the degradation space by threshold or point spread function width alone, the challenge is in deciding how many partitions and at what value of edge spread the divisions should be made. Clustering of different types of character features, fonts, sizes, resolutions and noise levels shows that edge spread is indeed shown to be a strong indicator of the homogeneity of character data clusters.

Unsupervised pattern recognition methods in ciders profiling based on GCE voltammetric signals.

PubMed

Jakubowska, Małgorzata; Sordoń, Wanda; Ciepiela, Filip

2016-07-15

This work presents a complete methodology of distinguishing between different brands of cider and ageing degrees, based on voltammetric signals, utilizing dedicated data preprocessing procedures and unsupervised multivariate analysis. It was demonstrated that voltammograms recorded on glassy carbon electrode in Britton-Robinson buffer at pH 2 are reproducible for each brand. By application of clustering algorithms and principal component analysis visible homogenous clusters were obtained. Advanced signal processing strategy which included automatic baseline correction, interval scaling and continuous wavelet transform with dedicated mother wavelet, was a key step in the correct recognition of the objects. The results show that voltammetry combined with optimized univariate and multivariate data processing is a sufficient tool to distinguish between ciders from various brands and to evaluate their freshness. Copyright © 2016 Elsevier Ltd. All rights reserved.

BioTextQuest: a web-based biomedical text mining suite for concept discovery.

PubMed

Papanikolaou, Nikolas; Pafilis, Evangelos; Nikolaou, Stavros; Ouzounis, Christos A; Iliopoulos, Ioannis; Promponas, Vasilis J

2011-12-01

BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed. http://biotextquest.biol.ucy.ac.cy vprobon@ucy.ac.cy; iliopj@med.uoc.gr Supplementary data are available at Bioinformatics online.

Adaptive fuzzy leader clustering of complex data sets in pattern recognition

NASA Technical Reports Server (NTRS)

Newton, Scott C.; Pemmaraju, Surya; Mitra, Sunanda

1992-01-01

A modular, unsupervised neural network architecture for clustering and classification of complex data sets is presented. The adaptive fuzzy leader clustering (AFLC) architecture is a hybrid neural-fuzzy system that learns on-line in a stable and efficient manner. The initial classification is performed in two stages: a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from fuzzy C-means system equations for the centroids and the membership values. The AFLC algorithm is applied to the Anderson Iris data and laser-luminescent fingerprint image data. It is concluded that the AFLC algorithm successfully classifies features extracted from real data, discrete or continuous.

Optical character recognition with feature extraction and associative memory matrix

NASA Astrophysics Data System (ADS)

Sasaki, Osami; Shibahara, Akihito; Suzuki, Takamasa

1998-06-01

A method is proposed in which handwritten characters are recognized using feature extraction and an associative memory matrix. In feature extraction, simple processes such as shifting and superimposing patterns are executed. A memory matrix is generated with singular value decomposition and by modifying small singular values. The method is optically implemented with two liquid crystal displays. Experimental results for the recognition of 25 handwritten alphabet characters clearly shows the effectiveness of the method.

Enabling analytical and Modeling Tools for Enhanced Disease Surveillance

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

Dawn K. Manley

2003-04-01

Early detection, identification, and warning are essential to minimize casualties from a biological attack. For covert attacks, sick people are likely to provide the first indication of an attack. An enhanced medical surveillance system that synthesizes distributed health indicator information and rapidly analyzes the information can dramatically increase the number of lives saved. Current surveillance methods to detect both biological attacks and natural outbreaks are hindered by factors such as distributed ownership of information, incompatible data storage and analysis programs, and patient privacy concerns. Moreover, because data are not widely shared, few data mining algorithms have been tested on andmore » applied to diverse health indicator data. This project addressed both integration of multiple data sources and development and integration of analytical tools for rapid detection of disease outbreaks. As a first prototype, we developed an application to query and display distributed patient records. This application incorporated need-to-know access control and incorporated data from standard commercial databases. We developed and tested two different algorithms for outbreak recognition. The first is a pattern recognition technique that searches for space-time data clusters that may signal a disease outbreak. The second is a genetic algorithm to design and train neural networks (GANN) that we applied toward disease forecasting. We tested these algorithms against influenza, respiratory illness, and Dengue Fever data. Through this LDRD in combination with other internal funding, we delivered a distributed simulation capability to synthesize disparate information and models for earlier recognition and improved decision-making in the event of a biological attack. The architecture incorporates user feedback and control so that a user's decision inputs can impact the scenario outcome as well as integrated security and role-based access-control for communicating between distributed data and analytical tools. This work included construction of interfaces to various commercial database products and to one of the data analysis algorithms developed through this LDRD.« less

Molecular cloning and functional characterization of peptidoglycan recognition protein 6 in grass carp Ctenopharyngodon idella.

PubMed

Li, Jun Hua; Yu, Zhang Long; Xue, Na Na; Zou, Peng Fei; Hu, Jing Yu; Nie, P; Chang, Ming Xian

2014-02-01

Peptidoglycan recognition proteins (PGRPs) are pattern recognition molecules of innate immunity. In this study, a long-form PGRP, designated as gcPGRP6, was identified from grass carp Ctenopharyngodon idella. The deduced amino acid sequence of gcPGRP6 is composed of 464 residues with a conserved PGRP domain at the C-terminus. The gcPGRP6 gene consists of four exons and three introns, spacing approximately 2.7 kb of genomic sequence. Phylogenetic analysis demonstrated that gcPGRP6 is clustered closely with zebrafish PGLYRP6, and formed a long-type PGRP subfamily together with PGLYRP2 members identified in teleosts and mammals. Real-time PCR and Western blotting analyses revealed that gcPGRP6 is constitutively expressed in organs/tissues examined, and its expression was significantly induced in liver and intestine of grass carp in response to PGN stimulation and in CIK cells treated with lipoteichoic acid (LTA), polyinosinic polycytidylic acid (Poly I:C) and peptidoglycan (PGN). Immunofluorescence microscopy and Western blotting analyses revealed that gcPGRP6 is effectively secreted to the exterior of CIK cells. The over-expression of gcPGRP6 in CIK cells leads to the activation of NF-κB and the inhibition of intracellular bacterial growth. Moreover, cell lysates from CIK cells transfected with pTurbo-gcPGRP6-GFP plasmid display the binding activity towards Lys-type PGN from Staphylococcus aureus and DAP-type PGN from Bacillus subtilis. Furthermore, proinflammatory cytokine IL-2 and intracellular PGN receptor NOD2 had a significantly increased expression in CIK cells overexpressed with gcPGRP6. It is demonstrated that the PGRP6 in grass carp has a role in binding PGN, in inhibiting the growth of intracellular bacteria, and in activating NF-κB, as well as in regulating innate immune genes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.

Vat, an Amazing Gene Conferring Resistance to Aphids and Viruses They Carry: From Molecular Structure to Field Effects

PubMed Central

Boissot, Nathalie; Schoeny, Alexandra; Vanlerberghe-Masutti, Flavie

2016-01-01

We review half a century of research on Cucumis melo resistance to Aphis gossypii from molecular to field levels. The Vat gene is unique in conferring resistance to both A. gossypii and the viruses it transmits. This double phenotype is aphid clone-dependent and has been observed in 25 melon accessions, mostly from Asia. It is controlled by a cluster of genes including CC-NLR, which has been characterized in detail. Copy-number polymorphisms (for the whole gene and for a domain that stands out in the LLR region) and single-nucleotide polymorphisms have been identified in the Vat cluster. The role of these polymorphisms in plant/aphid interactions remains unclear. The Vat gene structure suggests a functioning with separate recognition and response phases. During the recognition phase, the VAT protein is thought to interact (likely indirectly) with an aphid effector introduced during cell puncture by the aphid. A few hours later, several miRNAs are upregulated in Vat plants. Peroxidase activity increases, and callose and lignin are deposited in the walls of the cells adjacent to the stylet path, disturbing aphid behavior. In aphids feeding on Vat plants, Piwi-interacting RNA-like sequences are abundant and the levels of other miRNAs are modified. At the plant level, resistance to aphids is quantitative (aphids escape the plant and display low rates of reproduction). Resistance to viruses is qualitative and local. Durability of NLR genes is highly variable. A. gossypii clones are adapted to Vat resistance, either by introducing a new effector that interferes with the deployment of plant defenses, or by adapting to the defenses it triggered. Viruses transmitted in a non-persistent manner cannot adapt to Vat resistance. At population level, Vat reduces aphid density and genetic diversity. The durability of Vat resistance to A. gossypii populations depends strongly on the agro-ecosystem, including, in particular, the presence of other cucurbit crops serving as alternative hosts for adapted clones in fall and winter. At the crop level, Vat resistance decreases the intensity of virus epidemics when A. gossypii is the main aphid vector in the crop environment. PMID:27725823

The nonverbal expression of pride: evidence for cross-cultural recognition.

PubMed

Tracy, Jessica L; Robins, Richard W

2008-03-01

The present research tests whether recognition for the nonverbal expression of pride generalizes across cultures. Study 1 provided the first evidence for cross-cultural recognition of pride, demonstrating that the expression generalizes across Italy and the United States. Study 2 found that the pride expression generalizes beyond Western cultures; individuals from a preliterate, highly isolated tribe in Burkina Faso, West Africa, reliably recognized pride, regardless of whether it was displayed by African or American targets. These Burkinabe participants were unlikely to have learned the pride expression through cross-cultural transmission, so their recognition suggests that pride may be a human universal. Studies 3 and 4 used drawn figures to systematically manipulate the ethnicity and gender of targets showing the expression, and demonstrated that pride recognition generalizes across male and female targets of African, Asian, and Caucasian descent. Discussion focuses on the implications of the findings for the universality of the pride expression.

Technological and safety properties display biodiversity among enterococci isolated from two Egyptian cheeses, "Ras" and "Domiati".

PubMed

Malek, Reine; El-Attar, Aisha; Mohamed, Mariam; Anwar, Shimaa; El-Soda, Morsi; Béal, Catherine

2012-02-15

The technological and safety properties of 35 indigenous strains of Enterococcus faecium isolated from two Egyptian cheeses were characterised in order to determine their ability for rational manufacture of diversified and typical dairy products in the Middle East. A great diversity was observed within the 35 strains on the basis of their technological properties. A statistical analysis made it possible to distribute the 35 strains of E. faecium into different groups. Three groups were identified in terms of their acidification activity, measured by the Cinac system: a group of strains that quickly acidified milk, a second that moderately acidified milk, and a last cluster that revealed weak acidification activity. On the basis of texturing properties that were evaluated using a texturometer and a viscometer, a cluster of strains produced viscous and firm gels, a second cluster included fairly viscous, firm and cohesive gels, and a last group generated slightly viscous, but firm and very cohesive gels. By considering the aroma profiles that were determined by gas chromatography coupled with mass spectrometry, four clusters were identified. One cluster displayed a high dimethyl disulfide level, a second group of strains was highly aromatic, a third cluster led to typical "lactic" products, and the last cluster made it possible to obtain low aromatic products. None of the 35 strains proved to be β-haemolytic on the basis of the characterisation of their safety properties. The resistance to 20 antibiotics was assessed by the disc diffusion method. The 35 isolates were sensitive to 12 antibiotics, and among them, one isolate was resistant to only two antibiotics (nalixidic acid and streptomycin). The resistance to eight antibiotics was strain-dependant. Finally, this study demonstrates that some indigenous strains of E. faecium displayed interesting technological properties for cheese manufacture, together with good safety characteristics. They could be useful for the manufacture of typical products in Egypt. Copyright © 2011 Elsevier B.V. All rights reserved.

Emotional facial expressions differentially influence predictions and performance for face recognition.

PubMed

Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

2013-01-01

This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion.

Cluster structure of light nuclei

NASA Astrophysics Data System (ADS)

Iachello, Francesco

2018-02-01

Matter and charge densities of kα structures with k=2 (8Be), k=3 (12C) and k=4 (16O) calculated within the framework of the algebraic cluster model (ACM) are briefly reviewed and explicitly displayed. Their parameters are determined from a comparison with electron scattering data.

A possibilistic approach to clustering

NASA Technical Reports Server (NTRS)

Krishnapuram, Raghu; Keller, James M.

1993-01-01

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Annotation: Development of facial expression recognition from childhood to adolescence: behavioural and neurological perspectives.

PubMed

Herba, Catherine; Phillips, Mary

2004-10-01

Intact emotion processing is critical for normal emotional development. Recent advances in neuroimaging have facilitated the examination of brain development, and have allowed for the exploration of the relationships between the development of emotion processing abilities, and that of associated neural systems. A literature review was performed of published studies examining the development of emotion expression recognition in normal children and psychiatric populations, and of the development of neural systems important for emotion processing. Few studies have explored the development of emotion expression recognition throughout childhood and adolescence. Behavioural studies suggest continued development throughout childhood and adolescence (reflected by accuracy scores and speed of processing), which varies according to the category of emotion displayed. Factors such as sex, socio-economic status, and verbal ability may also affect this development. Functional neuroimaging studies in adults highlight the role of the amygdala in emotion processing. Results of the few neuroimaging studies in children have focused on the role of the amygdala in the recognition of fearful expressions. Although results are inconsistent, they provide evidence throughout childhood and adolescence for the continued development of and sex differences in amygdalar function in response to fearful expressions. Studies exploring emotion expression recognition in psychiatric populations of children and adolescents suggest deficits that are specific to the type of disorder and to the emotion displayed. Results from behavioural and neuroimaging studies indicate continued development of emotion expression recognition and neural regions important for this process throughout childhood and adolescence. Methodological inconsistencies and disparate findings make any conclusion difficult, however. Further studies are required examining the relationship between the development of emotion expression recognition and that of underlying neural systems, in particular subcortical and prefrontal cortical structures. These will inform understanding of the neural bases of normal and abnormal emotional development, and aid the development of earlier interventions for children and adolescents with psychiatric disorders.

Multilingual Data Selection for Low Resource Speech Recognition

DTIC Science & Technology

2016-09-12

Figure 1: Identification of language clusters using scores from an LID system training languages used in the Base and OP1 evaluation periods of the Babel...the posterior scores over frames. For a set of languages that are used to train the lan- guage identification (LID) network, pairs of languages that...which are combined during test time to produce 10 dimensional language 3854 Figure 3: Identification of language clusters using scores from individually

The time course of morphological processing during spoken word recognition in Chinese.

PubMed

Shen, Wei; Qu, Qingqing; Ni, Aiping; Zhou, Junyi; Li, Xingshan

2017-12-01

We investigated the time course of morphological processing during spoken word recognition using the printed-word paradigm. Chinese participants were asked to listen to a spoken disyllabic compound word while simultaneously viewing a printed-word display. Each visual display consisted of three printed words: a semantic associate of the first constituent of the compound word (morphemic competitor), a semantic associate of the whole compound word (whole-word competitor), and an unrelated word (distractor). Participants were directed to detect whether the spoken target word was on the visual display. Results indicated that both the morphemic and whole-word competitors attracted more fixations than the distractor. More importantly, the morphemic competitor began to diverge from the distractor immediately at the acoustic offset of the first constituent, which was earlier than the whole-word competitor. These results suggest that lexical access to the auditory word is incremental and morphological processing (i.e., semantic access to the first constituent) that occurs at an early processing stage before access to the representation of the whole word in Chinese.

Multi-Aircraft Video - Human/Automation Target Recognition Studies: Video Display Size in Unaided Target Acquisition Involving Multiple Videos

DTIC Science & Technology

2008-04-01

Index ( NASA - TLX : Hart & Staveland, 1988), and a Post-Test Questionnaire. Demographic data/Background Questionnaire. This questionnaire was used...very confident). NASA - TLX . The NASA TLX (Hart & Staveland, 1988) is a subjective workload assessment tool. A multidimensional weighting...completed the NASA - TLX . The test trials were randomized across participants and occurred in a counterbalanced order that took into account video display

Minimum Colour Differences Required To Recognise Small Objects On A Colour CRT

NASA Astrophysics Data System (ADS)

Phillips, Peter L.

1985-05-01

Data is required to assist in the assessment, evaluation and optimisation of colour and other displays for both military and general use. A general aim is to develop a mathematical technique to aid optimisation and reduce the amount of expensive hardware development and trials necessary when introducing new displays. The present standards and methods available for evaluating colour differences are known not to apply to the perception of typical objects on a display. Data is required for irregular objects viewed at small angular subtense ((1°) and relating the recognition of form rather than colour matching. Therefore laboratory experiments have been carried out using a computer controlled CRT to measure the threshold colour difference that an observer requires between object and background so that he can discriminate a variety of similar objects. Measurements are included for a variety of background and object colourings. The results are presented in the CIE colorimetric system similar to current standards used by the display engineer. Apart from the characteristic small field tritanopia, the results show that larger colour differences are required for object recognition than those assumed from conventional colour discrimination data. A simple relationship to account for object size and background colour is suggested to aid visual performance assessments and modelling.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Functional characterization of a short peptidoglycan recognition protein, PGRP5 in grass carp Ctenopharyngodon idella.

PubMed

Li, Jun Hua; Chang, Ming Xian; Xue, Na Na; Nie, P

2013-08-01

Peptidoglycan recognition proteins (PGRPs), which are evolutionarily conserved from insects to mammals, recognize bacterial peptidoglycan (PGN) and function in antibacterial innate immunity. In this study, a short-form PGRP, designated as gcPGRP5 was identified from grass carp Ctenopharyngodon idella. The deduced amino acid sequence of gcPGRP5 is composed of 180 residues with a conserved PGRP domain at the C-terminus. The gcPGRP5 gene consists of four exons and three introns, spacing approximately 2.3 kb in genomic sequence. Phylogenetic analysis demonstrated that the gcPGRP5 is clustered with other PGRP-S identified in teleost fish. The gcPGRP5 is constitutively expressed in all organs/tissues examined, and its expression was significantly induced in CIK cells treated with lipoteichoic acid (LTA), polyinosinic polycytidylic acid (Poly I:C) and PGN. Fluorescence analysis showed that gcPGRP5 is distributed in cytoplasm of CIK cells, and cell lysates from CIK cells transfected with pTurbo-gcPGRP5-GFP and ptGFP1-gcPGRP5 plasmids display the binding activity and peptidoglycan-lytic amidase activity toward Lys-PGN from Staphylococcus aureus and Dap-PGN from Bacillus subtilis. Furthermore, heat-shock protein70 (Hsp70), and MyD88, an adaptor molecule in Toll-like receptor pathway, had an increased expression in CIK cells overexpressed with gcPGRP5. It is thus indicated that gcPGRP5 exhibits amidase activity, and also possesses roles in anti-stress, and in Toll-like receptor signaling pathway. Copyright © 2013 Elsevier Ltd. All rights reserved.

Increasing the Runtime Speed of Case-Based Plan Recognition

DTIC Science & Technology

2015-05-01

number of situations that the robot might reasonably be expected to encounter. This requires ef- ficient indexing schemes to ensure that plan retrieval...collection of information if it does not display a currently valid OMB control number . 1. REPORT DATE MAY 2015 2. REPORT TYPE 3. DATES COVERED 00...00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Increasing the Runtime Speed of Case-Based Plan Recognition 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Parallel nucleic acid recognition by the LNA (locked nucleic acid) stereoisomers beta-L-LNA and alpha-D-LNA; studies in the mirror image world.

PubMed

Christensen, Nanna K; Bryld, Torsten; Sørensen, Mads D; Arar, Khalil; Wengel, Jesper; Nielsen, Poul

2004-02-07

Two LNA (locked nucleic acid) stereoisomers (beta-L-LNA and alpha-D-LNA) are evaluated in the mirror-image world, that is by the study of two mixed sequences of LNA and alpha-L-LNA and their L-DNA and L-RNA complements. Both are found to display high-affinity RNA-recognition by the formation of duplexes with parallel strand orientation.

Fluorescence enhancement through the formation of a single-layer two-dimensional supramolecular organic framework and its application in highly selective recognition of picric acid.

PubMed

Zhang, Ying; Zhan, Tian-Guang; Zhou, Tian-You; Qi, Qiao-Yan; Xu, Xiao-Na; Zhao, Xin

2016-06-18

A two-dimensional (2D) supramolecular organic framework (SOF) has been constructed through the co-assembly of a triphenylamine-based building block and cucurbit[8]uril (CB[8]). Fluorescence turn-on of the non-emissive building block was observed upon the formation of the 2D SOF, which displayed highly selective and sensitive recognition of picric acid over a variety of nitroaromatics.

Toward an automated signature recognition toolkit for mission operations

NASA Technical Reports Server (NTRS)

Cleghorn, T.; Laird, P; Perrine, L.; Culbert, C.; Macha, M.; Saul, R.; Hammen, D.; Moebes, T.; Shelton, R.

1994-01-01

Signature recognition is the problem of identifying an event or events from its time series. The generic problem has numerous applications to science and engineering. At NASA's Johnson Space Center, for example, mission control personnel, using electronic displays and strip chart recorders, monitor telemetry data from three-phase electrical buses on the Space Shuttle and maintain records of device activation and deactivation. Since few electrical devices have sensors to indicate their actual status, changes of state are inferred from characteristic current and voltage fluctuations. Controllers recognize these events both by examining the waveform signatures and by listening to audio channels between ground and crew. Recently the authors have developed a prototype system that identifies major electrical events from the telemetry and displays them on a workstation. Eventually the system will be able to identify accurately the signatures of over fifty distinct events in real time, while contending with noise, intermittent loss of signal, overlapping events, and other complications. This system is just one of many possible signature recognition applications in Mission Control. While much of the technology underlying these applications is the same, each application has unique data characteristics, and every control position has its own interface and performance requirements. There is a need, therefore, for CASE tools that can reduce the time to implement a running signature recognition application from months to weeks or days. This paper describes our work to date and our future plans.

The effect of visual and interaction fidelity on spatial cognition in immersive virtual environments.

PubMed

Mania, Katerina; Wooldridge, Dave; Coxon, Matthew; Robinson, Andrew

2006-01-01

Accuracy of memory performance per se is an imperfect reflection of the cognitive activity (awareness states) that underlies performance in memory tasks. The aim of this research is to investigate the effect of varied visual and interaction fidelity of immersive virtual environments on memory awareness states. A between groups experiment was carried out to explore the effect of rendering quality on location-based recognition memory for objects and associated states of awareness. The experimental space, consisting of two interconnected rooms, was rendered either flat-shaded or using radiosity rendering. The computer graphics simulations were displayed on a stereo head-tracked Head Mounted Display. Participants completed a recognition memory task after exposure to the experimental space and reported one of four states of awareness following object recognition. These reflected the level of visual mental imagery involved during retrieval, the familiarity of the recollection, and also included guesses. Experimental results revealed variations in the distribution of participants' awareness states across conditions while memory performance failed to reveal any. Interestingly, results revealed a higher proportion of recollections associated with mental imagery in the flat-shaded condition. These findings comply with similar effects revealed in two earlier studies summarized here, which demonstrated that the less "naturalistic" interaction interface or interface of low interaction fidelity provoked a higher proportion of recognitions based on visual mental images.

Toward an automated signature recognition toolkit for mission operations

NASA Astrophysics Data System (ADS)

Cleghorn, T.; Laird, P.; Perrine, L.; Culbert, C.; Macha, M.; Saul, R.; Hammen, D.; Moebes, T.; Shelton, R.

1994-10-01

Signature recognition is the problem of identifying an event or events from its time series. The generic problem has numerous applications to science and engineering. At NASA's Johnson Space Center, for example, mission control personnel, using electronic displays and strip chart recorders, monitor telemetry data from three-phase electrical buses on the Space Shuttle and maintain records of device activation and deactivation. Since few electrical devices have sensors to indicate their actual status, changes of state are inferred from characteristic current and voltage fluctuations. Controllers recognize these events both by examining the waveform signatures and by listening to audio channels between ground and crew. Recently the authors have developed a prototype system that identifies major electrical events from the telemetry and displays them on a workstation. Eventually the system will be able to identify accurately the signatures of over fifty distinct events in real time, while contending with noise, intermittent loss of signal, overlapping events, and other complications. This system is just one of many possible signature recognition applications in Mission Control. While much of the technology underlying these applications is the same, each application has unique data characteristics, and every control position has its own interface and performance requirements. There is a need, therefore, for CASE tools that can reduce the time to implement a running signature recognition application from months to weeks or days. This paper describes our work to date and our future plans.

X-Eye: a novel wearable vision system

NASA Astrophysics Data System (ADS)

Wang, Yuan-Kai; Fan, Ching-Tang; Chen, Shao-Ang; Chen, Hou-Ye

2011-03-01

This paper proposes a smart portable device, named the X-Eye, which provides a gesture interface with a small size but a large display for the application of photo capture and management. The wearable vision system is implemented with embedded systems and can achieve real-time performance. The hardware of the system includes an asymmetric dualcore processer with an ARM core and a DSP core. The display device is a pico projector which has a small volume size but can project large screen size. A triple buffering mechanism is designed for efficient memory management. Software functions are partitioned and pipelined for effective execution in parallel. The gesture recognition is achieved first by a color classification which is based on the expectation-maximization algorithm and Gaussian mixture model (GMM). To improve the performance of the GMM, we devise a LUT (Look Up Table) technique. Fingertips are extracted and geometrical features of fingertip's shape are matched to recognize user's gesture commands finally. In order to verify the accuracy of the gesture recognition module, experiments are conducted in eight scenes with 400 test videos including the challenge of colorful background, low illumination, and flickering. The processing speed of the whole system including the gesture recognition is with the frame rate of 22.9FPS. Experimental results give 99% recognition rate. The experimental results demonstrate that this small-size large-screen wearable system has effective gesture interface with real-time performance.

Natural 3D content on glasses-free light-field 3D cinema

NASA Astrophysics Data System (ADS)

Balogh, Tibor; Nagy, Zsolt; Kovács, Péter Tamás.; Adhikarla, Vamsi K.

