Recognizing suspicious activities in infrared imagery using appearance-based features and the theory of hidden conditional random fields for outdoor perimeter surveillance

NASA Astrophysics Data System (ADS)

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

2015-11-01

This work aims to present an extended framework for automatically recognizing suspicious activities in outdoor perimeter surveilling systems based on infrared video processing. By combining size-, speed-, and appearance-based features, like the local phase quantization and the histograms of oriented gradients, actions of small duration are recognized and used as input, along with spatial information, for modeling target activities using the theory of hidden conditional random fields (HCRFs). HCRFs are used to classify an observation sequence into the most appropriate activity label class, thus discriminating high-risk activities like trespassing from zero risk activities, such as loitering outside the perimeter. The effectiveness of this approach is demonstrated with experimental results in various scenarios that represent suspicious activities in perimeter surveillance systems.

Is semantic priming (ir)rational? Insights from the speeded word fragment completion task.

PubMed

Heyman, Tom; Hutchison, Keith A; Storms, Gert

2016-10-01

Semantic priming, the phenomenon that a target is recognized faster if it is preceded by a semantically related prime, is a well-established effect. However, the mechanisms producing semantic priming are subject of debate. Several theories assume that the underlying processes are controllable and tuned to prime utility. In contrast, purely automatic processes, like automatic spreading activation, should be independent of the prime's usefulness. The present study sought to disentangle both accounts by creating a situation where prime processing is actually detrimental. Specifically, participants were asked to quickly complete word fragments with either the letter a or e (e.g., sh_ve to be completed as shave). Critical fragments were preceded by a prime that was either related (e.g., push) or unrelated (write) to a prohibited completion of the target (e.g., shove). In 2 experiments, we found a significant inhibitory priming effect, which is inconsistent with purely "rational" explanations of semantic priming. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

38 CFR 51.31 - Automatic recognition.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) PER DIEM FOR NURSING HOME CARE OF VETERANS IN STATE HOMES Obtaining Per Diem for Nursing Home Care in... that already is recognized by VA as a State home for nursing home care at the time this part becomes effective, automatically will continue to be recognized as a State home for nursing home care but will be...

38 CFR 51.31 - Automatic recognition.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) PER DIEM FOR NURSING HOME CARE OF VETERANS IN STATE HOMES Obtaining Per Diem for Nursing Home Care in... that already is recognized by VA as a State home for nursing home care at the time this part becomes effective, automatically will continue to be recognized as a State home for nursing home care but will be...

38 CFR 51.31 - Automatic recognition.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) PER DIEM FOR NURSING HOME CARE OF VETERANS IN STATE HOMES Obtaining Per Diem for Nursing Home Care in... that already is recognized by VA as a State home for nursing home care at the time this part becomes effective, automatically will continue to be recognized as a State home for nursing home care but will be...

38 CFR 51.31 - Automatic recognition.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) PER DIEM FOR NURSING HOME CARE OF VETERANS IN STATE HOMES Obtaining Per Diem for Nursing Home Care in... that already is recognized by VA as a State home for nursing home care at the time this part becomes effective, automatically will continue to be recognized as a State home for nursing home care but will be...

38 CFR 51.31 - Automatic recognition.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) PER DIEM FOR NURSING HOME CARE OF VETERANS IN STATE HOMES Obtaining Per Diem for Nursing Home Care in... that already is recognized by VA as a State home for nursing home care at the time this part becomes effective, automatically will continue to be recognized as a State home for nursing home care but will be...

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.

Automatic speech recognition and training for severely dysarthric users of assistive technology: the STARDUST project.

PubMed

Parker, Mark; Cunningham, Stuart; Enderby, Pam; Hawley, Mark; Green, Phil

2006-01-01

The STARDUST project developed robust computer speech recognizers for use by eight people with severe dysarthria and concomitant physical disability to access assistive technologies. Independent computer speech recognizers trained with normal speech are of limited functional use by those with severe dysarthria due to limited and inconsistent proximity to "normal" articulatory patterns. Severe dysarthric output may also be characterized by a small mass of distinguishable phonetic tokens making the acoustic differentiation of target words difficult. Speaker dependent computer speech recognition using Hidden Markov Models was achieved by the identification of robust phonetic elements within the individual speaker output patterns. A new system of speech training using computer generated visual and auditory feedback reduced the inconsistent production of key phonetic tokens over time.

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

PubMed Central

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

2018-01-01

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

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.

[Schizophrenia and semantic priming effects].

PubMed

Lecardeur, L; Giffard, B; Eustache, F; Dollfus, S

2006-01-01

This article is a review of studies using the semantic priming paradigm to assess the functioning of semantic memory in schizophrenic patients. Semantic priming describes the phenomenon of increasing the speed with which a string of letters (the target) is recognized as a word (lexical decision task) by presenting to the subject a semantically related word (the prime) prior to the appearance of the target word. This semantic priming is linked to both automatic and controlled processes depending on experimental conditions (stimulus onset asynchrony (SOA), percentage of related words and explicit memory instructions). Automatic process observed with short SOA, low related word percentage and instructions asking only to process the target, could be linked to the "automatic spreading activation" through the semantic network. Controlled processes involve "semantic matching" (the number of related and unrelated pairs influences the subjects decision) and "expectancy" (the prime leads the subject to generate an expectancy set of potential target to the prime). These processes can be observed whatever the SOA for the former and with long SOA for the later, but both with only high related word percentage and explicit memory instructions. Studies evaluating semantic priming effects in schizophrenia show conflicting results: schizophrenic patients can present hyperpriming (semantic priming effect is larger in patients than in controls), hypopriming (semantic priming effect is lower in patients than in controls) or equal semantic priming effects compared to control subjects. These results could be associated to a global impairment of controlled processes in schizophrenia, essentially to a dysfunction of semantic matching process. On the other hand, efficiency of semantic automatic spreading activation process is controversial. These discrepancies could be linked to the different experimental conditions used (duration of SOA, proportion of related pairs and instructions), which influence on the degree of involvement of controlled processes and therefore prevent to really assess its functioning. In addition, manipulations of the relation between prime and target (semantic distance, type of semantic relation and strength of semantic relation) seem to influence reaction times. However, the relation between prime and target (mediated priming) frequently used could not be the most relevant relation to understand the way of spreading of activation in semantic network in patients with schizophrenia. Finally, patients with formal thought disorders present particularly high priming effects relative to controls. These abnormal semantic priming effects could reflect a dysfunction of automatic spreading activation process and consequently an exaggerated diffusion of activation in the semantic network. In the future, the inclusion of different groups schizophrenic subjects could allow us to determine whether semantic memory disorders are pathognomonic or specific of a particular group of patients with schizophrenia.

Research on application of LADAR in ground vehicle recognition

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Multi-brain fusion and applications to intelligence analysis

NASA Astrophysics Data System (ADS)

Stoica, A.; Matran-Fernandez, A.; Andreou, D.; Poli, R.; Cinel, C.; Iwashita, Y.; Padgett, C.

2013-05-01

In a rapid serial visual presentation (RSVP) images are shown at an extremely rapid pace. Yet, the images can still be parsed by the visual system to some extent. In fact, the detection of specific targets in a stream of pictures triggers a characteristic electroencephalography (EEG) response that can be recognized by a brain-computer interface (BCI) and exploited for automatic target detection. Research funded by DARPA's Neurotechnology for Intelligence Analysts program has achieved speed-ups in sifting through satellite images when adopting this approach. This paper extends the use of BCI technology from individual analysts to collaborative BCIs. We show that the integration of information in EEGs collected from multiple operators results in performance improvements compared to the single-operator case.

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.

Automatic Title Generation for Spoken Broadcast News

DTIC Science & Technology

2001-01-01

degrades much less with speech -recognized transcripts. Meanwhile, even though KNN performance not as well as TF.IDF and NBL in terms of F1 metric, it...test corpus of 1006 broadcast news documents, comparing the results over manual transcription to the results over automatically recognized speech . We...use both F1 and the average number of correct title words in the correct order as metric. Overall, the results show that title generation for speech

Development of A Two-Stage Procedure for the Automatic Recognition of Dysfluencies in the Speech of Children Who Stutter: I. Psychometric Procedures Appropriate for Selection of Training Material for Lexical Dysfluency Classifiers

PubMed Central

Howell, Peter; Sackin, Stevie; Glenn, Kazan

2007-01-01

This program of work is intended to develop automatic recognition procedures to locate and assess stuttered dysfluencies. This and the following article together, develop and test recognizers for repetitions and prolongations. The automatic recognizers classify the speech in two stages: In the first, the speech is segmented and in the second the segments are categorized. The units that are segmented are words. Here assessments by human judges on the speech of 12 children who stutter are described using a corresponding procedure. The accuracy of word boundary placement across judges, categorization of the words as fluent, repetition or prolongation, and duration of the different fluency categories are reported. These measures allow reliable instances of repetitions and prolongations to be selected for training and assessing the recognizers in the subsequent paper. PMID:9328878

Automatic recognition and analysis of synapses. [in brain tissue

NASA Technical Reports Server (NTRS)

Ungerleider, J. A.; Ledley, R. S.; Bloom, F. E.

1976-01-01

An automatic system for recognizing synaptic junctions would allow analysis of large samples of tissue for the possible classification of specific well-defined sets of synapses based upon structural morphometric indices. In this paper the three steps of our system are described: (1) cytochemical tissue preparation to allow easy recognition of the synaptic junctions; (2) transmitting the tissue information to a computer; and (3) analyzing each field to recognize the synapses and make measurements on them.

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.

The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences.

PubMed

Chaspari, Theodora; Soldatos, Constantin; Maragos, Petros

2015-01-01

The development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders. Following its development, presented with, the Athens Emotional States Inventory (AESI) proposes the design, recording and validation of an audiovisual database for five emotional states: anger, fear, joy, sadness and neutral. The items of the AESI consist of sentences each having content indicative of the corresponding emotion. Emotional content was assessed through a survey of 40 young participants with a questionnaire following the Latin square design. The emotional sentences that were correctly identified by 85% of the participants were recorded in a soundproof room with microphones and cameras. A preliminary validation of AESI is performed through automatic emotion recognition experiments from speech. The resulting database contains 696 recorded utterances in Greek language by 20 native speakers and has a total duration of approximately 28 min. Speech classification results yield accuracy up to 75.15% for automatically recognizing the emotions in AESI. These results indicate the usefulness of our approach for collecting emotional data with reliable content, balanced across classes and with reduced environmental variability.

Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer

DTIC Science & Technology

2016-06-01

TECHNICAL REPORT Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar...Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer Leon Vaizer, Jesse Angle, Neil...of Magnetic Dipole Targets Using LSG i June 2016 TABLE OF CONTENTS INTRODUCTION

Non-Target Screening of Veterinary Drugs Using Tandem Mass Spectrometry on SmartMass

NASA Astrophysics Data System (ADS)

Xia, Bing; Liu, Xin; Gu, Yu-Cheng; Zhang, Zhao-Hui; Wang, Hai-Yan; Ding, Li-Sheng; Zhou, Yan

2013-05-01

Non-target screening of veterinary drugs using tandem mass spectrometric data was performed on the SmartMass platform. This newly developed software uses the characteristic fragmentation patterns (CFP) to identify chemicals, especially those containing particular substructures. A mixture of 17 sulfonamides was separated by ultra performance liquid chromatography (UPLC), and SmartMass was used to process the tandem mass spectrometry (MS/MS) data acquired on an Orbitrap mass spectrometer. The data were automatically extracted, and each sulfonamide was recognized and analyzed with a prebuilt analysis rule. By using this software, over 98 % of the false candidate structures were eliminated, and all the correct structures were found within the top 10 of the ranking lists. Furthermore, SmartMass could also be used to identify slightly modified contraband drugs and metabolites with simple prebuilt rules. [Figure not available: see fulltext.

Automatic recognition of lactating sow behaviors through depth image processing

USDA-ARS?s Scientific Manuscript database

Manual observation and classification of animal behaviors is laborious, time-consuming, and of limited ability to process large amount of data. A computer vision-based system was developed that automatically recognizes sow behaviors (lying, sitting, standing, kneeling, feeding, drinking, and shiftin...

Automated Steering Control Design by Visual Feedback Approach —System Identification and Control Experiments with a Radio-Controlled Car—

NASA Astrophysics Data System (ADS)

Fujiwara, Yukihiro; Yoshii, Masakazu; Arai, Yasuhito; Adachi, Shuichi

Advanced safety vehicle(ASV)assists drivers’ manipulation to avoid trafic accidents. A variety of researches on automatic driving systems are necessary as an element of ASV. Among them, we focus on visual feedback approach in which the automatic driving system is realized by recognizing road trajectory using image information. The purpose of this paper is to examine the validity of this approach by experiments using a radio-controlled car. First, a practical image processing algorithm to recognize white lines on the road is proposed. Second, a model of the radio-controlled car is built by system identication experiments. Third, an automatic steering control system is designed based on H∞ control theory. Finally, the effectiveness of the designed control system is examined via traveling experiments.

Automatic panoramic thermal integrated sensor

NASA Astrophysics Data System (ADS)

Gutin, Mikhail A.; Tsui, Eddy K.; Gutin, Olga N.

2005-05-01

Historically, the US Army has recognized the advantages of panoramic imagers with high image resolution: increased area coverage with fewer cameras, instantaneous full horizon detection, location and tracking of multiple targets simultaneously, extended range, and others. The novel ViperViewTM high-resolution panoramic thermal imager is the heart of the Automatic Panoramic Thermal Integrated Sensor (APTIS), being jointly developed by Applied Science Innovative, Inc. (ASI) and the Armament Research, Development and Engineering Center (ARDEC) in support of the Future Combat Systems (FCS) and the Intelligent Munitions Systems (IMS). The APTIS is anticipated to operate as an intelligent node in a wireless network of multifunctional nodes that work together to improve situational awareness (SA) in many defense and offensive operations, as well as serve as a sensor node in tactical Intelligence Surveillance Reconnaissance (ISR). The ViperView is as an aberration-corrected omnidirectional imager with small optics designed to match the resolution of a 640x480 pixels IR camera with improved image quality for longer range target detection, classification, and tracking. The same approach is applicable to panoramic cameras working in the visible spectral range. Other components of the ATPIS sensor suite include ancillary sensors, advanced power management, and wakeup capability. This paper describes the development status of the APTIS system.

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.

Disadvantageous associations: Reversible spatial cueing effects in a discrimination task

PubMed Central

Nico, Daniele; Daprati, Elena

2015-01-01

Current theories describe learning in terms of cognitive or associative mechanisms. To assess whether cognitive mechanisms interact with automaticity of associative processes we devised a shape-discrimination task in which participants received both explicit instructions and implicit information. Instructions further allowed for the inference that a first event would precede the target. Albeit irrelevant to respond, this event acted as response prime and implicit spatial cue (i.e. it predicted target location). To modulate cognitive involvement, in three experiments we manipulated modality and salience of the spatial cue. Results always showed evidence for a priming effect, confirming that the first stimulus was never ignored. More importantly, although participants failed to consciously recognize the association, responses to spatially cued trials became either slower or faster depending on salience of the first event. These findings provide an empirical demonstration that cognitive and associative learning mechanisms functionally co-exist and interact to regulate behaviour. PMID:26534830

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

The advanced linked extended reconnaissance and targeting technology demonstration project

NASA Astrophysics Data System (ADS)

Cruickshank, James; de Villers, Yves; Maheux, Jean; Edwards, Mark; Gains, David; Rea, Terry; Banbury, Simon; Gauthier, Michelle

2007-06-01

The Advanced Linked Extended Reconnaissance & Targeting (ALERT) Technology Demonstration (TD) project is addressing key operational needs of the future Canadian Army's Surveillance and Reconnaissance forces by fusing multi-sensor and tactical data, developing automated processes, and integrating beyond line-of-sight sensing. We discuss concepts for displaying and fusing multi-sensor and tactical data within an Enhanced Operator Control Station (EOCS). The sensor data can originate from the Coyote's own visible-band and IR cameras, laser rangefinder, and ground-surveillance radar, as well as beyond line-of-sight systems such as a mini-UAV and unattended ground sensors. The authors address technical issues associated with the use of fully digital IR and day video cameras and discuss video-rate image processing developed to assist the operator to recognize poorly visible targets. Automatic target detection and recognition algorithms processing both IR and visible-band images have been investigated to draw the operator's attention to possible targets. The machine generated information display requirements are presented with the human factors engineering aspects of the user interface in this complex environment, with a view to establishing user trust in the automation. The paper concludes with a summary of achievements to date and steps to project completion.

A knowledge engineering approach to recognizing and extracting sequences of nucleic acids from scientific literature.

PubMed

García-Remesal, Miguel; Maojo, Victor; Crespo, José

2010-01-01

In this paper we present a knowledge engineering approach to automatically recognize and extract genetic sequences from scientific articles. To carry out this task, we use a preliminary recognizer based on a finite state machine to extract all candidate DNA/RNA sequences. The latter are then fed into a knowledge-based system that automatically discards false positives and refines noisy and incorrectly merged sequences. We created the knowledge base by manually analyzing different manuscripts containing genetic sequences. Our approach was evaluated using a test set of 211 full-text articles in PDF format containing 3134 genetic sequences. For such set, we achieved 87.76% precision and 97.70% recall respectively. This method can facilitate different research tasks. These include text mining, information extraction, and information retrieval research dealing with large collections of documents containing genetic sequences.

Second Language Learners and Speech Act Comprehension

ERIC Educational Resources Information Center

Holtgraves, Thomas

2007-01-01

Recognizing the specific speech act ( Searle, 1969) that a speaker performs with an utterance is a fundamental feature of pragmatic competence. Past research has demonstrated that native speakers of English automatically recognize speech acts when they comprehend utterances (Holtgraves & Ashley, 2001). The present research examined whether this…

Automatic Identification and Organization of Index Terms for Interactive Browsing.

ERIC Educational Resources Information Center

Wacholder, Nina; Evans, David K.; Klavans, Judith L.

The potential of automatically generated indexes for information access has been recognized for several decades, but the quantity of text and the ambiguity of natural language processing have made progress at this task more difficult than was originally foreseen. Recently, a body of work on development of interactive systems to support phrase…

Automatic image hanging protocol for chest radiographs in PACS.

PubMed

Luo, Hui; Hao, Wei; Foos, David H; Cornelius, Craig W

2006-04-01

Chest radiography is one of the most widely used techniques in diagnostic imaging. It comprises at least one-third of all diagnostic radiographic procedures in hospitals. However, in the picture archive and communication system, images are often stored with the projection and orientation unknown or mislabeled, which causes inefficiency for radiologists' interpretation. To address this problem, an automatic hanging protocol for chest radiographs is presented. The method targets the most effective region in a chest radiograph, and extracts a set of size-, rotation-, and translation-invariant features from it. Then, a well-trained classifier is used to recognize the projection. The orientation of the radiograph is later identified by locating the neck, heart, and abdomen positions in the radiographs. Initial experiments are performed on the radiographs collected from daily routine chest exams in hospitals and show promising results. Using the presented protocol, 98.2% of all cases could be hung correctly on projection view (without protocol, 62%), and 96.1% had correct orientation (without protocol, 75%). A workflow study on the protocol also demonstrates a significant improvement in efficiency for image display.

Improvement of Handwriting Automaticity among Children Treated for Graphomotor Difficulties over a Period of Six Months

ERIC Educational Resources Information Center

Wicki, Werner; Hurschler Lichtsteiner, Sibylle

2018-01-01

Although fluency and automaticity of handwriting have been recognized as important research topics for 30 years, empirical data on respective developmental courses among typically developing children as well as clinical samples have remained very limited. To fill this gap, this study investigates the development of handwriting automaticity…

Real-Time Reconnaissance-A Systems Look At Advanced Technology

NASA Astrophysics Data System (ADS)

Lapp, Henry

1981-12-01

An important role for reconnaissance is the location and identification of targets in real time. Current technology has been compartmented into sensors, automatic target recognizers, data links, ground exploitation and finally dissemination. In the days of bring home film recce, this segmentation of functions was appropriate. With the current emphasis on real time decision making from outputs of high resolution sensors this thinking has to be re-analyzed. A total systems approach to data management must be employed using the constraints imposed by technology as well as the atmosphere, survivable flight profiles, and the human workload. This paper will analyze the target acquisition through exploitation tasks and discuss the current advanced development technology that are applicable. A philosophy of processing data to get information as early as possible in the data handling chain is examined in the context of ground exploitation and dissemination needs. Examples of how the various real time sensors (screeners and processors), jam resistant data links and near real time ground data handling systems fit into this scenario are discussed. Specific DoD programs will be used to illustrate the credibility of this integrated approach.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark

2003-01-01

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.

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

Children's Recognition of Disgust in Others

ERIC Educational Resources Information Center

Widen, Sherri C.; Russell, James A.

2013-01-01

Disgust has been theorized to be a basic emotion with a facial signal that is easily, universally, automatically, and perhaps innately recognized by observers from an early age. This article questions one key part of that theory: the hypothesis that children recognize disgust from its purported facial signal. Over the first 5 years, children…

Automated analysis of whole skeletal muscle for muscular atrophy detection of ALS in whole-body CT images: preliminary study

NASA Astrophysics Data System (ADS)

Kamiya, Naoki; Ieda, Kosuke; Zhou, Xiangrong; Yamada, Megumi; Kato, Hiroki; Muramatsu, Chisako; Hara, Takeshi; Miyoshi, Toshiharu; Inuzuka, Takashi; Matsuo, Masayuki; Fujita, Hiroshi

2017-03-01

Amyotrophic lateral sclerosis (ALS) causes functional disorders such as difficulty in breathing and swallowing through the atrophy of voluntary muscles. ALS in its early stages is difficult to diagnose because of the difficulty in differentiating it from other muscular diseases. In addition, image inspection methods for aggressive diagnosis for ALS have not yet been established. The purpose of this study is to develop an automatic analysis system of the whole skeletal muscle to support the early differential diagnosis of ALS using whole-body CT images. In this study, the muscular atrophy parts including ALS patients are automatically identified by recognizing and segmenting whole skeletal muscle in the preliminary steps. First, the skeleton is identified by its gray value information. Second, the initial area of the body cavity is recognized by the deformation of the thoracic cavity based on the anatomical segmented skeleton. Third, the abdominal cavity boundary is recognized using ABM for precisely recognizing the body cavity. The body cavity is precisely recognized by non-rigid registration method based on the reference points of the abdominal cavity boundary. Fourth, the whole skeletal muscle is recognized by excluding the skeleton, the body cavity, and the subcutaneous fat. Additionally, the areas of muscular atrophy including ALS patients are automatically identified by comparison of the muscle mass. The experiments were carried out for ten cases with abnormality in the skeletal muscle. Global recognition and segmentation of the whole skeletal muscle were well realized in eight cases. Moreover, the areas of muscular atrophy including ALS patients were well identified in the lower limbs. As a result, this study indicated the basic technology to detect the muscle atrophy including ALS. In the future, it will be necessary to consider methods to differentiate other kinds of muscular atrophy as well as the clinical application of this detection method for early ALS detection and examine a large number of cases with stage and disease type.

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

Automatic attentional orienting to other people's gaze in schizophrenia.

PubMed

Langdon, Robyn; Seymour, Kiley; Williams, Tracey; Ward, Philip B

2017-08-01

Explicit tests of social cognition have revealed pervasive deficits in schizophrenia. Less is known of automatic social cognition in schizophrenia. We used a spatial orienting task to investigate automatic shifts of attention cued by another person's eye gaze in 29 patients and 28 controls. Central photographic images of a face with eyes shifted left or right, or looking straight ahead, preceded targets that appeared left or right of the cue. To examine automatic effects, cue direction was non-predictive of target location. Cue-target intervals were 100, 300, and 800 ms. In non-social control trials, arrows replaced eye-gaze cues. Both groups showed automatic attentional orienting indexed by faster reaction times (RTs) when arrows were congruent with target location across all cue-target intervals. Similar congruency effects were seen for eye-shift cues at 300 and 800 ms intervals, but patients showed significantly larger congruency effects at 800 ms, which were driven by delayed responses to incongruent target locations. At short 100-ms cue-target intervals, neither group showed faster RTs for congruent than for incongruent eye-shift cues, but patients were significantly slower to detect targets after direct-gaze cues. These findings conflict with previous studies using schematic line drawings of eye-shifts that have found automatic attentional orienting to be reduced in schizophrenia. Instead, our data indicate that patients display abnormalities in responding to gaze direction at various stages of gaze processing-reflected by a stronger preferential capture of attention by another person's direct eye contact at initial stages of gaze processing and difficulties disengaging from a gazed-at location once shared attention is established.

Methods for automatically analyzing humpback song units.

PubMed

Rickwood, Peter; Taylor, Andrew

2008-03-01

This paper presents mathematical techniques for automatically extracting and analyzing bioacoustic signals. Automatic techniques are described for isolation of target signals from background noise, extraction of features from target signals and unsupervised classification (clustering) of the target signals based on these features. The only user-provided inputs, other than raw sound, is an initial set of signal processing and control parameters. Of particular note is that the number of signal categories is determined automatically. The techniques, applied to hydrophone recordings of humpback whales (Megaptera novaeangliae), produce promising initial results, suggesting that they may be of use in automated analysis of not only humpbacks, but possibly also in other bioacoustic settings where automated analysis is desirable.

Rendezvous terminal phase automatic braking sequencing and targeting. [for space shuttle orbiter

NASA Technical Reports Server (NTRS)

Kachmar, P. M.

1973-01-01

The purpose of the rendezvous terminal phase braking program is to provide the means of automatically bringing the primary orbiter within desired station keeping boundaries relative to the target satellite. A detailed discussion is presented on the braking program and its navigation, targeting, and guidance functions.

Automatic target alignment of the Helios laser system

NASA Astrophysics Data System (ADS)

Liberman, I.; Viswanathan, V. K.; Klein, M.; Seery, B. D.

1980-05-01

An automatic target-alignment technique for the Helios laser facility is reported and verified experimentally. The desired alignment condition is completely described by an autocollimation test. A computer program examines the autocollimated return pattern from the surrogate target and correctly describes any changes required in mirror orientation to yield optimum target alignment with either aberrated or misaligned beams. Automated on-line target alignment is thus shown to be feasible.

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.

Does training under consistent mapping conditions lead to automatic attention attraction to targets in search tasks?

PubMed

Lefebvre, Christine; Cousineau, Denis; Larochelle, Serge

2008-11-01

Schneider and Shiffrin (1977) proposed that training under consistent stimulus-response mapping (CM) leads to automatic target detection in search tasks. Other theories, such as Treisman and Gelade's (1980) feature integration theory, consider target-distractor discriminability as the main determinant of search performance. The first two experiments pit these two principles against each other. The results show that CM training is neither necessary nor sufficient to achieve optimal search performance. Two other experiments examine whether CM trained targets, presented as distractors in unattended display locations, attract attention away from current targets. The results are again found to vary with target-distractor similarity. Overall, the present study strongly suggests that CM training does not invariably lead to automatic attention attraction in search tasks.

On the recognition of emotional vocal expressions: motivations for a holistic approach.

PubMed

Esposito, Anna; Esposito, Antonietta M

2012-10-01

Human beings seem to be able to recognize emotions from speech very well and information communication technology aims to implement machines and agents that can do the same. However, to be able to automatically recognize affective states from speech signals, it is necessary to solve two main technological problems. The former concerns the identification of effective and efficient processing algorithms capable of capturing emotional acoustic features from speech sentences. The latter focuses on finding computational models able to classify, with an approximation as good as human listeners, a given set of emotional states. This paper will survey these topics and provide some insights for a holistic approach to the automatic analysis, recognition and synthesis of affective states.

Patients with schizophrenia do not preserve automatic grouping when mentally re-grouping figures: shedding light on an ignored difficulty.

PubMed

Giersch, Anne; van Assche, Mitsouko; Capa, Rémi L; Marrer, Corinne; Gounot, Daniel

2012-01-01

Looking at a pair of objects is easy when automatic grouping mechanisms bind these objects together, but visual exploration can also be more flexible. It is possible to mentally "re-group" two objects that are not only separate but belong to different pairs of objects. "Re-grouping" is in conflict with automatic grouping, since it entails a separation of each item from the set it belongs to. This ability appears to be impaired in patients with schizophrenia. Here we check if this impairment is selective, which would suggest a dissociation between grouping and "re-grouping," or if it impacts on usual, automatic grouping, which would call for a better understanding of the interactions between automatic grouping and "re-grouping." Sixteen outpatients with schizophrenia and healthy controls had to identify two identical and contiguous target figures within a display of circles and squares alternating around a fixation point. Eye-tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. Identical figures were grouped by a connector (grouped automatically) or not (to be re-grouped). Attention modulation of automatic grouping was tested by manipulating the proportion of connected and unconnected targets, thus prompting subjects to focalize on either connected or unconnected pairs. Both groups were sensitive to automatic grouping in most conditions, but patients were unusually slowed down for connected targets while focalizing on unconnected pairs. In addition, this unusual effect occurred only when targets were presented within the same hemifield. Patients and controls differed on this asymmetry between within- and across-hemifield presentation, suggesting that patients with schizophrenia do not re-group figures in the same way as controls do. We discuss possible implications on how "re-grouping" ties in with ongoing, automatic perception in healthy volunteers.

Patients with Schizophrenia Do Not Preserve Automatic Grouping When Mentally Re-Grouping Figures: Shedding Light on an Ignored Difficulty

PubMed Central

Giersch, Anne; van Assche, Mitsouko; Capa, Rémi L.; Marrer, Corinne; Gounot, Daniel

2012-01-01

Looking at a pair of objects is easy when automatic grouping mechanisms bind these objects together, but visual exploration can also be more flexible. It is possible to mentally “re-group” two objects that are not only separate but belong to different pairs of objects. “Re-grouping” is in conflict with automatic grouping, since it entails a separation of each item from the set it belongs to. This ability appears to be impaired in patients with schizophrenia. Here we check if this impairment is selective, which would suggest a dissociation between grouping and “re-grouping,” or if it impacts on usual, automatic grouping, which would call for a better understanding of the interactions between automatic grouping and “re-grouping.” Sixteen outpatients with schizophrenia and healthy controls had to identify two identical and contiguous target figures within a display of circles and squares alternating around a fixation point. Eye-tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. Identical figures were grouped by a connector (grouped automatically) or not (to be re-grouped). Attention modulation of automatic grouping was tested by manipulating the proportion of connected and unconnected targets, thus prompting subjects to focalize on either connected or unconnected pairs. Both groups were sensitive to automatic grouping in most conditions, but patients were unusually slowed down for connected targets while focalizing on unconnected pairs. In addition, this unusual effect occurred only when targets were presented within the same hemifield. Patients and controls differed on this asymmetry between within- and across-hemifield presentation, suggesting that patients with schizophrenia do not re-group figures in the same way as controls do. We discuss possible implications on how “re-grouping” ties in with ongoing, automatic perception in healthy volunteers. PMID:22912621

Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review.

PubMed

Canan, Chelsea; Polinski, Jennifer M; Alexander, G Caleb; Kowal, Mary K; Brennan, Troyen A; Shrank, William H

2017-11-01

Improved methods to identify nonmedical opioid use can help direct health care resources to individuals who need them. Automated algorithms that use large databases of electronic health care claims or records for surveillance are a potential means to achieve this goal. In this systematic review, we reviewed the utility, attempts at validation, and application of such algorithms to detect nonmedical opioid use. We searched PubMed and Embase for articles describing automatable algorithms that used electronic health care claims or records to identify patients or prescribers with likely nonmedical opioid use. We assessed algorithm development, validation, and performance characteristics and the settings where they were applied. Study variability precluded a meta-analysis. Of 15 included algorithms, 10 targeted patients, 2 targeted providers, 2 targeted both, and 1 identified medications with high abuse potential. Most patient-focused algorithms (67%) used prescription drug claims and/or medical claims, with diagnosis codes of substance abuse and/or dependence as the reference standard. Eleven algorithms were developed via regression modeling. Four used natural language processing, data mining, audit analysis, or factor analysis. Automated algorithms can facilitate population-level surveillance. However, there is no true gold standard for determining nonmedical opioid use. Users must recognize the implications of identifying false positives and, conversely, false negatives. Few algorithms have been applied in real-world settings. Automated algorithms may facilitate identification of patients and/or providers most likely to need more intensive screening and/or intervention for nonmedical opioid use. Additional implementation research in real-world settings would clarify their utility. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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.

Does flexibility in perceptual organization compete with automatic grouping?

PubMed

van Assche, Mitsouko; Gos, Pierre; Giersch, Anne

2012-02-06

Segregated objects can be sought simultaneously, i.e., mentally "re-grouped." Although the mechanisms underlying such "re-grouping" clearly differ from automatic grouping, it is unclear whether or not the end products of "re-grouping" and automatic grouping are the same. If they are, they would have similar impact on visual organization but would be in conflict. We compared the consequences of grouping and re-grouping on the performance cost induced by stimuli presented across hemifields. Two identical and contiguous target figures had to be identified within a display of circles and squares alternating around a fixation point. Eye tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. A large cost of presenting targets across hemifields was observed. Grouping by connectedness yielded two types of target pair, connected and unconnected. Subjects prioritized unconnected pairs efficiently when prompted to do so, suggesting "re-grouping." However, unlike automatic grouping, this did not affect the cost of across-hemifield presentation. The suggestion is that re-grouping yields different outputs to automatic grouping, such that a fresh representation resulting from re-grouping complements the one resulting from automatic grouping but does not replace it. This is one step toward understanding how our mental exploration of the world ties in and coexists with ongoing perception.

Automatic priming of attentional control by relevant colors.

PubMed

Ansorge, Ulrich; Becker, Stefanie I

2012-01-01

We tested whether color word cues automatically primed attentional control settings during visual search, or whether color words were used in a strategic manner for the control of attention. In Experiment 1, we used color words as cues that were informative or uninformative with respect to the target color. Regardless of the cue's informativeness, distractors similar to the color cue captured more attention. In Experiment 2, the participants either indicated their expectation about the target color or recalled the last target color, which was uncorrelated with the present target color. We observed more attentional capture by distractors that were similar to the participants' predictions and recollections, but no difference between effects of the recollected and predicted colors. In Experiment 3, we used 100%-informative word cues that were congruent with the predicted target color (e.g., the word "red" informed that the target would be red) or incongruent with the predicted target color (e.g., the word "green" informed that the target would be red) and found that informative incongruent word cues primed attention capture by a word-similar distractor. Together, the results suggest that word cues (Exps. 1 and 3) and color representations (Exp. 2) primed attention capture in an automatic manner. This indicates that color cues automatically primed temporary adjustments in attention control settings.

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.

A Familiar-Size Stroop Effect: Real-World Size Is an Automatic Property of Object Representation

ERIC Educational Resources Information Center

Konkle, Talia; Oliva, Aude

2012-01-01

When we recognize an object, do we automatically know how big it is in the world? We employed a Stroop-like paradigm, in which two familiar objects were presented at different visual sizes on the screen. Observers were faster to indicate which was bigger or smaller on the screen when the real-world size of the objects was congruent with the visual…

Automatic recognition of light source from color negative films using sorting classification techniques

NASA Astrophysics Data System (ADS)

Sanger, Demas S.; Haneishi, Hideaki; Miyake, Yoichi

1995-08-01

This paper proposed a simple and automatic method for recognizing the light sources from various color negative film brands by means of digital image processing. First, we stretched the image obtained from a negative based on the standardized scaling factors, then extracted the dominant color component among red, green, and blue components of the stretched image. The dominant color component became the discriminator for the recognition. The experimental results verified that any one of the three techniques could recognize the light source from negatives of any film brands and all brands greater than 93.2 and 96.6% correct recognitions, respectively. This method is significant for the automation of color quality control in color reproduction from color negative film in mass processing and printing machine.

Group Dynamics in Automatic Imitation

PubMed Central

Wilson, Neil; Reddy, Geetha; Catmur, Caroline

2016-01-01

Imitation–matching the configural body movements of another individual–plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach. PMID:27657926

Group Dynamics in Automatic Imitation.

PubMed

Gleibs, Ilka H; Wilson, Neil; Reddy, Geetha; Catmur, Caroline

Imitation-matching the configural body movements of another individual-plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach.

Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

PubMed

Dos Reis, Julio Cesar; Dinh, Duy; Da Silveira, Marcos; Pruski, Cédric; Reynaud-Delaître, Chantal

2015-03-01

Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappings are highly demanded. The accuracy of such methods relies on the available description about the evolution of ontologies, especially regarding concepts involved in mappings. However, from one ontology version to another, a further understanding of ontology changes relevant for supporting mapping adaptation is typically lacking. This research work defines a set of change patterns at the level of concept attributes, and proposes original methods to automatically recognize instances of these patterns based on the similarity between attributes denoting the evolving concepts. This investigation evaluates the benefits of the proposed methods and the influence of the recognized change patterns to select the strategies for mapping adaptation. The summary of the findings is as follows: (1) the Precision (>60%) and Recall (>35%) achieved by comparing manually identified change patterns with the automatic ones; (2) a set of potential impact of recognized change patterns on the way mappings is adapted. We found that the detected correlations cover ∼66% of the mapping adaptation actions with a positive impact; and (3) the influence of the similarity coefficient calculated between concept attributes on the performance of the recognition algorithms. The experimental evaluations conducted with real life science ontologies showed the effectiveness of our approach to accurately characterize ontology evolution at the level of concept attributes. This investigation confirmed the relevance of the proposed change patterns to support decisions on mapping adaptation. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic detection and recognition of signs from natural scenes.

PubMed

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

2004-01-01

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

How automatic is the hand's automatic pilot? Evidence from dual-task studies.

PubMed

McIntosh, Robert D; Mulroue, Amy; Brockmole, James R

2010-10-01

The ability to correct reaching movements for changes in target position has been described as the hand's 'automatic pilot'. These corrections are preconscious and occur by default in double-step reaching tasks, even if the goal is to react to the target jump in some other way, for instance by stopping the movement (STOP instruction). Nonetheless, corrections are strongly modulated by conscious intention: participants make more corrections when asked to follow the target (GO instruction) and can suppress them when explicitly asked not to follow the target (NOGO instruction). We studied the influence of a cognitively demanding (auditory 1-back) task upon correction behaviour under GO, STOP and NOGO instructions. Correction rates under the STOP instruction were unaffected by cognitive load, consistent with the assumption that they reflect the default behaviour of the automatic pilot. Correction rates under the GO instruction were also unaffected, suggesting that minimal cognitive resources are required to enhance online correction. By contrast, cognitive load impeded the ability to suppress online corrections under the NOGO instruction. These data reveal a constitutional bias in the automatic pilot system: intentional suppression of the default correction behaviour is cognitively demanding, but enhancement towards greater responsiveness is seemingly effortless.

General Metropolis-Hastings jump diffusions for automatic target recognition in infrared scenes

NASA Astrophysics Data System (ADS)

Lanterman, Aaron D.; Miller, Michael I.; Snyder, Donald L.

1997-04-01

To locate and recognize ground-based targets in forward- looking IR (FLIR) images, 3D faceted models with associated pose parameters are formulated to accommodate the variability found in FLIR imagery. Taking a Bayesian approach, scenes are simulated from the emissive characteristics of the CAD models and compared with the collected data by a likelihood function based on sensor statistics. This likelihood is combined with a prior distribution defined over the set of possible scenes to form a posterior distribution. To accommodate scenes with variable numbers of targets, the posterior distribution is defined over parameter vectors of varying dimension. An inference algorithm based on Metropolis-Hastings jump- diffusion processes empirically samples from the posterior distribution, generating configurations of templates and transformations that match the collected sensor data with high probability. The jumps accommodate the addition and deletion of targets and the estimation of target identities; diffusions refine the hypotheses by drifting along the gradient of the posterior distribution with respect to the orientation and position parameters. Previous results on jumps strategies analogous to the Metropolis acceptance/rejection algorithm, with proposals drawn from the prior and accepted based on the likelihood, are extended to encompass general Metropolis-Hastings proposal densities. In particular, the algorithm proposes moves by drawing from the posterior distribution over computationally tractible subsets of the parameter space. The algorithm is illustrated by an implementation on a Silicon Graphics Onyx/Reality Engine.

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

NREL and CSIRO Validating Advanced Microgrid Control Solution | Energy

Science.gov Websites

Organisation NREL and CSIRO Validating Advanced Microgrid Control Solution Australia's Commonwealth Scientific microgrid control solution. This technology helps hybrid microgrids to automatically recognize when solar

Stylistic gait synthesis based on hidden Markov models

NASA Astrophysics Data System (ADS)

Tilmanne, Joëlle; Moinet, Alexis; Dutoit, Thierry

2012-12-01

In this work we present an expressive gait synthesis system based on hidden Markov models (HMMs), following and modifying a procedure originally developed for speaking style adaptation, in speech synthesis. A large database of neutral motion capture walk sequences was used to train an HMM of average walk. The model was then used for automatic adaptation to a particular style of walk using only a small amount of training data from the target style. The open source toolkit that we adapted for motion modeling also enabled us to take into account the dynamics of the data and to model accurately the duration of each HMM state. We also address the assessment issue and propose a procedure for qualitative user evaluation of the synthesized sequences. Our tests show that the style of these sequences can easily be recognized and look natural to the evaluators.

Automatic identification of species with neural networks.

PubMed

Hernández-Serna, Andrés; Jiménez-Segura, Luz Fernanda

2014-01-01

A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.

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.

