A fusion approach for coarse-to-fine target recognition

NASA Astrophysics Data System (ADS)

Folkesson, Martin; Grönwall, Christina; Jungert, Erland

2006-04-01

A fusion approach in a query based information system is presented. The system is designed for querying multimedia data bases, and here applied to target recognition using heterogeneous data sources. The recognition process is coarse-to-fine, with an initial attribute estimation step and a following matching step. Several sensor types and algorithms are involved in each of these two steps. An independence of the matching results, on the origin of the estimation results, is observed. It allows for distribution of data between algorithms in an intermediate fusion step, without risk of data incest. This increases the overall chance of recognising the target. An implementation of the system is described.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Target recognition of ladar range images using even-order Zernike moments.

PubMed

Liu, Zheng-Jun; Li, Qi; Xia, Zhi-Wei; Wang, Qi

2012-11-01

Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.

Domain Regeneration for Cross-Database Micro-Expression Recognition

NASA Astrophysics Data System (ADS)

Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

2018-05-01

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

Extended target recognition in cognitive radar networks.

PubMed

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

2010-01-01

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

Parietal lobe critically supports successful paired immediate and single-item delayed memory for targets.

PubMed

Krumm, Sabine; Kivisaari, Sasa L; Monsch, Andreas U; Reinhardt, Julia; Ulmer, Stephan; Stippich, Christoph; Kressig, Reto W; Taylor, Kirsten I

2017-05-01

The parietal lobe is important for successful recognition memory, but its role is not yet fully understood. We investigated the parietal lobes' contribution to immediate paired-associate memory and delayed item-recognition memory separately for hits (targets) and correct rejections (distractors). We compared the behavioral performance of 56 patients with known parietal and medial temporal lobe dysfunction (i.e. early Alzheimer's Disease) to 56 healthy control participants in an immediate paired and delayed single item object memory task. Additionally, we performed voxel-based morphometry analyses to investigate the functional-neuroanatomic relationships between performance and voxel-based estimates of atrophy in whole-brain analyses. Behaviorally, all participants performed better identifying targets than rejecting distractors. The voxel-based morphometry analyses associated atrophy in the right ventral parietal cortex with fewer correct responses to familiar items (i.e. hits) in the immediate and delayed conditions. Additionally, medial temporal lobe integrity correlated with better performance in rejecting distractors, but not in identifying targets, in the immediate paired-associate task. Our findings suggest that the parietal lobe critically supports successful immediate and delayed target recognition memory, and that the ventral aspect of the parietal cortex and the medial temporal lobe may have complementary preferences for identifying targets and rejecting distractors, respectively, during recognition memory. Copyright © 2017. Published by Elsevier Inc.

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute

PubMed Central

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-01-01

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson–Crick base-pairing even in the 3′-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5′ base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region. PMID:27325485

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute.

PubMed

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-06-21

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson-Crick base-pairing even in the 3'-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5' base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region.

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.

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.

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Composite Wavelet Filters for Enhanced Automated Target Recognition

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Using eye movements as an index of implicit face recognition in autism spectrum disorder.

PubMed

Hedley, Darren; Young, Robyn; Brewer, Neil

2012-10-01

Individuals with an autism spectrum disorder (ASD) typically show impairment on face recognition tasks. Performance has usually been assessed using overt, explicit recognition tasks. Here, a complementary method involving eye tracking was used to examine implicit face recognition in participants with ASD and in an intelligence quotient-matched non-ASD control group. Differences in eye movement indices between target and foil faces were used as an indicator of implicit face recognition. Explicit face recognition was assessed using old-new discrimination and reaction time measures. Stimuli were faces of studied (target) or unfamiliar (foil) persons. Target images at test were either identical to the images presented at study or altered by changing the lighting, pose, or by masking with visual noise. Participants with ASD performed worse than controls on the explicit recognition task. Eye movement-based measures, however, indicated that implicit recognition may not be affected to the same degree as explicit recognition. Autism Res 2012, 5: 363-379. © 2012 International Society for Autism Research, Wiley Periodicals, Inc. © 2012 International Society for Autism Research, Wiley Periodicals, Inc.

Object recognition of real targets using modelled SAR images

NASA Astrophysics Data System (ADS)

Zherdev, D. A.

2017-12-01

In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework.

PubMed

Wei, Shengjing; Chen, Xiang; Yang, Xidong; Cao, Shuai; Zhang, Xu

2016-04-19

Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL) sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set) suggested by two reference subjects, (82.6 ± 13.2)% and (79.7 ± 13.4)% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7)% and (86.3 ± 13.7)% when the training set included 50~60 gestures (about half of the target gesture set). The proposed framework can significantly reduce the user's training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.

The method of micro-motion cycle feature extraction based on confidence coefficient evaluation criteria

NASA Astrophysics Data System (ADS)

Tang, Chuanzi; Ren, Hongmei; Bo, Li; Jing, Huang

2017-11-01

In radar target recognition, the micro motion characteristics of target is one of the characteristics that researchers pay attention to at home and abroad, in which the characteristics of target precession cycle is one of the important characteristics of target movement characteristics. Periodic feature extraction methods have been studied for years, the complex shape of the target and the scattering center stack lead to random fluctuations of the RCS. These random fluctuations also exist certain periodicity, which has a great influence on the target recognition result. In order to solve the problem, this paper proposes a extraction method of micro-motion cycle feature based on confidence coefficient evaluation criteria.

The research of multi-frame target recognition based on laser active imaging

NASA Astrophysics Data System (ADS)

Wang, Can-jin; Sun, Tao; Wang, Tin-feng; Chen, Juan

2013-09-01

Laser active imaging is fit to conditions such as no difference in temperature between target and background, pitch-black night, bad visibility. Also it can be used to detect a faint target in long range or small target in deep space, which has advantage of high definition and good contrast. In one word, it is immune to environment. However, due to the affect of long distance, limited laser energy and atmospheric backscatter, it is impossible to illuminate the whole scene at the same time. It means that the target in every single frame is unevenly or partly illuminated, which make the recognition more difficult. At the same time the speckle noise which is common in laser active imaging blurs the images . In this paper we do some research on laser active imaging and propose a new target recognition method based on multi-frame images . Firstly, multi pulses of laser is used to obtain sub-images for different parts of scene. A denoising method combined homomorphic filter with wavelet domain SURE is used to suppress speckle noise. And blind deconvolution is introduced to obtain low-noise and clear sub-images. Then these sub-images are registered and stitched to combine a completely and uniformly illuminated scene image. After that, a new target recognition method based on contour moments is proposed. Firstly, canny operator is used to obtain contours. For each contour, seven invariant Hu moments are calculated to generate the feature vectors. At last the feature vectors are input into double hidden layers BP neural network for classification . Experiments results indicate that the proposed algorithm could achieve a high recognition rate and satisfactory real-time performance for laser active imaging.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Specific recognition of polyphenols by molecularly imprinted polymers based on a ternary deep eutectic solvent.

PubMed

Fu, Najing; Li, Liteng; Liu, Xiao; Fu, Nian; Zhang, Chenchen; Hu, Liandong; Li, Donghao; Tang, Baokun; Zhu, Tao

2017-12-29

Typically, a target compound is selected as a template for a molecularly imprinted polymer (MIP); however, some target compounds are not suitable as templates because of their poor solubility. Using the tailoring properties of a deep eutectic solvent (DES), the insoluble target compound caffeic acid was transformed into a ternary choline chloride-caffeic acid-ethylene glycol (ChCl-CA-EG) DES, which was then employed as a template to prepare MIPs. The ternary DES-based MIPs were characterized by Fourier transform infrared spectroscopy, elemental analysis, scanning electron microscopy, and atomic force microscopy. The effects of time, temperature, ionic strength, and pH on the recognition processes for four polyphenols (caffeic acid, protocatechuic acid, catechin, and epicatechin) by 13 ChCl-CA-EG ternary DES-based MIPs was investigated using high-performance liquid chromatography. The recognition specificity of the MIPs for CA was significantly better than that for the other polyphenols, and the MIPs exhibited obvious characteristics of chromatographic packing materials. In addition, the recognition processes mainly followed a second-order kinetics model and the Freundlich isotherm model, which together indicated that the MIPs mainly recognized the polyphenols by chemical interactions including ion exchange, electron exchange, and new bond formation. Furthermore, the specific recognition ability of the MIPs for polyphenols, which was better than those of C 18 , C 8 , or non-molecularly imprinted polymer adsorbents, was successfully applied to the recognition of polyphenols in a Radix asteris sample. The transformation of an insoluble target compound in a polymeric DES for MIP preparation and recognition is a novel and feasible strategy suitable for use in further MIP research developments. Copyright © 2017 Elsevier B.V. All rights reserved.

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.

2011-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

Target recognition based on convolutional neural network

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

2017-11-01

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

NASA Astrophysics Data System (ADS)

Yan, Yue

2018-03-01

A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

Cat-eye effect target recognition with single-pixel detectors

NASA Astrophysics Data System (ADS)

Jian, Weijian; Li, Li; Zhang, Xiaoyue

2015-12-01

A prototype of cat-eye effect target recognition with single-pixel detectors is proposed. Based on the framework of compressive sensing, it is possible to recognize cat-eye effect targets by projecting a series of known random patterns and measuring the backscattered light with three single-pixel detectors in different locations. The prototype only requires simpler, less expensive detectors and extends well beyond the visible spectrum. The simulations are accomplished to evaluate the feasibility of the proposed prototype. We compared our results to that obtained from conventional cat-eye effect target recognition methods using area array sensor. The experimental results show that this method is feasible and superior to the conventional method in dynamic and complicated backgrounds.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Model-based vision using geometric hashing

NASA Astrophysics Data System (ADS)

Akerman, Alexander, III; Patton, Ronald

1991-04-01

The Geometric Hashing technique developed by the NYU Courant Institute has been applied to various automatic target recognition applications. In particular, I-MATH has extended the hashing algorithm to perform automatic target recognition ofsynthetic aperture radar (SAR) imagery. For this application, the hashing is performed upon the geometric locations of dominant scatterers. In addition to being a robust model-based matching algorithm -- invariant under translation, scale, and 3D rotations of the target -- hashing is of particular utility because it can still perform effective matching when the target is partially obscured. Moreover, hashing is very amenable to a SIMD parallel processing architecture, and thus potentially realtime implementable.

Learning target masks in infrared linescan imagery

NASA Astrophysics Data System (ADS)

Fechner, Thomas; Rockinger, Oliver; Vogler, Axel; Knappe, Peter

1997-04-01

In this paper we propose a neural network based method for the automatic detection of ground targets in airborne infrared linescan imagery. Instead of using a dedicated feature extraction stage followed by a classification procedure, we propose the following three step scheme: In the first step of the recognition process, the input image is decomposed into its pyramid representation, thus obtaining a multiresolution signal representation. At the lowest three levels of the Laplacian pyramid a neural network filter of moderate size is trained to indicate the target location. The last step consists of a fusion process of the several neural network filters to obtain the final result. To perform this fusion we use a belief network to combine the various filter outputs in a statistical meaningful way. In addition, the belief network allows the integration of further knowledge about the image domain. By applying this multiresolution recognition scheme, we obtain a nearly scale- and rotational invariant target recognition with a significantly decreased false alarm rate compared with a single resolution target recognition scheme.

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

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

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

The utility of multiple synthesized views in the recognition of unfamiliar faces.

PubMed

Jones, Scott P; Dwyer, Dominic M; Lewis, Michael B

2017-05-01

The ability to recognize an unfamiliar individual on the basis of prior exposure to a photograph is notoriously poor and prone to errors, but recognition accuracy is improved when multiple photographs are available. In applied situations, when only limited real images are available (e.g., from a mugshot or CCTV image), the generation of new images might provide a technological prosthesis for otherwise fallible human recognition. We report two experiments examining the effects of providing computer-generated additional views of a target face. In Experiment 1, provision of computer-generated views supported better target face recognition than exposure to the target image alone and equivalent performance to that for exposure of multiple photograph views. Experiment 2 replicated the advantage of providing generated views, but also indicated an advantage for multiple viewings of the single target photograph. These results strengthen the claim that identifying a target face can be improved by providing multiple synthesized views based on a single target image. In addition, our results suggest that the degree of advantage provided by synthesized views may be affected by the quality of synthesized material.

Research and Development of Target Recognition and Location Crawling Platform based on Binocular Vision

NASA Astrophysics Data System (ADS)

Xu, Weidong; Lei, Zhu; Yuan, Zhang; Gao, Zhenqing

2018-03-01

The application of visual recognition technology in industrial robot crawling and placing operation is one of the key tasks in the field of robot research. In order to improve the efficiency and intelligence of the material sorting in the production line, especially to realize the sorting of the scattered items, the robot target recognition and positioning crawling platform based on binocular vision is researched and developed. The images were collected by binocular camera, and the images were pretreated. Harris operator was used to identify the corners of the images. The Canny operator was used to identify the images. Hough-chain code recognition was used to identify the images. The target image in the image, obtain the coordinates of each vertex of the image, calculate the spatial position and posture of the target item, and determine the information needed to capture the movement and transmit it to the robot control crawling operation. Finally, In this paper, we use this method to experiment the wrapping problem in the express sorting process The experimental results show that the platform can effectively solve the problem of sorting of loose parts, so as to achieve the purpose of efficient and intelligent sorting.

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Vigilante: Ultrafast Smart Sensor for Target Recognition and Precision Tracking in a Simulated CMD Scenario

NASA Technical Reports Server (NTRS)

Uldomkesmalee, Suraphol; Suddarth, Steven C.

1997-01-01

VIGILANTE is an ultrafast smart sensor testbed for generic Automatic Target Recognition (ATR) applications with a series of capability demonstration focussed on cruise missile defense (CMD). VIGILANTE's sensor/processor architecture is based on next-generation UV/visible/IR sensors and a tera-operations per second sugar-cube processor, as well as supporting airborne vehicle. Excellent results of efficient ATR methodologies that use an eigenvectors/neural network combination and feature-based precision tracking have been demonstrated in the laboratory environment.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people's dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by the proposed ELRCC algorithm. This amount of improvement represents a reduction of probability of false alarm by about a factor of 5 at the probability of detection of 0.5. Our study concerns mainly the detection of colored targets; and issues for the recognition of white or gray targets will be addressed in a forthcoming study.

Laser range profiling for small target recognition

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Tulldahl, Michael

2016-05-01

The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

Low, slow, small target recognition based on spatial vision network

NASA Astrophysics Data System (ADS)

Cheng, Zhao; Guo, Pei; Qi, Xin

2018-03-01

Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.

Autonomous space target recognition and tracking approach using star sensors based on a Kalman filter.

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.

Bioinspired Pollen-Like Hierarchical Surface for Efficient Recognition of Target Cancer Cells.

PubMed

Wang, Wenshuo; Yang, Gao; Cui, Haijun; Meng, Jingxin; Wang, Shutao; Jiang, Lei

2017-08-01

The efficient recognition and isolation of rare cancer cells holds great promise for cancer diagnosis and prognosis. In nature, pollens exploit spiky structures to realize recognition and adhesion to stigma. Herein, a bioinspired pollen-like hierarchical surface is developed by replicating the assembly of pollen grains, and efficient and specific recognition to target cancer cells is achieved. The pollen-like surface is fabricated by combining filtering-assisted assembly and soft lithography-based replication of pollen grains of wild chrysanthemum. After modification with a capture agent specific to cancer cells, the pollen-like surface enables the capture of target cancer cells with high efficiency and specificity. In addition, the pollen-like surface not only assures high viability of captured cells but also performs well in cell mixture system and at low cell density. This study represents a good example of constructing cell recognition biointerfaces inspired by pollen-stigma adhesion. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The study of infrared target recognition at sea background based on visual attention computational model

NASA Astrophysics Data System (ADS)

Wang, Deng-wei; Zhang, Tian-xu; Shi, Wen-jun; Wei, Long-sheng; Wang, Xiao-ping; Ao, Guo-qing

2009-07-01

Infrared images at sea background are notorious for the low signal-to-noise ratio, therefore, the target recognition of infrared image through traditional methods is very difficult. In this paper, we present a novel target recognition method based on the integration of visual attention computational model and conventional approach (selective filtering and segmentation). The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The visual attention algorithm searches the salient regions automatically, and represented them by a set of winner points, at the same time, demonstrated the salient regions in terms of circles centered at these winner points. This provides a priori knowledge for the filtering and segmentation process. Based on the winner point, we construct a rectangular region to facilitate the filtering and segmentation, then the labeling operation will be added selectively by requirement. Making use of the labeled information, from the final segmentation result we obtain the positional information of the interested region, label the centroid on the corresponding original image, and finish the localization for the target. The cost time does not depend on the size of the image but the salient regions, therefore the consumed time is greatly reduced. The method is used in the recognition of several kinds of real infrared images, and the experimental results reveal the effectiveness of the algorithm presented in this paper.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

On a problematic procedure to manipulate response biases in recognition experiments: the case of "implied" base rates.

PubMed

Bröder, Arndt; Malejka, Simone

2017-07-01

The experimental manipulation of response biases in recognition-memory tests is an important means for testing recognition models and for estimating their parameters. The textbook manipulations for binary-response formats either vary the payoff scheme or the base rate of targets in the recognition test, with the latter being the more frequently applied procedure. However, some published studies reverted to implying different base rates by instruction rather than actually changing them. Aside from unnecessarily deceiving participants, this procedure may lead to cognitive conflicts that prompt response strategies unknown to the experimenter. To test our objection, implied base rates were compared to actual base rates in a recognition experiment followed by a post-experimental interview to assess participants' response strategies. The behavioural data show that recognition-memory performance was estimated to be lower in the implied base-rate condition. The interview data demonstrate that participants used various second-order response strategies that jeopardise the interpretability of the recognition data. We thus advice researchers against substituting actual base rates with implied base rates.

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units

PubMed Central

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-01-01

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions. PMID:28208684

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units.

PubMed

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-02-12

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

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

PubMed

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

2002-01-01

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

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

PubMed Central

Peng, Yuan; Qiu, Mengran; Shi, Jianfei; Liu, Liangliang

2018-01-01

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved. PMID:29780407

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Programmable and multiparameter DNA-based logic platform for cancer recognition and targeted therapy.

PubMed

You, Mingxu; Zhu, Guizhi; Chen, Tao; Donovan, Michael J; Tan, Weihong

2015-01-21

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy.

Unusual target site disruption by the rare-cutting HNH restriction endonuclease PacI

PubMed Central

Shen, Betty; Heiter, Daniel F.; Chan, Siu-Hong; Wang, Hua; Xu, Shuang-Yong; Morgan, Richard D.; Wilson, Geoffrey G.; Stoddard, Barry L.

2010-01-01

The crystal structure of the rare-cutting HNH restriction endonuclease PacI in complex with its eight base pair target recognition sequence 5'-TTAATTAA-3' has been determined to 1.9 Å resolution. The enzyme forms an extended homodimer, with each subunit containing two zinc-bound motifs surrounding a ββα-metal catalytic site. The latter is unusual in that a tyrosine residue likely initiates strand-cleavage. PacI dramatically distorts its target sequence from Watson-Crick duplex DNA basepairing, with every base separated from its original partner. Two bases on each strand are unpaired, four are engaged in non-canonical A:A and T:T base pairs, and the remaining two bases are matched with new Watson-Crick partners. This represents a highly unusual DNA binding mechanism for a restriction endonuclease, and implies that initial recognition of the target site might involve significantly different contacts from those visualized in the DNA-bound cocrystal structures. PMID:20541511

Hierarchical Context Modeling for Video Event Recognition.

PubMed

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

Space-based infrared sensors of space target imaging effect analysis

NASA Astrophysics Data System (ADS)

Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang

2018-02-01

Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.

A new FOD recognition algorithm based on multi-source information fusion and experiment analysis

NASA Astrophysics Data System (ADS)

Li, Yu; Xiao, Gang

2011-08-01

Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.

An automatic target recognition system based on SAR image

NASA Astrophysics Data System (ADS)

Li, Qinfu; Wang, Jinquan; Zhao, Bo; Luo, Furen; Xu, Xiaojian

2009-10-01

In this paper, an automatic target recognition (ATR) system based on synthetic aperture radar (SAR) is proposed. This ATR system can play an important role in the simulation of up-to-data battlefield environment and be used in ATR research. To establish an integral and available system, the processing of SAR image was divided into four main stages which are de-noise, detection, cluster-discrimination and segment-recognition, respectively. The first three stages are used for searching region of interest (ROI). Once the ROIs are extracted, the recognition stage will be taken to compute the similarity between the ROIs and the templates in the electromagnetic simulation software National Electromagnetic Scattering Code (NESC). Due to the lack of the SAR raw data, the electromagnetic simulated images are added to the measured SAR background to simulate the battlefield environment8. The purpose of the system is to find the ROIs which can be the artificial military targets such as tanks, armored cars and so on and to categorize the ROIs into the right classes according to the existing templates. From the results we can see that the proposed system achieves a satisfactory result.

Testing Saliency Parameters for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Pandya, Sagar

2012-01-01

A bottom-up visual attention model (the saliency model) is tested to enhance the performance of Automated Target Recognition (ATR). JPL has developed an ATR system that identifies regions of interest (ROI) using a trained OT-MACH filter, and then classifies potential targets as true- or false-positives using machine-learning techniques. In this project, saliency is used as a pre-processing step to reduce the space for performing OT-MACH filtering. Saliency parameters, such as output level and orientation weight, are tuned to detect known target features. Preliminary results are promising and future work entails a rigrous and parameter-based search to gain maximum insight about this method.

Proactive and coactive interference in age-related performance in a recognition-based operation span task.

PubMed

Zeintl, Melanie; Kliegel, Matthias

2010-01-01

Generally, older adults perform worse than younger adults in complex working memory span tasks. So far, it is unclear which processes mainly contribute to age-related differences in working memory span. The aim of the present study was to investigate age effects and the roles of proactive and coactive interference in a recognition-based version of the operation span task. Younger and older adults performed standard versions and distracter versions of the operation span task. At retrieval, participants had to recognize target words in word lists containing targets as well as proactive and/or coactive interference-related lures. Results show that, overall, younger adults outperformed older adults in the recognition of target words. Furthermore, analyses of error types indicate that, while younger adults were only affected by simultaneously presented distracter words, older adults had difficulties with both proactive and coactive interference. Results suggest that age effects in complex span tasks may not be mainly due to retrieval deficits in old age. Copyright 2009 S. Karger AG, Basel.

Recognition Imaging of Acetylated Chromatin Using a DNA Aptamer

PubMed Central

Lin, Liyun; Fu, Qiang; Williams, Berea A.R.; Azzaz, Abdelhamid M.; Shogren-Knaak, Michael A.; Chaput, John C.; Lindsay, Stuart

2009-01-01

Histone acetylation plays an important role in the regulation of gene expression. A DNA aptamer generated by in vitro selection to be highly specific for histone H4 protein acetylated at lysine 16 was used as a recognition element for atomic force microscopy-based recognition imaging of synthetic nucleosomal arrays with precisely controlled acetylation. The aptamer proved to be reasonably specific at recognizing acetylated histones, with recognition efficiencies of 60% on-target and 12% off-target. Though this selectivity is much poorer than the >2000:1 equilibrium specificity of the aptamer, it is a large improvement on the performance of a ChIP-quality antibody, which is not selective at all in this application, and it should permit high-fidelity recognition with repeated imaging. The ability to image the precise location of posttranslational modifications may permit nanometer-scale investigation of their effect on chromatin structure. PMID:19751687

From scores to face templates: a model-based approach.

PubMed

Mohanty, Pranab; Sarkar, Sudeep; Kasturi, Rangachar

2007-12-01

Regeneration of templates from match scores has security and privacy implications related to any biometric authentication system. We propose a novel paradigm to reconstruct face templates from match scores using a linear approach. It proceeds by first modeling the behavior of the given face recognition algorithm by an affine transformation. The goal of the modeling is to approximate the distances computed by a face recognition algorithm between two faces by distances between points, representing these faces, in an affine space. Given this space, templates from an independent image set (break-in) are matched only once with the enrolled template of the targeted subject and match scores are recorded. These scores are then used to embed the targeted subject in the approximating affine (non-orthogonal) space. Given the coordinates of the targeted subject in the affine space, the original template of the targeted subject is reconstructed using the inverse of the affine transformation. We demonstrate our ideas using three, fundamentally different, face recognition algorithms: Principal Component Analysis (PCA) with Mahalanobis cosine distance measure, Bayesian intra-extrapersonal classifier (BIC), and a feature-based commercial algorithm. To demonstrate the independence of the break-in set with the gallery set, we select face templates from two different databases: Face Recognition Grand Challenge (FRGC) and Facial Recognition Technology (FERET) Database (FERET). With an operational point set at 1 percent False Acceptance Rate (FAR) and 99 percent True Acceptance Rate (TAR) for 1,196 enrollments (FERET gallery), we show that at most 600 attempts (score computations) are required to achieve a 73 percent chance of breaking in as a randomly chosen target subject for the commercial face recognition system. With similar operational set up, we achieve a 72 percent and 100 percent chance of breaking in for the Bayesian and PCA based face recognition systems, respectively. With three different levels of score quantization, we achieve 69 percent, 68 percent and 49 percent probability of break-in, indicating the robustness of our proposed scheme to score quantization. We also show that the proposed reconstruction scheme has 47 percent more probability of breaking in as a randomly chosen target subject for the commercial system as compared to a hill climbing approach with the same number of attempts. Given that the proposed template reconstruction method uses distinct face templates to reconstruct faces, this work exposes a more severe form of vulnerability than a hill climbing kind of attack where incrementally different versions of the same face are used. Also, the ability of the proposed approach to reconstruct actual face templates of the users increases privacy concerns in biometric systems.

Infrared target recognition based on improved joint local ternary pattern

NASA Astrophysics Data System (ADS)

Sun, Junding; Wu, Xiaosheng

2016-05-01

This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

The rational development of molecularly imprinted polymer-based sensors for protein detection.

PubMed

Whitcombe, Michael J; Chianella, Iva; Larcombe, Lee; Piletsky, Sergey A; Noble, James; Porter, Robert; Horgan, Adrian

2011-03-01

The detection of specific proteins as biomarkers of disease, health status, environmental monitoring, food quality, control of fermenters and civil defence purposes means that biosensors for these targets will become increasingly more important. Among the technologies used for building specific recognition properties, molecularly imprinted polymers (MIPs) are attracting much attention. In this critical review we describe many methods used for imprinting recognition for protein targets in polymers and their incorporation with a number of transducer platforms with the aim of identifying the most promising approaches for the preparation of MIP-based protein sensors (277 references).

DNA nanotechnology-enabled biosensors.

PubMed

Chao, Jie; Zhu, Dan; Zhang, Yinan; Wang, Lianhui; Fan, Chunhai

2016-02-15

Biosensors employ biological molecules to recognize the target and utilize output elements which can translate the biorecognition event into electrical, optical or mass-sensitive signals to determine the quantities of the target. DNA-based biosensors, as a sub-field to biosensor, utilize DNA strands with short oligonucleotides as probes for target recognition. Although DNA-based biosensors have offered a promising alternative for fast, simple and cheap detection of target molecules, there still exist key challenges including poor stability and reproducibility that hinder their competition with the current gold standard for DNA assays. By exploiting the self-recognition properties of DNA molecules, researchers have dedicated to make versatile DNA nanostructures in a highly rigid, controllable and functionalized manner, which offers unprecedented opportunities for developing DNA-based biosensors. In this review, we will briefly introduce the recent advances on design and fabrication of static and dynamic DNA nanostructures, and summarize their applications for fabrication and functionalization of DNA-based biosensors. Copyright © 2015 Elsevier B.V. All rights reserved.

Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

DTIC Science & Technology

2014-03-27

and machine learning for a range of research including such topics as medical imaging [10] and handwriting recognition [11]. The type of feature...1989. [11] C. Bahlmann, B. Haasdonk, and H. Burkhardt, “Online handwriting recognition with support vector machines-a kernel approach,” in Eighth...International Workshop on Frontiers in Handwriting Recognition, pp. 49–54, IEEE, 2002. [12] C. Cortes and V. Vapnik, “Support-vector networks,” Machine

The cross-category effect: mere social categorization is sufficient to elicit an own-group bias in face recognition.

PubMed

Bernstein, Michael J; Young, Steven G; Hugenberg, Kurt

2007-08-01

Although the cross-race effect (CRE) is a well-established phenomenon, both perceptual-expertise and social-categorization models have been proposed to explain the effect. The two studies reported here investigated the extent to which categorizing other people as in-group versus out-group members is sufficient to elicit a pattern of face recognition analogous to that of the CRE, even when perceptual expertise with the stimuli is held constant. In Study 1, targets were categorized as members of real-life in-groups and out-groups (based on university affiliation), whereas in Study 2, targets were categorized into experimentally created minimal groups. In both studies, recognition performance was better for targets categorized as in-group members, despite the fact that perceptual expertise was equivalent for in-group and out-group faces. These results suggest that social-cognitive mechanisms of in-group and out-group categorization are sufficient to elicit performance differences for in-group and out-group face recognition.

The research of edge extraction and target recognition based on inherent feature of objects

NASA Astrophysics Data System (ADS)

Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

2008-03-01

Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots fields. The results of simulation experiments and theory analyzing demonstrate that the proposed method could suppress noise effectively, extracted target edges robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

Transfer Learning for Activity Recognition: A Survey

PubMed Central

Cook, Diane; Feuz, Kyle D.; Krishnan, Narayanan C.

2013-01-01

Many intelligent systems that focus on the needs of a human require information about the activities being performed by the human. At the core of this capability is activity recognition, which is a challenging and well-researched problem. Activity recognition algorithms require substantial amounts of labeled training data yet need to perform well under very diverse circumstances. As a result, researchers have been designing methods to identify and utilize subtle connections between activity recognition datasets, or to perform transfer-based activity recognition. In this paper we survey the literature to highlight recent advances in transfer learning for activity recognition. We characterize existing approaches to transfer-based activity recognition by sensor modality, by differences between source and target environments, by data availability, and by type of information that is transferred. Finally, we present some grand challenges for the community to consider as this field is further developed. PMID:24039326

Adamantane in Drug Delivery Systems and Surface Recognition.

PubMed

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

2017-02-16

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

Simultaneous detection of multiple DNA targets by integrating dual-color graphene quantum dot nanoprobes and carbon nanotubes.

PubMed

Qian, Zhaosheng; Shan, Xiaoyue; Chai, Lujing; Chen, Jianrong; Feng, Hui

2014-12-01

Simultaneous detection of multiple DNA targets was achieved based on a biocompatible graphene quantum dots (GQDs) and carbon nanotubes (CNTs) platform through spontaneous assembly between dual-color GQD-based probes and CNTs and subsequently self-recognition between DNA probes and targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

Research on Radar Micro-Doppler Feature Parameter Estimation of Propeller Aircraft

NASA Astrophysics Data System (ADS)

He, Zhihua; Tao, Feixiang; Duan, Jia; Luo, Jingsheng

2018-01-01

The micro-motion modulation effect of the rotated propellers to radar echo can be a steady feature for aircraft target recognition. Thus, micro-Doppler feature parameter estimation is a key to accurate target recognition. In this paper, the radar echo of rotated propellers is modelled and simulated. Based on which, the distribution characteristics of the micro-motion modulation energy in time, frequency and time-frequency domain are analyzed. The micro-motion modulation energy produced by the scattering points of rotating propellers is accumulated using the Inverse-Radon (I-Radon) transform, which can be used to accomplish the estimation of micro-modulation parameter. Finally, it is proved that the proposed parameter estimation method is effective with measured data. The micro-motion parameters of aircraft can be used as the features of radar target recognition.

Programmable and Multiparameter DNA-Based Logic Platform For Cancer Recognition and Targeted Therapy

PubMed Central

2014-01-01

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy. PMID:25361164

Study of environmental sound source identification based on hidden Markov model for robust speech recognition

NASA Astrophysics Data System (ADS)

Nishiura, Takanobu; Nakamura, Satoshi

2003-10-01

Humans communicate with each other through speech by focusing on the target speech among environmental sounds in real acoustic environments. We can easily identify the target sound from other environmental sounds. For hands-free speech recognition, the identification of the target speech from environmental sounds is imperative. This mechanism may also be important for a self-moving robot to sense the acoustic environments and communicate with humans. Therefore, this paper first proposes hidden Markov model (HMM)-based environmental sound source identification. Environmental sounds are modeled by three states of HMMs and evaluated using 92 kinds of environmental sounds. The identification accuracy was 95.4%. This paper also proposes a new HMM composition method that composes speech HMMs and an HMM of categorized environmental sounds for robust environmental sound-added speech recognition. As a result of the evaluation experiments, we confirmed that the proposed HMM composition outperforms the conventional HMM composition with speech HMMs and a noise (environmental sound) HMM trained using noise periods prior to the target speech in a captured signal. [Work supported by Ministry of Public Management, Home Affairs, Posts and Telecommunications of Japan.

Optical implementation of a feature-based neural network with application to automatic target recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1993-01-01

An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

Automatic target recognition using a feature-based optical neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

Divided attention enhances the recognition of emotional stimuli: evidence from the attentional boost effect.

PubMed

Rossi-Arnaud, Clelia; Spataro, Pietro; Costanzi, Marco; Saraulli, Daniele; Cestari, Vincenzo

2018-01-01

The present study examined predictions of the early-phase-elevated-attention hypothesis of the attentional boost effect (ABE), which suggests that transient increases in attention at encoding, as instantiated in the ABE paradigm, should enhance the recognition of neutral and positive items (whose encoding is mostly based on controlled processes), while having small or null effects on the recognition of negative items (whose encoding is primarily based on automatic processes). Participants were presented a sequence of negative, neutral and positive stimuli (pictures in Experiment 1, words in Experiment 2) associated to target (red) squares, distractor (green) squares or no squares (baseline condition). They were told to attend to the pictures/words and simultaneously press the spacebar of the computer when a red square appeared. In a later recognition task, stimuli associated to target squares were recognised better than stimuli associated to distractor squares, replicating the standard ABE. More importantly, we also found that: (a) the memory enhancement following target detection occurred with all types of stimuli (neutral, negative and positive) and (b) the advantage of negative stimuli over neutral stimuli was intact in the DA condition. These findings suggest that the encoding of negative stimuli depends on both controlled (attention-dependent) and automatic (attention-independent) processes.

Retrieval Failure Contributes to Gist-Based False Recognition

PubMed Central

Guerin, Scott A.; Robbins, Clifford A.; Gilmore, Adrian W.; Schacter, Daniel L.

2011-01-01

People often falsely recognize items that are similar to previously encountered items. This robust memory error is referred to as gist-based false recognition. A widely held view is that this error occurs because the details fade rapidly from our memory. Contrary to this view, an initial experiment revealed that, following the same encoding conditions that produce high rates of gist-based false recognition, participants overwhelmingly chose the correct target rather than its related foil when given the option to do so. A second experiment showed that this result is due to increased access to stored details provided by reinstatement of the originally encoded photograph, rather than to increased attention to the details. Collectively, these results suggest that details needed for accurate recognition are, to a large extent, still stored in memory and that a critical factor determining whether false recognition will occur is whether these details can be accessed during retrieval. PMID:22125357

Recognition during recall failure: Semantic feature matching as a mechanism for recognition of semantic cues when recall fails.

PubMed

Cleary, Anne M; Ryals, Anthony J; Wagner, Samantha R

2016-01-01

Research suggests that a feature-matching process underlies cue familiarity-detection when cued recall with graphemic cues fails. When a test cue (e.g., potchbork) overlaps in graphemic features with multiple unrecalled studied items (e.g., patchwork, pitchfork, pocketbook, pullcork), higher cue familiarity ratings are given during recall failure of all of the targets than when the cue overlaps in graphemic features with only one studied target and that target fails to be recalled (e.g., patchwork). The present study used semantic feature production norms (McRae et al., Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005) to examine whether the same holds true when the cues are semantic in nature (e.g., jaguar is used to cue cheetah). Indeed, test cues (e.g., cedar) that overlapped in semantic features (e.g., a_tree, has_bark, etc.) with four unretrieved studied items (e.g., birch, oak, pine, willow) received higher cue familiarity ratings during recall failure than test cues that overlapped in semantic features with only two (also unretrieved) studied items (e.g., birch, oak), which in turn received higher familiarity ratings during recall failure than cues that did not overlap in semantic features with any studied items. These findings suggest that the feature-matching theory of recognition during recall failure can accommodate recognition of semantic cues during recall failure, providing a potential mechanism for conceptually-based forms of cue recognition during target retrieval failure. They also provide converging evidence for the existence of the semantic features envisaged in feature-based models of semantic knowledge representation and for those more concretely specified by the production norms of McRae et al. (Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005).

Thermodynamics of DNA target site recognition by homing endonucleases

PubMed Central

Eastberg, Jennifer H.; Smith, Audrey McConnell; Zhao, Lei; Ashworth, Justin; Shen, Betty W.; Stoddard, Barry L.

2007-01-01

The thermodynamic profiles of target site recognition have been surveyed for homing endonucleases from various structural families. Similar to DNA-binding proteins that recognize shorter target sites, homing endonucleases display a narrow range of binding free energies and affinities, mediated by structural interactions that balance the magnitude of enthalpic and entropic forces. While the balance of ΔH and TΔS are not strongly correlated with the overall extent of DNA bending, unfavorable ΔHbinding is associated with unstacking of individual base steps in the target site. The effects of deleterious basepair substitutions in the optimal target sites of two LAGLIDADG homing endonucleases, and the subsequent effect of redesigning one of those endonucleases to accommodate that DNA sequence change, were also measured. The substitution of base-specific hydrogen bonds in a wild-type endonuclease/DNA complex with hydrophobic van der Waals contacts in a redesigned complex reduced the ability to discriminate between sites, due to nonspecific ΔSbinding. PMID:17947319

Evaluation of target acquisition difficulty using recognition distance to measure required retinal area

NASA Astrophysics Data System (ADS)

Nilsson, Thomy H.

2001-09-01

The psychophysical method of limits was used to measure the distance at which observers could distinguish military vehicles photographed in natural landscapes. Obtained from the TNO-TM Search_2 dataset, these pictures either were rear-projected 35-mm slides or were presented on a computer monitor. Based on the rationale that more difficult vehicle targets would require more visual pathways for recognition, difficult of acquisition was defined in terms of the relative retinal area required for recognition. Relative retinal area was derived from the inverse square of the recognition distance of a particular vehicle relative to the distance of the vehicle that could be seen furthest away. Results are compared with data on the time required to find the vehicles in these pictures. These comparison indicate recognition distance thresholds can be a suitable means of defining standards for the effectiveness of vital graphic information; and the two methods are complementary with respect to distinguishing different degrees of acquisition difficulty, and together may provide a means to measure the total information processing required for recognition.

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at participating nodes. Therefore, the feature-extraction method based on the Haar DWT is presented that employs a maximum-entropy measure to determine significant wavelet coefficients. Features are formed by calculating the energy of coefficients grouped around the competing clusters. A DWT-based feature extraction algorithm used for vehicle classification in WSNs can be enhanced by an added rule for selecting the optimal number of resolution levels to improve the correct classification rate and reduce energy consumption expended in local algorithm computations. Published field trial data for vehicular ground targets, measured with multiple sensor types, are used to evaluate the wavelet-assisted algorithms. Extracted features are used in established target recognition routines, e.g., the Bayesian minimum-error-rate classifier, to compare the effects on the classification performance of the wavelet compression. Simulations of feature sets and recognition routines at different resolution levels in target scenarios indicate the impact on classification rates, while formulas are provided to estimate reduction in resource use due to distributed compression.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

NASA Astrophysics Data System (ADS)

Kim, Sungho

2017-06-01

Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

An Unsolved Mystery: The Target-Recognizing RNA Species of MicroRNA Genes

PubMed Central

Chen, Chang-Zheng

2013-01-01

MicroRNAs (miRNAs) are an abundant class of endogenous ~ 21-nucleotide (nt) RNAs. These small RNAs are produced from long primary miRNA transcripts — pri-miRNAs — through sequential endonucleolytic maturation steps that yield precursor miRNA (pre-miRNA) intermediates and then the mature miRNAs. The mature miRNAs are loaded into the RNA-induced silencing complexes (RISC), and guide RISC to target mRNAs for cleavage and/or translational repression. This paradigm, which represents one of major discoveries of modern molecular biology, is built on the assumption that mature miRNAs are the only species produced from miRNA genes that recognize targets. This assumption has guided the miRNA field for more than a decade and has led to our current understanding of the mechanisms of target recognition and repression by miRNAs. Although progress has been made, fundamental questions remain unanswered with regard to the principles of target recognition and mechanisms of repression. Here I raise questions about the assumption that mature miRNAs are the only target-recognizing species produced from miRNA genes and discuss the consequences of working under an incomplete or incorrect assumption. Moreover, I present evolution-based and experimental evidence that support the roles of pri-/pre-miRNAs in target recognition and repression. Finally, I propose a conceptual framework that integrates the functions of pri-/pre-miRNAs and mature miRNAs in target recognition and repression. The integrated framework opens experimental enquiry and permits interpretation of fundamental problems that have so far been precluded. PMID:23685275

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

The effects of context in item-based directed forgetting: Evidence for "one-shot" context storage.

PubMed

Burgess, Nicole; Hockley, William E; Hourihan, Kathleen L

2017-07-01

The effects of context on item-based directed forgetting were assessed. Study words were presented against different background pictures and were followed by a cue to remember (R) or forget (F) the target item. The effects of incidental and intentional encoding of context on recognition of the study words were examined in Experiments 1 and 2. Recognition memory for the picture contexts was assessed in Experiments 3a and 3b. Recognition was greater for R-cued compared to F-cued targets, demonstrating an effect of directed forgetting. In contrast, no directed forgetting effect was seen for the background pictures. An effect of context-dependent recognition was seen in Experiments 1 and 2, such that the hit rate and the false-alarm rate were greater for items tested in an old compared to a novel context. An effect of context-dependent discrimination was also observed in Experiment 2 as the hit rate was greater for targets shown in their same old study context compared to a different old context. The effects of context and directed forgetting did not interact. The results are consistent with Malmberg and Shiffrin's (Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 322-336, 2005) "one-shot" context storage hypothesis that assumes that a fixed amount of context is stored in the first 1 to 2 s of the presentation of the study item. The effects of context are independent of item-based directed forgetting because context is encoded prior to the R or F cue, and the differential processing of target information that gives rise to the directed forgetting effect occurs after the cue.

Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including protein markers, pathogens and cellular debris

DOEpatents

Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM

2009-06-02

An assay element is described including recognition ligands bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

PubMed

Ren, Weitong; Ji, Dongqing; Xu, Xiulian

2018-01-01

The HIV-1 nucleocapsid 7 (NCp7) plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3) recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

PNA containing isocytidine nucleobase: synthesis and recognition of double helical RNA

PubMed Central

Zengeya, Thomas; Li, Ming; Rozners, Eriks

2011-01-01

Peptide nucleic acid (PNA1) containing a 5-methylisocytidine (iC) nucleobase has been synthesized. Triple helix formation between PNA1 and RNA hairpins having variable base pairs interacting with iC was studied using isothermal titration calorimetry. The iC nucleobase recognized the proposed target, C-G inversion in polypurine tract of RNA, with slightly higher affinity than the natural nucleobases, though the sequence selectivity of recognition was low. Compared to non-modified PNA, PNA1 had lower affinity for its RNA target. PMID:21333533

An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition.

PubMed

Niu, Li; Li, Wen; Xu, Dong; Cai, Jianfei

2018-02-01

In this paper, we propose a new exemplar-based multi-view domain generalization (EMVDG) framework for visual recognition by learning robust classifier that are able to generalize well to arbitrary target domain based on the training samples with multiple types of features (i.e., multi-view features). In this framework, we aim to address two issues simultaneously. First, the distribution of training samples (i.e., the source domain) is often considerably different from that of testing samples (i.e., the target domain), so the performance of the classifiers learnt on the source domain may drop significantly on the target domain. Moreover, the testing data are often unseen during the training procedure. Second, when the training data are associated with multi-view features, the recognition performance can be further improved by exploiting the relation among multiple types of features. To address the first issue, considering that it has been shown that fusing multiple SVM classifiers can enhance the domain generalization ability, we build our EMVDG framework upon exemplar SVMs (ESVMs), in which a set of ESVM classifiers are learnt with each one trained based on one positive training sample and all the negative training samples. When the source domain contains multiple latent domains, the learnt ESVM classifiers are expected to be grouped into multiple clusters. To address the second issue, we propose two approaches under the EMVDG framework based on the consensus principle and the complementary principle, respectively. Specifically, we propose an EMVDG_CO method by adding a co-regularizer to enforce the cluster structures of ESVM classifiers on different views to be consistent based on the consensus principle. Inspired by multiple kernel learning, we also propose another EMVDG_MK method by fusing the ESVM classifiers from different views based on the complementary principle. In addition, we further extend our EMVDG framework to exemplar-based multi-view domain adaptation (EMVDA) framework when the unlabeled target domain data are available during the training procedure. The effectiveness of our EMVDG and EMVDA frameworks for visual recognition is clearly demonstrated by comprehensive experiments on three benchmark data sets.