2013-03-01

This paper presents a complete framework for capturing, processing and displaying the free viewpoint video on a large scale immersive light-field display. We present a combined hardware-software solution to visualize free viewpoint 3D video on a cinema-sized screen. The new glasses-free 3D projection technology can support larger audience than the existing autostereoscopic displays. We introduce and describe our new display system including optical and mechanical design considerations, the capturing system and render cluster for producing the 3D content, and the various software modules driving the system. The indigenous display is first of its kind, equipped with front-projection light-field HoloVizio technology, controlling up to 63 MP. It has all the advantages of previous light-field displays and in addition, allows a more flexible arrangement with a larger screen size, matching cinema or meeting room geometries, yet simpler to set-up. The software system makes it possible to show 3D applications in real-time, besides the natural content captured from dense camera arrangements as well as from sparse cameras covering a wider baseline. Our software system on the GPU accelerated render cluster, can also visualize pre-recorded Multi-view Video plus Depth (MVD4) videos on this light-field glasses-free cinema system, interpolating and extrapolating missing views.

A pattern recognition approach to transistor array parameter variance

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Fuzzy Set Methods for Object Recognition in Space Applications

NASA Technical Reports Server (NTRS)

Keller, James M. (Editor)

1992-01-01

Progress on the following four tasks is described: (1) fuzzy set based decision methodologies; (2) membership calculation; (3) clustering methods (including derivation of pose estimation parameters), and (4) acquisition of images and testing of algorithms.

Inattentional blindness increased with augmented reality surgical navigation.

PubMed

Dixon, Benjamin J; Daly, Michael J; Chan, Harley H L; Vescan, Allan; Witterick, Ian J; Irish, Jonathan C

2014-01-01

Augmented reality (AR) surgical navigation systems, designed to increase accuracy and efficiency, have been shown to negatively impact on attention. We wished to assess the effect "head-up" AR displays have on attention, efficiency, and accuracy, while performing a surgical task, compared with the same information being presented on a submonitor (SM). Fifty experienced otolaryngology surgeons (n = 42) and senior otolaryngology trainees (n = 8) performed an endoscopic surgical navigation exercise on a predissected cadaveric model. Computed tomography-generated anatomic contours were fused with the endoscopic image to provide an AR view. Subjects were randomized to perform the task with a standard endoscopic monitor with the AR navigation displayed on an SM or with AR as a single display. Accuracy, task completion time, and the recognition of unexpected findings (a foreign body and a critical complication) were recorded. Recognition of the foreign body was significantly better in the SM group (15/25 [60%]) compared with the AR alone group (8/25 [32%]; p = 0.02). There was no significant difference in task completion time (p = 0.83) or accuracy (p = 0.78) between the two groups. Providing identical surgical navigation on a SM, rather than on a single head-up display, reduced the level of inattentional blindness as measured by detection of unexpected findings. These gains were achieved without any measurable impact on efficiency or accuracy. AR displays may distract the user and we caution injudicious adoption of this technology for medical procedures.

State Recognition and Visualization of Hoisting Motor of Quayside Container Crane Based on SOFM

NASA Astrophysics Data System (ADS)

Yang, Z. Q.; He, P.; Tang, G.; Hu, X.

2017-07-01

The neural network structure and algorithm of self-organizing feature map (SOFM) are researched and analysed. The method is applied to state recognition and visualization of the quayside container crane hoisting motor. By using SOFM, the clustering and visualization of attribute reduction of data are carried out, and three kinds motor states are obtained with Root Mean Square(RMS), Impulse Index and Margin Index, and the simulation visualization interface is realized by MATLAB. Through the processing of the sample data, it can realize the accurate identification of the motor state, thus provide better monitoring of the quayside container crane hoisting motor and a new way for the mechanical state recognition.

Characterizing the spatio-temporal dynamics of the neural events occurring prior to and up to overt recognition of famous faces.

PubMed

Jemel, Boutheina; Schuller, Anne-Marie; Goffaux, Valérie

2010-10-01

Although it is generally acknowledged that familiar face recognition is fast, mandatory, and proceeds outside conscious control, it is still unclear whether processes leading to familiar face recognition occur in a linear (i.e., gradual) or a nonlinear (i.e., all-or-none) manner. To test these two alternative accounts, we recorded scalp ERPs while participants indicated whether they recognize as familiar the faces of famous and unfamiliar persons gradually revealed in a descending sequence of frames, from the noisier to the least noisy. This presentation procedure allowed us to characterize the changes in scalp ERP responses occurring prior to and up to overt recognition. Our main finding is that gradual and all-or-none processes are possibly involved during overt recognition of familiar faces. Although the N170 and the N250 face-sensitive responses displayed an abrupt activity change at the moment of overt recognition of famous faces, later ERPs encompassing the N400 and late positive component exhibited an incremental increase in amplitude as the point of recognition approached. In addition, famous faces that were not overtly recognized at one trial before recognition elicited larger ERP potentials than unfamiliar faces, probably reflecting a covert recognition process. Overall, these findings present evidence that recognition of familiar faces implicates spatio-temporally complex neural processes exhibiting differential pattern activity changes as a function of recognition state.

15 CFR 922.164 - Additional activity regulations by Sanctuary area.

Code of Federal Regulations, 2012 CFR

2012-01-01

...-access buffer” zone or as “closed”, and allowing instant, long-range recognition by boaters. Such signs shall display the official logo of the Sanctuary. (2) The following activities are prohibited within the...

15 CFR 922.164 - Additional activity regulations by Sanctuary area.

Code of Federal Regulations, 2014 CFR

2014-01-01

...-access buffer” zone or as “closed”, and allowing instant, long-range recognition by boaters. Such signs shall display the official logo of the Sanctuary. (2) The following activities are prohibited within the...

15 CFR 922.164 - Additional activity regulations by Sanctuary area.

Code of Federal Regulations, 2013 CFR

2013-01-01

...-access buffer” zone or as “closed”, and allowing instant, long-range recognition by boaters. Such signs shall display the official logo of the Sanctuary. (2) The following activities are prohibited within the...

An Annotated Bibliography on Tactical Map Display Symbology

DTIC Science & Technology

1989-08-01

failure of attention to be focused on one element selectively in filtering tasks where only that one element was relevant to the discrimination. Failure of...The present study evaluates a class of models of human information processing made popular by Broadbent . A brief tachistoscopic display of one or two...213-219. Two experiments were performed to test Neisser’s two-stage model of recognition as applied to matching. Evidence of parallel processing was

Human recognition based on head-shoulder contour extraction and BP neural network

NASA Astrophysics Data System (ADS)

Kong, Xiao-fang; Wang, Xiu-qin; Gu, Guohua; Chen, Qian; Qian, Wei-xian

2014-11-01

In practical application scenarios like video surveillance and human-computer interaction, human body movements are uncertain because the human body is a non-rigid object. Based on the fact that the head-shoulder part of human body can be less affected by the movement, and will seldom be obscured by other objects, in human detection and recognition, a head-shoulder model with its stable characteristics can be applied as a detection feature to describe the human body. In order to extract the head-shoulder contour accurately, a head-shoulder model establish method with combination of edge detection and the mean-shift algorithm in image clustering has been proposed in this paper. First, an adaptive method of mixture Gaussian background update has been used to extract targets from the video sequence. Second, edge detection has been used to extract the contour of moving objects, and the mean-shift algorithm has been combined to cluster parts of target's contour. Third, the head-shoulder model can be established, according to the width and height ratio of human head-shoulder combined with the projection histogram of the binary image, and the eigenvectors of the head-shoulder contour can be acquired. Finally, the relationship between head-shoulder contour eigenvectors and the moving objects will be formed by the training of back-propagation (BP) neural network classifier, and the human head-shoulder model can be clustered for human detection and recognition. Experiments have shown that the method combined with edge detection and mean-shift algorithm proposed in this paper can extract the complete head-shoulder contour, with low calculating complexity and high efficiency.

True 3D display and BeoWulf connectivity

NASA Astrophysics Data System (ADS)

Jannson, Tomasz P.; Kostrzewski, Andrew A.; Kupiec, Stephen A.; Yu, Kevin H.; Aye, Tin M.; Savant, Gajendra D.

2003-09-01

We propose a novel true 3-D display based on holographic optics, called HAD (Holographic Autostereoscopic Display), or Holographic Inverse Look-around and Autostereoscopic Reality (HILAR), its latest generation. It does not require goggles, unlike the state of the art 3-D system which do not work without goggles, and has a table-like 360° look-around capability. Also, novel 3-D image-rendering software, based on Beowulf PC cluster hardware is discussed.

Game engines and immersive displays

NASA Astrophysics Data System (ADS)

Chang, Benjamin; Destefano, Marc

2014-02-01

While virtual reality and digital games share many core technologies, the programming environments, toolkits, and workflows for developing games and VR environments are often distinct. VR toolkits designed for applications in visualization and simulation often have a different feature set or design philosophy than game engines, while popular game engines often lack support for VR hardware. Extending a game engine to support systems such as the CAVE gives developers a unified development environment and the ability to easily port projects, but involves challenges beyond just adding stereo 3D visuals. In this paper we outline the issues involved in adapting a game engine for use with an immersive display system including stereoscopy, tracking, and clustering, and present example implementation details using Unity3D. We discuss application development and workflow approaches including camera management, rendering synchronization, GUI design, and issues specific to Unity3D, and present examples of projects created for a multi-wall, clustered, stereoscopic display.

Astroglial CB1 Receptors Determine Synaptic D-Serine Availability to Enable Recognition Memory.

PubMed

Robin, Laurie M; Oliveira da Cruz, José F; Langlais, Valentin C; Martin-Fernandez, Mario; Metna-Laurent, Mathilde; Busquets-Garcia, Arnau; Bellocchio, Luigi; Soria-Gomez, Edgar; Papouin, Thomas; Varilh, Marjorie; Sherwood, Mark W; Belluomo, Ilaria; Balcells, Georgina; Matias, Isabelle; Bosier, Barbara; Drago, Filippo; Van Eeckhaut, Ann; Smolders, Ilse; Georges, Francois; Araque, Alfonso; Panatier, Aude; Oliet, Stéphane H R; Marsicano, Giovanni

2018-06-06

Bidirectional communication between neurons and astrocytes shapes synaptic plasticity and behavior. D-serine is a necessary co-agonist of synaptic N-methyl-D-aspartate receptors (NMDARs), but the physiological factors regulating its impact on memory processes are scantly known. We show that astroglial CB 1 receptors are key determinants of object recognition memory by determining the availability of D-serine at hippocampal synapses. Mutant mice lacking CB 1 receptors from astroglial cells (GFAP-CB 1 -KO) displayed impaired object recognition memory and decreased in vivo and in vitro long-term potentiation (LTP) at CA3-CA1 hippocampal synapses. Activation of CB 1 receptors increased intracellular astroglial Ca 2+ levels and extracellular levels of D-serine in hippocampal slices. Accordingly, GFAP-CB 1 -KO displayed lower occupancy of the co-agonist binding site of synaptic hippocampal NMDARs. Finally, elevation of D-serine levels fully rescued LTP and memory impairments of GFAP-CB 1 -KO mice. These data reveal a novel mechanism of in vivo astroglial control of memory and synaptic plasticity via the D-serine-dependent control of NMDARs. Copyright © 2018 Elsevier Inc. All rights reserved.

Perceiving patterns of play in dynamic sport tasks: investigating the essential information underlying skilled performance.

PubMed

Willams, A Mark; Hodges, Nicola J; North, Jamie S; Barton, Gabor

2006-01-01

The perceptual-cognitive information used to support pattern-recognition skill in soccer was examined. In experiment 1, skilled players were quicker and more accurate than less-skilled players at recognising familiar and unfamiliar soccer action sequences presented on film. In experiment 2, these action sequences were converted into point-light displays, with superficial display features removed and the positions of players and the relational information between them made more salient. Skilled players were more accurate than less-skilled players in recognising sequences presented in point-light form, implying that each pattern of play can be defined by the unique relations between players. In experiment 3, various offensive and defensive players were occluded for the duration of each trial in an attempt to identify the most important sources of information underpinning successful performance. A decrease in response accuracy was observed under occluded compared with non-occluded conditions and the expertise effect was no longer observed. The relational information between certain key players, team-mates and their defensive counterparts may provide the essential information for effective pattern-recognition skill in soccer. Structural feature analysis, temporal phase relations, and knowledge-based information are effectively integrated to facilitate pattern recognition in dynamic sport tasks.

Age-congruency and contact effects in body expression recognition from point-light displays (PLD)

PubMed Central

Hermens, Frouke; Willmott, Alexander P.

2016-01-01

Recognition of older people’s body expressions is a crucial social skill. We here investigate how age, not just of the observer, but also of the observed individual, affects this skill. Age may influence the ability to recognize other people’s body expressions by changes in one’s own ability to perform certain action over the life-span (i.e., an own-age bias may occur, with best recognition for one’s own age). Whole body point light displays of children, young adults and older adults (>70 years) expressing six different emotions were presented to observers of the same three age-groups. Across two variations of the paradigm, no evidence for the predicted own-age bias (a cross-over interaction between one’s own age and the observed person’s age) was found. Instead, experience effects were found with children better recognizing older actors’ expressions of ‘active emotions,’ such as anger and happiness with greater exposure in daily life. Together, the findings suggest that age-related changes in one own’s mobility only influences body expression categorization in young children who interact frequently with older adults. PMID:27994986

Reconciling change blindness with long-term memory for objects.

PubMed

Wood, Katherine; Simons, Daniel J

2017-02-01

How can we reconcile remarkably precise long-term memory for thousands of images with failures to detect changes to similar images? We explored whether people can use detailed, long-term memory to improve change detection performance. Subjects studied a set of images of objects and then performed recognition and change detection tasks with those images. Recognition memory performance exceeded change detection performance, even when a single familiar object in the postchange display consistently indicated the change location. In fact, participants were no better when a familiar object predicted the change location than when the displays consisted of unfamiliar objects. When given an explicit strategy to search for a familiar object as a way to improve performance on the change detection task, they performed no better than in a 6-alternative recognition memory task. Subjects only benefited from the presence of familiar objects in the change detection task when they had more time to view the prechange array before it switched. Once the cost to using the change detection information decreased, subjects made use of it in conjunction with memory to boost performance on the familiar-item change detection task. This suggests that even useful information will go unused if it is sufficiently difficult to extract.

Harlequin color change after abdominal paracentesis in a newborn with neonatal hemochromatosis.

PubMed

Cizmeci, Mehmet N; Alagoz, Demet; Avsar, Mehmet I; Alis, Gulten; Tutanc, Murat

2014-01-01

Harlequin color change is a distinctive cutaneous phenomenon presenting as a well-demarcated color change, with half of the body displaying erythema and the other half pallor. Only a few cases have been reported, possibly because of under-recognition. Recognition of this benign, self-limited condition may enable physicians to avoid unnecessary interventions. Herein we describe a neonate with nonimmune hydrops fetalis due to neonatal hemochromatosis who developed Harlequin color change after abdominal paracentesis. © 2014 Wiley Periodicals, Inc.

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

PubMed

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

2016-01-01

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

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Younger and Older Users’ Recognition of Virtual Agent Facial Expressions

PubMed Central

Beer, Jenay M.; Smarr, Cory-Ann; Fisk, Arthur D.; Rogers, Wendy A.

2015-01-01

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent’s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell, Sullivan, Prevost, & Churchill, 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck & Reichenbach, 2005; Courgeon et al. 2009; 2011; Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent’s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a possible explanation for age-related differences in emotion recognition. First, our findings show age-related differences in the recognition of emotions expressed by a virtual agent, with older adults showing lower recognition for the emotions of anger, disgust, fear, happiness, sadness, and neutral. These age-related difference might be explained by older adults having difficulty discriminating similarity in configural arrangement of facial features for certain emotions; for example, older adults often mislabeled the similar emotions of fear as surprise. Second, our results did not provide evidence for the dynamic formation improving emotion recognition; but, in general, the intensity of the emotion improved recognition. Lastly, we learned that emotion recognition, for older and younger adults, differed by character type, from best to worst: human, synthetic human, and then iCat. Our findings provide guidance for design, as well as the development of a framework of age-related differences in emotion recognition. PMID:25705105

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

NASA Astrophysics Data System (ADS)

Lai, King C.; Evans, James W.; Liu, Da-Jiang

2017-11-01

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, DN ˜ N-β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for "perfect" sizes Np = L2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for Np+3, Np+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes Np+1 and Np+2. DN versus N oscillates strongly between the slowest branch (for Np+3) and the fastest branch (for Np+1). All branches merge for N = O(102), but macroscale behavior is only achieved for much larger N = O(103). This analysis reveals the unprecedented diversity of behavior on the nanoscale.

Characterization of edible seaweed harvested on the Galician coast (northwestern Spain) using pattern recognition techniques and major and trace element data.

PubMed

Romarís-Hortas, Vanessa; García-Sartal, Cristina; Barciela-Alonso, María Carmen; Moreda-Piñeiro, Antonio; Bermejo-Barrera, Pilar

2010-02-10

Major and trace elements in North Atlantic seaweed originating from Galicia (northwestern Spain) were determined by using inductively coupled plasma-optical emission spectrometry (ICP-OES) (Ba, Ca, Cu, K, Mg, Mn, Na, Sr, and Zn), inductively coupled plasma-mass spectrometry (ICP-MS) (Br and I) and hydride generation-atomic fluorescence spectrometry (HG-AFS) (As). Pattern recognition techniques were then used to classify the edible seaweed according to their type (red, brown, and green seaweed) and also their variety (Wakame, Fucus, Sea Spaghetti, Kombu, Dulse, Nori, and Sea Lettuce). Principal component analysis (PCA) and cluster analysis (CA) were used as exploratory techniques, and linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA) were used as classification procedures. In total, t12 elements were determined in a range of 35 edible seaweed samples (20 brown seaweed, 10 red seaweed, 4 green seaweed, and 1 canned seaweed). Natural groupings of the samples (brown, red, and green types) were observed using PCA and CA (squared Euclidean distance between objects and Ward method as clustering procedure). The application of LDA gave correct assignation percentages of 100% for brown, red, and green types at a significance level of 5%. However, a satisfactory classification (recognition and prediction) using SIMCA was obtained only for red seaweed (100% of cases correctly classified), whereas percentages of 89 and 80% were obtained for brown seaweed for recognition (training set) and prediction (testing set), respectively.

Bringing an Ecological Perspective to the Study of Aging and Recognition of Emotional Facial Expressions: Past, Current, and Future Methods

PubMed Central

Isaacowitz, Derek M.; Stanley, Jennifer Tehan

2011-01-01

Older adults perform worse on traditional tests of emotion recognition accuracy than do young adults. In this paper, we review descriptive research to date on age differences in emotion recognition from facial expressions, as well as the primary theoretical frameworks that have been offered to explain these patterns. We propose that this is an area of inquiry that would benefit from an ecological approach in which contextual elements are more explicitly considered and reflected in experimental methods. Use of dynamic displays and examination of specific cues to accuracy, for example, may reveal more nuanced age-related patterns and may suggest heretofore unexplored underlying mechanisms. PMID:22125354

High throughput profile-profile based fold recognition for the entire human proteome.

PubMed

McGuffin, Liam J; Smith, Richard T; Bryson, Kevin; Sørensen, Søren-Aksel; Jones, David T

2006-06-07

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

A Photon Interference Detector with Continuous Display.

ERIC Educational Resources Information Center

Gilmore, R. S.

1978-01-01

Describes an apparatus which attempts to give a direct visual impression of the random detection of individual photons coupled with the recognition of the classical intensity distribution as a result of fairly high proton statistics. (Author/GA)

Music causes deterioration of source memory: evidence from normal ageing.

PubMed

El Haj, Mohamad; Omigie, Diana; Clément, Sylvain

2014-01-01

Previous research has shown that music exposure can impair a wide variety of cognitive and behavioural performance. We investigated whether this is the case for source memory. Forty-one younger adults and 35 healthy elderly were required to retain the location in which pictures of coloured objects were displayed. On a subsequent recognition test they were required to decide whether the objects were displayed in the same location as before or not. Encoding took place (a) in silence, (b) while listening to street noise, or (c) while listening to Vivaldi's "Four Seasons". Recognition always took place during silence. A significant reduction in source memory was observed following music exposure, a reduction that was more pronounced for older adults than for younger adults. This pattern was significantly correlated with performance on an executive binding task. The exposure to music appeared to interfere with binding in working memory, worsening source recall.

The relation between the mass-to-light ratio and the relaxation state of globular clusters

NASA Astrophysics Data System (ADS)

Bianchini, P.; Sills, A.; van de Ven, G.; Sippel, A. C.

2017-08-01

The internal dynamics of globular clusters (GCs) is strongly affected by two-body interactions that bring the systems to a state of partial energy equipartition. Using a set of Monte Carlo clusters simulations, we investigate the role of the onset of energy equipartition in shaping the mass-to-light ratio (M/L) in GCs. Our simulations show that the M/L profiles cannot be considered constant and their specific shape strongly depends on the dynamical age of the clusters. Dynamically younger clusters display a central peak up to M/L ≃ 25 M⊙/L⊙ caused by the retention of dark remnants; this peak flattens out for dynamically older clusters. Moreover, we find that also the global values of M/L correlate with the dynamical state of a cluster quantified as either the number of relaxation times a system has experienced nrel or the equipartition parameter meq: clusters closer to full equipartition (higher nrel or lower meq) display a lower M/L. We show that the decrease of M/L is primarily driven by the dynamical ejection of dark remnants, rather than by the escape of low-mass stars. The predictions of our models are in good agreement with observations of GCs in the Milky Way and M31, indicating that differences in relaxation state alone can explain variations of M/L up to a factor of ≃3. Our characterization of the M/L as a function of relaxation state is of primary relevance for the application and interpretation of dynamical models.

Processing environmental stimuli in paranoid schizophrenia: recognizing facial emotions and performing executive functions.

PubMed

Yu, Shao Hua; Zhu, Jun Peng; Xu, You; Zheng, Lei Lei; Chai, Hao; He, Wei; Liu, Wei Bo; Li, Hui Chun; Wang, Wei

2012-12-01

To study the contribution of executive function to abnormal recognition of facial expressions of emotion in schizophrenia patients. Abnormal recognition of facial expressions of emotion was assayed according to Japanese and Caucasian facial expressions of emotion (JACFEE), Wisconsin card sorting test (WCST), positive and negative symptom scale, and Hamilton anxiety and depression scale, respectively, in 88 paranoid schizophrenia patients and 75 healthy volunteers. Patients scored higher on the Positive and Negative Symptom Scale and the Hamilton Anxiety and Depression Scales, displayed lower JACFEE recognition accuracies and poorer WCST performances. The JACFEE recognition accuracy of contempt and disgust was negatively correlated with the negative symptom scale score while the recognition accuracy of fear was positively with the positive symptom scale score and the recognition accuracy of surprise was negatively with the general psychopathology score in patients. Moreover, the WCST could predict the JACFEE recognition accuracy of contempt, disgust, and sadness in patients, and the perseverative errors negatively predicted the recognition accuracy of sadness in healthy volunteers. The JACFEE recognition accuracy of sadness could predict the WCST categories in paranoid schizophrenia patients. Recognition accuracy of social-/moral emotions, such as contempt, disgust and sadness is related to the executive function in paranoid schizophrenia patients, especially when regarding sadness. Copyright © 2012 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

Partner-Drug Resistance and Population Substructuring of Artemisinin-Resistant Plasmodium falciparum in Cambodia

PubMed Central

Parobek, Christian M.; Parr, Jonathan B.; Brazeau, Nicholas F.; Lon, Chanthap; Chaorattanakawee, Suwanna; Gosi, Panita; Barnett, Eric J.; Norris, Lauren D.; Meshnick, Steven R.; Spring, Michele D.; Lanteri, Charlotte A.; Bailey, Jeffrey A.; Saunders, David L.; Lin, Jessica T.

2017-01-01

Abstract Plasmodium falciparum in western Cambodia has developed resistance to artemisinin and its partner drugs, causing frequent treatment failure. Understanding this evolution can inform the deployment of new therapies. We investigated the genetic architecture of 78 falciparum isolates using whole-genome sequencing, correlating results to in vivo and ex vivo drug resistance and exploring the relationship between population structure, demographic history, and partner drug resistance. Principle component analysis, network analysis and demographic inference identified a diverse central population with three clusters of clonally expanding parasite populations, each associated with specific K13 artemisinin resistance alleles and partner drug resistance profiles which were consistent with the sequential deployment of artemisinin combination therapies in the region. One cluster displayed ex vivo piperaquine resistance and mefloquine sensitivity with a high rate of in vivo failure of dihydroartemisinin-piperaquine. Another cluster displayed ex vivo mefloquine resistance and piperaquine sensitivity with high in vivo efficacy of dihydroartemisinin-piperaquine. The final cluster was clonal and displayed intermediate sensitivity to both drugs. Variations in recently described piperaquine resistance markers did not explain the difference in mean IC90 or clinical failures between the high and intermediate piperaquine resistance groups, suggesting additional loci may be involved in resistance. The results highlight an important role for partner drug resistance in shaping the P. falciparum genetic landscape in Southeast Asia and suggest that further work is needed to evaluate for other mutations that drive piperaquine resistance. PMID:28854635

A Genomic Survey of SCPP Family Genes in Fishes Provides Novel Insights into the Evolution of Fish Scales.

PubMed

Lv, Yunyun; Kawasaki, Kazuhiko; Li, Jia; Li, Yanping; Bian, Chao; Huang, Yu; You, Xinxin; Shi, Qiong

2017-11-16

The family of secretory calcium-binding phosphoproteins (SCPPs) have been considered vital to skeletal tissue mineralization. However, most previous SCPP studies focused on phylogenetically distant animals but not on those closely related species. Here we provide novel insights into the coevolution of SCPP genes and fish scales in 10 species from Otophysi . According to their scale phenotypes, these fishes can be divided into three groups, i.e., scaled, sparsely scaled, and scaleless. We identified homologous SCPP genes in the genomes of these species and revealed an absence of some SCPP members in some genomes, suggesting an uneven evolutionary history of SCPP genes in fishes. In addition, most of these SCPP genes, with the exception of SPP1 , individually form one or two gene cluster(s) on each corresponding genome. Furthermore, we constructed phylogenetic trees using maximum likelihood method to estimate their evolution. The phylogenetic topology mostly supports two subclasses in some species, such as Cyprinus carpio , Sinocyclocheilus anshuiensis , S. grahamin , and S. rhinocerous , but not in the other examined fishes. By comparing the gene structures of recently reported candidate genes, SCPP1 and SCPP5 , for determining scale phenotypes, we found that the hypothesis is suitable for Astyanax mexicanus , but denied by S. anshuiensis , even though they are both sparsely scaled for cave adaptation. Thus, we conclude that, although different fish species display similar scale phenotypes, the underlying genetic changes however might be diverse. In summary, this paper accelerates the recognition of the SCPP family in teleosts for potential scale evolution.