Recent advances in automatic alignment system for the National Ignition Facility

NASA Astrophysics Data System (ADS)

Wilhelmsen, Karl; Awwal, Abdul A. S.; Kalantar, Dan; Leach, Richard; Lowe-Webb, Roger; McGuigan, David; Miller Kamm, Vicki

2011-03-01

The automatic alignment system for the National Ignition Facility (NIF) is a large-scale parallel system that directs all 192 laser beams along the 300-m optical path to a 50-micron focus at target chamber in less than 50 minutes. The system automatically commands 9,000 stepping motors to adjust mirrors and other optics based upon images acquired from high-resolution digital cameras viewing beams at various locations. Forty-five control loops per beamline request image processing services running on a LINUX cluster to analyze these images of the beams and references, and automatically steer the beams toward the target. This paper discusses the upgrades to the NIF automatic alignment system to handle new alignment needs and evolving requirements as related to various types of experiments performed. As NIF becomes a continuously-operated system and more experiments are performed, performance monitoring is increasingly important for maintenance and commissioning work. Data, collected during operations, is analyzed for tuning of the laser and targeting maintenance work. Handling evolving alignment and maintenance needs is expected for the planned 30-year operational life of NIF.

Young Children's Automatic Encoding of Social Categories

ERIC Educational Resources Information Center

Weisman, Kara; Johnson, Marissa V.; Shutts, Kristin

2015-01-01

The present research investigated young children's automatic encoding of two social categories that are highly relevant to adults: gender and race. Three- to 6-year-old participants learned facts about unfamiliar target children who varied in either gender or race and were asked to remember which facts went with which targets. When participants…

Automatic recognition of vector and parallel operations in a higher level language

NASA Technical Reports Server (NTRS)

Schneck, P. B.

1971-01-01

A compiler for recognizing statements of a FORTRAN program which are suited for fast execution on a parallel or pipeline machine such as Illiac-4, Star or ASC is described. The technique employs interval analysis to provide flow information to the vector/parallel recognizer. Where profitable the compiler changes scalar variables to subscripted variables. The output of the compiler is an extension to FORTRAN which shows parallel and vector operations explicitly.

Automatic building identification under bomb damage conditions

NASA Astrophysics Data System (ADS)

Woodley, Robert; Noll, Warren; Barker, Joseph; Wunsch, Donald C., II

2009-05-01

Given the vast amount of image intelligence utilized in support of planning and executing military operations, a passive automated image processing capability for target identification is urgently required. Furthermore, transmitting large image streams from remote locations would quickly use available band width (BW) precipitating the need for processing to occur at the sensor location. This paper addresses the problem of automatic target recognition for battle damage assessment (BDA). We utilize an Adaptive Resonance Theory approach to cluster templates of target buildings. The results show that the network successfully classifies targets from non-targets in a virtual test bed environment.

Vision-based Nano Robotic System for High-throughput Non-embedded Cell Cutting

NASA Astrophysics Data System (ADS)

Shang, Wanfeng; Lu, Haojian; Wan, Wenfeng; Fukuda, Toshio; Shen, Yajing

2016-03-01

Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded cell cutting with this system. First, the nano robotic system is developed and integrated with a nanoknife inside an environmental scanning electron microscopy (ESEM). Then, the positions of the nanoknife and the single cell are recognized, and the distance between them is calculated dynamically based on image processing. To guarantee the positioning accuracy and the working efficiency, we propose a distance-regulated speed adapting strategy, in which the moving speed is adjusted intelligently based on the distance between the nanoknife and the target cell. The results indicate that the automatic non-embedded cutting is able to be achieved within 1-2 mins with low invasion benefiting from the high precise nanorobot system and the sharp edge of nanoknife. This research paves a way for the high-throughput cell cutting at cell’s natural condition, which is expected to make significant impact on the biology studies, especially for the in-situ analysis at cellular and subcellular scale, such as cell interaction investigation, neural signal transduction and low invasive cell surgery.

Automatic lip reading by using multimodal visual features

NASA Astrophysics Data System (ADS)

Takahashi, Shohei; Ohya, Jun

2013-12-01

Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

Bridging automatic speech recognition and psycholinguistics: Extending Shortlist to an end-to-end model of human speech recognition (L)

NASA Astrophysics Data System (ADS)

Scharenborg, Odette; ten Bosch, Louis; Boves, Lou; Norris, Dennis

2003-12-01

This letter evaluates potential benefits of combining human speech recognition (HSR) and automatic speech recognition by building a joint model of an automatic phone recognizer (APR) and a computational model of HSR, viz., Shortlist [Norris, Cognition 52, 189-234 (1994)]. Experiments based on ``real-life'' speech highlight critical limitations posed by some of the simplifying assumptions made in models of human speech recognition. These limitations could be overcome by avoiding hard phone decisions at the output side of the APR, and by using a match between the input and the internal lexicon that flexibly copes with deviations from canonical phonemic representations.

SailSpy: a vision system for yacht sail shape measurement

NASA Astrophysics Data System (ADS)

Olsson, Olof J.; Power, P. Wayne; Bowman, Chris C.; Palmer, G. Terry; Clist, Roger S.

1992-11-01

SailSpy is a real-time vision system which we have developed for automatically measuring sail shapes and masthead rotation on racing yachts. Versions have been used by the New Zealand team in two America's Cup challenges in 1988 and 1992. SailSpy uses four miniature video cameras mounted at the top of the mast to provide views of the headsail and mainsail on either tack. The cameras are connected to the SailSpy computer below deck using lightweight cables mounted inside the mast. Images received from the cameras are automatically analyzed by the SailSpy computer, and sail shape and mast rotation parameters are calculated. The sail shape parameters are calculated by recognizing sail markers (ellipses) that have been attached to the sails, and the mast rotation parameters by recognizing deck markers painted on the deck. This paper describes the SailSpy system and some of the vision algorithms used.

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.

Visual Benefits in Apparent Motion Displays: Automatically Driven Spatial and Temporal Anticipation Are Partially Dissociated

PubMed Central

Ahrens, Merle-Marie; Veniero, Domenica; Gross, Joachim; Harvey, Monika; Thut, Gregor

2015-01-01

Many behaviourally relevant sensory events such as motion stimuli and speech have an intrinsic spatio-temporal structure. This will engage intentional and most likely unintentional (automatic) prediction mechanisms enhancing the perception of upcoming stimuli in the event stream. Here we sought to probe the anticipatory processes that are automatically driven by rhythmic input streams in terms of their spatial and temporal components. To this end, we employed an apparent visual motion paradigm testing the effects of pre-target motion on lateralized visual target discrimination. The motion stimuli either moved towards or away from peripheral target positions (valid vs. invalid spatial motion cueing) at a rhythmic or arrhythmic pace (valid vs. invalid temporal motion cueing). Crucially, we emphasized automatic motion-induced anticipatory processes by rendering the motion stimuli non-predictive of upcoming target position (by design) and task-irrelevant (by instruction), and by creating instead endogenous (orthogonal) expectations using symbolic cueing. Our data revealed that the apparent motion cues automatically engaged both spatial and temporal anticipatory processes, but that these processes were dissociated. We further found evidence for lateralisation of anticipatory temporal but not spatial processes. This indicates that distinct mechanisms may drive automatic spatial and temporal extrapolation of upcoming events from rhythmic event streams. This contrasts with previous findings that instead suggest an interaction between spatial and temporal attention processes when endogenously driven. Our results further highlight the need for isolating intentional from unintentional processes for better understanding the various anticipatory mechanisms engaged in processing behaviourally relevant stimuli with predictable spatio-temporal structure such as motion and speech. PMID:26623650

Priming production: Neural evidence for enhanced automatic semantic activity preceding language production in schizophrenia.

PubMed

Kuperberg, Gina R; Delaney-Busch, Nathaniel; Fanucci, Kristina; Blackford, Trevor

2018-01-01

Lexico-semantic disturbances are considered central to schizophrenia. Clinically, their clearest manifestation is in language production. However, most studies probing their underlying mechanisms have used comprehension or categorization tasks. Here, we probed automatic semantic activity prior to language production in schizophrenia using event-related potentials (ERPs). 19 people with schizophrenia and 16 demographically-matched healthy controls named target pictures that were very quickly preceded by masked prime words. To probe automatic semantic activity prior to production, we measured the N400 ERP component evoked by these targets. To determine the origin of any automatic semantic abnormalities, we manipulated the type of relationship between prime and target such that they overlapped in (a) their semantic features (semantically related, e.g. "cake" preceding a < picture of a pie >, (b) their initial phonemes (phonemically related, e.g. "stomach" preceding a < picture of a starfish >), or (c) both their semantic features and their orthographic/phonological word form (identity related, e.g. "socks" preceding a < picture of socks >). For each of these three types of relationship, the same targets were paired with unrelated prime words (counterbalanced across lists). We contrasted ERPs and naming times to each type of related target with its corresponding unrelated target. People with schizophrenia showed abnormal N400 modulation prior to naming identity related (versus unrelated) targets: whereas healthy control participants produced a smaller amplitude N400 to identity related than unrelated targets, patients showed the opposite pattern, producing a larger N400 to identity related than unrelated targets. This abnormality was specific to the identity related targets. Just like healthy control participants, people with schizophrenia produced a smaller N400 to semantically related than to unrelated targets, and showed no difference in the N400 evoked by phonemically related and unrelated targets. There were no differences between the two groups in the pattern of naming times across conditions. People with schizophrenia can show abnormal neural activity associated with automatic semantic processing prior to language production. The specificity of this abnormality to the identity related targets suggests that that, rather than arising from abnormalities of either semantic features or lexical form alone, it may stem from disruptions of mappings (connections) between the meaning of words and their form.

Is gaze following purely reflexive or goal-directed instead? Revisiting the automaticity of orienting attention by gaze cues.

PubMed

Ricciardelli, Paola; Carcagno, Samuele; Vallar, Giuseppe; Bricolo, Emanuela

2013-01-01

Distracting gaze has been shown to elicit automatic gaze following. However, it is still debated whether the effects of perceived gaze are a simple automatic spatial orienting response or are instead sensitive to the context (i.e. goals and task demands). In three experiments, we investigated the conditions under which gaze following occurs. Participants were instructed to saccade towards one of two lateral targets. A face distracter, always present in the background, could gaze towards: (a) a task-relevant target--("matching" goal-directed gaze shift)--congruent or incongruent with the instructed direction, (b) a task-irrelevant target, orthogonal to the one instructed ("non-matching" goal-directed gaze shift), or (c) an empty spatial location (no-goal-directed gaze shift). Eye movement recordings showed faster saccadic latencies in correct trials in congruent conditions especially when the distracting gaze shift occurred before the instruction to make a saccade. Interestingly, while participants made a higher proportion of gaze-following errors (i.e. errors in the direction of the distracting gaze) in the incongruent conditions when the distracter's gaze shift preceded the instruction onset indicating an automatic gaze following, they never followed the distracting gaze when it was directed towards an empty location or a stimulus that was never the target. Taken together, these findings suggest that gaze following is likely to be a product of both automatic and goal-driven orienting mechanisms.

Acute Alcohol Consumption Impairs Controlled but Not Automatic Processes in a Psychophysical Pointing Paradigm

PubMed Central

Johnston, Kevin; Timney, Brian; Goodale, Melvyn A.

2013-01-01

Numerous studies have investigated the effects of alcohol consumption on controlled and automatic cognitive processes. Such studies have shown that alcohol impairs performance on tasks requiring conscious, intentional control, while leaving automatic performance relatively intact. Here, we sought to extend these findings to aspects of visuomotor control by investigating the effects of alcohol in a visuomotor pointing paradigm that allowed us to separate the influence of controlled and automatic processes. Six male participants were assigned to an experimental “correction” condition in which they were instructed to point at a visual target as quickly and accurately as possible. On a small percentage of trials, the target “jumped” to a new location. On these trials, the participants’ task was to amend their movement such that they pointed to the new target location. A second group of 6 participants were assigned to a “countermanding” condition, in which they were instructed to terminate their movements upon detection of target “jumps”. In both the correction and countermanding conditions, participants served as their own controls, taking part in alcohol and no-alcohol conditions on separate days. Alcohol had no effect on participants’ ability to correct movements “in flight”, but impaired the ability to withhold such automatic corrections. Our data support the notion that alcohol selectively impairs controlled processes in the visuomotor domain. PMID:23861934

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

PubMed

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatic detection of small surface targets with electro-optical sensors in a harbor environment

NASA Astrophysics Data System (ADS)

Bouma, Henri; de Lange, Dirk-Jan J.; van den Broek, Sebastiaan P.; Kemp, Rob A. W.; Schwering, Piet B. W.

2008-10-01

In modern warfare scenarios naval ships must operate in coastal environments. These complex environments, in bays and narrow straits, with cluttered littoral backgrounds and many civilian ships may contain asymmetric threats of fast targets, such as rhibs, cabin boats and jet-skis. Optical sensors, in combination with image enhancement and automatic detection, assist an operator to reduce the response time, which is crucial for the protection of the naval and land-based supporting forces. In this paper, we present our work on automatic detection of small surface targets which includes multi-scale horizon detection and robust estimation of the background intensity. To evaluate the performance of our detection technology, data was recorded with both infrared and visual-light cameras in a coastal zone and in a harbor environment. During these trials multiple small targets were used. Results of this evaluation are shown in this paper.

A new type industrial total station based on target automatic collimation

NASA Astrophysics Data System (ADS)

Lao, Dabao; Zhou, Weihu; Ji, Rongyi; Dong, Dengfeng; Xiong, Zhi; Wei, Jiang

2018-01-01

In the case of industrial field measurement, the present measuring instruments work with manual operation and collimation, which give rise to low efficiency for field measurement. In order to solve the problem, a new type industrial total station is presented in this paper. The new instrument can identify and trace cooperative target automatically, in the mean time, coordinate of the target is measured in real time. For realizing the system, key technology including high precision absolutely distance measurement, small high accuracy angle measurement, target automatic collimation with vision, and quick precise controlling should be worked out. After customized system assemblage and adjustment, the new type industrial total station will be established. As the experiments demonstrated, the coordinate accuracy of the instrument is under 15ppm in the distance of 60m, which proved that the measuring system is feasible. The result showed that the total station can satisfy most industrial field measurement requirements.

Dendritic cell recognition using template matching based on one-dimensional (1D) Fourier descriptors (FD)

NASA Astrophysics Data System (ADS)

Muhd Suberi, Anis Azwani; Wan Zakaria, Wan Nurshazwani; Tomari, Razali; Lau, Mei Xia

2016-07-01

Identification of Dendritic Cell (DC) particularly in the cancer microenvironment is a unique disclosure since fighting tumor from the harnessing immune system has been a novel treatment under investigation. Nowadays, the staining procedure in sorting DC can affect their viability. In this paper, a computer aided system is proposed for automatic classification of DC in peripheral blood mononuclear cell (PBMC) images. Initially, the images undergo a few steps in preprocessing to remove uneven illumination and artifacts around the cells. In segmentation, morphological operators and Canny edge are implemented to isolate the cell shapes and extract the contours. Following that, information from the contours are extracted based on Fourier descriptors, derived from one dimensional (1D) shape signatures. Eventually, cells are classified as DC by comparing template matching (TM) of established template and target images. The results show that the proposed scheme is reliable and effective to recognize DC.

A Face Attention Technique for a Robot Able to Interpret Facial Expressions

NASA Astrophysics Data System (ADS)

Simplício, Carlos; Prado, José; Dias, Jorge

Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.

Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts

PubMed Central

Chun, Hong-Woo; Tsuruoka, Yoshimasa; Kim, Jin-Dong; Shiba, Rie; Nagata, Naoki; Hishiki, Teruyoshi; Tsujii, Jun'ichi

2006-01-01

Background Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations. Methods We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer. Results Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%. Conclusion A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques. PMID:17134477

Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts.

PubMed

Chun, Hong-Woo; Tsuruoka, Yoshimasa; Kim, Jin-Dong; Shiba, Rie; Nagata, Naoki; Hishiki, Teruyoshi; Tsujii, Jun'ichi

2006-11-24

Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations. We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer. Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%. A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques.

Separating Automatic and Intentional Inhibitory Mechanisms of Attention in Adults with Attention-Deficit/Hyperactivity Disorder

PubMed Central

Roberts, Walter; Fillmore, Mark T.; Milich, Richard

2011-01-01

Researchers in the cognitive sciences recognize a fundamental distinction between automatic and intentional mechanisms of inhibitory control. The use of eye-tracking tasks to assess selective attention has led to a better understanding of this distinction in specific populations such as children with attention-deficit/hyperactivity disorder (ADHD). This study examined automatic and intentional inhibitory control mechanisms in adults with ADHD using a saccadic interference (SI) task and a delayed ocular response (DOR) task. Thirty adults with ADHD were compared to 27 comparison adults on measures of inhibitory control. The DOR task showed that adults with ADHD were less able than comparison adults to inhibit a reflexive saccade towards the sudden appearance of a stimulus in the periphery. However, SI task performance showed that the ADHD group did not differ significantly from the comparison group on a measure of automatic inhibitory control. These findings suggest a dissociation between automatic and intentional inhibitory deficits in adults with ADHD. PMID:21058752

Monitoring caustic injuries from emergency department databases using automatic keyword recognition software.

PubMed

Vignally, P; Fondi, G; Taggi, F; Pitidis, A

2011-03-31

In Italy the European Union Injury Database reports the involvement of chemical products in 0.9% of home and leisure accidents. The Emergency Department registry on domestic accidents in Italy and the Poison Control Centres record that 90% of cases of exposure to toxic substances occur in the home. It is not rare for the effects of chemical agents to be observed in hospitals, with a high potential risk of damage - the rate of this cause of hospital admission is double the domestic injury average. The aim of this study was to monitor the effects of injuries caused by caustic agents in Italy using automatic free-text recognition in Emergency Department medical databases. We created a Stata software program to automatically identify caustic or corrosive injury cases using an agent-specific list of keywords. We focused attention on the procedure's sensitivity and specificity. Ten hospitals in six regions of Italy participated in the study. The program identified 112 cases of injury by caustic or corrosive agents. Checking the cases by quality controls (based on manual reading of ED reports), we assessed 99 cases as true positive, i.e. 88.4% of the patients were automatically recognized by the software as being affected by caustic substances (99% CI: 80.6%- 96.2%), that is to say 0.59% (99% CI: 0.45%-0.76%) of the whole sample of home injuries, a value almost three times as high as that expected (p < 0.0001) from European codified information. False positives were 11.6% of the recognized cases (99% CI: 5.1%- 21.5%). Our automatic procedure for caustic agent identification proved to have excellent product recognition capacity with an acceptable level of excess sensitivity. Contrary to our a priori hypothesis, the automatic recognition system provided a level of identification of agents possessing caustic effects that was significantly much greater than was predictable on the basis of the values from current codifications reported in the European Database.

Assisting People with Multiple Disabilities by Improving Their Computer Pointing Efficiency with an Automatic Target Acquisition Program

ERIC Educational Resources Information Center

Shih, Ching-Hsiang; Shih, Ching-Tien; Peng, Chin-Ling

2011-01-01

This study evaluated whether two people with multiple disabilities would be able to improve their pointing performance through an Automatic Target Acquisition Program (ATAP) and a newly developed mouse driver (i.e. a new mouse driver replaces standard mouse driver, and is able to monitor mouse movement and intercept click action). Initially, both…

Self-assessing target with automatic feedback

DOEpatents

Larkin, Stephen W.; Kramer, Robert L.

2004-03-02

A self assessing target with four quadrants and a method of use thereof. Each quadrant containing possible causes for why shots are going into that particular quadrant rather than the center mass of the target. Each possible cause is followed by a solution intended to help the marksman correct the problem causing the marksman to shoot in that particular area. In addition, the self assessing target contains possible causes for general shooting errors and solutions to the causes of the general shooting error. The automatic feedback with instant suggestions and corrections enables the shooter to improve their marksmanship.

Automatic textual annotation of video news based on semantic visual object extraction

NASA Astrophysics Data System (ADS)

Boujemaa, Nozha; Fleuret, Francois; Gouet, Valerie; Sahbi, Hichem

2003-12-01

In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.

Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation.

PubMed

Daisne, Jean-François; Blumhofer, Andreas

2013-06-26

Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for "manual to automatic" and "manual to corrected" volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert.

Automatic calibration method for plenoptic camera

NASA Astrophysics Data System (ADS)

Luan, Yinsen; He, Xing; Xu, Bing; Yang, Ping; Tang, Guomao

2016-04-01

An automatic calibration method is proposed for a microlens-based plenoptic camera. First, all microlens images on the white image are searched and recognized automatically based on digital morphology. Then, the center points of microlens images are rearranged according to their relative position relationships. Consequently, the microlens images are located, i.e., the plenoptic camera is calibrated without the prior knowledge of camera parameters. Furthermore, this method is appropriate for all types of microlens-based plenoptic cameras, even the multifocus plenoptic camera, the plenoptic camera with arbitrarily arranged microlenses, or the plenoptic camera with different sizes of microlenses. Finally, we verify our method by the raw data of Lytro. The experiments show that our method has higher intelligence than the methods published before.

A man-made object detection for underwater TV

NASA Astrophysics Data System (ADS)

Cheng, Binbin; Wang, Wenwu; Chen, Yao

2018-03-01

It is a great challenging task to complete an automatic search of objects underwater. Usually the forward looking sonar is used to find the target, and then the initial identification of the target is completed by the side-scan sonar, and finally the confirmation of the target is accomplished by underwater TV. This paper presents an efficient method for automatic extraction of man-made sensitive targets in underwater TV. Firstly, the image of underwater TV is simplified with taking full advantage of the prior knowledge of the target and the background; then template matching technology is used for target detection; finally the target is confirmed by extracting parallel lines on the target contour. The algorithm is formulated for real-time execution on limited-memory commercial-of-the-shelf platforms and is capable of detection objects in underwater TV.

Automatic segmentation and centroid detection of skin sensors for lung interventions

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Xu, Sheng; Xue, Zhong; Wong, Stephen T.

2012-02-01

Electromagnetic (EM) tracking has been recognized as a valuable tool for locating the interventional devices in procedures such as lung and liver biopsy or ablation. The advantage of this technology is its real-time connection to the 3D volumetric roadmap, i.e. CT, of a patient's anatomy while the intervention is performed. EM-based guidance requires tracking of the tip of the interventional device, transforming the location of the device onto pre-operative CT images, and superimposing the device in the 3D images to assist physicians to complete the procedure more effectively. A key requirement of this data integration is to find automatically the mapping between EM and CT coordinate systems. Thus, skin fiducial sensors are attached to patients before acquiring the pre-operative CTs. Then, those sensors can be recognized in both CT and EM coordinate systems and used calculate the transformation matrix. In this paper, to enable the EM-based navigation workflow and reduce procedural preparation time, an automatic fiducial detection method is proposed to obtain the centroids of the sensors from the pre-operative CT. The approach has been applied to 13 rabbit datasets derived from an animal study and eight human images from an observation study. The numerical results show that it is a reliable and efficient method for use in EM-guided application.

Automatic target detection using binary template matching

NASA Astrophysics Data System (ADS)

Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook

2005-03-01

This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

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.

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.

Autonomous Exploration for Gathering Increased Science

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin J.; Castano, Rebecca; Estlin, Tara A.; Gaines, Daniel M.; Anderson, Robert C.; Thompson, David R.; DeGranville, Charles K.; Chien, Steve A.; Tang, Benyang; Burl, Michael C.;

Mathematical algorithm for the automatic recognition of intestinal parasites.

PubMed

Alva, Alicia; Cangalaya, Carla; Quiliano, Miguel; Krebs, Casey; Gilman, Robert H; Sheen, Patricia; Zimic, Mirko

2017-01-01

Parasitic infections are generally diagnosed by professionals trained to recognize the morphological characteristics of the eggs in microscopic images of fecal smears. However, this laboratory diagnosis requires medical specialists which are lacking in many of the areas where these infections are most prevalent. In response to this public health issue, we developed a software based on pattern recognition analysis from microscopi digital images of fecal smears, capable of automatically recognizing and diagnosing common human intestinal parasites. To this end, we selected 229, 124, 217, and 229 objects from microscopic images of fecal smears positive for Taenia sp., Trichuris trichiura, Diphyllobothrium latum, and Fasciola hepatica, respectively. Representative photographs were selected by a parasitologist. We then implemented our algorithm in the open source program SCILAB. The algorithm processes the image by first converting to gray-scale, then applies a fourteen step filtering process, and produces a skeletonized and tri-colored image. The features extracted fall into two general categories: geometric characteristics and brightness descriptions. Individual characteristics were quantified and evaluated with a logistic regression to model their ability to correctly identify each parasite separately. Subsequently, all algorithms were evaluated for false positive cross reactivity with the other parasites studied, excepting Taenia sp. which shares very few morphological characteristics with the others. The principal result showed that our algorithm reached sensitivities between 99.10%-100% and specificities between 98.13%- 98.38% to detect each parasite separately. We did not find any cross-positivity in the algorithms for the three parasites evaluated. In conclusion, the results demonstrated the capacity of our computer algorithm to automatically recognize and diagnose Taenia sp., Trichuris trichiura, Diphyllobothrium latum, and Fasciola hepatica with a high sensitivity and specificity.

Mathematical algorithm for the automatic recognition of intestinal parasites

PubMed Central

Alva, Alicia; Cangalaya, Carla; Quiliano, Miguel; Krebs, Casey; Gilman, Robert H.; Sheen, Patricia; Zimic, Mirko

2017-01-01

Parasitic infections are generally diagnosed by professionals trained to recognize the morphological characteristics of the eggs in microscopic images of fecal smears. However, this laboratory diagnosis requires medical specialists which are lacking in many of the areas where these infections are most prevalent. In response to this public health issue, we developed a software based on pattern recognition analysis from microscopi digital images of fecal smears, capable of automatically recognizing and diagnosing common human intestinal parasites. To this end, we selected 229, 124, 217, and 229 objects from microscopic images of fecal smears positive for Taenia sp., Trichuris trichiura, Diphyllobothrium latum, and Fasciola hepatica, respectively. Representative photographs were selected by a parasitologist. We then implemented our algorithm in the open source program SCILAB. The algorithm processes the image by first converting to gray-scale, then applies a fourteen step filtering process, and produces a skeletonized and tri-colored image. The features extracted fall into two general categories: geometric characteristics and brightness descriptions. Individual characteristics were quantified and evaluated with a logistic regression to model their ability to correctly identify each parasite separately. Subsequently, all algorithms were evaluated for false positive cross reactivity with the other parasites studied, excepting Taenia sp. which shares very few morphological characteristics with the others. The principal result showed that our algorithm reached sensitivities between 99.10%-100% and specificities between 98.13%- 98.38% to detect each parasite separately. We did not find any cross-positivity in the algorithms for the three parasites evaluated. In conclusion, the results demonstrated the capacity of our computer algorithm to automatically recognize and diagnose Taenia sp., Trichuris trichiura, Diphyllobothrium latum, and Fasciola hepatica with a high sensitivity and specificity. PMID:28410387

Recognizing Action Units for Facial Expression Analysis

PubMed Central

Tian, Ying-li; Kanade, Takeo; Cohn, Jeffrey F.

2010-01-01

Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, and fear. Such prototypic expressions, however, occur rather infrequently. Human emotions and intentions are more often communicated by changes in one or a few discrete facial features. In this paper, we develop an Automatic Face Analysis (AFA) system to analyze facial expressions based on both permanent facial features (brows, eyes, mouth) and transient facial features (deepening of facial furrows) in a nearly frontal-view face image sequence. The AFA system recognizes fine-grained changes in facial expression into action units (AUs) of the Facial Action Coding System (FACS), instead of a few prototypic expressions. Multistate face and facial component models are proposed for tracking and modeling the various facial features, including lips, eyes, brows, cheeks, and furrows. During tracking, detailed parametric descriptions of the facial features are extracted. With these parameters as the inputs, a group of action units (neutral expression, six upper face AUs and 10 lower face AUs) are recognized whether they occur alone or in combinations. The system has achieved average recognition rates of 96.4 percent (95.4 percent if neutral expressions are excluded) for upper face AUs and 96.7 percent (95.6 percent with neutral expressions excluded) for lower face AUs. The generalizability of the system has been tested by using independent image databases collected and FACS-coded for ground-truth by different research teams. PMID:25210210

A chest-shape target automatic detection method based on Deformable Part Models

NASA Astrophysics Data System (ADS)

Zhang, Mo; Jin, Weiqi; Li, Li

2016-10-01

Automatic weapon platform is one of the important research directions at domestic and overseas, it needs to accomplish fast searching for the object to be shot under complex background. Therefore, fast detection for given target is the foundation of further task. Considering that chest-shape target is common target of shoot practice, this paper treats chestshape target as the target and studies target automatic detection method based on Deformable Part Models. The algorithm computes Histograms of Oriented Gradient(HOG) features of the target and trains a model using Latent variable Support Vector Machine(SVM); In this model, target image is divided into several parts then we can obtain foot filter and part filters; Finally, the algorithm detects the target at the HOG features pyramid with method of sliding window. The running time of extracting HOG pyramid with lookup table can be shorten by 36%. The result indicates that this algorithm can detect the chest-shape target in natural environments indoors or outdoors. The true positive rate of detection reaches 76% with many hard samples, and the false positive rate approaches 0. Running on a PC (Intel(R)Core(TM) i5-4200H CPU) with C++ language, the detection time of images with the resolution of 640 × 480 is 2.093s. According to TI company run library about image pyramid and convolution for DM642 and other hardware, our detection algorithm is expected to be implemented on hardware platform, and it has application prospect in actual system.

Lessons from (co-)evolution in the docking of proteins and peptides for CAPRI Rounds 28-35.

PubMed

Yu, Jinchao; Andreani, Jessica; Ochsenbein, Françoise; Guerois, Raphaël

2017-03-01

Computational protein-protein docking is of great importance for understanding protein interactions at the structural level. Critical assessment of prediction of interactions (CAPRI) experiments provide the protein docking community with a unique opportunity to blindly test methods based on real-life cases and help accelerate methodology development. For CAPRI Rounds 28-35, we used an automatic docking pipeline integrating the coarse-grained co-evolution-based potential InterEvScore. This score was developed to exploit the information contained in the multiple sequence alignments of binding partners and selectively recognize co-evolved interfaces. Together with Zdock/Frodock for rigid-body docking, SOAP-PP for atomic potential and Rosetta applications for structural refinement, this pipeline reached high performance on a majority of targets. For protein-peptide docking and interfacial water position predictions, we also explored different means of taking evolutionary information into account. Overall, our group ranked 1 st by correctly predicting 10 targets, composed of 1 High, 7 Medium and 2 Acceptable predictions. Excellent and Outstanding levels of accuracy were reached for each of the two water prediction targets, respectively. Altogether, in 15 out of 18 targets in total, evolutionary information, either through co-evolution or conservation analyses, could provide key constraints to guide modeling towards the most likely assemblies. These results open promising perspectives regarding the way evolutionary information can be valuable to improve docking prediction accuracy. Proteins 2017; 85:378-390. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Real-time speech gisting for ATC applications

NASA Astrophysics Data System (ADS)

Dunkelberger, Kirk A.

1995-06-01

Command and control within the ATC environment remains primarily voice-based. Hence, automatic real time, speaker independent, continuous speech recognition (CSR) has many obvious applications and implied benefits to the ATC community: automated target tagging, aircraft compliance monitoring, controller training, automatic alarm disabling, display management, and many others. However, while current state-of-the-art CSR systems provide upwards of 98% word accuracy in laboratory environments, recent low-intrusion experiments in the ATCT environments demonstrated less than 70% word accuracy in spite of significant investments in recognizer tuning. Acoustic channel irregularities and controller/pilot grammar verities impact current CSR algorithms at their weakest points. It will be shown herein, however, that real time context- and environment-sensitive gisting can provide key command phrase recognition rates of greater than 95% using the same low-intrusion approach. The combination of real time inexact syntactic pattern recognition techniques and a tight integration of CSR, gisting, and ATC database accessor system components is the key to these high phase recognition rates. A system concept for real time gisting in the ATC context is presented herein. After establishing an application context, discussion presents a minimal CSR technology context then focuses on the gisting mechanism, desirable interfaces into the ATCT database environment, and data and control flow within the prototype system. Results of recent tests for a subset of the functionality are presented together with suggestions for further research.

Automatic detection and classification of EOL-concrete and resulting recovered products by hyperspectral imaging

NASA Astrophysics Data System (ADS)

Palmieri, Roberta; Bonifazi, Giuseppe; Serranti, Silvia

2014-05-01

The recovery of materials from Demolition Waste (DW) represents one of the main target of the recycling industry and the its characterization is important in order to set up efficient sorting and/or quality control systems. End-Of-Life (EOL) concrete materials identification is necessary to maximize DW conversion into useful secondary raw materials, so it is fundamental to develop strategies for the implementation of an automatic recognition system of the recovered products. In this paper, HyperSpectral Imaging (HSI) technique was applied in order to detect DW composition. Hyperspectral images were acquired by a laboratory device equipped with a HSI sensing device working in the near infrared range (1000-1700 nm): NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Acquired spectral data were analyzed adopting the PLS_Toolbox (Version 7.5, Eigenvector Research, Inc.) under Matlab® environment (Version 7.11.1, The Mathworks, Inc.), applying different chemometric methods: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square- Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials, distinguishing recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood, foam, etc.). The developed procedure is cheap, fast and non-destructive: it could be used to make some steps of the recycling process more efficient and less expensive.

Use of target-date funds in 401(k) plans, 2007.

PubMed

Copeland, Craig

2009-03-01

WHAT THEY ARE: Target-date funds (also called "life-cycle" funds) are a type of mutual fund that automatically rebalances its asset allocation following a predetermined pattern over time. They typically rebalance to more conservative and income-producing assets as the participant's target date of retirement approaches. WHY THEY'RE IMPORTANT AND GROWING: Of the 401(k) plan participants in the EBRI/ICI 401(k) database who were found to be in plans that offeredtarget-date funds, 37 percent had at least some fraction of their account in target-date funds in 2007. Target-date funds held about 7 percent of total assets in 401(k) plans and the use of these funds is expected to increase in the future. The Pension Protection Act of 2006 made it easier for plan sponsors to automatically enroll new workers in a 401(k) plan, and target-date funds were one of the types of approved funds specified for a "default" investment if the participant does not elect a choice. BRI/ICI 401(K) DATABASE: This study uses the unique richness of the data in the EBRI/ICI Participant-Directed Retirement Plan Data Collection Project, which has almost 22 million participants, to examine the choices and characteristics of participants whose plans offer target-date funds. EFFECT OF AGE, SALARY, JOB TENURE, AND ACCOUNT BALANCE: Younger workers are significantly more likely to invest in target-date funds than are older workers: Almost 44 percent of participants under age 30 had assets in a target-date fund, compared with 27 percent of those 60 or older. Target-date funds appeal to those with lower incomes, little time on the job, and with few assets. On average, target-date fund investors are about 2.5 years younger than those who do not invest in target-date funds, have about 3.5 years less tenure, make about $11,000 less in salary, have $25,000 less in their account, and are in smaller plans. EFFECT OF AUTOMATIC ENROLLMENT: While the EBRI/ICI database does not contain specific information on whether a 401(k) plan had automatic enrollment, this analysis was able to proxy for those who could be identified as automatically enrolled. The data show that workers who were considered to be automatically enrolled in their employer's 401(k) plan are significantly more likely to invest all their assets in a target-date fund than those who voluntarily joined, and were also less likely to have extreme all-or-nothing asset allocations to equities. EQUITY ALLOCATIONS AND FUND FAMILIES: One of the major questions surrounding target-date funds is the equity allocations that these funds use over time (the so-called "glide path") as a participant's retirement target date approaches. The glide paths of different target-date funds have significantly different shapes and starting/ending equity allocations. As of 2007, the equity allocation ranges from about 80-90 percent for 2040 funds (for workers about 30 years away from retirement), and from 26-66 percent for 2010 funds (for workers one year away from retirement)--a 40 percentage-point difference. Moreover, the fund families change their relative rank in equity allocation within the different fund years. This analysis finds that the relative rank of the equity allocation within a target-date fund does not appear to affect the percentage of participants investing all their account into that fund. Nevertheless, investors in specific fund families are more likely to invest all their assets in a single target-date fund from that family.

Localization accuracy from automatic and semi-automatic rigid registration of locally-advanced lung cancer targets during image-guided radiation therapy

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

Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D.

2012-01-15

Purpose: To evaluate localization accuracy resulting from rigid registration of locally-advanced lung cancer targets using fully automatic and semi-automatic protocols for image-guided radiation therapy. Methods: Seventeen lung cancer patients, fourteen also presenting with involved lymph nodes, received computed tomography (CT) scans once per week throughout treatment under active breathing control. A physician contoured both lung and lymph node targets for all weekly scans. Various automatic and semi-automatic rigid registration techniques were then performed for both individual and simultaneous alignments of the primary gross tumor volume (GTV{sub P}) and involved lymph nodes (GTV{sub LN}) to simulate the localization process in image-guidedmore » radiation therapy. Techniques included ''standard'' (direct registration of weekly images to a planning CT), ''seeded'' (manual prealignment of targets to guide standard registration), ''transitive-based'' (alignment of pretreatment and planning CTs through one or more intermediate images), and ''rereferenced'' (designation of a new reference image for registration). Localization error (LE) was assessed as the residual centroid and border distances between targets from planning and weekly CTs after registration. Results: Initial bony alignment resulted in centroid LE of 7.3 {+-} 5.4 mm and 5.4 {+-} 3.4 mm for the GTV{sub P} and GTV{sub LN}, respectively. Compared to bony alignment, transitive-based and seeded registrations significantly reduced GTV{sub P} centroid LE to 4.7 {+-} 3.7 mm (p = 0.011) and 4.3 {+-} 2.5 mm (p < 1 x 10{sup -3}), respectively, but the smallest GTV{sub P} LE of 2.4 {+-} 2.1 mm was provided by rereferenced registration (p < 1 x 10{sup -6}). Standard registration significantly reduced GTV{sub LN} centroid LE to 3.2 {+-} 2.5 mm (p < 1 x 10{sup -3}) compared to bony alignment, with little additional gain offered by the other registration techniques. For simultaneous target alignment, centroid LE as low as 3.9 {+-} 2.7 mm and 3.8 {+-} 2.3 mm were achieved for the GTV{sub P} and GTV{sub LN}, respectively, using rereferenced registration. Conclusions: Target shape, volume, and configuration changes during radiation therapy limited the accuracy of standard rigid registration for image-guided localization in locally-advanced lung cancer. Significant error reductions were possible using other rigid registration techniques, with LE approaching the lower limit imposed by interfraction target variability throughout treatment.« less

Best Practices & Outstanding Initiatives

ERIC Educational Resources Information Center

Training, 2011

2011-01-01

In this article, "Training" editors recognize innovative and successful learning and development programs and practices. They share best practices from Automatic Data Processing, Inc., Farmers Insurance Group, FedEx Express, InterContinental Hotels Group, and Oakwood Temporary Housing. They also present the outstanding initiatives of EMD Serono,…

Face recognition for criminal identification: An implementation of principal component analysis for face recognition

NASA Astrophysics Data System (ADS)

Abdullah, Nurul Azma; Saidi, Md. Jamri; Rahman, Nurul Hidayah Ab; Wen, Chuah Chai; Hamid, Isredza Rahmi A.

2017-10-01

In practice, identification of criminal in Malaysia is done through thumbprint identification. However, this type of identification is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. However, because of limited software developed to automatically detect the similarity between photo in the footage and recorded photo of criminals, the law enforce thumbprint identification. In this paper, an automated facial recognition system for criminal database was proposed using known Principal Component Analysis approach. This system will be able to detect face and recognize face automatically. This will help the law enforcements to detect or recognize suspect of the case if no thumbprint present on the scene. The results show that about 80% of input photo can be matched with the template data.

A coloured oil level indicator detection method based on simple linear iterative clustering

NASA Astrophysics Data System (ADS)

Liu, Tianli; Li, Dongsong; Jiao, Zhiming; Liang, Tao; Zhou, Hao; Yang, Guoqing

2017-12-01

A detection method of coloured oil level indicator is put forward. The method is applied to inspection robot in substation, which realized the automatic inspection and recognition of oil level indicator. Firstly, the detected image of the oil level indicator is collected, and the detected image is clustered and segmented to obtain the label matrix of the image. Secondly, the detection image is processed by colour space transformation, and the feature matrix of the image is obtained. Finally, the label matrix and feature matrix are used to locate and segment the detected image, and the upper edge of the recognized region is obtained. If the upper limb line exceeds the preset oil level threshold, the alarm will alert the station staff. Through the above-mentioned image processing, the inspection robot can independently recognize the oil level of the oil level indicator, and instead of manual inspection. It embodies the automatic and intelligent level of unattended operation.

Selected Topics from LVCSR Research for Asian Languages at Tokyo Tech

NASA Astrophysics Data System (ADS)

Furui, Sadaoki

This paper presents our recent work in regard to building Large Vocabulary Continuous Speech Recognition (LVCSR) systems for the Thai, Indonesian, and Chinese languages. For Thai, since there is no word boundary in the written form, we have proposed a new method for automatically creating word-like units from a text corpus, and applied topic and speaking style adaptation to the language model to recognize spoken-style utterances. For Indonesian, we have applied proper noun-specific adaptation to acoustic modeling, and rule-based English-to-Indonesian phoneme mapping to solve the problem of large variation in proper noun and English word pronunciation in a spoken-query information retrieval system. In spoken Chinese, long organization names are frequently abbreviated, and abbreviated utterances cannot be recognized if the abbreviations are not included in the dictionary. We have proposed a new method for automatically generating Chinese abbreviations, and by expanding the vocabulary using the generated abbreviations, we have significantly improved the performance of spoken query-based search.

Automatic measurement of target crossing speed

NASA Astrophysics Data System (ADS)

Wardell, Mark; Lougheed, James H.

1992-11-01

The motion of ground vehicle targets after a ballistic round is launched can be a major source of inaccuracy for small (handheld) anti-armour weapon systems. A method of automatically measuring the crossing component to compensate the fire control solution has been devised and tested against various targets in a range of environments. A photodetector array aligned with the sight's horizontal reticle obtains scene features, which are digitized and processed to separate target from sight motion. Relative motion of the target against the background is briefly monitored to deduce angular crossing rate and a compensating lead angle is introduced into the aim point. Research to gather quantitative data and optimize algorithm performance is described, and some results from field testing are presented.