Computer-Assisted Face Processing Instruction Improves Emotion Recognition, Mentalizing, and Social Skills in Students with ASD.

PubMed

Rice, Linda Marie; Wall, Carla Anne; Fogel, Adam; Shic, Frederick

2015-07-01

This study examined the extent to which a computer-based social skills intervention called FaceSay was associated with improvements in affect recognition, mentalizing, and social skills of school-aged children with Autism Spectrum Disorder (ASD). FaceSay offers students simulated practice with eye gaze, joint attention, and facial recognition skills. This randomized control trial included school-aged children meeting educational criteria for autism (N = 31). Results demonstrated that participants who received the intervention improved their affect recognition and mentalizing skills, as well as their social skills. These findings suggest that, by targeting face-processing skills, computer-based interventions may produce changes in broader cognitive and social-skills domains in a cost- and time-efficient manner.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Effects of pre-experimental knowledge on recognition memory.

PubMed

Bird, Chris M; Davies, Rachel A; Ward, Jamie; Burgess, Neil

2011-01-01

The influence of pre-experimental autobiographical knowledge on recognition memory was investigated using as memoranda faces that were either personally known or unknown to the participant. Under a dual process theory, such knowledge boosted both recollection- and familiarity-based recognition judgements. Under an unequal variance signal detection model, pre-experimental knowledge increased both the variance and the separation of the target and foil memory strength distributions, boosting hits and correct rejections. Thus, pre-experimental knowledge has profound effects on the multiple, interacting processes that subserve recognition memory, and likely in the neural systems that underpin them.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

TALE-PvuII fusion proteins--novel tools for gene targeting.

PubMed

Yanik, Mert; Alzubi, Jamal; Lahaye, Thomas; Cathomen, Toni; Pingoud, Alfred; Wende, Wolfgang

2013-01-01

Zinc finger nucleases (ZFNs) consist of zinc fingers as DNA-binding module and the non-specific DNA-cleavage domain of the restriction endonuclease FokI as DNA-cleavage module. This architecture is also used by TALE nucleases (TALENs), in which the DNA-binding modules of the ZFNs have been replaced by DNA-binding domains based on transcription activator like effector (TALE) proteins. Both TALENs and ZFNs are programmable nucleases which rely on the dimerization of FokI to induce double-strand DNA cleavage at the target site after recognition of the target DNA by the respective DNA-binding module. TALENs seem to have an advantage over ZFNs, as the assembly of TALE proteins is easier than that of ZFNs. Here, we present evidence that variant TALENs can be produced by replacing the catalytic domain of FokI with the restriction endonuclease PvuII. These fusion proteins recognize only the composite recognition site consisting of the target site of the TALE protein and the PvuII recognition sequence (addressed site), but not isolated TALE or PvuII recognition sites (unaddressed sites), even at high excess of protein over DNA and long incubation times. In vitro, their preference for an addressed over an unaddressed site is > 34,000-fold. Moreover, TALE-PvuII fusion proteins are active in cellula with minimal cytotoxicity.

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

NASA Astrophysics Data System (ADS)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

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

PubMed

Lin, C H; Patel, D J

1997-11-01

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

Vertex Space Analysis for Model-Based Target Recognition.

DTIC Science & Technology

1996-08-01

performed in our unique invariant representation, Vertex Space, that reduces both the dimensionality and size of the required search space. Vertex Space ... mapping results in a reduced representation that serves as a characteristic target signature which is invariant to four of the six viewing geometry

Sleep and eyewitness memory: Fewer false identifications after sleep when the target is absent from the lineup.

PubMed

Stepan, Michelle E; Dehnke, Taylor M; Fenn, Kimberly M

2017-01-01

Inaccurate eyewitness identifications are the leading cause of known false convictions in the United States. Moreover, improving eyewitness memory is difficult and often unsuccessful. Sleep consistently strengthens and protects memory from interference, particularly when a recall test is used. However, the effect of sleep on recognition memory is more equivocal. Eyewitness identification tests are often recognition based, thus leaving open the question of how sleep affects recognition performance in an eyewitness context. In the current study, we investigated the effect of sleep on eyewitness memory. Participants watched a video of a mock-crime and attempted to identify the perpetrator from a simultaneous lineup after a 12-hour retention interval that either spanned a waking day or night of sleep. In Experiment 1, we used a target-present lineup and, in Experiment 2, we used a target-absent lineup in order to investigate correct and false identifications, respectively. Sleep reduced false identifications in the target-absent lineup (Experiment 2) but had no effect on correct identifications in the target-present lineup (Experiment 1). These results are discussed with respect to memory strength and decision making strategies.

Sleep and eyewitness memory: Fewer false identifications after sleep when the target is absent from the lineup

PubMed Central

Dehnke, Taylor M.; Fenn, Kimberly M.

2017-01-01

Inaccurate eyewitness identifications are the leading cause of known false convictions in the United States. Moreover, improving eyewitness memory is difficult and often unsuccessful. Sleep consistently strengthens and protects memory from interference, particularly when a recall test is used. However, the effect of sleep on recognition memory is more equivocal. Eyewitness identification tests are often recognition based, thus leaving open the question of how sleep affects recognition performance in an eyewitness context. In the current study, we investigated the effect of sleep on eyewitness memory. Participants watched a video of a mock-crime and attempted to identify the perpetrator from a simultaneous lineup after a 12-hour retention interval that either spanned a waking day or night of sleep. In Experiment 1, we used a target-present lineup and, in Experiment 2, we used a target-absent lineup in order to investigate correct and false identifications, respectively. Sleep reduced false identifications in the target-absent lineup (Experiment 2) but had no effect on correct identifications in the target-present lineup (Experiment 1). These results are discussed with respect to memory strength and decision making strategies. PMID:28877169

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

PubMed Central

Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

2014-01-01

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

Automatic recognition of ship types from infrared images using superstructure moment invariants

NASA Astrophysics Data System (ADS)

Li, Heng; Wang, Xinyu

2007-11-01

Automatic object recognition is an active area of interest for military and commercial applications. In this paper, a system addressing autonomous recognition of ship types in infrared images is proposed. Firstly, an approach of segmentation based on detection of salient features of the target with subsequent shadow removing is proposed, as is the base of the subsequent object recognition. Considering the differences between the shapes of various ships mainly lie in their superstructures, we then use superstructure moment functions invariant to translation, rotation and scale differences in input patterns and develop a robust algorithm of obtaining ship superstructure. Subsequently a back-propagation neural network is used as a classifier in the recognition stage and projection images of simulated three-dimensional ship models are used as the training sets. Our recognition model was implemented and experimentally validated using both simulated three-dimensional ship model images and real images derived from video of an AN/AAS-44V Forward Looking Infrared(FLIR) sensor.

Triggered optical biosensor

DOEpatents

Song, Xuedong; Swanson, Basil I.

2001-10-02

An optical biosensor is provided for the detection of a multivalent target biomolecule, the biosensor including a substrate having a bilayer membrane thereon, a recognition molecule situated at the surface, the recognition molecule capable of binding with the multivalent target biomolecule, the recognition molecule further characterized as including a fluorescence label thereon and as being movable at the surface and a device for measuring a fluorescence change in response to binding between the recognition molecule and the multivalent target biomolecule.

Evolution of I-SceI Homing Endonucleases with Increased DNA Recognition Site Specificity

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

Joshi, Rakesh; Ho, Kwok Ki; Tenney, Kristen

2013-09-18

Elucidating how homing endonucleases undergo changes in recognition site specificity will facilitate efforts to engineer proteins for gene therapy applications. I-SceI is a monomeric homing endonuclease that recognizes and cleaves within an 18-bp target. It tolerates limited degeneracy in its target sequence, including substitution of a C:G{sub +4} base pair for the wild-type A:T{sub +4} base pair. Libraries encoding randomized amino acids at I-SceI residue positions that contact or are proximal to A:T{sub +4} were used in conjunction with a bacterial one-hybrid system to select I-SceI derivatives that bind to recognition sites containing either the A:T{sub +4} or the C:G{submore » +4} base pairs. As expected, isolates encoding wild-type residues at the randomized positions were selected using either target sequence. All I-SceI proteins isolated using the C:G{sub +4} recognition site included small side-chain substitutions at G100 and either contained (K86R/G100T, K86R/G100S and K86R/G100C) or lacked (G100A, G100T) a K86R substitution. Interestingly, the binding affinities of the selected variants for the wild-type A:T{sub +4} target are 4- to 11-fold lower than that of wild-type I-SceI, whereas those for the C:G{sub +4} target are similar. The increased specificity of the mutant proteins is also evident in binding experiments in vivo. These differences in binding affinities account for the observed -36-fold difference in target preference between the K86R/G100T and wild-type proteins in DNA cleavage assays. An X-ray crystal structure of the K86R/G100T mutant protein bound to a DNA duplex containing the C:G{sub +4} substitution suggests how sequence specificity of a homing enzyme can increase. This biochemical and structural analysis defines one pathway by which site specificity is augmented for a homing endonuclease.« less

Robust and Effective Component-based Banknote Recognition for the Blind

PubMed Central

Hasanuzzaman, Faiz M.; Yang, Xiaodong; Tian, YingLi

2012-01-01

We develop a novel camera-based computer vision technology to automatically recognize banknotes for assisting visually impaired people. Our banknote recognition system is robust and effective with the following features: 1) high accuracy: high true recognition rate and low false recognition rate, 2) robustness: handles a variety of currency designs and bills in various conditions, 3) high efficiency: recognizes banknotes quickly, and 4) ease of use: helps blind users to aim the target for image capture. To make the system robust to a variety of conditions including occlusion, rotation, scaling, cluttered background, illumination change, viewpoint variation, and worn or wrinkled bills, we propose a component-based framework by using Speeded Up Robust Features (SURF). Furthermore, we employ the spatial relationship of matched SURF features to detect if there is a bill in the camera view. This process largely alleviates false recognition and can guide the user to correctly aim at the bill to be recognized. The robustness and generalizability of the proposed system is evaluated on a dataset including both positive images (with U.S. banknotes) and negative images (no U.S. banknotes) collected under a variety of conditions. The proposed algorithm, achieves 100% true recognition rate and 0% false recognition rate. Our banknote recognition system is also tested by blind users. PMID:22661884

Redox polymer and probe DNA tethered to gold electrodes for enzyme-amplified amperometric detection of DNA hybridization.

PubMed

Kavanagh, Paul; Leech, Dónal

2006-04-15

The detection of nucleic acids based upon recognition surfaces formed by co-immobilization of a redox polymer mediator and DNA probe sequences on gold electrodes is described. The recognition surface consists of a redox polymer, [Os(2,2'-bipyridine)2(polyvinylimidazole)(10)Cl](+/2+), and a model single DNA strand cross-linked and tethered to a gold electrode via an anchoring self-assembled monolayer (SAM) of cysteamine. Hybridization between the immobilized probe DNA of the recognition surface and a biotin-conjugated target DNA sequence (designed from the ssrA gene of Listeria monocytogenes), followed by addition of an enzyme (glucose oxidase)-avidin conjugate, results in electrical contact between the enzyme and the mediating redox polymer. In the presence of glucose, the current generated due to the catalytic oxidation of glucose to gluconolactone is measured, and a response is obtained that is binding-dependent. The tethering of the probe DNA and redox polymer to the SAM improves the stability of the surface to assay conditions of rigorous washing and high salt concentration (1 M). These conditions eliminate nonspecific interaction of both the target DNA and the enzyme-avidin conjugate with the recognition surfaces. The sensor response increases linearly with increasing concentration of target DNA in the range of 1 x 10(-9) to 2 x 10(-6) M. The detection limit is approximately 1.4 fmol, (corresponding to 0.2 nM of target DNA). Regeneration of the recognition surface is possible by treatment with 0.25 M NaOH solution. After rehybridization of the regenerated surface with the target DNA sequence, >95% of the current is recovered, indicating that the redox polymer and probe DNA are strongly bound to the surface. These results demonstrate the utility of the proposed approach.

A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database.

PubMed

Huang, Zhiwu; Shan, Shiguang; Wang, Ruiping; Zhang, Haihong; Lao, Shihong; Kuerban, Alifu; Chen, Xilin

2015-12-01

Face recognition with still face images has been widely studied, while the research on video-based face recognition is inadequate relatively, especially in terms of benchmark datasets and comparisons. Real-world video-based face recognition applications require techniques for three distinct scenarios: 1) Videoto-Still (V2S); 2) Still-to-Video (S2V); and 3) Video-to-Video (V2V), respectively, taking video or still image as query or target. To the best of our knowledge, few datasets and evaluation protocols have benchmarked for all the three scenarios. In order to facilitate the study of this specific topic, this paper contributes a benchmarking and comparative study based on a newly collected still/video face database, named COX(1) Face DB. Specifically, we make three contributions. First, we collect and release a largescale still/video face database to simulate video surveillance with three different video-based face recognition scenarios (i.e., V2S, S2V, and V2V). Second, for benchmarking the three scenarios designed on our database, we review and experimentally compare a number of existing set-based methods. Third, we further propose a novel Point-to-Set Correlation Learning (PSCL) method, and experimentally show that it can be used as a promising baseline method for V2S/S2V face recognition on COX Face DB. Extensive experimental results clearly demonstrate that video-based face recognition needs more efforts, and our COX Face DB is a good benchmark database for evaluation.

A study of payload specialist station monitor size constraints. [space shuttle orbiters

NASA Technical Reports Server (NTRS)

Kirkpatrick, M., III; Shields, N. L., Jr.; Malone, T. B.

1975-01-01

Constraints on the CRT display size for the shuttle orbiter cabin are studied. The viewing requirements placed on these monitors were assumed to involve display of imaged scenes providing visual feedback during payload operations and display of alphanumeric characters. Data on target recognition/resolution, target recognition, and range rate detection by human observers were utilized to determine viewing requirements for imaged scenes. Field-of-view and acuity requirements for a variety of payload operations were obtained along with the necessary detection capability in terms of range-to-target size ratios. The monitor size necessary to meet the acuity requirements was established. An empirical test was conducted to determine required recognition sizes for displayed alphanumeric characters. The results of the test were used to determine the number of characters which could be simultaneously displayed based on the recognition size requirements using the proposed monitor size. A CRT display of 20 x 20 cm is recommended. A portion of the display area is used for displaying imaged scenes and the remaining display area is used for alphanumeric characters pertaining to the displayed scene. The entire display is used for the character alone mode.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Doppler-Only Synthetic Aperture Radar

DTIC Science & Technology

2006-12-01

5 B. TARGET RECOGNITION TECHNIQUES .................................................6 1. Cooperative Targets...6 3. Techniques ............................................................................................6 C. TARGET RECOGNITION...3. Implementation of High Range Resolution Techniques .................12 F. TWO-DIMENSIONAL IMAGING

Simultaneous fluorescence light-up and selective multicolor nucleobase recognition based on sequence-dependent strong binding of berberine to DNA abasic site.

PubMed

Wu, Fei; Shao, Yong; Ma, Kun; Cui, Qinghua; Liu, Guiying; Xu, Shujuan

2012-04-28

Label-free DNA nucleobase recognition by fluorescent small molecules has received much attention due to its simplicity in mutation identification and drug screening. However, sequence-dependent fluorescence light-up nucleobase recognition and multicolor emission with individual emission energy for individual nucleobases have been seldom realized. Herein, an abasic site (AP site) in a DNA duplex was employed as a binding field for berberine, one of isoquinoline alkaloids. Unlike weak binding of berberine to the fully matched DNAs without the AP site, strong binding of berberine to the AP site occurs and the berberine's fluorescence light-up behaviors are highly dependent on the target nucleobases opposite the AP site in which the targets thymine and cytosine produce dual emission bands, while the targets guanine and adenine only give a single emission band. Furthermore, more intense emissions are observed for the target pyrimidines than purines. The flanking bases of the AP site also produce some modifications of the berberine's emission behavior. The binding selectivity of berberine at the AP site is also confirmed by measurements of fluorescence resonance energy transfer, excited-state lifetime, DNA melting and fluorescence quenching by ferrocyanide and sodium chloride. It is expected that the target pyrimidines cause berberine to be stacked well within DNA base pairs near the AP site, which results in a strong resonance coupling of the electronic transitions to the particular vibration mode to produce the dual emissions. The fluorescent signal-on and emission energy-modulated sensing for nucleobases based on this fluorophore is substantially advantageous over the previously used fluorophores. We expect that this approach will be developed as a practical device for differentiating pyrimidines from purines by positioning an AP site toward a target that is available for readout by this alkaloid probe. This journal is © The Royal Society of Chemistry 2012

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

Target Acquisition for Projectile Vision-Based Navigation

DTIC Science & Technology

2014-03-01

Future Work 20 8. References 21 Appendix A. Simulation Results 23 Appendix B. Derivation of Ground Resolution for a Diffraction-Limited Pinhole Camera...results for visual acquisition (left) and target recognition (right). ..........19 Figure B-1. Differential object and image areas for pinhole camera...projectile and target (measured in terms of the angle ) will depend on target heading. In particular, because we have aligned the x axis along the

Shape recognition of microbial cells by colloidal cell imprints

NASA Astrophysics Data System (ADS)

Borovička, Josef; Stoyanov, Simeon D.; Paunov, Vesselin N.

2013-08-01

We have engineered a class of colloids which can recognize the shape and size of targeted microbial cells and selectively bind to their surfaces. These imprinted colloid particles, which we called ``colloid antibodies'', were fabricated by partial fragmentation of silica shells obtained by templating the targeted microbial cells. We successfully demonstrated the shape and size recognition between such colloidal imprints and matching microbial cells. High percentage of binding events of colloidal imprints with the size matching target particles was achieved. We demonstrated selective binding of colloidal imprints to target microbial cells in a binary mixture of cells of different shapes and sizes, which also resulted in high binding selectivity. We explored the role of the electrostatic interactions between the target cells and their colloid imprints by pre-coating both of them with polyelectrolytes. Selective binding occurred predominantly in the case of opposite surface charges of the colloid cell imprint and the targeted cells. The mechanism of the recognition is based on the amplification of the surface adhesion in the case of shape and size match due to the increased contact area between the target cell and the colloidal imprint. We also tested the selective binding for colloid imprints of particles of fixed shape and varying sizes. The concept of cell recognition by colloid imprints could be used for development of colloid antibodies for shape-selective binding of microbes. Such colloid antibodies could be additionally functionalized with surface groups to enhance their binding efficiency to cells of specific shape and deliver a drug payload directly to their surface or allow them to be manipulated using external fields. They could benefit the pharmaceutical industry in developing selective antimicrobial therapies and formulations.

Evaluating structural pattern recognition for handwritten math via primitive label graphs

NASA Astrophysics Data System (ADS)

Zanibbi, Richard; Mouchère, Harold; Viard-Gaudin, Christian

2013-01-01

Currently, structural pattern recognizer evaluations compare graphs of detected structure to target structures (i.e. ground truth) using recognition rates, recall and precision for object segmentation, classification and relationships. In document recognition, these target objects (e.g. symbols) are frequently comprised of multiple primitives (e.g. connected components, or strokes for online handwritten data), but current metrics do not characterize errors at the primitive level, from which object-level structure is obtained. Primitive label graphs are directed graphs defined over primitives and primitive pairs. We define new metrics obtained by Hamming distances over label graphs, which allow classification, segmentation and parsing errors to be characterized separately, or using a single measure. Recall and precision for detected objects may also be computed directly from label graphs. We illustrate the new metrics by comparing a new primitive-level evaluation to the symbol-level evaluation performed for the CROHME 2012 handwritten math recognition competition. A Python-based set of utilities for evaluating, visualizing and translating label graphs is publicly available.

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

TALE-PvuII Fusion Proteins – Novel Tools for Gene Targeting

PubMed Central

Yanik, Mert; Alzubi, Jamal; Lahaye, Thomas; Cathomen, Toni; Pingoud, Alfred; Wende, Wolfgang

2013-01-01

Zinc finger nucleases (ZFNs) consist of zinc fingers as DNA-binding module and the non-specific DNA-cleavage domain of the restriction endonuclease FokI as DNA-cleavage module. This architecture is also used by TALE nucleases (TALENs), in which the DNA-binding modules of the ZFNs have been replaced by DNA-binding domains based on transcription activator like effector (TALE) proteins. Both TALENs and ZFNs are programmable nucleases which rely on the dimerization of FokI to induce double-strand DNA cleavage at the target site after recognition of the target DNA by the respective DNA-binding module. TALENs seem to have an advantage over ZFNs, as the assembly of TALE proteins is easier than that of ZFNs. Here, we present evidence that variant TALENs can be produced by replacing the catalytic domain of FokI with the restriction endonuclease PvuII. These fusion proteins recognize only the composite recognition site consisting of the target site of the TALE protein and the PvuII recognition sequence (addressed site), but not isolated TALE or PvuII recognition sites (unaddressed sites), even at high excess of protein over DNA and long incubation times. In vitro, their preference for an addressed over an unaddressed site is > 34,000-fold. Moreover, TALE-PvuII fusion proteins are active in cellula with minimal cytotoxicity. PMID:24349308

A comparison of the real-time controllability of pattern recognition to conventional myoelectric control for discrete and simultaneous movements

PubMed Central

2014-01-01

Myoelectric control has been used for decades to control powered upper limb prostheses. Conventional, amplitude-based control has been employed to control a single prosthesis degree of freedom (DOF) such as closing and opening of the hand. Within the last decade, new and advanced arm and hand prostheses have been constructed that are capable of actuating numerous DOFs. Pattern recognition control has been proposed to control a greater number of DOFs than conventional control, but has traditionally been limited to sequentially controlling DOFs one at a time. However, able-bodied individuals use multiple DOFs simultaneously, and it may be beneficial to provide amputees the ability to perform simultaneous movements. In this study, four amputees who had undergone targeted motor reinnervation (TMR) surgery with previous training using myoelectric prostheses were configured to use three control strategies: 1) conventional amplitude-based myoelectric control, 2) sequential (one-DOF) pattern recognition control, 3) simultaneous pattern recognition control. Simultaneous pattern recognition was enabled by having amputees train each simultaneous movement as a separate motion class. For tasks that required control over just one DOF, sequential pattern recognition based control performed the best with the lowest average completion times, completion rates and length error. For tasks that required control over 2 DOFs, the simultaneous pattern recognition controller performed the best with the lowest average completion times, completion rates and length error compared to the other control strategies. In the two strategies in which users could employ simultaneous movements (conventional and simultaneous pattern recognition), amputees chose to use simultaneous movements 78% of the time with simultaneous pattern recognition and 64% of the time with conventional control for tasks that required two DOF motions to reach the target. These results suggest that when amputees are given the ability to control multiple DOFs simultaneously, they choose to perform tasks that utilize multiple DOFs with simultaneous movements. Additionally, they were able to perform these tasks with higher performance (faster speed, lower length error and higher completion rates) without losing substantial performance in 1 DOF tasks. PMID:24410948

Research on target tracking in coal mine based on optical flow method

NASA Astrophysics Data System (ADS)

Xue, Hongye; Xiao, Qingwei

2015-03-01

To recognize, track and count the bolting machine in coal mine video images, a real-time target tracking method based on the Lucas-Kanade sparse optical flow is proposed in this paper. In the method, we judge whether the moving target deviate from its trajectory, predicate and correct the position of the moving target. The method solves the problem of failure to track the target or lose the target because of the weak light, uneven illumination and blocking. Using the VC++ platform and Opencv lib we complete the recognition and tracking. The validity of the method is verified by the result of the experiment.

A universal entropy-driven mechanism for thioredoxin–target recognition

PubMed Central

Palde, Prakash B.; Carroll, Kate S.

2015-01-01

Cysteine residues in cytosolic proteins are maintained in their reduced state, but can undergo oxidation owing to posttranslational modification during redox signaling or under conditions of oxidative stress. In large part, the reduction of oxidized protein cysteines is mediated by a small 12-kDa thiol oxidoreductase, thioredoxin (Trx). Trx provides reducing equivalents for central metabolic enzymes and is implicated in redox regulation of a wide number of target proteins, including transcription factors. Despite its importance in cellular redox homeostasis, the precise mechanism by which Trx recognizes target proteins, especially in the absence of any apparent signature binding sequence or motif, remains unknown. Knowledge of the forces associated with the molecular recognition that governs Trx–protein interactions is fundamental to our understanding of target specificity. To gain insight into Trx–target recognition, we have thermodynamically characterized the noncovalent interactions between Trx and target proteins before S-S reduction using isothermal titration calorimetry (ITC). Our findings indicate that Trx recognizes the oxidized form of its target proteins with exquisite selectivity, compared with their reduced counterparts. Furthermore, we show that recognition is dependent on the conformational restriction inherent to oxidized targets. Significantly, the thermodynamic signatures for multiple Trx targets reveal favorable entropic contributions as the major recognition force dictating these protein–protein interactions. Taken together, our data afford significant new insight into the molecular forces responsible for Trx–target recognition and should aid the design of new strategies for thiol oxidoreductase inhibition. PMID:26080424

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.

Conditions for positive and negative recencies in running memory-span recognition.

PubMed

Ruiz, R Marcos; Elosúa, M Rosa

2013-10-01

A positive recency effect in a running-span recognition procedure was obtained in Experiment 1 for hits and for intratrial false alarms. In running recall procedures, recency does not fit well with an active updating hypothesis. In Experiment 2, in which the beginning of the target set was marked with a cue upon presentation, the recency effects disappeared. In Experiments 3 and 4 participants were forced to maintain 2 items in memory until the last one was presented for recognition. These three items were the target set. When the last item presentation was uncertain-because of the variable length list-an unexpected negative recency effect appeared. An explanation for this change from positive to negative recency is offered based on the sharing of attentional resources put forward by others for similar procedures. © 2013.

Recognition of Emotions in Mexican Spanish Speech: An Approach Based on Acoustic Modelling of Emotion-Specific Vowels

PubMed Central

Caballero-Morales, Santiago-Omar

2013-01-01

An approach for the recognition of emotions in speech is presented. The target language is Mexican Spanish, and for this purpose a speech database was created. The approach consists in the phoneme acoustic modelling of emotion-specific vowels. For this, a standard phoneme-based Automatic Speech Recognition (ASR) system was built with Hidden Markov Models (HMMs), where different phoneme HMMs were built for the consonants and emotion-specific vowels associated with four emotional states (anger, happiness, neutral, sadness). Then, estimation of the emotional state from a spoken sentence is performed by counting the number of emotion-specific vowels found in the ASR's output for the sentence. With this approach, accuracy of 87–100% was achieved for the recognition of emotional state of Mexican Spanish speech. PMID:23935410

Quantitative Expression and Immunogenicity of MAGE-3 and -6 in Upper Aerodigestive Tract Cancer

PubMed Central

Andrade Filho, Pedro A.; López-Albaitero, Andrés; Xi, Liqiang; Gooding, William; Godfrey, Tony; Ferris, Robert L.

2009-01-01

The MAGE antigens are frequently expressed cancer vaccine targets. However, quantitative analysis of MAGE expression in upper aero-digestive tract (UADT) tumor cells and its association with T cell recognition has not been performed, hindering the selection of appropriate candidates for MAGE specific immunotherapy. Using quantitative RT-PCR (QRT-PCR), we evaluated the expression of MAGE-3/6 in 65 UADT cancers, 48 normal samples from tumor matched sites and 7 HLA-A*0201+squamous cell carcinoma of the head and neck (SCCHN) cell lines. Expression results were confirmed using western blot. HLA-A*0201:MAGE-3(271–279) specific cytotoxic T lymphocytes (MAGE-CTL) from SCCHN patients and healthy donors showed that MAGE-3/6 expression was highly associated with CTL recognition in vitro. Based on MAGE-3/6 expression we could identify 31 (47%) of the 65 UADT tumors which appeared to express MAGE-3/6 at levels that correlated with efficient CTL recognition. To confirm that the level of MAGE-3 expression was responsible for CTL recognition, two MAGE-3/6 mRNAhigh SCCHN cell lines, PCI-13 and PCI-30, were subjected to MAGE-3/6 specific knockdown. RNAi–transfected cells showed that MAGE expression, and MAGE-CTL recognition, were significantly reduced. Furthermore, treatment of cells expressing low MAGE-3/6 mRNA with a demethylating agent, 5-aza-2'-deoxycytidine (DAC), increased the expression of MAGE-3/6 and CTL recognition. Thus, using QRT-PCR UADT cancers frequently express MAGE-3/6 at levels sufficient for CTL recognition, supporting the use of a QRT-PCR based assay for the selection of candidates likely to respond to MAGE-3/6 immunotherapy. Demethylating agents could increase the number of patients amenable for targeting epigenetically modified tumor antigens in vaccine trials. PMID:19610063

Hetero-enzyme-based two-round signal amplification strategy for trace detection of aflatoxin B1 using an electrochemical aptasensor.

PubMed

Zheng, Wanli; Teng, Jun; Cheng, Lin; Ye, Yingwang; Pan, Daodong; Wu, Jingjing; Xue, Feng; Liu, Guodong; Chen, Wei

2016-06-15

An electrochemical aptasensor for trace detection of aflatoxin B1 (AFB1) was developed by using an aptamer as the recognition unit while adopting the telomerase and EXO III based two-round signal amplification strategy as the signal enhancement units. The telomerase amplification was used to elongate the ssDNA probes on the surface of gold nanoparticles, by which the signal response range of the signal-off model electrochemical aptasensor could be correspondingly enlarged. Then, the EXO III amplification was used to hydrolyze the 3'-end of the dsDNA after the recognition of target AFB1, which caused the release of bounded AFB1 into the sensing system, where it participated in the next recognition-sensing cycle. With this two-round signal amplified electrochemical aptasensor, target AFB1 was successfully measured at trace concentrations with excellent detection limit of 0.6*10(-4)ppt and satisfied specificity due to the excellent affinity of the aptamer against AFB1. Based on this designed two-round signal amplification strategy, both the sensing range and detection limit were greatly improved. This proposed ultrasensitive electrochemical aptasensor method was also validated by comparison with the classic instrumental methods. Importantly, this hetero-enzyme based two-round signal amplified electrochemical aptasensor offers a great promising protocol for ultrasensitive detection of AFB1 and other mycotoxins by replacing the core recognition sequence of the aptamer. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

Geometric shapes inversion method of space targets by ISAR image segmentation

NASA Astrophysics Data System (ADS)

Huo, Chao-ying; Xing, Xiao-yu; Yin, Hong-cheng; Li, Chen-guang; Zeng, Xiang-yun; Xu, Gao-gui

2017-11-01

The geometric shape of target is an effective characteristic in the process of space targets recognition. This paper proposed a method of shape inversion of space target based on components segmentation from ISAR image. The Radon transformation, Hough transformation, K-means clustering, triangulation will be introduced into ISAR image processing. Firstly, we use Radon transformation and edge detection to extract space target's main body spindle and solar panel spindle from ISAR image. Then the targets' main body, solar panel, rectangular and circular antenna are segmented from ISAR image based on image detection theory. Finally, the sizes of every structural component are computed. The effectiveness of this method is verified using typical targets' simulation data.

Ballistic missile precession frequency extraction based on the Viterbi & Kalman algorithm

NASA Astrophysics Data System (ADS)

Wu, Longlong; Xie, Yongjie; Xu, Daping; Ren, Li

2015-12-01

Radar Micro-Doppler signatures are of great potential for target detection, classification and recognition. In the mid-course phase, warheads flying outside the atmosphere are usually accompanied by precession. Precession may induce additional frequency modulations on the returned radar signal, which can be regarded as a unique signature and provide additional information that is complementary to existing target recognition methods. The main purpose of this paper is to establish a more actual precession model of conical ballistic missile warhead and extract the precession parameters by utilizing Viterbi & Kalman algorithm, which improving the precession frequency estimation accuracy evidently , especially in low SNR.

EEG based topography analysis in string recognition task

NASA Astrophysics Data System (ADS)

Ma, Xiaofei; Huang, Xiaolin; Shen, Yuxiaotong; Qin, Zike; Ge, Yun; Chen, Ying; Ning, Xinbao

2017-03-01

Vision perception and recognition is a complex process, during which different parts of brain are involved depending on the specific modality of the vision target, e.g. face, character, or word. In this study, brain activities in string recognition task compared with idle control state are analyzed through topographies based on multiple measurements, i.e. sample entropy, symbolic sample entropy and normalized rhythm power, extracted from simultaneously collected scalp EEG. Our analyses show that, for most subjects, both symbolic sample entropy and normalized gamma power in string recognition task are significantly higher than those in idle state, especially at locations of P4, O2, T6 and C4. It implies that these regions are highly involved in string recognition task. Since symbolic sample entropy measures complexity, from the perspective of new information generation, and normalized rhythm power reveals the power distributions in frequency domain, complementary information about the underlying dynamics can be provided through the two types of indices.

Recognition-induced forgetting is not due to category-based set size.

PubMed

Maxcey, Ashleigh M

2016-01-01

What are the consequences of accessing a visual long-term memory representation? Previous work has shown that accessing a long-term memory representation via retrieval improves memory for the targeted item and hurts memory for related items, a phenomenon called retrieval-induced forgetting. Recently we found a similar forgetting phenomenon with recognition of visual objects. Recognition-induced forgetting occurs when practice recognizing an object during a two-alternative forced-choice task, from a group of objects learned at the same time, leads to worse memory for objects from that group that were not practiced. An alternative explanation of this effect is that category-based set size is inducing forgetting, not recognition practice as claimed by some researchers. This alternative explanation is possible because during recognition practice subjects make old-new judgments in a two-alternative forced-choice task, and are thus exposed to more objects from practiced categories, potentially inducing forgetting due to set-size. Herein I pitted the category-based set size hypothesis against the recognition-induced forgetting hypothesis. To this end, I parametrically manipulated the amount of practice objects received in the recognition-induced forgetting paradigm. If forgetting is due to category-based set size, then the magnitude of forgetting of related objects will increase as the number of practice trials increases. If forgetting is recognition induced, the set size of exemplars from any given category should not be predictive of memory for practiced objects. Consistent with this latter hypothesis, additional practice systematically improved memory for practiced objects, but did not systematically affect forgetting of related objects. These results firmly establish that recognition practice induces forgetting of related memories. Future directions and important real-world applications of using recognition to access our visual memories of previously encountered objects are discussed.

Gross feature recognition of Anatomical Images based on Atlas grid (GAIA): Incorporating the local discrepancy between an atlas and a target image to capture the features of anatomic brain MRI.

PubMed

Qin, Yuan-Yuan; Hsu, Johnny T; Yoshida, Shoko; Faria, Andreia V; Oishi, Kumiko; Unschuld, Paul G; Redgrave, Graham W; Ying, Sarah H; Ross, Christopher A; van Zijl, Peter C M; Hillis, Argye E; Albert, Marilyn S; Lyketsos, Constantine G; Miller, Michael I; Mori, Susumu; Oishi, Kenichi

2013-01-01

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas-image misregistration, is used to capture the anatomical features of target images. As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

Precise small molecule recognition of a toxic CUG RNA repeat expansion

PubMed Central

Rzuczek, Suzanne G; Colgan, Lesley A; Nakai, Yoshio; Cameron, Michael D; Furling, Denis; Yasuda, Ryohei; Disney, Matthew D

2017-01-01

Excluding the ribosome and riboswitches, developing small molecules that selectively target RNA is a longstanding problem in chemical biology. A typical cellular RNA is difficult to target because it has little tertiary, but abundant secondary structure. We designed allele-selective compounds that target such an RNA, the toxic noncoding repeat expansion (r(CUG)exp) that causes myotonic dystrophy type 1 (DM1). We developed several strategies to generate allele-selective small molecules, including non-covalent binding, covalent binding, cleavage and on-site probe synthesis. Covalent binding and cleavage enabled target profiling in cells derived from individuals with DM1, showing precise recognition of r(CUG)exp. In the on-site probe synthesis approach, small molecules bound adjacent sites in r(CUG)exp and reacted to afford picomolar inhibitors via a proximity-based click reaction only in DM1-affected cells. We expanded this approach to image r(CUG)exp in its natural context. PMID:27941760

Precise small-molecule recognition of a toxic CUG RNA repeat expansion.

PubMed

Rzuczek, Suzanne G; Colgan, Lesley A; Nakai, Yoshio; Cameron, Michael D; Furling, Denis; Yasuda, Ryohei; Disney, Matthew D

2017-02-01

Excluding the ribosome and riboswitches, developing small molecules that selectively target RNA is a longstanding problem in chemical biology. A typical cellular RNA is difficult to target because it has little tertiary, but abundant secondary structure. We designed allele-selective compounds that target such an RNA, the toxic noncoding repeat expansion (r(CUG) exp ) that causes myotonic dystrophy type 1 (DM1). We developed several strategies to generate allele-selective small molecules, including non-covalent binding, covalent binding, cleavage and on-site probe synthesis. Covalent binding and cleavage enabled target profiling in cells derived from individuals with DM1, showing precise recognition of r(CUG) exp . In the on-site probe synthesis approach, small molecules bound adjacent sites in r(CUG) exp and reacted to afford picomolar inhibitors via a proximity-based click reaction only in DM1-affected cells. We expanded this approach to image r(CUG) exp in its natural context.

Design of a sensitive aptasensor based on magnetic microbeads-assisted strand displacement amplification and target recycling.

PubMed

Li, Ying; Ji, Xiaoting; Song, Weiling; Guo, Yingshu

2013-04-03

A cross-circular amplification system for sensitive detection of adenosine triphosphate (ATP) in cancer cells was developed based on aptamer-target interaction, magnetic microbeads (MBs)-assisted strand displacement amplification and target recycling. Here we described a new recognition probe possessing two parts, the ATP aptamer and the extension part. The recognition probe was firstly immobilized on the surface of MBs and hybridized with its complementary sequence to form a duplex. When combined with ATP, the probe changed its conformation, revealing the extension part in single-strand form, which further served as a toehold for subsequent target recycling. The released complementary sequence of the probe acted as the catalyst of the MB-assisted strand displacement reaction. Incorporated with target recycling, a large amount of biotin-tagged MB complexes were formed to stimulate the generation of chemiluminescence (CL) signal in the presence of luminol and H2O2 by incorporating with streptavidin-HRP, reaching a detection limit of ATP as low as 6.1×10(-10)M. Moreover, sample assays of ATP in Ramos Burkitt's lymphoma B cells were performed, which confirmed the reliability and practicality of the protocol. Copyright © 2013 Elsevier B.V. All rights reserved.

Deep feature extraction and combination for synthetic aperture radar target classification

NASA Astrophysics Data System (ADS)

Amrani, Moussa; Jiang, Feng

2017-10-01

Feature extraction has always been a difficult problem in the classification performance of synthetic aperture radar automatic target recognition (SAR-ATR). It is very important to select discriminative features to train a classifier, which is a prerequisite. Inspired by the great success of convolutional neural network (CNN), we address the problem of SAR target classification by proposing a feature extraction method, which takes advantage of exploiting the extracted deep features from CNNs on SAR images to introduce more powerful discriminative features and robust representation ability for them. First, the pretrained VGG-S net is fine-tuned on moving and stationary target acquisition and recognition (MSTAR) public release database. Second, after a simple preprocessing is performed, the fine-tuned network is used as a fixed feature extractor to extract deep features from the processed SAR images. Third, the extracted deep features are fused by using a traditional concatenation and a discriminant correlation analysis algorithm. Finally, for target classification, K-nearest neighbors algorithm based on LogDet divergence-based metric learning triplet constraints is adopted as a baseline classifier. Experiments on MSTAR are conducted, and the classification accuracy results demonstrate that the proposed method outperforms the state-of-the-art methods.

Emotionally conditioning the target-speech voice enhances recognition of the target speech under "cocktail-party" listening conditions.

PubMed

Lu, Lingxi; Bao, Xiaohan; Chen, Jing; Qu, Tianshu; Wu, Xihong; Li, Liang

2018-05-01

Under a noisy "cocktail-party" listening condition with multiple people talking, listeners can use various perceptual/cognitive unmasking cues to improve recognition of the target speech against informational speech-on-speech masking. One potential unmasking cue is the emotion expressed in a speech voice, by means of certain acoustical features. However, it was unclear whether emotionally conditioning a target-speech voice that has none of the typical acoustical features of emotions (i.e., an emotionally neutral voice) can be used by listeners for enhancing target-speech recognition under speech-on-speech masking conditions. In this study we examined the recognition of target speech against a two-talker speech masker both before and after the emotionally neutral target voice was paired with a loud female screaming sound that has a marked negative emotional valence. The results showed that recognition of the target speech (especially the first keyword in a target sentence) was significantly improved by emotionally conditioning the target speaker's voice. Moreover, the emotional unmasking effect was independent of the unmasking effect of the perceived spatial separation between the target speech and the masker. Also, (skin conductance) electrodermal responses became stronger after emotional learning when the target speech and masker were perceptually co-located, suggesting an increase of listening efforts when the target speech was informationally masked. These results indicate that emotionally conditioning the target speaker's voice does not change the acoustical parameters of the target-speech stimuli, but the emotionally conditioned vocal features can be used as cues for unmasking target speech.

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

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

The Automatic Recognition of the Abnormal Sky-subtraction Spectra Based on Hadoop

NASA Astrophysics Data System (ADS)

An, An; Pan, Jingchang

2017-10-01

The skylines, superimposing on the target spectrum as a main noise, If the spectrum still contains a large number of high strength skylight residuals after sky-subtraction processing, it will not be conducive to the follow-up analysis of the target spectrum. At the same time, the LAMOST can observe a quantity of spectroscopic data in every night. We need an efficient platform to proceed the recognition of the larger numbers of abnormal sky-subtraction spectra quickly. Hadoop, as a distributed parallel data computing platform, can deal with large amounts of data effectively. In this paper, we conduct the continuum normalization firstly and then a simple and effective method will be presented to automatic recognize the abnormal sky-subtraction spectra based on Hadoop platform. Obtain through the experiment, the Hadoop platform can implement the recognition with more speed and efficiency, and the simple method can recognize the abnormal sky-subtraction spectra and find the abnormal skyline positions of different residual strength effectively, can be applied to the automatic detection of abnormal sky-subtraction of large number of spectra.

Drilling Rig Operation Mode Recognition by an Artificial Neuronet

NASA Astrophysics Data System (ADS)

Abu-Abed, Fares; Borisov, Nikolay

2017-11-01

The article proposes a way to develop a drilling rig operation mode classifier specialized to recognize pre-emergency situations appearable in commercial oil-and-gas well drilling. The classifier is based on the theory of image recognition and artificial neuronet taught on real geological and technological information obtained while drilling. To teach the neuronet, a modified backpropagation algorithm that can teach to reach the global extremum of a target function has been proposed. The target function was a relative recognition error to minimize in the teaching. Two approaches to form the drilling rig pre-emergency situation classifier based on a taught neuronet have been considered. The first one involves forming an output classifier of N different signals, each of which corresponds to a single recognizable situation and, and can be formed on the basis of the analysis of M indications, that is using a uniform indication vocabulary for all recognized situations. The second way implements a universal classifier comprising N specialized ones, each of which can recognize a single pre-emergency situation and having a single output.

State Recognition of High Voltage Isolation Switch Based on Background Difference and Iterative Search

NASA Astrophysics Data System (ADS)

Xu, Jiayuan; Yu, Chengtao; Bo, Bin; Xue, Yu; Xu, Changfu; Chaminda, P. R. Dushantha; Hu, Chengbo; Peng, Kai

2018-03-01

The automatic recognition of the high voltage isolation switch by remote video monitoring is an effective means to ensure the safety of the personnel and the equipment. The existing methods mainly include two ways: improving monitoring accuracy and adopting target detection technology through equipment transformation. Such a method is often applied to specific scenarios, with limited application scope and high cost. To solve this problem, a high voltage isolation switch state recognition method based on background difference and iterative search is proposed in this paper. The initial position of the switch is detected in real time through the background difference method. When the switch starts to open and close, the target tracking algorithm is used to track the motion trajectory of the switch. The opening and closing state of the switch is determined according to the angle variation of the switch tracking point and the center line. The effectiveness of the method is verified by experiments on different switched video frames of switching states. Compared with the traditional methods, this method is more robust and effective.