Multifunctional Metal-Organic Frameworks Based on Redox-Active Rhenium Octahedral Clusters.

PubMed

Litvinova, Yulia M; Gayfulin, Yakov M; Kovalenko, Konstantin A; Samsonenko, Denis G; van Leusen, Jan; Korolkov, Ilya V; Fedin, Vladimir P; Mironov, Yuri V

2018-02-19

The redox-active rhenium octahedral cluster unit [Re 6 Se 8 (CN) 6 ] 4- was combined with Gd 3+ ions and dicarboxylate linkers in novel types of metal-organic frameworks (MOFs) that display a set of functional properties. The hydrolytically stable complexes [{Gd(H 2 O) 3 } 2 (L)Re 6 Se 8 (CN) 6 ]·nH 2 O (1, L = furan-2,5-dicarboxylate, fdc; 2, L = thiophene-2,5-dicarboxylate, tdc) exhibit a 3D framework of trigonal symmetry where 1D chains of [{Gd(H 2 O) 3 } 2 (L)] 4+ are connected by [Re 6 Se 8 (CN) 6 ] 4- clusters. Frameworks contain spacious channels filled with H 2 O. Solvent molecules can be easily removed under vacuum to produce permanently porous solids with high volumetric CO 2 uptake and remarkable CO 2 /N 2 selectivity at room temperature. The frameworks demonstrate an ability for reversible redox transformations of the cluster fragment. The orange powders of compounds 1 and 2 react with Br 2 , yielding dark-green powders of [{Gd(H 2 O) 3 } 2 (L)Re 6 Se 8 (CN) 6 ]Br·nH 2 O (3, L = fdc; 4, L = tdc). Compounds 3 and 4 are isostructural with 1 and 2 and also have permanently porous frameworks but display different optical, magnetic, and sorption properties. In particular, oxidation of the cluster fragment "switches off" its luminescence in the red region, and the incorporation of Br - leads to a decrease of the solvent-accessible volume in the channels of 3 and 4. Finally, the green powders of 3 and 4 can be reduced back to the orange powders of 1 and 2 by reaction with hydrazine, thus displaying a rare ability for fully reversible chemical redox transitions. Compounds 1-4 are mentioned as a new class of redox-active cluster-based MOFs with potential usage as multifunctional materials for gas separation and chemical contamination sensors.

Exploratory visualization of astronomical data on ultra-high-resolution wall displays

NASA Astrophysics Data System (ADS)

Pietriga, Emmanuel; del Campo, Fernando; Ibsen, Amanda; Primet, Romain; Appert, Caroline; Chapuis, Olivier; Hempel, Maren; Muñoz, Roberto; Eyheramendy, Susana; Jordan, Andres; Dole, Hervé

2016-07-01

Ultra-high-resolution wall displays feature a very high pixel density over a large physical surface, which makes them well-suited to the collaborative, exploratory visualization of large datasets. We introduce FITS-OW, an application designed for such wall displays, that enables astronomers to navigate in large collections of FITS images, query astronomical databases, and display detailed, complementary data and documents about multiple sources simultaneously. We describe how astronomers interact with their data using both the wall's touchsensitive surface and handheld devices. We also report on the technical challenges we addressed in terms of distributed graphics rendering and data sharing over the computer clusters that drive wall displays.

Bio-recognition and detection using liquid crystals.

PubMed

Hussain, A; Pina, A S; Roque, A C A

2009-09-15

Liquid crystals (LCs) are used extensively by the electronics industry as display devices. Advances in the understanding of the liquid crystalline phase and the chemistry therein lead to the development of LC exhibiting faster switching speed with greater twist angle. This in turn lead to the emergence of liquid crystal displays, rendering dial-and-needle based displays (such as those used in various meters) and cathode ray tubes obsolete. In this article, we review the history of LC and their emergence as an invaluable material for display devices and the more recent discovery of their use as sensing elements in biosensors. This new application of LC as tools in the development of fast and simple biosensors is envisaged to gain more importance in the foreseeable future.

Understanding carbohydrate-carbohydrate interactions by means of glyconanotechnology.

PubMed

de la Fuente, Jesus M; Penadés, Soledad

2004-01-01

Carbohydrate-carbohydrate interaction is a reliable and versatile mechanism for cell adhesion and recognition. Glycosphingolipid (GSL) clusters at the cell membrane are mainly involved in this interaction. To investigate carbohydrate-carbohydrate interaction an integrated strategy (Glyconanotechnology) was developed. This strategy includes polyvalent tools (gold glyconanoparticles) mimicking GSL clustering at the cell membrane as well as analytical techniques such as AFM, TEM, and SPR to evaluate the interactions. The results obtained by means of this strategy and current status are presented.

Isotopomer-selective spectra of a single intact H2O molecule in the Cs+(D2O)5H2O isotopologue: Going beyond pattern recognition to harvest the structural information encoded in vibrational spectra

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

Wolke, Conrad T.; Fournier, Joseph A.; Miliordos, Evangelos

We report the vibrational signatures of a single H2O water molecule occupying distinct sites of the hydration network in the Cs+(H2O)6 cluster. This is accomplished using isotopomer selective IR-IR hole-burning on the Cs+(D2O)5(H2O) clusters formed by gas-phase exchange of a single, intact H2O molecule for D2O in the Cs+(D2O)6 ion. The OH stretching pattern of the Cs+(H2O)6 isotopologue is accurately recovered by superposition of the isotopomer spectra, thus establishing that the H2O incorporation is random and that the OH stretching manifold is largely due to contributions from decoupled water molecules. This behavior enables a powerful new way to extract structuralmore » information from vibrational spectra of size-selected clusters by explicitly identifying the local environments responsible for specific infrared features. The Cs+(H2O)6 structure was unambiguously assigned to the 4.1.1 isomer (a homodromic water tetramer with two additional flanking water molecules) from the fact that its computed IR spectrum matches the observed overall pattern and recovers the embedded correlations in the two OH stretching bands of the water molecule in the Cs+(D2O)5(H2O) isotopomers. The 4.1.1 isomer is the lowest in energy among other candidate networks at advanced (e.g., CCSD(T)) levels of theoretical treatment after corrections for (anharmonic) zero-point energy (ZPE). With the structure in hand, we then explore the mechanical origin of the various band locations using a local electric field formalism. This approach promises to provide a transferrable scheme for the prediction of the OH stretching fundamentals displayed by water networks in close proximity to solute ions.« less

Image Descriptors for Displays

DTIC Science & Technology

1977-02-01

Information available for shape recognition in the dot field . What we do is to open up a nw dimension of the display, a dimension of color variation. The...line in a random location in the field of view (b); this is followed by a line mask and response choices (c). Accuracy feedback (d) follows response...dot field (c) and then gives a :4 /button response to indicate whether or not he thinks the triangle is present. Accuracy feedback (d) follows the

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system.

PubMed

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

CNN based approach for activity recognition using a wrist-worn accelerometer.

PubMed

Panwar, Madhuri; Dyuthi, S Ram; Chandra Prakash, K; Biswas, Dwaipayan; Acharyya, Amit; Maharatna, Koushik; Gautam, Arvind; Naik, Ganesh R

2017-07-01

In recent years, significant advancements have taken place in human activity recognition using various machine learning approaches. However, feature engineering have dominated conventional methods involving the difficult process of optimal feature selection. This problem has been mitigated by using a novel methodology based on deep learning framework which automatically extracts the useful features and reduces the computational cost. As a proof of concept, we have attempted to design a generalized model for recognition of three fundamental movements of the human forearm performed in daily life where data is collected from four different subjects using a single wrist worn accelerometer sensor. The validation of the proposed model is done with different pre-processing and noisy data condition which is evaluated using three possible methods. The results show that our proposed methodology achieves an average recognition rate of 99.8% as opposed to conventional methods based on K-means clustering, linear discriminant analysis and support vector machine.

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

NASA Astrophysics Data System (ADS)

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Déjà vu experiences in healthy subjects are unrelated to laboratory tests of recollection and familiarity for word stimuli.

PubMed

O'Connor, Akira R; Moulin, Chris J A

2013-01-01

Recent neuropsychological and neuroscientific research suggests that people who experience more déjà vu display characteristic patterns in normal recognition memory. We conducted a large individual differences study (n = 206) to test these predictions using recollection and familiarity parameters recovered from a standard memory task. Participants reported déjà vu frequency and a number of its correlates, and completed a recognition memory task analogous to a Remember-Know procedure. The individual difference measures replicated an established correlation between déjà vu frequency and frequency of travel, and recognition performance showed well-established word frequency and accuracy effects. Contrary to predictions, no relationships were found between déjà vu frequency and recollection or familiarity memory parameters from the recognition test. We suggest that déjà vu in the healthy population reflects a mismatch between errant memory signaling and memory monitoring processes not easily characterized by standard recognition memory task performance.

Déjà vu experiences in healthy subjects are unrelated to laboratory tests of recollection and familiarity for word stimuli

PubMed Central

O’Connor, Akira R.; Moulin, Chris J. A.

2013-01-01

Recent neuropsychological and neuroscientific research suggests that people who experience more déjà vu display characteristic patterns in normal recognition memory. We conducted a large individual differences study (n = 206) to test these predictions using recollection and familiarity parameters recovered from a standard memory task. Participants reported déjà vu frequency and a number of its correlates, and completed a recognition memory task analogous to a Remember-Know procedure. The individual difference measures replicated an established correlation between déjà vu frequency and frequency of travel, and recognition performance showed well-established word frequency and accuracy effects. Contrary to predictions, no relationships were found between déjà vu frequency and recollection or familiarity memory parameters from the recognition test. We suggest that déjà vu in the healthy population reflects a mismatch between errant memory signaling and memory monitoring processes not easily characterized by standard recognition memory task performance. PMID:24409159

Orientation congruency effects for familiar objects: coordinate transformations in object recognition.

PubMed

Graf, M; Kaping, D; Bülthoff, H H

2005-03-01

How do observers recognize objects after spatial transformations? Recent neurocomputational models have proposed that object recognition is based on coordinate transformations that align memory and stimulus representations. If the recognition of a misoriented object is achieved by adjusting a coordinate system (or reference frame), then recognition should be facilitated when the object is preceded by a different object in the same orientation. In the two experiments reported here, two objects were presented in brief masked displays that were in close temporal contiguity; the objects were in either congruent or incongruent picture-plane orientations. Results showed that naming accuracy was higher for congruent than for incongruent orientations. The congruency effect was independent of superordinate category membership (Experiment 1) and was found for objects with different main axes of elongation (Experiment 2). The results indicate congruency effects for common familiar objects even when they have dissimilar shapes. These findings are compatible with models in which object recognition is achieved by an adjustment of a perceptual coordinate system.

Applications of Some Artificial Intelligence Methods to Satellite Soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.

1985-01-01

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Self-recognition in pigeons revisited.

PubMed

Uchino, Emiko; Watanabe, Shigeru

2014-11-01

Recognition of a self-image in a mirror is investigated using the mark test during which a mark is placed onto a point on the body that is not directly visible, and the presence or absence of self-directed behaviors is evaluated for the mirror-observing subjects. Great apes, dolphins, possibly elephants, and magpies have all passed the mark test, that is, displayed self-directed behaviors, whereas monkeys, crows, and other animals have failed the test even though they were able to use a mirror to find a not-directly-visible object. Self-directed behavior and mirror use are prerequisites of a successful mark test, and the absence of these behaviors may lead to false negative results. Epstein, Lanza, and Skinner (1981) reported self-directed behavior of pigeons in front of a mirror after explicit training of self-directed pecking and of pecking an object with the aid of a mirror, but certain other researchers could not confirm the results. The aim of the present study was to conduct the mark test with two pigeons that had received extensive training of the prerequisite behaviors. Crucial points of the training were identical topography (pecking) and the same reinforcement (food) in the prerequisite behaviors as well as sufficient training of these behaviors. After training for the prerequisite behaviors, both pigeons spontaneously integrated the learned self-directed and mirror-use behavior and displayed self-directed behavior in a mark test. This indicates that pigeons display mirror self-recognition after training of suitable ontogenetic contingency. © Society for the Experimental Analysis of Behavior.

Computational investigation on the structures and electronic properties of the nanosized rhenium clusters

DOE PAGES

Zhao, Run -Ning; Chen, Rui; Yuan, Yan -Hong; ...

2017-08-10

Here, the stable equilibrium geometries, relative stabilities, and electronic and magnetic characteristics of Re n (n = 2–16) clusters were investigated by density functional theory method. The calculated fragmentation energies and second-order differences of energies exhibited interestingly that the stabilities of Re n (n = 2–16) clusters show a dramatic odd-even alternative behavior of the cluster size n: with the even-numbered Ren clusters being obviously more stable than their neighboring odd-numbered Re n clusters (beside n = 11). Simultaneously, the calculated HOMO-LUMO gaps of Re n (n = 6–16) display an oscillatory feature at large-sized Ren clusters. From the calculatedmore » magnetic moments and growth behaviors of Rhenium clusters, the magnetic Re 6 unit can be seen as the building block for the novel magnetic cluster-assembled nanomaterial. Such calculated results are in good agreement with the available experimental measurements.« less

Computational investigation on the structures and electronic properties of the nanosized rhenium clusters

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

Zhao, Run -Ning; Chen, Rui; Yuan, Yan -Hong

Here, the stable equilibrium geometries, relative stabilities, and electronic and magnetic characteristics of Re n (n = 2–16) clusters were investigated by density functional theory method. The calculated fragmentation energies and second-order differences of energies exhibited interestingly that the stabilities of Re n (n = 2–16) clusters show a dramatic odd-even alternative behavior of the cluster size n: with the even-numbered Ren clusters being obviously more stable than their neighboring odd-numbered Re n clusters (beside n = 11). Simultaneously, the calculated HOMO-LUMO gaps of Re n (n = 6–16) display an oscillatory feature at large-sized Ren clusters. From the calculatedmore » magnetic moments and growth behaviors of Rhenium clusters, the magnetic Re 6 unit can be seen as the building block for the novel magnetic cluster-assembled nanomaterial. Such calculated results are in good agreement with the available experimental measurements.« less

Behavioral features recognition and oestrus detection based on fast approximate clustering algorithm in dairy cows

NASA Astrophysics Data System (ADS)

Tian, Fuyang; Cao, Dong; Dong, Xiaoning; Zhao, Xinqiang; Li, Fade; Wang, Zhonghua

2017-06-01

Behavioral features recognition was an important effect to detect oestrus and sickness in dairy herds and there is a need for heat detection aid. The detection method was based on the measure of the individual behavioural activity, standing time, and temperature of dairy using vibrational sensor and temperature sensor in this paper. The data of behavioural activity index, standing time, lying time and walking time were sent to computer by lower power consumption wireless communication system. The fast approximate K-means algorithm (FAKM) was proposed to deal the data of the sensor for behavioral features recognition. As a result of technical progress in monitoring cows using computers, automatic oestrus detection has become possible.

Learning in shifts of transient attention improves recognition of parts of ambiguous figure-ground displays.

PubMed

Kristjánsson, Arni

2009-04-24

Previously demonstrated learning effects in shifts of transient attention have only been shown to result in beneficial effects upon secondary discrimination tasks and affect landing points of express saccades. Can such learning result in more direct effects upon perception than previously demonstrated? Observers performed a cued Vernier acuity discrimination task where the cue was one of a set of ambiguous figure-ground displays (with a black and white part). The critical measure was whether, if a target appeared consistently within a part of a cue of a certain brightness, this would result in learning effects and whether such learning would then affect recognition of the cue parts. Critically the target always appeared within the same part of each individual cue. Some cues were used in early parts of streaks of repetition of cue-part brightness, and others in latter parts of such streaks. All the observers showed learning in shifts of transient attention, with improved performance the more often the target appeared within the part of the cue of the same brightness. Subsequently the observers judged whether cue-parts had been parts of the cues used on the preceding discrimination task. Recognition of the figure parts, where the target had consistently appeared, improved strongly with increased length of streaks of repetition of cue-part brightness. Learning in shifts of transient attention leads not only to faster attention shifts but to direct effects upon perception, in this case recognition of parts of figure-ground ambiguous cues.

A multistream model of visual word recognition.

PubMed

Allen, Philip A; Smith, Albert F; Lien, Mei-Ching; Kaut, Kevin P; Canfield, Angie

2009-02-01

Four experiments are reported that test a multistream model of visual word recognition, which associates letter-level and word-level processing channels with three known visual processing streams isolated in macaque monkeys: the magno-dominated (MD) stream, the interblob-dominated (ID) stream, and the blob-dominated (BD) stream (Van Essen & Anderson, 1995). We show that mixing the color of adjacent letters of words does not result in facilitation of response times or error rates when the spatial-frequency pattern of a whole word is familiar. However, facilitation does occur when the spatial-frequency pattern of a whole word is not familiar. This pattern of results is not due to different luminance levels across the different-colored stimuli and the background because isoluminant displays were used. Also, the mixed-case, mixed-hue facilitation occurred when different display distances were used (Experiments 2 and 3), so this suggests that image normalization can adjust independently of object size differences. Finally, we show that this effect persists in both spaced and unspaced conditions (Experiment 4)--suggesting that inappropriate letter grouping by hue cannot account for these results. These data support a model of visual word recognition in which lower spatial frequencies are processed first in the more rapid MD stream. The slower ID and BD streams may process some lower spatial frequency information in addition to processing higher spatial frequency information, but these channels tend to lose the processing race to recognition unless the letter string is unfamiliar to the MD stream--as with mixed-case presentation.

Face Age and Eye Gaze Influence Older Adults' Emotion Recognition.

PubMed

Campbell, Anna; Murray, Janice E; Atkinson, Lianne; Ruffman, Ted

2017-07-01

Eye gaze has been shown to influence emotion recognition. In addition, older adults (over 65 years) are not as influenced by gaze direction cues as young adults (18-30 years). Nevertheless, these differences might stem from the use of young to middle-aged faces in emotion recognition research because older adults have an attention bias toward old-age faces. Therefore, using older face stimuli might allow older adults to process gaze direction cues to influence emotion recognition. To investigate this idea, young and older adults completed an emotion recognition task with young and older face stimuli displaying direct and averted gaze, assessing labeling accuracy for angry, disgusted, fearful, happy, and sad faces. Direct gaze rather than averted gaze improved young adults' recognition of emotions in young and older faces, but for older adults this was true only for older faces. The current study highlights the impact of stimulus face age and gaze direction on emotion recognition in young and older adults. The use of young face stimuli with direct gaze in most research might contribute to age-related emotion recognition differences. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Stabilizing subnanometer Ag(0) nanoclusters by thiolate and diphosphine ligands and their crystal structures

NASA Astrophysics Data System (ADS)

Yang, Huayan; Wang, Yu; Zheng, Nanfeng

2013-03-01

The combined use of thiolate and diphosphine as surface ligands helps to stabilize subnanometer Ag(0) nanoclusters, resulting in the successful crystallization of two Ag(0)-containing nanoclusters (Ag16 and Ag32) for X-ray single crystal analysis. Both clusters have core-shell structures with Ag86+ and Ag2212+ as their cores, which are not simply either fragments of face-centered cubic metals or their five-fold twinned counterparts. The clusters display UV-Vis absorption spectra consisting of molecule-like optical transitions.The combined use of thiolate and diphosphine as surface ligands helps to stabilize subnanometer Ag(0) nanoclusters, resulting in the successful crystallization of two Ag(0)-containing nanoclusters (Ag16 and Ag32) for X-ray single crystal analysis. Both clusters have core-shell structures with Ag86+ and Ag2212+ as their cores, which are not simply either fragments of face-centered cubic metals or their five-fold twinned counterparts. The clusters display UV-Vis absorption spectra consisting of molecule-like optical transitions. Electronic supplementary information (ESI) available: Experimental details, more pictures of the structure and XPS spectra of the clusters. CCDC 916463 and 916464. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c3nr34328f

Unique ζ-chain motifs mediate a direct TCR-actin linkage critical for immunological synapse formation and T-cell activation.

PubMed

Klieger, Yair; Almogi-Hazan, Osnat; Ish-Shalom, Eliran; Pato, Aviad; Pauker, Maor H; Barda-Saad, Mira; Wang, Lynn; Baniyash, Michal

2014-01-01

TCR-mediated activation induces receptor microclusters that evolve to a defined immune synapse (IS). Many studies showed that actin polymerization and remodeling, which create a scaffold critical to IS formation and stabilization, are TCR mediated. However, the mechanisms controlling simultaneous TCR and actin dynamic rearrangement in the IS are yet not fully understood. Herein, we identify two novel TCR ζ-chain motifs, mediating the TCR's direct interaction with actin and inducing actin bundling. While T cells expressing the ζ-chain mutated in these motifs lack cytoskeleton (actin) associated (cska)-TCRs, they express normal levels of non-cska and surface TCRs as cells expressing wild-type ζ-chain. However, such mutant cells are unable to display activation-dependent TCR clustering, IS formation, expression of CD25/CD69 activation markers, or produce/secrete cytokine, effects also seen in the corresponding APCs. We are the first to show a direct TCR-actin linkage, providing the missing gap linking between TCR-mediated Ag recognition, specific cytoskeleton orientation toward the T-cell-APC interacting pole and long-lived IS maintenance. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Glossary of terms used by radiologists in image processing].

PubMed

Rolland, Y; Collorec, R; Bruno, A; Ramée, A; Morcet, N; Haigron, P

1995-01-01

We give the definition of 166 words used in image processing. Adaptivity, aliazing, analog-digital converter, analysis, approximation, arc, artifact, artificial intelligence, attribute, autocorrelation, bandwidth, boundary, brightness, calibration, class, classification, classify, centre, cluster, coding, color, compression, contrast, connectivity, convolution, correlation, data base, decision, decomposition, deconvolution, deduction, descriptor, detection, digitization, dilation, discontinuity, discretization, discrimination, disparity, display, distance, distorsion, distribution dynamic, edge, energy, enhancement, entropy, erosion, estimation, event, extrapolation, feature, file, filter, filter floaters, fitting, Fourier transform, frequency, fusion, fuzzy, Gaussian, gradient, graph, gray level, group, growing, histogram, Hough transform, Houndsfield, image, impulse response, inertia, intensity, interpolation, interpretation, invariance, isotropy, iterative, JPEG, knowledge base, label, laplacian, learning, least squares, likelihood, matching, Markov field, mask, matching, mathematical morphology, merge (to), MIP, median, minimization, model, moiré, moment, MPEG, neural network, neuron, node, noise, norm, normal, operator, optical system, optimization, orthogonal, parametric, pattern recognition, periodicity, photometry, pixel, polygon, polynomial, prediction, pulsation, pyramidal, quantization, raster, reconstruction, recursive, region, rendering, representation space, resolution, restoration, robustness, ROC, thinning, transform, sampling, saturation, scene analysis, segmentation, separable function, sequential, smoothing, spline, split (to), shape, threshold, tree, signal, speckle, spectrum, spline, stationarity, statistical, stochastic, structuring element, support, syntaxic, synthesis, texture, truncation, variance, vision, voxel, windowing.

Profile Analysis of the Woodcock-Johnson III Tests of Cognitive Abilities with Gifted Students.

ERIC Educational Resources Information Center

Rizza, Mary G.; McIntosh, David E.; McCunn, Alice

2001-01-01

The Cattell-Horn-Carroll (CHC) factor clusters of the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III COG) were studied with a group of gifted and nongifted individuals. Results found both groups display similar patterns of performance across the CHC factor clusters. Discusses clinical and educational considerations when using the WJ III…

Display technologies: application for the discovery of drug and gene delivery agents

PubMed Central

Sergeeva, Anna; Kolonin, Mikhail G.; Molldrem, Jeffrey J.; Pasqualini, Renata; Arap, Wadih

2007-01-01

Recognition of molecular diversity of cell surface proteomes in disease is essential for the development of targeted therapies. Progress in targeted therapeutics requires establishing effective approaches for high-throughput identification of agents specific for clinically relevant cell surface markers. Over the past decade, a number of platform strategies have been developed to screen polypeptide libraries for ligands targeting receptors selectively expressed in the context of various cell surface proteomes. Streamlined procedures for identification of ligand-receptor pairs that could serve as targets in disease diagnosis, profiling, imaging and therapy have relied on the display technologies, in which polypeptides with desired binding profiles can be serially selected, in a process called biopanning, based on their physical linkage with the encoding nucleic acid. These technologies include virus/phage display, cell display, ribosomal display, mRNA display and covalent DNA display (CDT), with phage display being by far the most utilized. The scope of this review is the recent advancements in the display technologies with a particular emphasis on molecular mapping of cell surface proteomes with peptide phage display. Prospective applications of targeted compounds derived from display libraries in the discovery of targeted drugs and gene therapy vectors are discussed. PMID:17123658

A comprehensive analysis of filamentous phage display vectors for cytoplasmic proteins: an analysis with different fluorescent proteins.

PubMed

Velappan, Nileena; Fisher, Hugh E; Pesavento, Emanuele; Chasteen, Leslie; D'Angelo, Sara; Kiss, Csaba; Longmire, Michelle; Pavlik, Peter; Bradbury, Andrew R M

2010-03-01

Filamentous phage display has been extensively used to select proteins with binding properties of specific interest. Although many different display platforms using filamentous phage have been described, no comprehensive comparison of their abilities to display similar proteins has been conducted. This is particularly important for the display of cytoplasmic proteins, which are often poorly displayed with standard filamentous phage vectors. In this article, we have analyzed the ability of filamentous phage to display a stable form of green fluorescent protein and modified variants in nine different display vectors, a number of which have been previously proposed as being suitable for cytoplasmic protein display. Correct folding and display were assessed by phagemid particle fluorescence, and with anti-GFP antibodies. The poor correlation between phagemid particle fluorescence and recognition of GFP by antibodies, indicates that proteins may fold correctly without being accessible for display. The best vector used a twin arginine transporter leader to transport the displayed protein to the periplasm, and a coil-coil arrangement to link the displayed protein to g3p. This vector was able to display less robust forms of GFP, including ones with inserted epitopes, as well as fluorescent proteins of the Azami green series. It was also functional in mock selection experiments.