Astronomy Education and Research With Digital Viewing: Forming a New Network of Small Observatories

NASA Astrophysics Data System (ADS)

Bogard, Arthur; Hamilton, T. S.

2011-01-01

Small observatories face two major hindrances in teaching astronomy to students: weather and getting students to recognize what they're seeing. The normal astronomy class use of a single telescope with an eyepiece is restricted to good skies, and it allows only one viewer at a time. Since astronomy labs meet at regular times, bad weather can mean the loss of an entire week. As for the second problem, students often have difficulties recognizing what they are seeing through an eyepiece, and the instructor cannot point out the target's features. Commercial multimedia resources, although structured and easy to explain to students, do not give students the same level of interactivity. A professor cannot improvise a new target nor can he adjust the image to view different features of an object. Luckily, advancements in technology provide solutions for both of these limitations without breaking the bank. Astronomical video cameras can automatically stack, align, and integrate still frames, providing instructors with the ability to explain things to groups of students in real time under actual seeing conditions. Using Shawnee State University's Mallincam on an 8" Cassegrain, our students are now able to understand and classify both planetary and deep sky objects better than they can through an eyepiece. To address the problems with weather, SSU proposes forming a network among existing small observatories. With inexpensive software and cameras, telescopes can be aligned and operated over the web, and with reciprocal viewing agreements, users who are clouded out could view from another location. By partnering with institutions in the eastern hemisphere, even daytime viewing would be possible. Not only will this network aid in instruction, but the common user interface will make student research projects much easier.

Automatic Welding System of Aluminum Pipe by Monitoring Backside Image of Molten Pool Using Vision Sensor

NASA Astrophysics Data System (ADS)

Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

An automatic welding system using Tungsten Inert Gas (TIG) welding with vision sensor for welding of aluminum pipe was constructed. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position and moving welding torch with the AC welding machine. The monitoring system consists of a vision sensor using a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Neural network model for welding speed control were constructed to perform the process automatically. From the experimental results it shows the effectiveness of the control system confirmed by good detection of molten pool and sound weld of experimental result.

Size-based cell sorting with a resistive pulse sensor and an electromagnetic pump in a microfluidic chip.

PubMed

Song, Yongxin; Li, Mengqi; Pan, Xinxiang; Wang, Qi; Li, Dongqing

2015-02-01

An electrokinetic microfluidic chip is developed to detect and sort target cells by size from human blood samples. Target-cell detection is achieved by a differential resistive pulse sensor (RPS) based on the size difference between the target cell and other cells. Once a target cell is detected, the detected RPS signal will automatically actuate an electromagnetic pump built in a microchannel to push the target cell into a collecting channel. This method was applied to automatically detect and sort A549 cells and T-lymphocytes from a peripheral fingertip blood sample. The viability of A549 cells sorted in the collecting well was verified by Hoechst33342 and propidium iodide staining. The results show that as many as 100 target cells per minute can be sorted out from the sample solution and thus is particularly suitable for sorting very rare target cells, such as circulating tumor cells. The actuation of the electromagnetic valve has no influence on RPS cell detection and the consequent cell-sorting process. The viability of the collected A549 cell is not impacted by the applied electric field when the cell passes the RPS detection area. The device described in this article is simple, automatic, and label-free and has wide applications in size-based rare target cell sorting for medical diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

Facial recognition in education system

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Controlled cooling of an electronic system for reduced energy consumption

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

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

Energy efficient control of a cooling system cooling an electronic system is provided. The control includes automatically determining at least one adjusted control setting for at least one adjustable cooling component of a cooling system cooling the electronic system. The automatically determining is based, at least in part, on power being consumed by the cooling system and temperature of a heat sink to which heat extracted by the cooling system is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the coolingmore » system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on one or more experimentally obtained models relating the targeted temperature and power consumption of the one or more adjustable cooling components of the cooling system.« less

Controlled cooling of an electronic system based on projected conditions

DOEpatents

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2016-05-17

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

Controlled cooling of an electronic system based on projected conditions

DOEpatents

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2015-08-18

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

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

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

Energy efficient control of a cooling system cooling an electronic system is provided. The control includes automatically determining at least one adjusted control setting for at least one adjustable cooling component of a cooling system cooling the electronic system. The automatically determining is based, at least in part, on power being consumed by the cooling system and temperature of a heat sink to which heat extracted by the cooling system is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the coolingmore » system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on one or more experimentally obtained models relating the targeted temperature and power consumption of the one or more adjustable cooling components of the cooling system.« less

Suicide Risk Response: Enhancing Patient Safety Through Development of Effective Institutional Policies

DTIC Science & Technology

2004-01-01

potentially lethal self harm ). The CWG recognized the importance of having well-defined policies for response to suicidal TIDES and WAVES patients, and...calculates responses and automatically triggers the suicidality protocol 3.1 3 Spontaneous mention of suicide, self - harm , or persistent thoughts

Documents Similarity Measurement Using Field Association Terms.

ERIC Educational Resources Information Center

Atlam, El-Sayed; Fuketa, M.; Morita, K.; Aoe, Jun-ichi

2003-01-01

Discussion of text analysis and information retrieval and measurement of document similarity focuses on a new text manipulation system called FA (field association)-Sim that is useful for retrieving information in large heterogeneous texts and for recognizing content similarity in text excerpts. Discusses recall and precision, automatic indexing…

An image-based automatic recognition method for the flowering stage of maize

NASA Astrophysics Data System (ADS)

Yu, Zhenghong; Zhou, Huabing; Li, Cuina

2018-03-01

In this paper, we proposed an image-based approach for automatic recognizing the flowering stage of maize. A modified HOG/SVM detection framework is first adopted to detect the ears of maize. Then, we use low-rank matrix recovery technology to precisely extract the ears at pixel level. At last, a new feature called color gradient histogram, as an indicator, is proposed to determine the flowering stage. Comparing experiment has been carried out to testify the validity of our method and the results indicate that our method can meet the demand for practical observation.

Automatic Mexican sign language and digits recognition using normalized central moments

NASA Astrophysics Data System (ADS)

Solís, Francisco; Martínez, David; Espinosa, Oscar; Toxqui, Carina

2016-09-01

This work presents a framework for automatic Mexican sign language and digits recognition based on computer vision system using normalized central moments and artificial neural networks. Images are captured by digital IP camera, four LED reflectors and a green background in order to reduce computational costs and prevent the use of special gloves. 42 normalized central moments are computed per frame and used in a Multi-Layer Perceptron to recognize each database. Four versions per sign and digit were used in training phase. 93% and 95% of recognition rates were achieved for Mexican sign language and digits respectively.

Decision-level fusion of SAR and IR sensor information for automatic target detection

NASA Astrophysics Data System (ADS)

Cho, Young-Rae; Yim, Sung-Hyuk; Cho, Hyun-Woong; Won, Jin-Ju; Song, Woo-Jin; Kim, So-Hyeon

2017-05-01

We propose a decision-level architecture that combines synthetic aperture radar (SAR) and an infrared (IR) sensor for automatic target detection. We present a new size-based feature, called target-silhouette to reduce the number of false alarms produced by the conventional target-detection algorithm. Boolean Map Visual Theory is used to combine a pair of SAR and IR images to generate the target-enhanced map. Then basic belief assignment is used to transform this map into a belief map. The detection results of sensors are combined to build the target-silhouette map. We integrate the fusion mass and the target-silhouette map on the decision level to exclude false alarms. The proposed algorithm is evaluated using a SAR and IR synthetic database generated by SE-WORKBENCH simulator, and compared with conventional algorithms. The proposed fusion scheme achieves higher detection rate and lower false alarm rate than the conventional algorithms.

Development of an Automatic Grid Generator for Multi-Element High-Lift Wings

NASA Technical Reports Server (NTRS)

Eberhardt, Scott; Wibowo, Pratomo; Tu, Eugene

1996-01-01

The procedure to generate the grid around a complex wing configuration is presented in this report. The automatic grid generation utilizes the Modified Advancing Front Method as a predictor and an elliptic scheme as a corrector. The scheme will advance the surface grid one cell outward and the newly obtained grid is corrected using the Laplace equation. The predictor-corrector step ensures that the grid produced will be smooth for every configuration. The predictor-corrector scheme is extended for a complex wing configuration. A new technique is developed to deal with the grid generation in the wing-gaps and on the flaps. It will create the grids that fill the gap on the wing surface and the gap created by the flaps. The scheme recognizes these configurations automatically so that minimal user input is required. By utilizing an appropriate sequence in advancing the grid points on a wing surface, the automatic grid generation for complex wing configurations is achieved.

Development of an Automatic Testing Platform for Aviator's Night Vision Goggle Honeycomb Defect Inspection.

PubMed

Jian, Bo-Lin; Peng, Chao-Chung

2017-06-15

Due to the direct influence of night vision equipment availability on the safety of night-time aerial reconnaissance, maintenance needs to be carried out regularly. Unfortunately, some defects are not easy to observe or are not even detectable by human eyes. As a consequence, this study proposed a novel automatic defect detection system for aviator's night vision imaging systems AN/AVS-6(V)1 and AN/AVS-6(V)2. An auto-focusing process consisting of a sharpness calculation and a gradient-based variable step search method is applied to achieve an automatic detection system for honeycomb defects. This work also developed a test platform for sharpness measurement. It demonstrates that the honeycomb defects can be precisely recognized and the number of the defects can also be determined automatically during the inspection. Most importantly, the proposed approach significantly reduces the time consumption, as well as human assessment error during the night vision goggle inspection procedures.

A new airborne laser rangefinder dynamic target simulator for non-stationary environment

NASA Astrophysics Data System (ADS)

Ma, Pengge; Pang, Dongdong; Yi, Yang

2017-11-01

For the non-stationary environment simulation in laser range finder product testing, a new dynamic target simulation system is studied. First of all, the three-pulsed laser ranging principle, laser target signal composition and mathematical representation are introduced. Then, the actual nonstationary working environment of laser range finder is analyzed, and points out that the real sunshine background light clutter and target shielding effect in laser echo become the main influencing factors. After that, the dynamic laser target signal simulation method is given. Eventlly, the implementation of automatic test system based on arbitrary waveform generator is described. Practical application shows that the new echo signal automatic test system can simulate the real laser ranging environment of laser range finder, and is suitable for performance test of products.

Automatic Docking System Sensor Design, Test, and Mission Performance

NASA Technical Reports Server (NTRS)

Jackson, John L.; Howard, Richard T.; Cole, Helen J.

1998-01-01

The Video Guidance Sensor is a key element of an automatic rendezvous and docking program administered by NASA that was flown on STS-87 in November of 1997. The system used laser illumination of a passive target in the field of view of an on-board camera and processed the video image to determine the relative position and attitude between the target and the sensor. Comparisons of mission results with theoretical models and laboratory measurements will be discussed.

Tier-scalable reconnaissance: the future in autonomous C4ISR systems has arrived: progress towards an outdoor testbed

NASA Astrophysics Data System (ADS)

Fink, Wolfgang; Brooks, Alexander J.-W.; Tarbell, Mark A.; Dohm, James M.

2017-05-01

Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-)deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous C4ISR systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous tele-commanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).

Figural properties are prioritized for search under conditions of uncertainty: Setting boundary conditions on claims that figures automatically attract attention.

PubMed

Peterson, Mary A; Mojica, Andrew J; Salvagio, Elizabeth; Kimchi, Ruth

2017-01-01

Nelson and Palmer (2007) concluded that figures/figural properties automatically attract attention, after they found that participants were faster to detect/discriminate targets appearing where a portion of a familiar object was suggested in an otherwise ambiguous display. We investigated whether these effects are truly automatic and whether they generalize to another figural property-convexity. We found that Nelson and Palmer's results do generalize to convexity, but only when participants are uncertain regarding when and where the target will appear. Dependence on uncertainty regarding target location/timing was also observed for familiarity. Thus, although we could replicate and extend Nelson and Palmer's results, our experiments showed that figures do not automatically draw attention. In addition, our research went beyond Nelson and Palmer's, in that we were able to separate figural properties from perceived figures. Because figural properties are regularities that predict where objects lie in the visual field, our results join other evidence that regularities in the environment can attract attention. More generally, our results are consistent with Bayesian theories in which priors are given more weight under conditions of uncertainty.

Automatic graphene transfer system for improved material quality and efficiency

PubMed Central

Boscá, Alberto; Pedrós, Jorge; Martínez, Javier; Palacios, Tomás; Calle, Fernando

2016-01-01

In most applications based on chemical vapor deposition (CVD) graphene, the transfer from the growth to the target substrate is a critical step for the final device performance. Manual procedures are time consuming and depend on handling skills, whereas existing automatic roll-to-roll methods work well for flexible substrates but tend to induce mechanical damage in rigid ones. A new system that automatically transfers CVD graphene to an arbitrary target substrate has been developed. The process is based on the all-fluidic manipulation of the graphene to avoid mechanical damage, strain and contamination, and on the combination of capillary action and electrostatic repulsion between the graphene and its container to ensure a centered sample on top of the target substrate. The improved carrier mobility and yield of the automatically transferred graphene, as compared to that manually transferred, is demonstrated by the optical and electrical characterization of field-effect transistors fabricated on both materials. In particular, 70% higher mobility values, with a 30% decrease in the unintentional doping and a 10% strain reduction are achieved. The system has been developed for lab-scale transfer and proved to be scalable for industrial applications. PMID:26860260

Category Cued Recall Evokes a Generate-Recognize Retrieval Process

ERIC Educational Resources Information Center

Hunt, R. Reed; Smith, Rebekah E.; Toth, Jeffrey P.

2016-01-01

The experiments reported here were designed to replicate and extend McCabe, Roediger, and Karpicke's (2011) finding that retrieval in category cued recall involves both controlled and automatic processes. The extension entailed identifying whether distinctive encoding affected 1 or both of these 2 processes. The first experiment successfully…

Implantable Heart Aid

NASA Technical Reports Server (NTRS)

1984-01-01

CPI's human-implantable automatic implantable defibrillator (AID) is a heart assist system, derived from NASA's space circuitry technology, that can prevent erratic heart action known as arrhythmias. Implanted AID, consisting of microcomputer power source and two electrodes for sensing heart activity, recognizes onset of ventricular fibrillation (VF) and delivers corrective electrical countershock to restore rhythmic heartbeat.

Automated Signal Processing Applied to Volatile-Based Inspection of Greenhouse Crops

PubMed Central

Jansen, Roel; Hofstee, Jan Willem; Bouwmeester, Harro; van Henten, Eldert

2010-01-01

Gas chromatograph–mass spectrometers (GC-MS) have been used and shown utility for volatile-based inspection of greenhouse crops. However, a widely recognized difficulty associated with GC-MS application is the large and complex data generated by this instrument. As a consequence, experienced analysts are often required to process this data in order to determine the concentrations of the volatile organic compounds (VOCs) of interest. Manual processing is time-consuming, labour intensive and may be subject to errors due to fatigue. The objective of this study was to assess whether or not GC-MS data can also be automatically processed in order to determine the concentrations of crop health associated VOCs in a greenhouse. An experimental dataset that consisted of twelve data files was processed both manually and automatically to address this question. Manual processing was based on simple peak integration while the automatic processing relied on the algorithms implemented in the MetAlign™ software package. The results of automatic processing of the experimental dataset resulted in concentrations similar to that after manual processing. These results demonstrate that GC-MS data can be automatically processed in order to accurately determine the concentrations of crop health associated VOCs in a greenhouse. When processing GC-MS data automatically, noise reduction, alignment, baseline correction and normalisation are required. PMID:22163594

How should a speech recognizer work?

PubMed

Scharenborg, Odette; Norris, Dennis; Bosch, Louis; McQueen, James M

2005-11-12

Although researchers studying human speech recognition (HSR) and automatic speech recognition (ASR) share a common interest in how information processing systems (human or machine) recognize spoken language, there is little communication between the two disciplines. We suggest that this lack of communication follows largely from the fact that research in these related fields has focused on the mechanics of how speech can be recognized. In Marr's (1982) terms, emphasis has been on the algorithmic and implementational levels rather than on the computational level. In this article, we provide a computational-level analysis of the task of speech recognition, which reveals the close parallels between research concerned with HSR and ASR. We illustrate this relation by presenting a new computational model of human spoken-word recognition, built using techniques from the field of ASR that, in contrast to current existing models of HSR, recognizes words from real speech input. 2005 Lawrence Erlbaum Associates, Inc.

Challenges and Opportunities: One Stop Processing of Automatic Large-Scale Base Map Production Using Airborne LIDAR Data Within GIS Environment. Case Study: Makassar City, Indonesia

NASA Astrophysics Data System (ADS)

Widyaningrum, E.; Gorte, B. G. H.

2017-05-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.

Can a CNN recognize Catalan diet?

NASA Astrophysics Data System (ADS)

Herruzo, P.; Bolaños, M.; Radeva, P.

2016-10-01

Nowadays, we can find several diseases related to the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, these diseases are related to the food consumption of people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent many metabolic diseases. In particular, our work focuses on the recognition of Mediterranean food and dishes. The development of this methodology would allow to analise the daily habits of users with wearable cameras, within the topic of lifelogging. By using automatic mechanisms we could build an objective tool for the analysis of the patient's behavior, allowing specialists to discover unhealthy food patterns and understand the user's lifestyle. With the aim to automatically recognize a complete diet, we introduce a challenging multi-labeled dataset related to Mediter-ranean diet called FoodCAT. The first type of label provided consists of 115 food classes with an average of 400 images per dish, and the second one consists of 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet recognition. In this context, deep learning and more specifically, Convolutional Neural Networks (CNNs), currently are state-of-the-art methods for automatic food recognition. In our work, we compare several architectures for image classification, with the purpose of diet recognition. Applying the best model for recognising food categories, we achieve a top-1 accuracy of 72.29%, and top-5 of 97.07%. In a complete diet recognition of dishes from Mediterranean diet, enlarged with the Food-101 dataset for international dishes recognition, we achieve a top-1 accuracy of 68.07%, and top-5 of 89.53%, for a total of 115+101 food classes.

Task-Dependent Masked Priming Effects in Visual Word Recognition

PubMed Central

Kinoshita, Sachiko; Norris, Dennis

2012-01-01

A method used widely to study the first 250 ms of visual word recognition is masked priming: These studies have yielded a rich set of data concerning the processes involved in recognizing letters and words. In these studies, there is an implicit assumption that the early processes in word recognition tapped by masked priming are automatic, and masked priming effects should therefore be invariant across tasks. Contrary to this assumption, masked priming effects are modulated by the task goal: For example, only word targets show priming in the lexical decision task, but both words and non-words do in the same-different task; semantic priming effects are generally weak in the lexical decision task but are robust in the semantic categorization task. We explain how such task dependence arises within the Bayesian Reader account of masked priming (Norris and Kinoshita, 2008), and how the task dissociations can be used to understand the early processes in lexical access. PMID:22675316

Found and Missed: Failing to Recognize a Search Target despite Moving It

ERIC Educational Resources Information Center

Solman, Grayden J. F.; Cheyne, J. Allan; Smilek, Daniel

2012-01-01

We present results from five search experiments using a novel "unpacking" paradigm in which participants use a mouse to sort through random heaps of distractors to locate the target. We report that during this task participants often fail to recognize the target despite moving it, and despite having looked at the item. Additionally, the missed…

The analysis of selected orientation methods of architectural objects' scans

NASA Astrophysics Data System (ADS)

Markiewicz, Jakub S.; Kajdewicz, Irmina; Zawieska, Dorota

2015-05-01

The terrestrial laser scanning is commonly used in different areas, inter alia in modelling architectural objects. One of the most important part of TLS data processing is scans registration. It significantly affects the accuracy of generation of high resolution photogrammetric documentation. This process is time consuming, especially in case of a large number of scans. It is mostly based on an automatic detection and a semi-automatic measurement of control points placed on the object. In case of the complicated historical buildings, sometimes it is forbidden to place survey targets on an object or it may be difficult to distribute survey targets in the optimal way. Such problems encourage the search for the new methods of scan registration which enable to eliminate the step of placing survey targets on the object. In this paper the results of target-based registration method are presented The survey targets placed on the walls of historical chambers of the Museum of King Jan III's Palace at Wilanów and on the walls of ruins of the Bishops Castle in Iłża were used for scan orientation. Several variants of orientation were performed, taking into account different placement and different number of survey marks. Afterwards, during next research works, raster images were generated from scans and the SIFT and SURF algorithms for image processing were used to automatically search for corresponding natural points. The case of utilisation of automatically identified points for TLS data orientation was analysed. The results of both methods for TLS data registration were summarized and presented in numerical and graphical forms.

Volitional and automatic control of the hand when reaching to grasp objects.

PubMed

Chen, Zhongting; Saunders, Jeffrey Allen

2018-06-01

When picking up an object, we tend to grasp at contact points that allow a stable grip. Recent studies have demonstrated that appropriate grasp points can be selected during an ongoing movement in response to unexpected perturbations of the target object. In this study, we tested whether such online grip adjustments are automatic responses or can be controlled volitionally. Subjects performed virtual grasping movements toward target 2D shapes that sometimes changed shape or orientation during movement. Unlike in previous studies, the conditions and task requirements discouraged any online adjustments toward the perturbed shapes. In Experiment 1, target shapes were perturbed briefly (200 ms) during movement before reverting to the original shape, and subjects were instructed to ignore the transient perturbations. Despite subjects' intentions, we observed online adjustments of grip orientation that were toward the expected grip axis of the briefly presented shape. In Experiment 2, we added a stop-signal to the grasping task, with target perturbation as the stop cue. We again observed unnecessary online adjustments toward the grip axis of the perturbed shape, with similar latency. Furthermore, the grip adjustments continued after the forward motion of the hand had stopped, indicating that the automatic response to the perturbed target shape co-occurred with the volitional response to the perturbation onset. Our results provide evidence that automatic control mechanisms are used to guide the fingers to appropriate grasp points and suggest that these mechanisms are distinct from those involved with volitional control. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Definition of epitopes and antigens recognized by vaccinia specific immune responses: their conservation in variola virus sequences, and use as a model system to study complex pathogens.

PubMed

Sette, Alessandro; Grey, Howard; Oseroff, Carla; Peters, Bjoern; Moutaftsi, Magdalini; Crotty, Shane; Assarsson, Erika; Greenbaum, Jay; Kim, Yohan; Kolla, Ravi; Tscharke, David; Koelle, David; Johnson, R Paul; Blum, Janice; Head, Steven; Sidney, John

2009-12-30

In the last few years, a wealth of information has become available relating to the targets of vaccinia virus (VACV)-specific CD4(+) T cell, CD8(+) T cell and antibody responses. Due to the large size of its genome, encoding more than 200 different proteins, VACV represents a useful model system to study immunity to complex pathogens. Our data demonstrate that both cellular and humoral responses target a large number of antigens and epitopes. This broad spectrum of targets is detected in both mice and humans. CD4(+) T cell responses target late and structural antigens, while CD8(+) T cells preferentially recognize early antigens. While both CD4(+) and CD8(+) T cell responses target different types of antigens, the antigens recognized by T(H) cells are highly correlated with those recognized by antibody responses. We further show that protein abundance and antibody recognition can be used to predict antigens recognized by CD4(+) T cell responses, while early expression at the mRNA level predicts antigens targeted by CD8(+) T cells. Finally, we find that the vast majority of VACV epitopes are conserved in variola virus (VARV), thus suggesting that the epitopes defined herein also have relevance for the efficacy of VACV as a smallpox vaccine.

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 role of the P3 and CNV components in voluntary and automatic temporal orienting: A high spatial-resolution ERP study.

PubMed

Mento, Giovanni

2017-12-01

A main distinction has been proposed between voluntary and automatic mechanisms underlying temporal orienting (TO) of selective attention. Voluntary TO implies the endogenous directing of attention induced by symbolic cues. Conversely, automatic TO is exogenously instantiated by the physical properties of stimuli. A well-known example of automatic TO is sequential effects (SEs), which refer to the adjustments in participants' behavioral performance as a function of the trial-by-trial sequential distribution of the foreperiod between two stimuli. In this study a group of healthy adults underwent a cued reaction time task purposely designed to assess both voluntary and automatic TO. During the task, both post-cue and post-target event-related potentials (ERPs) were recorded by means of a high spatial resolution EEG system. In the results of the post-cue analysis, the P3a and P3b were identified as two distinct ERP markers showing distinguishable spatiotemporal features and reflecting automatic and voluntary a priori expectancy generation, respectively. The brain source reconstruction further revealed that distinct cortical circuits supported these two temporally dissociable components. Namely, the voluntary P3b was supported by a left sensorimotor network, while the automatic P3a was generated by a more distributed frontoparietal circuit. Additionally, post-cue contingent negative variation (CNV) and post-target P3 modulations were observed as common markers of voluntary and automatic expectancy implementation and response selection, although partially dissociable neural networks subserved these two mechanisms. Overall, these results provide new electrophysiological evidence suggesting that distinct neural substrates can be recruited depending on the voluntary or automatic cognitive nature of the cognitive mechanisms subserving TO. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping.

PubMed

Probst, Yasmine; Nguyen, Duc Thanh; Tran, Minh Khoi; Li, Wanqing

2015-07-27

Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT), local binary patterns (LBP), and colour are used for describing food images. The popular bag-of-words (BoW) model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work.

Toward Dietary Assessment via Mobile Phone Video Cameras.

PubMed

Chen, Nicholas; Lee, Yun Young; Rabb, Maurice; Schatz, Bruce

2010-11-13

Reliable dietary assessment is a challenging yet essential task for determining general health. Existing efforts are manual, require considerable effort, and are prone to underestimation and misrepresentation of food intake. We propose leveraging mobile phones to make this process faster, easier and automatic. Using mobile phones with built-in video cameras, individuals capture short videos of their meals; our software then automatically analyzes the videos to recognize dishes and estimate calories. Preliminary experiments on 20 typical dishes from a local cafeteria show promising results. Our approach complements existing dietary assessment methods to help individuals better manage their diet to prevent obesity and other diet-related diseases.

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

PubMed

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

The other-race effect does not apply to infant faces: An ERP attentional study.

PubMed

Proverbio, Alice Mado; De Gabriele, Valeria

2017-03-29

It is known that paedomorphic characteristics, called "baby schema" by Lorenz, trigger an orienting response in adults, are judged as attractive and stimulate parental care. On the other hand, it is known that ethnicity may influence face encoding, with an advantage in recognizing faces of their own ethnicity (called own-race effect). Some have argued that this effect holds also for infant faces, which conflicts with the "baby schema" phenomenon. The aim of the study was to investigate the possible presence of the own-race effect on infant vs. adult face processing. Seventeen Caucasian students participated to the study. Their EEG/ERPs were recorded as they watched 400 pictures of adult and infant faces of different ethnicity (half Caucasian, half non-Caucasian), and subsequently responded to a target orientation. The behavioral results showed that responses were faster when the target was preceded by a child face, which enhanced the arousal level, regardless of ethnicity. The electrophysiological results showed an enhanced anterior N2 response to infant than adult faces, and a lack of ORE effect only for infant faces. Overall, the data indicate that baby faces automatically attract the adult viewer's attention and that face ethnicity has no effect on this innate response. Copyright © 2017 Elsevier Ltd. All rights reserved.

78 FR 24402 - Commission Information Collection Activities (FERC Form 80); Comment Request; Extension

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-25

... Information Collection Activities (FERC Form 80); Comment Request; Extension AGENCY: Federal Energy Regulatory... automatic notification of activity in this docket or in viewing/downloading comments and issuances in this... jurisdiction to recognize the resources that are affected by their activities and to play a role in protecting...

Team-Based Learning in Honors Science Education: The Benefit of Complex Writing Assignments

ERIC Educational Resources Information Center

Wiegant, Fred; Boonstra, Johannes; Peeters, Anton; Scager, Karin

2012-01-01

Cooperative learning and team-based learning have been widely recognized as beneficial strategies to improve all levels of education, including higher education. Just forming groups, however, does not automatically lead to better learning and motivation; cooperation flourishes only under appropriate conditions (Fink; Gillies; Parmelee et al.).…

Effects of Feedback in an Online Algebra Intervention

ERIC Educational Resources Information Center

Bokhove, Christian; Drijvers, Paul

2012-01-01

The design and arrangement of appropriate automatic feedback in digital learning environment is a widely recognized issue. In this article, we investigate the effect of feedback on the design and the results of a digital intervention for algebra. Three feedback principles guided the intervention: timing and fading, crises, and feedback variation.…

Cardiac Structure and Function in Humans: A New Cardiovascular Physiology Laboratory

ERIC Educational Resources Information Center

Song, Su; Burleson, Paul D.; Passo, Stanley; Messina, Edward J.; Levine, Norman; Thompson, Carl I.; Belloni, Francis L.; Recchia, Fabio A.; Ojaimi, Caroline; Kaley, Gabor; Hintze, Thomas H.

2009-01-01

As the traditional cardiovascular control laboratory has disappeared from the first-year medical school curriculum, we have recognized the need to develop another "hands-on" experience as a vehicle for wide-ranging discussions of cardiovascular control mechanisms. Using an echocardiograph, an automatic blood pressure cuff, and a reclining bicycle,…

Down Syndrome and Automatic Processing of Familiar and Unfamiliar Emotional Faces

ERIC Educational Resources Information Center

Morales, Guadalupe E.; Lopez, Ernesto O.

2010-01-01

Participants with Down syndrome (DS) were required to participate in a face recognition experiment to recognize familiar (DS faces) and unfamiliar emotional faces (non DS faces), by using an affective priming paradigm. Pairs of emotional facial stimuli were presented (one face after another) with a short Stimulus Onset Asynchrony of 300…

AuDeNTES: Automatic Detection of teNtative Plagiarism According to a rEference Solution

ERIC Educational Resources Information Center

Mariani, Leonardo; Micucci, Daniela

2012-01-01

In academic courses, students frequently take advantage of someone else's work to improve their own evaluations or grades. This unethical behavior seriously threatens the integrity of the academic system, and teachers invest substantial effort in preventing and recognizing plagiarism. When students take examinations requiring the production of…

The automaticity of emotion recognition.

PubMed

Tracy, Jessica L; Robins, Richard W

2008-02-01

Evolutionary accounts of emotion typically assume that humans evolved to quickly and efficiently recognize emotion expressions because these expressions convey fitness-enhancing messages. The present research tested this assumption in 2 studies. Specifically, the authors examined (a) how quickly perceivers could recognize expressions of anger, contempt, disgust, embarrassment, fear, happiness, pride, sadness, shame, and surprise; (b) whether accuracy is improved when perceivers deliberate about each expression's meaning (vs. respond as quickly as possible); and (c) whether accurate recognition can occur under cognitive load. Across both studies, perceivers quickly and efficiently (i.e., under cognitive load) recognized most emotion expressions, including the self-conscious emotions of pride, embarrassment, and shame. Deliberation improved accuracy in some cases, but these improvements were relatively small. Discussion focuses on the implications of these findings for the cognitive processes underlying emotion recognition.

Targeted Help for Spoken Dialogue Systems: Intelligent Feedback Improves Naive Users' Performance

NASA Technical Reports Server (NTRS)

Hockey, Beth Ann; Lemon, Oliver; Campana, Ellen; Hiatt, Laura; Aist, Gregory; Hieronymous, Jim; Gruenstein, Alexander; Dowding, John

2003-01-01

We present experimental evidence that providing naive users of a spoken dialogue system with immediate help messages related to their out-of-coverage utterances improves their success in using the system. A grammar-based recognizer and a Statistical Language Model (SLM) recognizer are run simultaneously. If the grammar-based recognizer suceeds, the less accurate SLM recognizer hypothesis is not used. When the grammar-based recognizer fails and the SLM recognizer produces a recognition hypothesis, this result is used by the Targeted Help agent to give the user feed-back on what was recognized, a diagnosis of what was problematic about the utterance, and a related in-coverage example. The in-coverage example is intended to encourage alignment between user inputs and the language model of the system. We report on controlled experiments on a spoken dialogue system for command and control of a simulated robotic helicopter.

Posthypnotic suggestion alters conscious color perception in an automatic manner.

PubMed

Kallio, Sakari; Koivisto, Mika

2013-01-01

The authors studied whether a posthypnotic suggestion to see a brief, masked target as gray can change the color experience of a hypnotic virtuoso. The visibility of the target was manipulated by varying the delay between the target and the mask that followed it. The virtuoso's subjective reports indicated that her conscious color experience was altered already at short delays between the target and the subsequent mask. The virtuoso's objectively measured pattern of responding under posthypnotic suggestion could not be mimicked either by control participants nor the virtuoso herself. Due to posthypnotic amnesia, the virtuoso was unaware of suggestions given during hypnosis. Importantly, the virtuoso could not alter her color perception without a hypnotic suggestion. These results suggest that hypnosis can affect even a highly automatic process such as color perception.

An Automatic Multi-Target Independent Analysis Framework for Non-Planar Infrared-Visible Registration.

PubMed

Sun, Xinglong; Xu, Tingfa; Zhang, Jizhou; Zhao, Zishu; Li, Yuankun

2017-07-26

In this paper, we propose a novel automatic multi-target registration framework for non-planar infrared-visible videos. Previous approaches usually analyzed multiple targets together and then estimated a global homography for the whole scene, however, these cannot achieve precise multi-target registration when the scenes are non-planar. Our framework is devoted to solving the problem using feature matching and multi-target tracking. The key idea is to analyze and register each target independently. We present a fast and robust feature matching strategy, where only the features on the corresponding foreground pairs are matched. Besides, new reservoirs based on the Gaussian criterion are created for all targets, and a multi-target tracking method is adopted to determine the relationships between the reservoirs and foreground blobs. With the matches in the corresponding reservoir, the homography of each target is computed according to its moving state. We tested our framework on both public near-planar and non-planar datasets. The results demonstrate that the proposed framework outperforms the state-of-the-art global registration method and the manual global registration matrix in all tested datasets.

Installation and Testing Instructions for the Sandia Automatic Report Generator (ARG).

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

Clay, Robert L.

Robert L. CLAY Sandia National Laboratories P.O. Box 969 Livermore, CA 94551, U.S.A. rlclay@sandia.gov In this report, we provide detailed and reproducible installation instructions of the Automatic Report Generator (ARG), for both Linux and macOS target platforms.

Automatic Online Motor Control Is Intact in Parkinson's Disease With and Without Perceptual Awareness.

PubMed

Merritt, Kate E; Seergobin, Ken N; Mendonça, Daniel A; Jenkins, Mary E; Goodale, Melvyn A; MacDonald, Penny A

2017-01-01

In the double-step paradigm, healthy human participants automatically correct reaching movements when targets are displaced. Motor deficits are prominent in Parkinson's disease (PD) patients. In the lone investigation of online motor correction in PD using the double-step task, a recent study found that PD patients performed unconscious adjustments appropriately but seemed impaired for consciously-perceived modifications. Conscious perception of target movement was achieved by linking displacement to movement onset. PD-related bradykinesia disproportionately prolonged preparatory phases for movements to original target locations for patients, potentially accounting for deficits. Eliminating this confound in a double-step task, we evaluated the effect of conscious awareness of trajectory change on online motor corrections in PD. On and off dopaminergic therapy, PD patients ( n = 14) and healthy controls ( n = 14) reached to peripheral visual targets that remained stationary or unexpectedly moved during an initial saccade. Saccade latencies in PD are comparable to controls'. Hence, target displacements occurred at equal times across groups. Target jump size affected conscious awareness, confirmed in an independent target displacement judgment task. Small jumps were subliminal, but large target displacements were consciously perceived. Contrary to the previous result, PD patients performed online motor corrections normally and automatically, irrespective of conscious perception. Patients evidenced equivalent movement durations for jump and stay trials, and trajectories for patients and controls were identical, irrespective of conscious perception. Dopaminergic therapy had no effect on performance. In summary, online motor control is intact in PD, unaffected by conscious perceptual awareness. The basal ganglia are not implicated in online corrective responses.

Automatic Online Motor Control Is Intact in Parkinson’s Disease With and Without Perceptual Awareness

PubMed Central

Seergobin, Ken N.; Mendonça, Daniel A.

2017-01-01

Abstract In the double-step paradigm, healthy human participants automatically correct reaching movements when targets are displaced. Motor deficits are prominent in Parkinson’s disease (PD) patients. In the lone investigation of online motor correction in PD using the double-step task, a recent study found that PD patients performed unconscious adjustments appropriately but seemed impaired for consciously-perceived modifications. Conscious perception of target movement was achieved by linking displacement to movement onset. PD-related bradykinesia disproportionately prolonged preparatory phases for movements to original target locations for patients, potentially accounting for deficits. Eliminating this confound in a double-step task, we evaluated the effect of conscious awareness of trajectory change on online motor corrections in PD. On and off dopaminergic therapy, PD patients (n = 14) and healthy controls (n = 14) reached to peripheral visual targets that remained stationary or unexpectedly moved during an initial saccade. Saccade latencies in PD are comparable to controls’. Hence, target displacements occurred at equal times across groups. Target jump size affected conscious awareness, confirmed in an independent target displacement judgment task. Small jumps were subliminal, but large target displacements were consciously perceived. Contrary to the previous result, PD patients performed online motor corrections normally and automatically, irrespective of conscious perception. Patients evidenced equivalent movement durations for jump and stay trials, and trajectories for patients and controls were identical, irrespective of conscious perception. Dopaminergic therapy had no effect on performance. In summary, online motor control is intact in PD, unaffected by conscious perceptual awareness. The basal ganglia are not implicated in online corrective responses. PMID:29085900

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.

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.

Truncated feature representation for automatic target detection using transformed data-based decomposition

NASA Astrophysics Data System (ADS)

Riasati, Vahid R.

2016-05-01

In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.

An automated on-line turbulent flow liquid-chromatography technology coupled to a high resolution mass spectrometer LTQ-Orbitrap for suspect screening of antibiotic transformation products during microalgae wastewater treatment.

PubMed

Jaén-Gil, Adrián; Hom-Diaz, Andrea; Llorca, Marta; Vicent, Teresa; Blánquez, Paqui; Barceló, Damià; Rodríguez-Mozaz, Sara

2018-06-11

The evaluation of wastewater treatment capabilities in terms of removal of water pollutants is crucial when assessing water mitigation issues. Not only the monitoring of target pollutants becomes a critical point, but also the transformation products (TPs) generated. Since these TPs are very often unknown compounds, their study in both wastewater and natural environment is currently recognized as a tedious task and challenging research field. In this study, a novel automated suspect screening methodology was developed for a comprehensive assessment of the TPs generated from nine antibiotics during microalgae water treatment. Three macrolides (azithromycin, erythromycin, clarithromycin), three fluoroquinolones (ofloxacin, ciprofloxacin, norfloxacin) and three additional antibiotics (trimethoprim, pipemidic acid, sulfapyridine) were selected as target pollutants. The analysis of samples was carried out by direct injection in an on-line turbulent flow liquid chromatography-high resolution mass spectrometry (TFC-LC-LTQ-Orbitrap-MS/MS) system, followed by automatic data processing for compound identification. The screening methodology allowed the identification of 40 tentative TPs from a list of software predicted intermediates created automatically. Once known and unknown TPs were identified, degradation pathways were suggested considering the different mechanisms involved on their formation (biotic and abiotic). Results reveal microalgae ability for macrolide biotransformation, but not for other antibiotics such as for fluoroquinolones. Finally, the intermediates detected were included into an in-house library and applied to the identification of tentative TPs in real toilet wastewater treated in a microalgae based photobioreactor (PBR). The overall approach allowed a comprehensive overview of the performance of microalgae water treatment in a fast and reliable manner: it represents a useful tool for the rapid screening of wide range of compounds, reducing time invested in data analysis and providing reliable structural identification. Copyright © 2018 Elsevier B.V. All rights reserved.

Automatic identification of IASLC-defined mediastinal lymph node stations on CT scans using multi-atlas organ segmentation

NASA Astrophysics Data System (ADS)

Hoffman, Joanne; Liu, Jiamin; Turkbey, Evrim; Kim, Lauren; Summers, Ronald M.

2015-03-01

Station-labeling of mediastinal lymph nodes is typically performed to identify the location of enlarged nodes for cancer staging. Stations are usually assigned in clinical radiology practice manually by qualitative visual assessment on CT scans, which is time consuming and highly variable. In this paper, we developed a method that automatically recognizes the lymph node stations in thoracic CT scans based on the anatomical organs in the mediastinum. First, the trachea, lungs, and spines are automatically segmented to locate the mediastinum region. Then, eight more anatomical organs are simultaneously identified by multi-atlas segmentation. Finally, with the segmentation of those anatomical organs, we convert the text definitions of the International Association for the Study of Lung Cancer (IASLC) lymph node map into patient-specific color-coded CT image maps. Thus, a lymph node station is automatically assigned to each lymph node. We applied this system to CT scans of 86 patients with 336 mediastinal lymph nodes measuring equal or greater than 10 mm. 84.8% of mediastinal lymph nodes were correctly mapped to their stations.

Automatic and Direct Identification of Blink Components from Scalp EEG

PubMed Central

Kong, Wanzeng; Zhou, Zhanpeng; Hu, Sanqing; Zhang, Jianhai; Babiloni, Fabio; Dai, Guojun

2013-01-01

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn't need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects. PMID:23959240

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

NASA Astrophysics Data System (ADS)

Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

2015-11-01

In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

Towards Autonomous Agriculture: Automatic Ground Detection Using Trinocular Stereovision

PubMed Central

Reina, Giulio; Milella, Annalisa

2012-01-01

Autonomous driving is a challenging problem, particularly when the domain is unstructured, as in an outdoor agricultural setting. Thus, advanced perception systems are primarily required to sense and understand the surrounding environment recognizing artificial and natural structures, topology, vegetation and paths. In this paper, a self-learning framework is proposed to automatically train a ground classifier for scene interpretation and autonomous navigation based on multi-baseline stereovision. The use of rich 3D data is emphasized where the sensor output includes range and color information of the surrounding environment. Two distinct classifiers are presented, one based on geometric data that can detect the broad class of ground and one based on color data that can further segment ground into subclasses. The geometry-based classifier features two main stages: an adaptive training stage and a classification stage. During the training stage, the system automatically learns to associate geometric appearance of 3D stereo-generated data with class labels. Then, it makes predictions based on past observations. It serves as well to provide training labels to the color-based classifier. Once trained, the color-based classifier is able to recognize similar terrain classes in stereo imagery. The system is continuously updated online using the latest stereo readings, thus making it feasible for long range and long duration navigation, over changing environments. Experimental results, obtained with a tractor test platform operating in a rural environment, are presented to validate this approach, showing an average classification precision and recall of 91.0% and 77.3%, respectively.