Constraints in distortion-invariant target recognition system simulation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Target recognition and phase acquisition by using incoherent digital holographic imaging

NASA Astrophysics Data System (ADS)

Lee, Munseob; Lee, Byung-Tak

2017-05-01

In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

NASA Astrophysics Data System (ADS)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high-definition video exploitation.

Bio-recognitive photonics of a DNA-guided organic semiconductor

PubMed Central

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA–DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an ‘inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA–DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition. PMID:26725969

Bio-recognitive photonics of a DNA-guided organic semiconductor.

PubMed

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor

NASA Astrophysics Data System (ADS)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Structural biology of antibody recognition of carbohydrate epitopes and potential uses for targeted cancer immunotherapies.

PubMed

Dingjan, Tamir; Spendlove, Ian; Durrant, Lindy G; Scott, Andrew M; Yuriev, Elizabeth; Ramsland, Paul A

2015-10-01

Monoclonal antibodies represent the most successful class of biopharmaceuticals for the treatment of cancer. Mechanisms of action of therapeutic antibodies are very diverse and reflect their ability to engage in antibody-dependent effector mechanisms, internalize to deliver cytotoxic payloads, and display direct effects on cells by lysis or by modulating the biological pathways of their target antigens. Importantly, one of the universal changes in cancer is glycosylation and carbohydrate-binding antibodies can be produced to selectively recognize tumor cells over normal tissues. A promising group of cell surface antibody targets consists of carbohydrates presented as glycolipids or glycoproteins. In this review, we outline the basic principles of antibody-based targeting of carbohydrate antigens in cancer. We also present a detailed structural view of antibody recognition and the conformational properties of a series of related tissue-blood group (Lewis) carbohydrates that are being pursued as potential targets of cancer immunotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

PubMed

Yang, Lixue; Chen, Kean

2015-11-01

To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

Action Recognition in a Crowded Environment

PubMed Central

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

2017-01-01

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

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames. Experimental results show that the improved automatic threshold processing has special application value for the recognition of dynamic target with low contrast.

Comparison of eye imaging pattern recognition using neural network

NASA Astrophysics Data System (ADS)

Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.

2015-05-01

The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.

TAL effector-DNA specificity.

PubMed

Scholze, Heidi; Boch, Jens

2010-01-01

TAL effectors are important virulence factors of bacterial plant pathogenic Xanthomonas, which infect a wide variety of plants including valuable crops like pepper, rice, and citrus. TAL proteins are translocated via the bacterial type III secretion system into host cells and induce transcription of plant genes by binding to target gene promoters. Members of the TAL effector family differ mainly in their central domain of tandemly arranged repeats of typically 34 amino acids each with hypervariable di-amino acids at positions 12 and 13. We recently showed that target DNA-recognition specificity of TAL effectors is encoded in a modular and clearly predictable mode. The repeats of TAL effectors feature a surprising one repeat-to-one-bp correlation with different repeat types exhibiting a different DNA base pair specificity. Accordingly, we predicted DNA specificities of TAL effectors and generated artificial TAL proteins with novel DNA recognition specificities. We describe here novel artificial TALs and discuss implications for the DNA recognition specificity. The unique TAL-DNA binding domain allows design of proteins with potentially any given DNA recognition specificity enabling many uses for biotechnology.

Adaptive optics to enhance target recognition

NASA Astrophysics Data System (ADS)

McAulay, Alastair D.

2012-06-01

Target recognition can be enhanced by reducing image degradation due to atmospheric turbulence. This is accomplished by an adaptive optic system. We discuss the forms of degradation when a target is viewed through the atmosphere1: scintillation from ground targets on a hot day in visible or infrared light; beam spreading and wavering around in time; atmospheric turbulence caused by motion of the target or by weather. In the case of targets we can use a beacon laser that reflects back from the target into a wavefront detector to measure the effects of turbulence on propagation to and from the target before imaging.1 A deformable mirror then corrects the wavefront shape of the transmitted, reflected or scattered data for enhanced imaging. Further, recognition of targets is enhanced by performing accurate distance measurements to localized parts of the target using lidar. Distance is obtained by sending a short pulse to the target and measuring the time for the pulse to return. There is inadequate time to scan the complete field of view so that the beam must be steered to regions of interest such as extremities of the image during image recognition. Distance is particularly valuable to recognize fine features in range along the target or when segmentation is required to separate a target from background or from other targets. We discuss the issues involved.

Electrochemical impedimetric sensor based on molecularly imprinted polymers/sol-gel chemistry for methidathion organophosphorous insecticide recognition.

PubMed

Bakas, Idriss; Hayat, Akhtar; Piletsky, Sergey; Piletska, Elena; Chehimi, Mohamed M; Noguer, Thierry; Rouillon, Régis

2014-12-01

We report here a novel method to detect methidathion organophosphorous insecticides. The sensing platform was architected by the combination of molecularly imprinted polymers and sol-gel technique on inexpensive, portable and disposable screen printed carbon electrodes. Electrochemical impedimetric detection technique was employed to perform the label free detection of the target analyte on the designed MIP/sol-gel integrated platform. The selection of the target specific monomer by electrochemical impedimetric methods was consistent with the results obtained by the computational modelling method. The prepared electrochemical MIP/sol-gel based sensor exhibited a high recognition capability toward methidathion, as well as a broad linear range and a low detection limit under the optimized conditions. Satisfactory results were also obtained for the methidathion determination in waste water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Perceptual fluency and affect without recognition.

PubMed

Anand, P; Sternthal, B

1991-05-01

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

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

Face shape and face identity processing in behavioral variant fronto-temporal dementia: A specific deficit for familiarity and name recognition of famous faces.

PubMed

De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan

2016-01-01

Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.

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

PubMed

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

2000-04-01

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

A robust recognition and accurate locating method for circular coded diagonal target

NASA Astrophysics Data System (ADS)

Bao, Yunna; Shang, Yang; Sun, Xiaoliang; Zhou, Jiexin

2017-10-01

As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.

Determinants for DNA target structure selectivity of the human LINE-1 retrotransposon endonuclease.

PubMed

Repanas, Kostas; Zingler, Nora; Layer, Liliana E; Schumann, Gerald G; Perrakis, Anastassis; Weichenrieder, Oliver

2007-01-01

The human LINE-1 endonuclease (L1-EN) is the targeting endonuclease encoded by the human LINE-1 (L1) retrotransposon. L1-EN guides the genomic integration of new L1 and Alu elements that presently account for approximately 28% of the human genome. L1-EN bears considerable technological interest, because its target selectivity may ultimately be engineered to allow the site-specific integration of DNA into defined genomic locations. Based on the crystal structure, we generated L1-EN mutants to analyze and manipulate DNA target site recognition. Crystal structures and their dynamic and functional analysis show entire loop grafts to be feasible, resulting in altered specificity, while individual point mutations do not change the nicking pattern of L1-EN. Structural parameters of the DNA target seem more important for recognition than the nucleotide sequence, and nicking profiles on DNA oligonucleotides in vitro are less well defined than the respective integration site consensus in vivo. This suggests that additional factors other than the DNA nicking specificity of L1-EN contribute to the targeted integration of non-LTR retrotransposons.

Oxytocin increases bias, but not accuracy, in face recognition line-ups.

PubMed

Bate, Sarah; Bennetts, Rachel; Parris, Benjamin A; Bindemann, Markus; Udale, Robert; Bussunt, Amanda

2015-07-01

Previous work indicates that intranasal inhalation of oxytocin improves face recognition skills, raising the possibility that it may be used in security settings. However, it is unclear whether oxytocin directly acts upon the core face-processing system itself or indirectly improves face recognition via affective or social salience mechanisms. In a double-blind procedure, 60 participants received either an oxytocin or placebo nasal spray before completing the One-in-Ten task-a standardized test of unfamiliar face recognition containing target-present and target-absent line-ups. Participants in the oxytocin condition outperformed those in the placebo condition on target-present trials, yet were more likely to make false-positive errors on target-absent trials. Signal detection analyses indicated that oxytocin induced a more liberal response bias, rather than increasing accuracy per se. These findings support a social salience account of the effects of oxytocin on face recognition and indicate that oxytocin may impede face recognition in certain scenarios. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Target detection method by airborne and spaceborne images fusion based on past images

NASA Astrophysics Data System (ADS)

Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng

2017-11-01

To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

Creation of a type IIS restriction endonuclease with a long recognition sequence

PubMed Central

Lippow, Shaun M.; Aha, Patti M.; Parker, Matthew H.; Blake, William J.; Baynes, Brian M.; Lipovšek, Daša

2009-01-01

Type IIS restriction endonucleases cleave DNA outside their recognition sequences, and are therefore particularly useful in the assembly of DNA from smaller fragments. A limitation of type IIS restriction endonucleases in assembly of long DNA sequences is the relative abundance of their target sites. To facilitate ligation-based assembly of extremely long pieces of DNA, we have engineered a new type IIS restriction endonuclease that combines the specificity of the homing endonuclease I-SceI with the type IIS cleavage pattern of FokI. We linked a non-cleaving mutant of I-SceI, which conveys to the chimeric enzyme its specificity for an 18-bp DNA sequence, to the catalytic domain of FokI, which cuts DNA at a defined site outside the target site. Whereas previously described chimeric endonucleases do not produce type IIS-like precise DNA overhangs suitable for ligation, our chimeric endonuclease cleaves double-stranded DNA exactly 2 and 6 nt from the target site to generate homogeneous, 5′, four-base overhangs, which can be ligated with 90% fidelity. We anticipate that these enzymes will be particularly useful in manipulation of DNA fragments larger than a thousand bases, which are very likely to contain target sites for all natural type IIS restriction endonucleases. PMID:19304757

Deep learning model-based algorithm for SAR ATR

NASA Astrophysics Data System (ADS)

Friedlander, Robert D.; Levy, Michael; Sudkamp, Elizabeth; Zelnio, Edmund

2018-05-01

Many computer-vision-related problems have successfully applied deep learning to improve the error rates with respect to classifying images. As opposed to optically based images, we have applied deep learning via a Siamese Neural Network (SNN) to classify synthetic aperture radar (SAR) images. This application of Automatic Target Recognition (ATR) utilizes an SNN made up of twin AlexNet-based Convolutional Neural Networks (CNNs). Using the processing power of GPUs, we trained the SNN with combinations of synthetic images on one twin and Moving and Stationary Target Automatic Recognition (MSTAR) measured images on a second twin. We trained the SNN with three target types (T-72, BMP2, and BTR-70) and have used a representative, synthetic model from each target to classify new SAR images. Even with a relatively small quantity of data (with respect to machine learning), we found that the SNN performed comparably to a CNN and had faster convergence. The results of processing showed the T-72s to be the easiest to identify, whereas the network sometimes mixed up the BMP2s and the BTR-70s. In addition we also incorporated two additional targets (M1 and M35) into the validation set. Without as much training (for example, one additional epoch) the SNN did not produce the same results as if all five targets had been trained over all the epochs. Nevertheless, an SNN represents a novel and beneficial approach to SAR ATR.

Imidazopyridine/Pyrrole and hydroxybenzimidazole/pyrrole pairs for DNA minor groove recognition.

PubMed

Renneberg, Dorte; Dervan, Peter B

2003-05-14

The DNA binding properties of fused heterocycles imidazo[4,5-b]pyridine (Ip) and hydroxybenzimidazole (Hz) paired with pyrrole (Py) in eight-ring hairpin polyamides are reported. The recognition profile of Ip/Py and Hz/Py pairs were compared to the five-membered ring pairs Im/Py and Hp/Py on a DNA restriction fragment at four 6-base pair recognition sites which vary at a single position 5'-TGTNTA-3', where N = G, C, T, A. The Ip/Py pair distinguishes G.C from C.G, T.A, and A.T, and the Hz/Py pair distinguishes T.A from A.T, G.C, and C.G, affording a new set of heterocycle pairs to target the four Watson-Crick base pairs in the minor groove of DNA.

Speech recognition in one- and two-talker maskers in school-age children and adults: Development of perceptual masking and glimpsing

PubMed Central

Buss, Emily; Leibold, Lori J.; Porter, Heather L.; Grose, John H.

2017-01-01

Children perform more poorly than adults on a wide range of masked speech perception paradigms, but this effect is particularly pronounced when the masker itself is also composed of speech. The present study evaluated two factors that might contribute to this effect: the ability to perceptually isolate the target from masker speech, and the ability to recognize target speech based on sparse cues (glimpsing). Speech reception thresholds (SRTs) were estimated for closed-set, disyllabic word recognition in children (5–16 years) and adults in a one- or two-talker masker. Speech maskers were 60 dB sound pressure level (SPL), and they were either presented alone or in combination with a 50-dB-SPL speech-shaped noise masker. There was an age effect overall, but performance was adult-like at a younger age for the one-talker than the two-talker masker. Noise tended to elevate SRTs, particularly for older children and adults, and when summed with the one-talker masker. Removing time-frequency epochs associated with a poor target-to-masker ratio markedly improved SRTs, with larger effects for younger listeners; the age effect was not eliminated, however. Results were interpreted as indicating that development of speech-in-speech recognition is likely impacted by development of both perceptual masking and the ability recognize speech based on sparse cues. PMID:28464682

Primitive Auditory Memory Is Correlated with Spatial Unmasking That Is Based on Direct-Reflection Integration

PubMed Central

Li, Huahui; Kong, Lingzhi; Wu, Xihong; Li, Liang

2013-01-01

In reverberant rooms with multiple-people talking, spatial separation between speech sources improves recognition of attended speech, even though both the head-shadowing and interaural-interaction unmasking cues are limited by numerous reflections. It is the perceptual integration between the direct wave and its reflections that bridges the direct-reflection temporal gaps and results in the spatial unmasking under reverberant conditions. This study further investigated (1) the temporal dynamic of the direct-reflection-integration-based spatial unmasking as a function of the reflection delay, and (2) whether this temporal dynamic is correlated with the listeners’ auditory ability to temporally retain raw acoustic signals (i.e., the fast decaying primitive auditory memory, PAM). The results showed that recognition of the target speech against the speech-masker background is a descending exponential function of the delay of the simulated target reflection. In addition, the temporal extent of PAM is frequency dependent and markedly longer than that for perceptual fusion. More importantly, the temporal dynamic of the speech-recognition function is significantly correlated with the temporal extent of the PAM of low-frequency raw signals. Thus, we propose that a chain process, which links the earlier-stage PAM with the later-stage correlation computation, perceptual integration, and attention facilitation, plays a role in spatially unmasking target speech under reverberant conditions. PMID:23658664

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition

NASA Astrophysics Data System (ADS)

Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang

2018-03-01

Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

NASA Astrophysics Data System (ADS)

Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2014-03-01

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

Lesion search and recognition by thymine DNA glycosylase revealed by single molecule imaging

PubMed Central

Buechner, Claudia N.; Maiti, Atanu; Drohat, Alexander C.; Tessmer, Ingrid

2015-01-01

The ability of DNA glycosylases to rapidly and efficiently detect lesions among a vast excess of nondamaged DNA bases is vitally important in base excision repair (BER). Here, we use single molecule imaging by atomic force microscopy (AFM) supported by a 2-aminopurine fluorescence base flipping assay to study damage search by human thymine DNA glycosylase (hTDG), which initiates BER of mutagenic and cytotoxic G:T and G:U mispairs in DNA. Our data reveal an equilibrium between two conformational states of hTDG–DNA complexes, assigned as search complex (SC) and interrogation complex (IC), both at target lesions and undamaged DNA sites. Notably, for both hTDG and a second glycosylase, hOGG1, which recognizes structurally different 8-oxoguanine lesions, the conformation of the DNA in the SC mirrors innate structural properties of their respective target sites. In the IC, the DNA is sharply bent, as seen in crystal structures of hTDG lesion recognition complexes, which likely supports the base flipping required for lesion identification. Our results support a potentially general concept of sculpting of glycosylases to their targets, allowing them to exploit the energetic cost of DNA bending for initial lesion sensing, coupled with continuous (extrahelical) base interrogation during lesion search by DNA glycosylases. PMID:25712093

Quantitative analysis of TALE-DNA interactions suggests polarity effects.

PubMed

Meckler, Joshua F; Bhakta, Mital S; Kim, Moon-Soo; Ovadia, Robert; Habrian, Chris H; Zykovich, Artem; Yu, Abigail; Lockwood, Sarah H; Morbitzer, Robert; Elsäesser, Janett; Lahaye, Thomas; Segal, David J; Baldwin, Enoch P

2013-04-01

Transcription activator-like effectors (TALEs) have revolutionized the field of genome engineering. We present here a systematic assessment of TALE DNA recognition, using quantitative electrophoretic mobility shift assays and reporter gene activation assays. Within TALE proteins, tandem 34-amino acid repeats recognize one base pair each and direct sequence-specific DNA binding through repeat variable di-residues (RVDs). We found that RVD choice can affect affinity by four orders of magnitude, with the relative RVD contribution in the order NG > HD ≈ NN > NI > NK. The NN repeat preferred the base G over A, whereas the NK repeat bound G with 10(3)-fold lower affinity. We compared AvrBs3, a naturally occurring TALE that recognizes its target using some atypical RVD-base combinations, with a designed TALE that precisely matches 'standard' RVDs with the target bases. This comparison revealed unexpected differences in sensitivity to substitutions of the invariant 5'-T. Another surprising observation was that base mismatches at the 5' end of the target site had more disruptive effects on affinity than those at the 3' end, particularly in designed TALEs. These results provide evidence that TALE-DNA recognition exhibits a hitherto un-described polarity effect, in which the N-terminal repeats contribute more to affinity than C-terminal ones.

Assessment of Spectral and Temporal Resolution in Cochlear Implant Users Using Psychoacoustic Discrimination and Speech Cue Categorization.

PubMed

Winn, Matthew B; Won, Jong Ho; Moon, Il Joon

This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). The authors hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. The authors further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Nineteen cochlear implant listeners and 10 listeners with normal hearing participated in a suite of tasks that included spectral ripple discrimination, temporal modulation detection, and syllable categorization, which was split into a spectral cue-based task (targeting the /ba/-/da/ contrast) and a timing cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for cochlear implant listeners. Cochlear implant users were generally less successful at utilizing both spectral and temporal cues for categorization compared with listeners with normal hearing. For the cochlear implant listener group, spectral ripple discrimination was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. Temporal modulation detection using 100- and 10-Hz-modulated noise was not correlated either with the cochlear implant subjects' categorization of voice onset time or with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart nonlinguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (voice onset time) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language.

Assessment of spectral and temporal resolution in cochlear implant users using psychoacoustic discrimination and speech cue categorization

PubMed Central

Winn, Matthew B.; Won, Jong Ho; Moon, Il Joon

2016-01-01

Objectives This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). We hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. We further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Design Nineteen CI listeners and 10 listeners with normal hearing (NH) participated in a suite of tasks that included spectral ripple discrimination (SRD), temporal modulation detection (TMD), and syllable categorization, which was split into a spectral-cue-based task (targeting the /ba/-/da/ contrast) and a timing-cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated in order to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression in order to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for CI listeners. Results CI users were generally less successful at utilizing both spectral and temporal cues for categorization compared to listeners with normal hearing. For the CI listener group, SRD was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. TMD using 100 Hz and 10 Hz modulated noise was not correlated with the CI subjects’ categorization of VOT, nor with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. Conclusions When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart non-linguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (VOT) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language. PMID:27438871

Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

PubMed Central

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

2016-01-01

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

[Recognition of visual objects under forward masking. Effects of cathegorial similarity of test and masking stimuli].

PubMed

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

2013-01-01

In 38 healthy subjects accuracy and response time were examined during recognition of two categories of images--animals andnonliving objects--under forward masking. We revealed new data that masking effects depended of categorical similarity of target and masking stimuli. The recognition accuracy was the lowest and the response time was the most slow, when the target and masking stimuli belongs to the same category, that was combined with high dispersion of response times. The revealed effects were more clear in the task of animal recognition in comparison with the recognition of nonliving objects. We supposed that the revealed effects connected with interference between cortical representations of the target and masking stimuli and discussed our results in context of cortical interference and negative priming.

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

Motion Based Target Acquisition and Evaluation in an Adaptive Machine Vision System

DTIC Science & Technology

1995-05-01

paths in facial recognition and learning. Annals of Neurology, 22, 41-45. Tolman, E.C. (1932) Purposive behavior in Animals and Men. New York: Appleton...Learned scan paths are the active processes of perception. Rizzo et al. (1987) studied the fixation patterns of two patients with impaired facial ... recognition and learning and found an increase in the randomness of the scan patterns compared to controls, indicating that the cortex was failing to direct

Capacity limits in list item recognition: evidence from proactive interference.

PubMed

Cowan, Nelson; Johnson, Troy D; Saults, J Scott

2005-01-01

Capacity limits in short-term recall were investigated using proactive interference (PI) from previous lists in a speeded-recognition task. PI was taken to indicate that the target list length surpassed working memory capacity. Unlike previous studies, words were presented either concurrently or sequentially and a new method was introduced to increase the amount of PI. On average, participants retrieved about four items without PI. We suggest an activation-based account of capacity limits.

Effective Prediction of Errors by Non-native Speakers Using Decision Tree for Speech Recognition-Based CALL System

NASA Astrophysics Data System (ADS)

Wang, Hongcui; Kawahara, Tatsuya

CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.

Speech recognition-based and automaticity programs to help students with severe reading and spelling problems.

PubMed

Higgins, Eleanor L; Raskind, Marshall H

2004-12-01

This study was conducted to assess the effectiveness of two programs developed by the Frostig Center Research Department to improve the reading and spelling of students with learning disabilities (LD): a computer Speech Recognition-based Program (SRBP) and a computer and text-based Automaticity Program (AP). Twenty-eight LD students with reading and spelling difficulties (aged 8 to 18) received each program for 17 weeks and were compared with 16 students in a contrast group who did not receive either program. After adjusting for age and IQ, both the SRBP and AP groups showed significant differences over the contrast group in improving word recognition and reading comprehension. Neither program showed significant differences over contrasts in spelling. The SRBP also improved the performance of the target group when compared with the contrast group on phonological elision and nonword reading efficiency tasks. The AP showed significant differences in all process and reading efficiency measures.

An exemplar-familiarity model predicts short-term and long-term probe recognition across diverse forms of memory search.

PubMed

Nosofsky, Robert M; Cox, Gregory E; Cao, Rui; Shiffrin, Richard M

2014-11-01

Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across diverse conditions that manipulated relations between targets and foils across trials. Subjects saw lists of from 1 to 16 items followed by a single item recognition probe. In a varied-mapping condition, targets and foils could switch roles across trials; in a consistent-mapping condition, targets and foils never switched roles; and in an all-new condition, on each trial a completely new set of items formed the memory set. In the varied-mapping and all-new conditions, mean correct response times (RTs) and error proportions were curvilinear increasing functions of memory set size, with the RT results closely resembling ones from hybrid visual-memory search experiments reported by Wolfe (2012). In the consistent-mapping condition, new-probe RTs were invariant with set size, whereas old-probe RTs increased slightly with increasing study-test lag. With appropriate choice of psychologically interpretable free parameters, the model accounted well for the complete set of results. The work provides support for the hypothesis that a common set of processes involving exemplar-based familiarity may govern long-term and short-term probe recognition across wide varieties of memory- search conditions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Target-responsive DNA-capped nanocontainer used for fabricating universal detector and performing logic operations

PubMed Central

Wu, Li; Ren, Jinsong; Qu, Xiaogang

2014-01-01

Nucleic acids have become a powerful tool in nanotechnology because of their controllable diverse conformational transitions and adaptable higher-order nanostructure. Using single-stranded DNA probes as the pore-caps for various target recognition, here we present an ultrasensitive universal electrochemical detection system based on graphene and mesoporous silica, and achieve sensitivity with all of the major classes of analytes and simultaneously realize DNA logic gate operations. The concept is based on the locking of the pores and preventing the signal-reporter molecules from escape by target-induced the conformational change of the tailored DNA caps. The coupling of ‘waking up’ gatekeeper with highly specific biochemical recognition is an innovative strategy for the detection of various targets, able to compete with classical methods which need expensive instrumentation and sophisticated experimental operations. The present study has introduced a new electrochemical signal amplification concept and also adds a new dimension to the function of graphene-mesoporous materials hybrids as multifunctional nanoscale logic devices. More importantly, the development of this approach would spur further advances in important areas, such as point-of-care diagnostics or detection of specific biological contaminations, and hold promise for use in field analysis. PMID:25249622

Personal glucose meters for detection and quantification of a broad range of analytes

DOEpatents

Lu, Yi; Xiang, Yu

2015-02-03

A general methodology for the development of highly sensitive and selective sensors that can achieve portable, low-cost and quantitative detection of a broad range of targets using only a personal glucose meter (PGM) is disclosed. The method uses recognition molecules that are specific for a target agent, enzymes that can convert an enzyme substrate into glucose, and PGM. Also provided are sensors, which can include a solid support to which is attached a recognition molecule that permits detection of a target agent, wherein the recognition molecule specifically binds to the target agent in the presence of the target agent but not significantly to other agents as well as an enzyme that can catalyze the conversion of a substance into glucose, wherein the enzyme is attached directly or indirectly to the recognition molecule, and wherein in the presence of the target agent the enzyme can convert the substance into glucose. The disclosed sensors can be part of a lateral flow device. Methods of using such sensors for detecting target agents are also provided.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

The intrinsic flexibility of the aptamer targeting the ribosomal protein S8 is a key factor for the molecular recognition.

PubMed

Autiero, Ida; Ruvo, Menotti; Improta, Roberto; Vitagliano, Luigi

2018-04-01

Aptamers are RNA/DNA biomolecules representing an emerging class of protein interactors and regulators. Despite the growing interest in these molecules, current understanding of chemical-physical basis of their target recognition is limited. Recently, the characterization of the aptamer targeting the protein-S8 has suggested that flexibility plays important functional roles. We investigated the structural versatility of the S8-aptamer by molecular dynamics simulations. Five different simulations have been conducted by varying starting structures and temperatures. The simulation of S8-aptamer complex provides a dynamic view of the contacts occurring at the complex interface. The simulation of the aptamer in ligand-free state indicates that its central region is intrinsically endowed with a remarkable flexibility. Nevertheless, none of the trajectory structures adopts the structure observed in the S8-aptamer complex. The aptamer ligand-bound is very rigid in the simulation carried out at 300 K. A structural transition of this state, providing insights into the aptamer-protein recognition process, is observed in a simulation carried out at 400 K. These data indicate that a key event in the binding is linked to the widening of the central region of the aptamer. Particularly relevant is switch of the A26 base from its ligand-free state to a location that allows the G13-C28 base-pairing. Intrinsic flexibility of the aptamer is essential for partner recognition. Present data indicate that S8 recognizes the aptamer through an induced-fit rather than a population-shift mechanism. The present study provides deeper understanding of the structural basis of the structural versatility of aptamers. Copyright © 2018 Elsevier B.V. All rights reserved.

Distinguishing highly confident accurate and inaccurate memory: insights about relevant and irrelevant influences on memory confidence

PubMed Central

Chua, Elizabeth F.; Hannula, Deborah E.; Ranganath, Charan

2012-01-01

It is generally believed that accuracy and confidence in one’s memory are related, but there are many instances when they diverge. Accordingly, it is important to disentangle the factors which contribute to memory accuracy and confidence, especially those factors that contribute to confidence, but not accuracy. We used eye movements to separately measure fluent cue processing, the target recognition experience, and relative evidence assessment on recognition confidence and accuracy. Eye movements were monitored during a face-scene associative recognition task, in which participants first saw a scene cue, followed by a forced-choice recognition test for the associated face, with confidence ratings. Eye movement indices of the target recognition experience were largely indicative of accuracy, and showed a relationship to confidence for accurate decisions. In contrast, eye movements during the scene cue raised the possibility that more fluent cue processing was related to higher confidence for both accurate and inaccurate recognition decisions. In a second experiment, we manipulated cue familiarity, and therefore cue fluency. Participants showed higher confidence for cue-target associations for when the cue was more familiar, especially for incorrect responses. These results suggest that over-reliance on cue familiarity and under-reliance on the target recognition experience may lead to erroneous confidence. PMID:22171810

Distinguishing highly confident accurate and inaccurate memory: insights about relevant and irrelevant influences on memory confidence.

PubMed

Chua, Elizabeth F; Hannula, Deborah E; Ranganath, Charan

2012-01-01

It is generally believed that accuracy and confidence in one's memory are related, but there are many instances when they diverge. Accordingly it is important to disentangle the factors that contribute to memory accuracy and confidence, especially those factors that contribute to confidence, but not accuracy. We used eye movements to separately measure fluent cue processing, the target recognition experience, and relative evidence assessment on recognition confidence and accuracy. Eye movements were monitored during a face-scene associative recognition task, in which participants first saw a scene cue, followed by a forced-choice recognition test for the associated face, with confidence ratings. Eye movement indices of the target recognition experience were largely indicative of accuracy, and showed a relationship to confidence for accurate decisions. In contrast, eye movements during the scene cue raised the possibility that more fluent cue processing was related to higher confidence for both accurate and inaccurate recognition decisions. In a second experiment we manipulated cue familiarity, and therefore cue fluency. Participants showed higher confidence for cue-target associations for when the cue was more familiar, especially for incorrect responses. These results suggest that over-reliance on cue familiarity and under-reliance on the target recognition experience may lead to erroneous confidence.

Structure–function studies of STAR family Quaking proteins bound to their in vivo RNA target sites

PubMed Central

Teplova, Marianna; Hafner, Markus; Teplov, Dmitri; Essig, Katharina; Tuschl, Thomas; Patel, Dinshaw J.

2013-01-01

Mammalian Quaking (QKI) and its Caenorhabditis elegans homolog, GLD-1 (defective in germ line development), are evolutionarily conserved RNA-binding proteins, which post-transcriptionally regulate target genes essential for developmental processes and myelination. We present X-ray structures of the STAR (signal transduction and activation of RNA) domain, composed of Qua1, K homology (KH), and Qua2 motifs of QKI and GLD-1 bound to high-affinity in vivo RNA targets containing YUAAY RNA recognition elements (RREs). The KH and Qua2 motifs of the STAR domain synergize to specifically interact with bases and sugar-phosphate backbones of the bound RRE. Qua1-mediated homodimerization generates a scaffold that enables concurrent recognition of two RREs, thereby plausibly targeting tandem RREs present in many QKI-targeted transcripts. Structure-guided mutations reduced QKI RNA-binding affinity in vitro and in vivo, and expression of QKI mutants in human embryonic kidney cells (HEK293) significantly decreased the abundance of QKI target mRNAs. Overall, our studies define principles underlying RNA target selection by STAR homodimers and provide insights into the post-transcriptional regulatory function of mammalian QKI proteins. PMID:23630077

Label-Free Aptasensors for the Detection of Mycotoxins

PubMed Central

Rhouati, Amina; Catanante, Gaelle; Nunes, Gilvanda; Hayat, Akhtar; Marty, Jean-Louis

2016-01-01

Various methodologies have been reported in the literature for the qualitative and quantitative monitoring of mycotoxins in food and feed samples. Based on their enhanced specificity, selectivity and versatility, bio-affinity assays have inspired many researchers to develop sensors by exploring bio-recognition phenomena. However, a significant problem in the fabrication of these devices is that most of the biomolecules do not generate an easily measurable signal upon binding to the target analytes, and signal-generating labels are required to perform the measurements. In this context, aptamers have been emerged as a potential and attractive bio-recognition element to design label-free aptasensors for various target analytes. Contrary to other bioreceptor-based approaches, the aptamer-based assays rely on antigen binding-induced conformational changes or oligomerization states rather than binding-assisted changes in adsorbed mass or charge. This review will focus on current designs in label-free conformational switchable design strategies, with a particular focus on applications in the detection of mycotoxins. PMID:27999353

A Comparison of the Effects of Electrode Implantation and Targeting on Pattern Classification Accuracy for Prosthesis Control

PubMed Central

Farrell, Todd R.; Weir, Richard F. ff.

2011-01-01

The use of surface versus intramuscular electrodes as well as the effect of electrode targeting on pattern-recognition-based multifunctional prosthesis control was explored. Surface electrodes are touted for their ability to record activity from relatively large portions of muscle tissue. Intramuscular electromyograms (EMGs) can provide focal recordings from deep muscles of the forearm and independent signals relatively free of crosstalk. However, little work has been done to compare the two. Additionally, while previous investigations have either targeted electrodes to specific muscles or used untargeted (symmetric) electrode arrays, no work has compared these approaches to determine if one is superior. The classification accuracies of pattern-recognition-based classifiers utilizing surface and intramuscular as well as targeted and untargeted electrodes were compared across 11 subjects. A repeated-measures analysis of variance revealed that when only EMG amplitude information was used from all available EMG channels, the targeted surface, targeted intramuscular, and untargeted surface electrodes produced similar classification accuracies while the untargeted intramuscular electrodes produced significantly lower accuracies. However, no statistical differences were observed between any of the electrode conditions when additional features were extracted from the EMG signal. It was concluded that the choice of electrode should be driven by clinical factors, such as signal robustness/stability, cost, etc., instead of by classification accuracy. PMID:18713689

Hyperspectral face recognition using improved inter-channel alignment based on qualitative prediction models.

PubMed

Cho, Woon; Jang, Jinbeum; Koschan, Andreas; Abidi, Mongi A; Paik, Joonki

2016-11-28

A fundamental limitation of hyperspectral imaging is the inter-band misalignment correlated with subject motion during data acquisition. One way of resolving this problem is to assess the alignment quality of hyperspectral image cubes derived from the state-of-the-art alignment methods. In this paper, we present an automatic selection framework for the optimal alignment method to improve the performance of face recognition. Specifically, we develop two qualitative prediction models based on: 1) a principal curvature map for evaluating the similarity index between sequential target bands and a reference band in the hyperspectral image cube as a full-reference metric; and 2) the cumulative probability of target colors in the HSV color space for evaluating the alignment index of a single sRGB image rendered using all of the bands of the hyperspectral image cube as a no-reference metric. We verify the efficacy of the proposed metrics on a new large-scale database, demonstrating a higher prediction accuracy in determining improved alignment compared to two full-reference and five no-reference image quality metrics. We also validate the ability of the proposed framework to improve hyperspectral face recognition.

Examination of soldier target recognition with direct view optics

NASA Astrophysics Data System (ADS)

Long, Frederick H.; Larkin, Gabriella; Bisordi, Danielle; Dorsey, Shauna; Marianucci, Damien; Goss, Lashawnta; Bastawros, Michael; Misiuda, Paul; Rodgers, Glenn; Mazz, John P.

2017-10-01

Target recognition and identification is a problem of great military and scientific importance. To examine the correlation between target recognition and optical magnification, ten U.S. Army soldiers were tasked with identifying letters on targets at 800 and 1300 meters away. Letters were used since they are a standard method for measuring visual acuity. The letters were approximately 90 cm high, which is the size of a well-known rifle. Four direct view optics with angular magnifications of 1.5x, 4x, 6x, and 9x were used. The goal of this approach was to measure actual probabilities for correct target identification. Previous scientific literature suggests that target recognition can be modeled as a linear response problem in angular frequency space using the established values for the contrast sensitivity function for a healthy human eye and the experimentally measured modulation transfer function of the optic. At the 9x magnification, the soldiers could identify the letters with almost no errors (i.e., 97% probability of correct identification). At lower magnification, errors in letter identification were more frequent. The identification errors were not random but occurred most frequently with a few pairs of letters (e.g., O and Q), which is consistent with the literature for letter recognition. In addition, in the small subject sample of ten soldiers, there was considerable variation in the observer recognition capability at 1.5x and a range of 800 meters. This can be directly attributed to the variation in the observer visual acuity.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

NASA Astrophysics Data System (ADS)

Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

2017-01-01

A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution.

PubMed

Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

2017-01-06

A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.

Crystal structure of an EfPDF complex with Met-Ala-Ser based on crystallographic packing.

PubMed

Nam, Ki Hyun; Kim, Kook-Han; Kim, Eunice Eun Kyeong; Hwang, Kwang Yeon

2009-04-17

PDF (peptide deformylase) plays a critical role in the production of mature proteins by removing the N-formyl polypeptide of nascent proteins in the prokaryote cell system. This protein is essential for bacterial growth, making it an attractive target for the design of new antibiotics. Accordingly, PDF has been evaluated as a drug target; however, architectural mechanism studies of PDF have not yet fully elucidated its molecular function. We recently reported the crystal structure of PDF produced by Enterococcus faecium [K.H. Nam, J.I. Ham, A. Priyadarshi, E.E. Kim, N. Chung, K.Y. Hwang, "Insight into the antibacterial drug design and architectural mechanism of peptide recognition from the E. faecium peptide deformylase structure", Proteins 74 (2009) 261-265]. Here, we present the crystal structure of the EfPDF complex with MAS (Met-Ser-Ala), thereby not only delineating the architectural mechanism for the recognition of mimic-peptides by N-terminal cleaved expression peptide, but also suggesting possible targets for rational design of antibacterial drugs. In addition to their implications for drug design, these structural studies will facilitate elucidation of the architectural mechanism responsible for the peptide recognition of PDF.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

PubMed Central

Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

2017-01-01

A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining. PMID:28059147

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis

NASA Astrophysics Data System (ADS)

Afzal, Peyman; Mirzaei, Misagh; Yousefi, Mahyar; Adib, Ahmad; Khalajmasoumi, Masoumeh; Zarifi, Afshar Zia; Foster, Patrick; Yasrebi, Amir Bijan

2016-07-01

Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.

Target recognition based on the moment functions of radar signatures

NASA Astrophysics Data System (ADS)

Kim, Kyung-Tae; Kim, Hyo-Tae

2002-03-01

In this paper, we present the results of target recognition research based on the moment functions of various radar signatures, such as time-frequency signatures, range profiles, and scattering centers. The proposed approach utilizes geometrical moments or central moments of the obtained radar signatures. In particular, we derived exact and closed form expressions of the geometrical moments of the adaptive Gaussian representation (AGR), which is one of the adaptive joint time-frequency techniques, and also computed the central moments of range profiles and one-dimensional (1-D) scattering centers on a target, which are obtained by various super-resolution techniques. The obtained moment functions are further processed to provide small dimensional and redundancy-free feature vectors, and classified via a neural network approach or a Bayes classifier. The performances of the proposed technique are demonstrated using a simulated radar cross section (RCS) data set, or a measured RCS data set of various scaled aircraft models, obtained at the Pohang University of Science and Technology (POSTECH) compact range facility. Results show that the techniques in this paper can not only provide reliable classification accuracy, but also save computational resources.

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.

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

Bioinspired Methodology for Artificial Olfaction

PubMed Central

Raman, Baranidharan; Hertz, Joshua L.; Benkstein, Kurt D.; Semancik, Steve

2008-01-01

Artificial olfaction is a potential tool for noninvasive chemical monitoring. Application of “electronic noses” typically involves recognition of “pretrained” chemicals, while long-term operation and generalization of training to allow chemical classification of “unknown” analytes remain challenges. The latter analytical capability is critically important, as it is unfeasible to pre-expose the sensor to every analyte it might encounter. Here, we demonstrate a biologically inspired approach where the recognition and generalization problems are decoupled and resolved in a hierarchical fashion. Analyte composition is refined in a progression from general (e.g., target is a hydrocarbon) to precise (e.g., target is ethane), using highly optimized response features for each step. We validate this approach using a MEMS-based chemiresistive microsensor array. We show that this approach, a unique departure from existing methodologies in artificial olfaction, allows the recognition module to better mitigate sensor-aging effects and to better classify unknowns, enhancing the utility of chemical sensors for real-world applications. PMID:18855409

Real-time observation of DNA recognition and rejection by the RNA-guided endonuclease Cas9.

PubMed

Singh, Digvijay; Sternberg, Samuel H; Fei, Jingyi; Doudna, Jennifer A; Ha, Taekjip

2016-09-14

Binding specificity of Cas9-guide RNA complexes to DNA is important for genome-engineering applications; however, how mismatches influence target recognition/rejection kinetics is not well understood. Here we used single-molecule FRET to probe real-time interactions between Cas9-RNA and DNA targets. The bimolecular association rate is only weakly dependent on sequence; however, the dissociation rate greatly increases from <0.006 s(-1) to >2 s(-1) upon introduction of mismatches proximal to protospacer-adjacent motif (PAM), demonstrating that mismatches encountered early during heteroduplex formation induce rapid rejection of off-target DNA. In contrast, PAM-distal mismatches up to 11 base pairs in length, which prevent DNA cleavage, still allow formation of a stable complex (dissociation rate <0.006 s(-1)), suggesting that extremely slow rejection could sequester Cas9-RNA, increasing the Cas9 expression level necessary for genome-editing, thereby aggravating off-target effects. We also observed at least two different bound FRET states that may represent distinct steps in target search and proofreading.

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

A unique dual recognition hairpin probe mediated fluorescence amplification method for sensitive detection of uracil-DNA glycosylase and endonuclease IV activities.

PubMed

Wu, Yushu; Yan, Ping; Xu, Xiaowen; Jiang, Wei

2016-03-07

Uracil-DNA glycosylase (UDG) and endonuclease IV (Endo IV) play cooperative roles in uracil base-excision repair (UBER) and inactivity of either will interrupt the UBER to cause disease. Detection of UDG and Endo IV activities is crucial to evaluate the UBER process in fundamental research and diagnostic application. Here, a unique dual recognition hairpin probe mediated fluorescence amplification method was developed for sensitively and selectively detecting UDG and Endo IV activities. For detecting UDG activity, the uracil base in the probe was excised by the target enzyme to generate an apurinic/apyrimidinic (AP) site, achieving the UDG recognition. Then, the AP site was cleaved by a tool enzyme Endo IV, releasing a primer to trigger rolling circle amplification (RCA) reaction. Finally, the RCA reaction produced numerous repeated G-quadruplex sequences, which interacted with N-methyl-mesoporphyrin IX to generate an enhanced fluorescence signal. Alternatively, for detecting Endo IV activity, the uracil base in the probe was first converted into an AP site by a tool enzyme UDG. Next, the AP site was cleaved by the target enzyme, achieving the Endo IV recognition. The signal was then generated and amplified in the same way as those in the UDG activity assay. The detection limits were as low as 0.00017 U mL(-1) for UDG and 0.11 U mL(-1) for Endo IV, respectively. Moreover, UDG and Endo IV can be well distinguished from their analogs. This method is beneficial for properly evaluating the UBER process in function studies and disease prognoses.

Differences in antigen presentation to MHC class I-and class II- restricted influenza virus-specific cytolytic T lymphocyte clones

PubMed Central

1986-01-01

We have examined requirements for antigen presentation to a panel of MHC class I-and class II-restricted, influenza virus-specific CTL clones by controlling the form of virus presented on the target cell surface. Both H-2K/D- and I region-restricted CTL recognize target cells exposed to infectious virus, but only the I region-restricted clones efficiently lysed histocompatible target cells pulsed with inactivated virus preparations. The isolated influenza hemagglutinin (HA) polypeptide also could sensitize target cells for recognition by class II-restricted, HA-specific CTL, but not by class I-restricted, HA- specific CTL. Inhibition of nascent viral protein synthesis abrogated the ability of target cells to present viral antigen relevant for class I-restricted CTL recognition. Significantly, presentation for class II- restricted recognition was unaffected in target cells exposed to preparations of either inactivated or infectious virus. This differential sensitivity suggested that these H-2I region-restricted CTL recognized viral polypeptides derived from the exogenously introduced virions, rather than viral polypeptides newly synthesized in the infected cell. In support of this contention, treatment of the target cells with the lysosomotropic agent chloroquine abolished recognition of infected target cells by class II-restricted CTL without diminishing class I-restricted recognition of infected target cells. Furthermore, when the influenza HA gene was introduced into target cells without exogenous HA polypeptide, the target cells that expressed the newly synthesized protein product of the HA gene were recognized only by H-2K/D-restricted CTL. These observations suggest that important differences may exist in requirements for antigen presentation between H-2K/D and H-2I region-restricted CTL. These differences may reflect the nature of the antigenic epitopes recognized by these two CTL subsets. PMID:3485173

Excimer-based peptide beacons: a convenient experimental approach for monitoring polypeptide-protein and polypeptide-oligonucleotide interactions.