First instalment in resolution of the Banksia spinulosa complex (Proteaceae): B. neoanglica, a new species supported by phenetic analysis, ecology and geography

PubMed Central

Stimpson, Margaret L.; Weston, Peter H.; Telford, Ian R.H.; Bruhl, Jeremy J.

2012-01-01

Abstract Taxa in the Banksia spinulosa Sm. complex (Proteaceae) have populations with sympatric, parapatric and allopatric distributions and unclear or disputed boundaries. Our hypothesis is that under biological, phenetic and diagnosable species concepts that each of the currently named taxa within the Banksia spinulosa complex is a separate species. Based on specimens collected as part of this study, and data recorded from specimens in six Australian herbaria, complemented by phenetic analysis (semi–strong multidimensional scaling and UPGMA clustering) and a detailed morphological study, we investigated both morphological variation and geographic distribution in the Banksia spinulosa complex. All specimens used for this study are held at the N.C.W. Beadle Herbarium or the National Herbarium of New South Wales. In total 23 morphological characters (11 quantitative, five binary, and seven multistate characters) were analysed phenetically for 89 specimens. Ordination and cluster analysis resulted in individuals grouping strongly allowing recognition of distinct groups consistent with their recognition as separate species. Additional morphological analysis was completed on all specimens using leaf, floral, fruit and stem morphology, providing clear cut diagnosable groups and strong support for the recognition of Banksia spinulosa var. cunninghamii and Banksia spinulosa var. neoanglica as species. PMID:23170073

Automated thematic mapping and change detection of ERTS-A images. [farmlands, cities, and mountain identification in Utah, Washington, Arizona, and California

NASA Technical Reports Server (NTRS)

Gramenopoulos, N. (Principal Investigator)

1974-01-01

The author has identified the following significant results. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month, but vary substantially between seasons. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains, and urban areas. To eliminate the need for training data, a new clustering algorithm has been developed. Seven ERTS-1 images from four test sites have been processed through the clustering algorithm, and high recognition rates have been achieved for all terrain classes.

Linked supramolecular building blocks for enhanced cluster formation

DOE PAGES

McLellan, Ross; Palacios, Maria A.; Beavers, Christine M.; ...

2015-01-09

Methylene-bridged calix[4]arenes have emerged as extremely versatile ligand supports in the formation of new polymetallic clusters possessing fascinating magnetic properties. Metal ion binding rules established for this building block allow one to partially rationalise the complex assembly process. The ability to covalently link calix[4]arenes at the methylene bridge provides significantly improved control over the introduction of different metal centres to resulting cluster motifs. Clusters assembled from bis-calix[4]arenes and transition metal ions or 3d-4f combinations display characteristic features of the analogous calix[4]arene supported clusters, thereby demonstrating an enhanced and rational approach towards the targeted synthesis of complex and challenging structures.

Self-recognition in retarded children.

PubMed

Hill, S D; Tomlin, C

1981-03-01

This study was designed to investigate the relationship between cognitive and affective development. Young preverbal retarded children watched TV images of themselves with faces marked or unmarked and of a peer whose face was marked. We used the objective technique of increased mark-directed responses as evidence of self-recognition and rated the children's reactions as they watched these images. The emergence of self-recognition was closely tied to the maturity of the children's general responsiveness to their reflections. The Down's syndrome children made a broad range of responses, including the curiosity and self-conscious behaviors characteristic of normal children during the second year of life, and all except one of these children showed evidence that they recognized their images. In contrast, the range of behaviors displayed by multihandicapped children was greatly restricted and similar to children in the first year of life. Less than half of these children showed an emergence of self-recognition.

Gender affects body language reading.

PubMed

Sokolov, Arseny A; Krüger, Samuel; Enck, Paul; Krägeloh-Mann, Ingeborg; Pavlova, Marina A

2011-01-01

Body motion is a rich source of information for social cognition. However, gender effects in body language reading are largely unknown. Here we investigated whether, and, if so, how recognition of emotional expressions revealed by body motion is gender dependent. To this end, females and males were presented with point-light displays portraying knocking at a door performed with different emotional expressions. The findings show that gender affects accuracy rather than speed of body language reading. This effect, however, is modulated by emotional content of actions: males surpass in recognition accuracy of happy actions, whereas females tend to excel in recognition of hostile angry knocking. Advantage of women in recognition accuracy of neutral actions suggests that females are better tuned to the lack of emotional content in body actions. The study provides novel insights into understanding of gender effects in body language reading, and helps to shed light on gender vulnerability to neuropsychiatric and neurodevelopmental impairments in visual social cognition.

V2S: Voice to Sign Language Translation System for Malaysian Deaf People

NASA Astrophysics Data System (ADS)

Mean Foong, Oi; Low, Tang Jung; La, Wai Wan

The process of learning and understand the sign language may be cumbersome to some, and therefore, this paper proposes a solution to this problem by providing a voice (English Language) to sign language translation system using Speech and Image processing technique. Speech processing which includes Speech Recognition is the study of recognizing the words being spoken, regardless of whom the speaker is. This project uses template-based recognition as the main approach in which the V2S system first needs to be trained with speech pattern based on some generic spectral parameter set. These spectral parameter set will then be stored as template in a database. The system will perform the recognition process through matching the parameter set of the input speech with the stored templates to finally display the sign language in video format. Empirical results show that the system has 80.3% recognition rate.

Intact suppression of increased false recognition in schizophrenia.

PubMed

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.

Poster: Building a Large Tiled-Display Cluster

DTIC Science & Technology

2012-10-01

graphics cards ( Nvidia Quadro FX 5800), and each graphics ∗e-mail: mark.livingston@nrl.navy.mil †e-mail: jonathan.decker@nrl.navy.mil card in a display...such as DisplayPort and HDMI (see: Nvidia Quadro 6000). We recommend these formats because they are much easier to plug-and-play. 3.4 Leverage Open...will find yourself with all the issues related to owning a server room. Today, there are a number of companies offering turn-key so- lutions for tiled

Ebola virus disease cases among health care workers not working in Ebola treatment units--Liberia, June-August, 2014.

PubMed

Matanock, Almea; Arwady, M Allison; Ayscue, Patrick; Forrester, Joseph D; Gaddis, Bethany; Hunter, Jennifer C; Monroe, Benjamin; Pillai, Satish K; Reed, Christie; Schafer, Ilana J; Massaquoi, Moses; Dahn, Bernice; De Cock, Kevin M

2014-11-21

West Africa is experiencing the largest Ebola virus disease (Ebola) epidemic in recorded history. Health care workers (HCWs) are at increased risk for Ebola. In Liberia, as of August 14, 2014, a total of 810 cases of Ebola had been reported, including 10 clusters of Ebola cases among HCWs working in facilities that were not Ebola treatment units (non-ETUs). The Liberian Ministry of Health and Social Welfare and CDC investigated these clusters by reviewing surveillance data, interviewing county health officials, HCWs, and contact tracers, and visiting health care facilities. Ninety-seven cases of Ebola (12% of the estimated total) were identified among HCWs; 62 HCW cases (64%) were part of 10 distinct clusters in non-ETU health care facilities, primarily hospitals. Early recognition and diagnosis of Ebola in patients who were the likely source of introduction to the HCWs (i.e., source patients) was missed in four clusters. Inconsistent recognition and triage of cases of Ebola, overcrowding, limitations in layout of physical spaces, lack of training in the use of and adequate supply of personal protective equipment (PPE), and limited supervision to ensure consistent adherence to infection control practices all were observed. Improving infection control infrastructure in non-ETUs is essential for protecting HCWs. Since August, the Liberian Ministry of Health and Social Welfare with a consortium of partners have undertaken collaborative efforts to strengthen infection control infrastructure in non-ETU health facilities.

Multimedia-based decision support system for hazards recognition and abatement

DOEpatents

Czachowski, John B.; Zoldak, John T.

1998-01-01

A system for monitoring a site includes a portable data collection module used in the field to collect site specific data, and a processor module located at a central location. The data collection module displays choices of categories of findings, and then specific findings within each category. A selected specific finding is then displayed in report form with a citation to the specific code or statutory requirement, as well as a recommended course of action and an abatement date.

Identification of natural metabolites in mixture: a pattern recognition strategy based on (13)C NMR.

PubMed

Hubert, Jane; Nuzillard, Jean-Marc; Purson, Sylvain; Hamzaoui, Mahmoud; Borie, Nicolas; Reynaud, Romain; Renault, Jean-Hugues

2014-03-18

Because of their highly complex metabolite profile, the chemical characterization of bioactive natural extracts usually requires time-consuming multistep purification procedures to achieve the structural elucidation of pure individual metabolites. The aim of the present work was to develop a dereplication strategy for the identification of natural metabolites directly within mixtures. Exploiting the polarity range of metabolites, the principle was to rapidly fractionate a multigram quantity of a crude extract by centrifugal partition extraction (CPE). The obtained fractions of simplified chemical composition were subsequently analyzed by (13)C NMR. After automatic collection and alignment of (13)C signals across spectra, hierarchical clustering analysis (HCA) was performed for pattern recognition. As a result, strong correlations between (13)C signals of a single structure within the mixtures of the fraction series were visualized as chemical shift clusters. Each cluster was finally assigned to a molecular structure with the help of a locally built (13)C NMR chemical shift database. The proof of principle of this strategy was achieved on a simple model mixture of commercially available plant secondary metabolites and then applied to a bark extract of the African tree Anogeissus leiocarpus Guill. & Perr. (Combretaceae). Starting from 5 g of this genuine extract, the fraction series was generated by CPE in only 95 min. (13)C NMR analyses of all fractions followed by pattern recognition of (13)C chemical shifts resulted in the unambiguous identification of seven major compounds, namely, sericoside, trachelosperogenin E, ellagic acid, an epimer mixture of (+)-gallocatechin and (-)-epigallocatechin, 3,3'-di-O-methylellagic acid 4'-O-xylopyranoside, and 3,4,3'-tri-O-methylflavellagic acid 4'-O-glucopyranoside.

Crop species recognition and mensuration in the Sacramento Valley

NASA Technical Reports Server (NTRS)

Thomson, F. J.

1973-01-01

The goal of the second recognition map was to delineate various crop species in a portion of the Sacramento Valley, and at the same time to determine how accurately each could be classified and measured from ERTS-1 data. The new recognition map, a new and concise display of the old map, and classification and mensuration accuracy data are presented and discussed. The mensuration accuracy, in particular, is affected by the presence of an edge effect one resolution wide surrounding nearly all fields. Points on the edge are misclassified because they contain a mixture of, crop and bare soil. Using a processing technique to estimate the proportions of unresolved objects in this edge region, a much improved mensuration capability will be demonstrated.

Iris recognition using image moments and k-means algorithm.

PubMed

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%.

Iris Recognition Using Image Moments and k-Means Algorithm

PubMed Central

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%. PMID:24977221

Investigation of correlation classification techniques

NASA Technical Reports Server (NTRS)

Haskell, R. E.

1975-01-01

A two-step classification algorithm for processing multispectral scanner data was developed and tested. The first step is a single pass clustering algorithm that assigns each pixel, based on its spectral signature, to a particular cluster. The output of that step is a cluster tape in which a single integer is associated with each pixel. The cluster tape is used as the input to the second step, where ground truth information is used to classify each cluster using an iterative method of potentials. Once the clusters have been assigned to classes the cluster tape is read pixel-by-pixel and an output tape is produced in which each pixel is assigned to its proper class. In addition to the digital classification programs, a method of using correlation clustering to process multispectral scanner data in real time by means of an interactive color video display is also described.

Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy

PubMed Central

Jiang, Shenghang; Park, Seongjin; Challapalli, Sai Divya; Fei, Jingyi; Wang, Yong

2017-01-01

We report a robust nonparametric descriptor, J′(r), for quantifying the density of clustering molecules in single-molecule localization microscopy. J′(r), based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that J′(r) displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. Most importantly, the position of the J′(r) valley (rJm′) depends exclusively on the density of clustering molecules (ρc). Therefore, it is ideal for direct estimation of the clustering density of molecules in single-molecule localization microscopy. As an example, this descriptor was applied to estimate the clustering density of ptsG mRNA in E. coli bacteria. PMID:28636661

Deletion of the GluA1 AMPA receptor subunit impairs recency-dependent object recognition memory

PubMed Central

Sanderson, David J.; Hindley, Emma; Smeaton, Emily; Denny, Nick; Taylor, Amy; Barkus, Chris; Sprengel, Rolf; Seeburg, Peter H.; Bannerman, David M.

2011-01-01

Deletion of the GluA1 AMPA receptor subunit impairs short-term spatial recognition memory. It has been suggested that short-term recognition depends upon memory caused by the recent presentation of a stimulus that is independent of contextual–retrieval processes. The aim of the present set of experiments was to test whether the role of GluA1 extends to nonspatial recognition memory. Wild-type and GluA1 knockout mice were tested on the standard object recognition task and a context-independent recognition task that required recency-dependent memory. In a first set of experiments it was found that GluA1 deletion failed to impair performance on either of the object recognition or recency-dependent tasks. However, GluA1 knockout mice displayed increased levels of exploration of the objects in both the sample and test phases compared to controls. In contrast, when the time that GluA1 knockout mice spent exploring the objects was yoked to control mice during the sample phase, it was found that GluA1 deletion now impaired performance on both the object recognition and the recency-dependent tasks. GluA1 deletion failed to impair performance on a context-dependent recognition task regardless of whether object exposure in knockout mice was yoked to controls or not. These results demonstrate that GluA1 is necessary for nonspatial as well as spatial recognition memory and plays an important role in recency-dependent memory processes. PMID:21378100

Familial covariation of facial emotion recognition and IQ in schizophrenia.

PubMed

Andric, Sanja; Maric, Nadja P; Mihaljevic, Marina; Mirjanic, Tijana; van Os, Jim

2016-12-30

Alterations in general intellectual ability and social cognition in schizophrenia are core features of the disorder, evident at the illness' onset and persistent throughout its course. However, previous studies examining cognitive alterations in siblings discordant for schizophrenia yielded inconsistent results. Present study aimed to investigate the nature of the association between facial emotion recognition and general IQ by applying genetically sensitive cross-trait cross-sibling design. Participants (total n=158; patients, unaffected siblings, controls) were assessed using the Benton Facial Recognition Test, the Degraded Facial Affect Recognition Task (DFAR) and the Wechsler Adult Intelligence Scale-III. Patients had lower IQ and altered facial emotion recognition in comparison to other groups. Healthy siblings and controls did not significantly differ in IQ and DFAR performance, but siblings exhibited intermediate angry facial expression recognition. Cross-trait within-subject analyses showed significant associations between overall DFAR performance and IQ in all participants. Within-trait cross-sibling analyses found significant associations between patients' and siblings' IQ and overall DFAR performance, suggesting their familial clustering. Finally, cross-trait cross-sibling analyses revealed familial covariation of facial emotion recognition and IQ in siblings discordant for schizophrenia, further indicating their familial etiology. Both traits are important phenotypes for genetic studies and potential early clinical markers of schizophrenia-spectrum disorders. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The hierarchical brain network for face recognition.

PubMed

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

Beyond Information Retrieval: Ways To Provide Content in Context.

ERIC Educational Resources Information Center

Wiley, Deborah Lynne

1998-01-01

Provides an overview of information retrieval from mainframe systems to Web search engines; discusses collaborative filtering, data extraction, data visualization, agent technology, pattern recognition, classification and clustering, and virtual communities. Argues that rather than huge data-storage centers and proprietary software, we need…

Biochemical and Genetic Characterization of the vanC-2 Vancomycin Resistance Gene Cluster of Enterococcus casseliflavus ATCC 25788

PubMed Central

Dutta, Ireena; Reynolds, Peter E.

2002-01-01

The vanC-2 cluster of Enterococcus casseliflavus ATCC 25788 consisted of five genes (vanC-2, vanXYC-2, vanTC-2, vanRC-2, and vanSC-2) and shared the same organization as the vanC cluster of E. gallinarum BM4174. The proteins encoded by these genes displayed a high degree of amino acid identity to the proteins encoded within the vanC gene cluster. The putative d,d-dipeptidase-d,d-carboxypeptidase, VanXYC-2, exhibited 81% amino acid identity to VanXYC, and VanTC-2 displayed 65% amino acid identity to the serine racemase, VanT. VanRC-2 and VanSC-2 displayed high degrees of identity to VanRC and VanSC, respectively, and contained the conserved residues identified as important to their function as a response regulator and histidine kinase, respectively. Resistance to vancomycin was expressed inducibly in E. casseliflavus ATCC 25788 and required an extended period of induction. Analysis of peptidoglycan precursors revealed that UDP-N-acetylmuramyl-l-Ala-δ-d-Glu-l-Lys-d-Ala-d-Ser could not be detected until several hours after the addition of vancomycin, and its appearance coincided with the resumption of growth. The introduction of additional copies of the vanTC-2 gene, encoding a putative serine racemase, and the presence of supplementary d-serine in the growth medium both significantly reduced the period before growth resumed after addition of vancomycin. This suggested that the availability of d-serine plays an important role in the induction process. PMID:12234834

Is the orthographic/phonological onset a single unit in reading aloud?

PubMed

Mousikou, Petroula; Coltheart, Max; Saunders, Steven; Yen, Lisa

2010-02-01

Two main theories of visual word recognition have been developed regarding the way orthographic units in printed words map onto phonological units in spoken words. One theory suggests that a string of single letters or letter clusters corresponds to a string of phonemes (Coltheart, 1978; Venezky, 1970), while the other suggests that a string of single letters or letter clusters corresponds to coarser phonological units, for example, onsets and rimes (Treiman & Chafetz, 1987). These theoretical assumptions were critical for the development of coding schemes in prominent computational models of word recognition and reading aloud. In a reading-aloud study, we tested whether the human reading system represents the orthographic/phonological onset of printed words and nonwords as single units or as separate letters/phonemes. Our results, which favored a letter and not an onset-coding scheme, were successfully simulated by the dual-route cascaded (DRC) model (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001). A separate experiment was carried out to further adjudicate between 2 versions of the DRC model.

Complement activation by ligand-driven juxtaposition of discrete pattern recognition complexes

PubMed Central

Degn, Søren E.; Kjaer, Troels R.; Kidmose, Rune T.; Jensen, Lisbeth; Hansen, Annette G.; Tekin, Mustafa; Jensenius, Jens C.; Andersen, Gregers R.; Thiel, Steffen

2014-01-01

Defining mechanisms governing translation of molecular binding events into immune activation is central to understanding immune function. In the lectin pathway of complement, the pattern recognition molecules (PRMs) mannan-binding lectin (MBL) and ficolins complexed with the MBL-associated serine proteases (MASP)-1 and MASP-2 cleave C4 and C2 to generate C3 convertase. MASP-1 was recently found to be the exclusive activator of MASP-2 under physiological conditions, yet the predominant oligomeric forms of MBL carry only a single MASP homodimer. This prompted us to investigate whether activation of MASP-2 by MASP-1 occurs through PRM-driven juxtaposition on ligand surfaces. We demonstrate that intercomplex activation occurs between discrete PRM/MASP complexes. PRM ligand binding does not directly escort the transition of MASP from zymogen to active enzyme in the PRM/MASP complex; rather, clustering of PRM/MASP complexes directly causes activation. Our results support a clustering-based mechanism of activation, fundamentally different from the conformational model suggested for the classical pathway of complement. PMID:25197071

Fuzzy approach for improved recognition of citric acid induced piglet coughing from continuous registration

NASA Astrophysics Data System (ADS)

Van Hirtum, A.; Berckmans, D.

2003-09-01

A natural acoustic indicator of animal welfare is the appearance (or absence) of coughing in the animal habitat. A sound-database of 5319 individual sounds including 2034 coughs was collected on six healthy piglets containing both animal vocalizations and background noises. Each of the test animals was repeatedly placed in a laboratory installation where coughing was induced by nebulization of citric acid. A two-class classification into 'cough' or 'other' was performed by the application of a distance function to a fast Fourier spectral sound analysis. This resulted in a positive cough recognition of 92%. For the whole sound-database however there was a misclassification of 21%. As spectral information up to 10000 Hz is available, an improved overall classification on the same database is obtained by applying the distance function to nine frequency ranges and combining the achieved distance-values in fuzzy rules. For each frequency range clustering threshold is determined by fuzzy c-means clustering.

Phylogeny of marine Bacillus isolates from the Gulf of Mexico

NASA Technical Reports Server (NTRS)

Siefert, J. L.; Larios-Sanz, M.; Nakamura, L. K.; Slepecky, R. A.; Paul, J. H.; Moore, E. R.; Fox, G. E.; Jurtshuk, P. Jr

2000-01-01

The phylogeny of 11 pigmented, aerobic, spore-forming isolates from marine sources was studied. Forty-two biochemical characteristics were examined, and a 16S rDNA sequence was obtained for each isolate. In a phylogenetic tree based on 16S sequencing, four isolates (NRRL B-14850, NRRL B-14904, NRRL B-14907, and NRRL B-14908) clustered with B. subtilis and related organisms; NRRL B-14907 was closely related to B. amyloliquefaciens. NRRL B-14907 and NRRL B-14908 were phenotypically similar to B. amyloliquefaciens and B. pumilus, respectively. Three strains (NRRL B-14906, NRRL B-14910, and NRRL B-14911) clustered in a clade that included B. firmus, B. lentus, and B. megaterium. NRRL B-14910 was closely related phenotypically and phylogenetically to B. megaterium. NRRL B-14905 clustered with the mesophilic round spore-producing species, B. fusiformis and B. sphaericus; the isolate was more closely related to B. fusiformis. NRRL B-14905 displayed characteristics typical of the B. sphaericus-like organisms. NRRL B-14909 and NRRL B-14912 clustered with the Paenibacillus species and displayed characteristics typical of the genus. Only NRRL B-14851, an unusually thin rod that forms very small spores, may represent a new Bacillus species.

Photofragment Coincidence Imaging of Small I- (H2O)n Clusters Excited to the Charge-transfer-to-solvent State

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

Neumark, D. E. Szpunar, K. E. Kautzman, A. E. Faulhaber, and D. M.; Kautzman, K.E.; Faulhaber, A.E.

2005-11-09

The photodissociation dynamics of small I{sup -}(H{sub 2}O){sub n} (n = 2-5) clusters excited to their charge-transfer-to-solvent (CTTS) states have been studied using photofragment coincidence imaging. Upon excitation to the CTTS state, two photodissociation channels were observed. The major channel ({approx}90%) is a 2-body process forming neutral I + (H{sub 2}O){sub n} photofragments, and the minor channel is a 3-body process forming I + (H{sub 2}O){sub n-1} + H{sub 2}O fragments. Both process display translational energy (P(E{sub T})) distributions peaking at E{sub T} = 0 with little available energy partitioned into translation. Clusters excited to the detachment continuum rather thanmore » to the CTTS state display the same two channels with similar P(E{sub T}) distributions. The observation of similar P(E{sub T}) distributions from the two sets of experiments suggests that in the CTTS experiments, I atom loss occurs after autodetachment of the excited (I(H{sub 2}O){sub n}{sup -})* cluster, or, less probably, that the presence of the excess electron has little effect on the departing I atom.« less

The Origin Of Cosmic Rays And The Stars Of Berkeley 87

NASA Astrophysics Data System (ADS)

Turner, David G.; Majaess, D. J.; Lane, D. J.; Balam, D. D.

2010-01-01

Spectroscopic observations and the results of photometric monitoring are presented for members of the heavily-reddened, young, 1.2 kpc-distant, open cluster Berkeley 87, which is spatially coincident with the strongest source of cosmic rays in the northern sky. Many cluster members exhibit evidence for extreme loss of mass over their lifetimes: the M3 Ia supergiant BC Cyg has an evolutionary mass half that of stars at the main-sequence turnoff, the B2 Iabe emission-line supergiant HDE 229059 also has an evolutionary mass smaller than that of the main-sequence turnoff, the WO2 star WR 142, the only example of an oxygen sequence Wolf-Rayet star in an open cluster, displays evidence for variable, high velocity winds in its spectrum, the curious object V439 Cyg (B0: Vnne) appears to be an example of a recent binary merger, and Vatican Emission Star VES 203 (B0.5 Ve) displays a strong P Cygni signature in its Balmer line emission. It appears that heavy mass loss is a common factor associated with cluster stars. Could that be associated with the location of a cosmic ray production factory from the vicinity of Berkeley 87?

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

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

Lai, King C.; Evans, James W.; Liu, Da -Jiang

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, D N ~ N –β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for “perfect” sizes N p = L 2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for N p+3, Nmore » p+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes N p+1 and N p+2. D N versus N oscillates strongly between the slowest branch (for N p+3) and the fastest branch (for N p+1). All branches merge for N = O(10 2), but macroscale behavior is only achieved for much larger N = O(10 3). Here, this analysis reveals the unprecedented diversity of behavior on the nanoscale.« less

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

DOE PAGES

Lai, King C.; Evans, James W.; Liu, Da -Jiang

2017-11-27

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, D N ~ N –β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for “perfect” sizes N p = L 2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for N p+3, Nmore » p+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes N p+1 and N p+2. D N versus N oscillates strongly between the slowest branch (for N p+3) and the fastest branch (for N p+1). All branches merge for N = O(10 2), but macroscale behavior is only achieved for much larger N = O(10 3). Here, this analysis reveals the unprecedented diversity of behavior on the nanoscale.« less

Constitutional chromothripsis rearrangements involve clustered double-stranded DNA breaks and nonhomologous repair mechanisms.