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data.

PubMed

Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

2015-11-21

In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

Automatic Focusing for a 675 GHz Imaging Radar with Target Standoff Distances from 14 to 34 Meters

NASA Technical Reports Server (NTRS)

Tang, Adrian; Cooper, Ken B.; Dengler, Robert J.; Llombart, Nuria; Siegel, Peter H.

2013-01-01

This paper dicusses the issue of limited focal depth for high-resolution imaging radar operating over a wide range of standoff distances. We describe a technique for automatically focusing a THz imaging radar system using translational optics combined with range estimation based on a reduced chirp bandwidth setting. The demonstarted focusing algorithm estimates the correct focal depth for desired targets in the field of view at unknown standoffs and in the presence of clutter to provide good imagery at 14 to 30 meters of standoff.

Automatic laser beam alignment using blob detection for an environment monitoring spectroscopy

NASA Astrophysics Data System (ADS)

Khidir, Jarjees; Chen, Youhua; Anderson, Gary

2013-05-01

This paper describes a fully automated system to align an infra-red laser beam with a small retro-reflector over a wide range of distances. The component development and test were especially used for an open-path spectrometer gas detection system. Using blob detection under OpenCV library, an automatic alignment algorithm was designed to achieve fast and accurate target detection in a complex background environment. Test results are presented to show that the proposed algorithm has been successfully applied to various target distances and environment conditions.

Automatic visibility retrieval from thermal camera images

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Ott, Beat; Wellig, Peter; Wunderle, Stefan

2017-10-01

This study presents an automatic visibility retrieval of a FLIR A320 Stationary Thermal Imager installed on a measurement tower on the mountain Lagern located in the Swiss Jura Mountains. Our visibility retrieval makes use of edges that are automatically detected from thermal camera images. Predefined target regions, such as mountain silhouettes or buildings with high thermal differences to the surroundings, are used to derive the maximum visibility distance that is detectable in the image. To allow a stable, automatic processing, our procedure additionally removes noise in the image and includes automatic image alignment to correct small shifts of the camera. We present a detailed analysis of visibility derived from more than 24000 thermal images of the years 2015 and 2016 by comparing them to (1) visibility derived from a panoramic camera image (VISrange), (2) measurements of a forward-scatter visibility meter (Vaisala FD12 working in the NIR spectra), and (3) modeled visibility values using the Thermal Range Model TRM4. Atmospheric conditions, mainly water vapor from European Center for Medium Weather Forecast (ECMWF), were considered to calculate the extinction coefficients using MODTRAN. The automatic visibility retrieval based on FLIR A320 images is often in good agreement with the retrieval from the systems working in different spectral ranges. However, some significant differences were detected as well, depending on weather conditions, thermal differences of the monitored landscape, and defined target size.

Attention capture by contour onsets and offsets: no special role for onsets.

PubMed

Watson, D G; Humphreys, G W

1995-07-01

In five experiments, we investigated the power of targets defined by the onset or offset of one of an object's parts (contour onsets and offsets) either to guide or to capture visual attention. In Experiment 1, search for a single contour onset target was compared with search for a single contour offset target against a static background of distractors; no difference was found between the efficiency with which each could be detected. In Experiment 2, onsets and offsets were compared for automatic attention capture, when both occurred simultaneously. Unlike in previous studies, the effects of overall luminance change, new-object creation, and number of onset and offset items were controlled. It was found that contour onset and offset items captured attention equally well. However, display size effects on both target types were also apparent. Such effects may have been due to competition for selection between multiple onset and offset stimuli. In Experiments 3 and 4, single onset and offset stimuli were presented simultaneously and pitted directly against one another among a background of static distractors. In Experiment 3, we examined "guided search," for a target that was formed either from an onset or from an offset among static items. In Experiment 4, the onsets and offsets were uncorrelated with the target location. Similar results occurred in both experiments: target onsets and offsets were detected more efficiently than static stimuli which needed serial search; there remained effects of display size on performance; but there was still no advantage for onsets. In Experiment 5, we examined automatic attention capture by single onset and offset stimuli presented individually among static distractors. Again, there was no advantage for onset over offset targets and a display size effect was also present. These results suggest that, both in isolation and in competition, onsets that do not form new objects neither guide nor gain automatic attention more efficiently than offsets. In addition, in contrast to previous studies in which onsets formed new objects, contour onsets and offsets did not reliably capture attention automatically.

Scale invariant SURF detector and automatic clustering segmentation for infrared small targets detection

NASA Astrophysics Data System (ADS)

Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong

2017-06-01

The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.

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.

An Automatic Caption Filtering and Partial Hiding Approach to Improving the English Listening Comprehension of EFL Students

ERIC Educational Resources Information Center

Hsu, Ching-Kun; Hwang, Gwo-Jen; Chang, Chih-Kai

2014-01-01

Fostering the listening comprehension of English as Foreign Language (EFL) learners has been recognized as an important and challenging issue. Videos have been used as one of the English listening learning resources; however, without effective learning supports, EFL students are likely to encounter difficulties in comprehending the video content,…

Exploring Creative Thinking in Graphically Mediated Synchronous Dialogues

ERIC Educational Resources Information Center

Wegerif, Rupert; McLaren, Bruce M.; Chamrada, Marian; Scheuer, Oliver; Mansour, Nasser; Miksatko, Jan; Williams, Mriga

2010-01-01

This paper reports on an aspect of the EC funded Argunaut project which researched and developed awareness tools for moderators of online dialogues. In this study we report on an investigation into the nature of creative thinking in online dialogues and whether or not this creative thinking can be coded for and recognized automatically such that…

A Hierarchical and Contextual Model for Learning and Recognizing Highly Variant Visual Categories

DTIC Science & Technology

2010-01-01

neighboring pattern primitives, to create our model. We also present a minimax entropy framework for automatically learning which contextual constraints are...Grammars . . . . . . . . . . . . . . . . . . 19 3.2 Markov Random Fields . . . . . . . . . . . . . . . . . . . . . . . . 23 3.3 Creating a Contextual...Compositional Boosting. . . . . 119 7.8 Top-down hallucinations of missing objects. . . . . . . . . . . . . . . 121 7.9 The bottom-up to top-down

Learning L2 Pronunciation with a Mobile Speech Recognizer: French /y/

ERIC Educational Resources Information Center

Liakin, Denis; Cardoso, Walcir; Liakina, Natallia

2015-01-01

This study investigates the acquisition of the L2 French vowel /y/ in a mobile-assisted learning environment, via the use of automatic speech recognition (ASR). Particularly, it addresses the question of whether ASR-based pronunciation instruction using a mobile device can improve the production and perception of French /y/. Forty-two elementary…

The Relationship Between Reading Fluency and Vocabulary in Fifth Grade Turkish Students

ERIC Educational Resources Information Center

Yildirim, Kasim; Rasinski, Timothy; Ates, Seyit; Fitzgerald, Shawn; Zimmerman, Belinda; Yildiz, Mustafa

2014-01-01

Reading fluency has traditionally been recognized as a competency associated with word recognition and comprehension. As readers become more automatic in word identification they are able to devote less attention and cognitive resources to word decoding and more to text comprehension. The act of reading itself has been associated with growth in…

Sensor-Free or Sensor-Full: A Comparison of Data Modalities in Multi-Channel Affect Detection

ERIC Educational Resources Information Center

Paquette, Luc; Rowe, Jonathan; Baker, Ryan; Mott, Bradford; Lester, James; DeFalco, Jeanine; Brawner, Keith; Sottilare, Robert; Georgoulas, Vasiliki

2016-01-01

Computational models that automatically detect learners' affective states are powerful tools for investigating the interplay of affect and learning. Over the past decade, affect detectors--which recognize learners' affective states at run-time using behavior logs and sensor data--have advanced substantially across a range of K-12 and postsecondary…

Molecular Recognition of Human Liver Cancer Cells Using DNA Aptamers Generated via Cell-SELEX.

PubMed

Xu, Jiehua; Teng, I-Ting; Zhang, Liqin; Delgado, Stefanie; Champanhac, Carole; Cansiz, Sena; Wu, Cuichen; Shan, Hong; Tan, Weihong

2015-01-01

Most clinical cases of liver cancer cannot be diagnosed until they have evolved to an advanced stage, thus resulting in high mortality. It is well recognized that the implementation of early detection methods and the development of targeted therapies for liver cancer are essential to reducing the high mortality rates associated with this disease. To achieve these goals, molecular probes capable of recognizing liver cancer cell-specific targets are needed. Here we describe a panel of aptamers able to distinguish hepatocarcinoma from normal liver cells. The aptamers, which were selected by cell-based SELEX (Systematic Evolution of Ligands by Exponential Enrichment), have Kd values in the range of 64-349 nM toward the target human hepatoma cell HepG2, and also recognize ovarian cancer cells and lung adenocarcinoma. The proteinase treatment experiment indicated that all aptamers could recognize target HepG2 cells through surface proteins. This outcome suggested that these aptamers could be used as potential probes for further research in cancer studies, such as developing early detection assays, targeted therapies, and imaging agents, as well as for the investigation of common membrane proteins in these distinguishable cancers.

Human Immune Response to Dengue Infections

DTIC Science & Technology

1990-07-31

flavivirus-crossreactive clone recognized dengue-l, -2, -3, and -4 virus and West Nile virus (WNV), but did not recognize yellow fever virus ( YFV ), while...three flavivirus-crossreactive clones recognized dengue-1, -2, -3 and -4 virus, WNV and YFV . We also examined the recognition of purified NS3 proteins of...dengue-l, YFV or WNV Ag. JK44 lysed target cells cultured with dengue-1, -2, and -3, but did not lyse target cells cultured with dengue-4, YFV or WNV Ag

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

Knowledge Base Editor (SharpKBE)

NASA Technical Reports Server (NTRS)

Tikidjian, Raffi; James, Mark; Mackey, Ryan

2007-01-01

The SharpKBE software provides a graphical user interface environment for domain experts to build and manage knowledge base systems. Knowledge bases can be exported/translated to various target languages automatically, including customizable target languages.

SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo

2017-06-01

Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate that the proposed method is able to recognize street furniture in a practical scenario. Remaining difficult cases are touching objects, like a lamp pole close to a tree.

Progress in The Semantic Analysis of Scientific Code

NASA Technical Reports Server (NTRS)

Stewart, Mark

2000-01-01

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.

Category cued recall evokes a generate-recognize retrieval process.

PubMed

Hunt, R Reed; Smith, Rebekah E; Toth, Jeffrey P

2016-03-01

The experiments reported here were designed to replicate and extend McCabe, Roediger, and Karpicke's (2011) finding that retrieval in category cued recall involves both controlled and automatic processes. The extension entailed identifying whether distinctive encoding affected 1 or both of these 2 processes. The first experiment successfully replicated McCabe et al., but the second, which added a critical baseline condition, produced data inconsistent with a 2 independent process model of recall. The third experiment provided evidence that retrieval in category cued recall reflects a generate-recognize strategy, with the effect of distinctive processing being localized to recognition. Overall, the data suggest that category cued recall evokes a generate-recognize retrieval strategy and that the subprocesses underlying this strategy can be dissociated as a function of distinctive versus relational encoding processes. (c) 2016 APA, all rights reserved).

Category Cued Recall Evokes a Generate-Recognize Retrieval Process

PubMed Central

Hunt, R. Reed; Smith, Rebekah E.; Toth, Jeffrey P.

2015-01-01

The experiments reported here were designed to replicate and extend McCabe, Roediger, and Karpicke’s (2011) finding that retrieval in category cued recall involves both controlled and automatic processes. The extension entailed identifying whether distinctive encoding affected one or both of these two processes. The first experiment successfully replicated McCabe et al., but the second, which added a critical baseline condition, produced data inconsistent with a two independent process model of recall. The third experiment provided evidence that retrieval in category cued recall reflects a generate-recognize strategy, with the effect of distinctive processing being localized to recognition. Overall, the data suggest that category cued recall evokes a generate-recognize retrieval strategy and that the sub-processes underlying this strategy can be dissociated as a function of distinctive versus relational encoding processes. PMID:26280355

Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping

PubMed Central

Probst, Yasmine; Nguyen, Duc Thanh; Tran, Minh Khoi; Li, Wanqing

2015-01-01

Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT), local binary patterns (LBP), and colour are used for describing food images. The popular bag-of-words (BoW) model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work. PMID:26225994

An automatic indexing method for medical documents.

PubMed Central

Wagner, M. M.

1991-01-01

This paper describes MetaIndex, an automatic indexing program that creates symbolic representations of documents for the purpose of document retrieval. MetaIndex uses a simple transition network parser to recognize a language that is derived from the set of main concepts in the Unified Medical Language System Metathesaurus (Meta-1). MetaIndex uses a hierarchy of medical concepts, also derived from Meta-1, to represent the content of documents. The goal of this approach is to improve document retrieval performance by better representation of documents. An evaluation method is described, and the performance of MetaIndex on the task of indexing the Slice of Life medical image collection is reported. PMID:1807564

Automatic classification of bottles in crates

NASA Astrophysics Data System (ADS)

Aas, Kjersti; Eikvil, Line; Bremnes, Dag; Norbryhn, Andreas

1995-03-01

This paper presents a statistical method for classification of bottles in crates for use in automatic return bottle machines. For the automatons to reimburse the correct deposit, a reliable recognition is important. The images are acquired by a laser range scanner coregistering the distance to the object and the strength of the reflected signal. The objective is to identify the crate and the bottles from a library with a number of legal types. The bottles with significantly different size are separated using quite simple methods, while a more sophisticated recognizer is required to distinguish the more similar bottle types. Good results have been obtained when testing the method developed on bottle types which are difficult to distinguish using simple methods.

Analysis of straw row in the image to control the trajectory of the agricultural combine harvester

NASA Astrophysics Data System (ADS)

Shkanaev, Aleksandr Yurievich; Polevoy, Dmitry Valerevich; Panchenko, Aleksei Vladimirovich; Krokhina, Darya Alekseevna; Nailevish, Sadekov Rinat

2018-04-01

The paper proposes a solution to the automatic operation of the combine harvester along the straw rows by means of the images from the camera, installed in the cab of the harvester. The U-Net is used to recognize straw rows in the image. The edges of the row are approximated in the segmented image by the curved lines and further converted into the harvester coordinate system for the automatic operating system. The "new" network architecture and approaches to the row approximation has improved the quality of the recognition task and the processing speed of the frames up to 96% and 7.5 fps, respectively. Keywords: Grain harvester,

Automatic Certification of Kalman Filters for Reliable Code Generation

NASA Technical Reports Server (NTRS)

Denney, Ewen; Fischer, Bernd; Schumann, Johann; Richardson, Julian

2005-01-01

AUTOFILTER is a tool for automatically deriving Kalman filter code from high-level declarative specifications of state estimation problems. It can generate code with a range of algorithmic characteristics and for several target platforms. The tool has been designed with reliability of the generated code in mind and is able to automatically certify that the code it generates is free from various error classes. Since documentation is an important part of software assurance, AUTOFILTER can also automatically generate various human-readable documents, containing both design and safety related information. We discuss how these features address software assurance standards such as DO-178B.

Automatic Item Generation via Frame Semantics: Natural Language Generation of Math Word Problems.

ERIC Educational Resources Information Center

Deane, Paul; Sheehan, Kathleen

This paper is an exploration of the conceptual issues that have arisen in the course of building a natural language generation (NLG) system for automatic test item generation. While natural language processing techniques are applicable to general verbal items, mathematics word problems are particularly tractable targets for natural language…

Attentional Signatures of Perception: Multiple Object Tracking Reveals the Automaticity of Contour Interpolation

ERIC Educational Resources Information Center

Keane, Brian P.; Mettler, Everett; Tsoi, Vicky; Kellman, Philip J.

2011-01-01

Multiple object tracking (MOT) is an attentional task wherein observers attempt to track multiple targets among moving distractors. Contour interpolation is a perceptual process that fills-in nonvisible edges on the basis of how surrounding edges (inducers) are spatiotemporally related. In five experiments, we explored the automaticity of…

Practical automatic Arabic license plate recognition system

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Agaian, Sos; Saleh, Hani

2011-02-01

Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

Associative priming in a masked perceptual identification task: evidence for automatic processes.

PubMed

Pecher, Diane; Zeelenberg, René; Raaijmakers, Jeroen G W

2002-10-01

Two experiments investigated the influence of automatic and strategic processes on associative priming effects in a perceptual identification task in which prime-target pairs are briefly presented and masked. In this paradigm, priming is defined as a higher percentage of correctly identified targets for related pairs than for unrelated pairs. In Experiment 1, priming was obtained for mediated word pairs. This mediated priming effect was affected neither by the presence of direct associations nor by the presentation time of the primes, indicating that automatic priming effects play a role in perceptual identification. Experiment 2 showed that the priming effect was not affected by the proportion (.90 vs. .10) of related pairs if primes were presented briefly to prevent their identification. However, a large proportion effect was found when primes were presented for 1000 ms so that they were clearly visible. These results indicate that priming in a masked perceptual identification task is the result of automatic processes and is not affected by strategies. The present paradigm provides a valuable alternative to more commonly used tasks such as lexical decision.

Does gaze cueing produce automatic response activation: a lateralized readiness potential (LRP) study.

PubMed

Vainio, L; Heimola, M; Heino, H; Iljin, I; Laamanen, P; Seesjärvi, E; Paavilainen, P

2014-05-01

Previous research has shown that gaze cues facilitate responses to an upcoming target if the target location is compatible with the direction of the cue. Similar cueing effects have also been observed with central arrow cues. Both of these cueing effects have been attributed to a reflexive orienting of attention triggered by the cue. In addition, orienting of attention has been proposed to result in a partial response activation of the corresponding hand that, in turn, can be observed in the lateralized readiness potential (LRP), an electrophysiological indicator of automatic hand-motor response preparation. For instance, a central arrow cue has been observed to produce automatic hand-motor activation as indicated by the LRPs. The present study investigated whether gaze cues could also produce similar activation patterns in LRP. Although the standard gaze cueing effect was observed in the behavioural data, the LRP data did not reveal any consistent automatic hand-motor activation. The study suggests that motor processes associated with gaze cueing effect may operate exclusively at the level of oculomotor programming. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Cell-mediated immunity to herpes simplex virus: recognition of type-specific and type-common surface antigens by cytotoxic T cell populations.

PubMed Central

Eberle, R; Russell, R G; Rouse, B T

1981-01-01

In this communication, we examine the specificity of anti-herpes simplex virus (HSV) cytotoxic T lymphocytes (CTL). Serological studies of the two related HSV serotypes (HSV-1 and HSV-2) have revealed both type-specific and cross-reactive antigenic determinants in the viral envelope and on the surface of infected cells. By analysis of cytotoxicity of CTL, generated in vitro by restimulation of splenocytes from mice primed with one or the other HSV serotype, the recognition of both type-specific and cross-reactive determinants on infected target cells by anti-HSV CTL was detectable. Thus, effector cells generated by priming and restimulating with the same virus recognized both type-specific and cross-reactive determinants on target cells infected with the homologous virus, but only cross-reactive determinants on target cells infected with the heterologous HSV serotype. CTL generated by restimulation with the heterologous virus were capable of recognizing only the cross-reactive determinants on either HSV-1- or HSV-2-infected target cells. These results indicate that two subpopulations of CTL exist in a population of anti-HSV immune spleen cells--those which recognize type-specific determinants and those specific for cross-reactive antigenic determinants present on the surface of HSV infected cells. The type-specific subset of anti-HSV CTL was shown to recognize the gC glycoprotein of HSV-1 infected target cells. In addition to the gC glycoprotein, at least one other type-specific surface antigen was also recognized by anti-HSV CTL in addition to the cross-reactive determinants recognized by anti-HSV CTL. PMID:6277790

Automatic feature-based grouping during multiple object tracking.

PubMed

Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

2013-12-01

Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

Automatic Semantic Activation of Embedded Words: Is There a ''Hat'' in ''That''

ERIC Educational Resources Information Center

Bowers, J.S.; Davis, C.J.; Hanley, D.A.

2005-01-01

Participants semantically categorized target words that contain subsets (Experiment 1; e.g., target=hatch, subset=hat) or that are parts of supersets (Experiment 2; e.g., target=bee, superset=beer). In both experiments, the targets were categorized in a congruent condition (in which the subset-superset was associated with the same response, e.g.,…

[Development of a Software for Automatically Generated Contours in Eclipse TPS].

PubMed

Xie, Zhao; Hu, Jinyou; Zou, Lian; Zhang, Weisha; Zou, Yuxin; Luo, Kelin; Liu, Xiangxiang; Yu, Luxin

2015-03-01

The automatic generation of planning targets and auxiliary contours have achieved in Eclipse TPS 11.0. The scripting language autohotkey was used to develop a software for automatically generated contours in Eclipse TPS. This software is named Contour Auto Margin (CAM), which is composed of operational functions of contours, script generated visualization and script file operations. RESULTS Ten cases in different cancers have separately selected, in Eclipse TPS 11.0 scripts generated by the software could not only automatically generate contours but also do contour post-processing. For different cancers, there was no difference between automatically generated contours and manually created contours. The CAM is a user-friendly and powerful software, and can automatically generated contours fast in Eclipse TPS 11.0. With the help of CAM, it greatly save plan preparation time and improve working efficiency of radiation therapy physicists.

Culture, attribution and automaticity: a social cognitive neuroscience view

PubMed Central

Morris, Michael W.

2010-01-01

A fundamental challenge facing social perceivers is identifying the cause underlying other people’s behavior. Evidence indicates that East Asian perceivers are more likely than Western perceivers to reference the social context when attributing a cause to a target person’s actions. One outstanding question is whether this reflects a culture’s influence on automatic or on controlled components of causal attribution. After reviewing behavioral evidence that culture can shape automatic mental processes as well as controlled reasoning, we discuss the evidence in favor of cultural differences in automatic and controlled components of causal attribution more specifically. We contend that insights emerging from social cognitive neuroscience research can inform this debate. After introducing an attribution framework popular among social neuroscientists, we consider findings relevant to the automaticity of attribution, before speculating how one could use a social neuroscience approach to clarify whether culture affects automatic, controlled or both types of attribution processes. PMID:20460302

DELINEATING SUBTYPES OF SELF-INJURIOUS BEHAVIOR MAINTAINED BY AUTOMATIC REINFORCEMENT

PubMed Central

Hagopian, Louis P.; Rooker, Griffin W.; Zarcone, Jennifer R.

2016-01-01

Self-injurious behavior (SIB) is maintained by automatic reinforcement in roughly 25% of cases. Automatically reinforced SIB typically has been considered a single functional category, and is less understood than socially reinforced SIB. Subtyping automatically reinforced SIB into functional categories has the potential to guide the development of more targeted interventions and increase our understanding of its biological underpinnings. The current study involved an analysis of 39 individuals with automatically reinforced SIB and a comparison group of 13 individuals with socially reinforced SIB. Automatically reinforced SIB was categorized into 3 subtypes based on patterns of responding in the functional analysis and the presence of self-restraint. These response features were selected as the basis for subtyping on the premise that they could reflect functional properties of SIB unique to each subtype. Analysis of treatment data revealed important differences across subtypes and provides preliminary support to warrant additional research on this proposed subtyping model. PMID:26223959

On-Orbit MTF Measurement and Product Quality Monitoring for Commercial Remote Sensing Systems

NASA Technical Reports Server (NTRS)

Person, Steven

2007-01-01

Initialization and opportunistic targets are chosen that represent the MTF on the spatial domain. Ideal targets have simple mathematical relationships. Determine the MTF of an on-orbit satellite using in-scene targets: Slant-Edge, Line Source, point Source, and Radial Target. Attempt to facilitate the MTF calculation by automatically locating targets of opportunity. Incorporate MTF results into a product quality monitoring architecture.

Effects of Word Recognition Training in a Picture-Word Interference Task: Automaticity vs. Speed.

ERIC Educational Resources Information Center

Ehri, Linnea C.

First and second graders were taught to recognize a set of written words either more accurately or more rapidly. Both before and after word training, they named pictures printed with and without these words as distractors. Of interest was whether training would enhance or diminish the interference created by these words in the picture naming task.…

26 CFR 1.338(h)(10)-1 - Deemed asset sale and liquidation.

Code of Federal Regulations, 2014 CFR

2014-04-01

...)(iii) of this section, K recognizes no gain or loss, and K's basis in its T stock remains at $5,000... section 338(h)(10) election for T are as follows: (1) P. P is automatically deemed to have made a gain recognition election for its nonrecently purchased T stock, if any. The effect of a gain recognition election...

26 CFR 1.338(h)(10)-1 - Deemed asset sale and liquidation.

Code of Federal Regulations, 2012 CFR

2012-04-01

...)(iii) of this section, K recognizes no gain or loss, and K's basis in its T stock remains at $5,000... section 338(h)(10) election for T are as follows: (1) P. P is automatically deemed to have made a gain recognition election for its nonrecently purchased T stock, if any. The effect of a gain recognition election...

26 CFR 1.338(h)(10)-1 - Deemed asset sale and liquidation.

Code of Federal Regulations, 2013 CFR

2013-04-01

...)(iii) of this section, K recognizes no gain or loss, and K's basis in its T stock remains at $5,000... section 338(h)(10) election for T are as follows: (1) P. P is automatically deemed to have made a gain recognition election for its nonrecently purchased T stock, if any. The effect of a gain recognition election...

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

NASA Astrophysics Data System (ADS)

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

2011-04-01

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

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.

a Target Aware Texture Mapping for Sculpture Heritage Modeling

NASA Astrophysics Data System (ADS)

Yang, C.; Zhang, F.; Huang, X.; Li, D.; Zhu, Y.

2017-08-01

In this paper, we proposed a target aware image to model registration method using silhouette as the matching clues. The target sculpture object in natural environment can be automatically detected from image with complex background with assistant of 3D geometric data. Then the silhouette can be automatically extracted and applied in image to model matching. Due to the user don't need to deliberately draw target area, the time consumption for precisely image to model matching operation can be greatly reduced. To enhance the function of this method, we also improved the silhouette matching algorithm to support conditional silhouette matching. Two experiments using a stone lion sculpture of Ming Dynasty and a potable relic in museum are given to evaluate the method we proposed. The method we proposed in this paper is extended and developed into a mature software applied in many culture heritage documentation projects.

Reflector automatic acquisition and pointing based on auto-collimation theodolite.

PubMed

Luo, Jun; Wang, Zhiqian; Wen, Zhuoman; Li, Mingzhu; Liu, Shaojin; Shen, Chengwu

2018-01-01

An auto-collimation theodolite (ACT) for reflector automatic acquisition and pointing is designed based on the principle of autocollimators and theodolites. First, the principle of auto-collimation and theodolites is reviewed, and then the coaxial ACT structure is developed. Subsequently, the acquisition and pointing strategies for reflector measurements are presented, which first quickly acquires the target over a wide range and then points the laser spot to the charge coupled device zero position. Finally, experiments are conducted to verify the acquisition and pointing performance, including the calibration of the ACT, the comparison of the acquisition mode and pointing mode, and the accuracy measurement in horizontal and vertical directions. In both directions, a measurement accuracy of ±3″ is achieved. The presented ACT is suitable for automatic pointing and monitoring the reflector over a small scanning area and can be used in a wide range of applications such as bridge structure monitoring and cooperative target aiming.

Reflector automatic acquisition and pointing based on auto-collimation theodolite

NASA Astrophysics Data System (ADS)

Luo, Jun; Wang, Zhiqian; Wen, Zhuoman; Li, Mingzhu; Liu, Shaojin; Shen, Chengwu

2018-01-01

An auto-collimation theodolite (ACT) for reflector automatic acquisition and pointing is designed based on the principle of autocollimators and theodolites. First, the principle of auto-collimation and theodolites is reviewed, and then the coaxial ACT structure is developed. Subsequently, the acquisition and pointing strategies for reflector measurements are presented, which first quickly acquires the target over a wide range and then points the laser spot to the charge coupled device zero position. Finally, experiments are conducted to verify the acquisition and pointing performance, including the calibration of the ACT, the comparison of the acquisition mode and pointing mode, and the accuracy measurement in horizontal and vertical directions. In both directions, a measurement accuracy of ±3″ is achieved. The presented ACT is suitable for automatic pointing and monitoring the reflector over a small scanning area and can be used in a wide range of applications such as bridge structure monitoring and cooperative target aiming.

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

Automatic anatomy recognition in post-tonsillectomy MR images of obese children with OSAS

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, Jayaram K.; Odhner, Dewey; Sin, Sanghun; Arens, Raanan

2015-03-01

Automatic Anatomy Recognition (AAR) is a recently developed approach for the automatic whole body wide organ segmentation. We previously tested that methodology on image cases with some pathology where the organs were not distorted significantly. In this paper, we present an advancement of AAR to handle organs which may have been modified or resected by surgical intervention. We focus on MRI of the neck in pediatric Obstructive Sleep Apnea Syndrome (OSAS). The proposed method consists of an AAR step followed by support vector machine techniques to detect the presence/absence of organs. The AAR step employs a hierarchical organization of the organs for model building. For each organ, a fuzzy model over a population is built. The model of the body region is then described in terms of the fuzzy models and a host of other descriptors which include parent to offspring relationship estimated over the population. Organs are recognized following the organ hierarchy by using an optimal threshold based search. The SVM step subsequently checks for evidence of the presence of organs. Experimental results show that AAR techniques can be combined with machine learning strategies within the AAR recognition framework for good performance in recognizing missing organs, in our case missing tonsils in post-tonsillectomy images as well as in simulating tonsillectomy images. The previous recognition performance is maintained achieving an organ localization accuracy of within 1 voxel when the organ is actually not removed. To our knowledge, no methods have been reported to date for handling significantly deformed or missing organs, especially in neck MRI.

Automatic Annotation Method on Learners' Opinions in Case Method Discussion

ERIC Educational Resources Information Center

Samejima, Masaki; Hisakane, Daichi; Komoda, Norihisa

2015-01-01

Purpose: The purpose of this paper is to annotate an attribute of a problem, a solution or no annotation on learners' opinions automatically for supporting the learners' discussion without a facilitator. The case method aims at discussing problems and solutions in a target case. However, the learners miss discussing some of problems and solutions.…

Relatedness Proportion Effects in Semantic Categorization: Reconsidering the Automatic Spreading Activation Process

ERIC Educational Resources Information Center

de Wit, Bianca; Kinoshita, Sachiko

2014-01-01

Semantic priming effects at a short prime-target stimulus onset asynchrony are commonly explained in terms of an automatic spreading activation process. According to this view, the proportion of related trials should have no impact on the size of the semantic priming effect. Using a semantic categorization task ("Is this a living…

To hear or not to hear: Voice processing under visual load.

PubMed

Zäske, Romi; Perlich, Marie-Christin; Schweinberger, Stefan R

2016-07-01

Adaptation to female voices causes subsequent voices to be perceived as more male, and vice versa. This contrastive aftereffect disappears under spatial inattention to adaptors, suggesting that voices are not encoded automatically. According to Lavie, Hirst, de Fockert, and Viding (2004), the processing of task-irrelevant stimuli during selective attention depends on perceptual resources and working memory. Possibly due to their social significance, faces may be an exceptional domain: That is, task-irrelevant faces can escape perceptual load effects. Here we tested voice processing, to study whether voice gender aftereffects (VGAEs) depend on low or high perceptual (Exp. 1) or working memory (Exp. 2) load in a relevant visual task. Participants adapted to irrelevant voices while either searching digit displays for a target (Exp. 1) or recognizing studied digits (Exp. 2). We found that the VGAE was unaffected by perceptual load, indicating that task-irrelevant voices, like faces, can also escape perceptual-load effects. Intriguingly, the VGAE was increased under high memory load. Therefore, visual working memory load, but not general perceptual load, determines the processing of task-irrelevant voices.

Perceptual organization, visual attention, and objecthood.

PubMed

Kimchi, Ruth; Yeshurun, Yaffa; Spehar, Branka; Pirkner, Yossef

2016-09-01

We have previously demonstrated that the mere organization of some elements in the visual field into an object attracts attention automatically. Here, we explored three different aspects of this automatic attentional capture: (a) Does the attentional capture by an object involve a spatial component? (b) Which Gestalt organization factors suffice for an object to capture attention? (c) Does the strength of organization affect the object's ability to capture attention? Participants viewed multi-elements displays and either identified the color of one element or responded to a Vernier target. On some trials, a subset of the elements grouped by Gestalt factors into an object that was irrelevant to the task and not predictive of the target. An object effect - faster performance for targets within the object than for targets outside the object - was found even when the target appeared after the object offset, and was sensitive to target-object distance, suggesting that the capture of attention by an object is accompanied by a deployment of attention to the object location. Object effects of similar magnitude were found for objects grouped by a combination of factors (collinearity, closure, and symmetry, or closure and symmetry) or by a single factor when it was collinearity, but not symmetry, suggesting that collinearity, or closure combined with symmetry, suffices for automatic capture of attention by an object, but symmetry does not. Finally, the strength of grouping in modal completion, manipulated by varying contrast polarity between and within elements, affected the effectiveness of the attentional capture by the induced object. Copyright © 2015 Elsevier Ltd. All rights reserved.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve the speed and orientation efficiency of target identification effectively, and validate the feasibility of this method primarily.

Extending Automatic Parallelization to Optimize High-Level Abstractions for Multicore

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

Liao, C; Quinlan, D J; Willcock, J J

2008-12-12

Automatic introduction of OpenMP for sequential applications has attracted significant attention recently because of the proliferation of multicore processors and the simplicity of using OpenMP to express parallelism for shared-memory systems. However, most previous research has only focused on C and Fortran applications operating on primitive data types. C++ applications using high-level abstractions, such as STL containers and complex user-defined types, are largely ignored due to the lack of research compilers that are readily able to recognize high-level object-oriented abstractions and leverage their associated semantics. In this paper, we automatically parallelize C++ applications using ROSE, a multiple-language source-to-source compiler infrastructuremore » which preserves the high-level abstractions and gives us access to their semantics. Several representative parallelization candidate kernels are used to explore semantic-aware parallelization strategies for high-level abstractions, combined with extended compiler analyses. Those kernels include an array-base computation loop, a loop with task-level parallelism, and a domain-specific tree traversal. Our work extends the applicability of automatic parallelization to modern applications using high-level abstractions and exposes more opportunities to take advantage of multicore processors.« less

A new fast scanning system for the measurement of large angle tracks in nuclear emulsions

NASA Astrophysics Data System (ADS)

Alexandrov, A.; Buonaura, A.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; Di Crescenzo, A.; Di Marco, N.; Galati, G.; Lauria, A.; Montesi, M. C.; Pupilli, F.; Shchedrina, T.; Tioukov, V.; Vladymyrov, M.

2015-11-01

Nuclear emulsions have been widely used in particle physics to identify new particles through the observation of their decays thanks to their unique spatial resolution. Nevertheless, before the advent of automatic scanning systems, the emulsion analysis was very demanding in terms of well trained manpower. Due to this reason, they were gradually replaced by electronic detectors, until the '90s, when automatic microscopes started to be developed in Japan and in Europe. Automatic scanning was essential to conceive large scale emulsion-based neutrino experiments like CHORUS, DONUT and OPERA. Standard scanning systems have been initially designed to recognize tracks within a limited angular acceptance (θ lesssim 30°) where θ is the track angle with respect to a line perpendicular to the emulsion plane. In this paper we describe the implementation of a novel fast automatic scanning system aimed at extending the track recognition to the full angular range and improving the present scanning speed. Indeed, nuclear emulsions do not have any intrinsic limit to detect particle direction. Such improvement opens new perspectives to use nuclear emulsions in several fields in addition to large scale neutrino experiments, like muon radiography, medical applications and dark matter directional detection.

Activity classification using realistic data from wearable sensors.

PubMed

Pärkkä, Juha; Ermes, Miikka; Korpipää, Panu; Mäntyjärvi, Jani; Peltola, Johannes; Korhonen, Ilkka

2006-01-01

Automatic classification of everyday activities can be used for promotion of health-enhancing physical activities and a healthier lifestyle. In this paper, methods used for classification of everyday activities like walking, running, and cycling are described. The aim of the study was to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required. A large and realistic data library of sensor data was collected. Sixteen test persons took part in the data collection, resulting in approximately 31 h of annotated, 35-channel data recorded in an everyday environment. The test persons carried a set of wearable sensors while performing several activities during the 2-h measurement session. Classification results of three classifiers are shown: custom decision tree, automatically generated decision tree, and artificial neural network. The classification accuracies using leave-one-subject-out cross validation range from 58 to 97% for custom decision tree classifier, from 56 to 97% for automatically generated decision tree, and from 22 to 96% for artificial neural network. Total classification accuracy is 82 % for custom decision tree classifier, 86% for automatically generated decision tree, and 82% for artificial neural network.

Realization of the ergonomics design and automatic control of the fundus cameras

NASA Astrophysics Data System (ADS)

Zeng, Chi-liang; Xiao, Ze-xin; Deng, Shi-chao; Yu, Xin-ye

2012-12-01

The principles of ergonomics design in fundus cameras should be extending the agreeableness by automatic control. Firstly, a 3D positional numerical control system is designed for positioning the eye pupils of the patients who are doing fundus examinations. This system consists of a electronically controlled chin bracket for moving up and down, a lateral movement of binocular with the detector and the automatic refocusing of the edges of the eye pupils. Secondly, an auto-focusing device for the object plane of patient's fundus is designed, which collects the patient's fundus images automatically whether their eyes is ametropic or not. Finally, a moving visual target is developed for expanding the fields of the fundus images.

Performance of automatic scanning microscope for nuclear emulsion experiments

NASA Astrophysics Data System (ADS)

Güler, A. Murat; Altınok, Özgür

2015-12-01

The impressive improvements in scanning technology and methods let nuclear emulsion to be used as a target in recent large experiments. We report the performance of an automatic scanning microscope for nuclear emulsion experiments. After successful calibration and alignment of the system, we have reached 99% tracking efficiency for the minimum ionizing tracks that penetrating through the emulsions films. The automatic scanning system is successfully used for the scanning of emulsion films in the OPERA experiment and plan to use for the next generation of nuclear emulsion experiments.

Performance of automatic scanning microscope for nuclear emulsion experiments

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

Güler, A. Murat, E-mail: mguler@newton.physics.metu.edu.tr; Altınok, Özgür; Tufts University, Medford, MA 02155

The impressive improvements in scanning technology and methods let nuclear emulsion to be used as a target in recent large experiments. We report the performance of an automatic scanning microscope for nuclear emulsion experiments. After successful calibration and alignment of the system, we have reached 99% tracking efficiency for the minimum ionizing tracks that penetrating through the emulsions films. The automatic scanning system is successfully used for the scanning of emulsion films in the OPERA experiment and plan to use for the next generation of nuclear emulsion experiments.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

Two aspects of work on automatic target detection and tracking for electro-optic (EO) surveillance are described. Firstly, a detection and tracking algorithm test-bed developed by DSTO and running on a PC under Windows NT is being used to assess candidate algorithms for unresolved and minimally resolved target detection. The structure of this test-bed is described and examples are given of its user interfaces and outputs. Secondly, a development by Australian industry under a Defence-funded contract, of a reconfigurable generic track processor (GTP) is outlined. The GTP will include reconfigurable image processing stages and target tracking algorithms. It will be used to demonstrate to the Australian Defence Force automatic detection and tracking capabilities, and to serve as a hardware base for real time algorithm refinement.

Nuclear Security: Target Analysis-rev

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

Singh, Surinder Paul; Gibbs, Philip W.; Bultz, Garl A.

2014-03-01

The objectives of this presentation are to understand target identification, including roll-up and protracted theft; evaluate target identification in the SNRI; recognize the target characteristics and consequence levels; and understand graded safeguards.

The place-value of a digit in multi-digit numbers is processed automatically.

PubMed

Kallai, Arava Y; Tzelgov, Joseph

2012-09-01

The automatic processing of the place-value of digits in a multi-digit number was investigated in 4 experiments. Experiment 1 and two control experiments employed a numerical comparison task in which the place-value of a non-zero digit was varied in a string composed of zeros. Experiment 2 employed a physical comparison task in which strings of digits varied in their physical sizes. In both types of tasks, the place-value of the non-zero digit in the string was irrelevant to the task performed. Interference of the place-value information was found in both tasks. When the non-zero digit occupied a lower place-value, it was recognized slower as a larger digit or as written in a larger font size. We concluded that place-value in a multi-digit number is processed automatically. These results support the notion of a decomposed representation of multi-digit numbers in memory. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Digital signal processing algorithms for automatic voice recognition

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1987-01-01

The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

Automatic Quadcopter Control Avoiding Obstacle Using Camera with Integrated Ultrasonic Sensor

NASA Astrophysics Data System (ADS)

Anis, Hanafi; Haris Indra Fadhillah, Ahmad; Darma, Surya; Soekirno, Santoso

2018-04-01

Automatic navigation on the drone is being developed these days, a wide variety of types of drones and its automatic functions. Drones used in this study was an aircraft with four propellers or quadcopter. In this experiment, image processing used to recognize the position of an object and ultrasonic sensor used to detect obstacle distance. The method used to trace an obsctacle in image processing was the Lucas-Kanade-Tomasi Tracker, which had been widely used due to its high accuracy. Ultrasonic sensor used to complement the image processing success rate to be fully detected object. The obstacle avoidance system was to observe at the program decisions from some obstacle conditions read by the camera and ultrasonic sensors. Visual feedback control based PID controllers are used as a control of drones movement. The conclusion of the obstacle avoidance system was to observe at the program decisions from some obstacle conditions read by the camera and ultrasonic sensors.