PubMed

Oh, Kenneth J; Cash, Kevin J; Plaxco, Kevin W

2006-11-01

While protein-polypeptide and nucleic acid-polypeptide interactions are of significant experimental interest, quantitative methods for the characterization of such interactions are often cumbersome. Here we described a relatively simple means of optically monitoring such interactions using excimer-based peptide beacons (PBs). The design of PBs is based on the observation that, whereas short peptides are almost invariably unfolded and highly dynamic, they become rigid when complexed with macromolecular targets. Using this binding-induced folding to segregate two pyrene moieties and therefore inhibit excimer formation, we have produced PBs directed against both anti-HIV antibodies and the retroviral transactive response (TAR) RNA hairpin. For both polypeptides, target recognition is accompanied by a roughly 2-fold decrease in excimer emission, thus allowing the detection of their respective targets at concentrations of a few nanomolar. Because excimer emission requires the formation of a tight, precisely oriented pyrene dimer, even relatively trivial binding-induced segregation reduces fluorescence significantly. This suggests that the PB approach will be suitable for monitoring a wide range of peptide-macromolecule recognition events. Moreover, the synthesis of excimer-based PBs utilizes commercially available modified pyrenes in a simple and well-established protocol, making the approach well suited for routine laboratory applications.

Open set recognition of aircraft in aerial imagery using synthetic template models

NASA Astrophysics Data System (ADS)

Bapst, Aleksander B.; Tran, Jonathan; Koch, Mark W.; Moya, Mary M.; Swahn, Robert

2017-05-01

Fast, accurate and robust automatic target recognition (ATR) in optical aerial imagery can provide game-changing advantages to military commanders and personnel. ATR algorithms must reject non-targets with a high degree of confidence in a world with an infinite number of possible input images. Furthermore, they must learn to recognize new targets without requiring massive data collections. Whereas most machine learning algorithms classify data in a closed set manner by mapping inputs to a fixed set of training classes, open set recognizers incorporate constraints that allow for inputs to be labelled as unknown. We have adapted two template-based open set recognizers to use computer generated synthetic images of military aircraft as training data, to provide a baseline for military-grade ATR: (1) a frequentist approach based on probabilistic fusion of extracted image features, and (2) an open set extension to the one-class support vector machine (SVM). These algorithms both use histograms of oriented gradients (HOG) as features as well as artificial augmentation of both real and synthetic image chips to take advantage of minimal training data. Our results show that open set recognizers trained with synthetic data and tested with real data can successfully discriminate real target inputs from non-targets. However, there is still a requirement for some knowledge of the real target in order to calibrate the relationship between synthetic template and target score distributions. We conclude by proposing algorithm modifications that may improve the ability of synthetic data to represent real data.

RecceMan: an interactive recognition assistance for image-based reconnaissance: synergistic effects of human perception and computational methods for object recognition, identification, and infrastructure analysis

NASA Astrophysics Data System (ADS)

El Bekri, Nadia; Angele, Susanne; Ruckhäberle, Martin; Peinsipp-Byma, Elisabeth; Haelke, Bruno

2015-10-01

This paper introduces an interactive recognition assistance system for imaging reconnaissance. This system supports aerial image analysts on missions during two main tasks: Object recognition and infrastructure analysis. Object recognition concentrates on the classification of one single object. Infrastructure analysis deals with the description of the components of an infrastructure and the recognition of the infrastructure type (e.g. military airfield). Based on satellite or aerial images, aerial image analysts are able to extract single object features and thereby recognize different object types. It is one of the most challenging tasks in the imaging reconnaissance. Currently, there are no high potential ATR (automatic target recognition) applications available, as consequence the human observer cannot be replaced entirely. State-of-the-art ATR applications cannot assume in equal measure human perception and interpretation. Why is this still such a critical issue? First, cluttered and noisy images make it difficult to automatically extract, classify and identify object types. Second, due to the changed warfare and the rise of asymmetric threats it is nearly impossible to create an underlying data set containing all features, objects or infrastructure types. Many other reasons like environmental parameters or aspect angles compound the application of ATR supplementary. Due to the lack of suitable ATR procedures, the human factor is still important and so far irreplaceable. In order to use the potential benefits of the human perception and computational methods in a synergistic way, both are unified in an interactive assistance system. RecceMan® (Reconnaissance Manual) offers two different modes for aerial image analysts on missions: the object recognition mode and the infrastructure analysis mode. The aim of the object recognition mode is to recognize a certain object type based on the object features that originated from the image signatures. The infrastructure analysis mode pursues the goal to analyze the function of the infrastructure. The image analyst extracts visually certain target object signatures, assigns them to corresponding object features and is finally able to recognize the object type. The system offers him the possibility to assign the image signatures to features given by sample images. The underlying data set contains a wide range of objects features and object types for different domains like ships or land vehicles. Each domain has its own feature tree developed by aerial image analyst experts. By selecting the corresponding features, the possible solution set of objects is automatically reduced and matches only the objects that contain the selected features. Moreover, we give an outlook of current research in the field of ground target analysis in which we deal with partly automated methods to extract image signatures and assign them to the corresponding features. This research includes methods for automatically determining the orientation of an object and geometric features like width and length of the object. This step enables to reduce automatically the possible object types offered to the image analyst by the interactive recognition assistance system.

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

PubMed Central

Shinozaki, Takahiro

2018-01-01

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

New Approaches Towards Recognition of Nucleic Acid Triple Helices

PubMed Central

Arya, Dev P.

2012-01-01

We show that groove recognition of nucleic acid triple helices can be achieved with aminosugars. Among these aminosugars, neomycin is the most effective aminoglycoside (groove binder) for stabilizing a DNA triple helix. It stabilizes both the T·A·T triplex and mixed-base DNA triplexes better than known DNA minor groove binders (which usually destabilize the triplex) and polyamines. Neomycin selectively stabilizes the triplex (T·A·T and mixed base) without any effect on the DNA duplex. The selectivity of neomycin likely originates from its potential and shape complementarity to the triplex Watson–Hoogsteen groove, making it the first molecule that selectively recognizes a triplex groove over a duplex groove. The groove recognition of aminoglycosides is not limited to DNA triplexes, but also extends to RNA and hybrid triple helical structures. Intercalator–neomycin conjugates are shown to simultaneously probe the base stacking and groove surface in the DNA triplex. Calorimetric and spectrosocopic studies allow the quantification of the effect of surface area of the intercalating moiety on binding to the triplex. These studies outline a novel approach to the recognition of DNA triplexes that incorporates the use of non-competing binding sites. These principles of dual recognition should be applicable to the design of ligands that can bind any given nucleic acid target with nanomolar affinities and with high selectivity. PMID:21073199

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

PubMed

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

2006-10-01

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

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.

Synthetic lipoprotein as nano-material vehicle in the targeted drug delivery.

PubMed

Zhang, Xueqin; Huang, Gangliang

2017-12-01

High-density lipoprotein (HDL) and low-density lipoprotein (LDL), as human endogenous lipoprotein particles, have low toxicity, high selectivity, and good safety. They can avoid the recognition and clearance of human reticuloendothelial system. These synthetic lipoproteins (sLPs) have been attracted extensive attention as the nanovectors for tumor-targeted drug and gene delivery. Herein, recent advances in the field of anticancer based on these two lipid proteins and recombinant lipoproteins (rLPs) as target delivery vectors were analyzed and discussed.

Pattern recognition with parallel associative memory

NASA Technical Reports Server (NTRS)

Toth, Charles K.; Schenk, Toni

1990-01-01

An examination is conducted of the feasibility of searching targets in aerial photographs by means of a parallel associative memory (PAM) that is based on the nearest-neighbor algorithm; the Hamming distance is used as a measure of closeness, in order to discriminate patterns. Attention has been given to targets typically used for ground-control points. The method developed sorts out approximate target positions where precise localizations are needed, in the course of the data-acquisition process. The majority of control points in different images were correctly identified.

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

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.

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

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

PubMed

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

2016-12-01

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

Effect of colour pop-out on the recognition of letters in crowding conditions.

PubMed

Põder, Endel

2007-11-01

The crowding effect of adjacent objects on the recognition of a target can be reduced when target and flankers differ in some feature, that is irrelevant to the recognition task. In this study, the mechanisms of this effect were explored using targets and flankers of the same and different colours. It was found that facilitation nearly equal to that of differently coloured targets and flankers can be observed with a differently coloured background blob in the location of the target. The different-colour effect does not require advance knowledge of the target and flanker colours, but the effect increases in the course of three trials with constant mapping of colours. The results are consistent with the notion of exogenous attention that facilitates the processing at the most salient locations in the visual field.

Search algorithm complexity modeling with application to image alignment and matching

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2014-05-01

Search algorithm complexity modeling, in the form of penetration rate estimation, provides a useful way to estimate search efficiency in application domains which involve searching over a hypothesis space of reference templates or models, as in model-based object recognition, automatic target recognition, and biometric recognition. The penetration rate quantifies the expected portion of the database that must be searched, and is useful for estimating search algorithm computational requirements. In this paper we perform mathematical modeling to derive general equations for penetration rate estimates that are applicable to a wide range of recognition problems. We extend previous penetration rate analyses to use more general probabilistic modeling assumptions. In particular we provide penetration rate equations within the framework of a model-based image alignment application domain in which a prioritized hierarchical grid search is used to rank subspace bins based on matching probability. We derive general equations, and provide special cases based on simplifying assumptions. We show how previously-derived penetration rate equations are special cases of the general formulation. We apply the analysis to model-based logo image alignment in which a hierarchical grid search is used over a geometric misalignment transform hypothesis space. We present numerical results validating the modeling assumptions and derived formulation.

Discriminating Famous from Fictional Names Based on Lifetime Experience: Evidence in Support of a Signal-Detection Model Based on Finite Mixture Distributions

ERIC Educational Resources Information Center

Bowles, Ben; Harlow, Iain M.; Meeking, Melissa M.; Kohler, Stefan

2012-01-01

It is widely accepted that signal-detection mechanisms contribute to item-recognition memory decisions that involve discriminations between targets and lures based on a controlled laboratory study episode. Here, the authors employed mathematical modeling of receiver operating characteristics (ROC) to determine whether and how a signal-detection…

New technique for real-time distortion-invariant multiobject recognition and classification

NASA Astrophysics Data System (ADS)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

Increase in Speech Recognition Due to Linguistic Mismatch between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

ERIC Educational Resources Information Center

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose: To examine whether improved speech recognition during linguistically mismatched target-masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method: Monolingual English speakers (n = 20) and English-Greek simultaneous bilinguals (n = 20) listened to…

A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts’ law style assessment procedure

PubMed Central

2014-01-01

Background Pattern recognition (PR) based strategies for the control of myoelectric upper limb prostheses are generally evaluated through offline classification accuracy, which is an admittedly useful metric, but insufficient to discuss functional performance in real time. Existing functional tests are extensive to set up and most fail to provide a challenging, objective framework to assess the strategy performance in real time. Methods Nine able-bodied and two amputee subjects gave informed consent and participated in the local Institutional Review Board approved study. We designed a two-dimensional target acquisition task, based on the principles of Fitts’ law for human motor control. Subjects were prompted to steer a cursor from the screen center of into a series of subsequently appearing targets of different difficulties. Three cursor control systems were tested, corresponding to three electromyography-based prosthetic control strategies: 1) amplitude-based direct control (the clinical standard of care), 2) sequential PR control, and 3) simultaneous PR control, allowing for a concurrent activation of two degrees of freedom (DOF). We computed throughput (bits/second), path efficiency (%), reaction time (second), and overshoot (%)) and used general linear models to assess significant differences between the strategies for each metric. Results We validated the proposed methodology by achieving very high coefficients of determination for Fitts’ law. Both PR strategies significantly outperformed direct control in two-DOF targets and were more intuitive to operate. In one-DOF targets, the simultaneous approach was the least precise. The direct control was efficient in one-DOF targets but cumbersome to operate in two-DOF targets through a switch-depended sequential cursor control. Conclusions We designed a test, capable of comprehensively describing prosthetic control strategies in real time. When implemented on control subjects, the test was able to capture statistically significant differences (p < 0.05) in control strategies when considering throughputs, path efficiencies and reaction times. Of particular note, we found statistically significant (p < 0.01) improvements in throughputs and path efficiencies with simultaneous PR when compared to direct control or sequential PR. Amputees could readily achieve the task; however a limited number of subjects was tested and a statistical analysis was not performed with that population. PMID:24886664

A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts' law style assessment procedure.

PubMed

Wurth, Sophie M; Hargrove, Levi J

2014-05-30

Pattern recognition (PR) based strategies for the control of myoelectric upper limb prostheses are generally evaluated through offline classification accuracy, which is an admittedly useful metric, but insufficient to discuss functional performance in real time. Existing functional tests are extensive to set up and most fail to provide a challenging, objective framework to assess the strategy performance in real time. Nine able-bodied and two amputee subjects gave informed consent and participated in the local Institutional Review Board approved study. We designed a two-dimensional target acquisition task, based on the principles of Fitts' law for human motor control. Subjects were prompted to steer a cursor from the screen center of into a series of subsequently appearing targets of different difficulties. Three cursor control systems were tested, corresponding to three electromyography-based prosthetic control strategies: 1) amplitude-based direct control (the clinical standard of care), 2) sequential PR control, and 3) simultaneous PR control, allowing for a concurrent activation of two degrees of freedom (DOF). We computed throughput (bits/second), path efficiency (%), reaction time (second), and overshoot (%)) and used general linear models to assess significant differences between the strategies for each metric. We validated the proposed methodology by achieving very high coefficients of determination for Fitts' law. Both PR strategies significantly outperformed direct control in two-DOF targets and were more intuitive to operate. In one-DOF targets, the simultaneous approach was the least precise. The direct control was efficient in one-DOF targets but cumbersome to operate in two-DOF targets through a switch-depended sequential cursor control. We designed a test, capable of comprehensively describing prosthetic control strategies in real time. When implemented on control subjects, the test was able to capture statistically significant differences (p < 0.05) in control strategies when considering throughputs, path efficiencies and reaction times. Of particular note, we found statistically significant (p < 0.01) improvements in throughputs and path efficiencies with simultaneous PR when compared to direct control or sequential PR. Amputees could readily achieve the task; however a limited number of subjects was tested and a statistical analysis was not performed with that population.

Semantic congruence affects hippocampal response to repetition of visual associations.

PubMed

McAndrews, Mary Pat; Girard, Todd A; Wilkins, Leanne K; McCormick, Cornelia

2016-09-01

Recent research has shown complementary engagement of the hippocampus and medial prefrontal cortex (mPFC) in encoding and retrieving associations based on pre-existing or experimentally-induced schemas, such that the latter supports schema-congruent information whereas the former is more engaged for incongruent or novel associations. Here, we attempted to explore some of the boundary conditions in the relative involvement of those structures in short-term memory for visual associations. The current literature is based primarily on intentional evaluation of schema-target congruence and on study-test paradigms with relatively long delays between learning and retrieval. We used a continuous recognition paradigm to investigate hippocampal and mPFC activation to first and second presentations of scene-object pairs as a function of semantic congruence between the elements (e.g., beach-seashell versus schoolyard-lamp). All items were identical at first and second presentation and the context scene, which was presented 500ms prior to the appearance of the target object, was incidental to the task which required a recognition response to the central target only. Very short lags 2-8 intervening stimuli occurred between presentations. Encoding the targets with congruent contexts was associated with increased activation in visual cortical regions at initial presentation and faster response time at repetition, but we did not find enhanced activation in mPFC relative to incongruent stimuli at either presentation. We did observe enhanced activation in the right anterior hippocampus, as well as regions in visual and lateral temporal and frontal cortical regions, for the repetition of incongruent scene-object pairs. This pattern demonstrates rapid and incidental effects of schema processing in hippocampal, but not mPFC, engagement during continuous recognition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design Strategies for Aptamer-Based Biosensors

PubMed Central

Han, Kun; Liang, Zhiqiang; Zhou, Nandi

2010-01-01

Aptamers have been widely used as recognition elements for biosensor construction, especially in the detection of proteins or small molecule targets, and regarded as promising alternatives for antibodies in bioassay areas. In this review, we present an overview of reported design strategies for the fabrication of biosensors and classify them into four basic modes: target-induced structure switching mode, sandwich or sandwich-like mode, target-induced dissociation/displacement mode and competitive replacement mode. In view of the unprecedented advantages brought about by aptamers and smart design strategies, aptamer-based biosensors are expected to be one of the most promising devices in bioassay related applications. PMID:22399891

Anodal tDCS targeting the right orbitofrontal cortex enhances facial expression recognition

PubMed Central

Murphy, Jillian M.; Ridley, Nicole J.; Vercammen, Ans

2015-01-01

The orbitofrontal cortex (OFC) has been implicated in the capacity to accurately recognise facial expressions. The aim of the current study was to determine if anodal transcranial direct current stimulation (tDCS) targeting the right OFC in healthy adults would enhance facial expression recognition, compared with a sham condition. Across two counterbalanced sessions of tDCS (i.e. anodal and sham), 20 undergraduate participants (18 female) completed a facial expression labelling task comprising angry, disgusted, fearful, happy, sad and neutral expressions, and a control (social judgement) task comprising the same expressions. Responses on the labelling task were scored for accuracy, median reaction time and overall efficiency (i.e. combined accuracy and reaction time). Anodal tDCS targeting the right OFC enhanced facial expression recognition, reflected in greater efficiency and speed of recognition across emotions, relative to the sham condition. In contrast, there was no effect of tDCS to responses on the control task. This is the first study to demonstrate that anodal tDCS targeting the right OFC boosts facial expression recognition. This finding provides a solid foundation for future research to examine the efficacy of this technique as a means to treat facial expression recognition deficits, particularly in individuals with OFC damage or dysfunction. PMID:25971602

Prediction of TF target sites based on atomistic models of protein-DNA complexes

PubMed Central

Angarica, Vladimir Espinosa; Pérez, Abel González; Vasconcelos, Ana T; Collado-Vides, Julio; Contreras-Moreira, Bruno

2008-01-01

Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs) plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition. PMID:18922190

Individual differences in forced-choice recognition memory: partitioning contributions of recollection and familiarity.

PubMed

Migo, Ellen M; Quamme, Joel R; Holmes, Selina; Bendell, Andrew; Norman, Kenneth A; Mayes, Andrew R; Montaldi, Daniela

2014-01-01

In forced-choice recognition memory, two different testing formats are possible under conditions of high target-foil similarity: Each target can be presented alongside foils similar to itself (forced-choice corresponding; FCC), or alongside foils similar to other targets (forced-choice noncorresponding; FCNC). Recent behavioural and neuropsychological studies suggest that FCC performance can be supported by familiarity whereas FCNC performance is supported primarily by recollection. In this paper, we corroborate this finding from an individual differences perspective. A group of older adults were given a test of FCC and FCNC recognition for object pictures, as well as standardized tests of recall, recognition, and IQ. Recall measures were found to predict FCNC, but not FCC performance, consistent with a critical role for recollection in FCNC only. After the common influence of recall was removed, standardized tests of recognition predicted FCC, but not FCNC performance. This is consistent with a contribution of only familiarity in FCC. Simulations show that a two-process model, where familiarity and recollection make separate contributions to recognition, is 10 times more likely to give these results than a single-process model. This evidence highlights the importance of recognition memory test design when examining the involvement of recollection and familiarity.

Recognition of visual stimuli and memory for spatial context in schizophrenic patients and healthy volunteers.

PubMed

Brébion, Gildas; David, Anthony S; Pilowsky, Lyn S; Jones, Hugh

2004-11-01

Verbal and visual recognition tasks were administered to 40 patients with schizophrenia and 40 healthy comparison subjects. The verbal recognition task consisted of discriminating between 16 target words and 16 new words. The visual recognition task consisted of discriminating between 16 target pictures (8 black-and-white and 8 color) and 16 new pictures (8 black-and-white and 8 color). Visual recognition was followed by a spatial context discrimination task in which subjects were required to remember the spatial location of the target pictures at encoding. Results showed that recognition deficit in patients was similar for verbal and visual material. In both schizophrenic and healthy groups, men, but not women, obtained better recognition scores for the colored than for the black-and-white pictures. However, men and women similarly benefited from color to reduce spatial context discrimination errors. Patients showed a significant deficit in remembering the spatial location of the pictures, independently of accuracy in remembering the pictures themselves. These data suggest that patients are impaired in the amount of visual information that they can encode. With regards to the perceptual attributes of the stimuli, memory for spatial information appears to be affected, but not processing of color information.

Quantitative expression and immunogenicity of MAGE-3 and -6 in upper aerodigestive tract cancer.

PubMed

Filho, Pedro A Andrade; López-Albaitero, Andrés; Xi, Liqiang; Gooding, William; Godfrey, Tony; Ferris, Robert L

2009-10-15

The MAGE antigens are frequently expressed cancer vaccine targets. However, quantitative analysis of MAGE expression in upper aerodigestive tract (UADT) tumor cells and its association with T-cell recognition has not been performed, hindering the selection of appropriate candidates for MAGE-specific immunotherapy. Using quantitative RT-PCR (QRT-PCR), we evaluated the expression of MAGE-3/6 in 65 UADT cancers, 48 normal samples from tumor matched sites and 7 HLA-A*0201+ squamous cell carcinoma of the head and neck (SCCHN) cell lines. Expression results were confirmed using Western blot. HLA-A*0201:MAGE-3- (271-279) specific cytotoxic T lymphocytes (MAGE-CTL) from SCCHN patients and healthy donors showed that MAGE-3/6 expression was highly associated with CTL recognition in vitro. On the basis of the MAGE-3/6 expression, we could identify 31 (47%) of the 65 UADT tumors, which appeared to express MAGE-3/6 at levels that correlated with efficient CTL recognition. To confirm that the level of MAGE-3 expression was responsible for CTL recognition, 2 MAGE-3/6 mRNA(high) SCCHN cell lines, PCI-13 and PCI-30, were subjected to MAGE-3/6-specific knockdown. RNAi-transfected cells showed that MAGE expression and MAGE-CTL recognition were significantly reduced. Furthermore, treatment of cells expressing low MAGE-3/6 mRNA with a demethylating agent, 5-aza-2'-deoxycytidine (DAC), increased the expression of MAGE-3/6 and CTL recognition. Thus, using QRT-PCR UADT cancers frequently express MAGE-3/6 at levels sufficient for CTL recognition, supporting the use of a QRT-PCR-based assay for the selection of candidates likely to respond to MAGE-3/6 immunotherapy. Demethylating agents could increase the number of patients amenable for targeting epigenetically modified tumor antigens in vaccine trials.

Advanced miniature processing handware for ATR applications

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Daud, Taher (Inventor); Thakoor, Anikumar (Inventor)

2003-01-01

A Hybrid Optoelectronic Neural Object Recognition System (HONORS), is disclosed, comprising two major building blocks: (1) an advanced grayscale optical correlator (OC) and (2) a massively parallel three-dimensional neural-processor. The optical correlator, with its inherent advantages in parallel processing and shift invariance, is used for target of interest (TOI) detection and segmentation. The three-dimensional neural-processor, with its robust neural learning capability, is used for target classification and identification. The hybrid optoelectronic neural object recognition system, with its powerful combination of optical processing and neural networks, enables real-time, large frame, automatic target recognition (ATR).

Target Recognition Using Neural Networks for Model Deformation Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hibler, David L.

1999-01-01

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

An ancient protein-DNA interaction underlying metazoan sex determination.

PubMed

Murphy, Mark W; Lee, John K; Rojo, Sandra; Gearhart, Micah D; Kurahashi, Kayo; Banerjee, Surajit; Loeuille, Guy-André; Bashamboo, Anu; McElreavey, Kenneth; Zarkower, David; Aihara, Hideki; Bardwell, Vivian J

2015-06-01

DMRT transcription factors are deeply conserved regulators of metazoan sexual development. They share the DM DNA-binding domain, a unique intertwined double zinc-binding module followed by a C-terminal recognition helix, which binds a pseudopalindromic target DNA. Here we show that DMRT proteins use a unique binding interaction, inserting two adjacent antiparallel recognition helices into a widened DNA major groove to make base-specific contacts. Versatility in how specific base contacts are made allows human DMRT1 to use multiple DNA binding modes (tetramer, trimer and dimer). Chromatin immunoprecipitation with exonuclease treatment (ChIP-exo) indicates that multiple DNA binding modes also are used in vivo. We show that mutations affecting residues crucial for DNA recognition are associated with an intersex phenotype in flies and with male-to-female sex reversal in humans. Our results illuminate an ancient molecular interaction underlying much of metazoan sexual development.

An ancient protein-DNA interaction underlying metazoan sex determination

DOE PAGES

Murphy, Mark W.; Lee, John K.; Rojo, Sandra; ...

2015-05-25

DMRT transcription factors are deeply conserved regulators of metazoan sexual development. They share the DM DNA-binding domain, a unique intertwined double zinc-binding module followed by a C-terminal recognition helix, which binds a pseudopalindromic target DNA. In this paper, we show that DMRT proteins use a unique binding interaction, inserting two adjacent antiparallel recognition helices into a widened DNA major groove to make base-specific contacts. Versatility in how specific base contacts are made allows human DMRT1 to use multiple DNA binding modes (tetramer, trimer and dimer). Chromatin immunoprecipitation with exonuclease treatment (ChIP-exo) indicates that multiple DNA binding modes also are usedmore » in vivo. We show that mutations affecting residues crucial for DNA recognition are associated with an intersex phenotype in flies and with male-to-female sex reversal in humans. Finally, our results illuminate an ancient molecular interaction underlying much of metazoan sexual development.« less

An ancient protein-DNA interaction underlying metazoan sex determination

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

Murphy, Mark W.; Lee, John K.; Rojo, Sandra

DMRT transcription factors are deeply conserved regulators of metazoan sexual development. They share the DM DNA-binding domain, a unique intertwined double zinc-binding module followed by a C-terminal recognition helix, which binds a pseudopalindromic target DNA. In this paper, we show that DMRT proteins use a unique binding interaction, inserting two adjacent antiparallel recognition helices into a widened DNA major groove to make base-specific contacts. Versatility in how specific base contacts are made allows human DMRT1 to use multiple DNA binding modes (tetramer, trimer and dimer). Chromatin immunoprecipitation with exonuclease treatment (ChIP-exo) indicates that multiple DNA binding modes also are usedmore » in vivo. We show that mutations affecting residues crucial for DNA recognition are associated with an intersex phenotype in flies and with male-to-female sex reversal in humans. Finally, our results illuminate an ancient molecular interaction underlying much of metazoan sexual development.« less

Neural Dynamics Underlying Target Detection in the Human Brain

PubMed Central

Bansal, Arjun K.; Madhavan, Radhika; Agam, Yigal; Golby, Alexandra; Madsen, Joseph R.

2014-01-01

Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses. PMID:24553944

Repetition priming across distinct contexts: effects of lexical status, word frequency, and retrieval test.

PubMed

Coane, Jennifer H; Balota, David A

2010-12-01

Repetition priming, the facilitation observed when a target is preceded by an identity prime, is a robust phenomenon that occurs across a variety of conditions. Oliphant (1983), however, failed to observe repetition priming for targets embedded in the instructions to an experiment in a subsequent lexical decision task. In the present experiments, we examined the roles of priming context (list or instructions), target lexicality, and target frequency in both lexical decision and episodic recognition performance. Initial encoding context did not modulate priming in lexical decision or recognition memory for low-frequency targets or nonwords, whereas context strongly modulated episodic recognition for high-frequency targets. The results indicate that priming across contexts is sensitive to the distinctiveness of the trace and the reliance on episodic retrieval mechanisms. These results also shed light on the influence of event boundaries, such that priming occurs across different events for relatively distinct (low-frequency) items.

Structural basis for microRNA targeting

DOE PAGES

Schirle, Nicole T.; Sheu-Gruttadauria, Jessica; MacRae, Ian J.

2014-10-31

MicroRNAs (miRNAs) control expression of thousands of genes in plants and animals. miRNAs function by guiding Argonaute proteins to complementary sites in messenger RNAs (mRNAs) targeted for repression. In this paper, we determined crystal structures of human Argonaute-2 (Ago2) bound to a defined guide RNA with and without target RNAs representing miRNA recognition sites. These structures suggest a stepwise mechanism, in which Ago2 primarily exposes guide nucleotides (nt) 2 to 5 for initial target pairing. Pairing to nt 2 to 5 promotes conformational changes that expose nt 2 to 8 and 13 to 16 for further target recognition. Interactions withmore » the guide-target minor groove allow Ago2 to interrogate target RNAs in a sequence-independent manner, whereas an adenosine binding-pocket opposite guide nt 1 further facilitates target recognition. Spurious slicing of miRNA targets is avoided through an inhibitory coordination of one catalytic magnesium ion. Finally, these results explain the conserved nucleotide-pairing patterns in animal miRNA target sites first observed over two decades ago.« less

An innovative pre-targeting strategy for tumor cell specific imaging and therapy

NASA Astrophysics Data System (ADS)

Qin, Si-Yong; Peng, Meng-Yun; Rong, Lei; Jia, Hui-Zhen; Chen, Si; Cheng, Si-Xue; Feng, Jun; Zhang, Xian-Zheng

2015-08-01

A programmed pre-targeting system for tumor cell imaging and targeting therapy was established based on the ``biotin-avidin'' interaction. In this programmed functional system, transferrin-biotin can be actively captured by tumor cells with the overexpression of transferrin receptors, thus achieving the pre-targeting modality. Depending upon avidin-biotin recognition, the attachment of multivalent FITC-avidin to biotinylated tumor cells not only offered the rapid fluorescence labelling, but also endowed the pre-targeted cells with targeting sites for the specifically designed biotinylated peptide nano-drug. Owing to the successful pre-targeting, tumorous HepG2 and HeLa cells were effectively distinguished from the normal 3T3 cells via fluorescence imaging. In addition, the self-assembled peptide nano-drug resulted in enhanced cell apoptosis in the observed HepG2 cells. The tumor cell specific pre-targeting strategy is applicable for a variety of different imaging and therapeutic agents for tumor treatments.A programmed pre-targeting system for tumor cell imaging and targeting therapy was established based on the ``biotin-avidin'' interaction. In this programmed functional system, transferrin-biotin can be actively captured by tumor cells with the overexpression of transferrin receptors, thus achieving the pre-targeting modality. Depending upon avidin-biotin recognition, the attachment of multivalent FITC-avidin to biotinylated tumor cells not only offered the rapid fluorescence labelling, but also endowed the pre-targeted cells with targeting sites for the specifically designed biotinylated peptide nano-drug. Owing to the successful pre-targeting, tumorous HepG2 and HeLa cells were effectively distinguished from the normal 3T3 cells via fluorescence imaging. In addition, the self-assembled peptide nano-drug resulted in enhanced cell apoptosis in the observed HepG2 cells. The tumor cell specific pre-targeting strategy is applicable for a variety of different imaging and therapeutic agents for tumor treatments. Electronic supplementary information (ESI) available: Experimental details, peptide structures, molecular weights, and additional data. See DOI: 10.1039/c5nr03862f

Physical signals for protein-DNA recognition

NASA Astrophysics Data System (ADS)

Cao, Xiao-Qin; Zeng, Jia; Yan, Hong

2009-09-01

This paper discovers consensus physical signals around eukaryotic splice sites, transcription start sites, and replication origin start and end sites on a genome-wide scale based on their DNA flexibility profiles calculated by three different flexibility models. These salient physical signals are localized highly rigid and flexible DNAs, which may play important roles in protein-DNA recognition by the sliding search mechanism. The found physical signals lead us to a detailed hypothetical view of the search process in which a DNA-binding protein first finds a genomic region close to the target site from an arbitrary starting location by three-dimensional (3D) hopping and intersegment transfer mechanisms for long distances, and subsequently uses the one-dimensional (1D) sliding mechanism facilitated by the localized highly rigid DNAs to accurately locate the target flexible binding site within 30 bp (base pair) short distances. Guided by these physical signals, DNA-binding proteins rapidly search the entire genome to recognize a specific target site from the 3D to 1D pathway. Our findings also show that current promoter prediction programs (PPPs) based on DNA physical properties may suffer from lots of false positives because other functional sites such as splice sites and replication origins have similar physical signals as promoters do.

Human target acquisition performance

NASA Astrophysics Data System (ADS)

Teaney, Brian P.; Du Bosq, Todd W.; Reynolds, Joseph P.; Thompson, Roger; Aghera, Sameer; Moyer, Steven K.; Flug, Eric; Espinola, Richard; Hixson, Jonathan

2012-06-01

The battlefield has shifted from armored vehicles to armed insurgents. Target acquisition (identification, recognition, and detection) range performance involving humans as targets is vital for modern warfare. The acquisition and neutralization of armed insurgents while at the same time minimizing fratricide and civilian casualties is a mounting concern. U.S. Army RDECOM CERDEC NVESD has conducted many experiments involving human targets for infrared and reflective band sensors. The target sets include human activities, hand-held objects, uniforms & armament, and other tactically relevant targets. This paper will define a set of standard task difficulty values for identification and recognition associated with human target acquisition performance.

Hyaluronan functionalizing QDs as turn-on fluorescent probe for targeted recognition CD44 receptor

NASA Astrophysics Data System (ADS)

Zhou, Shang; Huo, Danqun; Hou, Changjun; Yang, Mei; Fa, Huanbao

2017-09-01

The recognition of tumor markers in living cancer cells has attracted increasing interest. In the present study, the turn-on fluorescence probe was designed based on the fluorescence of thiolated chitosan-coated CdTe QDs (CdTe/TCS QDs) quenched by hyaluronan, which could provide the low background signal for sensitive cellular imaging. This system is expected to offer specific recognition of CD44 receptor over other substances owing to the specific affinity of hyaluronan and CD44 receptor ( 8-9 kcal/mol). The probe is stable in aqueous and has little toxicity to living cells; thus, it can be utilized for targeted cancer cell imaging. The living lung cancer cell imaging experiments further demonstrate its value in recognizing cell-surface CD44 receptor with turn-on mode. In addition, the probe can be used to recognize and differentiate the subtypes of lung cancer cells based on the difference of CD44 expression on the surface of lung cancer cells. And, the western blot test further confirmed that the expression level of the CD44 receptor in lung cancer cells is different. Therefore, this probe may be potentially applied in recognizing lung cancer cells with higher contrast and sensitivity and provide new tools for cancer prognosis and therapy. [Figure not available: see fulltext.

Position estimation and driving of an autonomous vehicle by monocular vision

NASA Astrophysics Data System (ADS)

Hanan, Jay C.; Kayathi, Pavan; Hughlett, Casey L.

2007-04-01

Automatic adaptive tracking in real-time for target recognition provided autonomous control of a scale model electric truck. The two-wheel drive truck was modified as an autonomous rover test-bed for vision based guidance and navigation. Methods were implemented to monitor tracking error and ensure a safe, accurate arrival at the intended science target. Some methods are situation independent relying only on the confidence error of the target recognition algorithm. Other methods take advantage of the scenario of combined motion and tracking to filter out anomalies. In either case, only a single calibrated camera was needed for position estimation. Results from real-time autonomous driving tests on the JPL simulated Mars yard are presented. Recognition error was often situation dependent. For the rover case, the background was in motion and may be characterized to provide visual cues on rover travel such as rate, pitch, roll, and distance to objects of interest or hazards. Objects in the scene may be used as landmarks, or waypoints, for such estimations. As objects are approached, their scale increases and their orientation may change. In addition, particularly on rough terrain, these orientation and scale changes may be unpredictable. Feature extraction combined with the neural network algorithm was successful in providing visual odometry in the simulated Mars environment.

Author name recognition in degraded journal images

NASA Astrophysics Data System (ADS)

de Bodard de la Jacopière, Aliette; Likforman-Sulem, Laurence

2006-01-01

A method for extracting names in degraded documents is presented in this article. The documents targeted are images of photocopied scientific journals from various scientific domains. Due to the degradation, there is poor OCR recognition, and pieces of other articles appear on the sides of the image. The proposed approach relies on the combination of a low-level textual analysis and an image-based analysis. The textual analysis extracts robust typographic features, while the image analysis selects image regions of interest through anchor components. We report results on the University of Washington benchmark database.

DNA interrogation by the CRISPR RNA-guided endonuclease Cas9.

PubMed

Sternberg, Samuel H; Redding, Sy; Jinek, Martin; Greene, Eric C; Doudna, Jennifer A

2014-03-06

The clustered regularly interspaced short palindromic repeats (CRISPR)-associated enzyme Cas9 is an RNA-guided endonuclease that uses RNA-DNA base-pairing to target foreign DNA in bacteria. Cas9-guide RNA complexes are also effective genome engineering agents in animals and plants. Here we use single-molecule and bulk biochemical experiments to determine how Cas9-RNA interrogates DNA to find specific cleavage sites. We show that both binding and cleavage of DNA by Cas9-RNA require recognition of a short trinucleotide protospacer adjacent motif (PAM). Non-target DNA binding affinity scales with PAM density, and sequences fully complementary to the guide RNA but lacking a nearby PAM are ignored by Cas9-RNA. Competition assays provide evidence that DNA strand separation and RNA-DNA heteroduplex formation initiate at the PAM and proceed directionally towards the distal end of the target sequence. Furthermore, PAM interactions trigger Cas9 catalytic activity. These results reveal how Cas9 uses PAM recognition to quickly identify potential target sites while scanning large DNA molecules, and to regulate scission of double-stranded DNA.

DNA interrogation by the CRISPR RNA-guided endonuclease Cas9

NASA Astrophysics Data System (ADS)

Sternberg, Samuel H.; Redding, Sy; Jinek, Martin; Greene, Eric C.; Doudna, Jennifer A.

2014-03-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-associated enzyme Cas9 is an RNA-guided endonuclease that uses RNA-DNA base-pairing to target foreign DNA in bacteria. Cas9-guide RNA complexes are also effective genome engineering agents in animals and plants. Here we use single-molecule and bulk biochemical experiments to determine how Cas9-RNA interrogates DNA to find specific cleavage sites. We show that both binding and cleavage of DNA by Cas9-RNA require recognition of a short trinucleotide protospacer adjacent motif (PAM). Non-target DNA binding affinity scales with PAM density, and sequences fully complementary to the guide RNA but lacking a nearby PAM are ignored by Cas9-RNA. Competition assays provide evidence that DNA strand separation and RNA-DNA heteroduplex formation initiate at the PAM and proceed directionally towards the distal end of the target sequence. Furthermore, PAM interactions trigger Cas9 catalytic activity. These results reveal how Cas9 uses PAM recognition to quickly identify potential target sites while scanning large DNA molecules, and to regulate scission of double-stranded DNA.

Automatic three-dimensional measurement of large-scale structure based on vision metrology.

PubMed

Zhu, Zhaokun; Guan, Banglei; Zhang, Xiaohu; Li, Daokui; Yu, Qifeng

2014-01-01

All relevant key techniques involved in photogrammetric vision metrology for fully automatic 3D measurement of large-scale structure are studied. A new kind of coded target consisting of circular retroreflective discs is designed, and corresponding detection and recognition algorithms based on blob detection and clustering are presented. Then a three-stage strategy starting with view clustering is proposed to achieve automatic network orientation. As for matching of noncoded targets, the concept of matching path is proposed, and matches for each noncoded target are found by determination of the optimal matching path, based on a novel voting strategy, among all possible ones. Experiments on a fixed keel of airship have been conducted to verify the effectiveness and measuring accuracy of the proposed methods.

Modulation of electronic structures of bases through DNA recognition of protein.

PubMed

Hagiwara, Yohsuke; Kino, Hiori; Tateno, Masaru

2010-04-21

The effects of environmental structures on the electronic states of functional regions in a fully solvated DNA·protein complex were investigated using combined ab initio quantum mechanics/molecular mechanics calculations. A complex of a transcriptional factor, PU.1, and the target DNA was used for the calculations. The effects of solvent on the energies of molecular orbitals (MOs) of some DNA bases strongly correlate with the magnitude of masking of the DNA bases from the solvent by the protein. In the complex, PU.1 causes a variation in the magnitude among DNA bases by means of directly recognizing the DNA bases through hydrogen bonds and inducing structural changes of the DNA structure from the canonical one. Thus, the strong correlation found in this study is the first evidence showing the close quantitative relationship between recognition modes of DNA bases and the energy levels of the corresponding MOs. Thus, it has been revealed that the electronic state of each base is highly regulated and organized by the DNA recognition of the protein. Other biological macromolecular systems can be expected to also possess similar modulation mechanisms, suggesting that this finding provides a novel basis for the understanding for the regulation functions of biological macromolecular systems.

Repetition priming in selective attention: A TVA analysis.

PubMed

Ásgeirsson, Árni Gunnar; Kristjánsson, Árni; Bundesen, Claus

2015-09-01

Current behavior is influenced by events in the recent past. In visual attention, this is expressed in many variations of priming effects. Here, we investigate color priming in a brief exposure digit-recognition task. Observers performed a masked odd-one-out singleton recognition task where the target-color either repeated or changed between subsequent trials. Performance was measured by recognition accuracy over exposure durations. The purpose of the study was to replicate earlier findings of perceptual priming in brief displays and to model those results based on a Theory of Visual Attention (TVA; Bundesen, 1990). We tested 4 different definitions of a generic TVA-model and assessed their explanatory power. Our hypothesis was that priming effects could be explained by selective mechanisms, and that target-color repetitions would only affect the selectivity parameter (α) of our models. Repeating target colors enhanced performance for all 12 observers. As predicted, this was only true under conditions that required selection of a target among distractors, but not when a target was presented alone. Model fits by TVA were obtained with a trial-by-trial maximum likelihood estimation procedure that estimated 4-15 free parameters, depending on the particular model. We draw two main conclusions. Color priming can be modeled simply as a change in selectivity between conditions of repetition or swap of target color. Depending on the desired resolution of analysis; priming can accurately be modeled by a simple four parameter model, where VSTM capacity and spatial biases of attention are ignored, or more fine-grained by a 10 parameter model that takes these aspects into account. Copyright © 2015 Elsevier B.V. All rights reserved.

Supramolecular chemistry-general principles and selected examples from anion recognition and metallosupramolecular chemistry.

PubMed

Albrecht, Markus

2007-12-01

This review gives an introduction into supramolecular chemistry describing in the first part general principles, focusing on terms like noncovalent interaction, molecular recognition, self-assembly, and supramolecular function. In the second part those will be illustrated by simple examples from our laboratories. Supramolecular chemistry is the science that bridges the gap between the world of molecules and nanotechnology. In supramolecular chemistry noncovalent interactions occur between molecular building blocks, which by molecular recognition and self-assembly form (functional) supramolecular entities. It is also termed the "chemistry of the noncovalent bond." Molecular recognition is based on geometrical complementarity based on the "key-and-lock" principle with nonshape-dependent effects, e.g., solvatization, being also highly influential. Self-assembly leads to the formation of well-defined aggregates. Hereby the overall structure of the target ensemble is controlled by the symmetry features of the certain building blocks. Finally, the aggregates can possess special properties or supramolecular functions, which are only found in the ensemble but not in the participating molecules. This review gives an introduction on supramolecular chemistry and illustrates the fundamental principles by recent examples from our group.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

Eyes on crowding: crowding is preserved when responding by eye and similarly affects identity and position accuracy.

PubMed

Yildirim, Funda; Meyer, Vincent; Cornelissen, Frans W

2015-02-16

Peripheral vision guides recognition and selection of targets for eye movements. Crowding—a decline in recognition performance that occurs when a potential target is surrounded by other, similar, objects—influences peripheral object recognition. A recent model study suggests that crowding may be due to increased uncertainty about both the identity and the location of peripheral target objects, but very few studies have assessed these properties in tandem. Eye tracking can integrally provide information on both the perceived identity and the position of a target and therefore could become an important approach in crowding studies. However, recent reports suggest that around the moment of saccade preparation crowding may be significantly modified. If these effects were to generalize to regular crowding tasks, it would complicate the interpretation of results obtained with eye tracking and the comparison to results obtained using manual responses. For this reason, we first assessed whether the manner by which participants responded—manually or by eye—affected their performance. We found that neither recognition performance nor response time was affected by the response type. Hence, we conclude that crowding magnitude was preserved when observers responded by eye. In our main experiment, observers made eye movements to the location of a tilted Gabor target while we varied flanker tilt to manipulate target-flanker similarity. The results indicate that this similarly affected the accuracy of peripheral recognition and saccadic target localization. Our results inform about the importance of both location and identity uncertainty in crowding. © 2015 ARVO.