PubMed

Kloosterman, Wigard P; Tavakoli-Yaraki, Masoumeh; van Roosmalen, Markus J; van Binsbergen, Ellen; Renkens, Ivo; Duran, Karen; Ballarati, Lucia; Vergult, Sarah; Giardino, Daniela; Hansson, Kerstin; Ruivenkamp, Claudia A L; Jager, Myrthe; van Haeringen, Arie; Ippel, Elly F; Haaf, Thomas; Passarge, Eberhard; Hochstenbach, Ron; Menten, Björn; Larizza, Lidia; Guryev, Victor; Poot, Martin; Cuppen, Edwin

2012-06-28

Chromothripsis represents a novel phenomenon in the structural variation landscape of cancer genomes. Here, we analyze the genomes of ten patients with congenital disease who were preselected to carry complex chromosomal rearrangements with more than two breakpoints. The rearrangements displayed unanticipated complexity resembling chromothripsis. We find that eight of them contain hallmarks of multiple clustered double-stranded DNA breaks (DSBs) on one or more chromosomes. In addition, nucleotide resolution analysis of 98 breakpoint junctions indicates that break repair involves nonhomologous or microhomology-mediated end joining. We observed that these eight rearrangements are balanced or contain sporadic deletions ranging in size between a few hundred base pairs and several megabases. The two remaining complex rearrangements did not display signs of DSBs and contain duplications, indicative of rearrangement processes involving template switching. Our work provides detailed insight into the characteristics of chromothripsis and supports a role for clustered DSBs driving some constitutional chromothripsis rearrangements. Copyright © 2012 The Authors. Published by Elsevier Inc. All rights reserved.

Varying face occlusion detection and iterative recovery for face recognition

NASA Astrophysics Data System (ADS)

Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

2017-05-01

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Effectiveness of educational poster on knowledge of emergency management of dental trauma--part 2: cluster randomised controlled trial for secondary school students.

PubMed

Young, Cecilia; Wong, Kin Yau; Cheung, Lim K

2014-01-01

To investigate the effectiveness of educational poster on improving secondary school students' knowledge of emergency management of dental trauma. A cluster randomised controlled trial was conducted. 16 schools with total 671 secondary students who can read Chinese or English were randomised into intervention (poster, 8 schools, 364 students) and control groups (8 schools, 305 students) at the school level. Baseline knowledge of dental trauma was obtained by a questionnaire. Poster containing information of dental trauma management was displayed in a classroom for 2 weeks in each school in the intervention group whereas in the control group there was no display of such posters. Students of both groups completed the same questionnaire after 2 weeks. Two-week display of posters improved the knowledge score by 1.25 (p-value = 0.0407) on average. Educational poster on dental trauma management significantly improved the level of knowledge of secondary school students in Hong Kong. HKClinicalTrial.com HKCTR-1343 ClinicalTrials.gov NCT01809457.

JuxtaView - A tool for interactive visualization of large imagery on scalable tiled displays

USGS Publications Warehouse

Krishnaprasad, N.K.; Vishwanath, V.; Venkataraman, S.; Rao, A.G.; Renambot, L.; Leigh, J.; Johnson, A.E.; Davis, B.

2004-01-01

JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive pre-fetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization. ?? 2004 IEEE.

A Probabilistic Clustering Theory of the Organization of Visual Short-Term Memory

ERIC Educational Resources Information Center

Orhan, A. Emin; Jacobs, Robert A.

2013-01-01

Experimental evidence suggests that the content of a memory for even a simple display encoded in visual short-term memory (VSTM) can be very complex. VSTM uses organizational processes that make the representation of an item dependent on the feature values of all displayed items as well as on these items' representations. Here, we develop a…

Hybrid Assembly of Different-Sized Supertetrahedral Clusters into a Unique Non-Interpenetrated Mn-In-S Open Framework with Large Cavity.

PubMed

Wang, Hongxiang; Wang, Wei; Hu, Dandan; Luo, Min; Xue, Chaozhuang; Li, Dongsheng; Wu, Tao

2018-06-04

Reported here is a unique crystalline semiconductor open-framework material built from the large-sized supertetrahedral T4 and T5 clusters with the Mn-In-S compositions. The hybrid assembly between T4 and T5 clusters by sharing terminal μ 2 -S 2- is for the first time observed among the cluster-based chalcogenide open frameworks. Such three-dimensional structure displays non-interpenetrated diamond-type topology with extra-large nonframework volume of 82%. Moreover, ion exchange, CO 2 adsorption, as well as photoluminescence properties of the title compound are also investigated.

Studies of the metastable decay of met-cars. The vanadium and niobium systems

NASA Astrophysics Data System (ADS)

Purnell, J.; Wei, S.; Castleman, A. W., Jr.

1994-10-01

The decay fractions and metastable decomposition channels were measured for V(m)C(n)(+) and Nb(m)C(n)(+) clusters using a reflectron time-of-flight mass spectrometer. These measurements for the V(m)C(n)(+) clusters reveal stable (8, 12) and (8, 13) met-car species. However, under the present experimental conditions, the Nb(m)C(n)(+) clusters display dominantly cubic structures, but the decay fraction and metastable decomposition measurements also show the presence of a stable (8, 12) species in the parent cluster spectrum. This evidence indicates that cubic structures and met-cars are being formed simultaneously for the niobium system.

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

Tone perception in Mandarin-speaking school age children with otitis media with effusion

PubMed Central

McPherson, Bradley; Li, Caiwei; Yang, Feng

2017-01-01

Objectives The present study explored tone perception ability in school age Mandarin-speaking children with otitis media with effusion (OME) in noisy listening environments. The study investigated the interaction effects of noise, tone type, age, and hearing status on monaural tone perception, and assessed the application of a hierarchical clustering algorithm for profiling hearing impairment in children with OME. Methods Forty-one children with normal hearing and normal middle ear status and 84 children with OME with or without hearing loss participated in this study. The children with OME were further divided into two subgroups based on their severity and pattern of hearing loss using a hierarchical clustering algorithm. Monaural tone recognition was measured using a picture-identification test format incorporating six sets of monosyllabic words conveying four lexical tones under speech spectrum noise, with the signal-to-noise ratio (SNR) conditions ranging from -9 to -21 dB. Results Linear correlation indicated tone recognition thresholds of children with OME were significantly correlated with age and pure tone hearing thresholds at every frequency tested. Children with hearing thresholds less affected by OME performed similarly to their peers with normal hearing. Tone recognition thresholds of children with auditory status more affected by OME were significantly inferior to those of children with normal hearing or with minor hearing loss. Younger children demonstrated poorer tone recognition performance than older children with OME. A mixed design repeated-measure ANCOVA showed significant main effects of listening condition, hearing status, and tone type on tone recognition. Contrast comparisons revealed that tone recognition scores were significantly better under -12 dB SNR than under -15 dB SNR conditions and tone recognition scores were significantly worse under -18 dB SNR than those obtained under -15 dB SNR conditions. Tone 1 was the easiest tone to identify and Tone 3 was the most difficult tone to identify for all participants, when considering -12, -15, and -18 dB SNR as within-subject variables. The interaction effect between hearing status and tone type indicated that children with greater levels of OME-related hearing loss had more impaired tone perception of Tone 1 and Tone 2 compared to their peers with lesser levels of OME-related hearing loss. However, tone perception of Tone 3 and Tone 4 remained similar among all three groups. Tone 2 and Tone 3 were the most perceptually difficult tones for children with or without OME-related hearing loss in all listening conditions. Conclusions The hierarchical clustering algorithm demonstrated usefulness in risk stratification for tone perception deficiency in children with OME-related hearing loss. There was marked impairment in tone perception in noise for children with greater levels of OME-related hearing loss. Monaural lexical tone perception in younger children was more vulnerable to noise and OME-related hearing loss than that in older children. PMID:28829840

Tone perception in Mandarin-speaking school age children with otitis media with effusion.

PubMed

Cai, Ting; McPherson, Bradley; Li, Caiwei; Yang, Feng

2017-01-01

The present study explored tone perception ability in school age Mandarin-speaking children with otitis media with effusion (OME) in noisy listening environments. The study investigated the interaction effects of noise, tone type, age, and hearing status on monaural tone perception, and assessed the application of a hierarchical clustering algorithm for profiling hearing impairment in children with OME. Forty-one children with normal hearing and normal middle ear status and 84 children with OME with or without hearing loss participated in this study. The children with OME were further divided into two subgroups based on their severity and pattern of hearing loss using a hierarchical clustering algorithm. Monaural tone recognition was measured using a picture-identification test format incorporating six sets of monosyllabic words conveying four lexical tones under speech spectrum noise, with the signal-to-noise ratio (SNR) conditions ranging from -9 to -21 dB. Linear correlation indicated tone recognition thresholds of children with OME were significantly correlated with age and pure tone hearing thresholds at every frequency tested. Children with hearing thresholds less affected by OME performed similarly to their peers with normal hearing. Tone recognition thresholds of children with auditory status more affected by OME were significantly inferior to those of children with normal hearing or with minor hearing loss. Younger children demonstrated poorer tone recognition performance than older children with OME. A mixed design repeated-measure ANCOVA showed significant main effects of listening condition, hearing status, and tone type on tone recognition. Contrast comparisons revealed that tone recognition scores were significantly better under -12 dB SNR than under -15 dB SNR conditions and tone recognition scores were significantly worse under -18 dB SNR than those obtained under -15 dB SNR conditions. Tone 1 was the easiest tone to identify and Tone 3 was the most difficult tone to identify for all participants, when considering -12, -15, and -18 dB SNR as within-subject variables. The interaction effect between hearing status and tone type indicated that children with greater levels of OME-related hearing loss had more impaired tone perception of Tone 1 and Tone 2 compared to their peers with lesser levels of OME-related hearing loss. However, tone perception of Tone 3 and Tone 4 remained similar among all three groups. Tone 2 and Tone 3 were the most perceptually difficult tones for children with or without OME-related hearing loss in all listening conditions. The hierarchical clustering algorithm demonstrated usefulness in risk stratification for tone perception deficiency in children with OME-related hearing loss. There was marked impairment in tone perception in noise for children with greater levels of OME-related hearing loss. Monaural lexical tone perception in younger children was more vulnerable to noise and OME-related hearing loss than that in older children.

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

PubMed

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

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

Specific Impairments in the Recognition of Emotional Facial Expressions in Parkinson’s Disease

PubMed Central

Clark, Uraina S.; Neargarder, Sandy; Cronin-Golomb, Alice

2008-01-01

Studies investigating the ability to recognize emotional facial expressions in non-demented individuals with Parkinson’s disease (PD) have yielded equivocal findings. A possible reason for this variability may lie in the confounding of emotion recognition with cognitive task requirements, a confound arising from the lack of a control condition using non-emotional stimuli. The present study examined emotional facial expression recognition abilities in 20 non-demented patients with PD and 23 control participants relative to their performances on a non-emotional landscape categorization test with comparable task requirements. We found that PD participants were normal on the control task but exhibited selective impairments in the recognition of facial emotion, specifically for anger (driven by those with right hemisphere pathology) and surprise (driven by those with left hemisphere pathology), even when controlling for depression level. Male but not female PD participants further displayed specific deficits in the recognition of fearful expressions. We suggest that the neural substrates that may subserve these impairments include the ventral striatum, amygdala, and prefrontal cortices. Finally, we observed that in PD participants, deficiencies in facial emotion recognition correlated with higher levels of interpersonal distress, which calls attention to the significant psychosocial impact that facial emotion recognition impairments may have on individuals with PD. PMID:18485422

Atypical development of configural face recognition in children with autism, Down syndrome and Williams syndrome.

PubMed

Dimitriou, D; Leonard, H C; Karmiloff-Smith, A; Johnson, M H; Thomas, M S C

2015-05-01

Configural processing in face recognition is a sensitivity to the spacing between facial features. It has been argued both that its presence represents a high level of expertise in face recognition, and also that it is a developmentally vulnerable process. We report a cross-syndrome investigation of the development of configural face recognition in school-aged children with autism, Down syndrome and Williams syndrome compared with a typically developing comparison group. Cross-sectional trajectory analyses were used to compare configural and featural face recognition utilising the 'Jane faces' task. Trajectories were constructed linking featural and configural performance either to chronological age or to different measures of mental age (receptive vocabulary, visuospatial construction), as well as the Benton face recognition task. An emergent inversion effect across age for detecting configural but not featural changes in faces was established as the marker of typical development. Children from clinical groups displayed atypical profiles that differed across all groups. We discuss the implications for the nature of face processing within the respective developmental disorders, and how the cross-sectional syndrome comparison informs the constraints that shape the typical development of face recognition. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Chirally directed formation of nanometer-scale proline clusters.

PubMed

Myung, Sunnie; Fioroni, Marco; Julian, Ryan R; Koeniger, Stormy L; Baik, Mu-Hyun; Clemmer, David E

2006-08-23

Ion mobility measurements, combined with molecular mechanics simulations, are used to study enantiopure and racemic proline clusters formed by electrospray ionization. Broad distributions of cluster sizes and charge states are observed, ranging from clusters containing only a few proline units to clusters that contain more than 100 proline units (i.e., protonated clusters of the form [xPro + nH](n+) with x = 1 to >100 and n = 1-7). As the sizes of clusters increase, there is direct evidence for nanometer scale, chirally induced organization into specific structures. For n = 4 and 5, enantiopure clusters of approximately 50 to 100 prolines assemble into structures that are more elongated than the most compact structure that is observed from the racemic proline clusters. A molecular analogue, cis-4-hydroxy-proline, displays significantly different behavior, indicating that in addition to the rigidity of the side chain ring, intermolecular interactions are important in the formation of chirally directed clusters. This is the first case in which assemblies of chirally selective elongated structures are observed in this size range of amino acid clusters. Relationships between enantiopurity, cluster shape, and overall energetics are discussed.

Lateral flow assay for rapid detection of white spot syndrome virus (WSSV) using a phage-displayed peptide as bio-recognition probe.

PubMed

Kulabhusan, Prabir Kumar; Rajwade, Jyutika M; Sahul Hameed, A S; Paknikar, Kishore M

2017-06-01

White spot disease caused by the white spot syndrome virus (WSSV) has a major socio-economic impact on shrimp farming in India. It has been realized that a field-usable diagnostic capable of rapid detection of WSSV can prevent huge economic losses in disease outbreaks. In this work, we explored the possibility of using a peptide as bio-recognition probe in a field-usable device for the detection of WSSV from infected shrimps and prawns. A commercially available random phage-display library was screened against rVP28 (a major structural protein of WSSV, expressed as a recombinant protein in Escherichia coli). A bacteriophage clone VP28-4L was obtained, and its binding to purified rVP28 protein as well as WSSV from infected shrimp Litopaeneus vannamei tissue was confirmed by ELISA and western blot. The apparent equilibrium dissociation constant (K d ,app) was calculated to be 810 nM. VP28-4L did not show cross-reactivity with any other shrimp viruses. A 12-mer peptide (pep28, with the sequence 'TFQAFDLSPFPS') displayed on the VP28-4L was synthesized, and its diagnostic potential was evaluated in a lateral flow assay (LFA). Visual detection of WSSV could be achieved using biotinylated-pep28 and streptavidin-conjugated gold nanoparticles. In LFA, 12.5 μg/mL of the virus could be detected from L. vannamei gill tissue homogenate within 20 min. Pep28 thus becomes an attractive candidate in bio-recognition of WSSV in field-usable diagnostic platforms benefitting the aquaculture sector.

Comparing object recognition from binary and bipolar edge images for visual prostheses.

PubMed

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2016-11-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition.

Syntheses, structures and characterizations of three novel vanadium selenites with organically bonded copper/nickel complex

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

Qian, Cheng; State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002; Kong, Fang

2016-06-15

A series of vanadium selenites covalently bonded with metal-organic complex, namely, Ni(2,2-bipy){sub 2}V{sub 2}O{sub 4}(SeO{sub 3}){sub 2} (1), Cu(2,2-bipy)V{sub 2}O{sub 4}(SeO{sub 3}){sub 2}·0.5H{sub 2}O (2) and Cu{sub 2}(2,2-bipy){sub 2}V{sub 5}O{sub 12}(SeO{sub 3}){sub 2} (3) (2,2-bipy=2,2-bipyridine) have been hydrothermally synthesized and structurally characterized. They exhibit three different structural dimensions, from 0D cluster, 1D chain to 2D layer. Compound 1 features a 0D {Ni(2,2-bipy)_2V_2O_4(SeO_3)_2}{sub 2} dimeric cluster composed of two {Ni(2,2-bipy)_2}{sup 2+} moieties connected by the {V_4O_8(SeO_3)_4}{sup 4-} cluster. Compound 2 shows a 1D {Cu(2,2-bipy)V_2O_4(SeO_3)_2}{sub n} chain in which the {Cu_2(2,2-bipy)_2}{sup 4+} moieties are bridged by the {V_4O_8(SeO_3)_4}{sup 4−} clusters. Compound 3more » displays a 2D structure consisted of mixed valence vanadium selenites layers {V"I"VV"V_4Se"I"V_2O_1_8}{sub n}{sup 4−} and {Cu(2,2-bipy)}{sup 2+} complex moieties. The adjacent layers are further interconnected via π-π interactions between the 2,2-bipy ligands exhibiting an interesting 3D supramolecular architecture. Both compound 1 and 2 contain a new {V_4O_8(SeO_3)_4}{sup 4−} cluster and compound 3 exhibits the first 2D vanadate polyhedral layer in vanadium selenites/tellurites with organic moieties. - Graphical abstract: We got three new vanadium selenites with organically linked copper/nickel complex, namely, Ni(2,2-bipy){sub 2}V{sub 2}O{sub 4}(SeO{sub 3}){sub 2} (1), Cu(2,2-bipy)V{sub 2}O{sub 4}(SeO{sub 3}){sub 2}·0.5H{sub 2}O (2) and Cu{sub 2}(2,2-bipy){sub 2}V{sub 5}O{sub 12}(SeO{sub 3}){sub 2} (3) by hydrothermally syntheses. They display three different structural dimensions, from 0D cluster, to 1D chain and 2D layer. Display Omitted - Highlights: • Three new compounds display three different structural dimensions, from 0D cluster, to 1D chain and 2D layer. • The Tetranuclear {V_4O_8(SeO_3)_4}{sup 4−} cluster and the vanadate {V_5O_1_7}{sub n} 2D layer are observed firstly. • Optical Properties and Magnetic Properties of three compounds are reported.« less

Identifying typical patterns of vulnerability: A 5-step approach based on cluster analysis

NASA Astrophysics Data System (ADS)

Sietz, Diana; Lüdeke, Matthias; Kok, Marcel; Lucas, Paul; Carsten, Walther; Janssen, Peter

2013-04-01

Specific processes that shape the vulnerability of socio-ecological systems to climate, market and other stresses derive from diverse background conditions. Within the multitude of vulnerability-creating mechanisms, distinct processes recur in various regions inspiring research on typical patterns of vulnerability. The vulnerability patterns display typical combinations of the natural and socio-economic properties that shape a systems' vulnerability to particular stresses. Based on the identification of a limited number of vulnerability patterns, pattern analysis provides an efficient approach to improving our understanding of vulnerability and decision-making for vulnerability reduction. However, current pattern analyses often miss explicit descriptions of their methods and pay insufficient attention to the validity of their groupings. Therefore, the question arises as to how do we identify typical vulnerability patterns in order to enhance our understanding of a systems' vulnerability to stresses? A cluster-based pattern recognition applied at global and local levels is scrutinised with a focus on an applicable methodology and practicable insights. Taking the example of drylands, this presentation demonstrates the conditions necessary to identify typical vulnerability patterns. They are summarised in five methodological steps comprising the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. Reflecting scale-dependent opportunities, a global study is able to support decision-making with insights into the up-scaling of interventions when available funds are limited. In contrast, local investigations encourage an outcome-based validation. This constitutes a crucial step in establishing the credibility of the patterns and hence their suitability for informing extension services and individual decisions. In this respect, working at the local level provides a clear advantage since, to a large extent, limitations in globally available observational data constrain such a validation on the global scale. Overall, the five steps are outlined in detail in order to facilitate and motivate the application of pattern recognition in other research studies concerned with vulnerability analysis, including future applications to different vulnerability frameworks. Such applications could promote the refinement of mechanisms in specific contexts and advance methodological adjustments. This would further increase the value of identifying typical patterns in the properties of socio-ecological systems for an improved understanding and management of the relation between these systems and particular stresses.

Clustering of risk factors for chronic diseases among adolescents from Southern Brazil

PubMed Central

Dumith, Samuel C.; Muniz, Ludmila C.; Tassitano, Rafael M.; Hallal, Pedro C.; Menezes, Ana M.B.

2012-01-01

Objective To investigate the clustering of risk behaviors for chronic non-communicable diseases and their associated factors among adolescents from Southern Brazil. Methods In 2008, a survey was conducted with 3990 adolescents aged 14–15 years (mean: 14.3; SD: 0.6) from the 1993 Pelotas Birth Cohort Study. Clustering was determined by comparing observed (O) and expected (E) prevalence of all possible combinations of the four risk factors investigated (smoking, alcohol intake, low fruit intake, and physical inactivity). We carried out Poisson regression to evaluate the effect of individual characteristics on the presence of at least three risk behaviors. Results All risk factors tended to cluster together (O/E prevalence = 3.0), especially smoking and alcohol intake (odds ratio to present on behavior in the presence of other > 5.0). Approximately 15% of adolescents displayed three or more risk behaviors. Females (adjusted OR = 1.55), people 15 years and older (OR = 1.47), with black skin color (OR = 1.23), and of low socioeconomic level (OR = 1.29) were more likely to display three or more risk factors. Conclusion These findings suggest that lifestyle-related risk factors tend to cluster among adolescents. Identifying subgroups at greater risk of simultaneously engaging in multiple risk behaviors may aid in the planning of preventive strategies. PMID:22484392

Kron 3: a fourth intermediate age cluster in the SMC with evidence of multiple populations

NASA Astrophysics Data System (ADS)

Hollyhead, K.; Lardo, C.; Kacharov, N.; Bastian, N.; Hilker, M.; Rejkuba, M.; Koch, A.; Grebel, E. K.; Georgiev, I.

2018-05-01

We present the results of a spectroscopic study of the intermediate age (≈6.5 Gyr) massive cluster Kron 3 in the Small Magellanic Cloud. We measure CN and CH band strengths (at ≃3839 and 4300 Å, respectively) using VLT FORS2 spectra of 16 cluster members and find a sub-population of five stars enriched in nitrogen. We conclude that this is evidence for multiple populations in Kron 3, the fourth intermediate age cluster, after Lindsay 1, NGC 416 and NGC 339 (ages 6-8 Gyr), to display this phenomenon originally thought to be a unique characteristic of old globular clusters. At ≈6.5 Gyr this is one of the youngest clusters with multiple populations, indicating that the mechanism responsible for their onset must operate until a redshift of at least 0.75, much later than the peak of globular cluster formation at redshift ˜3.

Saccadic movement deficiencies in adults with ADHD tendencies.

PubMed

Lee, Yun-Jeong; Lee, Sangil; Chang, Munseon; Kwak, Ho-Wan

2015-12-01

The goal of the present study was to explore deficits in gaze detection and emotional value judgment during a saccadic eye movement task in adults with attention deficit/hyperactivity disorder (ADHD) tendencies. Thirty-two participants, consisting of 16 ADHD tendencies and 16 controls, were recruited from a pool of 243 university students. Among the many problems in adults with ADHDs, our research focused on the deficits in the processing of nonverbal cues, such as gaze direction and the emotional value of others' faces. In Experiment 1, a cue display containing a face with emotional value and gaze direction was followed by a target display containing two faces located on the left and right side of the display. The participant's task was to make an anti-saccade opposite to the gaze direction if the cue face was not emotionally neutral. ADHD tendencies showed more overall errors than controls in making anti-saccades. Based on the hypothesis that the exposure duration of the cue display in Experiment 1 may have been too long, we presented the cue and target display simultaneously to prevent participants from preparing saccades in advance. Participants in Experiment 2 were asked to make either a pro-saccade or an anti-saccade depending on the emotional value of the central cue face. Interestingly, significant group differences were observed for errors of omission and commission. In addition, a significant three-way interaction among groups, cue emotion, and target gaze direction suggests that the emotional recognition and gaze control systems might somehow be interconnected. The result also shows that ADHDs are more easily distracted by a task-irrelevant gaze direction. Taken together, these results suggest that tasks requiring both response inhibition (anti-saccade) and gaze-emotion recognition might be useful in developing a diagnostic test for discriminating adults with ADHDs from healthy adults.

Is it worth changing pattern recognition methods for structural health monitoring?

NASA Astrophysics Data System (ADS)

Bull, L. A.; Worden, K.; Cross, E. J.; Dervilis, N.

2017-05-01

The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data.

Cross domains Arabic named entity recognition system

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Isochrone Fittings for the Open Star Clusters NGC 3680 and Melotte 66

NASA Astrophysics Data System (ADS)

Guillemaud, Nikolas; Frinchaboy, P. M.; Thompson, B. A.

2013-01-01

I will be displaying the results from isochrone fittings on two open star clusters. The stellar evolution models used to generate the isochrones are from Dartmouth (Dotter et al. 2007) and Padova (Mango et al. 2008). Both of the models were applied to two star clusters: NGC 3680 and Melotte 66. The analysis is performed by utilizing infrared observations from the CPAPIR instrument; which is operated in conjunction with CTIO’s 1.5m telescope. This research was made possible by the NSF’s REU grant; award number 0851558.

Expert Behavior in Children's Video Game Play.

ERIC Educational Resources Information Center

VanDeventer, Stephanie S.; White, James A.

2002-01-01

Investigates the display of expert behavior by seven outstanding video game-playing children ages 10 and 11. Analyzes observation and debriefing transcripts for evidence of self-monitoring, pattern recognition, principled decision making, qualitative thinking, and superior memory, and discusses implications for educators regarding the development…

Reevaluating split-fovea processing in word recognition: hemispheric dominance, retinal location, and the word-nonword effect.

PubMed

Jordan, Timothy R; Paterson, Kevin B; Kurtev, Stoyan

2009-03-01

Many studies have claimed that hemispheric projections are split precisely at the foveal midline and so hemispheric asymmetry affects word recognition right up to the point of fixation. To investigate this claim, four-letter words and nonwords were presented to the left or right of fixation, either close to fixation in foveal vision or farther from fixation in extrafoveal vision. Presentation accuracy was controlled using an eyetracker linked to a fixation-contingent display. Words presented foveally produced identical performance on each side of fixation, but words presented extrafoveally showed a clear left-hemisphere (LH) advantage. Nonwords produced no evidence of hemispheric asymmetry in any location. Foveal stimuli also produced an identical word-nonword effect on each side of fixation, whereas extrafoveal stimuli produced a word-nonword effect only for LH (not right-hemisphere) displays. These findings indicate that functional unilateral projections to contralateral hemispheres exist in extrafoveal locations but provide no evidence of a functional division in hemispheric processing at fixation.