Automatic Recognition of Fetal Facial Standard Plane in Ultrasound Image via Fisher Vector.

PubMed

Lei, Baiying; Tan, Ee-Leng; Chen, Siping; Zhuo, Liu; Li, Shengli; Ni, Dong; Wang, Tianfu

2015-01-01

Acquisition of the standard plane is the prerequisite of biometric measurement and diagnosis during the ultrasound (US) examination. In this paper, a new algorithm is developed for the automatic recognition of the fetal facial standard planes (FFSPs) such as the axial, coronal, and sagittal planes. Specifically, densely sampled root scale invariant feature transform (RootSIFT) features are extracted and then encoded by Fisher vector (FV). The Fisher network with multi-layer design is also developed to extract spatial information to boost the classification performance. Finally, automatic recognition of the FFSPs is implemented by support vector machine (SVM) classifier based on the stochastic dual coordinate ascent (SDCA) algorithm. Experimental results using our dataset demonstrate that the proposed method achieves an accuracy of 93.27% and a mean average precision (mAP) of 99.19% in recognizing different FFSPs. Furthermore, the comparative analyses reveal the superiority of the proposed method based on FV over the traditional methods.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

Different effects of the two types of spatial pre-cueing: what precisely is "attention" in Di Lollo's and Enns' substitution masking theory?

PubMed

Luiga, I; Bachmann, T

2007-11-01

Enns and Di Lollo [Psychological Science, 8 (2), 135-139, 1997] have introduced the object substitution theory of visual masking. Object substitution masking occurs when focusing attention on the target is delayed. However, Posner (Quarterly Journal of Experimental Psychology, 32, 3-25, 1980) has already shown that attention can be directed to a target at least in two ways: intentionally (endogenously) and automatically (exogenously). We conducted two experiments to explore the effects of endogenous and exogenous cues on substitution masking. The results showed that when attention was shifted to the target location automatically (using a local peripheral pre-cue), masking was attenuated. A decrease in target identification dependent on a delay of mask offset, typical to substitution masking, was not observed. However, strong substitution masking occurred when the target location was not pre-cued or when attention was directed to the target location intentionally (using a symbolic pre-cue displayed centrally). The hypothesis of two different mechanisms of attentional control in substitution masking was confirmed.

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

NASA Technical Reports Server (NTRS)

McGlynn, Thomas; Suchkov, A. A.; Winter, E. L.; Hanisch, R. J.; White, R. L.; Ochsenbein, F.; Derriere, S.; Voges, W.; Corcoran, M. F.

2004-01-01

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

An Intelligent Propulsion Control Architecture to Enable More Autonomous Vehicle Operation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Sowers, T. Shane; Simon, Donald L.; Owen, A. Karl; Rinehart, Aidan W.; Chicatelli, Amy K.; Acheson, Michael J.; Hueschen, Richard M.; Spiers, Christopher W.

2018-01-01

This paper describes an intelligent propulsion control architecture that coordinates with the flight control to reduce the amount of pilot intervention required to operate the vehicle. Objectives of the architecture include the ability to: automatically recognize the aircraft operating state and flight phase; configure engine control to optimize performance with knowledge of engine condition and capability; enhance aircraft performance by coordinating propulsion control with flight control; and recognize off-nominal propulsion situations and to respond to them autonomously. The hierarchical intelligent propulsion system control can be decomposed into a propulsion system level and an individual engine level. The architecture is designed to be flexible to accommodate evolving requirements, adapt to technology improvements, and maintain safety.

Automatic programming of simulation models

NASA Technical Reports Server (NTRS)

Schroer, Bernard J.; Tseng, Fan T.; Zhang, Shou X.; Dwan, Wen S.

1988-01-01

The objective of automatic programming is to improve the overall environment for describing the program. This improved environment is realized by a reduction in the amount of detail that the programmer needs to know and is exposed to. Furthermore, this improved environment is achieved by a specification language that is more natural to the user's problem domain and to the user's way of thinking and looking at the problem. The goal of this research is to apply the concepts of automatic programming (AP) to modeling discrete event simulation system. Specific emphasis is on the design and development of simulation tools to assist the modeler define or construct a model of the system and to then automatically write the corresponding simulation code in the target simulation language, GPSS/PC. A related goal is to evaluate the feasibility of various languages for constructing automatic programming simulation tools.

Reward-associated features capture attention in the absence of awareness: Evidence from object-substitution masking.

PubMed

Harris, Joseph A; Donohue, Sarah E; Schoenfeld, Mircea A; Hopf, Jens-Max; Heinze, Hans-Jochen; Woldorff, Marty G

2016-08-15

Reward-associated visual features have been shown to capture visual attention, evidenced in faster and more accurate behavioral performance, as well as in neural responses reflecting lateralized shifts of visual attention to those features. Specifically, the contralateral N2pc event-related-potential (ERP) component that reflects attentional shifting exhibits increased amplitude in response to task-relevant targets containing a reward-associated feature. In the present study, we examined the automaticity of such reward-association effects using object-substitution masking (OSM) in conjunction with MEG measures of visual attentional shifts. In OSM, a visual-search array is presented, with the target item to be detected indicated by a surrounding mask (here, four surrounding squares). Delaying the offset of the target-surrounding four-dot mask relative to the offset of the rest of the target/distracter array disrupts the viewer's awareness of the target (masked condition), whereas simultaneous offsets do not (unmasked condition). Here we manipulated whether the color of the OSM target was or was not of a previously reward-associated color. By tracking reward-associated enhancements of behavior and the N2pc in response to masked targets containing a previously rewarded or unrewarded feature, the automaticity of attentional capture by reward could be probed. We found an enhanced N2pc response to targets containing a previously reward-associated color feature. Moreover, this enhancement of the N2pc by reward did not differ between masking conditions, nor did it differ as a function of the apparent visibility of the target within the masked condition. Overall, these results underscore the automaticity of attentional capture by reward-associated features, and demonstrate the ability of feature-based reward associations to shape attentional capture and allocation outside of perceptual awareness. Copyright © 2016 Elsevier Inc. All rights reserved.

Automatic selective attention as a function of sensory modality in aging.

PubMed

Guerreiro, Maria J S; Adam, Jos J; Van Gerven, Pascal W M

2012-03-01

It was recently hypothesized that age-related differences in selective attention depend on sensory modality (Guerreiro, M. J. S., Murphy, D. R., & Van Gerven, P. W. M. (2010). The role of sensory modality in age-related distraction: A critical review and a renewed view. Psychological Bulletin, 136, 975-1022. doi:10.1037/a0020731). So far, this hypothesis has not been tested in automatic selective attention. The current study addressed this issue by investigating age-related differences in automatic spatial cueing effects (i.e., facilitation and inhibition of return [IOR]) across sensory modalities. Thirty younger (mean age = 22.4 years) and 25 older adults (mean age = 68.8 years) performed 4 left-right target localization tasks, involving all combinations of visual and auditory cues and targets. We used stimulus onset asynchronies (SOAs) of 100, 500, 1,000, and 1,500 ms between cue and target. The results showed facilitation (shorter reaction times with valid relative to invalid cues at shorter SOAs) in the unimodal auditory and in both cross-modal tasks but not in the unimodal visual task. In contrast, there was IOR (longer reaction times with valid relative to invalid cues at longer SOAs) in both unimodal tasks but not in either of the cross-modal tasks. Most important, these spatial cueing effects were independent of age. The results suggest that the modality hypothesis of age-related differences in selective attention does not extend into the realm of automatic selective attention.

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.

The Mechanical Recognition of Speech: Prospects for Use in the Teaching of Languages.

ERIC Educational Resources Information Center

Pulliam, Robert

1970-01-01

This paper begins with a brief account of the development of automatic speech recogniton (ASR) and then proceeds to an examination of ASR systems typical of the kind now in operation. It is stressed that such systems, although highly developed, do not recognize speech in the same sense as the human being does, and that they can not deal with a…

No Emergency Incident Recognizes Borders

DTIC Science & Technology

2011-03-01

ABSTRACT (maximum 200 words) The state of Arizona and the bordering towns of northern Mexico acknowledge the need for capability planning. They...northern Mexico are taking a preventive approach and have created the Bi- National Arizona Emergency Response Task Force (BAERTF). The goal of the...BAERTF is to deliver a timely, supportive response and automatic, mutual-aid capability to any jurisdiction in the state of Arizona or northern Mexico

Underspecification-Based Grammatical Feedback Generation Tailored to the Learner's Current Acquisition Level in an e-Learning System for German as Second Language

ERIC Educational Resources Information Center

Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes

2014-01-01

We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…

Semantic Priming from Letter-Searched Primes Occurs for Low- but Not High-Frequency Targets: Automatic Semantic Access May Not Be a Myth

ERIC Educational Resources Information Center

Tse, Chi-Shing; Neely, James H.

2007-01-01

Letter-search (LS) within a prime often eliminates semantic priming. In 2 lexical decision experiments, the authors found that priming from LS primes occurred for low-frequency (LF) but not high-frequency (HF) targets whether the target's word frequency was manipulated between or within participants and whether the prime-target pairs were…

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.

Automatic targeting of plasma spray gun

DOEpatents

Abbatiello, Leonard A.; Neal, Richard E.

1978-01-01

A means for monitoring the material portion in the flame of a plasma spray gun during spraying operations is provided. A collimated detector, sensitive to certain wavelengths of light emission, is used to locate the centroid of the material with each pass of the gun. The response from the detector is then relayed to the gun controller to be used to automatically realign the gun.

Assisting People with Developmental Disabilities to Improve Computer Pointing Efficiency through Multiple Mice and Automatic Pointing Assistive Programs

ERIC Educational Resources Information Center

Shih, Ching-Hsiang

2011-01-01

This study combines multi-mice technology (people with disabilities can use standard mice, instead of specialized alternative computer input devices, to achieve complete mouse operation) with an assistive pointing function (i.e. cursor-capturing, which enables the user to move the cursor to the target center automatically), to assess whether two…

An automatic tooth preparation technique: A preliminary study

NASA Astrophysics Data System (ADS)

Yuan, Fusong; Wang, Yong; Zhang, Yaopeng; Sun, Yuchun; Wang, Dangxiao; Lyu, Peijun

2016-04-01

The aim of this study is to validate the feasibility and accuracy of a new automatic tooth preparation technique in dental healthcare. An automatic tooth preparation robotic device with three-dimensional motion planning software was developed, which controlled an ultra-short pulse laser (USPL) beam (wavelength 1,064 nm, pulse width 15 ps, output power 30 W, and repeat frequency rate 100 kHz) to complete the tooth preparation process. A total of 15 freshly extracted human intact first molars were collected and fixed into a phantom head, and the target preparation shapes of these molars were designed using customised computer-aided design (CAD) software. The accuracy of tooth preparation was evaluated using the Geomagic Studio and Imageware software, and the preparing time of each tooth was recorded. Compared with the target preparation shape, the average shape error of the 15 prepared molars was 0.05-0.17 mm, the preparation depth error of the occlusal surface was approximately 0.097 mm, and the error of the convergence angle was approximately 1.0°. The average preparation time was 17 minutes. These results validated the accuracy and feasibility of the automatic tooth preparation technique.

An automatic tooth preparation technique: A preliminary study.

PubMed

Yuan, Fusong; Wang, Yong; Zhang, Yaopeng; Sun, Yuchun; Wang, Dangxiao; Lyu, Peijun

2016-04-29

The aim of this study is to validate the feasibility and accuracy of a new automatic tooth preparation technique in dental healthcare. An automatic tooth preparation robotic device with three-dimensional motion planning software was developed, which controlled an ultra-short pulse laser (USPL) beam (wavelength 1,064 nm, pulse width 15 ps, output power 30 W, and repeat frequency rate 100 kHz) to complete the tooth preparation process. A total of 15 freshly extracted human intact first molars were collected and fixed into a phantom head, and the target preparation shapes of these molars were designed using customised computer-aided design (CAD) software. The accuracy of tooth preparation was evaluated using the Geomagic Studio and Imageware software, and the preparing time of each tooth was recorded. Compared with the target preparation shape, the average shape error of the 15 prepared molars was 0.05-0.17 mm, the preparation depth error of the occlusal surface was approximately 0.097 mm, and the error of the convergence angle was approximately 1.0°. The average preparation time was 17 minutes. These results validated the accuracy and feasibility of the automatic tooth preparation technique.

Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment.

PubMed

Mezgec, Simon; Eftimov, Tome; Bucher, Tamara; Koroušić Seljak, Barbara

2018-04-06

The present study tested the combination of an established and a validated food-choice research method (the 'fake food buffet') with a new food-matching technology to automate the data collection and analysis. The methodology combines fake-food image recognition using deep learning and food matching and standardization based on natural language processing. The former is specific because it uses a single deep learning network to perform both the segmentation and the classification at the pixel level of the image. To assess its performance, measures based on the standard pixel accuracy and Intersection over Union were applied. Food matching firstly describes each of the recognized food items in the image and then matches the food items with their compositional data, considering both their food names and their descriptors. The final accuracy of the deep learning model trained on fake-food images acquired by 124 study participants and providing fifty-five food classes was 92·18 %, while the food matching was performed with a classification accuracy of 93 %. The present findings are a step towards automating dietary assessment and food-choice research. The methodology outperforms other approaches in pixel accuracy, and since it is the first automatic solution for recognizing the images of fake foods, the results could be used as a baseline for possible future studies. As the approach enables a semi-automatic description of recognized food items (e.g. with respect to FoodEx2), these can be linked to any food composition database that applies the same classification and description system.

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.

Robotic autopositioning of the operating microscope.

PubMed

Oppenlander, Mark E; Chowdhry, Shakeel A; Merkl, Brandon; Hattendorf, Guido M; Nakaji, Peter; Spetzler, Robert F

2014-06-01

Use of the operating microscope has become pervasive since its introduction to the neurosurgical world. Neuronavigation fused with the operating microscope has allowed accurate correlation of the focal point of the microscope and its location on the downloaded imaging study. However, the robotic ability of the Pentero microscope has not been utilized to orient the angle of the microscope or to change its focal length to hone in on a predefined target. To report a novel technology that allows automatic positioning of the operating microscope onto a set target and utilization of a planned trajectory, either determined with the StealthStation S7 by using preoperative imaging or intraoperatively with the microscope. By utilizing the current motorized capabilities of the Zeiss OPMI Pentero microscope, a robotic autopositioning feature was developed in collaboration with Surgical Technologies, Medtronic, Inc. (StealthStation S7). The system is currently being tested at the Barrow Neurological Institute. Three options were developed for automatically positioning the microscope: AutoLock Current Point, Align Parallel to Plan, and Point to Plan Target. These options allow the microscope to pivot around the lesion, hover in a set plane parallel to the determined trajectory, or rotate and point to a set target point, respectively. Integration of automatic microscope positioning into the operative workflow has potential to increase operative efficacy and safety. This technology is best suited for precise trajectories and entry points into deep-seated lesions.

Multiple sclerosis lesion segmentation using an automatic multimodal graph cuts.

PubMed

García-Lorenzo, Daniel; Lecoeur, Jeremy; Arnold, Douglas L; Collins, D Louis; Barillot, Christian

2009-01-01

Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed in synthetic and real images showing good agreement between the automatic segmentation and the target segmentation. We compare our algorithm with the state of the art techniques and with several manual segmentations. An advantage of our algorithm over previously published ones is the possibility to semi-automatically improve the segmentation due to the Graph Cuts interactive feature.

Intonation and dialog context as constraints for speech recognition.

PubMed

Taylor, P; King, S; Isard, S; Wright, H

1998-01-01

This paper describes a way of using intonation and dialog context to improve the performance of an automatic speech recognition (ASR) system. Our experiments were run on the DCIEM Maptask corpus, a corpus of spontaneous task-oriented dialog speech. This corpus has been tagged according to a dialog analysis scheme that assigns each utterance to one of 12 "move types," such as "acknowledge," "query-yes/no" or "instruct." Most ASR systems use a bigram language model to constrain the possible sequences of words that might be recognized. Here we use a separate bigram language model for each move type. We show that when the "correct" move-specific language model is used for each utterance in the test set, the word error rate of the recognizer drops. Of course when the recognizer is run on previously unseen data, it cannot know in advance what move type the speaker has just produced. To determine the move type we use an intonation model combined with a dialog model that puts constraints on possible sequences of move types, as well as the speech recognizer likelihoods for the different move-specific models. In the full recognition system, the combination of automatic move type recognition with the move specific language models reduces the overall word error rate by a small but significant amount when compared with a baseline system that does not take intonation or dialog acts into account. Interestingly, the word error improvement is restricted to "initiating" move types, where word recognition is important. In "response" move types, where the important information is conveyed by the move type itself--for example, positive versus negative response--there is no word error improvement, but recognition of the response types themselves is good. The paper discusses the intonation model, the language models, and the dialog model in detail and describes the architecture in which they are combined.

Infrared telephoto lenses design for joint transform correlator

NASA Astrophysics Data System (ADS)

Chen, Yu; Huo, Furong; Zheng, Liqin

2014-11-01

Joint transform correlator (JTC) is quite useful for pattern recognition in many fields, which can realize automatic real-time recognition of target in cluttered background with high precision. For military application, JTC can also be applied for thermo target recognition especially at night. To make JTC recognize thermo targets, an infrared telephoto lens is designed in this paper. Long focal length and short tube length are required for this usage. So the structure of a positive lens group and a negative lens group are adopted. Besides, the effective focal length and relative aperture should be large enough to ensure the distant targets can be detected with adequate illumination. In this paper, the working waveband of adopted infrared CCD detector is 8-12μm. According to Nyquist law, the characteristic frequency of the system is 14lp/mm. The optional materials are very few for infrared optical systems, in which only several kinds of materials such as Germanium, ZnSe, ZnS are commonly used. Various aberrations are not easy to be corrected. So it is very difficult to design a good infrared optical system. Besides, doublet or triplet should be avoided to be used in infrared optical system considering possible cracking for different thermal expansion coefficients of different infrared materials. The original configuration is composed of three lenses. After optimization, the image quality can get limit diffraction. The root mean square (RMS) radii of three fields are 6.754μm, 7.301μm and 12.158μm respectively. They are all less than the Airy spot diameter 48.8μm. Wavefront aberration at 0.707 field of view (FOV) is only 0.1wavelength. After adjusting the radius to surface templates, setting tolerances and giving element drawings, this system has been fabricated successfully. Optical experimental results of infrared target recognition using JTC are given in this paper. The correlation peaks can be detected and located easily, which confirms the good image quality of the designed infrared telephoto lens.

Dosimetric validation for an automatic brain metastases planning software using single-isocenter dynamic conformal arcsDosimetric validation for an automatic brain metastases planning software using single-isocenter dynamic conformal arcs.

PubMed

Liu, Haisong; Li, Jun; Pappas, Evangelos; Andrews, David; Evans, James; Werner-Wasik, Maria; Yu, Yan; Dicker, Adam; Shi, Wenyin

2016-09-08

An automatic brain-metastases planning (ABMP) software has been installed in our institution. It is dedicated for treating multiple brain metastases with radiosurgery on linear accelerators (linacs) using a single-setup isocenter with noncoplanar dynamic conformal arcs. This study is to validate the calculated absolute dose and dose distribution of ABMP. Three types of measurements were performed to validate the planning software: 1, dual micro ion chambers were used with an acrylic phantom to measure the absolute dose; 2, a 3D cylindrical phantom with dual diode array was used to evaluate 2D dose distribution and point dose for smaller targets; and 3, a 3D pseudo-in vivo patient-specific phantom filled with polymer gels was used to evaluate the accuracy of 3D dose distribution and radia-tion delivery. Micro chamber measurement of two targets (volumes of 1.2 cc and 0.9 cc, respectively) showed that the percentage differences of the absolute dose at both targets were less than 1%. Averaged GI passing rate of five different plans measured with the diode array phantom was above 98%, using criteria of 3% dose difference, 1 mm distance to agreement (DTA), and 10% low-dose threshold. 3D gel phantom measurement results demonstrated a 3D displacement of nine targets of 0.7 ± 0.4 mm (range 0.2 ~ 1.1 mm). The averaged two-dimensional (2D) GI passing rate for several region of interests (ROI) on axial slices that encompass each one of the nine targets was above 98% (5% dose difference, 2 mm DTA, and 10% low-dose threshold). Measured D95, the minimum dose that covers 95% of the target volume, of the nine targets was 0.7% less than the calculated D95. Three different types of dosimetric verification methods were used and proved the dose calculation of the new automatic brain metastases planning (ABMP) software was clinical acceptable. The 3D pseudo-in vivo patient-specific gel phantom test also served as an end-to-end test for validating not only the dose calculation, but the treatment delivery accuracy as well. © 2016 The Authors.

How does the 'rest-self overlap' mediate the qualitative and automatic features of self-reference?

PubMed

Northoff, Georg

2016-01-01

The target article points out the qualitative and automatic features of self-reference while leaving open the underlying neural mechanisms. Based on empirical evidence about rest-self overlap and rest-stimulus interaction being special for self-related stimuli, I postulate that the resting state shows self-specific organization. The resting state's self-specific organization may be encoded by activity balances between different networks which in turn predispose the qualitative features of subsequent self-related stimulus-induced activity in, for instance, SAN as well as the automatic features of self-reference effects.

Targetting and guidance program documentation. [a user's manual

NASA Technical Reports Server (NTRS)

Harrold, E. F.; Neyhard, J. F.

1974-01-01

A FORTRAN computer program was developed which automatically targets two and three burn rendezvous missions and performs feedback guidance using the GUIDE algorithm. The program was designed to accept a large class of orbit specifications and to automatically choose a two or three burn mission depending upon the time alignment of the vehicle and target. The orbits may be specified as any combination of circular and elliptical orbits and may be coplanar or inclined, but must be aligned coaxially with their perigees in the same direction. The program accomplishes the required targeting by repeatedly converging successively more complex missions. It solves the coplanar impulsive version of the mission, then the finite burn coplanar mission, and finally, the full plane change mission. The GUIDE algorithm is exercised in a feedback guidance mode by taking the targeted solution and moving the vehicle state step by step ahead in time, adding acceleration and navigational errors, and reconverging from the perturbed states at fixed guidance update intervals. A program overview is presented, along with a user's guide which details input, output, and the various subroutines.

Automatic detection of multiple UXO-like targets using magnetic anomaly inversion and self-adaptive fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining

2017-12-01

We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

Clustering analysis of moving target signatures

NASA Astrophysics Data System (ADS)

Martone, Anthony; Ranney, Kenneth; Innocenti, Roberto

2010-04-01

Previously, we developed a moving target indication (MTI) processing approach to detect and track slow-moving targets inside buildings, which successfully detected moving targets (MTs) from data collected by a low-frequency, ultra-wideband radar. Our MTI algorithms include change detection, automatic target detection (ATD), clustering, and tracking. The MTI algorithms can be implemented in a real-time or near-real-time system; however, a person-in-the-loop is needed to select input parameters for the clustering algorithm. Specifically, the number of clusters to input into the cluster algorithm is unknown and requires manual selection. A critical need exists to automate all aspects of the MTI processing formulation. In this paper, we investigate two techniques that automatically determine the number of clusters: the adaptive knee-point (KP) algorithm and the recursive pixel finding (RPF) algorithm. The KP algorithm is based on a well-known heuristic approach for determining the number of clusters. The RPF algorithm is analogous to the image processing, pixel labeling procedure. Both algorithms are used to analyze the false alarm and detection rates of three operational scenarios of personnel walking inside wood and cinderblock buildings.

The Extraction of Terrace in the Loess Plateau Based on radial method

NASA Astrophysics Data System (ADS)

Liu, W.; Li, F.

2016-12-01

The terrace of Loess Plateau, as a typical kind of artificial landform and an important measure of soil and water conservation, its positioning and automatic extraction will simplify the work of land use investigation. The existing methods of terrace extraction mainly include visual interpretation and automatic extraction. The manual method is used in land use investigation, but it is time-consuming and laborious. Researchers put forward some automatic extraction methods. For example, Fourier transform method can recognize terrace and find accurate position from frequency domain image, but it is more affected by the linear objects in the same direction of terrace; Texture analysis method is simple and have a wide range application of image processing. The disadvantage of texture analysis method is unable to recognize terraces' edge; Object-oriented is a new method of image classification, but when introduce it to terrace extracting, fracture polygons will be the most serious problem and it is difficult to explain its geological meaning. In order to positioning the terraces, we use high- resolution remote sensing image to extract and analyze the gray value of the pixels which the radial went through. During the recognition process, we firstly use the DEM data analysis or by manual selecting, to roughly confirm the position of peak points; secondly, take each of the peak points as the center to make radials in all directions; finally, extracting the gray values of the pixels which the radials went through, and analyzing its changing characteristics to confirm whether the terrace exists. For the purpose of getting accurate position of terrace, terraces' discontinuity, extension direction, ridge width, image processing algorithm, remote sensing image illumination and other influence factors were fully considered when designing the algorithms.

Automatic recognition of falls in gait-slip training: Harness load cell based criteria.

PubMed

Yang, Feng; Pai, Yi-Chung

2011-08-11

Over-head-harness systems, equipped with load cell sensors, are essential to the participants' safety and to the outcome assessment in perturbation training. The purpose of this study was to first develop an automatic outcome recognition criterion among young adults for gait-slip training and then verify such criterion among older adults. Each of 39 young and 71 older subjects, all protected by safety harness, experienced 8 unannounced, repeated slips, while walking on a 7m walkway. Each trial was monitored with a motion capture system, bilateral ground reaction force (GRF), harness force, and video recording. The fall trials were first unambiguously indentified with careful visual inspection of all video records. The recoveries without balance loss (in which subjects' trailing foot landed anteriorly to the slipping foot) were also first fully recognized from motion and GRF analyses. These analyses then set the gold standard for the outcome recognition with load cell measurements. Logistic regression analyses based on young subjects' data revealed that the peak load cell force was the best predictor of falls (with 100% accuracy) at the threshold of 30% body weight. On the other hand, the peak moving average force of load cell across 1s period, was the best predictor (with 100% accuracy) separating recoveries with backward balance loss (in which the recovery step landed posterior to slipping foot) from harness assistance at the threshold of 4.5% body weight. These threshold values were fully verified using the data from older adults (100% accuracy in recognizing falls). Because of the increasing popularity in the perturbation training coupling with the protective over-head-harness system, this new criterion could have far reaching implications in automatic outcome recognition during the movement therapy. Copyright © 2011 Elsevier Ltd. All rights reserved.

AUTOMATIC RECOGNITION OF FALLS IN GAIT-SLIP: A HARNESS LOAD CELL BASED CRITERION

PubMed Central

Yang, Feng; Pai, Yi-Chung

2012-01-01

Over-head-harness systems, equipped with load cell sensors, are essential to the participants’ safety and to the outcome assessment in perturbation training. The purpose of this study was to first develop an automatic outcome recognition criterion among young adults for gait-slip training and then verify such criterion among older adults. Each of 39 young and 71 older subjects, all protected by safety harness, experienced 8 unannounced, repeated slips, while walking on a 7-m walkway. Each trial was monitored with a motion capture system, bilateral ground reaction force (GRF), harness force and video recording. The fall trials were first unambiguously indentified with careful visual inspection of all video records. The recoveries without balance loss (in which subjects’ trailing foot landed anteriorly to the slipping foot) were also first fully recognized from motion and GRF analyses. These analyses then set the gold standard for the outcome recognition with load cell measurements. Logistic regression analyses based on young subjects’ data revealed that peak load cell force was the best predictor of falls (with 100% accuracy) at the threshold of 30% body weight. On the other hand, the peak moving average force of load cell across 1-s period, was the best predictor (with 100% accuracy) separating recoveries with backward balance loss (in which the recovery step landed posterior to slipping foot) from harness assistance at the threshold of 4.5% body weight. These threshold values were fully verified using the data from older adults (100% accuracy in recognizing falls). Because of the increasing popularity in the perturbation training coupling with the protective over-head-harness system, this new criterion could have far reaching implications in automatic outcome recognition during the movement therapy. PMID:21696744

Automation in visual inspection tasks: X-ray luggage screening supported by a system of direct, indirect or adaptable cueing with low and high system reliability.

PubMed

Chavaillaz, Alain; Schwaninger, Adrian; Michel, Stefan; Sauer, Juergen

2018-05-25

The present study evaluated three automation modes for improving performance in an X-ray luggage screening task. 140 participants were asked to detect the presence of prohibited items in X-ray images of cabin luggage. Twenty participants conducted this task without automatic support (control group), whereas the others worked with either indirect cues (system indicated the target presence without specifying its location), or direct cues (system pointed out the exact target location) or adaptable automation (participants could freely choose between no cue, direct and indirect cues). Furthermore, automatic support reliability was manipulated (low vs. high). The results showed a clear advantage for direct cues regarding detection performance and response time. No benefits were observed for adaptable automation. Finally, high automation reliability led to better performance and higher operator trust. The findings overall confirmed that automatic support systems for luggage screening should be designed such that they provide direct, highly reliable cues.

26 CFR 1.338-0 - Outline of topics.

Code of Federal Regulations, 2014 CFR

2014-04-01

... old target and new target. (a) In general. (1) Deemed transaction. (2) Application of other rules of... target; new target. (18) Target affiliate. (19) 12-month acquisition period. (d) Time and manner of... amount. (iii) Losses not recognized. (iv) Stock subject to election. (e) Liabilities of new target. (1...

Passive automatic anti-piracy defense system of ships

NASA Astrophysics Data System (ADS)

Szustakowski, M.; Życzkowski, M.; Ciurapiński, W.; Karol, M.; Kastek, M.; Stachowiak, R.; Markowski, P.

2013-10-01

The article describes the technological solution for ship self-defense against pirate attacks. The paper presents the design solutions in the field of direct physical protection. All the solutions are connected with the latest optoelectronic and microwave systems and sensors to detect, recognize and the threat posed by pirates. In particular, tests of effectiveness and the detection-range of technology demonstrator developed by a team of authors were carried out.

Retina vascular network recognition

NASA Astrophysics Data System (ADS)

Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

1993-09-01

The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.

Blood detection in wireless capsule endoscope images based on salient superpixels.

PubMed

Iakovidis, Dimitris K; Chatzis, Dimitris; Chrysanthopoulos, Panos; Koulaouzidis, Anastasios

2015-08-01

Wireless capsule endoscopy (WCE) enables screening of the gastrointestinal (GI) tract with a miniature, optical endoscope packed within a small swallowable capsule, wirelessly transmitting color images. In this paper we propose a novel method for automatic blood detection in contemporary WCE images. Blood is an alarming indication for the presence of pathologies requiring further treatment. The proposed method is based on a new definition of superpixel saliency. The saliency of superpixels is assessed upon their color, enabling the identification of image regions that are likely to contain blood. The blood patterns are recognized by their color features using a supervised learning machine. Experiments performed on a public dataset using automatically selected first-order statistical features from various color components indicate that the proposed method outperforms state-of-the-art methods.

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.

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.

Mutated PPP1R3B is recognized by T cells used to treat a melanoma patient who experienced a durable complete tumor regression

PubMed Central

Lu, Yong-Chen; Yao, Xin; Li, Yong F.; El-Gamil, Mona; Dudley, Mark E.; Yang, James C.; Almeida, Jorge R.; Douek, Daniel C.; Samuels, Yardena; Rosenberg, Steven A.; Robbins, Paul F.

2013-01-01

Adoptive cell therapy with tumor infiltrating lymphocytes (TILs) represents an effective treatment for patients with metastatic melanoma. However, most of the antigen targets recognized by effective melanoma reactive TILs remain elusive. In this study, patient 2369 experienced a complete response, including regressions of bulky liver tumor masses ongoing beyond seven years following adoptive TILs transfer. The screening of a cDNA library generated from the autologous melanoma cell line resulted in the isolation of a mutated PPP1R3B (protein phosphatase 1, regulatory (inhibitor) subunit 3B) gene product. The mutated PPP1R3B peptide represents the immunodominant epitope recognized by tumor reactive T cells in TIL 2369. Five years following adoptive transfer, peripheral blood T lymphocytes obtained from patient 2369 recognized the mutated PPP1R3B epitope. These results demonstrate that adoptive T cell therapy targeting a tumor-specific antigen can mediate long-term survival for a patient with metastatic melanoma. This study also provides an impetus to develop personalized immunotherapy targeting tumor-specific, mutated antigens. PMID:23690473

New Tools to Convert PDF Math Contents into Accessible e-Books Efficiently.

PubMed

Suzuki, Masakazu; Terada, Yugo; Kanahori, Toshihiro; Yamaguchi, Katsuhito

2015-01-01

New features in our math-OCR software to convert PDF math contents into accessible e-books are shown. A method for recognizing PDF is thoroughly improved. In addition, contents in any selected area including math formulas in a PDF file can be cut and pasted into a document in various accessible formats, which is automatically recognized and converted into texts and accessible math formulas through this process. Combining it with our authoring tool for a technical document, one can easily produce accessible e-books in various formats such as DAISY, accessible EPUB3, DAISY-like HTML5, Microsoft Word with math objects and so on. Those contents are useful for various print-disabled students ranging from the blind to the dyslexic.

An Experiment in Scientific Code Semantic Analysis

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.

1998-01-01

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, distributed expert parsers. These semantic parser are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. The parsers will automatically recognize and document some static, semantic concepts and locate some program semantic errors. Results are shown for a subroutine test case and a collection of combustion code routines. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Correlation applied to the recognition of regular geometric figures

NASA Astrophysics Data System (ADS)

Lasso, William; Morales, Yaileth; Vega, Fabio; Díaz, Leonardo; Flórez, Daniel; Torres, Cesar

2013-11-01

It developed a system capable of recognizing of regular geometric figures, the images are taken by the software automatically through a process of validating the presence of figure to the camera lens, the digitized image is compared with a database that contains previously images captured, to subsequently be recognized and finally identified using sonorous words referring to the name of the figure identified. The contribution of system set out is the fact that the acquisition of data is done in real time and using a spy smart glasses with usb interface offering an system equally optimal but much more economical. This tool may be useful as a possible application for visually impaired people can get information of surrounding environment.

Daylight control system device and method

DOEpatents

Paton, John Douglas

2007-03-13

A system and device for and a method of programming and controlling light fixtures is disclosed. A system in accordance with the present invention includes a stationary controller unit that is electrically coupled to the light fixtures. The stationary controller unit is configured to be remotely programmed with a portable commissioning device to automatically control the lights fixtures. The stationary controller unit and the portable commissioning device include light sensors, micro-computers and transceivers for measuring light levels, running programs, storing data and transmitting data between the stationary controller unit and the portable commissioning device. In operation, target light levels selected with the portable commissioning device and the controller unit is remotely programmed to automatically maintain the target level.

Daylight control system, device and method

DOEpatents

Paton, John Douglas

2012-08-28

A system and device for and a method of programming and controlling light fixtures is disclosed. A system in accordance with the present invention includes a stationary controller unit that is electrically coupled to the light fixtures. The stationary controller unit is configured to be remotely programmed with a portable commissioning device to automatically control the lights fixtures. The stationary controller unit and the portable commissioning device include light sensors, micro-computers and transceivers for measuring light levels, running programs, storing data and transmitting data between the stationary controller unit and the portable commissioning device. In operation, target light levels selected with the portable commissioning device and the controller unit is remotely programmed to automatically maintain the target level.

Daylight control system device and method

DOEpatents

Paton, John Douglas

2009-12-01

A system and device for and a method of programming and controlling light fixtures is disclosed. A system in accordance with the present invention includes a stationary controller unit that is electrically coupled to the light fixtures. The stationary controller unit is configured to be remotely programmed with a portable commissioning device to automatically control the lights fixtures. The stationary controller unit and the portable commissioning device include light sensors, micro-computers and transceivers for measuring light levels, running programs, storing data and transmitting data between the stationary controller unit and the portable commissioning device. In operation, target light levels selected with the portable commissioning device and the controller unit is remotely programmed to automatically maintain the target level.

Automatic recognition of seismic intensity based on RS and GIS: a case study in Wenchuan Ms8.0 earthquake of China.

PubMed

Zhang, Qiuwen; Zhang, Yan; Yang, Xiaohong; Su, Bin

2014-01-01

In recent years, earthquakes have frequently occurred all over the world, which caused huge casualties and economic losses. It is very necessary and urgent to obtain the seismic intensity map timely so as to master the distribution of the disaster and provide supports for quick earthquake relief. Compared with traditional methods of drawing seismic intensity map, which require many investigations in the field of earthquake area or are too dependent on the empirical formulas, spatial information technologies such as Remote Sensing (RS) and Geographical Information System (GIS) can provide fast and economical way to automatically recognize the seismic intensity. With the integrated application of RS and GIS, this paper proposes a RS/GIS-based approach for automatic recognition of seismic intensity, in which RS is used to retrieve and extract the information on damages caused by earthquake, and GIS is applied to manage and display the data of seismic intensity. The case study in Wenchuan Ms8.0 earthquake in China shows that the information on seismic intensity can be automatically extracted from remotely sensed images as quickly as possible after earthquake occurrence, and the Digital Intensity Model (DIM) can be used to visually query and display the distribution of seismic intensity.

Improve accuracy for automatic acetabulum segmentation in CT images.

PubMed

Liu, Hao; Zhao, Jianning; Dai, Ning; Qian, Hongbo; Tang, Yuehong

2014-01-01

Separation of the femur head and acetabulum is one of main difficulties in the diseased hip joint due to deformed shapes and extreme narrowness of the joint space. To improve the segmentation accuracy is the key point of existing automatic or semi-automatic segmentation methods. In this paper, we propose a new method to improve the accuracy of the segmented acetabulum using surface fitting techniques, which essentially consists of three parts: (1) design a surface iterative process to obtain an optimization surface; (2) change the ellipsoid fitting to two-phase quadric surface fitting; (3) bring in a normal matching method and an optimization region method to capture edge points for the fitting quadric surface. Furthermore, this paper cited vivo CT data sets of 40 actual patients (with 79 hip joints). Test results for these clinical cases show that: (1) the average error of the quadric surface fitting method is 2.3 (mm); (2) the accuracy ratio of automatically recognized contours is larger than 89.4%; (3) the error ratio of section contours is less than 10% for acetabulums without severe malformation and less than 30% for acetabulums with severe malformation. Compared with similar methods, the accuracy of our method, which is applied in a software system, is significantly enhanced.

Automatic polymerase chain reaction product detection system for food safety monitoring using zinc finger protein fused to luciferase.

PubMed

Yoshida, Wataru; Kezuka, Aki; Murakami, Yoshiyuki; Lee, Jinhee; Abe, Koichi; Motoki, Hiroaki; Matsuo, Takafumi; Shimura, Nobuaki; Noda, Mamoru; Igimi, Shizunobu; Ikebukuro, Kazunori

2013-11-01

An automatic polymerase chain reaction (PCR) product detection system for food safety monitoring using zinc finger (ZF) protein fused to luciferase was developed. ZF protein fused to luciferase specifically binds to target double stranded DNA sequence and has luciferase enzymatic activity. Therefore, PCR products that comprise ZF protein recognition sequence can be detected by measuring the luciferase activity of the fusion protein. We previously reported that PCR products from Legionella pneumophila and Escherichia coli (E. coli) O157 genomic DNA were detected by Zif268, a natural ZF protein, fused to luciferase. In this study, Zif268-luciferase was applied to detect the presence of Salmonella and coliforms. Moreover, an artificial zinc finger protein (B2) fused to luciferase was constructed for a Norovirus detection system. In the luciferase activity detection assay, several bound/free separation process is required. Therefore, an analyzer that automatically performed the bound/free separation process was developed to detect PCR products using the ZF-luciferase fusion protein. By means of the automatic analyzer with ZF-luciferase fusion protein, target pathogenic genomes were specifically detected in the presence of other pathogenic genomes. Moreover, we succeeded in the detection of 10 copies of E. coli BL21 without extraction of genomic DNA by the automatic analyzer and E. coli was detected with a logarithmic dependency in the range of 1.0×10 to 1.0×10(6) copies. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations

PubMed Central

Langenkämper, Daniel; Jakobi, Tobias; Feld, Dustin; Jelonek, Lukas; Goesmann, Alexander; Nattkemper, Tim W.

2016-01-01

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures. PMID:26904094

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations.

PubMed

Langenkämper, Daniel; Jakobi, Tobias; Feld, Dustin; Jelonek, Lukas; Goesmann, Alexander; Nattkemper, Tim W

2016-01-01

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures.

Automatic Target Recognition: Statistical Feature Selection of Non-Gaussian Distributed Target Classes

DTIC Science & Technology

2011-06-01

implementing, and evaluating many feature selection algorithms. Mucciardi and Gose compared seven different techniques for choosing subsets of pattern...122 THIS PAGE INTENTIONALLY LEFT BLANK 123 LIST OF REFERENCES [1] A. Mucciardi and E. Gose , “A comparison of seven techniques for

Automatic small target detection in synthetic infrared images

NASA Astrophysics Data System (ADS)

Yardımcı, Ozan; Ulusoy, Ä.°lkay

2017-05-01

Automatic detection of targets from far distances is a very challenging problem. Background clutter and small target size are the main difficulties which should be solved while reaching a high detection performance as well as a low computational load. The pre-processing, detection and post-processing approaches are very effective on the final results. In this study, first of all, various methods in the literature were evaluated separately for each of these stages using the simulated test scenarios. Then, a full system of detection was constructed among available solutions which resulted in the best performance in terms of detection. However, although a precision rate as 100% was reached, the recall values stayed low around 25-45%. Finally, a post-processing method was proposed which increased the recall value while keeping the precision at 100%. The proposed post-processing method, which is based on local operations, increased the recall value to 65-95% in all test scenarios.