A hierarchical, automated target recognition algorithm for a parallel analog processor

NASA Technical Reports Server (NTRS)

Woodward, Gail; Padgett, Curtis

1997-01-01

A hierarchical approach is described for an automated target recognition (ATR) system, VIGILANTE, that uses a massively parallel, analog processor (3DANN). The 3DANN processor is capable of performing 64 concurrent inner products of size 1x4096 every 250 nanoseconds.

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.

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method can achieve better performance than such previous methods as entropy and Gibbs error based methods and a conventional committee-based method. We also show that the incorporation of named entity recognition into the active learning for event extraction and the unknown word handling further improve the active learning method. In addition, the adaptation of the active learning method into named entity recognition tasks also improves the document selection for manual annotation of named entities.

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

DTIC Science & Technology

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

Review of Current Aided/Automatic Target Acquisition Technology for Military Target Acquisition Tasks

DTIC Science & Technology

2011-07-01

radar [e.g., synthetic aperture radar (SAR)]. EO/IR includes multi- and hyperspectral imaging. Signal processing of data from nonimaging sensors, such...enhanced recognition ability. Other nonimage -based techniques, such as category theory,45 hierarchical systems,46 and gradient index flow,47 are possible...the battle- field. There is a plethora of imaging and nonimaging sensors on the battlefield that are being networked together for trans- mission of

Toxins of Prokaryotic Toxin-Antitoxin Systems with Sequence-Specific Endoribonuclease Activity

PubMed Central

Masuda, Hisako; Inouye, Masayori

2017-01-01

Protein translation is the most common target of toxin-antitoxin system (TA) toxins. Sequence-specific endoribonucleases digest RNA in a sequence-specific manner, thereby blocking translation. While past studies mainly focused on the digestion of mRNA, recent analysis revealed that toxins can also digest tRNA, rRNA and tmRNA. Purified toxins can digest single-stranded portions of RNA containing recognition sequences in the absence of ribosome in vitro. However, increasing evidence suggests that in vivo digestion may occur in association with ribosomes. Despite the prevalence of recognition sequences in many mRNA, preferential digestion seems to occur at specific positions within mRNA and also in certain reading frames. In this review, a variety of tools utilized to study the nuclease activities of toxins over the past 15 years will be reviewed. A recent adaptation of an RNA-seq-based technique to analyze entire sets of cellular RNA will be introduced with an emphasis on its strength in identifying novel targets and redefining recognition sequences. The differences in biochemical properties and postulated physiological roles will also be discussed. PMID:28420090

Facial Expression Influences Face Identity Recognition During the Attentional Blink

PubMed Central

2014-01-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry—suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another. PMID:25286076

Facial expression influences face identity recognition during the attentional blink.

PubMed

Bach, Dominik R; Schmidt-Daffy, Martin; Dolan, Raymond J

2014-12-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry-suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another.

Single-Stranded γPNAs for In Vivo Site-Specific Genome Editing via Watson-Crick Recognition

PubMed Central

Bahal, Raman; Quijano, Elias; McNeer, Nicole Ali; Liu, Yanfeng; Bhunia, Dinesh C.; López-Giráldez, Francesco; Fields, Rachel J.; Saltzman, W. Mark; Ly, Danith H.; Glazer, Peter M.

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction. PMID:25174576

Single-stranded γPNAs for in vivo site-specific genome editing via Watson-Crick recognition.

PubMed

Bahal, Raman; Quijano, Elias; McNeer, Nicole A; Liu, Yanfeng; Bhunia, Dinesh C; Lopez-Giraldez, Francesco; Fields, Rachel J; Saltzman, William M; Ly, Danith H; Glazer, Peter M

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction.

Chemiresistive and Gravimetric Dual-Mode Gas Sensor toward Target Recognition and Differentiation.

PubMed

Chen, Yan; Zhang, Hao; Feng, Zhihong; Zhang, Hongxiang; Zhang, Rui; Yu, Yuanyuan; Tao, Jin; Zhao, Hongyuan; Guo, Wenlan; Pang, Wei; Duan, Xuexin; Liu, Jing; Zhang, Daihua

2016-08-24

We demonstrate a dual-mode gas sensor for simultaneous and independent acquisition of electrical and mechanical signals from the same gas adsorption event. The device integrates a graphene field-effect transistor (FET) with a piezoelectric resonator in a seamless manner by leveraging multiple structural and functional synergies. Dual signals resulting from independent physical processes, i.e., mass attachment and charge transfer can reflect intrinsic properties of gas molecules and potentially enable target recognition and quantification at the same time. Fabrication of the device is based on standard Integrated Circuit (IC) foundry processes and fully compatible with system-on-a-chip (SoC) integration to achieve extremely small form factors. In addition, the ability of simultaneous measurements of mass adsorption and charge transfer guides us to a more precise understanding of the interactions between graphene and various gas molecules. Besides its practical functions, the device serves as an effective tool to quantitatively investigate the physical processes and sensing mechanisms for a large library of sensing materials and target analytes.

Glucose enhancement of a facial recognition task in young adults.

PubMed

Metzger, M M

2000-02-01

Numerous studies have reported that glucose administration enhances memory processes in both elderly and young adult subjects. Although these studies have utilized a variety of procedures and paradigms, investigations of both young and elderly subjects have typically used verbal tasks (word list recall, paragraph recall, etc.). In the present study, the effect of glucose consumption on a nonverbal, facial recognition task in young adults was examined. Lemonade sweetened with either glucose (50 g) or saccharin (23.7 mg) was consumed by college students (mean age of 21.1 years) 15 min prior to a facial recognition task. The task consisted of a familiarization phase in which subjects were presented with "target" faces, followed immediately by a recognition phase in which subjects had to identify the targets among a random array of familiar target and novel "distractor" faces. Statistical analysis indicated that there were no differences on hit rate (target identification) for subjects who consumed either saccharin or glucose prior to the test. However, further analyses revealed that subjects who consumed glucose committed significantly fewer false alarms and had (marginally) higher d-prime scores (a signal detection measure) compared to subjects who consumed saccharin prior to the test. These results parallel a previous report demonstrating glucose enhancement of a facial recognition task in probable Alzheimer's patients; however, this is believed to be the first demonstration of glucose enhancement for a facial recognition task in healthy, young adults.

Individual differences in forced-choice recognition memory: Partitioning contributions of recollection and familiarity

PubMed Central

Migo, Ellen M.; Quamme, Joel R.; Holmes, Selina; Bendell, Andrew; Norman, Kenneth A.; Mayes, Andrew R.; Montaldi, Daniela

2014-01-01

In forced-choice recognition memory, two different testing formats are possible under conditions of high target-foil similarity: each target can be presented alongside foils similar to itself (forced-choice corresponding; FCC), or alongside foils similar to other targets (forced-choice non-corresponding; FCNC).Recent behavioural and neuropsychological studies suggest that FCC performance can be supported by familiarity whereas FCNC performance is supported primarily by recollection. In this paper, we corroborate this finding from an individual differences perspective. A group of older adults were given a test of FCC and FCNC recognition for object pictures, as well as standardised tests of recall, recognition and IQ. Recall measures were found to predict FCNC, but not FCC performance, consistent with a critical role for recollection in FCNC only. After the common influence of recall was removed, standardised tests of recognition predicted FCC, but not FCNC performance. This is consistent with a contribution of only familiarity in FCC. Simulations show that a two process model, where familiarity and recollection make separate contributions to recognition, is ten times more likely to give these results than a single-process model. This evidence highlights the importance of recognition memory test design when examining the involvement of recollection and familiarity. PMID:24796268

Multivariate fMRI and Eye Tracking Reveal Differential Effects of Visual Interference on Recognition Memory Judgments for Objects and Scenes.

PubMed

O'Neil, Edward B; Watson, Hilary C; Dhillon, Sonya; Lobaugh, Nancy J; Lee, Andy C H

2015-09-01

Recent work has demonstrated that the perirhinal cortex (PRC) supports conjunctive object representations that aid object recognition memory following visual object interference. It is unclear, however, how these representations interact with other brain regions implicated in mnemonic retrieval and how congruent and incongruent interference influences the processing of targets and foils during object recognition. To address this, multivariate partial least squares was applied to fMRI data acquired during an interference match-to-sample task, in which participants made object or scene recognition judgments after object or scene interference. This revealed a pattern of activity sensitive to object recognition following congruent (i.e., object) interference that included PRC, prefrontal, and parietal regions. Moreover, functional connectivity analysis revealed a common pattern of PRC connectivity across interference and recognition conditions. Examination of eye movements during the same task in a separate study revealed that participants gazed more at targets than foils during correct object recognition decisions, regardless of interference congruency. By contrast, participants viewed foils more than targets for incorrect object memory judgments, but only after congruent interference. Our findings suggest that congruent interference makes object foils appear familiar and that a network of regions, including PRC, is recruited to overcome the effects of interference.

Strip biosensor for amplified detection of nerve growth factor-beta based on a molecular translator and catalytic DNA circuit.

PubMed

Liu, Jun; Lai, Ting; Mu, Kejie; Zhou, Zheng

2014-10-07

We have demonstrated a new visual detection approach based on a molecular translator and a catalytic DNA circuit for the detection of nerve growth factor-beta (NGF-β). In this assay, a molecular translator based on the binding-induced DNA strand-displacement reaction was employed to convert the input protein to an output DNA signal. The molecular translator is composed of a target recognition element and a signal output element. Target recognition is achieved by the binding of the anti-NGF-β antibody to the target protein. Polyclonal anti-NGF-β antibody is conjugated to DNA1 and DNA2. The antibody conjugated DNA1 is initially hybridized to DNA3 to form a stable DNA1/DNA3 duplex. In the presence of NGF-β, the binding of the same target protein brings DNA1 and DNA2 into close proximity, resulting in an increase in their local effective concentration. This process triggers the strand-displacement reaction between DNA2 and DNA3 and releases the output DNA3. The released DNA3 is further amplified by a catalytic DNA circuit. The product of the catalytic DNA circuit is detected by a strip biosensor. This proposed assay has high sensitivity and selectivity with a dynamic response ranging from 10 fM to 10 pM, and its detection limit is 10 fM of NGF-β. This work provides a sensitive, enzyme-free, and universal strategy for the detection of other proteins.

Experiments and Analysis of Close-Shot Identification of On-Branch Citrus Fruit with RealSense

PubMed Central

Liu, Jizhan; Yuan, Yan; Zhou, Yao; Zhu, Xinxin

2018-01-01

Fruit recognition based on depth information has been a hot topic due to its advantages. However, the present equipment and methods cannot meet the requirements of rapid and reliable recognition and location of fruits in close shot for robot harvesting. To solve this problem, we propose a recognition algorithm for citrus fruit based on RealSense. This method effectively utilizes depth-point cloud data in a close-shot range of 160 mm and different geometric features of the fruit and leaf to recognize fruits with a intersection curve cut by the depth-sphere. Experiments with close-shot recognition of six varieties of fruit under different conditions were carried out. The detection rates of little occlusion and adhesion were from 80–100%. However, severe occlusion and adhesion still have a great influence on the overall success rate of on-branch fruits recognition, the rate being 63.8%. The size of the fruit has a more noticeable impact on the success rate of detection. Moreover, due to close-shot near-infrared detection, there was no obvious difference in recognition between bright and dark conditions. The advantages of close-shot limited target detection with RealSense, fast foreground and background removal and the simplicity of the algorithm with high precision may contribute to high real-time vision-servo operations of harvesting robots. PMID:29751594

A Pilot Study Examining a Computer-Based Intervention to Improve Recognition and Understanding of Emotions in Young Children with Communication and Social Deficits.

PubMed

Romero, Neri L

2017-06-01

A common social impairment in individuals with ASD is difficulty interpreting and or predicting emotions of others. To date, several interventions targeting teaching emotion recognition and understanding have been utilized both by researchers and practitioners. The results suggest that teaching emotion recognition is possible, but that the results do not generalize to non-instructional contexts. This study sought to replicate earlier findings of a positive impact of teaching emotion recognition using a computer-based intervention and to extend it by testing for generalization on live models in the classroom setting. Two boys and one girl, four to eight years in age, educated in self-contained classrooms for students with communication and social skills deficits, participated in this study. A multiple probe across participants design was utilized. Measures of emotion recognition and understanding were assessed at baseline, intervention, and one month post-intervention to determine maintenance effects. Social validity was assessed through parent and teacher questionnaires. All participants showed improvements in measures assessing their recognition of emotions in faces, generalized knowledge to live models, and maintained gains one month post intervention. These preliminary results are encouraging and should be utilized to inform a group design, in order to test efficacy with a larger population. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network.

PubMed

Islam, Kh Tohidul; Raj, Ram Gopal

2017-04-13

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

PubMed Central

Islam, Kh Tohidul; Raj, Ram Gopal

2017-01-01

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471

Target-context unitization effect on the familiarity-related FN400: a face recognition exclusion task.

PubMed

Guillaume, Fabrice; Etienne, Yann

2015-03-01

Using two exclusion tasks, the present study examined how the ERP correlates of face recognition are affected by the nature of the information to be retrieved. Intrinsic (facial expression) and extrinsic (background scene) visual information were paired with face identity and constituted the exclusion criterion at test time. Although perceptual information had to be taken into account in both situations, the FN400 old-new effect was observed only for old target faces on the expression-exclusion task, whereas it was found for both old target and old non-target faces in the background-exclusion situation. These results reveal that the FN400, which is generally interpreted as a correlate of familiarity, was modulated by the retrieval of intra-item and intrinsic face information, but not by the retrieval of extrinsic information. The observed effects on the FN400 depended on the nature of the information to be retrieved and its relationship (unitization) to the recognition target. On the other hand, the parietal old-new effect (generally described as an ERP correlate of recollection) reflected the retrieval of both types of contextual features equivalently. The current findings are discussed in relation to recent controversies about the nature of the recognition processes reflected by the ERP correlates of face recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Object recognition using deep convolutional neural networks with complete transfer and partial frozen layers

NASA Astrophysics Data System (ADS)

Kruithof, Maarten C.; Bouma, Henri; Fischer, Noëlle M.; Schutte, Klamer

2016-10-01

Object recognition is important to understand the content of video and allow flexible querying in a large number of cameras, especially for security applications. Recent benchmarks show that deep convolutional neural networks are excellent approaches for object recognition. This paper describes an approach of domain transfer, where features learned from a large annotated dataset are transferred to a target domain where less annotated examples are available as is typical for the security and defense domain. Many of these networks trained on natural images appear to learn features similar to Gabor filters and color blobs in the first layer. These first-layer features appear to be generic for many datasets and tasks while the last layer is specific. In this paper, we study the effect of copying all layers and fine-tuning a variable number. We performed an experiment with a Caffe-based network on 1000 ImageNet classes that are randomly divided in two equal subgroups for the transfer from one to the other. We copy all layers and vary the number of layers that is fine-tuned and the size of the target dataset. We performed additional experiments with the Keras platform on CIFAR-10 dataset to validate general applicability. We show with both platforms and both datasets that the accuracy on the target dataset improves when more target data is used. When the target dataset is large, it is beneficial to freeze only a few layers. For a large target dataset, the network without transfer learning performs better than the transfer network, especially if many layers are frozen. When the target dataset is small, it is beneficial to transfer (and freeze) many layers. For a small target dataset, the transfer network boosts generalization and it performs much better than the network without transfer learning. Learning time can be reduced by freezing many layers in a network.

Method of passive ranging from infrared image sequence based on equivalent area

NASA Astrophysics Data System (ADS)

Yang, Weiping; Shen, Zhenkang

2007-11-01

The information of range between missile and targets is important not only to missile controlling component, but also to automatic target recognition, so studying the technique of passive ranging from infrared images has important theoretic and practical meanings. Here we tried to get the range between guided missile and target and help to identify targets or dodge a hit. The issue of distance between missile and target is currently a hot and difficult research content. As all know, infrared imaging detector can not range so that it restricts the functions of the guided information processing system based on infrared images. In order to break through the technical puzzle, we investigated the principle of the infrared imaging, after analysing the imaging geometric relationship between the guided missile and the target, we brought forward the method of passive ranging based on equivalent area and provided mathematical analytic formulas. Validating Experiments demonstrate that the presented method has good effect, the lowest relative error can reach 10% in some circumstances.

Host-Guest Recognition-Assisted Electrochemical Release: Its Reusable Sensing Application Based on DNA Cross Configuration-Fueled Target Cycling and Strand Displacement Reaction Amplification.

PubMed

Chang, Yuanyuan; Zhuo, Ying; Chai, Yaqin; Yuan, Ruo

2017-08-15

In this work, an elegantly designed host-guest recognition-assisted electrochemical release was established and applied in a reusable electrochemical biosensor for the detection of microRNA-182-5p (miRNA-182-5p), a prostate cancer biomarker in prostate cancer, based on the DNA cross configuration-fueled target cycling and strand displacement reaction (SDR) amplification. With such a design, the single target miRNA input could be converted to large numbers of single-stranded DNA (S1-Trp and S2-Trp) output, which could be trapped by cucurbit[8]uril methyl viologen (CB-8-MV 2+ ) based on the host-guest recognition, significantly enhancing the sensitivity for miRNA detection. Moreover, the nucleic acids products obtained from the process of cycling amplification could be utilized sufficiently, avoiding the waste and saving the experiment cost. Impressively, by resetting a settled voltage, the proposed biosensor could release S1-Trp and S2-Trp from the electrode surface, attributing that the guest ion methyl viologen (MV 2+ ) was reduced to MV +· under this settled voltage and formed a more-stable CB-8-MV +· -MV +· complex. Once O 2 was introduced in this system, MV +· could be oxidized to MV 2+ , generating the complex of CB-8-MV 2+ for capturing S1-Trp and S2-Trp again in only 5 min. As a result, the simple and fast regeneration of biosensor for target detection was realized on the base of electrochemical redox-driven assembly and release, overcoming the challenges of time-consuming, burdensome operations and expensive experimental cost in traditional reusable biosensors and updating the construction method for a reusable bisensor. Furthermore, the biosensor could be reused for more than 10 times with a regeneration rate of 93.20%-102.24%. After all, the conception of this work provides a novel thought for the construction of effective reusable biosensor to detect miRNA and other biomarkers and has great potential application in the area requiring the release of nucleic acids or proteins.

Single-Stranded DNA Aptamers against Pathogens and Toxins: Identification and Biosensing Applications

PubMed Central

Hong, Ka Lok

2015-01-01

Molecular recognition elements (MREs) can be short sequences of single-stranded DNA, RNA, small peptides, or antibody fragments. They can bind to user-defined targets with high affinity and specificity. There has been an increasing interest in the identification and application of nucleic acid molecular recognition elements, commonly known as aptamers, since they were first described in 1990 by the Gold and Szostak laboratories. A large number of target specific nucleic acids MREs and their applications are currently in the literature. This review first describes the general methodologies used in identifying single-stranded DNA (ssDNA) aptamers. It then summarizes advancements in the identification and biosensing application of ssDNA aptamers specific for bacteria, viruses, their associated molecules, and selected chemical toxins. Lastly, an overview of the basic principles of ssDNA aptamer-based biosensors is discussed. PMID:26199940

Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

NASA Technical Reports Server (NTRS)

Walker, Brian; Lu, Thomas; Chao, Tien-Hsin

2012-01-01

We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

Emotionally enhanced memory for negatively arousing words: storage or retrieval advantage?

PubMed

Nadarevic, Lena

2017-12-01

People typically remember emotionally negative words better than neutral words. Two experiments are reported that investigate whether emotionally enhanced memory (EEM) for negatively arousing words is based on a storage or retrieval advantage. Participants studied non-word-word pairs that either involved negatively arousing or neutral target words. Memory for these target words was tested by means of a recognition test and a cued-recall test. Data were analysed with a multinomial model that allows the disentanglement of storage and retrieval processes in the present recognition-then-cued-recall paradigm. In both experiments the multinomial analyses revealed no storage differences between negatively arousing and neutral words but a clear retrieval advantage for negatively arousing words in the cued-recall test. These findings suggest that EEM for negatively arousing words is driven by associative processes.

Lexical Competition in Non-Native Spoken-Word Recognition

ERIC Educational Resources Information Center

Weber, Andrea; Cutler, Anne

2004-01-01

Four eye-tracking experiments examined lexical competition in non-native spoken-word recognition. Dutch listeners hearing English fixated longer on distractor pictures with names containing vowels that Dutch listeners are likely to confuse with vowels in a target picture name ("pencil," given target "panda") than on less confusable distractors…

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

Very-Long-Distance Remote Hearing and Vibrometry

NASA Technical Reports Server (NTRS)

Maleki, Lute; Yu, Nan; Matsko, Andrey; Savchenkov, Anatoliy

2009-01-01

A proposed development of laser-based instrumentation systems would extend the art of laser Doppler vibrometry beyond the prior limits of laser-assisted remote hearing and industrial vibrometry for detecting defects in operating mechanisms. A system according to the proposal could covertly measure vibrations of objects at distances as large as thousands of kilometers and could process the measurement data to enable recognition of vibrations characteristic of specific objects of interest, thereby enabling recognition of the objects themselves. A typical system as envisioned would be placed in orbit around the Earth for use as a means of determining whether certain objects on or under the ground are of interest as potential military targets. Terrestrial versions of these instruments designed for airborne or land- or sea-based operation could be similarly useful for military or law-enforcement purposes. Prior laser-based remote-hearing systems are not capable of either covert operation or detecting signals beyond modest distances when operated at realistic laser power levels. The performances of prior systems for recognition of objects by remote vibrometry are limited by low signal-to-noise ratios and lack of filtering of optical signals returned from targets. The proposed development would overcome these limitations. A system as proposed would include a narrow-band laser as its target illuminator, a lock-in-detection receiver subsystem, and a laser-power-control subsystem that would utilize feedback of the intensity of background illumination of the target to adjust the laser power. The laser power would be set at a level high enough to enable the desired measurements but below the threshold of detectability by an imaginary typical modern photodetector located at the target and there exposed to the background illumination. The laser beam would be focused tightly on the distant target, such that the receiving optics would be exposed to only one speckle. The return signal would be extremely-narrow-band filtered (to sub-kilohertz bandwidth) in the optical domain by a whispering-gallery- mode filter so as to remove most of the background illumination. The filtered optical signal would be optically amplified. This combination of optical filtering and optical amplification would provide an optical signal that would be strong enough to be detectable but not so strong as to saturate the detector in the lock-in detection subsystem.

Facelock: familiarity-based graphical authentication.

PubMed

Jenkins, Rob; McLachlan, Jane L; Renaud, Karen

2014-01-01

Authentication codes such as passwords and PIN numbers are widely used to control access to resources. One major drawback of these codes is that they are difficult to remember. Account holders are often faced with a choice between forgetting a code, which can be inconvenient, or writing it down, which compromises security. In two studies, we test a new knowledge-based authentication method that does not impose memory load on the user. Psychological research on face recognition has revealed an important distinction between familiar and unfamiliar face perception: When a face is familiar to the observer, it can be identified across a wide range of images. However, when the face is unfamiliar, generalisation across images is poor. This contrast can be used as the basis for a personalised 'facelock', in which authentication succeeds or fails based on image-invariant recognition of faces that are familiar to the account holder. In Study 1, account holders authenticated easily by detecting familiar targets among other faces (97.5% success rate), even after a one-year delay (86.1% success rate). Zero-acquaintance attackers were reduced to guessing (<1% success rate). Even personal attackers who knew the account holder well were rarely able to authenticate (6.6% success rate). In Study 2, we found that shoulder-surfing attacks by strangers could be defeated by presenting different photos of the same target faces in observed and attacked grids (1.9% success rate). Our findings suggest that the contrast between familiar and unfamiliar face recognition may be useful for developers of graphical authentication systems.

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

Unification of automatic target tracking and automatic target recognition

NASA Astrophysics Data System (ADS)

Schachter, Bruce J.

2014-06-01

The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers. The biological model of ATT∪ATR arises from dynamic patterns of activity distributed across many neural circuits and structures (including retina). The information that the brain receives from the eyes is "old news" at the time that it receives it. The eyes and brain forecast a tracked object's future position, rather than relying on received retinal position. Anticipation of the next moment - building up a consistent perception - is accomplished under difficult conditions: motion (eyes, head, body, scene background, target) and processing limitations (neural noise, delays, eye jitter, distractions). Not only does the human vision system surmount these problems, but it has innate mechanisms to exploit motion in support of target detection and classification. Biological vision doesn't normally operate on snapshots. Feature extraction, detection and recognition are spatiotemporal. When vision is viewed as a spatiotemporal process, target detection, recognition, tracking, event detection and activity recognition, do not seem as distinct as they are in current ATT and ATR designs. They appear as similar mechanism taking place at varying time scales. A framework is provided for unifying ATT and ATR.

The role of semantically related distractors during encoding and retrieval of words in long-term memory.

PubMed

Meade, Melissa E; Fernandes, Myra A

2016-07-01

We examined the influence of divided attention (DA) on recognition of words when the concurrent task was semantically related or unrelated to the to-be-recognised target words. Participants were asked to either study or retrieve a target list of semantically related words while simultaneously making semantic decisions (i.e., size judgements) to another set of related or unrelated words heard concurrently. We manipulated semantic relatedness of distractor to target words, and whether DA occurred during the encoding or retrieval phase of memory. Recognition accuracy was significantly diminished relative to full attention, following DA conditions at encoding, regardless of relatedness of distractors to study words. However, response times (RTs) were slower with related compared to unrelated distractors. Similarly, under DA at retrieval, recognition RTs were slower when distractors were semantically related than unrelated to target words. Unlike the effect from DA at encoding, recognition accuracy was worse under DA at retrieval when the distractors were related compared to unrelated to the target words. Results suggest that availability of general attentional resources is critical for successful encoding, whereas successful retrieval is particularly reliant on access to a semantic code, making it sensitive to related distractors under DA conditions.

The Last Meter: Blind Visual Guidance to a Target.

PubMed

Manduchi, Roberto; Coughlan, James M

2014-01-01

Smartphone apps can use object recognition software to provide information to blind or low vision users about objects in the visual environment. A crucial challenge for these users is aiming the camera properly to take a well-framed picture of the desired target object. We investigate the effects of two fundamental constraints of object recognition - frame rate and camera field of view - on a blind person's ability to use an object recognition smartphone app. The app was used by 18 blind participants to find visual targets beyond arm's reach and approach them to within 30 cm. While we expected that a faster frame rate or wider camera field of view should always improve search performance, our experimental results show that in many cases increasing the field of view does not help, and may even hurt, performance. These results have important implications for the design of object recognition systems for blind users.

Scenario-Based Spoken Interaction with Virtual Agents

ERIC Educational Resources Information Center

Morton, Hazel; Jack, Mervyn A.

2005-01-01

This paper describes a CALL approach which integrates software for speaker independent continuous speech recognition with embodied virtual agents and virtual worlds to create an immersive environment in which learners can converse in the target language in contextualised scenarios. The result is a self-access learning package: SPELL (Spoken…

An Underwater Target Detection System for Electro-Optical Imagery Data

DTIC Science & Technology

2010-06-01

detection and segmentation of underwater mine-like objects in the EO images captured with a CCD-based image sensor. The main focus of this research is to...develop a robust detection algorithm that can be used to detect low contrast and partial underwater objects from the EO imagery with low false alarm rate...underwater target detection I. INTRODUCTION Automatic detection and recognition of underwater objects from EO imagery poses a serious challenge due to poor

Feature Extraction Using Attributed Scattering Center Models for Model-Based Automatic Target Recognition (ATR)

DTIC Science & Technology

2005-10-01

section of the coiled arm. Right: measured realized total gain for a square spiral in free space with inductive treatment. . . . . . . . 154 8.5 Initial...appreciable velocities can often be easily separated from clutter returns, slow moving targets of more moderate cross sections can be very difficult to detect...electromagnetic radiation and measuring the energy scattered back. The data obtained as a result of this process is a finite-extent, noisy set of

Young people's comparative recognition and recall of an Australian Government Sexual Health Campaign.

PubMed

Lim, Megan S C; Gold, Judy; Bowring, Anna L; Pedrana, Alisa E; Hellard, Margaret E

2015-05-01

In 2009, the Australian Government's National Sexually Transmitted Infection Prevention Program launched a multi-million dollar sexual health campaign targeting young people. We assessed campaign recognition among a community sample of young people. Individuals aged 16-29 years self-completed a questionnaire at a music festival. Participants were asked whether they recognised the campaign image and attempted to match the correct campaign message. Recognition of two concurrent campaigns, GlaxoSmithKline's The Facts genital herpes campaign (targeting young women) and the Drama Downunder campaign (targeting gay men) were assessed simultaneously. Among 471 participants, just 29% recognised the National Sexually Transmitted Infection Prevention Program campaign. This compared to 52% recognising The Facts and 27% recognising Drama Downunder. Of 134 who recognised the National Sexually Transmitted Infection Prevention Program campaign, 27% correctly recalled the campaign messages compared to 61% of those recognising the Facts campaign, and 25% of those recognising the Drama Downunder campaign. There was no difference in National Sexually Transmitted Infection Prevention Program campaign recognition by gender or age. Campaign recognition and message recall of the National Sexually Transmitted Infection Prevention Program campaign was comparatively low. Future mass media sexual health campaigns targeting young people can aim for higher recognition and recall rates than that achieved by the National Sexually Transmitted Infection Prevention Program campaign. Alternative distribution channels and message styles should be considered to increase these rates. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Social appraisal influences recognition of emotions.

PubMed

Mumenthaler, Christian; Sander, David

2012-06-01

The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved

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

PubMed

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

2017-11-01

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

Diagnosing criterion-level effects on memory: what aspects of memory are enhanced by repeated retrieval?

PubMed

Vaughn, Kalif E; Rawson, Katherine A

2011-09-01

Previous research has shown that increasing the criterion level (i.e., the number of times an item must be correctly retrieved during practice) improves subsequent memory, but which specific components of memory does increased criterion level enhance? In two experiments, we examined the extent to which the criterion level affects associative memory, target memory, and cue memory. Participants studied Lithuanian-English word pairs via cued recall with restudy until items were correctly recalled one to five times. In Experiment 1, participants took one of four recall tests and one of three recognition tests after a 2-day delay. In Experiment 2, participants took only recognition tests after a 1-week delay. In both experiments, increasing the criterion level enhanced associative memory, as indicated by enhanced performance on forward and backward cued-recall tests and on tests of associative recognition. An increased criterion level also improved target memory, as indicated by enhanced free recall and recognition of targets, and improved cue memory, as indicated by enhanced free recall and recognition of cues.

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

The Temporal Dynamics of Spoken Word Recognition in Adverse Listening Conditions

ERIC Educational Resources Information Center

Brouwer, Susanne; Bradlow, Ann R.

2016-01-01

This study examined the temporal dynamics of spoken word recognition in noise and background speech. In two visual-world experiments, English participants listened to target words while looking at four pictures on the screen: a target (e.g. "candle"), an onset competitor (e.g. "candy"), a rhyme competitor (e.g.…

Morpho-Semantic Processing in Word Recognition: Evidence from Balanced and Biased Ambiguous Morphemes

ERIC Educational Resources Information Center

Tsang, Yiu-Kei; Chen, Hsuan-Chih

2013-01-01

The role of morphemic meaning in Chinese word recognition was examined with the masked and unmasked priming paradigms. Target words contained ambiguous morphemes biased toward the dominant or the subordinate meanings. Prime words either contained the same ambiguous morphemes in the subordinate interpretations or were unrelated to the targets. In…

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

PubMed Central

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L.; Rufo, Elena

2013-01-01

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. PMID:23609804

Computational burden resulting from image recognition of high resolution radar sensors.

PubMed

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L; Rufo, Elena

2013-04-22

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Distributed Pheromone-Based Swarming Control of Unmanned Air and Ground Vehicles for RSTA

DTIC Science & Technology

2008-03-20

Forthcoming in Proceedings of SPIE Defense & Security Conference, March 2008, Orlando, FL Distributed Pheromone -Based Swarming Control of Unmanned...describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of...onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm

Determining the optimal window length for pattern recognition-based myoelectric control: balancing the competing effects of classification error and controller delay.

PubMed

Smith, Lauren H; Hargrove, Levi J; Lock, Blair A; Kuiken, Todd A

2011-04-01

Pattern recognition-based control of myoelectric prostheses has shown great promise in research environments, but has not been optimized for use in a clinical setting. To explore the relationship between classification error, controller delay, and real-time controllability, 13 able-bodied subjects were trained to operate a virtual upper-limb prosthesis using pattern recognition of electromyogram (EMG) signals. Classification error and controller delay were varied by training different classifiers with a variety of analysis window lengths ranging from 50 to 550 ms and either two or four EMG input channels. Offline analysis showed that classification error decreased with longer window lengths (p < 0.01 ). Real-time controllability was evaluated with the target achievement control (TAC) test, which prompted users to maneuver the virtual prosthesis into various target postures. The results indicated that user performance improved with lower classification error (p < 0.01 ) and was reduced with longer controller delay (p < 0.01 ), as determined by the window length. Therefore, both of these effects should be considered when choosing a window length; it may be beneficial to increase the window length if this results in a reduced classification error, despite the corresponding increase in controller delay. For the system employed in this study, the optimal window length was found to be between 150 and 250 ms, which is within acceptable controller delays for conventional multistate amplitude controllers.

Investigating the potential of multiwalled carbon nanotubes based zinc nanocomposite as a recognition interface towards plant pathogen detection.

PubMed

Tahir, Muhammad Ali; Hameed, Sadaf; Munawar, Anam; Amin, Imran; Mansoor, Shahid; Khan, Waheed S; Bajwa, Sadia Zafar

2017-11-01

The emergence of nanotechnology has opened new horizons for constructing efficient recognition interfaces. This is the first report where the potential of a multiwalled carbon nanotube based zinc nanocomposite (MWCNTs-Zn NPs) investigated for the detection of an agricultural pathogen i.e. Chili leaf curl betasatellite (ChLCB). Atomic force microscope analyses revealed the presence of multiwalled carbon nanotubes (MWCNTs) having a diameter of 50-100nm with zinc nanoparticles (Zn-NPs) of 25-500nm. In this system, these bunches of Zn-NPs anchored along the whole lengths of MWCNTs were used for the immobilization of probe DNA strands. The electrochemical performance of DNA biosensor was assessed in the absence and presence of the complementary DNA during cyclic and differential pulse voltammetry scans. Target binding events occurring on the interface surface patterned with single-stranded DNA was quantitatively translated into electrochemical signals due to hybridization process. In the presence of complementary target DNA, as the result of duplex formation, there was a decrease in the peak current from 1.89×10 -04 to 5.84×10 -05 A. The specificity of this electrochemical DNA biosensor was found to be three times as compared to non-complementary DNA. This material structuring technique can be extended to design interfaces for the recognition of the other plant viruses and biomolecules. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of Non-Nucleic Acid Targets with an Unmodified Aptamer and a Fluorogenic Competitor

PubMed Central

Li, Na

2010-01-01

Aptamers are oligonucleotides that can bind to various non-nucleic acid targets, ranging from proteins to small molecules, with a specificity and affinity comparable to that of antibodies. Most aptamer-based detection strategies require modification on the aptamer, which could lead to a significant loss in its affinity and specificity to the target. Here we reported a generic strategy to design aptamer-based optical probes. An unmodified aptamer specific to the target and a fluorogenic competitor complementary to the aptamer are utilized for target recognition and signal generation, respectively. The competitor is a hairpin oligonucleotide with a fluorophore attached on one end and a quencher attached on the other. When no target is present, the competitor binds to the aptamer. However, when the target is introduced, the competitor will be displaced from the aptamer by the target, thus resulting in a target-specific decrease in fluorescence signal. Successful application of this strategy to different types of targets (small molecules and proteins) as well as different types of aptamers (DNA and RNA) has been demonstrated. Furthermore, a thermodynamics-based prediction model was established to further rationalize the optimization process. Due to its rapidness and simplicity, this aptamer-based detection strategy holds great promise in high throughput applications. PMID:20563298

Pose estimation of industrial objects towards robot operation

NASA Astrophysics Data System (ADS)

Niu, Jie; Zhou, Fuqiang; Tan, Haishu; Cao, Yu

2017-10-01

With the advantages of wide range, non-contact and high flexibility, the visual estimation technology of target pose has been widely applied in modern industry, robot guidance and other engineering practices. However, due to the influence of complicated industrial environment, outside interference factors, lack of object characteristics, restrictions of camera and other limitations, the visual estimation technology of target pose is still faced with many challenges. Focusing on the above problems, a pose estimation method of the industrial objects is developed based on 3D models of targets. By matching the extracted shape characteristics of objects with the priori 3D model database of targets, the method realizes the recognition of target. Thus a pose estimation of objects can be determined based on the monocular vision measuring model. The experimental results show that this method can be implemented to estimate the position of rigid objects based on poor images information, and provides guiding basis for the operation of the industrial robot.

Sensitive fluorescence detection of nucleic acids based on isothermal circular strand-displacement polymerization reaction.

PubMed

Guo, Qiuping; Yang, Xiaohai; Wang, Kemin; Tan, Weihong; Li, Wei; Tang, Hongxing; Li, Huimin

2009-02-01

Here we have developed a sensitive DNA amplified detection method based on isothermal strand-displacement polymerization reaction. This method takes advantage of both the hybridization property of DNA and the strand-displacement property of polymerase. Importantly, we demonstrate that our method produces a circular polymerization reaction activated by the target, which essentially allows it to self-detect. Functionally, this DNA system consists of a hairpin fluorescence probe, a short primer and polymerase. Upon recognition and hybridization with the target ssDNA, the stem of the hairpin probe is opened, after which the opened probe anneals with the primer and triggers the polymerization reaction. During this process of the polymerization reaction, a complementary DNA is synthesized and the hybridized target is displaced. Finally, the displaced target recognizes and hybridizes with another probe, triggering the next round of polymerization reaction, reaching a target detection limit of 6.4 x 10(-15) M.

Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept

PubMed Central

Drosou, A.; Ioannidis, D.; Moustakas, K.; Tzovaras, D.

2011-01-01

Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities. PMID:21380485

Unobtrusive behavioral and activity-related multimodal biometrics: The ACTIBIO Authentication concept.

PubMed

Drosou, A; Ioannidis, D; Moustakas, K; Tzovaras, D

2011-03-01

Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.

Applications of independent component analysis in SAR images

NASA Astrophysics Data System (ADS)

Huang, Shiqi; Cai, Xinhua; Hui, Weihua; Xu, Ping

2009-07-01

The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of SAR image and increase the detection rate for the faint small targets.

Bio-Mimetic Sensors Based on Molecularly Imprinted Membranes

PubMed Central

Algieri, Catia; Drioli, Enrico; Guzzo, Laura; Donato, Laura

2014-01-01

An important challenge for scientific research is the production of artificial systems able to mimic the recognition mechanisms occurring at the molecular level in living systems. A valid contribution in this direction resulted from the development of molecular imprinting. By means of this technology, selective molecular recognition sites are introduced in a polymer, thus conferring it bio-mimetic properties. The potential applications of these systems include affinity separations, medical diagnostics, drug delivery, catalysis, etc. Recently, bio-sensing systems using molecularly imprinted membranes, a special form of imprinted polymers, have received the attention of scientists in various fields. In these systems imprinted membranes are used as bio-mimetic recognition elements which are integrated with a transducer component. The direct and rapid determination of an interaction between the recognition element and the target analyte (template) was an encouraging factor for the development of such systems as alternatives to traditional bio-assay methods. Due to their high stability, sensitivity and specificity, bio-mimetic sensors-based membranes are used for environmental, food, and clinical uses. This review deals with the development of molecularly imprinted polymers and their different preparation methods. Referring to the last decades, the application of these membranes as bio-mimetic sensor devices will be also reported. PMID:25196110

Tolerance for distorted faces: challenges to a configural processing account of familiar face recognition.

PubMed

Sandford, Adam; Burton, A Mike

2014-09-01

Face recognition is widely held to rely on 'configural processing', an analysis of spatial relations between facial features. We present three experiments in which viewers were shown distorted faces, and asked to resize these to their correct shape. Based on configural theories appealing to metric distances between features, we reason that this should be an easier task for familiar than unfamiliar faces (whose subtle arrangements of features are unknown). In fact, participants were inaccurate at this task, making between 8% and 13% errors across experiments. Importantly, we observed no advantage for familiar faces: in one experiment participants were more accurate with unfamiliars, and in two experiments there was no difference. These findings were not due to general task difficulty - participants were able to resize blocks of colour to target shapes (squares) more accurately. We also found an advantage of familiarity for resizing other stimuli (brand logos). If configural processing does underlie face recognition, these results place constraints on the definition of 'configural'. Alternatively, familiar face recognition might rely on more complex criteria - based on tolerance to within-person variation rather than highly specific measurement. Copyright © 2014 Elsevier B.V. All rights reserved.

Structural insights into ligand recognition and selectivity for class A, B, and C GPCRs

PubMed Central

Lee, Sang-Min; Booe, Jason M.; Pioszak, Augen A.

2015-01-01

The G protein-coupled receptor (GPCR) superfamily constitutes the largest collection of cell surface signaling proteins with approximately 800 members in the human genome. GPCRs regulate virtually all aspects of physiology and they are an important class of drug targets with ~30% of drugs on the market targeting a GPCR. Breakthroughs in GPCR structural biology in recent years have significantly expanded our understanding of GPCR structure and function and ushered in a new era of structure-based drug design for GPCRs. Crystal structures for nearly thirty distinct GPCRs are now available including receptors from each of the major classes, A, B, C, and F. These structures provide a foundation for understanding the molecular basis of GPCR pharmacology. Here, we review structural mechanisms of ligand recognition and selectivity of GPCRs with a focus on selected examples from classes A, B, and C, and we highlight major unresolved questions for future structural studies. PMID:25981303

The Crystal Structure of TAL Effector PthXo1 Bound to Its DNA Target

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

Mak, Amanda Nga-Sze; Bradley, Philip; Cernadas, Raul A.

2012-02-10

DNA recognition by TAL effectors is mediated by tandem repeats, each 33 to 35 residues in length, that specify nucleotides via unique repeat-variable diresidues (RVDs). The crystal structure of PthXo1 bound to its DNA target was determined by high-throughput computational structure prediction and validated by heavy-atom derivatization. Each repeat forms a left-handed, two-helix bundle that presents an RVD-containing loop to the DNA. The repeats self-associate to form a right-handed superhelix wrapped around the DNA major groove. The first RVD residue forms a stabilizing contact with the protein backbone, while the second makes a base-specific contact to the DNA sense strand.more » Two degenerate amino-terminal repeats also interact with the DNA. Containing several RVDs and noncanonical associations, the structure illustrates the basis of TAL effector-DNA recognition.« less

EOID Evaluation and Automated Target Recognition

DTIC Science & Technology

2002-09-30

Electro - Optic IDentification (EOID) sensors into shallow water littoral zone minehunting systems on towed, remotely operated, and autonomous platforms. These downlooking laser-based sensors operate at unparalleled standoff ranges in visible wavelengths to image and identify mine-like objects (MLOs) that have been detected through other sensing means such as magnetic induction and various modes of acoustic imaging. Our long term goal is to provide a robust automated target cueing and identification capability for use with these imaging sensors. It is also our goal to assist

EOID Evaluation and Automated Target Recognition

DTIC Science & Technology

2001-09-30

Electro - Optic IDentification (EOID) sensors into shallow water littoral zone minehunting systems on towed, remotely operated, and autonomous platforms. These downlooking laser-based sensors operate at unparalleled standoff ranges in visible wavelengths to image and identify mine-like objects that have been detected through other sensing means such as magnetic induction and various modes of acoustic imaging. Our long term goal is to provide a robust automated target cueing and identification capability for use with these imaging sensors. It is also our goal to assist the

Argonaute-based programmable RNase as a tool for cleavage of highly-structured RNA.

PubMed

Dayeh, Daniel M; Cantara, William A; Kitzrow, Jonathan P; Musier-Forsyth, Karin; Nakanishi, Kotaro

2018-06-12

The recent identification and development of RNA-guided enzymes for programmable cleavage of target nucleic acids offers exciting possibilities for both therapeutic and biotechnological applications. However, critical challenges such as expensive guide RNAs and inability to predict the efficiency of target recognition, especially for highly-structured RNAs, remain to be addressed. Here, we introduce a programmable RNA restriction enzyme, based on a budding yeast Argonaute (AGO), programmed with cost-effective 23-nucleotide (nt) single-stranded DNAs as guides. DNA guides offer the advantage that diverse sequences can be easily designed and purchased, enabling high-throughput screening to identify optimal recognition sites in the target RNA. Using this DNA-induced slicing complex (DISC) programmed with 11 different guide DNAs designed to span the sequence, sites of cleavage were identified in the 352-nt human immunodeficiency virus type 1 5'-untranslated region. This assay, coupled with primer extension and capillary electrophoresis, allows detection and relative quantification of all DISC-cleavage sites simultaneously in a single reaction. Comparison between DISC cleavage and RNase H cleavage reveals that DISC not only cleaves solvent-exposed sites, but also sites that become more accessible upon DISC binding. This study demonstrates the advantages of the DISC system for programmable cleavage of highly-structured, functional RNAs.