Sex differences in the ability to recognise non-verbal displays of emotion: a meta-analysis.

PubMed

Thompson, Ashley E; Voyer, Daniel

2014-01-01

The present study aimed to quantify the magnitude of sex differences in humans' ability to accurately recognise non-verbal emotional displays. Studies of relevance were those that required explicit labelling of discrete emotions presented in the visual and/or auditory modality. A final set of 551 effect sizes from 215 samples was included in a multilevel meta-analysis. The results showed a small overall advantage in favour of females on emotion recognition tasks (d=0.19). However, the magnitude of that sex difference was moderated by several factors, namely specific emotion, emotion type (negative, positive), sex of the actor, sensory modality (visual, audio, audio-visual) and age of the participants. Method of presentation (computer, slides, print, etc.), type of measurement (response time, accuracy) and year of publication did not significantly contribute to variance in effect sizes. These findings are discussed in the context of social and biological explanations of sex differences in emotion recognition.

Segregation and persistence of form in the lateral occipital complex.

PubMed

Ferber, Susanne; Humphrey, G Keith; Vilis, Tutis

2005-01-01

While the lateral occipital complex (LOC) has been shown to be implicated in object recognition, it is unclear whether this brain area is responsive to low-level stimulus-driven features or high-level representational processes. We used scrambled shape-from-motion displays to disambiguate the presence of contours from figure-ground segregation and to measure the strength of the binding process for shapes without contours. We found persisting brain activation in the LOC for scrambled displays after the motion stopped indicating that this brain area subserves and maintains figure-ground segregation processes, a low-level function in the object processing hierarchy. In our second experiment, we found that the figure-ground segregation process has some form of spatial constancy indicating top-down influences. The persisting activation after the motion stops suggests an intermediate role in object recognition processes for this brain area and might provide further evidence for the idea that the lateral occipital complex subserves mnemonic functions mediating between iconic and short-term memory.

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

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

PubMed

Marsh, Abigail A; Blair, R J R

2008-01-01

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

USSR Report, Space

DTIC Science & Technology

1984-10-26

at a - speed of about 515 km/s, in the direction of the nearest galaxy cluster in the constellation Virgo , but not precisely at the cluster . The...Joint Publications Research Service, 1000 North Glebe Road, Arlington, Virginia 22201. Soviet books and journal articles displaying a copyright...8217 Experiment (I. A. Strukov; ZEMLYA I VSELENNAYA, No 4, Jul-Aug 84).. 46 Astrometry Research at Pulkovo Observatory (G. Oshin? VECHERNIY LENINGRAD

Patterns of Physical and Relational Aggression in a School-Based Sample of Boys and Girls

ERIC Educational Resources Information Center

Crapanzano, Ann Marie; Frick, Paul J.; Terranova, Andrew M.

2010-01-01

The current study investigated the patterns of aggressive behavior displayed in a sample of 282 students in the 4th through 7th grades (M age = 11.28; SD = 1.82). Using cluster analyses, two distinct patterns of physical aggression emerged for both boys and girls with one aggressive cluster showing mild levels of reactive aggression and one group…

A triboelectric motion sensor in wearable body sensor network for human activity recognition.

PubMed

Hui Huang; Xian Li; Ye Sun

2016-08-01

The goal of this study is to design a novel triboelectric motion sensor in wearable body sensor network for human activity recognition. Physical activity recognition is widely used in well-being management, medical diagnosis and rehabilitation. Other than traditional accelerometers, we design a novel wearable sensor system based on triboelectrification. The triboelectric motion sensor can be easily attached to human body and collect motion signals caused by physical activities. The experiments are conducted to collect five common activity data: sitting and standing, walking, climbing upstairs, downstairs, and running. The k-Nearest Neighbor (kNN) clustering algorithm is adopted to recognize these activities and validate the feasibility of this new approach. The results show that our system can perform physical activity recognition with a successful rate over 80% for walking, sitting and standing. The triboelectric structure can also be used as an energy harvester for motion harvesting due to its high output voltage in random low-frequency motion.

Practical automatic Arabic license plate recognition system

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Agaian, Sos; Saleh, Hani

2011-02-01

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

Chaotic map clustering algorithm for EEG analysis

NASA Astrophysics Data System (ADS)

Bellotti, R.; De Carlo, F.; Stramaglia, S.

2004-03-01

The non-parametric chaotic map clustering algorithm has been applied to the analysis of electroencephalographic signals, in order to recognize the Huntington's disease, one of the most dangerous pathologies of the central nervous system. The performance of the method has been compared with those obtained through parametric algorithms, as K-means and deterministic annealing, and supervised multi-layer perceptron. While supervised neural networks need a training phase, performed by means of data tagged by the genetic test, and the parametric methods require a prior choice of the number of classes to find, the chaotic map clustering gives a natural evidence of the pathological class, without any training or supervision, thus providing a new efficient methodology for the recognition of patterns affected by the Huntington's disease.

Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime

PubMed Central

Hubble, Kelly; Bowen, Katharine L.; Moore, Simon C.; van Goozen, Stephanie H. M.

2015-01-01

Background Children with antisocial behaviour show deficits in the perception of emotional expressions in others that may contribute to the development and persistence of antisocial and aggressive behaviour. Current treatments for antisocial youngsters are limited in effectiveness. It has been argued that more attention should be devoted to interventions that target neuropsychological correlates of antisocial behaviour. This study examined the effect of emotion recognition training on criminal behaviour. Methods Emotion recognition and crime levels were studied in 50 juvenile offenders. Whilst all young offenders received their statutory interventions as the study was conducted, a subgroup of twenty-four offenders also took part in a facial affect training aimed at improving emotion recognition. Offenders in the training and control groups were matched for age, SES, IQ and lifetime crime level. All offenders were tested twice for emotion recognition performance, and recent crime data were collected after the testing had been completed. Results Before the training there were no differences between the groups in emotion recognition, with both groups displaying poor fear, sadness and anger recognition. After the training fear, sadness and anger recognition improved significantly in juvenile offenders in the training group. Although crime rates dropped in all offenders in the 6 months following emotion testing, only the group of offenders who had received the emotion training showed a significant reduction in the severity of the crimes they committed. Conclusions The study indicates that emotion recognition can be relatively easily improved in youths who engage in serious antisocial and criminal behavior. The results suggest that improved emotion recognition has the potential to reduce the severity of reoffending. PMID:26121148

Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime.

PubMed

Hubble, Kelly; Bowen, Katharine L; Moore, Simon C; van Goozen, Stephanie H M

2015-01-01

Children with antisocial behaviour show deficits in the perception of emotional expressions in others that may contribute to the development and persistence of antisocial and aggressive behaviour. Current treatments for antisocial youngsters are limited in effectiveness. It has been argued that more attention should be devoted to interventions that target neuropsychological correlates of antisocial behaviour. This study examined the effect of emotion recognition training on criminal behaviour. Emotion recognition and crime levels were studied in 50 juvenile offenders. Whilst all young offenders received their statutory interventions as the study was conducted, a subgroup of twenty-four offenders also took part in a facial affect training aimed at improving emotion recognition. Offenders in the training and control groups were matched for age, SES, IQ and lifetime crime level. All offenders were tested twice for emotion recognition performance, and recent crime data were collected after the testing had been completed. Before the training there were no differences between the groups in emotion recognition, with both groups displaying poor fear, sadness and anger recognition. After the training fear, sadness and anger recognition improved significantly in juvenile offenders in the training group. Although crime rates dropped in all offenders in the 6 months following emotion testing, only the group of offenders who had received the emotion training showed a significant reduction in the severity of the crimes they committed. The study indicates that emotion recognition can be relatively easily improved in youths who engage in serious antisocial and criminal behavior. The results suggest that improved emotion recognition has the potential to reduce the severity of reoffending.

Preparation and Counseling for the World of Work: Supplement.

ERIC Educational Resources Information Center

Fort Benton Public Schools, MT.

The supplementary curriculum guide is designed to assist elementary classroom teachers in presenting a career education program based on: recognition of student needs, integration of career oriented mini-courses into the curriculum, relation to job clusters, and development of guidance concepts and methods. Coordinated with CE 005 139,…

Collected Notes on the Workshop for Pattern Discovery in Large Databases

NASA Technical Reports Server (NTRS)

Buntine, Wray (Editor); Delalto, Martha (Editor)

1991-01-01

These collected notes are a record of material presented at the Workshop. The core data analysis is addressed that have traditionally required statistical or pattern recognition techniques. Some of the core tasks include classification, discrimination, clustering, supervised and unsupervised learning, discovery and diagnosis, i.e., general pattern discovery.

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

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

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

Multi-exemplar affinity propagation.

PubMed

Wang, Chang-Dong; Lai, Jian-Huang; Suen, Ching Y; Zhu, Jun-Yong

2013-09-01

The affinity propagation (AP) clustering algorithm has received much attention in the past few years. AP is appealing because it is efficient, insensitive to initialization, and it produces clusters at a lower error rate than other exemplar-based methods. However, its single-exemplar model becomes inadequate when applied to model multisubclasses in some situations such as scene analysis and character recognition. To remedy this deficiency, we have extended the single-exemplar model to a multi-exemplar one to create a new multi-exemplar affinity propagation (MEAP) algorithm. This new model automatically determines the number of exemplars in each cluster associated with a super exemplar to approximate the subclasses in the category. Solving the model is NP-hard and we tackle it with the max-sum belief propagation to produce neighborhood maximum clusters, with no need to specify beforehand the number of clusters, multi-exemplars, and superexemplars. Also, utilizing the sparsity in the data, we are able to reduce substantially the computational time and storage. Experimental studies have shown MEAP's significant improvements over other algorithms on unsupervised image categorization and the clustering of handwritten digits.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping.

PubMed

Mukherjee, Sumanta; Warwicker, Jim; Chandra, Nagasuma

2015-07-01

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

[Research on automatic external defibrillator based on DSP].

PubMed

Jing, Jun; Ding, Jingyan; Zhang, Wei; Hong, Wenxue

2012-10-01

Electrical defibrillation is the most effective way to treat the ventricular tachycardia (VT) and ventricular fibrillation (VF). An automatic external defibrillator based on DSP is introduced in this paper. The whole design consists of the signal collection module, the microprocessor controlingl module, the display module, the defibrillation module and the automatic recognition algorithm for VF and non VF, etc. This automatic external defibrillator has achieved goals such as ECG signal real-time acquisition, ECG wave synchronous display, data delivering to U disk and automatic defibrillate when shockable rhythm appears, etc.

Mammalian Fe-S proteins: definition of a consensus motif recognized by the co-chaperone HSC20.

PubMed

Maio, N; Rouault, T A

2016-10-01

Iron-sulfur (Fe-S) clusters are inorganic cofactors that are fundamental to several biological processes in all three kingdoms of life. In most organisms, Fe-S clusters are initially assembled on a scaffold protein, ISCU, and subsequently transferred to target proteins or to intermediate carriers by a dedicated chaperone/co-chaperone system. The delivery of assembled Fe-S clusters to recipient proteins is a crucial step in the biogenesis of Fe-S proteins, and, in mammals, it relies on the activity of a multiprotein transfer complex that contains the chaperone HSPA9, the co-chaperone HSC20 and the scaffold ISCU. How the transfer complex efficiently engages recipient Fe-S target proteins involves specific protein interactions that are not fully understood. This mini review focuses on recent insights into the molecular mechanism of amino acid motif recognition and discrimination by the co-chaperone HSC20, which guides Fe-S cluster delivery.

A commentary on perception-action relationships in spatial display instruments

NASA Technical Reports Server (NTRS)

Shebilske, Wayne L.

1989-01-01

Transfer of information across disciplines is promoted, while basic and applied researchers are cautioned about the danger of assuming simple relationships between stimulus information, perceptual impressions, and performance including pattern recognition and sensorimotor skills. A theoretical and empirical foundation was developed predicting those relationships.

High Tech and Library Access for People with Disabilities.

ERIC Educational Resources Information Center

Roatch, Mary A.

1992-01-01

Describes tools that enable people with disabilities to access print information, including optical character recognition, synthetic voice output, other input devices, Braille access devices, large print displays, television and video, TDD (Telecommunications Devices for the Deaf), and Telebraille. Use of technology by libraries to meet mandates…

Recognizing Emotion in Faces: Developmental Effects of Child Abuse and Neglect.

ERIC Educational Resources Information Center

Pollak, Seth D.; Cicchetti, Dante; Hornung, Katherine; Reed, Alex

2000-01-01

Two experiments assessed recognition of emotion among physically abused and neglected preschoolers. Results showed that neglected children had more difficulty discriminating emotional expressions that control or abused children. Abused children displayed response bias for angry facial expressions. Control children viewed discrete emotions as…

Research for Key Techniques of Geophysical Recognition System of Hydrocarbon-induced Magnetic Anomalies Based on Hydrocarbon Seepage Theory

NASA Astrophysics Data System (ADS)

Zhang, L.; Hao, T.; Zhao, B.

2009-12-01

Hydrocarbon seepage effects can cause magnetic alteration zones in near surface, and the magnetic anomalies induced by the alteration zones can thus be used to locate oil-gas potential regions. In order to reduce the inaccuracy and multi-resolution of the hydrocarbon anomalies recognized only by magnetic data, and to meet the requirement of integrated management and sythetic analysis of multi-source geoscientfic data, it is necessary to construct a recognition system that integrates the functions of data management, real-time processing, synthetic evaluation, and geologic mapping. In this paper research for the key techniques of the system is discussed. Image processing methods can be applied to potential field images so as to make it easier for visual interpretation and geological understanding. For gravity or magnetic images, the anomalies with identical frequency-domain characteristics but different spatial distribution will reflect differently in texture and relevant textural statistics. Texture is a description of structural arrangements and spatial variation of a dataset or an image, and has been applied in many research fields. Textural analysis is a procedure that extracts textural features by image processing methods and thus obtains a quantitative or qualitative description of texture. When the two kinds of anomalies have no distinct difference in amplitude or overlap in frequency spectrum, they may be distinguishable due to their texture, which can be considered as textural contrast. Therefore, for the recognition system we propose a new “magnetic spots” recognition method based on image processing techniques. The method can be divided into 3 major steps: firstly, separate local anomalies caused by shallow, relatively small sources from the total magnetic field, and then pre-process the local magnetic anomaly data by image processing methods such that magnetic anomalies can be expressed as points, lines and polygons with spatial correlation, which includes histogram-equalization based image display, object recognition and extraction; then, mine the spatial characteristics and correlations of the magnetic anomalies using textural statistics and analysis, and study the features of known anomalous objects (closures, hydrocarbon-bearing structures, igneous rocks, etc.) in the same research area; finally, classify the anomalies, cluster them according to their similarity, and predict hydrocarbon induced “magnetic spots” combined with geologic, drilling and rock core data. The system uses the ArcGIS as the secondary development platform, inherits the basic functions of the ArcGIS, and develops two main sepecial functional modules, the module for conventional potential-field data processing methods and the module for feature extraction and enhancement based on image processing and analysis techniques. The system can be applied to realize the geophysical detection and recognition of near-surface hydrocarbon seepage anomalies, provide technical support for locating oil-gas potential regions, and promote geophysical data processing and interpretation to advance more efficiently.

A Recombinant Antibody with the Antigen-Specific, Major Histocompatibility Complex-Restricted Specificity of T Cells

NASA Astrophysics Data System (ADS)

Andersen, Peter S.; Stryhn, Anette; Hansen, Bjarke E.; Fugger, Lars; Engberg, Jan; Buus, Soren

1996-03-01

Specific recognition of peptide/major histocompatibility complex (MHC) molecule complexes by the T-cell receptor is a key reaction in the specific immune response. Antibodies against peptide/MHC complexes would therefore be valuable tools in studying MHC function and T-cell recognition and might lead to novel approaches in immunotherapy. However, it has proven difficult to generate antibodies with the specificity of T cells by conventional hybridoma techniques. Here we report that the phage display technology is a feasible alternative to generate antibodies recognizing specific, predetermined peptide/MHC complexes.

Mathematical morphology-based shape feature analysis for Chinese character recognition systems

NASA Astrophysics Data System (ADS)

Pai, Tun-Wen; Shyu, Keh-Hwa; Chen, Ling-Fan; Tai, Gwo-Chin

1995-04-01

This paper proposes an efficient technique of shape feature extraction based on the application of mathematical morphology theory. A new shape complexity index for preclassification of machine printed Chinese Character Recognition (CCR) is also proposed. For characters represented in different fonts/sizes or in a low resolution environment, a more stable local feature such as shape structure is preferred for character recognition. Morphological valley extraction filters are applied to extract the protrusive strokes from four sides of an input Chinese character. The number of extracted local strokes reflects the shape complexity of each side. These shape features of characters are encoded as corresponding shape complexity indices. Based on the shape complexity index, data base is able to be classified into 16 groups prior to recognition procedures. The performance of associating with shape feature analysis reclaims several characters from misrecognized character sets and results in an average of 3.3% improvement of recognition rate from an existing recognition system. In addition to enhance the recognition performance, the extracted stroke information can be further analyzed and classified its own stroke type. Therefore, the combination of extracted strokes from each side provides a means for data base clustering based on radical or subword components. It is one of the best solutions for recognizing high complexity characters such as Chinese characters which are divided into more than 200 different categories and consist more than 13,000 characters.

The Hierarchical Brain Network for Face Recognition

PubMed Central

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level. PMID:23527282

Biochemical and genetic characterization of the vanC-2 vancomycin resistance gene cluster of Enterococcus casseliflavus ATCC 25788.

PubMed

Dutta, Ireena; Reynolds, Peter E

2002-10-01

The vanC-2 cluster of Enterococcus casseliflavus ATCC 25788 consisted of five genes (vanC-2, vanXY(C-2), vanT(C-2), vanR(C-2), and vanS(C-2)) and shared the same organization as the vanC cluster of E. gallinarum BM4174. The proteins encoded by these genes displayed a high degree of amino acid identity to the proteins encoded within the vanC gene cluster. The putative D,D-dipeptidase-D,D-carboxypeptidase, VanXY(C-2), exhibited 81% amino acid identity to VanXY(C), and VanT(C-2) displayed 65% amino acid identity to the serine racemase, VanT. VanR(C-2) and VanS(C-2) displayed high degrees of identity to VanR(C) and VanS(C), respectively, and contained the conserved residues identified as important to their function as a response regulator and histidine kinase, respectively. Resistance to vancomycin was expressed inducibly in E. casseliflavus ATCC 25788 and required an extended period of induction. Analysis of peptidoglycan precursors revealed that UDP-N-acetylmuramyl-L-Ala-delta-D-Glu-L-Lys-D-Ala-D-Ser could not be detected until several hours after the addition of vancomycin, and its appearance coincided with the resumption of growth. The introduction of additional copies of the vanT(C-2) gene, encoding a putative serine racemase, and the presence of supplementary D-serine in the growth medium both significantly reduced the period before growth resumed after addition of vancomycin. This suggested that the availability of D-serine plays an important role in the induction process.

An exploratory study on cultural variations in oral health attitudes, behaviour and values of freshman (first-year) dental students.

PubMed

Kawamura, M; Wright, F A C; Declerck, D; Freire, M C M; Hu, D Y; Honkala, E; Lévy, G; Kalwitzki, M; Polychronopoulou, A; Yip, H K; Kinirons, M J; Eli, I; Petti, S; Komabayashi, T; Kim, K J; Razak, A A A; Srisilapanan, P; Kwan, S Y L

2005-08-01

To identify similarities and differences in oral health attitudes, behaviour and values among freshman dental students. Cross-cultural survey of dental students. 18 cultural areas. 904 first-year dental students completed the Hiroshima University-Dental Behavioural Inventory (HU-DBI) translated into their own languages. Individual areas were clustered by similarity in responses to the questions. The first group displayed an 'occidental-culture orientation' with the exception of Brazil (Cluster 1 comprised: Australia, United Kingdom, Ireland, Belgium and Brazil, Cluster 2: Germany, Italy, Finland and France). The second group displayed an 'oriental-cultural orientation' with the exception of Greece and Israel (Cluster 3 comprised: China and Indonesia, and Cluster 4: Japan, Korea, Israel, Hong Kong, Malaysia, Thailand and Greece). Australia and United Kingdom were the countries that were most alike. Ireland was the 'neighbour' to these countries. Greece and Malaysia had similar patterns of oral health behaviour although geographic conditions are very different. Although it was considered that in Hong Kong, occidental nations have affected the development of education, it remained in the oriental-culture group. Comparison with the data from the occidentals indicates that a higher percentage of the orientals put off going to the dentist until they have toothache (p < 0.001). Only a small proportion of the occidentals (8%) reported a perception of inevitability in having false teeth, whereas 33% of the orientals held this fatalistic belief (p = 0.001). Grouping the countries into key cultural orientations and international clusters yielded plausible results, using the HU-DBI.

Cluster formation by allelomimesis in real-world complex adaptive systems

NASA Astrophysics Data System (ADS)

Juanico, Dranreb Earl; Monterola, Christopher; Saloma, Caesar

2005-04-01

Animal and human clusters are complex adaptive systems and many organize in cluster sizes s that obey the frequency distribution D(s)∝s-τ . The exponent τ describes the relative abundance of the cluster sizes in a given system. Data analyses reveal that real-world clusters exhibit a broad spectrum of τ values, 0.7 (tuna fish schools) ⩽τ⩽4.61 (T4 bacteriophage gene family sizes). Allelomimesis is proposed as an underlying mechanism for adaptation that explains the observed broad τ spectrum. Allelomimesis is the tendency of an individual to imitate the actions of others and two cluster systems have different τ values when their component agents display unequal degrees of allelomimetic tendencies. Cluster formation by allelomimesis is shown to be of three general types: namely, blind copying, information-use copying, and noncopying. Allelomimetic adaptation also reveals that the most stable cluster size is formed by three strongly allelomimetic individuals. Our finding is consistent with available field data taken from killer whales and marmots.

Evaluation of iconic versus F-map microburst displays

NASA Technical Reports Server (NTRS)

Salzberger, Mark; Hansman, R. John; Wanke, Craig

1994-01-01

Previous studies have shown graphical presentation methods of hazardous wind shear to be superior to textual or audible warnings alone. Positional information and the strength of the hazard were observed to be and were cited by pilots as the most important factors in a display. In this experiment the use of the three different graphical presentations of hazardous wind shear are examined. Airborne predictive detectors of wind shear enable the dissemination of varying levels of information. The effectiveness of iconic and mapping display modes of different complexities are addressed through simulation and analysis. Different positional and time-varying situations are presented in a 'part-task' Boeing 767 simulator using data from actual microburst events. Experienced airline pilots fly approach profiles using both iconic and F-map wind shear alerting displays. Microburst accompanied each event is also shown to the pilot. Mapping display types are expected to be found exceptionally efficient at conveying location comparison information while iconic displays simplify the threat recognition process. Preliminary results from the simulator study are presented. Recommendations concerning the suitability of multilevel iconic and mapping displays are made. Situational problems with current display prototypes are also addressed.

Cross-cultural evidence that the nonverbal expression of pride is an automatic status signal.

PubMed

Tracy, Jessica L; Shariff, Azim F; Zhao, Wanying; Henrich, Joseph

2013-02-01

To test whether the pride expression is an implicit, reliably developing signal of high social status in humans, the authors conducted a series of experiments that measured implicit and explicit cognitive associations between pride displays and high-status concepts in two culturally disparate populations--North American undergraduates and Fijian villagers living in a traditional, small-scale society. In both groups, pride displays produced strong implicit associations with high status, despite Fijian social norms discouraging overt displays of pride. Also in both groups, implicit and explicit associations between emotion expressions and status were dissociated; despite the cross-cultural implicit association between pride displays and high status, happy displays were, cross-culturally, the more powerful status indicator at an explicit level, and among Fijians, happy and pride displays were equally strongly implicitly associated with status. Finally, a cultural difference emerged: Fijians viewed happy displays as more deserving of high status than did North Americans, both implicitly and explicitly. Together, these findings suggest that the display and recognition of pride may be part of a suite of adaptations for negotiating status relationships, but that the high-status message of pride is largely communicated through implicit cognitive processes. 2013 APA, all rights reserved

Molecular evolution of the CYP2D subfamily in primates: purifying selection on substrate recognition sites without the frequent or long-tract gene conversion.

PubMed

Yasukochi, Yoshiki; Satta, Yoko

2015-03-25

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Molecular Evolution of the CYP2D Subfamily in Primates: Purifying Selection on Substrate Recognition Sites without the Frequent or Long-Tract Gene Conversion

PubMed Central

Yasukochi, Yoshiki; Satta, Yoko

2015-01-01

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. PMID:25808902

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

PubMed Central

Yoshioka, Nayuta; Zangerl, Barbara; Nivison-Smith, Lisa; Khuu, Sieu K.; Jones, Bryan W.; Pfeiffer, Rebecca L.; Marc, Robert E.; Kalloniatis, Michael

2017-01-01

Purpose To characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease. Methods Single eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort. Results Pattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm). Conclusions Pattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease. PMID:28632847

Superexchange coupling and slow magnetic relaxation in a transuranium polymetallic complex.

PubMed

Magnani, N; Colineau, E; Eloirdi, R; Griveau, J-C; Caciuffo, R; Cornet, S M; May, I; Sharrad, C A; Collison, D; Winpenny, R E P

2010-05-14

{Np(VI)O2Cl2}{Np(V)O2Cl(thf)3}2 is the first studied example of a polymetallic transuranic complex displaying both slow relaxation of the magnetization and effective superexchange interactions between 5f centers. The coupling constant for Np(V)-Np(VI) pairs is 10.8 K, more than 1 order of magnitude larger than the common values found for rare-earth ions in similar environments. The dynamic magnetic behavior displays slow relaxation of magnetization of molecular origin with an energy barrier of 140 K, which is nearly twice the size of the highest barrier found in polymetallic clusters of the d block. Our observations also suggest that future actinide-based molecular magnets will have very different behavior to lanthanide-based clusters.