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.

Validation of a new classifier for the automated analysis of the human epidermal growth factor receptor 2 (HER2) gene amplification in breast cancer specimens

PubMed Central

2013-01-01

Amplification of the human epidermal growth factor receptor 2 (HER2) is a prognostic marker for poor clinical outcome and a predictive marker for therapeutic response to targeted therapies in breast cancer patients. With the introduction of anti-HER2 therapies, accurate assessment of HER2 status has become essential. Fluorescence in situ hybridization (FISH) is a widely used technique for the determination of HER2 status in breast cancer. However, the manual signal enumeration is time-consuming. Therefore, several companies like MetaSystem have developed automated image analysis software. Some of these signal enumeration software employ the so called “tile-sampling classifier”, a programming algorithm through which the software quantifies fluorescent signals in images on the basis of square tiles of fixed dimensions. Considering that the size of tile does not always correspond to the size of a single tumor cell nucleus, some users argue that this analysis method might not completely reflect the biology of cells. For that reason, MetaSystems has developed a new classifier which is able to recognize nuclei within tissue sections in order to determine the HER2 amplification status on nuclei basis. We call this new programming algorithm “nuclei-sampling classifier”. In this study, we evaluated the accuracy of the “nuclei-sampling classifier” in determining HER2 gene amplification by FISH in nuclei of breast cancer cells. To this aim, we randomly selected from our cohort 64 breast cancer specimens (32 nonamplified and 32 amplified) and we compared results obtained through manual scoring and through this new classifier. The new classifier automatically recognized individual nuclei. The automated analysis was followed by an optional human correction, during which the user interacted with the software in order to improve the selection of cell nuclei automatically selected. Overall concordance between manual scoring and automated nuclei-sampling analysis was 98.4% (100% for nonamplified cases and 96.9% for amplified cases). However, after human correction, concordance between the two methods was 100%. We conclude that the nuclei-based classifier is a new available tool for automated quantitative HER2 FISH signals analysis in nuclei in breast cancer specimen and it can be used for clinical purposes. PMID:23379971

The automaticity of vantage point shifts within a synaesthetes' spatial calendar.

PubMed

Jarick, Michelle; Jensen, Candice; Dixon, Michael J; Smilek, Daniel

2011-09-01

Time-space synaesthetes report that time units (e.g., months, days, hours) occupy idiosyncratic spatial locations. For the synaesthete (L), the months of the year are projected out in external space in the shape of a 'scoreboard 7', where January to July extend across the top from left to right and August to December make up the vertical segment from top to bottom. Interestingly, L can change the mental vantage point (MVP) from where she views her month-space depending on whether she sees or hears the month name. We used a spatial cueing task to demonstrate that L's attention could be directed to locations within her time-space and change vantage points automatically - from trial to trial. We also sought to eliminate any influence of strategy on L's performance by shortening the interval between the cue and target onset to only 150 ms, and have the targets fall in synaesthetically cued locations on only 15% of trials. If L's performance was attributable to intentionally using the cue to predict target location, these manipulations should eliminate any cueing effects. In two separate experiments, we found that L still showed an attentional bias consistent with her synaesthesia. Thus, we attribute L's rapid and resilient cueing effects to the automaticity of her spatial forms. ©2011 The British Psychological Society.

Precision Targeting With a Tracking Adaptive Optics Scanning Laser Ophthalmoscope

DTIC Science & Technology

2006-01-01

automatic high- resolution mosaic generation, and automatic blink detection and tracking re-lock were also tested. The system has the potential to become an...structures can lead to earlier detection of retinal diseases such as age-related macular degeneration (AMD) and diabetic retinopathy (DR). Combined...optics systems sense perturbations in the detected wave-front and apply corrections to an optical element that flatten the wave-front and allow near

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

Signal-Noise Identification of Magnetotelluric Signals Using Fractal-Entropy and Clustering Algorithm for Targeted De-Noising

NASA Astrophysics Data System (ADS)

Li, Jin; Zhang, Xian; Gong, Jinzhe; Tang, Jingtian; Ren, Zhengyong; Li, Guang; Deng, Yanli; Cai, Jin

A new technique is proposed for signal-noise identification and targeted de-noising of Magnetotelluric (MT) signals. This method is based on fractal-entropy and clustering algorithm, which automatically identifies signal sections corrupted by common interference (square, triangle and pulse waves), enabling targeted de-noising and preventing the loss of useful information in filtering. To implement the technique, four characteristic parameters — fractal box dimension (FBD), higuchi fractal dimension (HFD), fuzzy entropy (FuEn) and approximate entropy (ApEn) — are extracted from MT time-series. The fuzzy c-means (FCM) clustering technique is used to analyze the characteristic parameters and automatically distinguish signals with strong interference from the rest. The wavelet threshold (WT) de-noising method is used only to suppress the identified strong interference in selected signal sections. The technique is validated through signal samples with known interference, before being applied to a set of field measured MT/Audio Magnetotelluric (AMT) data. Compared with the conventional de-noising strategy that blindly applies the filter to the overall dataset, the proposed method can automatically identify and purposefully suppress the intermittent interference in the MT/AMT signal. The resulted apparent resistivity-phase curve is more continuous and smooth, and the slow-change trend in the low-frequency range is more precisely reserved. Moreover, the characteristic of the target-filtered MT/AMT signal is close to the essential characteristic of the natural field, and the result more accurately reflects the inherent electrical structure information of the measured site.

Difficulty identifying feelings and automatic activation in the fusiform gyrus in response to facial emotion.

PubMed

Eichmann, Mischa; Kugel, Harald; Suslow, Thomas

2008-12-01

Difficulties in identifying and differentiating one's emotions are a central characteristic of alexithymia. In the present study, automatic activation of the fusiform gyrus to facial emotion was investigated as a function of alexithymia as assessed by the 20-item Toronto Alexithymia Scale. During 3 Tesla fMRI scanning, pictures of faces bearing sad, happy, and neutral expressions masked by neutral faces were presented to 22 healthy adults who also responded to the Toronto Alexithymia Scale. The fusiform gyrus was selected as the region of interest, and voxel values of this region were extracted, summarized as means, and tested among the different conditions (sad, happy, and neutral faces). Masked sad facial emotions were associated with greater bilateral activation of the fusiform gyrus than masked neutral faces. The subscale, Difficulty Identifying Feelings, was negatively correlated with the neural response of the fusiform gyrus to masked sad faces. The correlation results suggest that automatic hyporesponsiveness of the fusiform gyrus to negative emotion stimuli may reflect problems in recognizing one's emotions in everyday life.

Automatic analysis for neuron by confocal laser scanning microscope

NASA Astrophysics Data System (ADS)

Satou, Kouhei; Aoki, Yoshimitsu; Mataga, Nobuko; Hensh, Takao K.; Taki, Katuhiko

2005-12-01

The aim of this study is to develop a system that recognizes both the macro- and microscopic configurations of nerve cells and automatically performs the necessary 3-D measurements and functional classification of spines. The acquisition of 3-D images of cranial nerves has been enabled by the use of a confocal laser scanning microscope, although the highly accurate 3-D measurements of the microscopic structures of cranial nerves and their classification based on their configurations have not yet been accomplished. In this study, in order to obtain highly accurate measurements of the microscopic structures of cranial nerves, existing positions of spines were predicted by the 2-D image processing of tomographic images. Next, based on the positions that were predicted on the 2-D images, the positions and configurations of the spines were determined more accurately by 3-D image processing of the volume data. We report the successful construction of an automatic analysis system that uses a coarse-to-fine technique to analyze the microscopic structures of cranial nerves with high speed and accuracy by combining 2-D and 3-D image analyses.

Nuclear Security: Target Analysis

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

Singh, Surinder Paul; Gibbs, Philip W.; Bultz, Garl A.

2014-03-01

This objectives of this session were to understand the basic steps of target identification; describe the SNRI targets in detail; characterize specific targets with more detail; prioritize targets based on guidance documents; understand the graded safeguards concept; identify roll up and understand why it is a concern; and recognize the category for different materials.

SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework

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

Santhanam, A; Min, Y; Beron, P

Purpose: Patient safety hazards such as a wrong patient/site getting treated can lead to catastrophic results. The purpose of this project is to automatically detect potential patient safety hazards during the radiotherapy setup and alert the therapist before the treatment is initiated. Methods: We employed a set of co-located and co-registered 3D cameras placed inside the treatment room. Each camera provided a point-cloud of fraxels (fragment pixels with 3D depth information). Each of the cameras were calibrated using a custom-built calibration target to provide 3D information with less than 2 mm error in the 500 mm neighborhood around the isocenter.more » To identify potential patient safety hazards, the treatment room components and the patient’s body needed to be identified and tracked in real-time. For feature recognition purposes, we used a graph-cut based feature recognition with principal component analysis (PCA) based feature-to-object correlation to segment the objects in real-time. Changes in the object’s position were tracked using the CamShift algorithm. The 3D object information was then stored for each classified object (e.g. gantry, couch). A deep learning framework was then used to analyze all the classified objects in both 2D and 3D and was then used to fine-tune a convolutional network for object recognition. The number of network layers were optimized to identify the tracked objects with >95% accuracy. Results: Our systematic analyses showed that, the system was effectively able to recognize wrong patient setups and wrong patient accessories. The combined usage of 2D camera information (color + depth) enabled a topology-preserving approach to verify patient safety hazards in an automatic manner and even in scenarios where the depth information is partially available. Conclusion: By utilizing the 3D cameras inside the treatment room and a deep learning based image classification, potential patient safety hazards can be effectively avoided.« less

Performance of the Colson MAM BP 3AA1-2 automatic blood pressure monitor according to the European Society of Hypertension validation protocol.

PubMed

Pereira, Telmo; Maldonado, João

2005-11-01

To evaluate the performance of the Colson MAM BP 3AA1-2 oscillometric automatic blood pressure monitor according to the validation protocol of the European Society of Hypertension, testing its suitability for self-measurement of blood pressure. The performance of the device was assessed in relation to various clinical variables, including age, gender, body mass index, arm circumference and arterial stiffness. 33 subjects (15 men and 18 women), with a mean age of 47 +/- 10 years, were studied according to the procedures laid down in the European Society of Hypertension validation protocol. Sequential same-arm blood pressure measurements were made, alternating between a mercury standard and the automatic device. The differences among the test-control measurements were assessed and divided into categorization zones of 5, 10 and 15 mmHg discrepancy. Aortic pulse wave velocity was assessed in all subjects with a Complior device (Colson, Paris). The Colson MAM BP 3AA1-2 passed all three phases of the protocol for both systolic and diastolic blood pressure. The mean differences between the test and control measurements were -1.0 +/- 5.0 mmHg for systolic blood pressure and -1.1 +/- 4.1 mmHg for diastolic blood pressure. Both standard deviations are well below the 8 mmHg limit proposed by the Association for the Advancement of Medical Instrumentation. The predictive value of various clinical variables for the discrepancies was assessed by a regression model analysis, with no variable being found that independently undermined the performance of the monitor. In another regression analysis, we found a similar relation between test and control blood pressures and aortic pulse wave velocity, a widely recognized and validated index of target organ damage. These data show that the Colson MAM BP 3AA1-2 satisfies the quality requirements proposed by the European Society of Hypertension, demonstrating its suitability for inclusion in integrated programs of clinical surveillance based on self-measurement of blood pressure. The uniformity of its performance over a wide spectrum of clinical characteristics and the relation found with pulse wave velocity further reinforce its clinical validity.

Real-time automatic registration in optical surgical navigation

NASA Astrophysics Data System (ADS)

Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming

2016-05-01

An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

Inexpensive automated paging system for use at remote research sites

USGS Publications Warehouse

Sargent, S.L.; Dey, W.S.; Keefer, D.A.

1998-01-01

The use of a flow-activated automatic sampler at a remote research site required personnel to periodically visit the site to collect samples and reset the automatic sampler. To reduce site visits, a cellular telephone was modified for activation by a datalogger. The purpose of this study was to demonstrate the use and benefit of the modified telephone. Both the power switch and the speed-dial button on the telephone were bypassed and wired to a relay driver. The datalogger was programmed to compare values of a monitored environmental parameter with a target value. When the target value was reached or exceeded, the datalogger pulsed a relay driver, activating power to the telephone. A separate relay activated the speed dial, dialing the number of a tone-only pager. The use of this system has saved time and reduced travel costs by reducing the number of trips to the site, without the loss of any data.The use of a flow-activated automatic sampler at a remote research site required personnel to periodically visit the site to collect samples and reset the automatic sampler. To reduce site visits, a cellular telephone was modified for activation by a datalogger. The purpose of this study was to demonstrate the use and benefit of the modified telephone. Both the power switch and the speed-dial button on the telephone were bypassed and wired to a relay driver. The datalogger was programmed to compare values of a monitored environmental parameter with a target value. When the target value was reached or exceeded, the datalogger pulsed a relay driver, activating power to the telephone. A separate relay activated the speed dial, dialing the number of a tone-only pager. The use of this system has saved time and reduced travel costs by reducing the number of trips to the site, without the loss of any data.

The Fragile X Mental Retardation Protein, FMRP, Recognizes G-Quartets

ERIC Educational Resources Information Center

Darnell, Jennifer C.; Warren, Stephen T.; Darnell, Robert B.

2004-01-01

Fragile X mental retardation is a disease caused by the loss of function of a single RNA-binding protein, FMRP. Identifying the RNA targets recognized by FMRP is likely to reveal much about its functions in controlling some aspects of memory and behavior. Recent evidence suggests that one of the predominant RNA motifs recognized by the FMRP…

Security Event Recognition for Visual Surveillance

NASA Astrophysics Data System (ADS)

Liao, W.; Yang, C.; Yang, M. Ying; Rosenhahn, B.

2017-05-01

With rapidly increasing deployment of surveillance cameras, the reliable methods for automatically analyzing the surveillance video and recognizing special events are demanded by different practical applications. This paper proposes a novel effective framework for security event analysis in surveillance videos. First, convolutional neural network (CNN) framework is used to detect objects of interest in the given videos. Second, the owners of the objects are recognized and monitored in real-time as well. If anyone moves any object, this person will be verified whether he/she is its owner. If not, this event will be further analyzed and distinguished between two different scenes: moving the object away or stealing it. To validate the proposed approach, a new video dataset consisting of various scenarios is constructed for more complex tasks. For comparison purpose, the experiments are also carried out on the benchmark databases related to the task on abandoned luggage detection. The experimental results show that the proposed approach outperforms the state-of-the-art methods and effective in recognizing complex security events.

Research of Daily Conversation Transmitting System Based on Mouth Part Pattern Recognition

NASA Astrophysics Data System (ADS)

Watanabe, Mutsumi; Nishi, Natsuko

The authors are developing a vision-based intension transfer technique by recognizing user’s face expressions and movements, to help free and convenient communications with aged or disabled persons who find difficulties in talking, discriminating small character prints and operating keyboards by hands and fingers. In this paper we report a prototype system, where layered daily conversations are successively selected by recognizing the transition in shape of user’s mouth parts using camera image sequences settled in front of the user. Four mouth part patterns are used in the system. A method that automatically recognizes these patterns by analyzing the intensity histogram data around the mouth region is newly developed. The confirmation of a selection on the way is executed by detecting the open and shut movements of mouth through the temporal change in intensity histogram data. The method has been installed in a desktop PC by VC++ programs. Experimental results of mouth shape pattern recognition by twenty-five persons have shown the effectiveness of the method.

Activity Recognition for Personal Time Management

NASA Astrophysics Data System (ADS)

Prekopcsák, Zoltán; Soha, Sugárka; Henk, Tamás; Gáspár-Papanek, Csaba

We describe an accelerometer based activity recognition system for mobile phones with a special focus on personal time management. We compare several data mining algorithms for the automatic recognition task in the case of single user and multiuser scenario, and improve accuracy with heuristics and advanced data mining methods. The results show that daily activities can be recognized with high accuracy and the integration with the RescueTime software can give good insights for personal time management.

DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real-Time Recognition and Localization of Marine Mammals

DTIC Science & Technology

2013-09-30

method has been successfully implemented to automatically detect and recognize pulse trains from minke whales ( songs ) and sperm whales (Physeter...workshops, conferences and data challenges 2. Enhancements of the ASR algorithm for frequency-modulated sounds: Right Whale Study 3...Enhancements of the ASR algorithm for pulse trains: Minke Whale Study 4. Mining Big Data Sound Archives using High Performance Computing software and hardware

Internally- and externally-driven network transitions as a basis for automatic and strategic processes in semantic priming: theory and experimental validation

PubMed Central

Lerner, Itamar; Shriki, Oren

2014-01-01

For the last four decades, semantic priming—the facilitation in recognition of a target word when it follows the presentation of a semantically related prime word—has been a central topic in research of human cognitive processing. Studies have drawn a complex picture of findings which demonstrated the sensitivity of this priming effect to a unique combination of variables, including, but not limited to, the type of relatedness between primes and targets, the prime-target Stimulus Onset Asynchrony (SOA), the relatedness proportion (RP) in the stimuli list and the specific task subjects are required to perform. Automatic processes depending on the activation patterns of semantic representations in memory and controlled strategies adapted by individuals when attempting to maximize their recognition performance have both been implicated in contributing to the results. Lately, we have published a new model of semantic priming that addresses the majority of these findings within one conceptual framework. In our model, semantic memory is depicted as an attractor neural network in which stochastic transitions from one stored pattern to another are continually taking place due to synaptic depression mechanisms. We have shown how such transitions, in combination with a reinforcement-learning rule that adjusts their pace, resemble the classic automatic and controlled processes involved in semantic priming and account for a great number of the findings in the literature. Here, we review the core findings of our model and present new simulations that show how similar principles of parameter-adjustments could account for additional data not addressed in our previous studies, such as the relation between expectancy and inhibition in priming, target frequency and target degradation effects. Finally, we describe two human experiments that validate several key predictions of the model. PMID:24795670

Musical space synesthesia: automatic, explicit and conceptual connections between musical stimuli and space.

PubMed

Akiva-Kabiri, Lilach; Linkovski, Omer; Gertner, Limor; Henik, Avishai

2014-08-01

In musical-space synesthesia, musical pitches are perceived as having a spatially defined array. Previous studies showed that symbolic inducers (e.g., numbers, months) can modulate response according to the inducer's relative position on the synesthetic spatial form. In the current study we tested two musical-space synesthetes and a group of matched controls on three different tasks: musical-space mapping, spatial cue detection and a spatial Stroop-like task. In the free mapping task, both synesthetes exhibited a diagonal organization of musical pitch tones rising from bottom left to the top right. This organization was found to be consistent over time. In the subsequent tasks, synesthetes were asked to ignore an auditory or visually presented musical pitch (irrelevant information) and respond to a visual target (i.e., an asterisk) on the screen (relevant information). Compatibility between musical pitch and the target's spatial location was manipulated to be compatible or incompatible with the synesthetes' spatial representations. In the spatial cue detection task participants had to press the space key immediately upon detecting the target. In the Stroop-like task, they had to reach the target by using a mouse cursor. In both tasks, synesthetes' performance was modulated by the compatibility between irrelevant and relevant spatial information. Specifically, the target's spatial location conflicted with the spatial information triggered by the irrelevant musical stimulus. These results reveal that for musical-space synesthetes, musical information automatically orients attention according to their specific spatial musical-forms. The present study demonstrates the genuineness of musical-space synesthesia by revealing its two hallmarks-automaticity and consistency. In addition, our results challenge previous findings regarding an implicit vertical representation for pitch tones in non-synesthete musicians. Copyright © 2014 Elsevier Inc. All rights reserved.

Using the QCM Biosensor-Based T7 Phage Display Combined with Bioinformatics Analysis for Target Identification of Bioactive Small Molecule.

PubMed

Takakusagi, Yoichi; Takakusagi, Kaori; Sugawara, Fumio; Sakaguchi, Kengo

2018-01-01

Identification of target proteins that directly bind to bioactive small molecule is of great interest in terms of clarifying the mode of action of the small molecule as well as elucidating the biological phenomena at the molecular level. Of the experimental technologies available, T7 phage display allows comprehensive screening of small molecule-recognizing amino acid sequence from the peptide libraries displayed on the T7 phage capsid. Here, we describe the T7 phage display strategy that is combined with quartz-crystal microbalance (QCM) biosensor for affinity selection platform and bioinformatics analysis for small molecule-recognizing short peptides. This method dramatically enhances efficacy and throughput of the screening for small molecule-recognizing amino acid sequences without repeated rounds of selection. Subsequent execution of bioinformatics programs allows combinatorial and comprehensive target protein discovery of small molecules with its binding site, regardless of protein sample insolubility, instability, or inaccessibility of the fixed small molecules to internally located binding site on larger target proteins when conventional proteomics approaches are used.

Effectiveness of an automatic tracking software in underwater motion analysis.

PubMed

Magalhaes, Fabrício A; Sawacha, Zimi; Di Michele, Rocco; Cortesi, Matteo; Gatta, Giorgio; Fantozzi, Silvia

2013-01-01

Tracking of markers placed on anatomical landmarks is a common practice in sports science to perform the kinematic analysis that interests both athletes and coaches. Although different software programs have been developed to automatically track markers and/or features, none of them was specifically designed to analyze underwater motion. Hence, this study aimed to evaluate the effectiveness of a software developed for automatic tracking of underwater movements (DVP), based on the Kanade-Lucas-Tomasi feature tracker. Twenty-one video recordings of different aquatic exercises (n = 2940 markers' positions) were manually tracked to determine the markers' center coordinates. Then, the videos were automatically tracked using DVP and a commercially available software (COM). Since tracking techniques may produce false targets, an operator was instructed to stop the automatic procedure and to correct the position of the cursor when the distance between the calculated marker's coordinate and the reference one was higher than 4 pixels. The proportion of manual interventions required by the software was used as a measure of the degree of automation. Overall, manual interventions were 10.4% lower for DVP (7.4%) than for COM (17.8%). Moreover, when examining the different exercise modes separately, the percentage of manual interventions was 5.6% to 29.3% lower for DVP than for COM. Similar results were observed when analyzing the type of marker rather than the type of exercise, with 9.9% less manual interventions for DVP than for COM. In conclusion, based on these results, the developed automatic tracking software presented can be used as a valid and useful tool for underwater motion analysis. Key PointsThe availability of effective software for automatic tracking would represent a significant advance for the practical use of kinematic analysis in swimming and other aquatic sports.An important feature of automatic tracking software is to require limited human interventions and supervision, thus allowing short processing time.When tracking underwater movements, the degree of automation of the tracking procedure is influenced by the capability of the algorithm to overcome difficulties linked to the small target size, the low image quality and the presence of background clutters.The newly developed feature-tracking algorithm has shown a good automatic tracking effectiveness in underwater motion analysis with significantly smaller percentage of required manual interventions when compared to a commercial software.

Automatic Processing and the Unitization of Two Features.

DTIC Science & Technology

1980-02-01

experiment, LaBerge (1973) showed that with practice two features could be automatically unitized to form a novel character. We wish to address a...different from a search for a target which requires identification of one of the features alone. Page 2 Indeed, LaBerge (1973) used a similar implicit...perception? Journal of Experimental Child Psychology, 1978, 26, 498-507. LaBerge , D. Attention and the measurement of perceptual learning. Memory and

Perspective taking combats automatic expressions of racial bias.

PubMed

Todd, Andrew R; Bodenhausen, Galen V; Richeson, Jennifer A; Galinsky, Adam D

2011-06-01

Five experiments investigated the hypothesis that perspective taking--actively contemplating others' psychological experiences--attenuates automatic expressions of racial bias. Across the first 3 experiments, participants who adopted the perspective of a Black target in an initial context subsequently exhibited more positive automatic interracial evaluations, with changes in automatic evaluations mediating the effect of perspective taking on more deliberate interracial evaluations. Furthermore, unlike other bias-reduction strategies, the interracial positivity resulting from perspective taking was accompanied by increased salience of racial inequalities (Experiment 3). Perspective taking also produced stronger approach-oriented action tendencies toward Blacks (but not Whites; Experiment 4). A final experiment revealed that face-to-face interactions with perspective takers were rated more positively by Black interaction partners than were interactions with nonperspective takers--a relationship that was mediated by perspective takers' increased approach-oriented nonverbal behaviors (as rated by objective, third-party observers). These findings indicate that perspective taking can combat automatic expressions of racial biases without simultaneously decreasing sensitivity to ongoing racial disparities. 2011 APA, all rights reserved

Modeling and Representation of Human Hearts for Volumetric Measurement

PubMed Central

Guan, Qiu; Wang, Wanliang; Wu, Guang

2012-01-01

This paper investigates automatic construction of a three-dimensional heart model from a set of medical images, represents it in a deformable shape, and uses it to perform volumetric measurements. This not only significantly improves its reliability and accuracy but also makes it possible to derive valuable novel information, like various assessment and dynamic volumetric measurements. The method is based on a flexible model trained from hundreds of patient image sets by a genetic algorithm, which takes advantage of complete segmentation of the heart shape to form a geometrical heart model. For an image set of a new patient, an interpretation scheme is used to obtain its shape and evaluate some important parameters. Apart from automatic evaluation of traditional heart functions, some new information of cardiovascular diseases may be recognized from the volumetric analysis. PMID:22162723

Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

PubMed

Corneanu, Ciprian Adrian; Simon, Marc Oliu; Cohn, Jeffrey F; Guerrero, Sergio Escalera

2016-08-01

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.

Sub-surface defects detection of by using active thermography and advanced image edge detection

NASA Astrophysics Data System (ADS)

Tse, Peter W.; Wang, Gaochao

2017-05-01

Active or pulsed thermography is a popular non-destructive testing (NDT) tool for inspecting the integrity and anomaly of industrial equipment. One of the recent research trends in using active thermography is to automate the process in detecting hidden defects. As of today, human effort has still been using to adjust the temperature intensity of the thermo camera in order to visually observe the difference in cooling rates caused by a normal target as compared to that by a sub-surface crack exists inside the target. To avoid the tedious human-visual inspection and minimize human induced error, this paper reports the design of an automatic method that is capable of detecting subsurface defects. The method used the technique of active thermography, edge detection in machine vision and smart algorithm. An infrared thermo-camera was used to capture a series of temporal pictures after slightly heating up the inspected target by flash lamps. Then the Canny edge detector was employed to automatically extract the defect related images from the captured pictures. The captured temporal pictures were preprocessed by a packet of Canny edge detector and then a smart algorithm was used to reconstruct the whole sequences of image signals. During the processes, noise and irrelevant backgrounds exist in the pictures were removed. Consequently, the contrast of the edges of defective areas had been highlighted. The designed automatic method was verified by real pipe specimens that contains sub-surface cracks. After applying such smart method, the edges of cracks can be revealed visually without the need of using manual adjustment on the setting of thermo-camera. With the help of this automatic method, the tedious process in manually adjusting the colour contract and the pixel intensity in order to reveal defects can be avoided.

Advanced MicroObserver UGS integration with and cueing of the BattleHawk squad level loitering munition and UAV

NASA Astrophysics Data System (ADS)

Steadman, Bob; Finklea, John; Kershaw, James; Loughman, Cathy; Shaffner, Patti; Frost, Dean; Deller, Sean

2014-06-01

Textron's Advanced MicroObserver(R) is a next generation remote unattended ground sensor system (UGS) for border security, infrastructure protection, and small combat unit security. The original MicroObserver(R) is a sophisticated seismic sensor system with multi-node fusion that supports target tracking. This system has been deployed in combat theaters. The system's seismic sensor nodes are uniquely able to be completely buried (including antennas) for optimal covertness. The advanced version adds a wireless day/night Electro-Optic Infrared (EOIR) system, cued by seismic tracking, with sophisticated target discrimination and automatic frame capture features. Also new is a field deployable Gateway configurable with a variety of radio systems and flexible networking, an important upgrade that enabled the research described herein. BattleHawkTM is a small tube launched Unmanned Air Vehicle (UAV) with a warhead. Using transmitted video from its EOIR subsystem an operator can search for and acquire a target day or night, select a target for attack, and execute terminal dive to destroy the target. It is designed as a lightweight squad level asset carried by an individual infantryman. Although BattleHawk has the best loiter time in its class, it's still relatively short compared to large UAVs. Also it's a one-shot asset in its munition configuration. Therefore Textron Defense Systems conducted research, funded internally, to determine if there was military utility in having the highly persistent MicroObserver(R) system cue BattleHawk's launch and vector it to beyond visual range targets for engagement. This paper describes that research; the system configuration implemented, and the results of field testing that was performed on a government range early in 2013. On the integrated system that was implemented, MicroObserver(R) seismic detections activated that system's camera which then automatically captured images of the target. The geo-referenced and time-tagged MicroObserver(R) target reports and images were then automatically forwarded to the BattleHawk Android-based controller. This allowed the operator to see the intruder (classified and geo-located) on the map based display, assess the intruder as likely hostile (via the image), and launch BattleHawk with the pre-loaded target coordinates. The operator was thus able to quickly acquire the intended target (without a search) and initiate target engagement immediately. System latencies were a major concern encountered during the research.

Classification of video sequences into chosen generalized use classes of target size and lighting level.

PubMed

Leszczuk, Mikołaj; Dudek, Łukasz; Witkowski, Marcin

The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage time-frame, discrimination level, target size, lighting level, and level of motion. These parameters form what are referred to as Generalized Use Classes (GUCs). The aim of our research was to develop algorithms that would automatically assist classification of input sequences into one of the GUCs. Target size and lighting level parameters were approached. The experiment described reveals the experts' ambiguity and hesitation during the manual target size determination process. However, the automatic methods developed for target size classification make it possible to determine GUC parameters with 70 % compliance to the end-users' opinion. Lighting levels of the entire sequence can be classified with an efficiency reaching 93 %. To make the algorithms available for use, a test application has been developed. It is able to process video files and display classification results, the user interface being very simple and requiring only minimal user interaction.

Resolution Enhanced Magnetic Sensing System for Wide Coverage Real Time UXO Detection

NASA Astrophysics Data System (ADS)

Zalevsky, Zeev; Bregman, Yuri; Salomonski, Nizan; Zafrir, Hovav

2012-09-01

In this paper we present a new high resolution automatic detection algorithm based upon a Wavelet transform and then validate it in marine related experiments. The proposed approach allows obtaining an automatic detection in a very low signal to noise ratios. The amount of calculations is reduced, the magnetic trend is depressed and the probability of detection/ false alarm rate can easily be controlled. Moreover, the algorithm enables to distinguish between close targets. In the algorithm we use the physical dependence of the magnetic field of a magnetic dipole in order to define a Wavelet mother function that later on can detect magnetic targets modeled as dipoles and embedded in noisy surrounding, at improved resolution. The proposed algorithm was realized on synthesized targets and then validated in field experiments involving a marine surface-floating system for wide coverage real time unexploded ordinance (UXO) detection and mapping. The detection probability achieved in the marine experiment was above 90%. The horizontal radial error of most of the detected targets was only 16 m and two baseline targets that were immersed about 20 m one to another could easily be distinguished.

Structural Basis for the Altered PAM Recognition by Engineered CRISPR-Cpf1.

PubMed

Nishimasu, Hiroshi; Yamano, Takashi; Gao, Linyi; Zhang, Feng; Ishitani, Ryuichiro; Nureki, Osamu

2017-07-06

The RNA-guided Cpf1 nuclease cleaves double-stranded DNA targets complementary to the CRISPR RNA (crRNA), and it has been harnessed for genome editing technologies. Recently, Acidaminococcus sp. BV3L6 (AsCpf1) was engineered to recognize altered DNA sequences as the protospacer adjacent motif (PAM), thereby expanding the target range of Cpf1-mediated genome editing. Whereas wild-type AsCpf1 recognizes the TTTV PAM, the RVR (S542R/K548V/N552R) and RR (S542R/K607R) variants can efficiently recognize the TATV and TYCV PAMs, respectively. However, their PAM recognition mechanisms remained unknown. Here we present the 2.0 Å resolution crystal structures of the RVR and RR variants bound to a crRNA and its target DNA. The structures revealed that the RVR and RR variants primarily recognize the PAM-complementary nucleotides via the substituted residues. Our high-resolution structures delineated the altered PAM recognition mechanisms of the AsCpf1 variants, providing a basis for the further engineering of CRISPR-Cpf1. Copyright © 2017 Elsevier Inc. All rights reserved.

An Experiment in Scientific Program Understanding

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.; Owen, Karl (Technical Monitor)

2000-01-01

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. Results are shown for three intensively studied codes and seven blind test cases; all test cases are state of the art scientific codes. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.

A versatile targeting system with lentiviral vectors bearing the biotin-adaptor peptide

PubMed Central

Morizono, Kouki; Xie, Yiming; Helguera, Gustavo; Daniels, Tracy R.; Lane, Timothy F.; Penichet, Manuel L.; Chen, Irvin S. Y.

2010-01-01

Background Targeted gene transduction in vivo is the ultimate preferred method for gene delivery. We previously developed targeting lentiviral vectors that specifically recognize cell surface molecules with conjugated antibodies and mediate targeted gene transduction both in vitro and in vivo. Although effective in some experimental settings, the conjugation of virus with antibodies is mediated by the interaction between protein A and the Fc region of antibodies, which is not as stable as covalent conjugation. We have now developed a more stable conjugation strategy utilizing the interaction between avidin and biotin. Methods We inserted the biotin-adaptor-peptide, which was biotinylated by secretory biotin ligase at specific sites, into our targeting envelope proteins, enabling conjugation of the pseudotyped virus with avidin, streptavidin or neutravidin. Results When conjugated with avidin-antibody fusion proteins or the complex of avidin and biotinylated targeting molecules, the vectors could mediate specific transduction to targeted cells recognized by the targeting molecules. When conjugated with streptavidin-coated magnetic beads, transduction by the vectors was targeted to the locations of magnets. Conclusions This targeting vector system can be used for broad applications of targeted gene transduction using biotinylated targeting molecules or targeting molecules fused with avidin. PMID:19455593

Sugar epitopes as potential universal disease transmission blocking targets.

PubMed

Dinglasan, Rhoel R; Valenzuela, Jesús G; Azad, Abdu F

2005-01-01

One promising method to prevent vector-borne diseases is through the use of transmission blocking vaccines (TBVs). However, developing several anti-pathogen TBVs may be impractical. In this study, we have identified a conserved candidate carbohydrate target in the midguts of several Arthropod vectors. A screen of the novel GlycoChip glycan array found that the anti-carbohydrate malaria transmission blocking monoclonal antibody (MG96) preferentially recognized D-mannose (alpha) and the type II lactosamine disaccharide. The specificity for D-mannose was confirmed by competition ELISA using alpha-methyl mannoside as inhibitor. Con A, which identifies terminal mannose residues, did not inhibit MG96 reactivity with mosquito midgut lysates, suggesting that Con A has differential recognition of this monosaccharide. However, the jack bean lectin, Jacalin, which recognizes D-mannose (alpha), d-galactose (alpha/beta) and the T antigen, not only displays a similar banding profile to that recognized by MG96 on immunoblot but was also shown to effectively inhibit MG96. Wheat-germ agglutinin, which recognizes N-acetyllactosamine units, only partially inhibited MG96 reactivity. This highlights the contribution of both glycan moieties to the MG96 epitope or glycotope. Enzyme deglycosylation results suggest that MG96 recognizes a mannose alpha1-6 substitution on an O-linked oligosaccharide. Taken together, the data suggest that MG96 recognizes a discontinuous glycotope composed of Manalpha1-6 proximal to Galbeta1-4GlcNAc-alpha-O-R glycans on arthropod vector midguts. As such, these glycotopes may represent potential transmission blocking vaccine targets for a wide range of vector-borne pathogens.

Sounds Activate Visual Cortex and Improve Visual Discrimination

PubMed Central

Störmer, Viola S.; Martinez, Antigona; McDonald, John J.; Hillyard, Steven A.

2014-01-01

A recent study in humans (McDonald et al., 2013) found that peripheral, task-irrelevant sounds activated contralateral visual cortex automatically as revealed by an auditory-evoked contralateral occipital positivity (ACOP) recorded from the scalp. The present study investigated the functional significance of this cross-modal activation of visual cortex, in particular whether the sound-evoked ACOP is predictive of improved perceptual processing of a subsequent visual target. A trial-by-trial analysis showed that the ACOP amplitude was markedly larger preceding correct than incorrect pattern discriminations of visual targets that were colocalized with the preceding sound. Dipole modeling of the scalp topography of the ACOP localized its neural generators to the ventrolateral extrastriate visual cortex. These results provide direct evidence that the cross-modal activation of contralateral visual cortex by a spatially nonpredictive but salient sound facilitates the discriminative processing of a subsequent visual target event at the location of the sound. Recordings of event-related potentials to the targets support the hypothesis that the ACOP is a neural consequence of the automatic orienting of visual attention to the location of the sound. PMID:25031419

Through-barrier electromagnetic imaging with an atomic magnetometer.

PubMed

Deans, Cameron; Marmugi, Luca; Renzoni, Ferruccio

2017-07-24

We demonstrate the penetration of thick metallic and ferromagnetic barriers for imaging of conductive targets underneath. Our system is based on an 85 Rb radio-frequency atomic magnetometer operating in electromagnetic induction imaging modality in an unshielded environment. Detrimental effects, including unpredictable magnetic signatures from ferromagnetic screens and variations in the magnetic background, are automatically compensated by active compensation coils controlled by servo loops. We exploit the tunability and low-frequency sensitivity of the atomic magnetometer to directly image multiple conductive targets concealed by a 2.5 mm ferromagnetic steel shield and/or a 2.0 mm aluminium shield, in a single scan. The performance of the atomic magnetometer allows imaging without any prior knowledge of the barriers or the targets, and without the need of background subtraction. A dedicated edge detection algorithm allows automatic estimation of the targets' size within 3.3 mm and of their position within 2.4 mm. Our results prove the feasibility of a compact, sensitive and automated sensing platform for imaging of concealed objects in a range of applications, from security screening to search and rescue.

Automatic gain control in the echolocation system of dolphins

NASA Astrophysics Data System (ADS)

Au, Whitlow W. L.; Benoit-Bird, Kelly J.

2003-06-01

In bats and technological sonars, the gain of the receiver is progressively increased with time after the transmission of a signal to compensate for acoustic propagation loss. The current understanding of dolphin echolocation indicates that automatic gain control is not a part of their sonar system. In order to test this understanding, we have performed field measurements of free-ranging echolocating dolphins. Here we show that dolphins do possess an automatic gain control mechanism, but that it is implemented in the transmission phase rather than the receiving phase of a sonar cycle. We find that the amplitude of the dolphins' echolocation signals are highly range dependent; this amplitude increases with increasing target range, R, in a 20log(R) fashion to compensate for propagation loss. If the echolocation target is a fish school with many sound scatterers, the echoes from the school will remain nearly constant with range as the dolphin closes in on it. This characteristic has the same effect as time-varying gain in bats and technological sonar when considered from a sonar system perspective.

Task-irrelevant spider associations affect categorization performance.

PubMed

Woud, Marcella L; Ellwart, Thomas; Langner, Oliver; Rinck, Mike; Becker, Eni S

2011-09-01

In two studies, the Single Target Implicit Association Test (STIAT) was used to investigate automatic associations toward spiders. In both experiments, we measured the strength of associations between pictures of spiders and either threat-related words or pleasant words. Unlike previous studies, we administered a STIAT version in which stimulus contents was task-irrelevant: The target spider pictures were categorized according to the label picture, irrespective of what they showed. In Study 1, spider-fearful individuals versus non-fearful controls were tested, Study 2 compared spider enthusiasts to non-fearful controls. Results revealed that the novel STIAT version was sensitive to group differences in automatic associations toward spiders. In Study 1, it successfully distinguished between spider-fearful individuals and non-fearful controls. Moreover, STIAT scores predicted automatic fear responses best, whereas controlled avoidance behavior was best predicted by the FAS (German translation of the Fear of Spiders Questionnaire). The results of Study 2 demonstrated that the novel STIAT version was also able to differentiate between spider enthusiasts and non-fearful controls. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Activating Human NK Cell Receptor KIR2DS2 Recognizes a β2-Microglobulin-Independent Ligand on Cancer Cells.

PubMed

Thiruchelvam-Kyle, Lavanya; Hoelsbrekken, Sigurd E; Saether, Per C; Bjørnsen, Elisabeth Gyllensten; Pende, Daniela; Fossum, Sigbjørn; Daws, Michael R; Dissen, Erik

2017-04-01

The functions of activating members of the killer cell Ig-like receptor (KIR) family are not fully understood, as the ligands for these receptors are largely unidentified. In this study, we report that KIR2DS2 reporter cells recognize a ligand expressed by cancer cell lines. All cancer targets recognized by KIR2DS2 were also recognized by KIR2DL2 and KIR2DL3 reporters. Trogocytosis of membrane proteins from the cancer targets was observed with responding reporter cells, indicating the formation of KIR2DS2 ligand-specific immunological synapses. HLA-C typing of target cells showed that KIR2DS2 recognition was independent of the HLA C1 or C2 group, whereas targets cells that were only recognized by KIR2DL3 expressed C1 group alleles. Anti-HLA class I Abs blocked KIR2DL3 responses toward C1-expressing targets, but they did not block KIR2DS2 recognition of cancer cells. Small interfering RNA knockdown of β 2 -microglobulin reduced the expression of class I H chain on the cancer targets by >97%, but it did not reduce the KIR2DS2 reporter responses, indicating a β 2 -microglobulin-independent ligand for KIR2DS2. Importantly, KIR2DL3 responses toward some KIR2DS2 ligand-expressing cells were also undiminished after β 2 -microglobulin knockdown, and they were not blocked by anti-HLA class I Abs, suggesting that KIR2DL3, in addition to the traditional HLA-C ligands, can bind to the same β 2 -microglobulin-independent ligand as KIR2DS2. These observations indicate the existence of a novel, presently uncharacterized ligand for the activating NK cell receptor KIR2DS2. Molecular identification of this ligand may lead to improved KIR-HLA mismatching in hematopoietic stem cell transplantation therapy for leukemia and new, more specific NK cell-based cancer therapies. Copyright © 2017 by The American Association of Immunologists, Inc.