Real-time road detection in infrared imagery

NASA Astrophysics Data System (ADS)

Andre, Haritini E.; McCoy, Keith

1990-09-01

Automatic road detection is an important part in many scene recognition applications. The extraction of roads provides a means of navigation and position update for remotely piloted vehicles or autonomous vehicles. Roads supply strong contextual information which can be used to improve the performance of automatic target recognition (ATh) systems by directing the search for targets and adjusting target classification confidences. This paper will describe algorithmic techniques for labeling roads in high-resolution infrared imagery. In addition, realtime implementation of this structural approach using a processor array based on the Martin Marietta Geometric Arithmetic Parallel Processor (GAPPTh) chip will be addressed. The algorithm described is based on the hypothesis that a road consists of pairs of line segments separated by a distance "d" with opposite gradient directions (antiparallel). The general nature of the algorithm, in addition to its parallel implementation in a single instruction, multiple data (SIMD) machine, are improvements to existing work. The algorithm seeks to identify line segments meeting the road hypothesis in a manner that performs well, even when the side of the road is fragmented due to occlusion or intersections. The use of geometrical relationships between line segments is a powerful yet flexible method of road classification which is independent of orientation. In addition, this approach can be used to nominate other types of objects with minor parametric changes.

Word Recognition is Affected by the Meaning of Orthographic Neighbours: Evidence from Semantic Decision Tasks

ERIC Educational Resources Information Center

Boot, Inge; Pecher, Diane

2008-01-01

Many models of word recognition predict that neighbours of target words will be activated during word processing. Cascaded models can make the additional prediction that semantic features of those neighbours get activated before the target has been uniquely identified. In two semantic decision tasks neighbours that were congruent (i.e., from the…

Relationship between fMRI response during a nonverbal memory task and marijuana use in college students.

PubMed

Dager, Alecia D; Tice, Madelynn R; Book, Gregory A; Tennen, Howard; Raskin, Sarah A; Austad, Carol S; Wood, Rebecca M; Fallahi, Carolyn R; Hawkins, Keith A; Pearlson, Godfrey D

2018-04-26

Marijuana (MJ) is widely used among college students, with peak use between ages 18-22. Research suggests memory dysfunction in adolescent and young adult MJ users, but the neural correlates are unclear. We examined functional magnetic resonance imaging (fMRI) response during a memory task among college students with varying degrees of MJ involvement. Participants were 64 college students, ages 18-20, who performed a visual encoding and recognition task during fMRI. MJ use was ascertained for 3 months prior to scanning; 27 individuals reported past 3-month MJ use, and 33 individuals did not. fMRI response was modeled during encoding based on whether targets were subsequently recognized (correct encoding), and during recognition based on target identification (hits). fMRI response in left and right inferior frontal gyrus (IFG) and hippocampal regions of interest was examined between MJ users and controls. There were no group differences between MJ users and controls on fMRI response during encoding, although single sample t-tests revealed that MJ users failed to activate the hippocampus. During recognition, MJ users showed less fMRI response than controls in right hippocampus (Cohen's d = 0.55), left hippocampus (Cohen's d = 0.67) and left IFG (Cohen's d = 0.61). Heavier MJ involvement was associated with lower fMRI response in left hippocampus and left IFG. This study provides evidence of MJ-related prefrontal and hippocampal dysfunction during recognition memory in college students. These findings may contribute to our previously identified decrements in academic performance in college MJ users and could have substantial implications for academic and occupational functioning. Copyright © 2018 Elsevier B.V. All rights reserved.

Fine tuning cellular recognition: The function of the leucine rich repeat (LRR) trans-membrane protein, LRT, in muscle targeting to tendon cells.

PubMed

Gilsohn, Eli; Volk, Talila

2010-01-01

The formation of complex tissues during embryonic development is often accompanied by directed cellular migration towards a target tissue. Specific mutual recognition between the migrating cell and its target tissue leads to the arrest of the cell migratory behavior and subsequent contact formation between the two interacting cell types. Recent studies implicated a novel family of surface proteins containing a trans-membrane domain and single leucine-rich repeat (LRR) domain in inter-cellular recognition and the arrest of cell migration. Here, we describe the involvement of a novel LRR surface protein, LRT, in targeting migrating muscles towards their corresponding tendon cells in the Drosophila embryo. LRT is specifically expressed by the target tendon cells and is essential for arresting the migratory behavior of the muscle cells. Additional studies in Drosophila S2 cultured cells suggest that LRT forms a protein complex with the Roundabout (Robo) receptor, essential for guiding muscles towards their tendon partners. Genetic analysis supports a model in which LRT performs its activity non-autonomously through its interaction with the Robo receptors expressed on the muscle surfaces. These results suggest a novel mechanism of intercellular recognition through interactions between LRR family members and Robo receptors.

The selectivity of protein-imprinted gels and its relation to protein properties: A computer simulation study.

PubMed

Yankelov, Rami; Yungerman, Irena; Srebnik, Simcha

2017-07-01

Polymer-based protein recognition systems have enormous potential within clinical and diagnostic fields due to their reusability, biocompatibility, ease of manufacturing, and potential specificity. Imprinted polymer matrices have been extensively studied and applied as a simple technique for creating artificial polymer-based recognition gels for a target molecule. Although this technique has been proven effective when targeting small molecules (such as drugs), imprinting of proteins have so far resulted in materials with limited selectivity due to the large molecular size of the protein and aqueous environment. Using coarse-grained molecular simulation, we investigate the relation between protein makeup, polymer properties, and the selectivity of imprinted gels. Nonspecific binding that results in poor selectivity is shown to be strongly dependent on surface chemistry of the template and competitor proteins as well as on polymer chemistry. Residence time distributions of proteins diffusing within the gels provide a transparent picture of the relation between polymer constitution, protein properties, and the nonspecific interactions with the imprinted gel. The pronounced effect of protein surface chemistry on imprinted gel specificity is demonstrated. Copyright © 2017 John Wiley & Sons, Ltd.

PHD Finger Recognition of Unmodified Histone H3R2 Links UHRF1 to Regulation of Euchromatic Gene Expression

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

E Rajakumara; Z Wang; H Ma

2011-12-31

Histone methylation occurs on both lysine and arginine residues, and its dynamic regulation plays a critical role in chromatin biology. Here we identify the UHRF1 PHD finger (PHD{sub UHRF1}), an important regulator of DNA CpG methylation, as a histone H3 unmodified arginine 2 (H3R2) recognition modality. This conclusion is based on binding studies and cocrystal structures of PHD{sub UHRF1} bound to histone H3 peptides, where the guanidinium group of unmodified R2 forms an extensive intermolecular hydrogen bond network, with methylation of H3R2, but not H3K4 or H3K9, disrupting complex formation. We have identified direct target genes of UHRF1 from microarraymore » and ChIP studies. Importantly, we show that UHRF1's ability to repress its direct target gene expression is dependent on PHD{sub UHRF1} binding to unmodified H3R2, thereby demonstrating the functional importance of this recognition event and supporting the potential for crosstalk between histone arginine methylation and UHRF1 function.« less

PHD Finger Recognition of Unmodified Histone H3R2 Links UHRF1 to Regulation of Euchromatic Gene Expression

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

Rajakumara, Eerappa; Wang, Zhentian; Ma, Honghui

2011-08-29

Histone methylation occurs on both lysine and arginine residues, and its dynamic regulation plays a critical role in chromatin biology. Here we identify the UHRF1 PHD finger (PHD{sub UHRF1}), an important regulator of DNA CpG methylation, as a histone H3 unmodified arginine 2 (H3R2) recognition modality. This conclusion is based on binding studies and cocrystal structures of PHD{sub UHRF1} bound to histone H3 peptides, where the guanidinium group of unmodified R2 forms an extensive intermolecular hydrogen bond network, with methylation of H3R2, but not H3K4 or H3K9, disrupting complex formation. We have identified direct target genes of UHRF1 from microarraymore » and ChIP studies. Importantly, we show that UHRF1's ability to repress its direct target gene expression is dependent on PHD{sub UHRF1} binding to unmodified H3R2, thereby demonstrating the functional importance of this recognition event and supporting the potential for crosstalk between histone arginine methylation and UHRF1 function.« less

Pattern-Recognition Algorithm for Locking Laser Frequency

NASA Technical Reports Server (NTRS)

Karayan, Vahag; Klipstein, William; Enzer, Daphna; Yates, Philip; Thompson, Robert; Wells, George

2006-01-01

A computer program serves as part of a feedback control system that locks the frequency of a laser to one of the spectral peaks of cesium atoms in an optical absorption cell. The system analyzes a saturation absorption spectrum to find a target peak and commands a laser-frequency-control circuit to minimize an error signal representing the difference between the laser frequency and the target peak. The program implements an algorithm consisting of the following steps: Acquire a saturation absorption signal while scanning the laser through the frequency range of interest. Condition the signal by use of convolution filtering. Detect peaks. Match the peaks in the signal to a pattern of known spectral peaks by use of a pattern-recognition algorithm. Add missing peaks. Tune the laser to the desired peak and thereafter lock onto this peak. Finding and locking onto the desired peak is a challenging problem, given that the saturation absorption signal includes noise and other spurious signal components; the problem is further complicated by nonlinearity and shifting of the voltage-to-frequency correspondence. The pattern-recognition algorithm, which is based on Hausdorff distance, is what enables the program to meet these challenges.

Age differences in accuracy and choosing in eyewitness identification and face recognition.

PubMed

Searcy, J H; Bartlett, J C; Memon, A

1999-05-01

Studies of aging and face recognition show age-related increases in false recognitions of new faces. To explore implications of this false alarm effect, we had young and senior adults perform (1) three eye-witness identification tasks, using both target present and target absent lineups, and (2) and old/new recognition task in which a study list of faces was followed by a test including old and new faces, along with conjunctions of old faces. Compared with the young, seniors had lower accuracy and higher choosing rates on the lineups, and they also falsely recognized more new faces on the recognition test. However, after screening for perceptual processing deficits, there was no age difference in false recognition of conjunctions, or in discriminating old faces from conjunctions. We conclude that the false alarm effect generalizes to lineup identification, but does not extend to conjunction faces. The findings are consistent with age-related deficits in recollection of context and relative age invariance in perceptual integrative processes underlying the experience of familiarity.

Improved detection sensitivity of γ-aminobutyric acid based on graphene oxide interface on an optical microfiber.

PubMed

Zhou, Jun; Huang, Yunyun; Chen, Chaoyan; Xiao, Aoxiang; Guo, Tuan; Guan, Bai-Ou

2018-05-11

Interfacing bio-recognition elements to optical materials is a longstanding challenge to manufacture sensitive biosensors and inexpensive diagnostic devices. In this work, a graphene oxide (GO) interface has been constructed between silica microfiber and bio-recognition elements to develop an improved γ-aminobutyric acid (GABA) sensing approach. The GO interface, which was located at the site with the strongest evanescent field on the microfiber surface, improved the detection sensitivity by providing a larger platform for more bio-recognition element immobilization, and amplifying surface refractive index change caused by combination between bio-recognition elements and target molecules. Owing to the interface improvement, the microfiber has a three times improved sensitivity of 1.03 nm/log M for GABA detection, and hence a lowest limit of detection of 2.91 × 10-18 M, which is 7 orders of magnitude higher than that without the GO interface. Moreover, the micrometer-sized footprint and non-radioactive nature enable easy implantation in human brains for in vivo applications.

Exploring Protein-Peptide Recognition Pathways Using a Supervised Molecular Dynamics Approach.

PubMed

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2017-04-04

Peptides have gained increased interest as therapeutic agents during recent years. The high specificity and relatively low toxicity of peptide drugs derive from their extremely tight binding to their targets. Indeed, understanding the molecular mechanism of protein-peptide recognition has important implications in the fields of biology, medicine, and pharmaceutical sciences. Even if crystallography and nuclear magnetic resonance are offering valuable atomic insights into the assembling of the protein-peptide complexes, the mechanism of their recognition and binding events remains largely unclear. In this work we report, for the first time, the use of a supervised molecular dynamics approach to explore the possible protein-peptide binding pathways within a timescale reduced up to three orders of magnitude compared with classical molecular dynamics. The better and faster understating of the protein-peptide recognition pathways could be very beneficial in enlarging the applicability of peptide-based drug design approaches in several biotechnological and pharmaceutical fields. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

NASA Astrophysics Data System (ADS)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-09-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 × 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver ( p < 0.05). Furthermore, the F-value, which was used as a scale for the difference in recognition rates, was highest in the average gray level, relatively high in the skewness and the entropy, and relatively low in the uniformity, the relative smoothness and the average contrast. The recognition rate for a fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Structures of the Signal Recognition Particle Receptor from the Archaeon Pyrococcus furiosus: Implications for the Targeting Step at the Membrane

PubMed Central

Egea, Pascal F.; Tsuruta, Hiro; de Leon, Gladys P.; Napetschnig, Johanna; Walter, Peter; Stroud, Robert M.

2008-01-01

In all organisms, a ribonucleoprotein called the signal recognition particle (SRP) and its receptor (SR) target nascent proteins from the ribosome to the translocon for secretion or membrane insertion. We present the first X-ray structures of an archeal FtsY, the receptor from the hyper-thermophile Pyrococcus furiosus (Pfu), in its free and GDP•magnesium-bound forms. The highly charged N-terminal domain of Pfu-FtsY is distinguished by a long N-terminal helix. The basic charges on the surface of this helix are likely to regulate interactions at the membrane. A peripheral GDP bound near a regulatory motif could indicate a site of interaction between the receptor and ribosomal or SRP RNAs. Small angle X-ray scattering and analytical ultracentrifugation indicate that the crystal structure of Pfu-FtsY correlates well with the average conformation in solution. Based on previous structures of two sub-complexes, we propose a model of the core of archeal and eukaryotic SRP•SR targeting complexes. PMID:18978942

The Relationship between Feelings-of-Knowing and Partial Knowledge for General Knowledge Questions

PubMed Central

Norman, Elisabeth; Blakstad, Oskar; Johnsen, Øivind; Martinsen, Stig K.; Price, Mark C.

2016-01-01

Feelings of knowing (FoK) are introspective self-report ratings of the felt likelihood that one will be able to recognize a currently unrecallable memory target. Previous studies have shown that FoKs are influenced by retrieved fragment knowledge related to the target, which is compatible with the accessibility hypothesis that FoK is partly based on currently activated partial knowledge about the memory target. However, previous results have been inconsistent as to whether or not FoKs are influenced by the accuracy of such information. In our study (N = 26), we used a recall-judge-recognize procedure where stimuli were general knowledge questions. The measure of partial knowledge was wider than those applied previously, and FoK was measured before rather than after partial knowledge. The accuracy of reported partial knowledge was positively related to subsequent recognition accuracy, and FoK only predicted recognition on trials where there was correct partial knowledge. Importantly, FoK was positively related to the amount of correct partial knowledge, but did not show a similar incremental relation with incorrect knowledge. PMID:27445950

Coordination of Word Recognition and Oculomotor Control During Reading: The Role of Implicit Lexical Decisions

PubMed Central

Choi, Wonil; Gordon, Peter C.

2013-01-01

The coordination of word-recognition and oculomotor processes during reading was evaluated in two eye-tracking experiments that examined how word skipping, where a word is not fixated during first-pass reading, is affected by the lexical status of a letter string in the parafovea and ease of recognizing that string. Ease of lexical recognition was manipulated through target-word frequency (Experiment 1) and through repetition priming between prime-target pairs embedded in a sentence (Experiment 2). Using the gaze-contingent boundary technique the target word appeared in the parafovea either with full preview or with transposed-letter (TL) preview. The TL preview strings were nonwords in Experiment 1 (e.g., bilnk created from the target blink), but were words in Experiment 2 (e.g., sacred created from the target scared). Experiment 1 showed greater skipping for high-frequency than low-frequency target words in the full preview condition but not in the TL preview (nonword) condition. Experiment 2 showed greater skipping for target words that repeated an earlier prime word than for those that did not, with this repetition priming occurring both with preview of the full target and with preview of the target’s TL neighbor word. However, time to progress from the word after the target was greater following skips of the TL preview word, whose meaning was anomalous in the sentence context, than following skips of the full preview word whose meaning fit sensibly into the sentence context. Together, the results support the idea that coordination between word-recognition and oculomotor processes occurs at the level of implicit lexical decisions. PMID:23106372

Chapter 17. Extension of endogenous primers as a tool to detect micro-RNA targets.

PubMed

Vatolin, Sergei; Weil, Robert J

2008-01-01

Mammalian cells express a large number of small, noncoding RNAs, including micro-RNAs (miRNAs), that can regulate both the level of a target mRNA and the protein produced by the target mRNA. Recognition of miRNA targets is a complicated process, as a single target mRNA may be regulated by several miRNAs. The potential for combinatorial miRNA-mediated regulation of miRNA targets complicates diagnostic and therapeutic applications of miRNAs. Despite significant progress in understanding the biology of miRNAs and advances in computational predictions of miRNA targets, methods that permit direct physical identification of miRNA-mRNA complexes in eukaryotic cells are still required. Several groups have utilized coimmunoprecipitation of RNA associated with a protein(s) that is part of the RNA silencing macromolecular complex. This chapter describes a detailed but straightforward strategy that identifies miRNA targets based on the assumption that small RNAs base paired with a complementary target mRNA can be used as a primer to synthesize cDNA that may be used for cloning, identification, and functional analysis.

Research on quantitative relationship between NIIRS and the probabilities of discrimination

NASA Astrophysics Data System (ADS)

Bai, Honggang

2011-08-01

There are a large number of electro-optical (EO) and infrared (IR) sensors used on military platforms including ground vehicle, low altitude air vehicle, high altitude air vehicle, and satellite systems. Ground vehicle and low-altitude air vehicle (rotary and fixed-wing aircraft) sensors typically use the probabilities of discrimination (detection, recognition, and identification) as design requirements and system performance indicators. High-altitude air vehicles and satellite sensors have traditionally used the National Imagery Interpretation Rating Scale (NIIRS) performance measures for guidance in design and measures of system performance. Recently, there has a large effort to make strategic sensor information available to tactical forces or make the information of targets acquisition can be used by strategic systems. In this paper, the two techniques about the probabilities of discrimination and NIIRS for sensor design are presented separately. For the typical infrared remote sensor design parameters, the function of the probability of recognition and NIIRS scale as the distance R is given to Standard NATO Target and M1Abrams two different size targets based on the algorithm of predicting the field performance and NIIRS. For Standard NATO Target, M1Abrams, F-15, and B-52 four different size targets, the conversion from NIIRS to the probabilities of discrimination are derived and calculated, and the similarities and differences between NIIRS and the probabilities of discrimination are analyzed based on the result of calculation. Comparisons with preliminary calculation results show that the conversion between NIIRS and the probabilities of discrimination is probable although more validation experiments are needed.

Cognitive Predictors of Spoken Word Recognition in Children With and Without Developmental Language Disorders.

PubMed

Evans, Julia L; Gillam, Ronald B; Montgomery, James W

2018-05-10

This study examined the influence of cognitive factors on spoken word recognition in children with developmental language disorder (DLD) and typically developing (TD) children. Participants included 234 children (aged 7;0-11;11 years;months), 117 with DLD and 117 TD children, propensity matched for age, gender, socioeconomic status, and maternal education. Children completed a series of standardized assessment measures, a forward gating task, a rapid automatic naming task, and a series of tasks designed to examine cognitive factors hypothesized to influence spoken word recognition including phonological working memory, updating, attention shifting, and interference inhibition. Spoken word recognition for both initial and final accept gate points did not differ for children with DLD and TD controls after controlling target word knowledge in both groups. The 2 groups also did not differ on measures of updating, attention switching, and interference inhibition. Despite the lack of difference on these measures, for children with DLD, attention shifting and interference inhibition were significant predictors of spoken word recognition, whereas updating and receptive vocabulary were significant predictors of speed of spoken word recognition for the children in the TD group. Contrary to expectations, after controlling for target word knowledge, spoken word recognition did not differ for children with DLD and TD controls; however, the cognitive processing factors that influenced children's ability to recognize the target word in a stream of speech differed qualitatively for children with and without DLDs.

Array based Discovery of Aptamer Pairs (Open Access Publisher’s Version)

DTIC Science & Technology

2014-12-11

Array-based Discovery of Aptamer Pairs Minseon Cho,†,‡ Seung Soo Oh,‡ Jeff Nie,§ Ron Stewart,§ Monte J. Radeke,⊥ Michael Eisenstein,†,‡ Peter J...bidentate” target recognition, with affinities greatly exceeding either monovalent component. DNA aptamers are especially well-suited for such...constructs, because they can be linked via standard synthesis techniques without requiring chemical conjugation. Unfortunately, aptamer pairs are difficult

Radar activities of the DFVLR Institute for Radio Frequency Technology

NASA Technical Reports Server (NTRS)

Keydel, W.

1983-01-01

Aerospace research and the respective applications microwave tasks with respect to remote sensing, position finding and communication are discussed. The radar activities are directed at point targets, area targets and volume targets; they center around signature research for earth and ocean remote sensing, target recognition, reconnaissance and camouflage and imaging and area observation radar techniques (SAR and SLAR). The radar activities cover a frequency range from 1 GHz up to 94 GHz. The radar program is oriented to four possible application levels: ground, air, shuttle orbits and satellite orbits. Ground based studies and measurements, airborne scatterometers and imaging radars, a space shuttle radar, the MRSE, and follow on experiments are considered.

Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems.

PubMed

Jiang, Feng; Liu, Biao; Lu, Jun; Li, Fangfei; Li, Defang; Liang, Chao; Dang, Lei; Liu, Jin; He, Bing; Badshah, Shaikh Atik; Lu, Cheng; He, Xiaojuan; Guo, Baosheng; Zhang, Xiao-Bing; Tan, Weihong; Lu, Aiping; Zhang, Ge

2015-10-09

Aptamers, which can be screened via systematic evolution of ligands by exponential enrichment (SELEX), are superior ligands for molecular recognition due to their high selectivity and affinity. The interest in the use of aptamers as ligands for targeted drug delivery has been increasing due to their unique advantages. Based on their different compositions and preparation methods, aptamer-functionalized targeted drug delivery systems can be divided into two main categories: aptamer-small molecule conjugated systems and aptamer-nanomaterial conjugated systems. In this review, we not only summarize recent progress in aptamer selection and the application of aptamers in these targeted drug delivery systems but also discuss the advantages, challenges and new perspectives associated with these delivery systems.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

Facelock: familiarity-based graphical authentication

PubMed Central

McLachlan, Jane L.; Renaud, Karen

2014-01-01

Authentication codes such as passwords and PIN numbers are widely used to control access to resources. One major drawback of these codes is that they are difficult to remember. Account holders are often faced with a choice between forgetting a code, which can be inconvenient, or writing it down, which compromises security. In two studies, we test a new knowledge-based authentication method that does not impose memory load on the user. Psychological research on face recognition has revealed an important distinction between familiar and unfamiliar face perception: When a face is familiar to the observer, it can be identified across a wide range of images. However, when the face is unfamiliar, generalisation across images is poor. This contrast can be used as the basis for a personalised ‘facelock’, in which authentication succeeds or fails based on image-invariant recognition of faces that are familiar to the account holder. In Study 1, account holders authenticated easily by detecting familiar targets among other faces (97.5% success rate), even after a one-year delay (86.1% success rate). Zero-acquaintance attackers were reduced to guessing (<1% success rate). Even personal attackers who knew the account holder well were rarely able to authenticate (6.6% success rate). In Study 2, we found that shoulder-surfing attacks by strangers could be defeated by presenting different photos of the same target faces in observed and attacked grids (1.9% success rate). Our findings suggest that the contrast between familiar and unfamiliar face recognition may be useful for developers of graphical authentication systems. PMID:25024913

Increased susceptibility to proactive interference in adults with dyslexia?

PubMed

Bogaerts, Louisa; Szmalec, Arnaud; Hachmann, Wibke M; Page, Mike P A; Woumans, Evy; Duyck, Wouter

2015-01-01

Recent findings show that people with dyslexia have an impairment in serial-order memory. Based on these findings, the present study aimed to test the hypothesis that people with dyslexia have difficulties dealing with proactive interference (PI) in recognition memory. A group of 25 adults with dyslexia and a group of matched controls were subjected to a 2-back recognition task, which required participants to indicate whether an item (mis)matched the item that had been presented 2 trials before. PI was elicited using lure trials in which the item matched the item in the 3-back position instead of the targeted 2-back position. Our results demonstrate that the introduction of lure trials affected 2-back recognition performance more severely in the dyslexic group than in the control group, suggesting greater difficulty in resisting PI in dyslexia.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes.

PubMed

Liu, Chuanjun; Wyszynski, Bartosz; Yatabe, Rui; Hayashi, Kenshi; Toko, Kiyoshi

2017-02-16

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes

PubMed Central

Liu, Chuanjun; Wyszynski, Bartosz; Yatabe, Rui; Hayashi, Kenshi; Toko, Kiyoshi

2017-01-01

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor. PMID:28212347

The effects of timbre on melody recognition are mediated by familiarity

NASA Astrophysics Data System (ADS)

McAuley, J. Devin; Ayala, Chris

2002-11-01

Two experiments examined the role of timbre in music recognition. In both experiments, participants rated the familiarity of a set of novel and well-known musical excerpts during a study phase and then were given a surprise old/new recognition test after a retention interval. The recognition test was comprised of the target melodies and an equal number of distractors; participants were instructed to respond yes to the targets and no to the distractors. In experiment 1, the timbre of the melodies was held constant throughout the study and then either stayed the same or switched to a different instrument sound during the test. In experiment 2, timbre varied randomly from trial to trial between the same two instruments used in experiment 1, yielding target melodies that were either mismatched or matched in their timbre. Switching timbre between study and test in experiment 1 was found to hurt the recognition of the novel melodies, but not the familiar melodies. The mediating effect of familiarity was eliminated in experiment 2 when timbre varied randomly from trial to trial rather than remaining constant. Possible reasons for the difference between studies will be discussed.

Large-Scale Chemical Similarity Networks for Target Profiling of Compounds Identified in Cell-Based Chemical Screens

PubMed Central

Lo, Yu-Chen; Senese, Silvia; Li, Chien-Ming; Hu, Qiyang; Huang, Yong; Damoiseaux, Robert; Torres, Jorge Z.

2015-01-01

Target identification is one of the most critical steps following cell-based phenotypic chemical screens aimed at identifying compounds with potential uses in cell biology and for developing novel disease therapies. Current in silico target identification methods, including chemical similarity database searches, are limited to single or sequential ligand analysis that have limited capabilities for accurate deconvolution of a large number of compounds with diverse chemical structures. Here, we present CSNAP (Chemical Similarity Network Analysis Pulldown), a new computational target identification method that utilizes chemical similarity networks for large-scale chemotype (consensus chemical pattern) recognition and drug target profiling. Our benchmark study showed that CSNAP can achieve an overall higher accuracy (>80%) of target prediction with respect to representative chemotypes in large (>200) compound sets, in comparison to the SEA approach (60–70%). Additionally, CSNAP is capable of integrating with biological knowledge-based databases (Uniprot, GO) and high-throughput biology platforms (proteomic, genetic, etc) for system-wise drug target validation. To demonstrate the utility of the CSNAP approach, we combined CSNAP's target prediction with experimental ligand evaluation to identify the major mitotic targets of hit compounds from a cell-based chemical screen and we highlight novel compounds targeting microtubules, an important cancer therapeutic target. The CSNAP method is freely available and can be accessed from the CSNAP web server (http://services.mbi.ucla.edu/CSNAP/). PMID:25826798

Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1998-01-01

The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest Citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1997-01-01

The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

Tree-structured sensor fusion architecture for distributed sensor networks

NASA Astrophysics Data System (ADS)

Iyengar, S. Sitharama; Kashyap, Rangasami L.; Madan, Rabinder N.; Thomas, Daryl D.

1990-10-01

An assessment of numerous activities in the field of multisensor target recognition reveals several trends and conditions which are cause for concern. .These concerns are analyzed in terms of their potential impact on the ultimate employment of automatic target recognition in military systems. Suggestions for additional investigation and guidance for current activities are presented with respect to some of the identified concerns.

Automatic integration of social information in emotion recognition.

PubMed

Mumenthaler, Christian; Sander, David

2015-04-01

This study investigated the automaticity of the influence of social inference on emotion recognition. Participants were asked to recognize dynamic facial expressions of emotion (fear or anger in Experiment 1 and blends of fear and surprise or of anger and disgust in Experiment 2) in a target face presented at the center of a screen while a subliminal contextual face appearing in the periphery expressed an emotion (fear or anger) or not (neutral) and either looked at the target face or not. Results of Experiment 1 revealed that recognition of the target emotion of fear was improved when a subliminal angry contextual face gazed toward-rather than away from-the fearful face. We replicated this effect in Experiment 2, in which facial expression blends of fear and surprise were more often and more rapidly categorized as expressing fear when the subliminal contextual face expressed anger and gazed toward-rather than away from-the target face. With the contextual face appearing for 30 ms in total, including only 10 ms of emotion expression, and being immediately masked, our data provide the first evidence that social influence on emotion recognition can occur automatically. (c) 2015 APA, all rights reserved).

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

[Representation of letter position in visual word recognition process].

PubMed

Makioka, S

1994-08-01

Two experiments investigated the representation of letter position in visual word recognition process. In Experiment 1, subjects (12 undergraduates and graduates) were asked to detect a target word in a briefly-presented probe. Probes consisted of two kanji words. The latters which formed targets (critical letters) were always contained in probes. (e.g. target: [symbol: see text] probe: [symbol: see text]) High false alarm rate was observed when critical letters occupied the same within-word relative position (left or right within the word) in the probe words as in the target word. In Experiment 2 (subject were ten undergraduates and graduates), spaces adjacent to probe words were replaced by randomly chosen hiragana letters (e.g. [symbol: see text]), because spaces are not used to separate words in regular Japanese sentences. In addition to the effect of within-word relative position as in Experiment 1, the effect of between-word relative position (left or right across the probe words) was observed. These results suggest that information about within-word relative position of a letter is used in word recognition process. The effect of within-word relative position was explained by a connectionist model of word recognition.

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

2013-04-01

To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

Suspicious activity recognition in infrared imagery using Hidden Conditional Random Fields for outdoor perimeter surveillance

NASA Astrophysics Data System (ADS)

Rogotis, Savvas; Ioannidis, Dimosthenis; Tzovaras, Dimitrios; Likothanassis, Spiros

2015-04-01

The aim of this work is to present a novel approach for automatic recognition of suspicious activities in outdoor perimeter surveillance systems based on infrared video processing. Through the combination of size, speed and appearance based features, like the Center-Symmetric Local Binary Patterns, short-term actions are identified and serve as input, along with user location, for modeling target activities using the theory of Hidden Conditional Random Fields. HCRFs are used to directly link a set of observations to the most appropriate activity label and as such to discriminate high risk activities (e.g. trespassing) from zero risk activities (e.g loitering outside the perimeter). Experimental results demonstrate the effectiveness of our approach in identifying suspicious activities for video surveillance systems.

Rapid extraction of gist from visual text and its influence on word recognition.

PubMed

Asano, Michiko; Yokosawa, Kazuhiko

2011-01-01

Two experiments explored rapid extraction of gist from a visual text and its influence on word recognition. In both, a short text (sentence) containing a target word was presented for 200 ms and was followed by a target recognition task. Results showed that participants recognized contextually anomalous word targets less frequently than contextually consistent counterparts (Experiment 1). This context effect was obtained when sentences contained the same semantic content but with disrupted syntactic structure (Experiment 2). Results demonstrate that words in a briefly presented visual sentence are processed in parallel and that rapid extraction of sentence gist relies on a primitive representation of sentence context (termed protocontext) that is semantically activated by the simultaneous presentation of multiple words (i.e., a sentence) before syntactic processing.

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

PubMed Central

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

2011-01-01

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

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

Event-Related Potentials Indicate Different Processes to Mediate Categorical and Associative Priming in Person Recognition

ERIC Educational Resources Information Center

Wiese, Holger; Schweinberger, Stefan R.

2008-01-01

Whether representations of people are stored in associative networks based on co-occurrence or are stored in terms of more abstract semantic categories is a controversial question. In the present study, participants performed fame decisions to unfamiliar or famous target faces (Experiment 1) or names (Experiment 2), which were primed, either by…

Integrating visual learning within a model-based ATR system

NASA Astrophysics Data System (ADS)

Carlotto, Mark; Nebrich, Mark

2017-05-01

Automatic target recognition (ATR) systems, like human photo-interpreters, rely on a variety of visual information for detecting, classifying, and identifying manmade objects in aerial imagery. We describe the integration of a visual learning component into the Image Data Conditioner (IDC) for target/clutter and other visual classification tasks. The component is based on an implementation of a model of the visual cortex developed by Serre, Wolf, and Poggio. Visual learning in an ATR context requires the ability to recognize objects independent of location, scale, and rotation. Our method uses IDC to extract, rotate, and scale image chips at candidate target locations. A bootstrap learning method effectively extends the operation of the classifier beyond the training set and provides a measure of confidence. We show how the classifier can be used to learn other features that are difficult to compute from imagery such as target direction, and to assess the performance of the visual learning process itself.

Stability of miRNA 5′terminal and seed regions is correlated with experimentally observed miRNA-mediated silencing efficacy

PubMed Central

Hibio, Naoki; Hino, Kimihiro; Shimizu, Eigo; Nagata, Yoshiro; Ui-Tei, Kumiko

2012-01-01

MicroRNAs (miRNAs) are key regulators of sequence-specific gene silencing. However, crucial factors that determine the efficacy of miRNA-mediated target gene silencing are poorly understood. Here we mathematized base-pairing stability and showed that miRNAs with an unstable 5′ terminal duplex and stable seed-target duplex exhibit strong silencing activity. The results are consistent with the previous findings that an RNA strand with unstable 5′ terminal in miRNA duplex easily loads onto the RNA-induced silencing complex (RISC), and miRNA recognizes target mRNAs with seed-complementary sequences to direct posttranscriptional repression. Our results suggested that both the unwinding and target recognition processes of miRNAs could be proficiently controlled by the thermodynamics of base-pairing in protein-free condition. Interestingly, such thermodynamic parameters might be evolutionarily well adapted to the body temperatures of various species. PMID:23251782

Biosensors based on DNA-Functionalized Graphene

NASA Astrophysics Data System (ADS)

Vishnubhotla, Ramya; Ping, Jinglei; Vrudhula, Amey; Johnson, A. T. Charlie

Since its discovery, graphene has been used for sensing applications due to its outstanding electrical properties and biocompatibility. Here, we demonstrate the capabilities of field effect transistors (FETs) based on CVD-grown graphene functionalized with commercially obtained DNA oligomers and aptamers for detection of various biomolecular targets (e.g., complementary DNA and small molecule drug targets). Graphene FETs were created with a scalable photolithography process that produces arrays consisting of 50-100 FETs with a layout suitable for multiplexed detection of four molecular targets. FETs were characterized via AFM to confirm the presence of the aptamer. From the measured electrical characteristics, it was determined that binding of molecular targets by the DNA chemical recognition element led to a reproducible, concentration-dependent shift in the Dirac voltage. This biosensor class is potentially suitable for applications in drug detection. This work is funded by NIH through the Center for AIDS Research at the University of Pennsylvania.

Thermodynamic basis for engineering high-affinity, high-specificity binding-induced DNA clamp nanoswitches.

PubMed

Idili, Andrea; Plaxco, Kevin W; Vallée-Bélisle, Alexis; Ricci, Francesco

2013-12-23

Naturally occurring chemoreceptors almost invariably employ structure-switching mechanisms, an observation that has inspired the use of biomolecular switches in a wide range of artificial technologies in the areas of diagnostics, imaging, and synthetic biology. In one mechanism for generating such behavior, clamp-based switching, binding occurs via the clamplike embrace of two recognition elements onto a single target molecule. In addition to coupling recognition with a large conformational change, this mechanism offers a second advantage: it improves both affinity and specificity simultaneously. To explore the physics of such switches we have dissected here the thermodynamics of a clamp-switch that recognizes a target DNA sequence through both Watson-Crick base pairing and triplex-forming Hoogsteen interactions. When compared to the equivalent linear DNA probe (which relies solely on Watson-Crick interactions), the extra Hoogsteen interactions in the DNA clamp-switch increase the probe's affinity for its target by ∼0.29 ± 0.02 kcal/mol/base. The Hoogsteen interactions of the clamp-switch likewise provide an additional specificity check that increases the discrimination efficiency toward a single-base mismatch by 1.2 ± 0.2 kcal/mol. This, in turn, leads to a 10-fold improvement in the width of the "specificity window" of this probe relative to that of the equivalent linear probe. Given these attributes, clamp-switches should be of utility not only for sensing applications but also, in the specific field of DNA nanotechnology, for applications calling for a better control over the building of nanostructures and nanomachines.

An innovative pre-targeting strategy for tumor cell specific imaging and therapy.

PubMed

Qin, Si-Yong; Peng, Meng-Yun; Rong, Lei; Jia, Hui-Zhen; Chen, Si; Cheng, Si-Xue; Feng, Jun; Zhang, Xian-Zheng

2015-09-21

A programmed pre-targeting system for tumor cell imaging and targeting therapy was established based on the "biotin-avidin" interaction. In this programmed functional system, transferrin-biotin can be actively captured by tumor cells with the overexpression of transferrin receptors, thus achieving the pre-targeting modality. Depending upon avidin-biotin recognition, the attachment of multivalent FITC-avidin to biotinylated tumor cells not only offered the rapid fluorescence labelling, but also endowed the pre-targeted cells with targeting sites for the specifically designed biotinylated peptide nano-drug. Owing to the successful pre-targeting, tumorous HepG2 and HeLa cells were effectively distinguished from the normal 3T3 cells via fluorescence imaging. In addition, the self-assembled peptide nano-drug resulted in enhanced cell apoptosis in the observed HepG2 cells. The tumor cell specific pre-targeting strategy is applicable for a variety of different imaging and therapeutic agents for tumor treatments.

Automated Target Acquisition, Recognition and Tracking (ATTRACT). Phase 1

NASA Technical Reports Server (NTRS)

Abdallah, Mahmoud A.

1995-01-01

The primary objective of phase 1 of this research project is to conduct multidisciplinary research that will contribute to fundamental scientific knowledge in several of the USAF critical technology areas. Specifically, neural networks, signal processing techniques, and electro-optic capabilities are utilized to solve problems associated with automated target acquisition, recognition, and tracking. To accomplish the stated objective, several tasks have been identified and were executed.

Recognition of familiar people with a mobile cloud architecture for Alzheimer patients.

PubMed

Fardoun, Habib M; Mashat, Abdullah A; Ramirez Castillo, Jaime

2017-02-01

This article aims to the evaluation of a prototypal assistive technology for Alzheimer's disease (AD) patients that helps them to remember personal details of familiar people they meet in their daily lives. An architecture is proposed for a personal information system powered by face recognition, where the main AD patient's interaction is performed in a smart watch device and the face recognition is carried out on the Cloud. A prototype was developed to perform some tests in a real-life scenario. The prototype showed correct results as a personal information system based on face recognition. However, usability flaws were identified in the interaction with the smart watch. Our architecture showed correct performance and we realized that it could be introduced in other fields, apart from assistive technology. However, when being targeted to patients with dementia some usability problems appeared, such as difficulties to read information in a small screen or take a proper photo. These problems should be addressed in further research. Implications for Rehabilitation This article presents a prototypal assistive technology for Alzheimer's disease (AD) patients. It targets AD patients to recognize their familiars, especially in medium-advanced stages of the disease. Analysing pictures taken by a smart watch, which the patient carries, the person in front is recognized and information about him is sent to the watch. This technology enables patients to have all the information of any close person, as a remainder, easing their daily lives, improving their self-esteem and stimulating the patient with novel technology.

Target recognition of ladar range images using slice image: comparison of four improved algorithms

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

Construction of proteins with molecular recognition capabilities using α3β3 de novo protein scaffolds.

PubMed

Okura, Hiromichi; Mihara, Hisakazu; Takahashi, Tsuyoshi

2013-10-01

The molecular recognition ability of proteins is essential in biological systems, and therefore a considerable amount of effort has been devoted to constructing desired target-binding proteins using a variety of naturally occurring proteins as scaffolds. However, since generating a binding site in a native protein can often affect its structural properties, highly stable de novo protein scaffolds may be more amenable than the native proteins. We previously reported the generation of de novo proteins comprising three α-helices and three β-strands (α3β3) from a genetic library coding simplified amino acid sets. Two α3β3 de novo proteins, vTAJ13 and vTAJ36, fold into a native-like stable and molten globule-like structures, respectively, even though the proteins have similar amino acid compositions. Here, we attempted to create binding sites for the vTAJ13 and vTAJ36 proteins to prove the utility of de novo designed artificial proteins as a molecular recognition tool. Randomization of six amino acids at two linker sites of vTAJ13 and vTAJ36 followed by biopanning generated binding proteins that recognize the target molecules, fluorescein and green fluorescent protein, with affinities of 10(-7)-10(-8) M. Of note, the selected proteins from the vTAJ13-based library tended to recognize the target molecules with high specificity, probably due to the native-like stable structure of vTAJ13. Our studies provide an example of the potential of de novo protein scaffolds, which are composed of a simplified amino acid set, to recognize a variety of target compounds.

Voice gender and the segregation of competing talkers: Perceptual learning in cochlear implant simulations

PubMed Central

Sullivan, Jessica R.; Assmann, Peter F.; Hossain, Shaikat; Schafer, Erin C.

2017-01-01

Two experiments explored the role of differences in voice gender in the recognition of speech masked by a competing talker in cochlear implant simulations. Experiment 1 confirmed that listeners with normal hearing receive little benefit from differences in voice gender between a target and masker sentence in four- and eight-channel simulations, consistent with previous findings that cochlear implants deliver an impoverished representation of the cues for voice gender. However, gender differences led to small but significant improvements in word recognition with 16 and 32 channels. Experiment 2 assessed the benefits of perceptual training on the use of voice gender cues in an eight-channel simulation. Listeners were assigned to one of four groups: (1) word recognition training with target and masker differing in gender; (2) word recognition training with same-gender target and masker; (3) gender recognition training; or (4) control with no training. Significant improvements in word recognition were observed from pre- to post-test sessions for all three training groups compared to the control group. These improvements were maintained at the late session (one week following the last training session) for all three groups. There was an overall improvement in masked word recognition performance provided by gender mismatch following training, but the amount of benefit did not differ as a function of the type of training. The training effects observed here are consistent with a form of rapid perceptual learning that contributes to the segregation of competing voices but does not specifically enhance the benefits provided by voice gender cues. PMID:28372046

Familiarity facilitates feature-based face processing.

PubMed

Visconti di Oleggio Castello, Matteo; Wheeler, Kelsey G; Cipolli, Carlo; Gobbini, M Ida

2017-01-01

Recognition of personally familiar faces is remarkably efficient, effortless and robust. We asked if feature-based face processing facilitates detection of familiar faces by testing the effect of face inversion on a visual search task for familiar and unfamiliar faces. Because face inversion disrupts configural and holistic face processing, we hypothesized that inversion would diminish the familiarity advantage to the extent that it is mediated by such processing. Subjects detected personally familiar and stranger target faces in arrays of two, four, or six face images. Subjects showed significant facilitation of personally familiar face detection for both upright and inverted faces. The effect of familiarity on target absent trials, which involved only rejection of unfamiliar face distractors, suggests that familiarity facilitates rejection of unfamiliar distractors as well as detection of familiar targets. The preserved familiarity effect for inverted faces suggests that facilitation of face detection afforded by familiarity reflects mostly feature-based processes.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Facial expression recognition under partial occlusion based on fusion of global and local features

NASA Astrophysics Data System (ADS)

Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji

2018-04-01

Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.

Virtual reality method to analyze visual recognition in mice.