Using an Improved SIFT Algorithm and Fuzzy Closed-Loop Control Strategy for Object Recognition in Cluttered Scenes

PubMed Central

Nie, Haitao; Long, Kehui; Ma, Jun; Yue, Dan; Liu, Jinguo

2015-01-01

Partial occlusions, large pose variations, and extreme ambient illumination conditions generally cause the performance degradation of object recognition systems. Therefore, this paper presents a novel approach for fast and robust object recognition in cluttered scenes based on an improved scale invariant feature transform (SIFT) algorithm and a fuzzy closed-loop control method. First, a fast SIFT algorithm is proposed by classifying SIFT features into several clusters based on several attributes computed from the sub-orientation histogram (SOH), in the feature matching phase only features that share nearly the same corresponding attributes are compared. Second, a feature matching step is performed following a prioritized order based on the scale factor, which is calculated between the object image and the target object image, guaranteeing robust feature matching. Finally, a fuzzy closed-loop control strategy is applied to increase the accuracy of the object recognition and is essential for autonomous object manipulation process. Compared to the original SIFT algorithm for object recognition, the result of the proposed method shows that the number of SIFT features extracted from an object has a significant increase, and the computing speed of the object recognition processes increases by more than 40%. The experimental results confirmed that the proposed method performs effectively and accurately in cluttered scenes. PMID:25714094

Separating the FN400 and N400 potentials across recognition memory experiments

PubMed Central

Stróżak, Paweł; Abedzadeh, Delora; Curran, Tim

2016-01-01

There is a growing debate as to whether frontally distributed FN400 potentials reflect familiarity-based recognition or are functionally identical to centro-parietal N400 reflecting semantic processing. We conducted two experiments in which event-related potentials (ERPs) associated with semantic priming and recognition were recorded, either when priming was embedded within a recognition test (Experiment 1), or when these two phases were separated (Experiment 2). In Experiment 1, we observed 300–500 ms differences between primed and unprimed old words as well as differences between old and new primed words, but these two effects did not differ topographically and both showed midline central maxima. In Experiment 2, the N400 for priming was recorded exclusively during encoding and again showed a midline central distribution. The ERP component of recognition was only found for unrelated words (not primed previously during encoding), and also showed a midline central maximum, but, in addition, was present in the left frontal area of the scalp. Conversely, the priming effect was absent in the left frontal cluster. This pattern of results indicate that FN400 and N400 potentials share similar neural generators; but when priming and recognition are not confounded, these potentials do not entirely overlap in terms of topographical distribution and presumably reflect functionally distinct processes. PMID:26776478

Gender differences in emotion recognition: Impact of sensory modality and emotional category.

PubMed

Lambrecht, Lena; Kreifelts, Benjamin; Wildgruber, Dirk

2014-04-01

Results from studies on gender differences in emotion recognition vary, depending on the types of emotion and the sensory modalities used for stimulus presentation. This makes comparability between different studies problematic. This study investigated emotion recognition of healthy participants (N = 84; 40 males; ages 20 to 70 years), using dynamic stimuli, displayed by two genders in three different sensory modalities (auditory, visual, audio-visual) and five emotional categories. The participants were asked to categorise the stimuli on the basis of their nonverbal emotional content (happy, alluring, neutral, angry, and disgusted). Hit rates and category selection biases were analysed. Women were found to be more accurate in recognition of emotional prosody. This effect was partially mediated by hearing loss for the frequency of 8,000 Hz. Moreover, there was a gender-specific selection bias for alluring stimuli: Men, as compared to women, chose "alluring" more often when a stimulus was presented by a woman as compared to a man.

Context effects and false memory for alcohol words in adolescents.

PubMed

Zack, Martin; Sharpley, Justin; Dent, Clyde W; Stacy, Alan W

2009-03-01

This study assessed incidental recognition of Alcohol and Neutral words in adolescents who encoded the words under distraction. Participants were 171 (87 male) 10th grade students, ages 14-16 (M=15.1) years. Testing was conducted by telephone: Participants listened to a list containing Alcohol and Neutral (Experimental--Group E, n=92) or only Neutral (Control--Group C, n=79) words, while counting backwards from 200 by two's. Recognition was tested immediately thereafter. Group C exhibited higher false recognition of Neutral than Alcohol items, whereas Group E displayed equivalent false rates for both word types. The reported number of alcohol TV ads seen in the past week predicted higher false recognition of Neutral words in Group C and of Alcohol words in Group E. False memory for Alcohol words in Group E was greater in males and high anxiety sensitive participants. These context-dependent biases may contribute to exaggerations in perceived drinking norms previously found to predict alcohol misuse in young drinkers.

DEVELOPMENT OF A SAFETY COMMUNICATION AND RECOGNITION PROGRAM FOR CONSTRUCTION

PubMed Central

SPARER, EMILY H.; HERRICK, ROBERT F.; DENNERLEIN, JACK T.

2017-01-01

Leading-indicator–based (e.g., hazard recognition) incentive programs provide an alternative to controversial lagging-indicator–based (e.g., injury rates) programs. We designed a leading-indicator–based safety communication and recognition program that incentivized safe working conditions. The program was piloted for two months on a commercial construction worksite, and then redesigned using qualitative interview and focus group data from management and workers. We then ran the redesigned program for six months on the same worksite. Foremen received detailed weekly feedback from safety inspections, and posters displayed worksite and subcontractor safety scores. In the final program design, the whole site, not individual subcontractors, was the unit of analysis and recognition. This received high levels of acceptance from workers, who noted increased levels of site unity and team-building. This pilot program showed that construction workers value solidarity with others on site, demonstrating the importance of health and safety programs that engage all workers through a reliable and consistent communication infrastructure. PMID:25815741

Compact hybrid optoelectrical unit for image processing and recognition

NASA Astrophysics Data System (ADS)

Cheng, Gang; Jin, Guofan; Wu, Minxian; Liu, Haisong; He, Qingsheng; Yuan, ShiFu

1998-07-01

In this paper a compact opto-electric unit (CHOEU) for digital image processing and recognition is proposed. The central part of CHOEU is an incoherent optical correlator, which is realized with a SHARP QA-1200 8.4 inch active matrix TFT liquid crystal display panel which is used as two real-time spatial light modulators for both the input image and reference template. CHOEU can do two main processing works. One is digital filtering; the other is object matching. Using CHOEU an edge-detection operator is realized to extract the edges from the input images. Then the reprocessed images are sent into the object recognition unit for identifying the important targets. A novel template- matching method is proposed for gray-tome image recognition. A positive and negative cycle-encoding method is introduced to realize the absolute difference measurement pixel- matching on a correlator structure simply. The system has god fault-tolerance ability for rotation distortion, Gaussian noise disturbance or information losing. The experiments are given at the end of this paper.

On the limited recognition of inorganic surfaces by short peptides compared with antibodies.

PubMed

Artzy-Schnirman, Arbel; Abu-Shah, Enas; Dishon, Matan; Soifer, Hadas; Sivan, Yotam; Reiter, Yoram; Benhar, Itai; Sivan, Uri

2014-06-01

The vast potential applications of biomolecules that bind inorganic surfaces led mostly to the isolation of short peptides that target selectively specific materials. The demonstrated differential affinity toward certain surfaces created the impression that the recognition capacity of short peptides may match that of rigid biomolecules. In the following, we challenge this view by comparing the capacity of antibody molecules to discriminate between the (100) and (111A) facets of a gallium arsenide semiconductor crystal with the capacity of short peptides to do the same. Applying selection from several peptide and single chain phage display libraries, we find a number of antibody molecules that bind preferentially a given crystal facet but fail to isolate, in dozens of attempts, a single peptide capable of such recognition. The experiments underscore the importance of rigidity to the recognition of inorganic flat targets and therefore set limitations on potential applications of short peptides in biomimetics. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd.

[Visual hemifield differences in recognition of kanji and hiragana and its relation to hemispheric cerebral asymmetries].

PubMed

Miyazaki, T; Sugimoto, Y; Sato, H

1990-07-01

Visual hemifield differences in recognition of kanji and hiragana were studied on forty male right handers. A letter of kanji or hiragana was presented unilaterally to the right or left visual hemifield on a CRT display for 123 msec. A hundred and twenty recognition trials were performed for each subject using 20 well-acquainted kanji, 20 unfamiliar kanji and 20 hiragana. Kanji was more accurately recognized in the left visual hemifield than in the right hemifield. This tendency was more prominent in unfamiliar kanji compared with well-acquainted kanji. There were no visual hemifield differences in recognition of hiragana. Learning effects were observed for the right hemifield on kanji and both hemifields on hiragana. The results were discussed in relation to cerebral asymmetries of function. Kanji might be processed in the right cerebral hemisphere as geometric forms. The results on hiragana may be explained by mental set. It is suggested that modes of processing may be different between kanji and hiragana.

Spatial patterns in electoral wards with high lymphoma incidence in Yorkshire health region.

PubMed Central

Barnes, N.; Cartwright, R. A.; O'Brien, C.; Roberts, B.; Richards, I. D.; Bird, C. C.

1987-01-01

The possibilities of clustering between those electoral wards which display higher than expected incidences of cases of the lymphomas occurring between 1978 and 1982 are examined. Clusters are defined as being those wards with cases in excess (at a probability of less than 10%) which are geographically adjacent to each other. A separate analysis extends the definition of cluster to include high incidence wards that are adjacent or separated by one other ward. The results indicate that many high incidence lymphoma wards do occur close together and when computer simulations are used to compute expected results, many of the observed results are shown to be highly improbable both in the overall number of clustering wards and in the largest number of wards comprising a 'cluster'. PMID:3663469

Fast distributed large-pixel-count hologram computation using a GPU cluster.

PubMed

Pan, Yuechao; Xu, Xuewu; Liang, Xinan

2013-09-10

Large-pixel-count holograms are one essential part for big size holographic three-dimensional (3D) display, but the generation of such holograms is computationally demanding. In order to address this issue, we have built a graphics processing unit (GPU) cluster with 32.5 Tflop/s computing power and implemented distributed hologram computation on it with speed improvement techniques, such as shared memory on GPU, GPU level adaptive load balancing, and node level load distribution. Using these speed improvement techniques on the GPU cluster, we have achieved 71.4 times computation speed increase for 186M-pixel holograms. Furthermore, we have used the approaches of diffraction limits and subdivision of holograms to overcome the GPU memory limit in computing large-pixel-count holograms. 745M-pixel and 1.80G-pixel holograms were computed in 343 and 3326 s, respectively, for more than 2 million object points with RGB colors. Color 3D objects with 1.02M points were successfully reconstructed from 186M-pixel hologram computed in 8.82 s with all the above three speed improvement techniques. It is shown that distributed hologram computation using a GPU cluster is a promising approach to increase the computation speed of large-pixel-count holograms for large size holographic display.

77 FR 30542 - Air Cargo Screening Fees

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-23

... Security Identification Display Area (SIDA) IDs. Another commenter requested that if TSA intends to limit... obtain SIDA IDs were not included in the fee models for this rulemaking because STAs for holders of SIDA... FR 51854. Comment: One commenter appreciated TSA's recognition that the STAs performed under the SIDA...

Middle-School Students' Map Construction: Understanding Complex Spatial Displays.

ERIC Educational Resources Information Center

Bausmith, Jennifer Merriman; Leinhardt, Gaea

1998-01-01

Examines the map-making process of middle-school students to determine which actions influence their accuracy, how prior knowledge helps their map construction, and what lessons can be learned from map making. Indicates that instruction that focuses on recognition of interconnections between map elements can promote map reasoning skills. (DSK)

An eye on reactor and computer control

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

Schryver, J.; Knee, B.

1992-01-01

At ORNL computer software has been developed to make possible an improved eye-gaze measurement technology. Such an inovation could be the basis for advanced eye-gaze systems that may have applications in reactor control, software development, cognitive engineering, evaluation of displays, prediction of mental workloads, and military target recognition.

Recognition of Cross-Cultural Meaning When Developing Online Web Displays.

ERIC Educational Resources Information Center

Brown, Ian; Hedberg, John

The perceptions and practical experiences are important influences when creating and developing online learning experiences in cross cultural contexts. In this study, 15 educational designers studying for their Master's Degree were asked to contribute their interpretations to an ongoing study of what meaning and interpretations were generated from…

Species differences in behavior and cell proliferation/survival in the adult brains of female meadow and prairie voles

PubMed Central

Pan, Yongliang; Liu, Yan; Lieberwirth, Claudia; Zhang, Zhibin; Wang, Zuoxin

2016-01-01

Microtine rodents display diverse patterns of social organization and behaviors, and thus provide a useful model for studying the effects of the social environment on physiology and behavior. The current study compared the species differences and the effects of oxytocin (OT) on anxiety-like, social affiliation, and social recognition behaviors in female meadow voles (Microtus pennsylvanicus) and prairie voles (M. ochrogaster). Furthermore, cell proliferation and survival in the brains of adult female meadow and prairie voles were compared. We found that female meadow voles displayed a higher level of anxiety-like behavior but lower levels of social affiliation and social recognition compared to female prairie voles. In addition, meadow voles showed lower levels of cell proliferation (measured by Ki67 staining) and cell survival (measured by BrdU staining) in the ventromedial hypothalamus (VMH) and amygdala (AMY), but not the dentate gyrus of the hippocampus (DG), than prairie voles. Interestingly, the numbers of new cells in the VMH and AMY, but not DG, also correlated with anxiety-like, social affiliation, and social recognition behaviors in a brain region-specific manner. Finally, central OT treatment (200 ng/kg, icv) did not lead to changes in behavior or cell proliferation/survival in the brain. Together, these data indicate a potential role of cell proliferation/survival in selected brain areas on different behaviors between vole species with distinct life strategies. PMID:26708743

Deaf-And-Mute Sign Language Generation System

NASA Astrophysics Data System (ADS)

Kawai, Hideo; Tamura, Shinichi

1984-08-01

We have developed a system which can recognize speech and generate the corresponding animation-like sign language sequence. The system is implemented in a popular personal computer. This has three video-RAM's and a voice recognition board which can recognize only registered voice of a specific speaker. Presently, fourty sign language patterns and fifty finger spellings are stored in two floppy disks. Each sign pattern is composed of one to four sub-patterns. That is, if the pattern is composed of one sub-pattern, it is displayed as a still pattern. If not, it is displayed as a motion pattern. This system will help communications between deaf-and-mute persons and healthy persons. In order to display in high speed, almost programs are written in a machine language.

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Toward the light field display: autostereoscopic rendering via a cluster of projectors.

PubMed

Yang, Ruigang; Huang, Xinyu; Li, Sifang; Jaynes, Christopher

2008-01-01

Ultimately, a display device should be capable of reproducing the visual effects observed in reality. In this paper we introduce an autostereoscopic display that uses a scalable array of digital light projectors and a projection screen augmented with microlenses to simulate a light field for a given three-dimensional scene. Physical objects emit or reflect light in all directions to create a light field that can be approximated by the light field display. The display can simultaneously provide many viewers from different viewpoints a stereoscopic effect without head tracking or special viewing glasses. This work focuses on two important technical problems related to the light field display; calibration and rendering. We present a solution to automatically calibrate the light field display using a camera and introduce two efficient algorithms to render the special multi-view images by exploiting their spatial coherence. The effectiveness of our approach is demonstrated with a four-projector prototype that can display dynamic imagery with full parallax.

Cluster adsorption on amorphous and crystalline surfaces - A molecular dynamics study of model Pt on Cu and model Pd on Pt

NASA Technical Reports Server (NTRS)

Garofalini, S. H.; Halicioglu, T.; Pound, G. M.

1981-01-01

Molecular dynamics was used to study the structure, dispersion and short-time behavior of ten-atom clusters adsorbed onto amorphous and crystalline substrates, in which the cluster atoms differed from the substrate atoms. Two adatom-substrate model systems were chosen; one, in which the interaction energy between adatom pairs was greater than that between substrate pairs, and the other, in which the reverse was true. At relatively low temperature ranges, increased dispersion of cluster atoms occurred: (a) on the amorphous substrate as compared to the FCC(100) surface, (b) with increasing reduced temperature, and (c) with adatom-substrate interaction energy stronger than adatom-adatom interaction. Two-dimensional clusters (rafts) on the FCC(100) surface displayed migration of edge atoms only, indicating a mechanism for the cluster rotation and shape changes found in experimental studies.

The signer and the sign: cortical correlates of person identity and language processing from point-light displays.

PubMed

Campbell, Ruth; Capek, Cheryl M; Gazarian, Karine; MacSweeney, Mairéad; Woll, Bencie; David, Anthony S; McGuire, Philip K; Brammer, Michael J

2011-09-01

In this study, the first to explore the cortical correlates of signed language (SL) processing under point-light display conditions, the observer identified either a signer or a lexical sign from a display in which different signers were seen producing a number of different individual signs. Many of the regions activated by point-light under these conditions replicated those previously reported for full-image displays, including regions within the inferior temporal cortex that are specialised for face and body-part identification, although such body parts were invisible in the display. Right frontal regions were also recruited - a pattern not usually seen in full-image SL processing. This activation may reflect the recruitment of information about person identity from the reduced display. A direct comparison of identify-signer and identify-sign conditions showed these tasks relied to a different extent on the posterior inferior regions. Signer identification elicited greater activation than sign identification in (bilateral) inferior temporal gyri (BA 37/19), fusiform gyri (BA 37), middle and posterior portions of the middle temporal gyri (BAs 37 and 19), and superior temporal gyri (BA 22 and 42). Right inferior frontal cortex was a further focus of differential activation (signer>sign). These findings suggest that the neural systems supporting point-light displays for the processing of SL rely on a cortical network including areas of the inferior temporal cortex specialized for face and body identification. While this might be predicted from other studies of whole body point-light actions (Vaina, Solomon, Chowdhury, Sinha, & Belliveau, 2001) it is not predicted from the perspective of spoken language processing, where voice characteristics and speech content recruit distinct cortical regions (Stevens, 2004) in addition to a common network. In this respect, our findings contrast with studies of voice/speech recognition (Von Kriegstein, Kleinschmidt, Sterzer, & Giraud, 2005). Inferior temporal regions associated with the visual recognition of a person appear to be required during SL processing, for both carrier and content information. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Characterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum.

PubMed

Van Rheenen, T E; Lewandowski, K E; Tan, E J; Ospina, L H; Ongur, D; Neill, E; Gurvich, C; Pantelis, C; Malhotra, A K; Rossell, S L; Burdick, K E

2017-07-01

Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

The re-emergence of felid camouflage with the decay of predator recognition in deer under relaxed selection

PubMed Central

Stankowich, Theodore; Coss, Richard G

2006-01-01

When a previously common predator disappears owing to local extinction, the strong source of natural selection on prey to visually recognize that predator becomes relaxed. At present, we do not know the extent to which recognition of a specific predator is generalized to similar looking predators or how a specific predator-recognition cue, such as coat pattern, degrades under prolonged relaxed selection. Using predator models, we show that deer exhibit a more rapid and stronger antipredator response to their current predator, the puma, than to a leopard displaying primitive rosettes similar to a locally extinct predator, an early jaguar. Presentation of a novel tiger with a striped coat engendered an intermediate speed of predator recognition and strength of antipredator behaviour. Responses to the leopard model slightly exceeded responses to a non-threatening deer model, suggesting that thousands of years of relaxed selection have led to the loss of recognition of the spotted coat as a jaguar-recognition cue, and that the spotted coat has regained its ability to camouflage the felid form. Our results shed light on the evolutionary arms race between adoption of camouflage to facilitate hunting and the ability of prey to quickly recognize predators by their formerly camouflaging patterns. PMID:17148247

Comparing object recognition from binary and bipolar edge images for visual prostheses

PubMed Central

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2017-01-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition. PMID:28458481

The study of the plasmon modes of square atomic clusters based on the eigen-oscillation equation of charge under the free-electron gas model

NASA Astrophysics Data System (ADS)

Xue, Hong-Jie; Wu, Reng-Lai; Hu, Cheng-Xi; Zhang, Ming

2018-04-01

In atomic clusters, plasmon modes are generally gained by the resonant responses for external fields. However, these resonant methods still carry some defects: some plasmon modes may not have been found as that may not have been excited by the external fields. Recently, by employing the extended Hubbard model to describe electron systems of atomic clusters, we have presented the eigen-oscillation equation of charge to study plasmon modes. In this work, based on the free-electron gas model, we further explore the eigen-equation method. Under different external electric fields, some of the plasmon mode spectrums with obvious differences are found, which display the defects of the resonant methods. All the plasmon modes obtained by the resonant methods are predicted by the eigen-equation method. This effectively shows that the eigen-equation method is feasible and reliable in the process of finding plasmon. In addition, various kinds of plasmons are displayed by charge distributions, and the evolution features of plasmon with system parameters are gained by the energy absorption spectrum.

The Prevalence of Comorbid Personality Disorders in Treatment-Seeking Problem Gamblers: A Systematic Review and Meta-Analysis.

PubMed

Dowling, Nicki A; Cowlishaw, S; Jackson, A C; Merkouris, S S; Francis, K L; Christensen, D R

2015-12-01

The aim of this study was to systematically review and meta-analyze the prevalence of comorbid personality disorders among treatment-seeking problem gamblers. Almost one half (47.9%) of problem gamblers displayed comorbid personality disorders. They were most likely to display Cluster B disorders (17.6%), with smaller proportions reporting Cluster C disorders (12.6%) and Cluster A disorders (6.1%). The most prevalent personality disorders were narcissistic (16.6%), antisocial (14.0%), avoidant (13.4%), obsessive-compulsive (13.4%), and borderline (13.1%) personality disorders. Sensitivity analyses suggested that these prevalence estimates were robust to the inclusion of clinical trials and self-selected samples. Although there was significant variability in reported rates, subgroup analyses revealed no significant differences in estimates of antisocial personality disorder according to problem gambling severity, measure of comorbidity employed, and study jurisdiction. The findings highlight the need for gambling treatment services to conduct routine screening and assessment of co-occurring personality disorders and to provide treatment approaches that adequately address these comorbid conditions.

Audio-visual affective expression recognition

NASA Astrophysics Data System (ADS)

Huang, Thomas S.; Zeng, Zhihong

2007-11-01

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

Binary zone-plate array for a parallel joint transform correlator applied to face recognition.

PubMed

Kodate, K; Hashimoto, A; Thapliya, R

1999-05-10

Taking advantage of small aberrations, high efficiency, and compactness, we developed a new, to our knowledge, design procedure for a binary zone-plate array (BZPA) and applied it to a parallel joint transform correlator for the recognition of the human face. Pairs of reference and unknown images of faces are displayed on a liquid-crystal spatial light modulator (SLM), Fourier transformed by the BZPA, intensity recorded on an optically addressable SLM, and inversely Fourier transformed to obtain correlation signals. Consideration of the bandwidth allows the relations among the channel number, the numerical aperture of the zone plates, and the pattern size to be determined. Experimentally a five-channel parallel correlator was implemented and tested successfully with a 100-person database. The design and the fabrication of a 20-channel BZPA for phonetic character recognition are also included.

Genetic characteristics of Streptococcus dysgalactiae isolated from cage cultured cobia, Rachycentron canadum (L.).

PubMed

Tsai, M-A; Wang, P-C; Yoshida, T; Chen, S-C

2015-12-01

Disease outbreaks occurred during 2007-2013 in Taiwan with 2.5-10% mortality among the cage cultured cobia, Rachycentron canadum (L.), characterized by the presence of polyserositis, pericarditis and peritonitis. The micro-organisms isolated from internal organs were Gram-positive cocci. The isolates were confirmed as Streptococcus dysgalactiae by a polymerase chain reaction assay that yielded the expected specific 259 bp amplicon. Additionally, partial sequence of the 16S-23S rDNA intergenic spacer region of the GCS strain isolates from fish was also compared and produced 100% sequence identity with S. dysgalactiae (GenBank accession number AB252398). The genetic characterization was then determined by pulsed-field gel electrophoresis (PFGE) analysis. Based on PFGE, the Apa I or Sma I digestion patterns of chromosomal DNA of these isolates were grouped into three main clusters. Taiwanese strains were divided into two clusters, and the tet(M) gene was detected in cluster 1 (pulsotypes: A1-A2 and S1-S3), but not in cluster 2 strains (pulsotypes: A3-A4 and S4-S5). Three Japanese strains from amberjack, Seriola dumerili (Risso), were grouped into cluster 3 (pulsotypes: A5-A7 and S6-S8) and displayed no mortality to cobia in the challenge experiment. Conversely, Taiwanese strains from cobia and snubnose pompano, Trachinotus blochii (L.), displayed a mortality rate of 50-87.5% in cobia. © 2014 John Wiley & Sons Ltd.

Dopamine replacement therapy and deep brain stimulation of the subthalamic nuclei induce modulation of emotional processes at different spatial frequencies in Parkinson's disease.

PubMed

Mermillod, Martial; Mondillon, Laurie; Rieu, Isabelle; Devaux, Damien; Chambres, Patrick; Auxiette, Catherine; Dalens, Hélène; Coulangeon, Louise Marie; Jalenques, Isabelle; Durif, Franck

2014-01-01

Deep brain stimulation of the subthalamic nuclei (STN-DBS) is an effective treatment for the most severe forms of Parkinson's disease (PD) and is intended to suppress these patients' motor symptoms. However, be it in association with Dopamine Replacement Therapy (DRT) or not, STN-DBS may in some cases induce addictive or emotional disorders. In the current study, we suggest that PD patients suffer from emotional deficits that have not been revealed in previous studies because in those experiments the stimuli were displayed for a time long enough to allow patients to have recourse to perceptual strategies in order to recognize the emotional facial expressions (EFE). The aim of the current article is to demonstrate the existence of emotional disorders in PD by using a rapid presentation of the visual stimuli (200-ms display time) which curtails their perceptual analysis, and to determine whether STN-DBS, either associated or not associated with DRT, has an impact on the recognition of emotions. The results show that EFE recognition performance depends on both STN-DBS ('on' vs. 'off') and medication ('on' vs. 'off'), but also that these variables have an interactive influence on EFE recognition performance. Moreover, we also reveal how these EFE impairments depend on different spatial frequencies perceptual channels (related to different cortical vs. subcortical neural structures). The effect of PD without therapy seems to be particularly acute for LSF emotional faces, possibly due to a subcortical dysfunction. However, our results indicate that the joint action of STN-DBS and DRT could also disrupt recognition of emotional expressions at the level of occipito-temporal cortical areas (processing HSF visual information) inducing broad global impairment of EFE at the level of HSF visual channels.