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

PubMed

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

Age-related differences in the automatic processing of single letters: implications for selective attention.

PubMed

Daffner, Kirk R; Alperin, Brittany R; Mott, Katherine K; Holcomb, Phillip J

2014-01-22

Older adults exhibit diminished ability to inhibit the processing of visual stimuli that are supposed to be ignored. The extent to which age-related changes in early visual processing contribute to impairments in selective attention remains to be determined. Here, 103 adults, 18-85 years of age, completed a color selective attention task in which they were asked to attend to a specified color and respond to designated target letters. An optimal approach would be to initially filter according to color and then process letter forms in the attend color to identify targets. An asymmetric N170 ERP component (larger amplitude over left posterior hemisphere sites) was used as a marker of the early automatic processing of letter forms. Young and middle-aged adults did not generate an asymmetric N170 component. In contrast, young-old and old-old adults produced a larger N170 over the left hemisphere. Furthermore, older adults generated a larger N170 to letter than nonletter stimuli over the left, but not right hemisphere. More asymmetric N170 responses predicted greater allocation of late selection resources to target letters in the ignore color, as indexed by P3b amplitude. These results suggest that unlike their younger counterparts, older adults automatically process stimuli as letters early in the selection process, when it would be more efficient to attend to color only. The inability to ignore letters early in the processing stream helps explain the age-related increase in subsequent processing of target letter forms presented in the ignore color.

Automatic patient dose registry and clinical audit on line for mammography.

PubMed

Ten, J I; Vano, E; Sánchez, R; Fernandez-Soto, J M

2015-07-01

The use of automatic registry systems for patient dose in digital mammography allows clinical audit and patient dose analysis of the whole sample of individual mammography exposures while fulfilling the requirements of the European Directives and other international recommendations. Further parameters associated with radiation exposure (tube voltage, X-ray tube output and HVL values for different kVp and target/filter combinations, breast compression, etc.) should be periodically verified and used to evaluate patient doses. This study presents an experience in routine clinical practice for mammography using automatic systems. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Shaping Attention with Reward: Effects of Reward on Space- and Object-Based Selection

PubMed Central

Shomstein, Sarah; Johnson, Jacoba

2014-01-01

The contribution of rewarded actions to automatic attentional selection remains obscure. We hypothesized that some forms of automatic orienting, such as object-based selection, can be completely abandoned in lieu of reward maximizing strategy. While presenting identical visual stimuli to the observer, in a set of two experiments, we manipulate what is being rewarded (different object targets or random object locations) and the type of reward received (money or points). It was observed that reward alone guides attentional selection, entirely predicting behavior. These results suggest that guidance of selective attention, while automatic, is flexible and can be adjusted in accordance with external non-sensory reward-based factors. PMID:24121412

Automatic rendezvous and docking systems functional and performance requirements

NASA Technical Reports Server (NTRS)

1985-01-01

A generalized mission design scheme which utilizes a standard mission profile for all OMV rendezvous operations, recognizes typical operational constraints, and minimizes propellant penalties due to nodal regression effects was developed. This scheme has been used to demonstrate a unified guidance and navigation maneuver processor (the UMP), which supports all mission phases through station-keeping. The initial demonstration version of the Orbital Rendezvous Mission Planner (ORMP) was provided for evaluation purposes, and program operation was discussed.

Automatic Recognition of Breathing Route During Sleep Using Snoring Sounds

NASA Astrophysics Data System (ADS)

Mikami, Tsuyoshi; Kojima, Yohichiro

This letter classifies snoring sounds into three breathing routes (oral, nasal, and oronasal) with discriminant analysis of the power spectra and k-nearest neighbor method. It is necessary to recognize breathing route during snoring, because oral snoring is a typical symptom of sleep apnea but we cannot know our own breathing and snoring condition during sleep. As a result, about 98.8% classification rate is obtained by using leave-one-out test for performance evaluation.

Intelligent technologies in process of highly-precise products manufacturing

NASA Astrophysics Data System (ADS)

Vakhidova, K. L.; Khakimov, Z. L.; Isaeva, M. R.; Shukhin, V. V.; Labazanov, M. A.; Ignatiev, S. A.

2017-10-01

One of the main control methods of the surface layer of bearing parts is the eddy current testing method. Surface layer defects of bearing parts, like burns, cracks and some others, are reflected in the results of the rolling surfaces scan. The previously developed method for detecting defects from the image of the raceway was quite effective, but the processing algorithm is complicated and lasts for about 12 ... 16 s. The real non-stationary signals from an eddy current transducer (ECT) consist of short-time high-frequency and long-time low-frequency components, therefore a transformation is used for their analysis, which provides different windows for different frequencies. The wavelet transform meets these conditions. Based on aforesaid, a methodology for automatically detecting and recognizing local defects in bearing parts surface layer has been developed on the basis of wavelet analysis using integral estimates. Some of the defects are recognized by the amplitude component, otherwise an automatic transition to recognition by the phase component of information signals (IS) is carried out. The use of intelligent technologies in the manufacture of bearing parts will, firstly, significantly improve the quality of bearings, and secondly, significantly improve production efficiency by reducing (eliminating) rejections in the manufacture of products, increasing the period of normal operation of the technological equipment (inter-adjustment period), the implementation of the system of Flexible facilities maintenance, as well as reducing production costs.

[Resuscitation - Basic Life Support in adults and application of automatic external defibrillators].

PubMed

Bohn, Andreas; Seewald, Stephan; Wnent, Jan

2016-03-01

Witnesses of a sudden cardiac arrest play a key-role in resuscitation. Lay-persons should therefore be trained to recognize that a collapsed person who is not breathing at all or breathing normally might suffer from cardiac arrest. Information of professional emergency medical staff by lay-persons and their initiation of cardio-pulmonary-resuscitation-measures are of great importance for cardiac-arrest victims. Ambulance-dispatchers have to support lay-rescuers via telephone. This support includes the localisation of the nearest Automatic External Defibrillator (AED). Presentation of agonal breathing or convulsions due to brain-hypoxia need to be recognized as potential early signs of cardiac arrest. In any case of cardiac arrest chest-compressions need to be started. There is insufficiant data to recommend "chest-compression-only"-CPR as being equally sufficient as cardio-pulmonary-resuscitation including ventilation. Rescuers trained in ventilation should therefore combine compressions and ventilations at a 30:2-ratio. Movement of the chest is being used as a sign of sufficient ventilation. High-quality chest-compressions of at least 5 cm of depth, not exceeding 6 cm, are recommended at a ratio of 100-120 chest conpressions/min. Interruption of chest-compression should be avoided. At busy public places AED should be available to enable lay-rescuers to apply early defibrillation. © Georg Thieme Verlag Stuttgart · New York.

Automatic detection of sweep-meshable volumes

DOEpatents

Tautges,; Timothy J. , White; David, R [Pittsburgh, PA

2006-05-23

A method of and software for automatically determining whether a mesh can be generated by sweeping for a representation of a geometric solid comprising: classifying surface mesh schemes for surfaces of the representation locally using surface vertex types; grouping mappable and submappable surfaces of the representation into chains; computing volume edge types for the representation; recursively traversing surfaces of the representation and grouping the surfaces into source, target, and linking surface lists; and checking traversal direction when traversing onto linking surfaces.

Unit Reference Sheet (URS) Cost Methodology.

DTIC Science & Technology

1980-08-01

LAUNCHER MONORAIL GUIDED MISSILE: W/E (NIKE-HERCULES) L45740 LAUNCHER TUBULAR GUIDED MISSILE: (TOW) L45757 LAUNCHER ZERO LENGTH GUIDED MISSILE: (IMP-HAWK...L76762 LOADER TRANSPORTER GUIDED MISSILE: W/E (HAWK) M57503 MOBILE TARGET TRACKING SYSTEM: USED TO SUPPORT MQM 34 ( FIRE BEE) M57549 MOBILITY KIT GUIDED...HIGH RATE THREE BARREL W/E J96479 GUN AUTOMATIC 20 MILLIMETER: GAS OPERATED MANUAL OR ELECT FIRED J96481 GUN AUTOMATIC 20 MILLIMETER: ELECTRIC J96694 GUN

Learning and Recognition of Clothing Genres From Full-Body Images.

PubMed

Hidayati, Shintami C; You, Chuang-Wen; Cheng, Wen-Huang; Hua, Kai-Lung

2018-05-01

According to the theory of clothing design, the genres of clothes can be recognized based on a set of visually differentiable style elements, which exhibit salient features of visual appearance and reflect high-level fashion styles for better describing clothing genres. Instead of using less-discriminative low-level features or ambiguous keywords to identify clothing genres, we proposed a novel approach for automatically classifying clothing genres based on the visually differentiable style elements. A set of style elements, that are crucial for recognizing specific visual styles of clothing genres, were identified based on the clothing design theory. In addition, the corresponding salient visual features of each style element were identified and formulated with variables that can be computationally derived with various computer vision algorithms. To evaluate the performance of our algorithm, a dataset containing 3250 full-body shots crawled from popular online stores was built. Recognition results show that our proposed algorithms achieved promising overall precision, recall, and -score of 88.76%, 88.53%, and 88.64% for recognizing upperwear genres, and 88.21%, 88.17%, and 88.19% for recognizing lowerwear genres, respectively. The effectiveness of each style element and its visual features on recognizing clothing genres was demonstrated through a set of experiments involving different sets of style elements or features. In summary, our experimental results demonstrate the effectiveness of the proposed method in clothing genre recognition.

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

Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments.

PubMed

Gao, Liqiang; Sun, Chao; Zhang, Chen; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2013-01-01

Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.

Automatic transfer function design for medical visualization using visibility distributions and projective color mapping.

PubMed

Cai, Lile; Tay, Wei-Liang; Nguyen, Binh P; Chui, Chee-Kong; Ong, Sim-Heng

2013-01-01

Transfer functions play a key role in volume rendering of medical data, but transfer function manipulation is unintuitive and can be time-consuming; achieving an optimal visualization of patient anatomy or pathology is difficult. To overcome this problem, we present a system for automatic transfer function design based on visibility distribution and projective color mapping. Instead of assigning opacity directly based on voxel intensity and gradient magnitude, the opacity transfer function is automatically derived by matching the observed visibility distribution to a target visibility distribution. An automatic color assignment scheme based on projective mapping is proposed to assign colors that allow for the visual discrimination of different structures, while also reflecting the degree of similarity between them. When our method was tested on several medical volumetric datasets, the key structures within the volume were clearly visualized with minimal user intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of a cerebral circulation model for the automatic control of brain physiology.

PubMed

Utsuki, T

2015-01-01

In various clinical guidelines of brain injury, intracranial pressure (ICP), cerebral blood flow (CBF) and brain temperature (BT) are essential targets for precise management for brain resuscitation. In addition, the integrated automatic control of BT, ICP, and CBF is required for improving therapeutic effects and reducing medical costs and staff burden. Thus, a new model of cerebral circulation was developed in this study for integrative automatic control. With this model, the CBF and cerebral perfusion pressure of a normal adult male were regionally calculated according to cerebrovascular structure, blood viscosity, blood distribution, CBF autoregulation, and ICP. The analysis results were consistent with physiological knowledge already obtained with conventional studies. Therefore, the developed model is potentially available for the integrative control of the physiological state of the brain as a reference model of an automatic control system, or as a controlled object in various control simulations.

Using suggestion to model different types of automatic writing.

PubMed

Walsh, E; Mehta, M A; Oakley, D A; Guilmette, D N; Gabay, A; Halligan, P W; Deeley, Q

2014-05-01

Our sense of self includes awareness of our thoughts and movements, and our control over them. This feeling can be altered or lost in neuropsychiatric disorders as well as in phenomena such as "automatic writing" whereby writing is attributed to an external source. Here, we employed suggestion in highly hypnotically suggestible participants to model various experiences of automatic writing during a sentence completion task. Results showed that the induction of hypnosis, without additional suggestion, was associated with a small but significant reduction of control, ownership, and awareness for writing. Targeted suggestions produced a double dissociation between thought and movement components of writing, for both feelings of control and ownership, and additionally, reduced awareness of writing. Overall, suggestion produced selective alterations in the control, ownership, and awareness of thought and motor components of writing, thus enabling key aspects of automatic writing, observed across different clinical and cultural settings, to be modelled. Copyright © 2014. Published by Elsevier Inc.

Design and realization of an AEC&AGC system for the CCD aerial camera

NASA Astrophysics Data System (ADS)

Liu, Hai ying; Feng, Bing; Wang, Peng; Li, Yan; Wei, Hao yun

2015-08-01

An AEC and AGC(Automatic Exposure Control and Automatic Gain Control) system was designed for a CCD aerial camera with fixed aperture and electronic shutter. The normal AEC and AGE algorithm is not suitable to the aerial camera since the camera always takes high-resolution photographs in high-speed moving. The AEC and AGE system adjusts electronic shutter and camera gain automatically according to the target brightness and the moving speed of the aircraft. An automatic Gamma correction is used before the image is output so that the image is better for watching and analyzing by human eyes. The AEC and AGC system could avoid underexposure, overexposure, or image blurring caused by fast moving or environment vibration. A series of tests proved that the system meet the requirements of the camera system with its fast adjusting speed, high adaptability, high reliability in severe complex environment.

Evaluation and control of miRNA-like off-target repression for RNA interference.

PubMed

Seok, Heeyoung; Lee, Haejeong; Jang, Eun-Sook; Chi, Sung Wook

2018-03-01

RNA interference (RNAi) has been widely adopted to repress specific gene expression and is easily achieved by designing small interfering RNAs (siRNAs) with perfect sequence complementarity to the intended target mRNAs. Although siRNAs direct Argonaute (Ago), a core component of the RNA-induced silencing complex (RISC), to recognize and silence target mRNAs, they also inevitably function as microRNAs (miRNAs) and suppress hundreds of off-targets. Such miRNA-like off-target repression is potentially detrimental, resulting in unwanted toxicity and phenotypes. Despite early recognition of the severity of miRNA-like off-target repression, this effect has often been overlooked because of difficulties in recognizing and avoiding off-targets. However, recent advances in genome-wide methods and knowledge of Ago-miRNA target interactions have set the stage for properly evaluating and controlling miRNA-like off-target repression. Here, we describe the intrinsic problems of miRNA-like off-target effects caused by canonical and noncanonical interactions. We particularly focus on various genome-wide approaches and chemical modifications for the evaluation and prevention of off-target repression to facilitate the use of RNAi with secured specificity.

Acoustic basis for recognition of aspect-dependent three-dimensional targets by an echolocating bottlenose dolphin.

PubMed

Helweg, D A; Au, W W; Roitblat, H L; Nachtigall, P E

1996-04-01

The relationships between acoustic features of target echoes and the cognitive representations of the target formed by an echolocating dolphin will influence the ease with which the dolphin can recognize a target. A blindfolded Atlantic bottlenose dolphin (Tursiops truncatus) learned to match aspect-dependent three-dimensional targets (such as a cube) at haphazard orientations, although with some difficulty. This task may have been difficult because aspect-dependent targets produce different echoes at different orientations, which required the dolphin to have some capability for object constancy across changes in echo characteristics. Significant target-related differences in echo amplitude, rms bandwidth, and distributions of interhighlight intervals were observed among echoes collected when the dolphin was performing the task. Targets could be classified using a combination of energy flux density and rms bandwidth by a linear discriminant analysis and a nearest centroid classifier. Neither statistical model could classify targets without amplitude information, but the highest accuracy required spectral information as well. This suggests that the dolphin recognized the targets using a multidimensional representation containing amplitude and spectral information and that dolphins can form stable representations of targets regardless of orientation based on varying sensory properties.

Low implicit self-esteem and dysfunctional automatic associations in social anxiety disorder.

PubMed

Glashouwer, Klaske A; Vroling, Maartje S; de Jong, Peter J; Lange, Wolf-Gero; de Keijser, Jos

2013-06-01

Negative automatic associations towards the self and social cues are assumed to play an important role in social anxiety disorder. We tested whether social anxiety disorder patients (n = 45) showed stronger dysfunctional automatic associations than non-clinical controls (n = 45) and panic disorder patients (n = 24) and whether there existed gender differences in this respect. We used a single-target Implicit Association Test and an Implicit Association Test to measure dysfunctional automatic associations with social cues and implicit self-esteem, respectively. Results showed that automatic associations with social cues were more dysfunctional in socially anxious patients than in both control groups, suggesting this might be a specific characteristic of social anxiety disorder. Socially anxious patients showed relatively low implicit self-esteem compared to non-clinical controls, whereas panic disorder patients scored in between both groups. Unexpectedly, we found that lower implicit self-esteem was related to higher severity of social anxiety symptoms in men, whereas no such relationship was found in women. These findings support the view that automatic negative associations with social cues and lowered implicit self-esteem may both help to enhance our understanding of the cognitive processes that underlie social anxiety disorder. Copyright © 2012 Elsevier Ltd. All rights reserved.

Targeting of deep-brain structures in nonhuman primates using MR and CT Images

NASA Astrophysics Data System (ADS)

Chen, Antong; Hines, Catherine; Dogdas, Belma; Bone, Ashleigh; Lodge, Kenneth; O'Malley, Stacey; Connolly, Brett; Winkelmann, Christopher T.; Bagchi, Ansuman; Lubbers, Laura S.; Uslaner, Jason M.; Johnson, Colena; Renger, John; Zariwala, Hatim A.

2015-03-01

In vivo gene delivery in central nervous systems of nonhuman primates (NHP) is an important approach for gene therapy and animal model development of human disease. To achieve a more accurate delivery of genetic probes, precise stereotactic targeting of brain structures is required. However, even with assistance from multi-modality 3D imaging techniques (e.g. MR and CT), the precision of targeting is often challenging due to difficulties in identification of deep brain structures, e.g. the striatum which consists of multiple substructures, and the nucleus basalis of meynert (NBM), which often lack clear boundaries to supporting anatomical landmarks. Here we demonstrate a 3D-image-based intracranial stereotactic approach applied toward reproducible intracranial targeting of bilateral NBM and striatum of rhesus. For the targeting we discuss the feasibility of an atlas-based automatic approach. Delineated originally on a high resolution 3D histology-MR atlas set, the NBM and the striatum could be located on the MR image of a rhesus subject through affine and nonrigid registrations. The atlas-based targeting of NBM was compared with the targeting conducted manually by an experienced neuroscientist. Based on the targeting, the trajectories and entry points for delivering the genetic probes to the targets could be established on the CT images of the subject after rigid registration. The accuracy of the targeting was assessed quantitatively by comparison between NBM locations obtained automatically and manually, and finally demonstrated qualitatively via post mortem analysis of slices that had been labelled via Evan Blue infusion and immunohistochemistry.

Position, rotation, and intensity invariant recognizing method

DOEpatents

Ochoa, Ellen; Schils, George F.; Sweeney, Donald W.

1989-01-01

A method for recognizing the presence of a particular target in a field of view which is target position, rotation, and intensity invariant includes the preparing of a target-specific invariant filter from a combination of all eigen-modes of a pattern of the particular target. Coherent radiation from the field of view is then imaged into an optical correlator in which the invariant filter is located. The invariant filter is rotated in the frequency plane of the optical correlator in order to produce a constant-amplitude rotational response in a correlation output plane when the particular target is present in the field of view. Any constant response is thus detected in the output The U.S. Government has rights in this invention pursuant to Contract No. DE-AC04-76DP00789 between the U.S. Department of Energy and AT&T Technologies, Inc.

Control Method for Video Guidance Sensor System

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

2005-01-01

A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are commands is permitted only when the system is in the carried out. Further, acceptance of reset and diagnostic standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

Control method for video guidance sensor system

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

2005-01-01

A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are carried out. Further, acceptance of reset and diagnostic commands is permitted only when the system is in the standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

ATR Performance Estimation Seed Program

DTIC Science & Technology

2015-09-28

to produce simulated MCM sonar data and demonstrate the impact of system, environmental, and target scattering effects on ATR detection...settings and achieving better understanding the relative impact of the factors influencing ATR performance. sonar, mine countermeasures, MCM , automatic...simulated MCM sonar data and demonstrate the impact of system, environmental, and target scattering effects on ATR detection/classification performance. The

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

Pasquier, David; Lacornerie, Thomas; Vermandel, Maximilien

Purpose: Target-volume and organ-at-risk delineation is a time-consuming task in radiotherapy planning. The development of automated segmentation tools remains problematic, because of pelvic organ shape variability. We evaluate a three-dimensional (3D), deformable-model approach and a seeded region-growing algorithm for automatic delineation of the prostate and organs-at-risk on magnetic resonance images. Methods and Materials: Manual and automatic delineation were compared in 24 patients using a sagittal T2-weighted (T2-w) turbo spin echo (TSE) sequence and an axial T1-weighted (T1-w) 3D fast-field echo (FFE) or TSE sequence. For automatic prostate delineation, an organ model-based method was used. Prostates without seminal vesicles were delineatedmore » as the clinical target volume (CTV). For automatic bladder and rectum delineation, a seeded region-growing method was used. Manual contouring was considered the reference method. The following parameters were measured: volume ratio (Vr) (automatic/manual), volume overlap (Vo) (ratio of the volume of intersection to the volume of union; optimal value = 1), and correctly delineated volume (Vc) (percent ratio of the volume of intersection to the manually defined volume; optimal value 100). Results: For the CTV, the Vr, Vo, and Vc were 1.13 ({+-}0.1 SD), 0.78 ({+-}0.05 SD), and 94.75 ({+-}3.3 SD), respectively. For the rectum, the Vr, Vo, and Vc were 0.97 ({+-}0.1 SD), 0.78 ({+-}0.06 SD), and 86.52 ({+-}5 SD), respectively. For the bladder, the Vr, Vo, and Vc were 0.95 ({+-}0.03 SD), 0.88 ({+-}0.03 SD), and 91.29 ({+-}3.1 SD), respectively. Conclusions: Our results show that the organ-model method is robust, and results in reproducible prostate segmentation with minor interactive corrections. For automatic bladder and rectum delineation, magnetic resonance imaging soft-tissue contrast enables the use of region-growing methods.« less

43 CFR 418.12 - Project efficiency.

Code of Federal Regulations, 2012 CFR

2012-10-01

... delivery level including droughts or allocations, automatically adjusts to changes during the year and... (except in a real drought), it allows for future planning and averaging over time. (3) Efficiency targets...

43 CFR 418.12 - Project efficiency.

Code of Federal Regulations, 2014 CFR

2014-10-01

... delivery level including droughts or allocations, automatically adjusts to changes during the year and... (except in a real drought), it allows for future planning and averaging over time. (3) Efficiency targets...

43 CFR 418.12 - Project efficiency.

Code of Federal Regulations, 2013 CFR

2013-10-01

... delivery level including droughts or allocations, automatically adjusts to changes during the year and... (except in a real drought), it allows for future planning and averaging over time. (3) Efficiency targets...

Predicting human activities in sequences of actions in RGB-D videos

NASA Astrophysics Data System (ADS)

Jardim, David; Nunes, Luís.; Dias, Miguel

2017-03-01

In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

[On efficiency of biomanagement with negative feedback from patient's EEG in correction of functional disorders, caused by stress].

PubMed

Fedotchev, A I

2010-01-01

The perspective approach to non-pharmacological correction of the stress induced functional disorders in humans, based on the double negative feedback from patient's EEG was validated and experimentally tested. The approach implies a simultaneous use of narrow frequency EEG-oscillators, characteristic for each patient and recorded in real time span, in two independent contours of negative feedback--traditional contour of adaptive biomanagement and additional contour of resonance stimulation. In the last the signals of negative feedback from individual narrow frequency EEG oscillators are not recognized by the subject, but serve for an automatic modulation of the parameters of the sensory impact. Was shown that due to combination of active (conscious perception) and passive (automatic modulation) use of signals of negative feedback from narrow frequency EEG components of the patient, opens a possibility of considerable increase of efficiency of the procedures of EEG biomanagement.

Concatenated logic circuits based on a three-way DNA junction: a keypad-lock security system with visible readout and an automatic reset function.

PubMed

Chen, Junhua; Zhou, Shungui; Wen, Junlin

2015-01-07

Concatenated logic circuits operating as a biocomputing keypad-lock security system with an automatic reset function have been successfully constructed on the basis of toehold-mediated strand displacement and three-way-DNA-junction architecture. In comparison with previously reported keypad locks, the distinctive advantage of the proposed security system is that it can be reset and cycled spontaneously a large number of times without an external stimulus, thus making practical applications possible. By the use of a split-G-quadruplex DNAzyme as the signal reporter, the output of the keypad lock can be recognized readily by the naked eye. The "lock" is opened only when the inputs are introduced in an exact order. This requirement provides defense against illegal invasion to protect information at the molecular scale. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Flow measurements in sewers based on image analysis: automatic flow velocity algorithm.

PubMed

Jeanbourquin, D; Sage, D; Nguyen, L; Schaeli, B; Kayal, S; Barry, D A; Rossi, L

2011-01-01

Discharges of combined sewer overflows (CSOs) and stormwater are recognized as an important source of environmental contamination. However, the harsh sewer environment and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. An in situ system for sewer water flow monitoring based on video images was evaluated. Algorithms to determine water velocities were developed based on image-processing techniques. The image-based water velocity algorithm identifies surface features and measures their positions with respect to real world coordinates. A web-based user interface and a three-tier system architecture enable remote configuration of the cameras and the image-processing algorithms in order to calculate automatically flow velocity on-line. Results of investigations conducted in a CSO are presented. The system was found to measure reliably water velocities, thereby providing the means to understand particular hydraulic behaviors.

Remote Safety Monitoring for Elderly Persons Based on Omni-Vision Analysis

PubMed Central

Xiang, Yun; Tang, Yi-ping; Ma, Bao-qing; Yan, Hang-chen; Jiang, Jun; Tian, Xu-yuan

2015-01-01

Remote monitoring service for elderly persons is important as the aged populations in most developed countries continue growing. To monitor the safety and health of the elderly population, we propose a novel omni-directional vision sensor based system, which can detect and track object motion, recognize human posture, and analyze human behavior automatically. In this work, we have made the following contributions: (1) we develop a remote safety monitoring system which can provide real-time and automatic health care for the elderly persons and (2) we design a novel motion history or energy images based algorithm for motion object tracking. Our system can accurately and efficiently collect, analyze, and transfer elderly activity information and provide health care in real-time. Experimental results show that our technique can improve the data analysis efficiency by 58.5% for object tracking. Moreover, for the human posture recognition application, the success rate can reach 98.6% on average. PMID:25978761

DTM-based automatic mapping and fractal clustering of putative mud volcanoes in Arabia Terra craters

NASA Astrophysics Data System (ADS)

Pozzobon, R. P.; Mazzarini, F. M.; Massironi, M. M.; Cremonese, G. C.; Rossi, A. P. R.; Pondrelli, M. P.; Marinangeli, L. M.

2017-09-01

Arabia Terra is a region of Mars where occurrence of past-water manifests at surface and subsurface. To date, several landforms associated with this activity were recognized and mapped, directly influencing the models of fluid circulation. In particular, within several craters such as Firsoff and an unnamed southern crater, putative mud volcanoes were described by several authors. In fact, numerous mounds (from 30 m of diameter in the case of monogenic cones, up to 3-400 m in the case of coalescing mounds) present an apical vent-like depression, resembling subaerial Azerbaijan mud volcanoes and gryphons. To this date, landform analysis through topographic position index and curvatures based on topography was never attempted. We hereby present a landform classification method suitable for mounds automatic mapping. Their resulting spatial distribution is then studied in terms of self-similar clustering.

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

Automatically measuring brain ventricular volume within PACS using artificial intelligence.

PubMed

Yepes-Calderon, Fernando; Nelson, Marvin D; McComb, J Gordon

2018-01-01

The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and access it at a voxel level, decrypted and uncompressed that allows analytical capabilities while not perturbing the system's daily operation. Additionally, the strategy is secure and vendor independent. Cerebral ventricular volume is important for the diagnosis and treatment of many neurological disorders. A significant change in ventricular volume is readily recognized, but subtle changes, especially over longer periods of time, may be difficult to discern. Clinical imaging protocols and parameters are often varied making it difficult to use a general solution with standard segmentation techniques. Presented is a segmentation strategy based on an algorithm that uses four features extracted from the medical images to create a statistical estimator capable of determining ventricular volume. When compared with manual segmentations, the correlation was 94% and holds promise for even better accuracy by incorporating the unlimited data available. The volume of any segmentable structure can be accurately determined utilizing the machine learning strategy presented and runs fully automatically within the PACS.

Simple automatic strategy for background drift correction in chromatographic data analysis.

PubMed

Fu, Hai-Yan; Li, He-Dong; Yu, Yong-Jie; Wang, Bing; Lu, Peng; Cui, Hua-Peng; Liu, Ping-Ping; She, Yuan-Bin

2016-06-03

Chromatographic background drift correction, which influences peak detection and time shift alignment results, is a critical stage in chromatographic data analysis. In this study, an automatic background drift correction methodology was developed. Local minimum values in a chromatogram were initially detected and organized as a new baseline vector. Iterative optimization was then employed to recognize outliers, which belong to the chromatographic peaks, in this vector, and update the outliers in the baseline until convergence. The optimized baseline vector was finally expanded into the original chromatogram, and linear interpolation was employed to estimate background drift in the chromatogram. The principle underlying the proposed method was confirmed using a complex gas chromatographic dataset. Finally, the proposed approach was applied to eliminate background drift in liquid chromatography quadrupole time-of-flight samples used in the metabolic study of Escherichia coli samples. The proposed method was comparable with three classical techniques: morphological weighted penalized least squares, moving window minimum value strategy and background drift correction by orthogonal subspace projection. The proposed method allows almost automatic implementation of background drift correction, which is convenient for practical use. Copyright © 2016 Elsevier B.V. All rights reserved.

Towards automatic planning for manufacturing generative processes

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

CALTON,TERRI L.

2000-05-24

Generative process planning describes methods process engineers use to modify manufacturing/process plans after designs are complete. A completed design may be the result from the introduction of a new product based on an old design, an assembly upgrade, or modified product designs used for a family of similar products. An engineer designs an assembly and then creates plans capturing manufacturing processes, including assembly sequences, component joining methods, part costs, labor costs, etc. When new products originate as a result of an upgrade, component geometry may change, and/or additional components and subassemblies may be added to or are omitted from themore » original design. As a result process engineers are forced to create new plans. This is further complicated by the fact that the process engineer is forced to manually generate these plans for each product upgrade. To generate new assembly plans for product upgrades, engineers must manually re-specify the manufacturing plan selection criteria and re-run the planners. To remedy this problem, special-purpose assembly planning algorithms have been developed to automatically recognize design modifications and automatically apply previously defined manufacturing plan selection criteria and constraints.« less

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.

PubMed

Tian, Shu; Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

PubMed Central

Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness. PMID:26693249

Alexithymia is associated with attenuated automatic brain response to facial emotion in clinical depression.

PubMed

Suslow, Thomas; Kugel, Harald; Rufer, Michael; Redlich, Ronny; Dohm, Katharina; Grotegerd, Dominik; Zaremba, Dario; Dannlowski, Udo

2016-02-04

Alexithymia is a clinically relevant personality trait related to difficulties in recognizing and describing emotions. Previous studies examining the neural correlates of alexithymia have shown mainly decreased response of several brain areas during emotion processing in healthy samples and patients suffering from autism or post-traumatic stress disorder. In the present study, we examined the effect of alexithymia on automatic brain reactivity to negative and positive facial expressions in clinical depression. Brain activation in response to sad, happy, neutral, and no facial expression (presented for 33 ms and masked by neutral faces) was measured by functional magnetic resonance imaging at 3 T in 26 alexithymic and 26 non-alexithymic patients with major depression. Alexithymic patients manifested less activation in response to masked sad and happy (compared to neutral) faces in right frontal regions and right caudate nuclei than non-alexithymic patients. Our neuroimaging study provides evidence that the personality trait alexithymia has a modulating effect on automatic emotion processing in clinical depression. Our findings support the idea that alexithymia could be associated with functional deficits of the right hemisphere. Future research on the neural substrates of emotion processing in depression should assess and control alexithymia in their analyses.

Theoretical Analysis of the Longitudinal Behavior of an Automatically Controlled Supersonic Interceptor During the Attack Phase

NASA Technical Reports Server (NTRS)

Gates, Ordway B., Jr.; Woodling, C. H.

1959-01-01

Theoretical analysis of the longitudinal behavior of an automatically controlled supersonic interceptor during the attack phase against a nonmaneuvering target is presented. Control of the interceptor's flight path is obtained by use of a pitch rate command system. Topics lift, and pitching moment, effects of initial tracking errors, discussion of normal acceleration limited, limitations of control surface rate and deflection, and effects of neglecting forward velocity changes of interceptor during attack phase.

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.

[Development of an automatic vacuum liquid chromatographic device and its application in the separation of the components from Schisandra chinensis (Turz) Baill].

PubMed

Zhu, Jingbo; Liu, Baoyue; Shan, Shibo; Ding, Yanl; Kou, Zinong; Xiao, Wei

2015-08-01

In order to meet the needs of efficient purification of products from natural resources, this paper developed an automatic vacuum liquid chromatographic device (AUTO-VLC) and applied it to the component separation of petroleum ether extracts of Schisandra chinensis (Turcz) Baill. The device was comprised of a solvent system, a 10-position distribution valve, a 3-position changes valve, dynamic axis compress chromatographic columns with three diameters, and a 10-position fraction valve. The programmable logic controller (PLC) S7- 200 was adopted to realize the automatic control and monitoring of the mobile phase changing, column selection, separation time setting and fraction collection. The separation results showed that six fractions (S1-S6) of different chemical components from 100 g Schisandra chinensis (Turcz) Baill. petroleum ether phase were obtained by the AUTO-VLC with 150 mm diameter dynamic axis compress chromatographic column. A new method used for the VLC separation parameters screened by using multiple development TLC was developed and confirmed. The initial mobile phase of AUTO-VLC was selected by taking Rf of all the target compounds ranging from 0 to 0.45 for fist development on the TLC; gradient elution ratio was selected according to k value (the slope of the linear function of Rf value and development times on the TLC) and the resolution of target compounds; elution times (n) were calculated by the formula n ≈ ΔRf/k. A total of four compounds with the purity more than 85% and 13 other components were separated from S5 under the selected conditions for only 17 h. Therefore, the development of the automatic VLC and its method are significant to the automatic and systematic separation of traditional Chinese medicines.

Assessing the feasibility, acceptability, and potential effectiveness of a behavioral-automaticity focused lifestyle intervention for African Americans with metabolic syndrome: The Pick two to Stick to protocol.

PubMed

Fritz, Heather; Brody, Aaron; Levy, Philip

2017-09-01

Metabolic syndrome (MetS) significantly increases the risk of developing diabetes and cardiovascular disease. Being physically active and eating a healthy diet can reduce MetS risk factors. Too frequently, however, studies report that the effects of interventions targeting those factors are not maintained once interventions are withdrawn. A potential solution to the problem is targeting behavioral automaticity (habit-development) to aid in initiation and maintenance of health-behavior changes. The Pick two to Stick To (P2S2), is an 8-week, theory-based hybrid (face-to-face/telecoaching) habit focused lifestyle intervention designed to increase healthful physical activity and dietary behavioral automaticity. The purpose of this article is to describe the rationale and protocol for evaluating the P2S2 program's feasibility, acceptability and potential effectiveness. Using a prospective, non-comparative design, the P2S2 program will be implemented by trained occupational therapy 'coaches' to 40 African Americans aged 40 and above with MetS recruited from the emergency department. Semi-structured interviews with participants, bi-weekly research meetings with study staff, and observations of intervention delivery will provide data for a process evaluation. Estimates of effectiveness include weight, blood pressure, waist circumference, BMI, and behavioral automaticity measures that will be collected at baseline and week 20. The P2S2 program could facilitate the development of healthful dietary and physical activity habits in an underserved population. Whether interventions aimed at changing habits can feasibly influence this automaticity, particularly for high-risk, low resource communities where other barriers exist, is not known. This pilot study, therefore, will fill an important gap, providing insight to inform subsequent trials.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

ISE-based sensor array system for classification of foodstuffs

NASA Astrophysics Data System (ADS)

Ciosek, Patrycja; Sobanski, Tomasz; Augustyniak, Ewa; Wróblewski, Wojciech

2006-01-01

A system composed of an array of polymeric membrane ion-selective electrodes and a pattern recognition block—a so-called 'electronic tongue'—was used for the classification of liquid samples: milk, fruit juice and tonic. The task of this system was to automatically recognize a brand of the product. To analyze the measurement set-up responses various non-parametric classifiers such as k-nearest neighbours, a feedforward neural network and a probabilistic neural network were used. In order to enhance the classification ability of the system, standard model solutions of salts were measured (in order to take into account any variation in time of the working parameters of the sensors). This system was capable of recognizing the brand of the products with accuracy ranging from 68% to 100% (in the case of the best classifier).

Attendance fingerprint identification system using arduino and single board computer

NASA Astrophysics Data System (ADS)

Muchtar, M. A.; Seniman; Arisandi, D.; Hasanah, S.

2018-03-01

Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

Machine learning phases of matter

NASA Astrophysics Data System (ADS)

Carrasquilla, Juan; Stoudenmire, Miles; Melko, Roger

We show how the technology that allows automatic teller machines read hand-written digits in cheques can be used to encode and recognize phases of matter and phase transitions in many-body systems. In particular, we analyze the (quasi-)order-disorder transitions in the classical Ising and XY models. Furthermore, we successfully use machine learning to study classical Z2 gauge theories that have important technological application in the coming wave of quantum information technologies and whose phase transitions have no conventional order parameter.

[Radiotherapy volume delineation based on (18F)-fluorodeoxyglucose positron emission tomography for locally advanced or inoperable oesophageal cancer].

PubMed

Encaoua, J; Abgral, R; Leleu, C; El Kabbaj, O; Caradec, P; Bourhis, D; Pradier, O; Schick, U

2017-06-01

To study the impact on radiotherapy planning of an automatically segmented target volume delineation based on ( 18 F)-fluorodeoxy-D-glucose (FDG)-hybrid positron emission tomography-computed tomography (PET-CT) compared to a manually delineation based on computed tomography (CT) in oesophageal carcinoma patients. Fifty-eight patients diagnosed with oesophageal cancer between September 2009 and November 2014 were included. The majority had squamous cell carcinoma (84.5 %), and advanced stage (37.9 % were stade IIIA) and 44.8 % had middle oesophageal lesion. Gross tumour volumes were retrospectively defined based either manually on CT or automatically on coregistered PET/CT images using three different threshold methods: standard-uptake value (SUV) of 2.5, 40 % of maximum intensity and signal-to-background ratio. Target volumes were compared in length, volume and using the index of conformality. Radiotherapy plans to the dose of 50Gy and 66Gy using intensity-modulated radiotherapy were generated and compared for both data sets. Planification target volume coverage and doses delivered to organs at risk (heart, lung and spinal cord) were compared. The gross tumour volume based manually on CT was significantly longer than that automatically based on signal-to-background ratio (6.4cm versus 5.3cm; P<0.008). Doses to the lungs (V20, D mean ), heart (V40), and spinal cord (D max ) were significantly lower on plans using the PTV SBR . The PTV SBR coverage was statistically better than the PTV CT coverage on both plans. (50Gy: P<0.0004 and 66Gy: P<0.0006). The automatic PET segmentation algorithm based on the signal-to-background ratio method for the delineation of oesophageal tumours is interesting, and results in better target volume coverage and decreased dose to organs at risk. This may allow dose escalation up to 66Gy to the gross tumour volume. Copyright © 2017 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

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

Chang, X; Yang, D

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was usedmore » to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.« less

Complex Event Recognition Architecture

NASA Technical Reports Server (NTRS)

Fitzgerald, William A.; Firby, R. James

2009-01-01

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Identifying typical physical activity on smartphone with varying positions and orientations.

PubMed

Miao, Fen; He, Yi; Liu, Jinlei; Li, Ye; Ayoola, Idowu

2015-04-13

Traditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body. By introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. The experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier. The utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.

Examining the robustness of automated aural classification of active sonar echoes.

PubMed

Murphy, Stefan M; Hines, Paul C

2014-02-01

Active sonar systems are used to detect underwater man-made objects of interest (targets) that are too quiet to be reliably detected with passive sonar. Performance of active sonar can be degraded by false alarms caused by echoes returned from geological seabed structures (clutter) in shallow regions. To reduce false alarms, a method of distinguishing target echoes from clutter echoes is required. Research has demonstrated that perceptual-based signal features similar to those employed in the human auditory system can be used to automatically discriminate between target and clutter echoes, thereby reducing the number of false alarms and improving sonar performance. An active sonar experiment on the Malta Plateau in the Mediterranean Sea was conducted during the Clutter07 sea trial and repeated during the Clutter09 sea trial. The dataset consists of more than 95,000 pulse-compressed echoes returned from two targets and many geological clutter objects. These echoes were processed using an automatic classifier that quantifies the timbre of each echo using a number of perceptual signal features. Using echoes from 2007, the aural classifier was trained to establish a boundary between targets and clutter in the feature space. Temporal robustness was then investigated by testing the classifier on echoes from the 2009 experiment.

A Method to Recognize Anatomical Site and Image Acquisition View in X-ray Images.