PubMed

Young, Brent Kevin; Brennan, Jayden Nicole; Wang, Ping; Tian, Ning

2018-01-01

Behavioral tests have been extensively used to measure the visual function of mice. To determine how precisely mice perceive certain visual cues, it is necessary to have a quantifiable measurement of their behavioral responses. Recently, virtual reality tests have been utilized for a variety of purposes, from analyzing hippocampal cell functionality to identifying visual acuity. Despite the widespread use of these tests, the training requirement for the recognition of a variety of different visual targets, and the performance of the behavioral tests has not been thoroughly characterized. We have developed a virtual reality behavior testing approach that can essay a variety of different aspects of visual perception, including color/luminance and motion detection. When tested for the ability to detect a color/luminance target or a moving target, mice were able to discern the designated target after 9 days of continuous training. However, the quality of their performance is significantly affected by the complexity of the visual target, and their ability to navigate on a spherical treadmill. Importantly, mice retained memory of their visual recognition for at least three weeks after the end of their behavioral training.

Programmable RNA Cleavage and Recognition by a Natural CRISPR-Cas9 System from Neisseria meningitidis.

PubMed

Rousseau, Beth A; Hou, Zhonggang; Gramelspacher, Max J; Zhang, Yan

2018-03-01

The microbial CRISPR systems enable adaptive defense against mobile elements and also provide formidable tools for genome engineering. The Cas9 proteins are type II CRISPR-associated, RNA-guided DNA endonucleases that identify double-stranded DNA targets by sequence complementarity and protospacer adjacent motif (PAM) recognition. Here we report that the type II-C CRISPR-Cas9 from Neisseria meningitidis (Nme) is capable of programmable, RNA-guided, site-specific cleavage and recognition of single-stranded RNA targets and that this ribonuclease activity is independent of the PAM sequence. We define the mechanistic feature and specificity constraint for RNA cleavage by NmeCas9 and also show that nuclease null dNmeCas9 binds to RNA target complementary to CRISPR RNA. Finally, we demonstrate that NmeCas9-catalyzed RNA cleavage can be blocked by three families of type II-C anti-CRISPR proteins. These results fundamentally expand the targeting capacities of CRISPR-Cas9 and highlight the potential utility of NmeCas9 as a single platform to target both RNA and DNA. Copyright © 2018 Elsevier Inc. All rights reserved.

Benchmarking of TALE- and CRISPR/dCas9-Based Transcriptional Regulators in Mammalian Cells for the Construction of Synthetic Genetic Circuits.

PubMed

Lebar, Tina; Jerala, Roman

2016-10-21

Transcriptional activator-like effector (TALE)- and CRISPR/Cas9-based designable recognition domains represent a technological breakthrough not only for genome editing but also for building designed genetic circuits. Both platforms are able to target rarely occurring DNA segments, even within complex genomes. TALE and dCas9 domains, genetically fused to transcriptional regulatory domains, can be used for the construction of engineered logic circuits. Here we benchmarked the performance of the two platforms, targeting the same DNA sequences, to compare their advantages for the construction of designed circuits in mammalian cells. Optimal targeting strands for repression and activation of dCas9-based designed transcription factors were identified; both platforms exhibited good orthogonality and were used to construct functionally complete NOR gates. Although the CRISPR/dCas9 system is clearly easier to construct, TALE-based activators were significantly stronger, and the TALE-based platform performed better, especially for the construction of layered circuits.

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

2015-01-01

The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

Influence of Emotional Facial Expressions on 3-5-Year-Olds' Face Recognition

ERIC Educational Resources Information Center

Freitag, Claudia; Schwarzer, Gudrun

2011-01-01

Three experiments examined 3- and 5-year-olds' recognition of faces in constant and varied emotional expressions. Children were asked to identify repeatedly presented target faces, distinguishing them from distractor faces, during an immediate recognition test and during delayed assessments after 10 min and one week. Emotional facial expression…

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Key features for ATA / ATR database design in missile systems

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2017-05-01

Automatic target acquisition (ATA) and automatic target recognition (ATR) are two vital tasks for missile systems, and having a robust detection and recognition algorithm is crucial for overall system performance. In order to have a robust target detection and recognition algorithm, an extensive image database is required. Automatic target recognition algorithms use the database of images in training and testing steps of algorithm. This directly affects the recognition performance, since the training accuracy is driven by the quality of the image database. In addition, the performance of an automatic target detection algorithm can be measured effectively by using an image database. There are two main ways for designing an ATA / ATR database. The first and easy way is by using a scene generator. A scene generator can model the objects by considering its material information, the atmospheric conditions, detector type and the territory. Designing image database by using a scene generator is inexpensive and it allows creating many different scenarios quickly and easily. However the major drawback of using a scene generator is its low fidelity, since the images are created virtually. The second and difficult way is designing it using real-world images. Designing image database with real-world images is a lot more costly and time consuming; however it offers high fidelity, which is critical for missile algorithms. In this paper, critical concepts in ATA / ATR database design with real-world images are discussed. Each concept is discussed in the perspective of ATA and ATR separately. For the implementation stage, some possible solutions and trade-offs for creating the database are proposed, and all proposed approaches are compared to each other with regards to their pros and cons.

Space infrared telescope pointing control system. Automated star pattern recognition

NASA Technical Reports Server (NTRS)

Powell, J. D.; Vanbezooijen, R. W. H.

1985-01-01

The Space Infrared Telescope Facility (SIRTF) is a free flying spacecraft carrying a 1 meter class cryogenically cooled infrared telescope nearly three oders of magnitude most sensitive than the current generation of infrared telescopes. Three automatic target acquisition methods will be presented that are based on the use of an imaging star tracker. The methods are distinguished by the number of guidestars that are required per target, the amount of computational capability necessary, and the time required for the complete acquisition process. Each method is described in detail.

The structure of semantic person memory: evidence from semantic priming in person recognition.

PubMed

Wiese, Holger

2011-11-01

This paper reviews research on the structure of semantic person memory as examined with semantic priming. In this experimental paradigm, a familiarity decision on a target face or written name is usually faster when it is preceded by a related as compared to an unrelated prime. This effect has been shown to be relatively short lived and susceptible to interfering items. Moreover, semantic priming can cross stimulus domains, such that a written name can prime a target face and vice versa. However, it remains controversial whether representations of people are stored in associative networks based on co-occurrence, or in more abstract semantic categories. In line with prominent cognitive models of face recognition, which explain semantic priming by shared semantic information between prime and target, recent research demonstrated that priming could be obtained from purely categorically related, non-associated prime/target pairs. Although strategic processes, such as expectancy and retrospective matching likely contribute, there is also evidence for a non-strategic contribution to priming, presumably related to spreading activation. Finally, a semantic priming effect has been demonstrated in the N400 event-related potential (ERP) component, which may reflect facilitated access to semantic information. It is concluded that categorical relatedness is one organizing principle of semantic person memory. ©2011 The British Psychological Society.

The Effects of Lexical Pitch Accent on Infant Word Recognition in Japanese

PubMed Central

Ota, Mitsuhiko; Yamane, Naoto; Mazuka, Reiko

2018-01-01

Learners of lexical tone languages (e.g., Mandarin) develop sensitivity to tonal contrasts and recognize pitch-matched, but not pitch-mismatched, familiar words by 11 months. Learners of non-tone languages (e.g., English) also show a tendency to treat pitch patterns as lexically contrastive up to about 18 months. In this study, we examined if this early-developing capacity to lexically encode pitch variations enables infants to acquire a pitch accent system, in which pitch-based lexical contrasts are obscured by the interaction of lexical and non-lexical (i.e., intonational) features. Eighteen 17-month-olds learning Tokyo Japanese were tested on their recognition of familiar words with the expected pitch or the lexically opposite pitch pattern. In early trials, infants were faster in shifting their eyegaze from the distractor object to the target object than in shifting from the target to distractor in the pitch-matched condition. In later trials, however, infants showed faster distractor-to-target than target-to-distractor shifts in both the pitch-matched and pitch-mismatched conditions. We interpret these results to mean that, in a pitch-accent system, the ability to use pitch variations to recognize words is still in a nascent state at 17 months. PMID:29375452

Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

NASA Astrophysics Data System (ADS)

El-Saba, A. M.; Alam, M. S.; Surpanani, A.

2006-05-01

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE PAGES

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

2014-10-23

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

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

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

CRISPR-Cas9 Structures and Mechanisms.

PubMed

Jiang, Fuguo; Doudna, Jennifer A

2017-05-22

Many bacterial clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated (Cas) systems employ the dual RNA-guided DNA endonuclease Cas9 to defend against invading phages and conjugative plasmids by introducing site-specific double-stranded breaks in target DNA. Target recognition strictly requires the presence of a short protospacer adjacent motif (PAM) flanking the target site, and subsequent R-loop formation and strand scission are driven by complementary base pairing between the guide RNA and target DNA, Cas9-DNA interactions, and associated conformational changes. The use of CRISPR-Cas9 as an RNA-programmable DNA targeting and editing platform is simplified by a synthetic single-guide RNA (sgRNA) mimicking the natural dual trans-activating CRISPR RNA (tracrRNA)-CRISPR RNA (crRNA) structure. This review aims to provide an in-depth mechanistic and structural understanding of Cas9-mediated RNA-guided DNA targeting and cleavage. Molecular insights from biochemical and structural studies provide a framework for rational engineering aimed at altering catalytic function, guide RNA specificity, and PAM requirements and reducing off-target activity for the development of Cas9-based therapies against genetic diseases.

Integrated approach for automatic target recognition using a network of collaborative sensors.

PubMed

Mahalanobis, Abhijit; Van Nevel, Alan

2006-10-01

We introduce what is believed to be a novel concept by which several sensors with automatic target recognition (ATR) capability collaborate to recognize objects. Such an approach would be suitable for netted systems in which the sensors and platforms can coordinate to optimize end-to-end performance. We use correlation filtering techniques to facilitate the development of the concept, although other ATR algorithms may be easily substituted. Essentially, a self-configuring geometry of netted platforms is proposed that positions the sensors optimally with respect to each other, and takes into account the interactions among the sensor, the recognition algorithms, and the classes of the objects to be recognized. We show how such a paradigm optimizes overall performance, and illustrate the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing position as a sensor parameter.

Cultural differences in gaze and emotion recognition: Americans contrast more than Chinese.

PubMed

Stanley, Jennifer Tehan; Zhang, Xin; Fung, Helene H; Isaacowitz, Derek M

2013-02-01

We investigated the influence of contextual expressions on emotion recognition accuracy and gaze patterns among American and Chinese participants. We expected Chinese participants would be more influenced by, and attend more to, contextual information than Americans. Consistent with our hypothesis, Americans were more accurate than Chinese participants at recognizing emotions embedded in the context of other emotional expressions. Eye-tracking data suggest that, for some emotions, Americans attended more to the target faces, and they made more gaze transitions to the target face than Chinese. For all emotions except anger and disgust, Americans appeared to use more of a contrasting strategy where each face was individually contrasted with the target face, compared with Chinese who used less of a contrasting strategy. Both cultures were influenced by contextual information, although the benefit of contextual information depended upon the perceptual dissimilarity of the contextual emotions to the target emotion and the gaze pattern employed during the recognition task. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Self-Assembled Smart Nanocarriers for Targeted Drug Delivery.

PubMed

Cui, Wei; Li, Junbai; Decher, Gero

2016-02-10

Nanostructured drug-carrier systems promise numerous benefits for drug delivery. They can be engineered to precisely control drug-release rates or to target specific sites within the body with a specific amount of therapeutic agent. However, to achieve the best therapeutic effects, the systems should be designed for carrying the optimum amount of a drug to the desired target where it should be released at the optimum rate for a specified time. Despite numerous attempts, fulfilling all of these requirements in a synergistic way remains a huge challenge. The trend in drug delivery is consequently directed toward integrated multifunctional carrier systems, providing selective recognition in combination with sustained or triggered release. Capsules as vesicular systems enable drugs to be confined for controlled release. Furthermore, carriers modified with recognition groups can enhance the capability of encapsulated drug efficacy. Here, recent advances are reviewed regarding designing and preparing assembled capsules with targeting ligands or size controllable for selective recognition in drug delivery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cultural Differences in Gaze and Emotion Recognition: Americans Contrast More than Chinese

PubMed Central

Tehan Stanley, Jennifer; Zhang, Xin; Fung, Helene H.; Isaacowitz, Derek M.

2014-01-01

We investigated the influence of contextual expressions on emotion recognition accuracy and gaze patterns among American and Chinese participants. We expected Chinese participants would be more influenced by, and attend more to, contextual information than Americans. Consistent with our hypothesis, Americans were more accurate than Chinese participants at recognizing emotions embedded in the context of other emotional expressions. Eye tracking data suggest that, for some emotions, Americans attended more to the target faces and made more gaze transitions to the target face than Chinese. For all emotions except anger and disgust, Americans appeared to use more of a contrasting strategy where each face was individually contrasted with the target face, compared with Chinese who used less of a contrasting strategy. Both cultures were influenced by contextual information, although the benefit of contextual information depended upon the perceptual dissimilarity of the contextual emotions to the target emotion and the gaze pattern employed during the recognition task. PMID:22889414

Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems

PubMed Central

Jiang, Feng; Liu, Biao; Lu, Jun; Li, Fangfei; Li, Defang; Liang, Chao; Dang, Lei; Liu, Jin; He, Bing; Atik Badshah, Shaikh; Lu, Cheng; He, Xiaojuan; Guo, Baosheng; Zhang, Xiao-Bing; Tan, Weihong; Lu, Aiping; Zhang, Ge

2015-01-01

Aptamers, which can be screened via systematic evolution of ligands by exponential enrichment (SELEX), are superior ligands for molecular recognition due to their high selectivity and affinity. The interest in the use of aptamers as ligands for targeted drug delivery has been increasing due to their unique advantages. Based on their different compositions and preparation methods, aptamer-functionalized targeted drug delivery systems can be divided into two main categories: aptamer-small molecule conjugated systems and aptamer-nanomaterial conjugated systems. In this review, we not only summarize recent progress in aptamer selection and the application of aptamers in these targeted drug delivery systems but also discuss the advantages, challenges and new perspectives associated with these delivery systems. PMID:26473828

Lexical association and false memory for words in two cultures.

PubMed

Lee, Yuh-shiow; Chiang, Wen-Chi; Hung, Hsu-Ching

2008-01-01

This study examined the relationship between language experience and false memory produced by the DRM paradigm. The word lists used in Stadler, et al. (Memory & Cognition, 27, 494-500, 1999) were first translated into Chinese. False recall and false recognition for critical non-presented targets were then tested on a group of Chinese users. The average co-occurrence rate of the list word and the critical word was calculated based on two large Chinese corpuses. List-level analyses revealed that the correlation between the American and Taiwanese participants was significant only in false recognition. More importantly, the co-occurrence rate was significantly correlated with false recall and recognition of Taiwanese participants, and not of American participants. In addition, the backward association strength based on Nelson et al. (The University of South Florida word association, rhyme and word fragment norms, 1999) was significantly correlated with false recall of American participants and not of Taiwanese participants. Results are discussed in terms of the relationship between language experiences and lexical association in creating false memory for word lists.

An algorithm for automatic target recognition using passive radar and an EKF for estimating aircraft orientation

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.

2005-07-01

Rather than emitting pulses, passive radar systems rely on "illuminators of opportunity," such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, further scaling the RCS. A Rician likelihood model compares the scaled RCS of the illuminated aircraft with those of the potential targets. To improve the robustness of the result, the algorithm jointly optimizes over feasible orientation profiles and target types via dynamic programming.

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

CRISPRTarget

PubMed Central

Biswas, Ambarish; Gagnon, Joshua N.; Brouns, Stan J.J.; Fineran, Peter C.; Brown, Chris M.

2013-01-01

The bacterial and archaeal CRISPR/Cas adaptive immune system targets specific protospacer nucleotide sequences in invading organisms. This requires base pairing between processed CRISPR RNA and the target protospacer. For type I and II CRISPR/Cas systems, protospacer adjacent motifs (PAM) are essential for target recognition, and for type III, mismatches in the flanking sequences are important in the antiviral response. In this study, we examine the properties of each class of CRISPR. We use this information to provide a tool (CRISPRTarget) that predicts the most likely targets of CRISPR RNAs (http://bioanalysis.otago.ac.nz/CRISPRTarget). This can be used to discover targets in newly sequenced genomic or metagenomic data. To test its utility, we discover features and targets of well-characterized Streptococcus thermophilus and Sulfolobus solfataricus type II and III CRISPR/Cas systems. Finally, in Pectobacterium species, we identify new CRISPR targets and propose a model of temperate phage exposure and subsequent inhibition by the type I CRISPR/Cas systems. PMID:23492433

Spoken Word Recognition in Toddlers Who Use Cochlear Implants

PubMed Central

Grieco-Calub, Tina M.; Saffran, Jenny R.; Litovsky, Ruth Y.

2010-01-01

Purpose The purpose of this study was to assess the time course of spoken word recognition in 2-year-old children who use cochlear implants (CIs) in quiet and in the presence of speech competitors. Method Children who use CIs and age-matched peers with normal acoustic hearing listened to familiar auditory labels, in quiet or in the presence of speech competitors, while their eye movements to target objects were digitally recorded. Word recognition performance was quantified by measuring each child’s reaction time (i.e., the latency between the spoken auditory label and the first look at the target object) and accuracy (i.e., the amount of time that children looked at target objects within 367 ms to 2,000 ms after the label onset). Results Children with CIs were less accurate and took longer to fixate target objects than did age-matched children without hearing loss. Both groups of children showed reduced performance in the presence of the speech competitors, although many children continued to recognize labels at above-chance levels. Conclusion The results suggest that the unique auditory experience of young CI users slows the time course of spoken word recognition abilities. In addition, real-world listening environments may slow language processing in young language learners, regardless of their hearing status. PMID:19951921

Correlations between psychometric schizotypy, scan path length, fixations on the eyes and face recognition.

PubMed

Hills, Peter J; Eaton, Elizabeth; Pake, J Michael

2016-01-01

Psychometric schizotypy in the general population correlates negatively with face recognition accuracy, potentially due to deficits in inhibition, social withdrawal, or eye-movement abnormalities. We report an eye-tracking face recognition study in which participants were required to match one of two faces (target and distractor) to a cue face presented immediately before. All faces could be presented with or without paraphernalia (e.g., hats, glasses, facial hair). Results showed that paraphernalia distracted participants, and that the most distracting condition was when the cue and the distractor face had paraphernalia but the target face did not, while there was no correlation between distractibility and participants' scores on the Schizotypal Personality Questionnaire (SPQ). Schizotypy was negatively correlated with proportion of time fixating on the eyes and positively correlated with not fixating on a feature. It was negatively correlated with scan path length and this variable correlated with face recognition accuracy. These results are interpreted as schizotypal traits being associated with a restricted scan path leading to face recognition deficits.

Must analysis of meaning follow analysis of form? A time course analysis

PubMed Central

Feldman, Laurie B.; Milin, Petar; Cho, Kit W.; Moscoso del Prado Martín, Fermín; O’Connor, Patrick A.

2015-01-01

Many models of word recognition assume that processing proceeds sequentially from analysis of form to analysis of meaning. In the context of morphological processing, this implies that morphemes are processed as units of form prior to any influence of their meanings. Some interpret the apparent absence of differences in recognition latencies to targets (SNEAK) in form and semantically similar (sneaky-SNEAK) and in form similar and semantically dissimilar (sneaker-SNEAK) prime contexts at a stimulus onset asynchrony (SOA) of 48 ms as consistent with this claim. To determine the time course over which degree of semantic similarity between morphologically structured primes and their targets influences recognition in the forward masked priming variant of the lexical decision paradigm, we compared facilitation for the same targets after semantically similar and dissimilar primes across a range of SOAs (34–100 ms). The effect of shared semantics on recognition latency increased linearly with SOA when long SOAs were intermixed (Experiments 1A and 1B) and latencies were significantly faster after semantically similar than dissimilar primes at homogeneous SOAs of 48 ms (Experiment 2) and 34 ms (Experiment 3). Results limit the scope of form-then-semantics models of recognition and demonstrate that semantics influences even the very early stages of recognition. Finally, once general performance across trials has been accounted for, we fail to provide evidence for individual differences in morphological processing that can be linked to measures of reading proficiency. PMID:25852512

Must analysis of meaning follow analysis of form? A time course analysis.

PubMed

Feldman, Laurie B; Milin, Petar; Cho, Kit W; Moscoso Del Prado Martín, Fermín; O'Connor, Patrick A

2015-01-01

Many models of word recognition assume that processing proceeds sequentially from analysis of form to analysis of meaning. In the context of morphological processing, this implies that morphemes are processed as units of form prior to any influence of their meanings. Some interpret the apparent absence of differences in recognition latencies to targets (SNEAK) in form and semantically similar (sneaky-SNEAK) and in form similar and semantically dissimilar (sneaker-SNEAK) prime contexts at a stimulus onset asynchrony (SOA) of 48 ms as consistent with this claim. To determine the time course over which degree of semantic similarity between morphologically structured primes and their targets influences recognition in the forward masked priming variant of the lexical decision paradigm, we compared facilitation for the same targets after semantically similar and dissimilar primes across a range of SOAs (34-100 ms). The effect of shared semantics on recognition latency increased linearly with SOA when long SOAs were intermixed (Experiments 1A and 1B) and latencies were significantly faster after semantically similar than dissimilar primes at homogeneous SOAs of 48 ms (Experiment 2) and 34 ms (Experiment 3). Results limit the scope of form-then-semantics models of recognition and demonstrate that semantics influences even the very early stages of recognition. Finally, once general performance across trials has been accounted for, we fail to provide evidence for individual differences in morphological processing that can be linked to measures of reading proficiency.

The Mycobacterium tuberculosis cell-surface glycoprotein apa as a potential adhesin to colonize target cells via the innate immune system pulmonary C-type lectin surfactant protein A.

PubMed

Ragas, Aude; Roussel, Lucie; Puzo, Germain; Rivière, Michel

2007-02-23

Tuberculosis is still a major health problem, and understanding the mechanism by which Mycobacterium tuberculosis (Mtb) invades and colonizes its host target cells remains an important issue for the control of infection. The innate immune system C-type lectins (C-TLs), including the human pulmonary surfactant protein A (PSP-A), have been recently identified as determinant players in the early recognition of the invading pathogen and in mounting the host defense response. Although the antigenic lipoglycan mannosylated lipoarabinomannan is currently considered to be the major C-TL target on the mycobacterial surface, the recognition by some C-TLs of the only mycobacterial species composing the "Mtb complex" indicates that mannosylated lipoarabinomannan cannot account alone for this specificity. Thus, we searched for the mycobacterial molecules targeted by human PSP-A, focusing our attention on the Mtb surface glycoproteins. We developed an original functional proteomic approach based on a lectin blot assay using crude human bronchoalveolar lavage fluid as a source of physiological PSP-A. Combined with selective cell-surface protein extraction and mass spectrometry peptide mapping, this strategy allowed us to identify the Apa (alanine- and proline-rich antigenic) glycoprotein as new potential target for PSP-A. This result was supported by direct binding of PSP-A to purified Apa. Moreover, EDTA addition or deglycosylation of purified Apa samples completely abolished the interaction, demonstrating that the interaction is calcium- and mannose-dependent, as expected. Finally, we provide convincing evidence that Apa, formerly considered as mainly secreted, is associated with the cell wall for a sufficiently long time to aid in the attachment of PSP-A. Because, to date, Apa seems to be restricted to the Mtb complex strains, we propose that it may account for the selective recognition of those strains by PSP-A and other immune system C-TLs containing homologous functional domains.

Improved maximum average correlation height filter with adaptive log base selection for object recognition

NASA Astrophysics Data System (ADS)

Tehsin, Sara; Rehman, Saad; Awan, Ahmad B.; Chaudry, Qaiser; Abbas, Muhammad; Young, Rupert; Asif, Afia

2016-04-01

Sensitivity to the variations in the reference image is a major concern when recognizing target objects. A combinational framework of correlation filters and logarithmic transformation has been previously reported to resolve this issue alongside catering for scale and rotation changes of the object in the presence of distortion and noise. In this paper, we have extended the work to include the influence of different logarithmic bases on the resultant correlation plane. The meaningful changes in correlation parameters along with contraction/expansion in the correlation plane peak have been identified under different scenarios. Based on our research, we propose some specific log bases to be used in logarithmically transformed correlation filters for achieving suitable tolerance to different variations. The study is based upon testing a range of logarithmic bases for different situations and finding an optimal logarithmic base for each particular set of distortions. Our results show improved correlation and target detection accuracies.

Collaboration in Associative Recognition Memory: Using Recalled Information to Defend "New" Judgments

ERIC Educational Resources Information Center

Clark, Steven E.; Abbe, Allison; Larson, Rakel P.

2006-01-01

S. E. Clark, A. Hori, A. Putnam, and T. J. Martin (2000) showed that collaboration on a recognition memory task produced facilitation in recognition of targets but had inconsistent and sometimes negative effects regarding distractors. They accounted for these results within the framework of a dual-process, recall-plus-familiarity model but…

Declines in Representational Quality and Strategic Retrieval Processes Contribute to Age-Related Increases in False Recognition

ERIC Educational Resources Information Center

Trelle, Alexandra N.; Henson, Richard N.; Green, Deborah A. E.; Simons, Jon S.

2017-01-01

In a Yes/No object recognition memory test with similar lures, older adults typically exhibit elevated rates of false recognition. However, the contributions of impaired retrieval, relative to reduced availability of target details, are difficult to disentangle using such a test. The present investigation sought to decouple these factors by…

The Slow Developmental Time Course of Real-Time Spoken Word Recognition

ERIC Educational Resources Information Center

Rigler, Hannah; Farris-Trimble, Ashley; Greiner, Lea; Walker, Jessica; Tomblin, J. Bruce; McMurray, Bob

2015-01-01

This study investigated the developmental time course of spoken word recognition in older children using eye tracking to assess how the real-time processing dynamics of word recognition change over development. We found that 9-year-olds were slower to activate the target words and showed more early competition from competitor words than…

A label-free ultrasensitive fluorescence detection of viable Salmonella enteritidis using enzyme-induced cascade two-stage toehold strand-displacement-driven assembly of G-quadruplex DNA.

PubMed

Zhang, Peng; Liu, Hui; Ma, Suzhen; Men, Shuai; Li, Qingzhou; Yang, Xin; Wang, Hongning; Zhang, Anyun

2016-06-15

The harm of Salmonella enteritidis (S. enteritidis ) to public health mainly by contaminating fresh food and water emphasizes the urgent need for rapid detection techniques to help control the spread of the pathogen. In this assay, an newly designed capture probe complex that contained specific S. enteritidis-aptamer and hybridized signal target sequence was used for viable S. enteritidis recognition directly. In the presence of the target S. enteritidis, single-stranded target sequences were liberated and initiated the replication-cleavage reaction, producing numerous G-quadruplex structures with a linker on the 3'-end. And then, the sensing system took innovative advantage of quadratic linker-induced strand-displacement for the first time to release target sequence in succession, leading to the cyclic reuse of the target sequences and cascade signal amplification, thereby achieving the successive production of G-quadruplex structures. The fluorescent dye, N-Methyl mesoporphyrin IX, binded to these G-quadruplex structures and generated significantly enhanced fluorescent signals to achieve highly sensitive detection of S. enteritidis down to 60 CFU/mL with a linear range from 10(2) to 10(7)CFU/mL. By coupling the cascade two-stage target sequences-recyclable toehold strand-displacement with aptamer-based target recognition successfully, it is the first report on a novel non-label, modification-free and DNA extraction-free ultrasensitive fluorescence biosensor for detecting viable S. enteritidis directly, which can discriminate from dead S. enteritidis. Copyright © 2016 Elsevier B.V. All rights reserved.

Birth order dependent growth cone segregation determines synaptic layer identity in the Drosophila visual system.

PubMed

Kulkarni, Abhishek; Ertekin, Deniz; Lee, Chi-Hon; Hummel, Thomas

2016-03-17

The precise recognition of appropriate synaptic partner neurons is a critical step during neural circuit assembly. However, little is known about the developmental context in which recognition specificity is important to establish synaptic contacts. We show that in the Drosophila visual system, sequential segregation of photoreceptor afferents, reflecting their birth order, lead to differential positioning of their growth cones in the early target region. By combining loss- and gain-of-function analyses we demonstrate that relative differences in the expression of the transcription factor Sequoia regulate R cell growth cone segregation. This initial growth cone positioning is consolidated via cell-adhesion molecule Capricious in R8 axons. Further, we show that the initial growth cone positioning determines synaptic layer selection through proximity-based axon-target interactions. Taken together, we demonstrate that birth order dependent pre-patterning of afferent growth cones is an essential pre-requisite for the identification of synaptic partner neurons during visual map formation in Drosophila.

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Tuning sensitivity of CAR to EGFR density limits recognition of normal tissue while maintaining potent anti-tumor activity

PubMed Central

Caruso, Hillary G.; Hurton, Lenka V.; Najjar, Amer; Rushworth, David; Ang, Sonny; Olivares, Simon; Mi, Tiejuan; Switzer, Kirsten; Singh, Harjeet; Huls, Helen; Lee, Dean A.; Heimberger, Amy B.; Champlin, Richard E.; Cooper, Laurence J. N.

2015-01-01

Many tumors over express tumor-associated antigens relative to normal tissue, such as epidermal growth factor receptor (EGFR). This limits targeting by human T cells modified to express chimeric antigen receptors (CARs) due to potential for deleterious recognition of normal cells. We sought to generate CAR+ T cells capable of distinguishing malignant from normal cells based on the disparate density of EGFR expression by generating two CARs from monoclonal antibodies which differ in affinity. T cells with low affinity Nimo-CAR selectively targeted cells over-expressing EGFR, but exhibited diminished effector function as the density of EGFR decreased. In contrast, the activation of T cells bearing high affinity Cetux-CAR was not impacted by the density of EGFR. In summary, we describe the generation of CARs able to tune T-cell activity to the level of EGFR expression in which a CAR with reduced affinity enabled T cells to distinguish malignant from non-malignant cells. PMID:26330164

Pitch-Based Segregation of Reverberant Speech

DTIC Science & Technology

2005-02-01

speaker recognition in real environments, audio information retrieval and hearing prosthesis. Second, although binaural listening improves the...intelligibility of target speech under anechoic conditions (Bronkhorst, 2000), this binaural advantage is largely eliminated by reverberation (Plomp, 1976...Brown and Cooke, 1994; Wang and Brown, 1999; Hu and Wang, 2004) as well as in binaural separation (e.g., Roman et al., 2003; Palomaki et al., 2004

Effects of Phonological and Orthographic Shifts on Children's Processing of Written Morphology: A Time-Course Study

ERIC Educational Resources Information Center

Quémart, Pauline; Casalis, Séverine

2014-01-01

We report two experiments that investigated whether phonological and/or orthographic shifts in a base word interfere with morphological processing by French 3rd, 4th, and 5th graders and adults (as a control group) along the time course of visual word recognition. In both experiments, prime-target pairs shared four possible relationships:…

The use of cue familiarity during retrieval failure is affected by past versus future orientation.

PubMed

Cleary, Anne M

2015-01-01

Cue familiarity that is brought on by cue resemblance to memory representations is useful for judging the likelihood of a past occurrence with an item that fails to actually be retrieved from memory. The present study examined the extent to which this type of resemblance-based cue familiarity is used in future-oriented judgments made during retrieval failure. Cue familiarity was manipulated using a previously-established method of creating differing degrees of feature overlap between the cue and studied items in memory, and the primary interest was in how these varying degrees of cue familiarity would influence future-oriented feeling-of-knowing (FOK) judgments given in instances of cued recall failure. The present results suggest that participants do use increases in resemblance-based cue familiarity to infer an increased likelihood of future recognition of an unretrieved target, but not to the extent that they use it to infer an increased likelihood of past experience with an unretrieved target. During retrieval failure, the increase in future-oriented FOK judgments with increasing cue familiarity was significantly less than the increase in past-oriented recognition judgments with increasing cue familiarity.

A new method for incoherent combining of far-field laser beams based on multiple faculae recognition

NASA Astrophysics Data System (ADS)

Ye, Demao; Li, Sichao; Yan, Zhihui; Zhang, Zenan; Liu, Yuan

2018-03-01

Compared to coherent beam combining, incoherent beam combining can complete the output of high power laser beam with high efficiency, simple structure, low cost and high thermal damage resistance, and it is easy to realize in engineering. Higher target power is achieved by incoherent beam combination which using technology of multi-channel optical path correction. However, each channel forms a spot in the far field respectively, which cannot form higher laser power density with low overlap ratio of faculae. In order to improve the combat effectiveness of the system, it is necessary to overlap different faculae that improve the target energy density. Hence, a novel method for incoherent combining of far-field laser beams is present. The method compromises piezoelectric ceramic technology and evaluation algorithm of faculae coincidence degree which based on high precision multi-channel optical path correction. The results show that the faculae recognition algorithm is low-latency(less than 10ms), which can meet the needs of practical engineering. Furthermore, the real time focusing ability of far field faculae is improved which was beneficial to the engineering of high-energy laser weapon or other laser jamming systems.

The relationship between action anticipation and emotion recognition in athletes of open skill sports.

PubMed

Shih, Yu-Ling; Lin, Chia-Yen

2016-08-01

Action anticipation plays an important role in the successful performance of open skill sports, such as ball and combat sports. Evidence has shown that elite athletes of open sports excel in action anticipation. Most studies have targeted ball sports and agreed that information on body mechanics is one of the key determinants for successful action anticipation in open sports. However, less is known about combat sports, and whether facial emotions have an influence on athletes' action anticipation skill. It has been suggested that the understanding of intention in combat sports relies heavily on emotional context. Based on this suggestion, the present study compared the action anticipation performances of taekwondo athletes, weightlifting athletes, and non-athletes and then correlated these with their performances of emotion recognition. This study primarily found that accurate action anticipation does not necessarily rely on the dynamic information of movement, and that action anticipation performance is correlated with that of emotion recognition in taekwondo athletes, but not in weightlifting athletes. Our results suggest that the recognition of facial emotions plays a role in the action prediction in such combat sports as taekwondo.

Domain repertoires as a tool to derive protein recognition rules.

PubMed

Zucconi, A; Panni, S; Paoluzi, S; Castagnoli, L; Dente, L; Cesareni, G

2000-08-25

Several approaches, some of which are described in this issue, have been proposed to assemble a complete protein interaction map. These are often based on high throughput methods that explore the ability of each gene product to bind any other element of the proteome of the organism. Here we propose that a large number of interactions can be inferred by revealing the rules underlying recognition specificity of a small number (a few hundreds) of families of protein recognition modules. This can be achieved through the construction and characterization of domain repertoires. A domain repertoire is assembled in a combinatorial fashion by allowing each amino acid position in the binding site of a given protein recognition domain to vary to include all the residues allowed at that position in the domain family. The repertoire is then searched by phage display techniques with any target of interest and from the primary structure of the binding site of the selected domains one derives rules that are used to infer the formation of complexes between natural proteins in the cell.

Amplitude (vu and rms) and Temporal (msec) Measures of Two Northwestern University Auditory Test No. 6 Recordings.

PubMed

Wilson, Richard H

2015-04-01

In 1940, a cooperative effort by the radio networks and Bell Telephone produced the volume unit (vu) meter that has been the mainstay instrument for monitoring the level of speech signals in commercial broadcasting and research laboratories. With the use of computers, today the amplitude of signals can be quantified easily using the root mean square (rms) algorithm. Researchers had previously reported that amplitude estimates of sentences and running speech were 4.8 dB higher when measured with a vu meter than when calculated with rms. This study addresses the vu-rms relation as applied to the carrier phrase and target word paradigm used to assess word-recognition abilities, the premise being that by definition the word-recognition paradigm is a special and different case from that described previously. The purpose was to evaluate the vu and rms amplitude relations for the carrier phrases and target words commonly used to assess word-recognition abilities. In addition, the relations with the target words between rms level and recognition performance were examined. Descriptive and correlational. Two recoded versions of the Northwestern University Auditory Test No. 6 were evaluated, the Auditec of St. Louis (Auditec) male speaker and the Department of Veterans Affairs (VA) female speaker. Using both visual and auditory cues from a waveform editor, the temporal onsets and offsets were defined for each carrier phrase and each target word. The rms amplitudes for those segments then were computed and expressed in decibels with reference to the maximum digitization range. The data were maintained for each of the four Northwestern University Auditory Test No. 6 word lists. Descriptive analyses were used with linear regressions used to evaluate the reliability of the measurement technique and the relation between the rms levels of the target words and recognition performances. Although there was a 1.3 dB difference between the calibration tones, the mean levels of the carrier phrases for the two recordings were -14.8 dB (Auditec) and -14.1 dB (VA) with standard deviations <1 dB. For the target words, the mean amplitudes were -19.9 dB (Auditec) and -18.3 dB (VA) with standard deviations ranging from 1.3 to 2.4 dB. The mean durations for the carrier phrases of both recordings were 593-594 msec, with the mean durations of the target words a little different, 509 msec (Auditec) and 528 msec (VA). Random relations were observed between the recognition performances and rms levels of the target words. Amplitude and temporal data for the individual words are provided. The rms levels of the carrier phrases closely approximated (±1 dB) the rms levels of the calibration tones, both of which were set to 0 vu (dB). The rms levels of the target words were 5-6 dB below the levels of the carrier phrases and were substantially more variable than the levels of the carrier phrases. The relation between the rms levels of the target words and recognition performances on the words was random. American Academy of Audiology.

Sparse and redundant representations for inverse problems and recognition

NASA Astrophysics Data System (ADS)

Patel, Vishal M.

Sparse and redundant representation of data enables the description of signals as linear combinations of a few atoms from a dictionary. In this dissertation, we study applications of sparse and redundant representations in inverse problems and object recognition. Furthermore, we propose two novel imaging modalities based on the recently introduced theory of Compressed Sensing (CS). This dissertation consists of four major parts. In the first part of the dissertation, we study a new type of deconvolution algorithm that is based on estimating the image from a shearlet decomposition. Shearlets provide a multi-directional and multi-scale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets. We develop a deconvolution algorithm that allows for the approximation inversion operator to be controlled on a multi-scale and multi-directional basis. Furthermore, we develop a method for the automatic determination of the threshold values for the noise shrinkage for each scale and direction without explicit knowledge of the noise variance using a generalized cross validation method. In the second part of the dissertation, we study a reconstruction method that recovers highly undersampled images assumed to have a sparse representation in a gradient domain by using partial measurement samples that are collected in the Fourier domain. Our method makes use of a robust generalized Poisson solver that greatly aids in achieving a significantly improved performance over similar proposed methods. We will demonstrate by experiments that this new technique is more flexible to work with either random or restricted sampling scenarios better than its competitors. In the third part of the dissertation, we introduce a novel Synthetic Aperture Radar (SAR) imaging modality which can provide a high resolution map of the spatial distribution of targets and terrain using a significantly reduced number of needed transmitted and/or received electromagnetic waveforms. We demonstrate that this new imaging scheme, requires no new hardware components and allows the aperture to be compressed. Also, it presents many new applications and advantages which include strong resistance to countermesasures and interception, imaging much wider swaths and reduced on-board storage requirements. The last part of the dissertation deals with object recognition based on learning dictionaries for simultaneous sparse signal approximations and feature extraction. A dictionary is learned for each object class based on given training examples which minimize the representation error with a sparseness constraint. A novel test image is then projected onto the span of the atoms in each learned dictionary. The residual vectors along with the coefficients are then used for recognition. Applications to illumination robust face recognition and automatic target recognition are presented.

The Binaural Masking-Level Difference of Mandarin Tone Detection and the Binaural Intelligibility-Level Difference of Mandarin Tone Recognition in the Presence of Speech-Spectrum Noise

PubMed Central

Ho, Cheng-Yu; Li, Pei-Chun; Chiang, Yuan-Chuan; Young, Shuenn-Tsong; Chu, Woei-Chyn

2015-01-01

Binaural hearing involves using information relating to the differences between the signals that arrive at the two ears, and it can make it easier to detect and recognize signals in a noisy environment. This phenomenon of binaural hearing is quantified in laboratory studies as the binaural masking-level difference (BMLD). Mandarin is one of the most commonly used languages, but there are no publication values of BMLD or BILD based on Mandarin tones. Therefore, this study investigated the BMLD and BILD of Mandarin tones. The BMLDs of Mandarin tone detection were measured based on the detection threshold differences for the four tones of the voiced vowels /i/ (i.e., /i1/, /i2/, /i3/, and /i4/) and /u/ (i.e., /u1/, /u2/, /u3/, and /u4/) in the presence of speech-spectrum noise when presented interaurally in phase (S0N0) and interaurally in antiphase (SπN0). The BILDs of Mandarin tone recognition in speech-spectrum noise were determined as the differences in the target-to-masker ratio (TMR) required for 50% correct tone recognitions between the S0N0 and SπN0 conditions. The detection thresholds for the four tones of /i/ and /u/ differed significantly (p<0.001) between the S0N0 and SπN0 conditions. The average detection thresholds of Mandarin tones were all lower in the SπN0 condition than in the S0N0 condition, and the BMLDs ranged from 7.3 to 11.5 dB. The TMR for 50% correct Mandarin tone recognitions differed significantly (p<0.001) between the S0N0 and SπN0 conditions, at –13.4 and –18.0 dB, respectively, with a mean BILD of 4.6 dB. The study showed that the thresholds of Mandarin tone detection and recognition in the presence of speech-spectrum noise are improved when phase inversion is applied to the target speech. The average BILDs of Mandarin tones are smaller than the average BMLDs of Mandarin tones. PMID:25835987

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

PubMed Central

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-01-01

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

PubMed

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-10-27

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

Recognising the forest, but not the trees: an effect of colour on scene perception and recognition.

PubMed

Nijboer, Tanja C W; Kanai, Ryota; de Haan, Edward H F; van der Smagt, Maarten J

2008-09-01

Colour has been shown to facilitate the recognition of scene images, but only when these images contain natural scenes, for which colour is 'diagnostic'. Here we investigate whether colour can also facilitate memory for scene images, and whether this would hold for natural scenes in particular. In the first experiment participants first studied a set of colour and greyscale natural and man-made scene images. Next, the same images were presented, randomly mixed with a different set. Participants were asked to indicate whether they had seen the images during the study phase. Surprisingly, performance was better for greyscale than for coloured images, and this difference is due to the higher false alarm rate for both natural and man-made coloured scenes. We hypothesized that this increase in false alarm rate was due to a shift from scrutinizing details of the image to recognition of the gist of the (coloured) image. A second experiment, utilizing images without a nameable gist, confirmed this hypothesis as participants now performed equally on greyscale and coloured images. In the final experiment we specifically targeted the more detail-based perception and recognition for greyscale images versus the more gist-based perception and recognition for coloured images with a change detection paradigm. The results show that changes to images are detected faster when image-pairs were presented in greyscale than in colour. This counterintuitive result held for both natural and man-made scenes (but not for scenes without nameable gist) and thus corroborates the shift from more detailed processing of images in greyscale to more gist-based processing of coloured images.

A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies.

PubMed

Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca

2017-04-15

Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller.

A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies

PubMed Central

Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca

2017-01-01

Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller. PMID:28420135

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Image-algebraic design of multispectral target recognition algorithms

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.

1994-06-01

In this paper, we discuss methods for multispectral ATR (Automated Target Recognition) of small targets that are sensed under suboptimal conditions, such as haze, smoke, and low light levels. In particular, we discuss our ongoing development of algorithms and software that effect intelligent object recognition by selecting ATR filter parameters according to ambient conditions. Our algorithms are expressed in terms of IA (image algebra), a concise, rigorous notation that unifies linear and nonlinear mathematics in the image processing domain. IA has been implemented on a variety of parallel computers, with preprocessors available for the Ada and FORTRAN languages. An image algebra C++ class library has recently been made available. Thus, our algorithms are both feasible implementationally and portable to numerous machines. Analyses emphasize the aspects of image algebra that aid the design of multispectral vision algorithms, such as parameterized templates that facilitate the flexible specification of ATR filters.

Recognition of facial emotion and affective prosody in children with ASD (+ADHD) and their unaffected siblings.