Effectiveness of Educational Poster on Knowledge of Emergency Management of Dental Trauma - Part 2: Cluster Randomised Controlled Trial for Secondary School Students

PubMed Central

Young, Cecilia; Wong, Kin Yau; Cheung, Lim K.

2014-01-01

Objective To investigate the effectiveness of educational poster on improving secondary school students' knowledge of emergency management of dental trauma. Methods A cluster randomised controlled trial was conducted. 16 schools with total 671 secondary students who can read Chinese or English were randomised into intervention (poster, 8 schools, 364 students) and control groups (8 schools, 305 students) at the school level. Baseline knowledge of dental trauma was obtained by a questionnaire. Poster containing information of dental trauma management was displayed in a classroom for 2 weeks in each school in the intervention group whereas in the control group there was no display of such posters. Students of both groups completed the same questionnarie after 2 weeks. Results Two-week display of posters improved the knowledge score by 1.25 (p-value = 0.0407) on average. Conclusion Educational poster on dental trauma management significantly improved the level of knowledge of secondary school students in Hong Kong. Trial Registration HKClinicalTrial.com HKCTR-1343 ClinicalTrials.gov NCT01809457 PMID:25093728

A New Integrated Threshold Selection Methodology for Spatial Forecast Verification of Extreme Events

NASA Astrophysics Data System (ADS)

Kholodovsky, V.

2017-12-01

Extreme weather and climate events such as heavy precipitation, heat waves and strong winds can cause extensive damage to the society in terms of human lives and financial losses. As climate changes, it is important to understand how extreme weather events may change as a result. Climate and statistical models are often independently used to model those phenomena. To better assess performance of the climate models, a variety of spatial forecast verification methods have been developed. However, spatial verification metrics that are widely used in comparing mean states, in most cases, do not have an adequate theoretical justification to benchmark extreme weather events. We proposed a new integrated threshold selection methodology for spatial forecast verification of extreme events that couples existing pattern recognition indices with high threshold choices. This integrated approach has three main steps: 1) dimension reduction; 2) geometric domain mapping; and 3) thresholds clustering. We apply this approach to an observed precipitation dataset over CONUS. The results are evaluated by displaying threshold distribution seasonally, monthly and annually. The method offers user the flexibility of selecting a high threshold that is linked to desired geometrical properties. The proposed high threshold methodology could either complement existing spatial verification methods, where threshold selection is arbitrary, or be directly applicable in extreme value theory.

Multivalent display of proteins on viral nanoparticles using molecular recognition and chemical ligation strategies

PubMed Central

Venter, P. Arno; Dirksen, Anouk; Thomas, Diane; Manchester, Marianne; Dawson, Philip E.; Schneemann, Anette

2011-01-01

Multivalent display of heterologous proteins on viral nanoparticles forms a basis for numerous applications in nanotechnology, including vaccine development, targeted therapeutic delivery and tissue-specific bio-imaging. In many instances, precise placement of proteins is required for optimal functioning of the supramolecular assemblies, but orientation- and site-specific coupling of proteins to viral scaffolds remains a significant technical challenge. We have developed two strategies that allow for controlled attachment of a variety of proteins on viral particles using covalent and noncovalent principles. In one strategy, an interaction between domain 4 of anthrax protective antigen and its receptor was used to display multiple copies of a target protein on virus-like particles. In the other, expressed protein ligation and aniline-catalyzed oximation was used to covalently display a model protein. The latter strategy, in particular, yielded nanoparticles that induced potent immune responses to the coupled protein, suggesting potential applications in vaccine development. PMID:21545187

Characterising laser beams with liquid crystal displays

NASA Astrophysics Data System (ADS)

Dudley, Angela; Naidoo, Darryl; Forbes, Andrew

2016-02-01

We show how one can determine the various properties of light, from the modal content of laser beams to decoding the information stored in optical fields carrying orbital angular momentum, by performing a modal decomposition. Although the modal decomposition of light has been known for a long time, applied mostly to pattern recognition, we illustrate how this technique can be implemented with the use of liquid-crystal displays. We show experimentally how liquid crystal displays can be used to infer the intensity, phase, wavefront, Poynting vector, and orbital angular momentum density of unknown optical fields. This measurement technique makes use of a single spatial light modulator (liquid crystal display), a Fourier transforming lens and detector (CCD or photo-diode). Such a diagnostic tool is extremely relevant to the real-time analysis of solid-state and fibre laser systems as well as mode division multiplexing as an emerging technology in optical communication.

Quantum pattern recognition with multi-neuron interactions

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Time-Frequency Analysis And Pattern Recognition Using Singular Value Decomposition Of The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Lovell, Brian; White, Langford

1988-01-01

Time-Frequency analysis based on the Wigner-Ville Distribution (WVD) is shown to be optimal for a class of signals where the variation of instantaneous frequency is the dominant characteristic. Spectral resolution and instantaneous frequency tracking is substantially improved by using a Modified WVD (MWVD) based on an Autoregressive spectral estimator. Enhanced signal-to-noise ratio may be achieved by using 2D windowing in the Time-Frequency domain. The WVD provides a tool for deriving descriptors of signals which highlight their FM characteristics. These descriptors may be used for pattern recognition and data clustering using the methods presented in this paper.

The social-cognitive basis of personality disorders.

PubMed

Herpertz, Sabine C; Bertsch, Katja

2014-01-01

The review summarizes recent results on abnormalities in social cognition in patients with personality disorders that predispose them to develop dysfunctional interaction with others. The review starts with more basic social cognition processes, such as emotion recognition and reactions to social exclusion that are followed by more complex processes such as cognitive and affective empathy. The deficits in social cognition depend on the particular function that is investigated and is strongly associated with characteristic symptoms of particular personality disorders. Thus, patients with borderline personality disorder are hypersensitive for social threat, they show deficits in cognitive empathy and high emotion contagion, that is, they share emotions of others without properly discriminating between one's own feelings and those of others. Psychopaths are characterized by deficiency in facial fear recognition and emotional empathy similar to patients with narcissistic personality disorder. Studies on social cognition in cluster A and C personality disorders are sparse. Research indicates deficits in social cognition in patients with personality disorders, but more research is needed to investigate social cognition in cluster A and C personality disorders and to compare deficits in social cognitive functions across personality disorders.

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

PubMed

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

2016-10-28

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

Ceria nanoclusters on graphene/Ru(0001): A new model catalyst system

DOE PAGES

Novotny, Z.; Netzer, F. P.; Dohnalek, Z.

2016-03-22

In this study, the growth of ceria nanoclusters on single-layer graphene on Ru(0001) has been examined, with a view towards fabricating a stable system for model catalysis studies. The surface morphology and cluster distribution as a function of oxide coverage and substrate temperature has been monitored by scanning tunneling microscopy (STM), whereas the chemical composition of the cluster deposits has been determined by Auger electron spectroscopy (AES). The ceria nanoparticles are of the CeO 2(111)-type and are anchored at the intrinsic defects of the graphene surface, resulting in a variation of the cluster densities across the macroscopic sample surface. Themore » ceria clusters on graphene display a remarkable stability against reduction in ultrahigh vacuum up to 900 K, but some sintering of clusters is observed for temperatures > 450 K. The evolution of the cluster size distribution suggests that the sintering proceeds via a Smoluchowski ripening mechanism, i.e. diffusion and aggregation of entire clusters.« less

Collaboration enhances later individual memory for emotional material.

PubMed

Bärthel, Gwennis A; Wessel, Ineke; Huntjens, Rafaële J C; Verwoerd, Johan

2017-05-01

Research on collaborative remembering suggests that collaboration hampers group memory (i.e., collaborative inhibition), yet enhances later individual memory. Studies examining collaborative effects on memory for emotional stimuli are scarce, especially concerning later individual memory. In the present study, female undergraduates watched an emotional movie and recalled it either collaboratively (n = 60) or individually (n = 60), followed by an individual free recall test and a recognition test. We replicated the standard collaborative inhibition effect. Further, in line with the literature, the collaborative condition displayed better post-collaborative individual memory. More importantly, in post-collaborative free recall, the centrality of the information to the movie plot did not play an important role. Recognition rendered slightly different results. Although collaboration rendered more correct recognition for more central details, it did not enhance recognition of background details. Secondly, the collaborative and individual conditions did not differ with respect to overlap of unique correct items in free recall. Yet, during recognition former collaborators more unanimously endorsed correct answers, as well as errors. Finally, extraversion, neuroticism, social anxiety, and depressive symptoms did not moderate the influence of collaboration on memory. Implications for the fields of forensic and clinical psychology are discussed.

Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels

PubMed Central

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of “recent” paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. Contact: sarkar@labri.fr. PMID:23457439

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

PubMed

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. sarkar@labri.fr.

Soft Clustering Criterion Functions for Partitional Document Clustering

DTIC Science & Technology

2004-05-26

in the clus- ter that it already belongs to. The refinement phase ends, as soon as we perform an iteration in which no documents moved between...for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 26 MAY 2004 2... it with the one obtained by the hard criterion functions. We present a comprehensive experimental evaluation involving twelve differ- ent datasets

Data processing 1: Advancements in machine analysis of multispectral data

NASA Technical Reports Server (NTRS)

Swain, P. H.

1972-01-01

Multispectral data processing procedures are outlined beginning with the data display process used to accomplish data editing and proceeding through clustering, feature selection criterion for error probability estimation, and sample clustering and sample classification. The effective utilization of large quantities of remote sensing data by formulating a three stage sampling model for evaluation of crop acreage estimates represents an improvement in determining the cost benefit relationship associated with remote sensing technology.

Network Analysis Tools: from biological networks to clusters and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Investigation of redshift- and duration-dependent clustering of gamma-ray bursts

DOE PAGES

Ukwatta, T. N.; Woźniak, P. R.

2015-11-05

Gamma-ray bursts (GRBs) are detectable out to very large distances and as such are potentially powerful cosmological probes. Historically, the angular distribution of GRBs provided important information about their origin and physical properties. As a general population, GRBs are distributed isotropically across the sky. However, there are published reports that once binned by duration or redshift, GRBs display significant clustering. We have studied the redshift- and duration-dependent clustering of GRBs using proximity measures and kernel density estimation. Utilizing bursts detected by Burst and Transient Source Experiment, Fermi/gamma-ray burst monitor, and Swift/Burst Alert Telescope, we found marginal evidence for clustering inmore » very short duration GRBs lasting less than 100 ms. As a result, our analysis provides little evidence for significant redshift-dependent clustering of GRBs.« less

Granular Segregation Driven by Particle Interactions

NASA Astrophysics Data System (ADS)

Lozano, C.; Zuriguel, I.; Garcimartín, A.; Mullin, T.

2015-05-01

We report the results of an experimental study of particle-particle interactions in a horizontally shaken granular layer that undergoes a second order phase transition from a binary gas to a segregation liquid as the packing fraction C is increased. By focusing on the behavior of individual particles, the effect of C is studied on (1) the process of cluster formation, (2) cluster dynamics, and (3) cluster destruction. The outcomes indicate that the segregation is driven by two mechanisms: attraction between particles with the same properties and random motion with a characteristic length that is inversely proportional to C . All clusters investigated are found to be transient and the probability distribution functions of the separation times display a power law tail, indicating that the splitting probability decreases with time.

Transmission of cluster ions through a tandem accelerator of several stripper gases.

PubMed

Saitoh, Yuichi; Chiba, Atsuya; Narumi, Kazumasa

2009-10-01

The transmissions of carbon cluster ion beams through a tandem accelerator using several stripper gases (He, N2, CO2, and SF6) with a terminal voltage of 2.5 MV were measured as a function of the gas pressure in investigating the most suitable gas for cluster ion acceleration. This resulted in it being demonstrated that the highest transmission could be obtained using the smaller size gas, i.e., helium displayed the best performance of the four gases used. In addition, the ratio of transmissions of C(n) with helium and nitrogen increased with increases in the n, thus revealing that helium gas should prove the most effective in larger cluster ion acceleration using the same energy.

Single-Molecule View of Small RNA-Guided Target Search and Recognition.

PubMed

Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

2018-05-20

Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

A new multidimensional population health indicator for policy makers: absolute level, inequality and spatial clustering - an empirical application using global sub-national infant mortality data.

PubMed

Sartorius, Benn K D; Sartorius, Kurt

2014-11-01

The need for a multidimensional measure of population health that accounts for its distribution remains a central problem to guide the allocation of limited resources. Absolute proxy measures, like the infant mortality rate (IMR), are limited because they ignore inequality and spatial clustering. We propose a novel, three-part, multidimensional mortality indicator that can be used as the first step to differentiate interventions in a region or country. The three-part indicator (MortalityABC index) combines absolute mortality rate, the Theil Index to calculate mortality inequality and the Getis-Ord G statistic to determine the degree of spatial clustering. The analysis utilises global sub-national IMR data to empirically illustrate the proposed indicator. The three-part indicator is mapped globally to display regional/country variation and further highlight its potential application. Developing countries (e.g. in sub-Saharan Africa) display high levels of absolute mortality as well as variable mortality inequality with evidence of spatial clustering within certain sub-national units ("hotspots"). Although greater inequality is observed outside developed regions, high mortality inequality and spatial clustering are common in both developed and developing countries. Significant positive correlation was observed between the degree of spatial clustering and absolute mortality. The proposed multidimensional indicator should prove useful for spatial allocation of healthcare resources within a country, because it can prompt a wide range of policy options and prioritise high-risk areas. The new indicator demonstrates the inadequacy of IMR as a single measure of population health, and it can also be adapted to lower administrative levels within a country and other population health measures.

CRAWview: for viewing splicing variation, gene families, and polymorphism in clusters of ESTs and full-length sequences.

PubMed

Chou, A; Burke, J

1999-05-01

DNA sequence clustering has become a valuable method in support of gene discovery and gene expression analysis. Our interest lies in leveraging the sequence diversity within clusters of expressed sequence tags (ESTs) to model gene structure for the study of gene variants that arise from, among other things, alternative mRNA splicing, polymorphism, and divergence after gene duplication, fusion, and translocation events. In previous work, CRAW was developed to discover gene variants from assembled clusters of ESTs. Most importantly, novel gene features (the differing units between gene variants, for example alternative exons, polymorphisms, transposable elements, etc.) that are specialized to tissue, disease, population, or developmental states can be identified when these tools collate DNA source information with gene variant discrimination. While the goal is complete automation of novel feature and gene variant detection, current methods are far from perfect and hence the development of effective tools for visualization and exploratory data analysis are of paramount importance in the process of sifting through candidate genes and validating targets. We present CRAWview, a Java based visualization extension to CRAW. Features that vary between gene forms are displayed using an automatically generated color coded index. The reporting format of CRAWview gives a brief, high level summary report to display overlap and divergence within clusters of sequences as well as the ability to 'drill down' and see detailed information concerning regions of interest. Additionally, the alignment viewing and editing capabilities of CRAWview make it possible to interactively correct frame-shifts and otherwise edit cluster assemblies. We have implemented CRAWview as a Java application across windows NT/95 and UNIX platforms. A beta version of CRAWview will be freely available to academic users from Pangea Systems (http://www.pangeasystems.com). Contact :

Effects on locomotion and memory in 2 models of cerebral hypoperfusion in male Wistar rats.

PubMed

Martínez-Díaz, J A; García, L I; Hernández, M E; Aranda-Abreu, G E

2015-09-01

Cerebral ischaemia is one of the most common neurological diseases worldwide. Its many sequelae range from motor and sensory symptoms to cognitive decline and dementia. Animal models of cerebral ischaemia/hypoperfusion elicit effects on long term memory; however, the effects of these procedures on short term memory are not clearly understood and effects induced by alternative hypoperfusion models are completely unknown. We evaluated the effects of 2 cerebral hyperperfusion models on memory in 3-month-old male rats. Episodic memory and working memory were assessed using the new object recognition test and the spontaneous alteration test, respectively. Neurological assessment was also performed, along with an open field test to evaluate locomotor activity. Rats in both hyperperfusion models displayed no cognitive changes. Rats with unilateral left-sided ligation plus temporary ligation of the right carotid tended to show slightly impaired performance on the new object recognition test on the second day after the procedure. In contrast, the group with permanent unilateral ligation tended to display alterations in working and episodic memory 9 days after the procedure, but they subsequently recovered. Despite these differences, both hypoperfusion groups displayed clear signs of motor impairment 2 days after the procedure, as reflected by their decreased locomotor activity during the open field test. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions.

PubMed

Tran, Tran T; Kulis, Christina; Long, Steven M; Bryant, Darryn; Adams, Peter; Smythe, Mark L

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions

NASA Astrophysics Data System (ADS)

Tran, Tran T.; Kulis, Christina; Long, Steven M.; Bryant, Darryn; Adams, Peter; Smythe, Mark L.

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Design and performance of a large vocabulary discrete word recognition system. Volume 1: Technical report. [real time computer technique for voice data processing

NASA Technical Reports Server (NTRS)

1973-01-01

The development, construction, and test of a 100-word vocabulary near real time word recognition system are reported. Included are reasonable replacement of any one or all 100 words in the vocabulary, rapid learning of a new speaker, storage and retrieval of training sets, verbal or manual single word deletion, continuous adaptation with verbal or manual error correction, on-line verification of vocabulary as spoken, system modes selectable via verification display keyboard, relationship of classified word to neighboring word, and a versatile input/output interface to accommodate a variety of applications.

Electrochemical supramolecular recognition of hemin-carbon composites

NASA Astrophysics Data System (ADS)

Le, Hien Thi Ngoc; Jeong, Hae Kyung

2018-04-01

Hemin-graphite oxide-carbon nanotube (hemin-GO-CNT) and hemin-thermally reduced graphite oxide-carbon nanotube (hemin-TRGO-CNT) composites are synthesized and investigated for the electrochemical supramolecular recognition by electron transfer between biomolecules (dopamine and hydrogen peroxide) and the composite electrodes. Redox reaction mechanisms of two composites with dopamine and hydrogen peroxide are explained in detail by using cyclic voltammetry and differential pulse voltammetry. Hemin-TRGO-CNT displays higher electrochemical detection for dopamine and hydrogen peroxide than that of hemin-GO-CNT, exhibiting enhancement of the electron transfer due to the effective immobilization of redox couple of hemin (Fe2+/Fe3+) on the TRGO-CNT surface.

Determining requirements for patient-centred care: a participatory concept mapping study.

PubMed

Ogden, Kathryn; Barr, Jennifer; Greenfield, David

2017-11-28

Recognition of a need for patient-centred care is not new, however making patient-centred care a reality remains a challenge to organisations. We need empirical studies to extend current understandings, create new representations of the complexity of patient-centred care, and guide collective action toward patient-centred health care. To achieve these ends, the research aim was to empirically determine what organisational actions are required for patient-centred care to be achieved. We used an established participatory concept mapping methodology. Cross-sector stakeholders contributed to the development of statements for patient-centred care requirements, sorting statements into groupings according to similarity, and rating each statement according to importance, feasibility, and achievement. The resultant data were analysed to produce a visual concept map representing participants' conceptualisation of patient-centred care requirements. Analysis included the development of a similarity matrix, multidimensional scaling, hierarchical cluster analysis, selection of the number of clusters and their labels, identifying overarching domains and quantitative representation of rating data. The outcome was the development of a conceptual map for the Requirements of Patient-Centred Care Systems (ROPCCS). ROPCCS incorporates 123 statements sorted into 13 clusters. Cluster labels were: shared responsibility for personalised health literacy; patient provider dynamic for care partnership; collaboration; shared power and responsibility; resources for coordination of care; recognition of humanity - skills and attributes; knowing and valuing the patient; relationship building; system review evaluation and new models; commitment to supportive structures and processes; elements to facilitate change; professional identity and capability development; and explicit education and learning. The clusters were grouped into three overarching domains, representing a cross-sectoral approach: humanity and partnership; career spanning education and training; and health systems, policy and management. Rating of statements allowed the generation of go-zone maps for further interrogation of the relative importance, feasibility, and achievement of each patient-centred care requirement and cluster. The study has empirically determined requirements for patient-centred care through the development of ROPCCS. The unique map emphasises collaborative responsibility of stakeholders to ensure that patient-centred care is comprehensively progressed. ROPCCS allows the complex requirements for patient-centred care to be understood, implemented, evaluated, measured, and shown to be occurring.

Data Mining Technologies Inspired from Visual Principle

NASA Astrophysics Data System (ADS)

Xu, Zongben

In this talk we review the recent work done by our group on data mining (DM) technologies deduced from simulating visual principle. Through viewing a DM problem as a cognition problems and treading a data set as an image with each light point located at a datum position, we developed a series of high efficient algorithms for clustering, classification and regression via mimicking visual principles. In pattern recognition, human eyes seem to possess a singular aptitude to group objects and find important structure in an efficient way. Thus, a DM algorithm simulating visual system may solve some basic problems in DM research. From this point of view, we proposed a new approach for data clustering by modeling the blurring effect of lateral retinal interconnections based on scale space theory. In this approach, as the data image blurs, smaller light blobs merge into large ones until the whole image becomes one light blob at a low enough level of resolution. By identifying each blob with a cluster, the blurring process then generates a family of clustering along the hierarchy. The proposed approach provides unique solutions to many long standing problems, such as the cluster validity and the sensitivity to initialization problems, in clustering. We extended such an approach to classification and regression problems, through combatively employing the Weber's law in physiology and the cell response classification facts. The resultant classification and regression algorithms are proven to be very efficient and solve the problems of model selection and applicability to huge size of data set in DM technologies. We finally applied the similar idea to the difficult parameter setting problem in support vector machine (SVM). Viewing the parameter setting problem as a recognition problem of choosing a visual scale at which the global and local structures of a data set can be preserved, and the difference between the two structures be maximized in the feature space, we derived a direct parameter setting formula for the Gaussian SVM. The simulations and applications show that the suggested formula significantly outperforms the known model selection methods in terms of efficiency and precision.

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

NASA Astrophysics Data System (ADS)

Oh, Yoo Rhee; Kim, Hong Kook

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

Syllables and bigrams: orthographic redundancy and syllabic units affect visual word recognition at different processing levels.

PubMed

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

2009-04-01

Over the last decade, there has been increasing evidence for syllabic processing during visual word recognition. If syllabic effects prove to be independent from orthographic redundancy, this would seriously challenge the ability of current computational models to account for the processing of polysyllabic words. Three experiments are presented to disentangle effects of the frequency of syllabic units and orthographic segments in lexical decision. In Experiment 1 the authors obtained an inhibitory syllable frequency effect that was unaffected by the presence or absence of a bigram trough at the syllable boundary. In Experiments 2 and 3 an inhibitory effect of initial syllable frequency but a facilitative effect of initial bigram frequency emerged when manipulating 1 of the 2 measures and controlling for the other in Spanish words starting with consonant-vowel syllables. The authors conclude that effects of syllable frequency and letter-cluster frequency are independent and arise at different processing levels of visual word recognition. Results are discussed within the framework of an interactive activation model of visual word recognition. (c) 2009 APA, all rights reserved.

Speech recognition systems on the Cell Broadband Engine

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

Liu, Y; Jones, H; Vaidya, S

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

Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

PubMed

Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

2018-01-11

By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

PubMed

Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

2015-12-01

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

C60 Recognition from Extended Tetrathiafulvalene Bis-acetylide Platinum(II) Complexes.

PubMed

Bastien, Guillaume; Dron, Paul I; Vincent, Manon; Canevet, David; Allain, Magali; Goeb, Sébastien; Sallé, Marc

2016-11-18

The favorable spatial organization imposed by the square planar 4,4'-di(tert-butyl)-2,2'-bipyridine (dbbpy) platinum(II) complex associated with the electronic and shape complementarity of π-extended tetrathiafulvalene derivatives (exTTF) toward fullerenes is usefully exploited to construct molecular tweezers, which display good affinities for C 60 .

Recognition of Schematic Facial Displays of Emotion in Parents of Children with Autism

ERIC Educational Resources Information Center

Palermo, Mark T.; Pasqualetti, Patrizio; Barbati, Giulia; Intelligente, Fabio; Rossini, Paolo Maria

2006-01-01

Performance on an emotional labeling task in response to schematic facial patterns representing five basic emotions without the concurrent presentation of a verbal category was investigated in 40 parents of children with autism and 40 matched controls. "Autism fathers" performed worse than "autism mothers," who performed worse than controls in…

49 CFR 571.101 - Standard No. 101; Controls and displays.

Code of Federal Regulations, 2013 CFR

2013-10-01

... accessibility, visibility and recognition of motor vehicle controls, telltales and indicators, and to facilitate... pressing on the center of the face plane of the steering wheel hub; or for a turn signal control that is operated in a plane essentially parallel to the face plane of the steering wheel in its normal driving...

49 CFR 571.101 - Standard No. 101; Controls and displays.

Code of Federal Regulations, 2010 CFR

2010-10-01

... accessibility, visibility and recognition of motor vehicle controls, telltales and indicators, and to facilitate... pressing on the center of the face plane of the steering wheel hub; or for a turn signal control that is operated in a plane essentially parallel to the face plane of the steering wheel in its normal driving...

49 CFR 571.101 - Standard No. 101; Controls and displays.

Code of Federal Regulations, 2014 CFR

2014-10-01

... accessibility, visibility and recognition of motor vehicle controls, telltales and indicators, and to facilitate... pressing on the center of the face plane of the steering wheel hub; or for a turn signal control that is operated in a plane essentially parallel to the face plane of the steering wheel in its normal driving...

49 CFR 571.101 - Standard No. 101; Controls and displays.

Code of Federal Regulations, 2012 CFR

2012-10-01

... accessibility, visibility and recognition of motor vehicle controls, telltales and indicators, and to facilitate... pressing on the center of the face plane of the steering wheel hub; or for a turn signal control that is operated in a plane essentially parallel to the face plane of the steering wheel in its normal driving...

49 CFR 571.101 - Standard No. 101; Controls and displays.

Code of Federal Regulations, 2011 CFR

2011-10-01

... accessibility, visibility and recognition of motor vehicle controls, telltales and indicators, and to facilitate... pressing on the center of the face plane of the steering wheel hub; or for a turn signal control that is operated in a plane essentially parallel to the face plane of the steering wheel in its normal driving...