PubMed

Oerlemans, Anoek M; van der Meer, Jolanda M J; van Steijn, Daphne J; de Ruiter, Saskia W; de Bruijn, Yvette G E; de Sonneville, Leo M J; Buitelaar, Jan K; Rommelse, Nanda N J

2014-05-01

Autism is a highly heritable and clinically heterogeneous neuropsychiatric disorder that frequently co-occurs with other psychopathologies, such as attention-deficit/hyperactivity disorder (ADHD). An approach to parse heterogeneity is by forming more homogeneous subgroups of autism spectrum disorder (ASD) patients based on their underlying, heritable cognitive vulnerabilities (endophenotypes). Emotion recognition is a likely endophenotypic candidate for ASD and possibly for ADHD. Therefore, this study aimed to examine whether emotion recognition is a viable endophenotypic candidate for ASD and to assess the impact of comorbid ADHD in this context. A total of 90 children with ASD (43 with and 47 without ADHD), 79 ASD unaffected siblings, and 139 controls aged 6-13 years, were included to test recognition of facial emotion and affective prosody. Our results revealed that the recognition of both facial emotion and affective prosody was impaired in children with ASD and aggravated by the presence of ADHD. The latter could only be partly explained by typical ADHD cognitive deficits, such as inhibitory and attentional problems. The performance of unaffected siblings could overall be considered at an intermediate level, performing somewhat worse than the controls and better than the ASD probands. Our findings suggest that emotion recognition might be a viable endophenotype in ASD and a fruitful target in future family studies of the genetic contribution to ASD and comorbid ADHD. Furthermore, our results suggest that children with comorbid ASD and ADHD are at highest risk for emotion recognition problems.

Molecular mechanisms of floral organ specification by MADS domain proteins.

PubMed

Yan, Wenhao; Chen, Dijun; Kaufmann, Kerstin

2016-02-01

Flower development is a model system to understand organ specification in plants. The identities of different types of floral organs are specified by homeotic MADS transcription factors that interact in a combinatorial fashion. Systematic identification of DNA-binding sites and target genes of these key regulators show that they have shared and unique sets of target genes. DNA binding by MADS proteins is not based on 'simple' recognition of a specific DNA sequence, but depends on DNA structure and combinatorial interactions. Homeotic MADS proteins regulate gene expression via alternative mechanisms, one of which may be to modulate chromatin structure and accessibility in their target gene promoters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Formation of target-specific binding sites in enzymes: solid-phase molecular imprinting of HRP

NASA Astrophysics Data System (ADS)

Czulak, J.; Guerreiro, A.; Metran, K.; Canfarotta, F.; Goddard, A.; Cowan, R. H.; Trochimczuk, A. W.; Piletsky, S.

2016-05-01

Here we introduce a new concept for synthesising molecularly imprinted nanoparticles by using proteins as macro-functional monomers. For a proof-of-concept, a model enzyme (HRP) was cross-linked using glutaraldehyde in the presence of glass beads (solid-phase) bearing immobilized templates such as vancomycin and ampicillin. The cross-linking process links together proteins and protein chains, which in the presence of templates leads to the formation of permanent target-specific recognition sites without adverse effects on the enzymatic activity. Unlike complex protein engineering approaches commonly employed to generate affinity proteins, the method proposed can be used to produce protein-based ligands in a short time period using native protein molecules. These affinity materials are potentially useful tools especially for assays since they combine the catalytic properties of enzymes (for signaling) and molecular recognition properties of antibodies. We demonstrate this concept in an ELISA-format assay where HRP imprinted with vancomycin and ampicillin replaced traditional enzyme-antibody conjugates for selective detection of templates at micromolar concentrations. This approach can potentially provide a fast alternative to raising antibodies for targets that do not require high assay sensitivities; it can also find uses as a biochemical research tool, as a possible replacement for immunoperoxidase-conjugates.Here we introduce a new concept for synthesising molecularly imprinted nanoparticles by using proteins as macro-functional monomers. For a proof-of-concept, a model enzyme (HRP) was cross-linked using glutaraldehyde in the presence of glass beads (solid-phase) bearing immobilized templates such as vancomycin and ampicillin. The cross-linking process links together proteins and protein chains, which in the presence of templates leads to the formation of permanent target-specific recognition sites without adverse effects on the enzymatic activity. Unlike complex protein engineering approaches commonly employed to generate affinity proteins, the method proposed can be used to produce protein-based ligands in a short time period using native protein molecules. These affinity materials are potentially useful tools especially for assays since they combine the catalytic properties of enzymes (for signaling) and molecular recognition properties of antibodies. We demonstrate this concept in an ELISA-format assay where HRP imprinted with vancomycin and ampicillin replaced traditional enzyme-antibody conjugates for selective detection of templates at micromolar concentrations. This approach can potentially provide a fast alternative to raising antibodies for targets that do not require high assay sensitivities; it can also find uses as a biochemical research tool, as a possible replacement for immunoperoxidase-conjugates. Electronic supplementary information (ESI) available: Additional circular dichroism data and nanoparticle tracking analysis trace. See DOI: 10.1039/c6nr02009g

Revisiting the TALE repeat.

PubMed

Deng, Dong; Yan, Chuangye; Wu, Jianping; Pan, Xiaojing; Yan, Nieng

2014-04-01

Transcription activator-like (TAL) effectors specifically bind to double stranded (ds) DNA through a central domain of tandem repeats. Each TAL effector (TALE) repeat comprises 33-35 amino acids and recognizes one specific DNA base through a highly variable residue at a fixed position in the repeat. Structural studies have revealed the molecular basis of DNA recognition by TALE repeats. Examination of the overall structure reveals that the basic building block of TALE protein, namely a helical hairpin, is one-helix shifted from the previously defined TALE motif. Here we wish to suggest a structure-based re-demarcation of the TALE repeat which starts with the residues that bind to the DNA backbone phosphate and concludes with the base-recognition hyper-variable residue. This new numbering system is consistent with the α-solenoid superfamily to which TALE belongs, and reflects the structural integrity of TAL effectors. In addition, it confers integral number of TALE repeats that matches the number of bound DNA bases. We then present fifteen crystal structures of engineered dHax3 variants in complex with target DNA molecules, which elucidate the structural basis for the recognition of bases adenine (A) and guanine (G) by reported or uncharacterized TALE codes. Finally, we analyzed the sequence-structure correlation of the amino acid residues within a TALE repeat. The structural analyses reported here may advance the mechanistic understanding of TALE proteins and facilitate the design of TALEN with improved affinity and specificity.

Control of working memory: effects of attention training on target recognition and distractor salience in an auditory selection task.

PubMed

Melara, Robert D; Tong, Yunxia; Rao, Aparna

2012-01-09

Behavioral and electrophysiological measures of target and distractor processing were examined in an auditory selective attention task before and after three weeks of distractor suppression training. Behaviorally, training improved target recognition and led to less conservative and more rapid responding. Training also effectively shortened the temporal distance between distractors and targets needed to achieve a fixed level of target sensitivity. The effects of training on event-related potentials were restricted to the distracting stimulus: earlier N1 latency, enhanced P2 amplitude, and weakened P3 amplitude. Nevertheless, as distractor P2 amplitude increased, so too did target P3 amplitude, connecting experience-dependent changes in distractor processing with greater distinctiveness of targets in working memory. We consider the effects of attention training on the processing priorities, representational noise, and inhibitory processes operating in working memory. Copyright © 2011 Elsevier B.V. All rights reserved.

Using computerized games to teach face recognition skills to children with autism spectrum disorder: the Let's Face It! program.

PubMed

Tanaka, James W; Wolf, Julie M; Klaiman, Cheryl; Koenig, Kathleen; Cockburn, Jeffrey; Herlihy, Lauren; Brown, Carla; Stahl, Sherin; Kaiser, Martha D; Schultz, Robert T

2010-08-01

An emerging body of evidence indicates that relative to typically developing children, children with autism are selectively impaired in their ability to recognize facial identity. A critical question is whether face recognition skills can be enhanced through a direct training intervention. In a randomized clinical trial, children diagnosed with autism spectrum disorder were pre-screened with a battery of subtests (the Let's Face It! Skills battery) examining face and object processing abilities. Participants who were significantly impaired in their face processing abilities were assigned to either a treatment or a waitlist group. Children in the treatment group (N = 42) received 20 hours of face training with the Let's Face It! (LFI!) computer-based intervention. The LFI! program is comprised of seven interactive computer games that target the specific face impairments associated with autism, including the recognition of identity across image changes in expression, viewpoint and features, analytic and holistic face processing strategies and attention to information in the eye region. Time 1 and Time 2 performance for the treatment and waitlist groups was assessed with the Let's Face It! Skills battery. The main finding was that relative to the control group (N = 37), children in the face training group demonstrated reliable improvements in their analytic recognition of mouth features and holistic recognition of a face based on its eyes features. These results indicate that a relatively short-term intervention program can produce measurable improvements in the face recognition skills of children with autism. As a treatment for face processing deficits, the Let's Face It! program has advantages of being cost-free, adaptable to the specific learning needs of the individual child and suitable for home and school applications.

An electrophysiological signature for proactive interference resolution in working memory.

PubMed

Du, Yingchun; Xiao, Zhuangwei; Song, Yan; Fan, Silu; Wu, Renhua; Zhang, John X

2008-08-01

We used event-related potentials (ERPs) to study the temporal dynamics of proactive interference in working memory. Participants performed a Sternberg item-recognition task to determine whether a probe was in a target memory set. Familiar negative probes were found to be more difficult to reject than less familiar ones. A fronto-central N2 component peaking around 300 ms post-probe-onset differentiated among target probes, familiar and less familiar non-target probes. The study identifies N2 as the ERP signature for proactive interference resolution. It also indicates that the resolution process occurs in the same time window as target/non-target discrimination and provides the first piece of electrophysiological evidence supporting a recent interference resolution model based on localization data [Jonides, J., Nee, D.E., 2006. Brain mechanisms of proactive interference in working memory. Neuroscience 139, 181-193].

The Effects of Aging and IQ on Item and Associative Memory

PubMed Central

Ratcliff, Roger; Thapar, Anjali; McKoon, Gail

2011-01-01

The effects of aging and IQ on performance were examined in four memory tasks: item recognition, associative recognition, cued recall, and free recall. For item and associative recognition, accuracy and the response time distributions for correct and error responses were explained by Ratcliff’s (1978) diffusion model, at the level of individual participants. The values of the components of processing identified by the model for the recognition tasks, as well as accuracy for cued and free recall, were compared across levels of IQ ranging from 85 to 140 and age (college-age, 60-74 year olds, and 75-90 year olds). IQ had large effects on the quality of the evidence from memory on which decisions were based in the recognition tasks and accuracy in the recall tasks, except for the oldest participants for whom some of the measures were near floor values. Drift rates in the recognition tasks, accuracy in the recall tasks, and IQ all correlated strongly with each other. However, there was a small decline in drift rates for item recognition and a large decline for associative recognition and accuracy in cued recall (about 70 percent). In contrast, there were large age effects on boundary separation and nondecision time (which correlated across tasks), but little effect of IQ. The implications of these results for single- and dual- process models of item recognition are discussed and it is concluded that models that deal with both RTs and accuracy are subject to many more constraints than models that deal with only one of these measures. Overall, the results of the study show a complicated but interpretable pattern of interactions that present important targets for response time and memory models. PMID:21707207

A novel "signal-on/off" sensing platform for selective detection of thrombin based on target-induced ratiometric electrochemical biosensing and bio-bar-coded nanoprobe amplification strategy.

PubMed

Wang, Lanlan; Ma, Rongna; Jiang, Liushan; Jia, Liping; Jia, Wenli; Wang, Huaisheng

2017-06-15

A novel dual-signal ratiometric electrochemical aptasensor for highly sensitive and selective detection of thrombin has been designed on the basis of signal-on and signal-off strategy. Ferrocene labeled hairpin probe (Fc-HP), thrombin aptamer and methyl blue labeled bio-bar-coded AuNPs (MB-P3-AuNPs) were rationally introduced for the construction of the assay platform, which combined the advantages of the recognition of aptamer, the amplification of bio-bar-coded nanoprobe, and the ratiometric signaling readout. In the presence of thrombin, the interaction between thrombin and the aptamer leads to the departure of MB-P3-AuNPs from the sensing interface, and the conformation of the single stranded Fc-HP to a hairpin structure to take the Fc confined near the electrode surface. Such conformational changes resulted in the oxidation current of Fc increased and that of MB decreased. Therefore, the recognition event of the target can be dual-signal ratiometric electrochemical readout in both the "signal-off" of MB and the "signal-on" of Fc. The proposed strategy showed a wide linear detection range from 0.003 to 30nM with a detection limit of 1.1 pM. Moreover, it exhibits good performance of excellent selectivity, good stability, and acceptable fabrication reproducibility. By changing the recognition probe, this protocol could be easily expanded into the detection of other targets, showing promising potential applications in disease diagnostics and bioanalysis. Copyright © 2016. Published by Elsevier B.V.

ERP Correlates of Target-Distracter Differentiation in Repeated Runs of a Continuous Recognition Task with Emotional and Neutral Faces

ERIC Educational Resources Information Center

Treese, Anne-Cecile; Johansson, Mikael; Lindgren, Magnus

2010-01-01

The emotional salience of faces has previously been shown to induce memory distortions in recognition memory tasks. This event-related potential (ERP) study used repeated runs of a continuous recognition task with emotional and neutral faces to investigate emotion-induced memory distortions. In the second and third runs, participants made more…

A Pilot Study of a Test for Visual Recognition Memory in Adults with Moderate to Severe Intellectual Disability

ERIC Educational Resources Information Center

Pyo, Geunyeong; Ala, Tom; Kyrouac, Gregory A.; Verhulst, Steven J.

2010-01-01

Objective assessment of memory functioning is an important part of evaluation for Dementia of Alzheimer Type (DAT). The revised Picture Recognition Memory Test (r-PRMT) is a test for visual recognition memory to assess memory functioning of persons with intellectual disabilities (ID), specifically targeting moderate to severe ID. A pilot study was…

Linguistic contributions to speech-on-speech masking for native and non-native listeners: language familiarity and semantic content.

PubMed

Brouwer, Susanne; Van Engen, Kristin J; Calandruccio, Lauren; Bradlow, Ann R

2012-02-01

This study examined whether speech-on-speech masking is sensitive to variation in the degree of similarity between the target and the masker speech. Three experiments investigated whether speech-in-speech recognition varies across different background speech languages (English vs Dutch) for both English and Dutch targets, as well as across variation in the semantic content of the background speech (meaningful vs semantically anomalous sentences), and across variation in listener status vis-à-vis the target and masker languages (native, non-native, or unfamiliar). The results showed that the more similar the target speech is to the masker speech (e.g., same vs different language, same vs different levels of semantic content), the greater the interference on speech recognition accuracy. Moreover, the listener's knowledge of the target and the background language modulate the size of the release from masking. These factors had an especially strong effect on masking effectiveness in highly unfavorable listening conditions. Overall this research provided evidence that that the degree of target-masker similarity plays a significant role in speech-in-speech recognition. The results also give insight into how listeners assign their resources differently depending on whether they are listening to their first or second language. © 2012 Acoustical Society of America

Linguistic contributions to speech-on-speech masking for native and non-native listeners: Language familiarity and semantic content

PubMed Central

Brouwer, Susanne; Van Engen, Kristin J.; Calandruccio, Lauren; Bradlow, Ann R.

2012-01-01

This study examined whether speech-on-speech masking is sensitive to variation in the degree of similarity between the target and the masker speech. Three experiments investigated whether speech-in-speech recognition varies across different background speech languages (English vs Dutch) for both English and Dutch targets, as well as across variation in the semantic content of the background speech (meaningful vs semantically anomalous sentences), and across variation in listener status vis-à-vis the target and masker languages (native, non-native, or unfamiliar). The results showed that the more similar the target speech is to the masker speech (e.g., same vs different language, same vs different levels of semantic content), the greater the interference on speech recognition accuracy. Moreover, the listener’s knowledge of the target and the background language modulate the size of the release from masking. These factors had an especially strong effect on masking effectiveness in highly unfavorable listening conditions. Overall this research provided evidence that that the degree of target-masker similarity plays a significant role in speech-in-speech recognition. The results also give insight into how listeners assign their resources differently depending on whether they are listening to their first or second language. PMID:22352516

Simultaneous Versus Sequential Presentation in Testing Recognition Memory for Faces.

PubMed

Finley, Jason R; Roediger, Henry L; Hughes, Andrea D; Wahlheim, Christopher N; Jacoby, Larry L

2015-01-01

Three experiments examined the issue of whether faces could be better recognized in a simul- taneous test format (2-alternative forced choice [2AFC]) or a sequential test format (yes-no). All experiments showed that when target faces were present in the test, the simultaneous procedure led to superior performance (area under the ROC curve), whether lures were high or low in similarity to the targets. However, when a target-absent condition was used in which no lures resembled the targets but the lures were similar to each other, the simultaneous procedure yielded higher false alarm rates (Experiments 2 and 3) and worse overall performance (Experi- ment 3). This pattern persisted even when we excluded responses that participants opted to withhold rather than volunteer. We conclude that for the basic recognition procedures used in these experiments, simultaneous presentation of alternatives (2AFC) generally leads to better discriminability than does sequential presentation (yes-no) when a target is among the alterna- tives. However, our results also show that the opposite can occur when there is no target among the alternatives. An important future step is to see whether these patterns extend to more realistic eyewitness lineup procedures. The pictures used in the experiment are available online at http://www.press.uillinois.edu/journals/ajp/media/testing_recognition/.

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.

From malignant hypertension to hypertension-MOD: a modern definition for an old but still dangerous emergency.

PubMed

Cremer, A; Amraoui, F; Lip, G Y H; Morales, E; Rubin, S; Segura, J; Van den Born, B J; Gosse, P

2016-08-01

The prevalence of malignant hypertension has clearly fallen with the advent of anti-hypertensive medication but has remained stable over the past 30-40 years in spite of progress in diagnosis and management of hypertension. A diagnosis of malignant hypertension is usually based on the association of severely elevated blood pressure with a Keith and Wagener stage III or IV retinopathy. We believe that this definition can be reconsidered for several reasons. Although simple and pragmatic, this definition corresponds to a time when there were few techniques for assessment of hypertensive target organ involvement, and does not take into account involvement of kidney, brain and heart; whereas the overall prognosis largely depends on how much they are affected. On the contrary, the acute blood pressure level and especially diastolic should not be a hard diagnostic criterion as it does not itself constitute the prognosis of the condition. We propose to consider that malignant hypertension with retinopathy is only one of a number of possible presentation(s) of acute hypertension with multi organ damage (hypertension multi organ damage (MOD)) and that the recognition of these hypertensive emergencies, when retinopathy is lacking, be based on acute elevation of BP associated with impairment of at least three different target organs. The objective of a new and expanded definition is to facilitate recognition of these true emergencies. The condition is more common than usually perceived and would have a much worse prognosis than the usual forms of hypertension. Early recognition and management of hypertension-MOD are fundamental to any improvement in prognosis.

Designer interface peptide grafts target estrogen receptor alpha dimerization

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

Chakraborty, S.; Asare, B.K.; Biswas, P.K., E-mail: pbiswas@tougaloo.edu

The nuclear transcription factor estrogen receptor alpha (ERα), triggered by its cognate ligand estrogen, regulates a variety of cellular signaling events. ERα is expressed in 70% of breast cancers and is a widely validated target for anti-breast cancer drug discovery. Administration of anti-estrogen to block estrogen receptor activation is still a viable anti-breast cancer treatment option but anti-estrogen resistance has been a significant bottle-neck. Dimerization of estrogen receptor is required for ER activation. Blocking ERα dimerization is therefore a complementary and alternative strategy to combat anti-estrogen resistance. Dimer interface peptide “I-box” derived from ER residues 503–518 specifically blocks ER dimerization.more » Recently using a comprehensive molecular simulation we studied the interaction dynamics of ERα LBDs in a homo-dimer. Based on this study, we identified three interface recognition peptide motifs LDKITDT (ERα residues 479–485), LQQQHQRLAQ (residues 497–506), and LSHIRHMSNK (residues 511–520) and reported the suitability of using LQQQHQRLAQ (ER 497–506) as a template to design inhibitors of ERα dimerization. Stability and self-aggregation of peptide based therapeutics poses a significant bottle-neck to proceed further. In this study utilizing peptide grafted to preserve their pharmacophoric recognition motif and assessed their stability and potential to block ERα mediated activity in silico and in vitro. The Grafted peptides blocked ERα mediated cell proliferation and viability of breast cancer cells but did not alter their apoptotic fate. We believe the structural clues identified in this study can be used to identify novel peptidometics and small molecules that specifically target ER dimer interface generating a new breed of anti-cancer agents. - Highlights: • Designer peptide grafts retain core molecular recognition motif during MD simulations. • Designer peptide grafts with Poly-ALA helix form stable complexes with estrogen receptor in silico. • Inhibitor peptides significantly decrease estrogen induced cell proliferation of ER positive breast cancer cells in vitro.« less

A Unitary Anesthetic Binding Site at High Resolution

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

Vedula, L. Sangeetha; Brannigan, Grace; Economou, Nicoleta J.

2009-10-21

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABA{sub A} receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show thatmore » apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Unitary Anesthetic Binding Site at High Resolution

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

L Vedula; G Brannigan; N Economou

2011-12-31

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABA{sub A} receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show thatmore » apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Unitary Anesthetic-Binding Site at High Resolution

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

Vedula, L.; Brannigan, G; Economou, N

2009-01-01

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABAA receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show that apoferritinmore » also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Hybrid Neural Network and Feature Extraction Technique for Target Recognition.

DTIC Science & Technology

target features are extracted, the extracted data being evaluated in an artificial neural network to identify a target at a location within the image scene from which the different viewing angles extend.

Bi-Spectral Method for Radar Target Recognition

DTIC Science & Technology

2006-12-01

θazimuth=60° and ϕelevation=30° with HV Polarization....................................53 Figure 50 Comparison of Radar Range Profile with Actual...radar systems. A comparison of the NCTR techniques and their relative advantages and disadvantages in target recognition performance is presented. 8...32 f fR i R R c c f fi R R i R R c c A e A e A e ψ ψ π ψ ψ π ψ ψ π ψ ψ

Defense Small Business Innovation Research Program (SBIR). Volume 1. Army Abstracts of Phase 1 Awards 1991

DTIC Science & Technology

1991-01-01

Office: MICOM HUNTSVILLE, AL 35805 Contract #: DAAHO1-92-C-R150 Phone: (205) 876-7502 Pi: D. BRETI BEASLEY Title: INFRARED LASER DIODE BASED INFRARED ...TECHNIQUES WILL BE INVESTIGATED TO DESIGN A FORM FIT GIMBALL-MOUNTED 94 GHZ/ INFRARED FOCAL PLANE ARRAY DUAL-MODE MISSILE SEEKER SENSOR BASED ON LOW...RESOLUTION AT 94 GHZ AND A 128X128 ARRAY IR IMAGE PROCESSING FOR AUTONOMOUS TARGET RECOGNITION AND AIMPOINT SELECTION. THE 94 GHZ AND INFRARED ELECTRONICS

Ultrafast Target Recognition via Super-Parallel Holograph Based Correlator, RAM and Associative Memory

DTIC Science & Technology

2008-03-11

JTC) 2𔃾 based on a dynamic material answers the challenge of fast correlation with large databases. Images retrieved from the SPHRAM and used as the...transform (JTC) and matched spatial filter or VanderLugt ( VLC ) correlators, either of which can be implemented in real-time by degenerate four wave-mixing in...proposed system, consisting of the SPHROM coupled with a shift-invariant real-time VLC . The correlation is performed in the VLC architecture to

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark; Selinsky, T.

2002-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

The striking similarities between standard, distractor-free, and target-free recognition

PubMed Central

Dobbins, Ian G.

2012-01-01

It is often assumed that observers seek to maximize correct responding during recognition testing by actively adjusting a decision criterion. However, early research by Wallace (Journal of Experimental Psychology: Human Learning and Memory 4:441–452, 1978) suggested that recognition rates for studied items remained similar, regardless of whether or not the tests contained distractor items. We extended these findings across three experiments, addressing whether detection rates or observer confidence changed when participants were presented standard tests (targets and distractors) versus “pure-list” tests (lists composed entirely of targets or distractors). Even when observers were made aware of the composition of the pure-list test, the endorsement rates and confidence patterns remained largely similar to those observed during standard testing, suggesting that observers are typically not striving to maximize the likelihood of success across the test. We discuss the implications for decision models that assume a likelihood ratio versus a strength decision axis, as well as the implications for prior findings demonstrating large criterion shifts using target probability manipulations. PMID:21476108

Geometry-Based Observability Metric

NASA Technical Reports Server (NTRS)

Eaton, Colin; Naasz, Bo

2012-01-01

The Satellite Servicing Capabilities Office (SSCO) is currently developing and testing Goddard s Natural Feature Image Recognition (GNFIR) software for autonomous rendezvous and docking missions. GNFIR has flight heritage and is still being developed and tailored for future missions with non-cooperative targets: (1) DEXTRE Pointing Package System on the International Space Station, (2) Relative Navigation System (RNS) on the Space Shuttle for the fourth Hubble Servicing Mission.

Risk-Based Aviation Security: Diffusion and Acceptance

DTIC Science & Technology

2012-03-01

Association ATR Automated Target Recognition BDO Behavior Detection Officer BIB Budget-In-Brief CBP Customs and Border Protection CDRH Center...Radiological Health ( CDRH ) (Cerra, 2006), the National Institute for Standards and Technology (NIST) (TSA, n.d. g), and the Johns Hopkins University Applied...safety related to AIT may have come from the Food and Drug Administration’s (FDA) Center for Devices and Radiological Health ( CDRH ), the National

Mapping monomeric threading to protein-protein structure prediction.

PubMed

Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

2013-03-25

The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD <2.5 Å by SPRING is 134% and 167% higher than these competing methods. SPRING is controlled with ZDOCK on 77 docking benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

Assessing the performance of a motion tracking system based on optical joint transform correlation

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

2015-08-01

We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

A host-guest-recognition-based electrochemical aptasensor for thrombin detection.

PubMed

Fan, Hao; Li, Hui; Wang, Qingjiang; He, Pingang; Fang, Yuzhi

2012-05-15

A sensitive electrochemical aptasensor for thrombin detection is presented based on the host-guest recognition technique. In this sensing protocol, a 15 based thrombin aptamer (ab. TBA) was dually labeled with a thiol at its 3' end and a 4-((4-(dimethylamino)phenyl)azo) benzoic acid (dabcyl) at its 5' end, respectively, which was previously immobilized on one Au electrode surface by AuS bond and used as the thrombin probe during the protein sensing procedure. One special electrochemical marker was prepared by modifying CdS nanoparticle with β-cyclodextrins (ab. CdS-CDs), which employed as electrochemical signal provider and would conjunct with the thrombin probe modified electrode through the host-guest recognition of CDs to dabcyl. In the absence of thrombin, the probe adopted linear structure to conjunct with CdS-CDs. In present of thrombin, the TBA bond with thrombin and transformed into its special G-quarter structure, which forced CdS-CDs into the solution. Therefore, the target-TBA binding event can be sensitively transduced via detecting the electrochemical oxidation current signal of Cd of CdS nanoparticles in the solution. Using this method, as low as 4.6 pM thrombin had been detected. Copyright © 2012 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2007-04-01

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

Modularly assembled designer TAL effector nucleases for targeted gene knockout and gene replacement in eukaryotes

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

Li, T; Huang, S; Zhao, XF

Recent studies indicate that the DNA recognition domain of transcription activator-like (TAL) effectors can be combined with the nuclease domain of FokI restriction enzyme to produce TAL effector nucleases (TALENs) that, in pairs, bind adjacent DNA target sites and produce double-strand breaks between the target sequences, stimulating non-homologous end-joining and homologous recombination. Here, we exploit the four prevalent TAL repeats and their DNA recognition cipher to develop a 'modular assembly' method for rapid production of designer TALENs (dTALENs) that recognize unique DNA sequence up to 23 bases in any gene. We have used this approach to engineer 10 dTALENs tomore » target specific loci in native yeast chromosomal genes. All dTALENs produced high rates of site-specific gene disruptions and created strains with expected mutant phenotypes. Moreover, dTALENs stimulated high rates (up to 34%) of gene replacement by homologous recombination. Finally, dTALENs caused no detectable cytotoxicity and minimal levels of undesired genetic mutations in the treated yeast strains. These studies expand the realm of verified TALEN activity from cultured human cells to an intact eukaryotic organism and suggest that low-cost, highly dependable dTALENs can assume a significant role for gene modifications of value in human and animal health, agriculture and industry.« less

Signature analysis of ballistic missile warhead with micro-nutation in terahertz band

NASA Astrophysics Data System (ADS)

Li, Ming; Jiang, Yue-song

2013-08-01

In recent years, the micro-Doppler effect has been proposed as a new technique for signature analysis and extraction of radar targets. The ballistic missile is known as a typical radar target and has been paid many attentions for the complexities of its motions in current researches. The trajectory of a ballistic missile can be generally divided into three stages: boost phase, midcourse phase and terminal phase. The midcourse phase is the most important phase for radar target recognition and interception. In this stage, the warhead forms a typical micro-motion called micro-nutation which consists of three basic micro-motions: spinning, coning and wiggle. This paper addresses the issue of signature analysis of ballistic missile warhead in terahertz band via discussing the micro-Doppler effect. We establish a simplified model (cone-shaped) for the missile warhead followed by the micro-motion models including of spinning, coning and wiggle. Based on the basic formulas of these typical micro-motions, we first derive the theoretical formula of micro-nutation which is the main micro-motion of the missile warhead. Then, we calculate the micro-Doppler frequency in both X band and terahertz band via these micro-Doppler formulas. The simulations are given to show the superiority of our proposed method for the recognition and detection of radar micro targets in terahertz band.

Structural basis of clade-specific HIV-1 neutralization by humanized anti-V3 monoclonal antibody KD-247.

PubMed

Kirby, Karen A; Ong, Yee Tsuey; Hachiya, Atsuko; Laughlin, Thomas G; Chiang, Leslie A; Pan, Yun; Moran, Jennifer L; Marchand, Bruno; Singh, Kamalendra; Gallazzi, Fabio; Quinn, Thomas P; Yoshimura, Kazuhisa; Murakami, Toshio; Matsushita, Shuzo; Sarafianos, Stefan G

2015-01-01

Humanized monoclonal antibody KD-247 targets the Gly(312)-Pro(313)-Gly(314)-Arg(315) arch of the third hypervariable (V3) loop of the HIV-1 surface glycoprotein. It potently neutralizes many HIV-1 clade B isolates, but not of other clades. To understand the molecular basis of this specificity, we solved a high-resolution (1.55 Å) crystal structure of the KD-247 antigen binding fragment and examined the potential interactions with various V3 loop targets. Unlike most antibodies, KD-247 appears to interact with its target primarily through light chain residues. Several of these interactions involve Arg(315) of the V3 loop. To evaluate the role of light chain residues in the recognition of the V3 loop, we generated 20 variants of KD-247 single-chain variable fragments with mutations in the antigen-binding site. Purified proteins were assessed for V3 loop binding using AlphaScreen technology and for HIV-1 neutralization. Our data revealed that recognition of the clade-specificity defining residue Arg(315) of the V3 loop is based on a network of interactions that involve Tyr(L32), Tyr(L92), and Asn(L27d) that directly interact with Arg(315), thus elucidating the molecular interactions of KD-247 with its V3 loop target. © FASEB.

Continued effects of context reinstatement in recognition.

PubMed

Hanczakowski, Maciej; Zawadzka, Katarzyna; Macken, Bill

2015-07-01

The context reinstatement effect refers to the enhanced memory performance found when the context information paired with a target item at study is re-presented at test. Here we investigated the consequences of the way that context information is processed in such a setting that gives rise to its beneficial effect on item recognition memory. Specifically, we assessed whether reinstating context in a recognition test facilitates subsequent memory for this context, beyond the facilitation conferred by presentation of the same context with a different study item. Reinstating the study context at test led to better accuracy in two-alternative forced choice recognition for target faces than did re-pairing those faces with another context encountered during the study phase. The advantage for reinstated over re-paired conditions occurred for both within-subjects (Exp. 1) and between-subjects (Exp. 2) manipulations. Critically, in a subsequent recognition test for the contexts themselves, contexts that had previously served in the reinstated condition were recognized better than contexts that had previously served in the re-paired context condition. This constitutes the first demonstration of continuous effects of context reinstatement on memory for context.

Increase in Speech Recognition due to Linguistic Mismatch Between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

PubMed Central

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose To examine whether improved speech recognition during linguistically mismatched target–masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method Monolingual English speakers (n = 20) and English–Greek simultaneous bilinguals (n = 20) listened to English sentences in the presence of competing English and Greek speech. Data were analyzed using mixed-effects regression models to determine differences in English recogition performance between the 2 groups and 2 masker conditions. Results Results indicated that English sentence recognition for monolinguals and simultaneous English–Greek bilinguals improved when the masker speech changed from competing English to competing Greek speech. Conclusion The improvement in speech recognition that has been observed for linguistically mismatched target–masker experiments cannot be simply explained by the masker language being linguistically unknown or unfamiliar to the listeners. Listeners can improve their speech recognition in linguistically mismatched target–masker experiments even when the listener is able to obtain meaningful linguistic information from the masker speech. PMID:24167230

Helix Unwinding and Base Flipping Enable Human MTERF1 to Terminate Mitochondrial Transcription

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

Yakubovskaya, E.; Mejia, E; Byrnes, J

2010-01-01

Defects in mitochondrial gene expression are associated with aging and disease. Mterf proteins have been implicated in modulating transcription, replication and protein synthesis. We have solved the structure of a member of this family, the human mitochondrial transcriptional terminator MTERF1, bound to dsDNA containing the termination sequence. The structure indicates that upon sequence recognition MTERF1 unwinds the DNA molecule, promoting eversion of three nucleotides. Base flipping is critical for stable binding and transcriptional termination. Additional structural and biochemical results provide insight into the DNA binding mechanism and explain how MTERF1 recognizes its target sequence. Finally, we have demonstrated that themore » mitochondrial pathogenic G3249A and G3244A mutations interfere with key interactions for sequence recognition, eliminating termination. Our results provide insight into the role of mterf proteins and suggest a link between mitochondrial disease and the regulation of mitochondrial transcription.« less

Substrate-based inhibitors exhibiting excellent protective and therapeutic effects against Botulinum Neurotoxin A intoxication.

PubMed

Guo, Jiubiao; Wang, Jinglin; Gao, Shan; Ji, Bin; Waichi Chan, Edward; Chen, Sheng

2015-11-20

Potent inhibitors to reverse Botulinum neurotoxins (BoNTs) activity in neuronal cells are currently not available. A better understanding of the substrate recognition mechanism of BoNTs enabled us to design a novel class of peptide inhibitors which were derivatives of the BoNT/A substrate, SNAP25. Through a combination of in vitro, cellular based, and in vivo mouse assays, several potent inhibitors of approximately one nanomolar inhibitory strength both in vitro and in vivo have been identified. These compounds represent the first set of inhibitors that exhibited full protection against BoNT/A intoxication in mice model with undetectable toxicity. Our findings validated the hypothesis that a peptide inhibitor targeting the two BoNT structural regions which were responsible for substrate recognition and cleavage respectively could exhibit excellent inhibitory effect, thereby providing insight on future development of more potent inhibitors against BoNTs.

Chemical biology-based approaches on fluorescent labeling of proteins in live cells.

PubMed

Jung, Deokho; Min, Kyoungmi; Jung, Juyeon; Jang, Wonhee; Kwon, Youngeun

2013-05-01

Recently, significant advances have been made in live cell imaging owing to the rapid development of selective labeling of proteins in vivo. Green fluorescent protein (GFP) was the first example of fluorescent reporters genetically introduced to protein of interest (POI). While GFP and various types of engineered fluorescent proteins (FPs) have been actively used for live cell imaging for many years, the size and the limited windows of fluorescent spectra of GFP and its variants set limits on possible applications. In order to complement FP-based labeling methods, alternative approaches that allow incorporation of synthetic fluorescent probes to target POIs were developed. Synthetic fluorescent probes are smaller than fluorescent proteins, often have improved photochemical properties, and offer a larger variety of colors. These synthetic probes can be introduced to POIs selectively by numerous approaches that can be largely categorized into chemical recognition-based labeling, which utilizes metal-chelating peptide tags and fluorophore-carrying metal complexes, and biological recognition-based labeling, such as (1) specific non-covalent binding between an enzyme tag and its fluorophore-carrying substrate, (2) self-modification of protein tags using substrate variants conjugated to fluorophores, (3) enzymatic reaction to generate a covalent binding between a small molecule substrate and a peptide tag, and (4) split-intein-based C-terminal labeling of target proteins. The chemical recognition-based labeling reaction often suffers from compromised selectivity of metal-ligand interaction in the cytosolic environment, consequently producing high background signals. Use of protein-substrate interactions or enzyme-mediated reactions generally shows improved specificity but each method has its limitations. Some examples are the presence of large linker protein, restriction on the choice of introducible probes due to the substrate specificity of enzymes, and competitive reaction mediated by an endogenous analogue of the introduced protein tag. These limitations have been addressed, in part, by the split-intein-based labeling approach, which introduces fluorescent probes with a minimal size (~4 amino acids) peptide tag. In this review, the advantages and the limitations of each labeling method are discussed.

Emotional System for Military Target Identification

DTIC Science & Technology

2009-10-01

algorithm [23], and used it to solve a facial recognition problem. In other works [24,25], we explored the potential of using emotional neural...other application areas, such as security ( facial recognition ) and medical (blood cell identification), can be also efficiently used in military...Application of an emotional neural network to facial recognition . Neural Computing and Applications, 18(4), 309-320. [25] Khashman, A. (2009). Blood cell

Ultra wide band 3-D cross section (RCS) holography

NASA Astrophysics Data System (ADS)

Collins, H. D.; Hall, T. E.

1992-07-01

Ultra wide band impulse holography is an exciting new concept for predictive radar cross section (RCS) evaluation employing near-field measurements. Reconstruction of the near-field hologram data maps the target's scattering areas, and uniquely identifies the 'hot spot' locations on the target. In addition, the target and calibration sphere's plane wave angular spectrums are computed (via digital algorithm) and used to generate the target's far-field RCS values in three dimensions for each frequency component in the impulse. Thin and thick targets are defined in terms of their near-field amplitude variations in range. Range gating and computer holographic techniques are applied to correct these variations. Preliminary experimental results on various targets verify the concept of RCS holography. The unique 3-D presentation (i.e., typically containing 524,288 RCS values for a 1024 (times) 512 sampled aperture for every frequency component) illustrates the efficacy of target recognition in terms of its far-field plane wave angular spectrum image. RCS images can then be viewed at different angles for target recognition, etc.

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction

PubMed Central

Li, Zhongke; Yang, Huifang; Lü, Peijun; Wang, Yong; Sun, Yuchun

2015-01-01

Background and Objective To develop a real-time recording system based on computer binocular vision and two-dimensional image feature extraction to accurately record mandibular movement in three dimensions. Methods A computer-based binocular vision device with two digital cameras was used in conjunction with a fixed head retention bracket to track occlusal movement. Software was developed for extracting target spatial coordinates in real time based on two-dimensional image feature recognition. A plaster model of a subject’s upper and lower dentition were made using conventional methods. A mandibular occlusal splint was made on the plaster model, and then the occlusal surface was removed. Temporal denture base resin was used to make a 3-cm handle extending outside the mouth connecting the anterior labial surface of the occlusal splint with a detection target with intersecting lines designed for spatial coordinate extraction. The subject's head was firmly fixed in place, and the occlusal splint was fully seated on the mandibular dentition. The subject was then asked to make various mouth movements while the mandibular movement target locus point set was recorded. Comparisons between the coordinate values and the actual values of the 30 intersections on the detection target were then analyzed using paired t-tests. Results The three-dimensional trajectory curve shapes of the mandibular movements were consistent with the respective subject movements. Mean XYZ coordinate values and paired t-test results were as follows: X axis: -0.0037 ± 0.02953, P = 0.502; Y axis: 0.0037 ± 0.05242, P = 0.704; and Z axis: 0.0007 ± 0.06040, P = 0.952. The t-test result showed that the coordinate values of the 30 cross points were considered statistically no significant. (P<0.05) Conclusions Use of a real-time recording system of three-dimensional mandibular movement based on computer binocular vision and two-dimensional image feature recognition technology produced a recording accuracy of approximately ± 0.1 mm, and is therefore suitable for clinical application. Certainly, further research is necessary to confirm the clinical applications of the method. PMID:26375800

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

Diode/magnetic tunnel junction cell for fully scalable matrix-based biochip

NASA Astrophysics Data System (ADS)

Cardoso, F. A.; Ferreira, H. A.; Conde, J. P.; Chu, V.; Freitas, P. P.; Vidal, D.; Germano, J.; Sousa, L.; Piedade, M. S.; Costa, B. A.; Lemos, J. M.

2006-04-01

Magnetoresistive biochips have been recently introduced for the detection of biomolecular recognition. In this work, the detection site incorporates a thin-film diode in series with a magnetic tunnel junction (MTJ), leading to a matrix-based biochip that can be easily scaled up to screen large numbers of different target analytes. The fabricated 16×16 cell matrix integrates hydrogenated amorphous silicon (a-Si:H) diodes with aluminum oxide barrier MTJ. Each detection site also includes a U-shaped current line for magnetically assisted target concentration at probe sites. The biochip is being integrated in a portable, credit card size electronics control platform. Detection of 250 nm diameter magnetic nanoparticles by one of the matrix cells is demonstrated.

Recognition of upper airway and surrounding structures at MRI in pediatric PCOS and OSAS

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, J. K.; Odhner, D.; Sin, Sanghun; Arens, Raanan

2013-03-01

Obstructive Sleep Apnea Syndrome (OSAS) is common in obese children with risk being 4.5 fold compared to normal control subjects. Polycystic Ovary Syndrome (PCOS) has recently been shown to be associated with OSAS that may further lead to significant cardiovascular and neuro-cognitive deficits. We are investigating image-based biomarkers to understand the architectural and dynamic changes in the upper airway and the surrounding hard and soft tissue structures via MRI in obese teenage children to study OSAS. At the previous SPIE conferences, we presented methods underlying Fuzzy Object Models (FOMs) for Automatic Anatomy Recognition (AAR) based on CT images of the thorax and the abdomen. The purpose of this paper is to demonstrate that the AAR approach is applicable to a different body region and image modality combination, namely in the study of upper airway structures via MRI. FOMs were built hierarchically, the smaller sub-objects forming the offspring of larger parent objects. FOMs encode the uncertainty and variability present in the form and relationships among the objects over a study population. Totally 11 basic objects (17 including composite) were modeled. Automatic recognition for the best pose of FOMs in a given image was implemented by using four methods - a one-shot method that does not require search, another three searching methods that include Fisher Linear Discriminate (FLD), a b-scale energy optimization strategy, and optimum threshold recognition method. In all, 30 multi-fold cross validation experiments based on 15 patient MRI data sets were carried out to assess the accuracy of recognition. The results indicate that the objects can be recognized with an average location error of less than 5 mm or 2-3 voxels. Then the iterative relative fuzzy connectedness (IRFC) algorithm was adopted for delineation of the target organs based on the recognized results. The delineation results showed an overall FP and TP volume fraction of 0.02 and 0.93.

Improved specificity of TALE-based genome editing using an expanded RVD repertoire.

PubMed

Miller, Jeffrey C; Zhang, Lei; Xia, Danny F; Campo, John J; Ankoudinova, Irina V; Guschin, Dmitry Y; Babiarz, Joshua E; Meng, Xiangdong; Hinkley, Sarah J; Lam, Stephen C; Paschon, David E; Vincent, Anna I; Dulay, Gladys P; Barlow, Kyle A; Shivak, David A; Leung, Elo; Kim, Jinwon D; Amora, Rainier; Urnov, Fyodor D; Gregory, Philip D; Rebar, Edward J

2015-05-01

Transcription activator-like effector (TALE) proteins have gained broad appeal as a platform for targeted DNA recognition, largely owing to their simple rules for design. These rules relate the base specified by a single TALE repeat to the identity of two key residues (the repeat variable diresidue, or RVD) and enable design for new sequence targets via modular shuffling of these units. A key limitation of these rules is that their simplicity precludes options for improving designs that are insufficiently active or specific. Here we address this limitation by developing an expanded set of RVDs and applying them to improve the performance of previously described TALEs. As an extreme example, total conversion of a TALE nuclease to new RVDs substantially reduced off-target cleavage in cellular studies. By providing new RVDs and design strategies, these studies establish options for developing improved TALEs for broader application across medicine and biotechnology.