PubMed

Chang, Xiao; Mazur, Thomas; Li, H Harold; Yang, Deshan

2017-12-01

A method was developed to recognize anatomical site and image acquisition view automatically in 2D X-ray images that are used in image-guided radiation therapy. The purpose is to enable site and view dependent automation and optimization in the image processing tasks including 2D-2D image registration, 2D image contrast enhancement, and independent treatment site confirmation. The X-ray images for 180 patients of six disease sites (the brain, head-neck, breast, lung, abdomen, and pelvis) were included in this study with 30 patients each site and two images of orthogonal views each patient. A hierarchical multiclass recognition model was developed to recognize general site first and then specific site. Each node of the hierarchical model recognized the images using a feature extraction step based on principal component analysis followed by a binary classification step based on support vector machine. Given two images in known orthogonal views, the site recognition model achieved a 99% average F1 score across the six sites. If the views were unknown in the images, the average F1 score was 97%. If only one image was taken either with or without view information, the average F1 score was 94%. The accuracy of the site-specific view recognition models was 100%.

Enantioselective Effects of Chiral Pesticides on their Primary Targets and Secondary Targets.

PubMed

Yang, Ye; Zhang, Jianyun; Yao, Yijun

2017-01-01

Enantioselectivity has been well recognized in the environmental fate and effects of chiral pesticides. Enantiospecific action of the optical enantiomers on the biological molecules establishes the mechanistic basis for the enantioselective toxicity of chiral pesticides to both target and non-target organisms. We undertook a structured search of bibliographic databases for research literature concerning the enantioselective effects of chiral pesticides, including insecticides, herbicides and fungicides, on biomolecules in various species by using some key words. The results of the relevant literatures were reviewed in the text and summarized in tables. Pesticides generally exert their activity on the target organisms via disrupting the primary target biomolecules. In non-target species, effects of pesticides on the secondary targets distinguished from the primary ones make great contribution to their toxicity. Recent investigations have provided convincing evidence of enantioselective toxicity of chiral pesticides to both target and non-target species which is recognized to result from their enantiospecific action on the primary or secondary targets in organisms. This review confirms that chiral pesticides have enantiospecific effects on both primary and secondary target biomolecules in organisms. Future studies regarding toxicological effects of chiral pesticides should focus on the relationship between the enantiomeric difference in the compound-biomolecules interaction and the enantioselectivity in their toxicity.

Opaque-2 is a transcriptional activator that recognizes a specific target site in 22-kD zein genes.

PubMed Central

Schmidt, R J; Ketudat, M; Aukerman, M J; Hoschek, G

1992-01-01

opaque-2 (o2) is a regulatory locus in maize that plays an essential role in controlling the expression of genes encoding the 22-kD zein proteins. Through DNase I footprinting and DNA binding analyses, we have identified the binding site for the O2 protein (O2) in the promoter of 22-kD zein genes. The sequence in the 22-kD zein gene promoter that is recognized by O2 is similar to the target site recognized by other "basic/leucine zipper" (bZIP) proteins in that it contains an ACGT core that is necessary for DNA binding. The site is located in the -300 region relative to the translation start and lies about 20 bp downstream of the highly conserved zein gene sequence motif known as the "prolamin box." Employing gel mobility shift assays, we used O2 antibodies and nuclear extracts from an o2 null mutant to demonstrate that the O2 protein in maize endosperm nuclei recognizes the target site in the zein gene promoter. Mobility shift assays using nuclear proteins from an o2 null mutant indicated that other endosperm proteins in addition to O2 can bind the O2 target site and that O2 may be associated with one of these proteins. We also demonstrated that in yeast cells the O2 protein can activate expression of a lacZ gene containing a multimer of the O2 target sequence as part of its promoter, thus confirming its role as a transcriptional activator. A computer-assisted search indicated that the O2 target site is not present in the promoters of zein genes other than those of the 22-kD class. These data suggest a likely explanation at the molecular level for the differential effect of o2 mutations on expression of certain members of the zein gene family. PMID:1392590

Automatic and strategic effects in the guidance of attention by working memory representations

PubMed Central

Carlisle, Nancy B.; Woodman, Geoffrey F.

2010-01-01

Theories of visual attention suggest that working memory representations automatically guide attention toward memory-matching objects. Some empirical tests of this prediction have produced results consistent with working memory automatically guiding attention. However, others have shown that individuals can strategically control whether working memory representations guide visual attention. Previous studies have not independently measured automatic and strategic contributions to the interactions between working memory and attention. In this study, we used a classic manipulation of the probability of valid, neutral, and invalid cues to tease apart the nature of such interactions. This framework utilizes measures of reaction time (RT) to quantify the costs and benefits of attending to memory-matching items and infer the relative magnitudes of automatic and strategic effects. We found both costs and benefits even when the memory-matching item was no more likely to be the target than other items, indicating an automatic component of attentional guidance. However, the costs and benefits essentially doubled as the probability of a trial with a valid cue increased from 20% to 80%, demonstrating a potent strategic effect. We also show that the instructions given to participants led to a significant change in guidance distinct from the actual probability of events during the experiment. Together, these findings demonstrate that the influence of working memory representations on attention is driven by both automatic and strategic interactions. PMID:20643386

Automaticity of higher cognitive functions: neurophysiological evidence for unconscious syntactic processing of masked words.

PubMed

Jiménez-Ortega, Laura; García-Milla, Marcos; Fondevila, Sabela; Casado, Pilar; Hernández-Gutiérrez, David; Martín-Loeches, Manuel

2014-12-01

Models of language comprehension assume that syntactic processing is automatic, at least at early stages. However, the degree of automaticity of syntactic processing is still controversial. Evidence of automaticity is either indirect or has been observed for pairs of words, which might provide a poor syntactic context in comparison to sentences. The present study investigates the automaticity of syntactic processing using event-related brain potentials (ERPs) during sentence processing. To this end, masked adjectives that could either be syntactically correct or incorrect relative to a sentence being processed appeared just prior to the presentation of supraliminal adjectives. The latter could also be correct or incorrect. According to our data, subliminal gender agreement violations embedded in a sentence trigger an early anterior negativity-like modulation, whereas supraliminal gender agreement violations elicited a later anterior negativity. First-pass syntactic parsing thus appears to be unconsciously and automatically elicited. Interestingly, a P600-like modulation of short duration and early latency could also be observed for masked violations. In addition, masked violations also modulated the P600 component elicited by unmasked targets, probably reflecting that the mechanisms of revising a structural mismatch appear affected by subliminal information. According to our findings, both conscious and unconscious processes apparently contribute to syntactic processing. These results are discussed in line with most recent theories of automaticity and syntactic processing. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic and strategic effects in the guidance of attention by working memory representations.

PubMed

Carlisle, Nancy B; Woodman, Geoffrey F

2011-06-01

Theories of visual attention suggest that working memory representations automatically guide attention toward memory-matching objects. Some empirical tests of this prediction have produced results consistent with working memory automatically guiding attention. However, others have shown that individuals can strategically control whether working memory representations guide visual attention. Previous studies have not independently measured automatic and strategic contributions to the interactions between working memory and attention. In this study, we used a classic manipulation of the probability of valid, neutral, and invalid cues to tease apart the nature of such interactions. This framework utilizes measures of reaction time (RT) to quantify the costs and benefits of attending to memory-matching items and infer the relative magnitudes of automatic and strategic effects. We found both costs and benefits even when the memory-matching item was no more likely to be the target than other items, indicating an automatic component of attentional guidance. However, the costs and benefits essentially doubled as the probability of a trial with a valid cue increased from 20% to 80%, demonstrating a potent strategic effect. We also show that the instructions given to participants led to a significant change in guidance distinct from the actual probability of events during the experiment. Together, these findings demonstrate that the influence of working memory representations on attention is driven by both automatic and strategic interactions. Copyright © 2010 Elsevier B.V. All rights reserved.

RoboTAP: Target priorities for robotic microlensing observations

NASA Astrophysics Data System (ADS)

Hundertmark, M.; Street, R. A.; Tsapras, Y.; Bachelet, E.; Dominik, M.; Horne, K.; Bozza, V.; Bramich, D. M.; Cassan, A.; D'Ago, G.; Figuera Jaimes, R.; Kains, N.; Ranc, C.; Schmidt, R. W.; Snodgrass, C.; Wambsganss, J.; Steele, I. A.; Mao, S.; Ment, K.; Menzies, J.; Li, Z.; Cross, S.; Maoz, D.; Shvartzvald, Y.

2018-01-01

Context. The ability to automatically select scientifically-important transient events from an alert stream of many such events, and to conduct follow-up observations in response, will become increasingly important in astronomy. With wide-angle time domain surveys pushing to fainter limiting magnitudes, the capability to follow-up on transient alerts far exceeds our follow-up telescope resources, and effective target prioritization becomes essential. The RoboNet-II microlensing program is a pathfinder project, which has developed an automated target selection process (RoboTAP) for gravitational microlensing events, which are observed in real time using the Las Cumbres Observatory telescope network. Aims: Follow-up telescopes typically have a much smaller field of view compared to surveys, therefore the most promising microlensing events must be automatically selected at any given time from an annual sample exceeding 2000 events. The main challenge is to select between events with a high planet detection sensitivity, with the aim of detecting many planets and characterizing planetary anomalies. Methods: Our target selection algorithm is a hybrid system based on estimates of the planet detection zones around a microlens. It follows automatic anomaly alerts and respects the expected survey coverage of specific events. Results: We introduce the RoboTAP algorithm, whose purpose is to select and prioritize microlensing events with high sensitivity to planetary companions. In this work, we determine the planet sensitivity of the RoboNet follow-up program and provide a working example of how a broker can be designed for a real-life transient science program conducting follow-up observations in response to alerts; we explore the issues that will confront similar programs being developed for the Large Synoptic Survey Telescope (LSST) and other time domain surveys.

The Improvement of Automated Spectral Identification Tool ASERA

NASA Astrophysics Data System (ADS)

Yuan, Hailong; zhang, Yanxia

2015-08-01

The regular survey of Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has acquired over four millions spectra of celestial objects by the summer of 2014, covering about a third of the whole sky area. More spectra will be obtained as the survey projects (eg. LAMOST, SDSS) keeps going on. To effectively make use of the massive spectral data, various advanced data analysis methods and technologies are in great requirement. ASERA, A Spectrum Eye Recognition Assistant, provides a simple convenient solution for the user to access spectra from LAMOST and SDSS, identify their types (QSO, galaxy, and various types of stars) and estimate their redshifts in an interactive graphic interface. The toolkit is at first especially designed for quasar identification. By shifting the quasar template overlaping the target spectrum interactively, one can easily find out the best broad emission line position and the redshift value. Now, besides the quasar template, various templates for different types of galaxies (early type, later type, starburst, bulge, elliptical and luminous red galaxies) and stars (O, B, A, F, G, K, M, WD, CV, Double Stars and Emission-Line-Objects) are added. We also have developed many new useful functionalities for inspecting and analyzing spectra, such as zooming, line fitting, smoothing and automatic result saving. The target information from input catalogues and data processing result from the pipeline as well as fitting parameters for various types of templates, can be presented at the same time. Several volume processing components are developed to support the cooperation with MySQL database, internet resources and SSAP services. ASERA will be a strong helper for astronomers to recognize spectra.

Automatic target recognition and detection in infrared imagery under cluttered background

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Koç, Aykut; Alatan, A. Aydın.

2017-10-01

Visual object classification has long been studied in visible spectrum by utilizing conventional cameras. Since the labeled images has recently increased in number, it is possible to train deep Convolutional Neural Networks (CNN) with significant amount of parameters. As the infrared (IR) sensor technology has been improved during the last two decades, labeled images extracted from IR sensors have been started to be used for object detection and recognition tasks. We address the problem of infrared object recognition and detection by exploiting 15K images from the real-field with long-wave and mid-wave IR sensors. For feature learning, a stacked denoising autoencoder is trained in this IR dataset. To recognize the objects, the trained stacked denoising autoencoder is fine-tuned according to the binary classification loss of the target object. Once the training is completed, the test samples are propagated over the network, and the probability of the test sample belonging to a class is computed. Moreover, the trained classifier is utilized in a detect-by-classification method, where the classification is performed in a set of candidate object boxes and the maximum confidence score in a particular location is accepted as the score of the detected object. To decrease the computational complexity, the detection step at every frame is avoided by running an efficient correlation filter based tracker. The detection part is performed when the tracker confidence is below a pre-defined threshold. The experiments conducted on the real field images demonstrate that the proposed detection and tracking framework presents satisfactory results for detecting tanks under cluttered background.

Comprehensive BRL-CAD Primitive Database

DTIC Science & Technology

2015-03-01

are not to be construed as an official Department of the Army position unless so designated by other authorized documents. Citation of...database provides the target describers of BRL–CAD with a representative example of each primitive’s shape and its properties. In addition to the...database was completed, a tool was created to generate primitive shapes automatically. This provides target describers—CAD experts who generate

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.

Combatting Inherent Vulnerabilities of CFAR Algorithms and a New Robust CFAR Design

DTIC Science & Technology

1993-09-01

elements of any automatic radar system. Unfortunately, CFAR systems are inherently vulnerable to degradation caused by large clutter edges, multiple ...edges, multiple targets, and electronic countermeasures (ECM) environments. 20 Distribution, Availability of Abstract 21 Abstract Security...inherently vulnerable to degradation caused by large clutter edges, multiple targets and jamming environments. This thesis presents eight popular and studied

Sounds activate visual cortex and improve visual discrimination.

PubMed

Feng, Wenfeng; Störmer, Viola S; Martinez, Antigona; McDonald, John J; Hillyard, Steven A

2014-07-16

A recent study in humans (McDonald et al., 2013) found that peripheral, task-irrelevant sounds activated contralateral visual cortex automatically as revealed by an auditory-evoked contralateral occipital positivity (ACOP) recorded from the scalp. The present study investigated the functional significance of this cross-modal activation of visual cortex, in particular whether the sound-evoked ACOP is predictive of improved perceptual processing of a subsequent visual target. A trial-by-trial analysis showed that the ACOP amplitude was markedly larger preceding correct than incorrect pattern discriminations of visual targets that were colocalized with the preceding sound. Dipole modeling of the scalp topography of the ACOP localized its neural generators to the ventrolateral extrastriate visual cortex. These results provide direct evidence that the cross-modal activation of contralateral visual cortex by a spatially nonpredictive but salient sound facilitates the discriminative processing of a subsequent visual target event at the location of the sound. Recordings of event-related potentials to the targets support the hypothesis that the ACOP is a neural consequence of the automatic orienting of visual attention to the location of the sound. Copyright © 2014 the authors 0270-6474/14/349817-08$15.00/0.

Neural network for intelligent query of an FBI forensic database

NASA Astrophysics Data System (ADS)

Uvanni, Lee A.; Rainey, Timothy G.; Balasubramanian, Uma; Brettle, Dean W.; Weingard, Fred; Sibert, Robert W.; Birnbaum, Eric

1997-02-01

Examiner is an automated fired cartridge case identification system utilizing a dual-use neural network pattern recognition technology, called the statistical-multiple object detection and location system (S-MODALS) developed by Booz(DOT)Allen & Hamilton, Inc. in conjunction with Rome Laboratory. S-MODALS was originally designed for automatic target recognition (ATR) of tactical and strategic military targets using multisensor fusion [electro-optical (EO), infrared (IR), and synthetic aperture radar (SAR)] sensors. Since S-MODALS is a learning system readily adaptable to problem domains other than automatic target recognition, the pattern matching problem of microscopic marks for firearms evidence was analyzed using S-MODALS. The physics; phenomenology; discrimination and search strategies; robustness requirements; error level and confidence level propagation that apply to the pattern matching problem of military targets were found to be applicable to the ballistic domain as well. The Examiner system uses S-MODALS to rank a set of queried cartridge case images from the most similar to the least similar image in reference to an investigative fired cartridge case image. The paper presents three independent tests and evaluation studies of the Examiner system utilizing the S-MODALS technology for the Federal Bureau of Investigation.

The development and progress of XeCl Excimer laser system

NASA Astrophysics Data System (ADS)

Zhang, Yongsheng; Ma, Lianying; Wang, Dahui; Zhao, Xueqing; Zhu, Yongxiang; Hu, Yun; Qian, Hang; Shao, Bibo; Yi, Aiping; Liu, Jingru

2015-05-01

A large angularly multiplexed XeCl Excimer laser system is under development at the Northwest Institute of Nuclear Technology (NINT). It is designed to explore the technical issues of uniform and controllable target illumination. Short wavelength, uniform and controllable target illumination is the fundamental requirement of high energy density physics research using large laser facility. With broadband, extended light source and multi-beam overlapping techniques, rare gas halide Excimer laser facility will provide uniform target illumination theoretically. Angular multiplexing and image relay techniques are briefly reviewed and some of the limitations are examined to put it more practical. The system consists of a commercial oscillator front end, three gas discharge amplifiers, two electron beam pumped amplifiers and the optics required to relay, encode and decode the laser beam. An 18 lens array targeting optics direct and focus the laser in the vacuum target chamber. The system is operational and currently undergoing tests. The total 18 beams output energy is more than 100J and the pulse width is 7ns (FWHM), the intensities on the target will exceed 1013W/cm2. The aberration of off-axis imaging optics at main amplifier should be minimized to improve the final image quality at the target. Automatic computer controlled alignment of the whole system is vital to efficiency and stability of the laser system, an array of automatic alignment model is under test and will be incorporated in the system soon.

Attention to baseline: does orienting visuospatial attention really facilitate target detection?

PubMed

Albares, Marion; Criaud, Marion; Wardak, Claire; Nguyen, Song Chi Trung; Ben Hamed, Suliann; Boulinguez, Philippe

2011-08-01

Standard protocols testing the orientation of visuospatial attention usually present spatial cues before targets and compare valid-cue trials with invalid-cue trials. The valid/invalid contrast results in a relative behavioral or physiological difference that is generally interpreted as a benefit of attention orientation. However, growing evidence suggests that inhibitory control of response is closely involved in this kind of protocol that requires the subjects to withhold automatic responses to cues, probably biasing behavioral and physiological baselines. Here, we used two experiments to disentangle the inhibitory control of automatic responses from orienting of visuospatial attention in a saccadic reaction time task in humans, a variant of the classical cue-target detection task and a sustained visuospatial attentional task. Surprisingly, when referring to a simple target detection task in which there is no need to refrain from reacting to avoid inappropriate responses, we found no consistent evidence of facilitation of target detection at the attended location. Instead, we observed a cost at the unattended location. Departing from the classical view, our results suggest that reaction time measures of visuospatial attention probably relie on the attenuation of elementary processes involved in visual target detection and saccade initiation away from the attended location rather than on facilitation at the attended location. This highlights the need to use proper control conditions in experimental designs to disambiguate relative from absolute cueing benefits on target detection reaction times, both in psychophysical and neurophysiological studies.

The Influence of Facial Signals on the Automatic Imitation of Hand Actions

PubMed Central

Butler, Emily E.; Ward, Robert; Ramsey, Richard

2016-01-01

Imitation and facial signals are fundamental social cues that guide interactions with others, but little is known regarding the relationship between these behaviors. It is clear that during expression detection, we imitate observed expressions by engaging similar facial muscles. It is proposed that a cognitive system, which matches observed and performed actions, controls imitation and contributes to emotion understanding. However, there is little known regarding the consequences of recognizing affective states for other forms of imitation, which are not inherently tied to the observed emotion. The current study investigated the hypothesis that facial cue valence would modulate automatic imitation of hand actions. To test this hypothesis, we paired different types of facial cue with an automatic imitation task. Experiments 1 and 2 demonstrated that a smile prompted greater automatic imitation than angry and neutral expressions. Additionally, a meta-analysis of this and previous studies suggests that both happy and angry expressions increase imitation compared to neutral expressions. By contrast, Experiments 3 and 4 demonstrated that invariant facial cues, which signal trait-levels of agreeableness, had no impact on imitation. Despite readily identifying trait-based facial signals, levels of agreeableness did not differentially modulate automatic imitation. Further, a Bayesian analysis showed that the null effect was between 2 and 5 times more likely than the experimental effect. Therefore, we show that imitation systems are more sensitive to prosocial facial signals that indicate “in the moment” states than enduring traits. These data support the view that a smile primes multiple forms of imitation including the copying actions that are not inherently affective. The influence of expression detection on wider forms of imitation may contribute to facilitating interactions between individuals, such as building rapport and affiliation. PMID:27833573

Scanner OPC signatures: automatic vendor-to-vendor OPE matching

NASA Astrophysics Data System (ADS)

Renwick, Stephen P.

2009-03-01

As 193nm lithography continues to be stretched and the k1 factor decreases, optical proximity correction (OPC) has become a vital part of the lithographer's tool kit. Unfortunately, as is now well known, the design variations of lithographic scanners from different vendors cause them to have slightly different optical-proximity effect (OPE) behavior, meaning that they print features through pitch in distinct ways. This in turn means that their response to OPC is not the same, and that an OPC solution designed for a scanner from Company 1 may or may not work properly on a scanner from Company 2. Since OPC is not inexpensive, that causes trouble for chipmakers using more than one brand of scanner. Clearly a scanner-matching procedure is needed to meet this challenge. Previously, automatic matching has only been reported for scanners of different tool generations from the same manufacturer. In contrast, scanners from different companies have been matched using expert tuning and adjustment techniques, frequently requiring laborious test exposures. Automatic matching between scanners from Company 1 and Company 2 has remained an unsettled problem. We have recently solved this problem and introduce a novel method to perform the automatic matching. The success in meeting this challenge required three enabling factors. First, we recognized the strongest drivers of OPE mismatch and are thereby able to reduce the information needed about a tool from another supplier to that information readily available from all modern scanners. Second, we developed a means of reliably identifying the scanners' optical signatures, minimizing dependence on process parameters that can cloud the issue. Third, we carefully employed standard statistical techniques, checking for robustness of the algorithms used and maximizing efficiency. The result is an automatic software system that can predict an OPC matching solution for scanners from different suppliers without requiring expert intervention.

The Influence of Facial Signals on the Automatic Imitation of Hand Actions.

PubMed

Butler, Emily E; Ward, Robert; Ramsey, Richard

2016-01-01

Imitation and facial signals are fundamental social cues that guide interactions with others, but little is known regarding the relationship between these behaviors. It is clear that during expression detection, we imitate observed expressions by engaging similar facial muscles. It is proposed that a cognitive system, which matches observed and performed actions, controls imitation and contributes to emotion understanding. However, there is little known regarding the consequences of recognizing affective states for other forms of imitation, which are not inherently tied to the observed emotion. The current study investigated the hypothesis that facial cue valence would modulate automatic imitation of hand actions. To test this hypothesis, we paired different types of facial cue with an automatic imitation task. Experiments 1 and 2 demonstrated that a smile prompted greater automatic imitation than angry and neutral expressions. Additionally, a meta-analysis of this and previous studies suggests that both happy and angry expressions increase imitation compared to neutral expressions. By contrast, Experiments 3 and 4 demonstrated that invariant facial cues, which signal trait-levels of agreeableness, had no impact on imitation. Despite readily identifying trait-based facial signals, levels of agreeableness did not differentially modulate automatic imitation. Further, a Bayesian analysis showed that the null effect was between 2 and 5 times more likely than the experimental effect. Therefore, we show that imitation systems are more sensitive to prosocial facial signals that indicate "in the moment" states than enduring traits. These data support the view that a smile primes multiple forms of imitation including the copying actions that are not inherently affective. The influence of expression detection on wider forms of imitation may contribute to facilitating interactions between individuals, such as building rapport and affiliation.

AMPS/PC - AUTOMATIC MANUFACTURING PROGRAMMING SYSTEM

NASA Technical Reports Server (NTRS)

Schroer, B. J.

1994-01-01

The AMPS/PC system is a simulation tool designed to aid the user in defining the specifications of a manufacturing environment and then automatically writing code for the target simulation language, GPSS/PC. The domain of problems that AMPS/PC can simulate are manufacturing assembly lines with subassembly lines and manufacturing cells. The user defines the problem domain by responding to the questions from the interface program. Based on the responses, the interface program creates an internal problem specification file. This file includes the manufacturing process network flow and the attributes for all stations, cells, and stock points. AMPS then uses the problem specification file as input for the automatic code generator program to produce a simulation program in the target language GPSS. The output of the generator program is the source code of the corresponding GPSS/PC simulation program. The system runs entirely on an IBM PC running PC DOS Version 2.0 or higher and is written in Turbo Pascal Version 4 requiring 640K memory and one 360K disk drive. To execute the GPSS program, the PC must have resident the GPSS/PC System Version 2.0 from Minuteman Software. The AMPS/PC program was developed in 1988.

Affective divergence: automatic responses to others' emotions depend on group membership.

PubMed

Weisbuch, Max; Ambady, Nalini

2008-11-01

Extant research suggests that targets' emotion expressions automatically evoke similar affect in perceivers. The authors hypothesized that the automatic impact of emotion expressions depends on group membership. In Experiments 1 and 2, an affective priming paradigm was used to measure immediate and preconscious affective responses to same-race or other-race emotion expressions. In Experiment 3, spontaneous vocal affect was measured as participants described the emotions of an ingroup or outgroup sports team fan. In these experiments, immediate and spontaneous affective responses depended on whether the emotional target was ingroup or outgroup. Positive responses to fear expressions and negative responses to joy expressions were observed in outgroup perceivers, relative to ingroup perceivers. In Experiments 4 and 5, discrete emotional responses were examined. In a lexical decision task (Experiment 4), facial expressions of joy elicited fear in outgroup perceivers, relative to ingroup perceivers. In contrast, facial expressions of fear elicited less fear in outgroup than in ingroup perceivers. In Experiment 5, felt dominance mediated emotional responses to ingroup and outgroup vocal emotion. These data support a signal-value model in which emotion expressions signal environmental conditions. (c) 2008 APA, all rights reserved.

An automatic markerless registration method for neurosurgical robotics based on an optical camera.

PubMed

Meng, Fanle; Zhai, Fangwen; Zeng, Bowei; Ding, Hui; Wang, Guangzhi

2018-02-01

Current markerless registration methods for neurosurgical robotics use the facial surface to match the robot space with the image space, and acquisition of the facial surface usually requires manual interaction and constrains the patient to a supine position. To overcome these drawbacks, we propose a registration method that is automatic and does not constrain patient position. An optical camera attached to the robot end effector captures images around the patient's head from multiple views. Then, high coverage of the head surface is reconstructed from the images through multi-view stereo vision. Since the acquired head surface point cloud contains color information, a specific mark that is manually drawn on the patient's head prior to the capture procedure can be extracted to automatically accomplish coarse registration rather than using facial anatomic landmarks. Then, fine registration is achieved by registering the high coverage of the head surface without relying solely on the facial region, thus eliminating patient position constraints. The head surface was acquired by the camera with a good repeatability accuracy. The average target registration error of 8 different patient positions measured with targets inside a head phantom was [Formula: see text], while the mean surface registration error was [Formula: see text]. The method proposed in this paper achieves automatic markerless registration in multiple patient positions and guarantees registration accuracy inside the head. This method provides a new approach for establishing the spatial relationship between the image space and the robot space.

Effects of ongoing task context and target typicality on prospective memory performance: the importance of associative cueing

NASA Technical Reports Server (NTRS)

Nowinski, Jessica Lang; Dismukes, Key R.

2005-01-01

Two experiments examined whether prospective memory performance is influenced by contextual cues. In our automatic activation model, any information available at encoding and retrieval should aid recall of the prospective task. The first experiment demonstrated an effect of the ongoing task context; performance was better when information about the ongoing task present at retrieval was available at encoding. Performance was also improved by a strong association between the prospective memory target as it was presented at retrieval and the intention as it was encoded. Experiment 2 demonstrated boundary conditions of the ongoing task context effect, which implicate the association between the ongoing and prospective tasks formed at encoding as the source of the context effect. The results of this study are consistent with predictions based on automatic activation of intentions.

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.

Effectiveness-weighted control method for a cooling system

DOEpatents

Campbell, Levi A.; Chu, Richard C.; David, Milnes P.; Ellsworth Jr., Michael J.; Iyengar, Madhusudan K.; Schmidt, Roger R.; Simons, Robert E.

2015-12-15

Energy efficient control of cooling system cooling of an electronic system is provided based, in part, on weighted cooling effectiveness of the components. The control includes automatically determining speed control settings for multiple adjustable cooling components of the cooling system. The automatically determining is based, at least in part, on weighted cooling effectiveness of the components of the cooling system, and the determining operates to limit power consumption of at least the cooling system, while ensuring that a target temperature associated with at least one of the cooling system or the electronic system is within a desired range by provisioning, based on the weighted cooling effectiveness, a desired target temperature change among the multiple adjustable cooling components of the cooling system. The provisioning includes provisioning applied power to the multiple adjustable cooling components via, at least in part, the determined control settings.

Effectiveness-weighted control of cooling system components

DOEpatents

Campbell, Levi A.; Chu, Richard C.; David, Milnes P.; Ellsworth Jr., Michael J.; Iyengar, Madhusudan K.; Schmidt, Roger R.; Simmons, Robert E.

2015-12-22

Energy efficient control of cooling system cooling of an electronic system is provided based, in part, on weighted cooling effectiveness of the components. The control includes automatically determining speed control settings for multiple adjustable cooling components of the cooling system. The automatically determining is based, at least in part, on weighted cooling effectiveness of the components of the cooling system, and the determining operates to limit power consumption of at least the cooling system, while ensuring that a target temperature associated with at least one of the cooling system or the electronic system is within a desired range by provisioning, based on the weighted cooling effectiveness, a desired target temperature change among the multiple adjustable cooling components of the cooling system. The provisioning includes provisioning applied power to the multiple adjustable cooling components via, at least in part, the determined control settings.

A Graph-Based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications

PubMed Central

Cameron, Delroy; Bodenreider, Olivier; Yalamanchili, Hima; Danh, Tu; Vallabhaneni, Sreeram; Thirunarayan, Krishnaprasad; Sheth, Amit P.; Rindflesch, Thomas C.

2014-01-01

Objectives This paper presents a methodology for recovering and decomposing Swanson’s Raynaud Syndrome–Fish Oil Hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically capture the informative associations originally discovered manually by Swanson. Demonstrating that Swanson’s manually intensive techniques can be undertaken semi-automatically, paves the way for fully automatic semantics-based hypothesis generation from scientific literature. Methods Semantic predications obtained from biomedical literature allow the construction of labeled directed graphs which contain various associations among concepts from the literature. By aggregating such associations into informative subgraphs, some of the relevant details originally articulated by Swanson has been uncovered. However, by leveraging background knowledge to bridge important knowledge gaps in the literature, a methodology for semi-automatically capturing the detailed associations originally explicated in natural language by Swanson has been developed. Results Our methodology not only recovered the 3 associations commonly recognized as Swanson’s Hypothesis, but also decomposed them into an additional 16 detailed associations, formulated as chains of semantic predications. Altogether, 14 out of the 19 associations that can be attributed to Swanson were retrieved using our approach. To the best of our knowledge, such an in-depth recovery and decomposition of Swanson’s Hypothesis has never been attempted. Conclusion In this work therefore, we presented a methodology for semi- automatically recovering and decomposing Swanson’s RS-DFO Hypothesis using semantic representations and graph algorithms. Our methodology provides new insights into potential prerequisites for semantics-driven Literature-Based Discovery (LBD). These suggest that three critical aspects of LBD include: 1) the need for more expressive representations beyond Swanson’s ABC model; 2) an ability to accurately extract semantic information from text; and 3) the semantic integration of scientific literature with structured background knowledge. PMID:23026233

VizieR Online Data Catalog: Swift Master Catalog (HEASARC, 2004-)

NASA Astrophysics Data System (ADS)

Nasa; Heasarc

2018-01-01

This table records high-level information for each Swift observation and provides access to the data archive. Each record is associated with a single observation that contains data from all instruments on board Swift. The BAT is the large field of view instrument and operates in the 10-300 keV energy band. The narrow field instruments, XRT and UVOT, operate in the X-ray and UV/optical regime, respectively. An observation is defined as a collection of snapshots, where a snapshot is defined as the time spent observing the same position continuously. Because of observing constraints, the length of a snapshot can be shorter than a single orbit and it can be interrupted because the satellite will point in a different direction of the sky or because the time allocated to that observation ends. The typical Swift observing strategy for a Gamma Ray Burst (GRB) and/or afterglow, consists of a serious of observations aimed at following the GRB and its afterglow evolution. This strategy is achieved with two different type of observations named Automatic Targets and Pre-Planned Targets. The Automatic Target is initiated on board soon after an event is triggered by the BAT. The Figure of Merit (FOM) algorithm, part of the observatory's autonomy, decides if it is worth requesting a slew maneuver to point the narrow field instruments (NFI) on Swift, XRT and UVOT, in the direction of the trigger. If the conditions to slew to the new position are satisfied, the Automatic Target observation takes place; all the instruments have a pre-set standard configuration of operating modes and filters and about 20000 seconds on source will be collected. The Pre-Planned Target observations instead are initiated from the ground once the trigger is known. These observations are planned on ground and uploaded onto the spacecraft. (1 data file).

Automatic target validation based on neuroscientific literature mining for tractography

PubMed Central

Vasques, Xavier; Richardet, Renaud; Hill, Sean L.; Slater, David; Chappelier, Jean-Cedric; Pralong, Etienne; Bloch, Jocelyne; Draganski, Bogdan; Cif, Laura

2015-01-01

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/. PMID:26074781

Automatic Speech Recognition from Neural Signals: A Focused Review.

PubMed

Herff, Christian; Schultz, Tanja

2016-01-01

Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people. This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography). As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the Brain-to-text system.

Quantum dots-based double imaging combined with organic dye imaging to establish an automatic computerized method for cancer Ki67 measurement.

PubMed

Wang, Lin-Wei; Qu, Ai-Ping; Liu, Wen-Lou; Chen, Jia-Mei; Yuan, Jing-Ping; Wu, Han; Li, Yan; Liu, Juan

2016-02-03

As a widely used proliferative marker, Ki67 has important impacts on cancer prognosis, especially for breast cancer (BC). However, variations in analytical practice make it difficult for pathologists to manually measure Ki67 index. This study is to establish quantum dots (QDs)-based double imaging of nuclear Ki67 as red signal by QDs-655, cytoplasmic cytokeratin (CK) as yellow signal by QDs-585, and organic dye imaging of cell nucleus as blue signal by 4',6-diamidino-2-phenylindole (DAPI), and to develop a computer-aided automatic method for Ki67 index measurement. The newly developed automatic computerized Ki67 measurement could efficiently recognize and count Ki67-positive cancer cell nuclei with red signals and cancer cell nuclei with blue signals within cancer cell cytoplasmic with yellow signals. Comparisons of computerized Ki67 index, visual Ki67 index, and marked Ki67 index for 30 patients of 90 images with Ki67 ≤ 10% (low grade), 10% < Ki67 < 50% (moderate grade), and Ki67 ≥ 50% (high grade) showed computerized Ki67 counting is better than visual Ki67 counting, especially for Ki67 low and moderate grades. Based on QDs-based double imaging and organic dye imaging on BC tissues, this study successfully developed an automatic computerized Ki67 counting method to measure Ki67 index.

Literacy and Schooling in One Family across Time

ERIC Educational Resources Information Center

Compton-Lilly, Catherine

2011-01-01

Most research involving the analyses of discourses targets particular points in time or relatively short durations (i.e., one semester, one year). Failure to recognize the ways discourses operate over long periods of time limits the ability of educators and researchers to recognize the temporal nature of meaning construction. Through this…

Curiosity Finds Hydrogen-Rich Area of Mars Subsurface

NASA Image and Video Library

2015-08-19

Curiosity's Russian-made instrument for checking hydration levels in the ground beneath the rover detected an unusually high amount at a site near "Marias Pass," prompting repeated passes over the area to map the hydrogen amounts. The instrument is named Dynamic Albedo of Neutrons, or DAN. It detects hydrogen by the effect of hydrogen atoms on neutrons entering the ground either from cosmic rays and Curiosity's power source (DAN's passive mode) or from the instrument's neutron pulse generator (DAN's active mode). DAN recognizes which neutrons have bounced off hydrogen from their rerduced energy level. This map, covering an area about 130 feet (40 meters) across, shows results from DAN's multiple traverses over the area, with color coding for levels of hydrogen detected. The red coding indicates amounts of hydrogen three to four times as high as the amounts detected anywhere previously along Curiosity's traverse of about 6.9 miles (11.1 kilometers) since landing in August 2012. The inset map at lower right shows the full traverse through Sol 1051 (July 21, 2015), with names assigned to rectangles within Gale Crater for geological mapping purposes. The vertical bar at left indicates the color coding according to counts per second in DAN's passive mode. The hydrogen detected by DAN is interpreted as water molecules or hydroxyl ions bound within minerals or water absorbed onto minerals in the rocks and soil, to a depth of about 3 feet (1 meter) beneath the rover. The amount of hydrogen is often expressed as "water equivalent hydrogen" based on two hydrogen atoms per molecule of water. In the same area where DAN detected an unusually high amount of hydration, Curiosity's Chemistry and Camera (ChemCam) instrument detected an unusually high amount of silica in several rock targets. The DAN and ChemCam findings led to the rover's science team choosing a rock target called "Buckskin" for collection of a drilled sample to be analyzed by the rover's internal laboratory instruments. Russia's Space Research Institute developed DAN in close cooperation with the N.L. Dukhov All-Russia Research Institute of Automatics, Moscow, and the Joint Institute for Nuclear Research, Dubna. The neutron generator development was supervised by the late technical designer German A. Smirnov of the All-Russia Institute of Automatics. Moscow. http://photojournal.jpl.nasa.gov/catalog/PIA19809

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

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

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

SU-F-J-34: Automatic Target-Based Patient Positioning Framework for Image-Guided Radiotherapy in Prostate Cancer Treatment

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

Sasahara, M; Arimura, H; Hirose, T

Purpose: Current image-guided radiotherapy (IGRT) procedure is bonebased patient positioning, followed by subjective manual correction using cone beam computed tomography (CBCT). This procedure might cause the misalignment of the patient positioning. Automatic target-based patient positioning systems achieve the better reproducibility of patient setup. Our aim of this study was to develop an automatic target-based patient positioning framework for IGRT with CBCT images in prostate cancer treatment. Methods: Seventy-three CBCT images of 10 patients and 24 planning CT images with digital imaging and communications in medicine for radiotherapy (DICOM-RT) structures were used for this study. Our proposed framework started from themore » generation of probabilistic atlases of bone and prostate from 24 planning CT images and prostate contours, which were made in the treatment planning. Next, the gray-scale histograms of CBCT values within CTV regions in the planning CT images were obtained as the occurrence probability of the CBCT values. Then, CBCT images were registered to the atlases using a rigid registration with mutual information. Finally, prostate regions were estimated by applying the Bayesian inference to CBCT images with the probabilistic atlases and CBCT value occurrence probability. The proposed framework was evaluated by calculating the Euclidean distance of errors between two centroids of prostate regions determined by our method and ground truths of manual delineations by a radiation oncologist and a medical physicist on CBCT images for 10 patients. Results: The average Euclidean distance between the centroids of extracted prostate regions determined by our proposed method and ground truths was 4.4 mm. The average errors for each direction were 1.8 mm in anteroposterior direction, 0.6 mm in lateral direction and 2.1 mm in craniocaudal direction. Conclusion: Our proposed framework based on probabilistic atlases and Bayesian inference might be feasible to automatically determine prostate regions on CBCT images.« less

Hidden Markov models in automatic speech recognition

NASA Astrophysics Data System (ADS)

Wrzoskowicz, Adam

1993-11-01

This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.

Emotion and language: Valence and arousal affect word recognition

PubMed Central

Brysbaert, Marc; Warriner, Amy Beth

2014-01-01

Emotion influences most aspects of cognition and behavior, but emotional factors are conspicuously absent from current models of word recognition. The influence of emotion on word recognition has mostly been reported in prior studies on the automatic vigilance for negative stimuli, but the precise nature of this relationship is unclear. Various models of automatic vigilance have claimed that the effect of valence on response times is categorical, an inverted-U, or interactive with arousal. The present study used a sample of 12,658 words, and included many lexical and semantic control factors, to determine the precise nature of the effects of arousal and valence on word recognition. Converging empirical patterns observed in word-level and trial-level data from lexical decision and naming indicate that valence and arousal exert independent monotonic effects: Negative words are recognized more slowly than positive words, and arousing words are recognized more slowly than calming words. Valence explained about 2% of the variance in word recognition latencies, whereas the effect of arousal was smaller. Valence and arousal do not interact, but both interact with word frequency, such that valence and arousal exert larger effects among low-frequency words than among high-frequency words. These results necessitate a new model of affective word processing whereby the degree of negativity monotonically and independently predicts the speed of responding. This research also demonstrates that incorporating emotional factors, especially valence, improves the performance of models of word recognition. PMID:24490848

In Vivo Photoacoustic Imaging of Prostate Cancer Using Targeted Contrast Agent

DTIC Science & Technology

2015-09-01

detection of early stage prostate cancer, development of near infrared dyes - labeled RNA aptamer that recognizes the prostate specific cell surface protein...the application of PAI for the detection of early stage prostate cancer, development of a NIR dye - labeled RNA aptamer that recognizes the prostate...proposed to enhance the application of PAI for the detection of early stage PrCa: 1. Use of a NIR dye labeled RNA aptamer that recognizes the prostate

Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

NASA Astrophysics Data System (ADS)

Yao, Shoukui; Qin, Xiaojuan

2018-02-01

Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

The Detection of Protein via ZnO Resonant Raman Scattering Signal

NASA Astrophysics Data System (ADS)

Shan, Guiye; Yang, Guoliang; Wang, Shuang; Liu, Yichun

2008-03-01

Detecting protein with high sensitivity and specificity is essential for disease diagnostics, drug screening and other application. Semiconductor nanoparticles show better properties than organic dye molecules when used as markers for optical measurements. We used ZnO nanoparticles as markers for detecting protein in resonant Raman scattering measurements. The highly sensitive detection of proteins was achieved by an antibody-based sandwich assay. A probe for the target protein was constructed by binding the ZnO/Au nanoparticles to a primary antibody by eletrostatic interaction between Au and the antibody. A secondary antibody, which could be specifically recognized by target protein, was attached to a solid surface. The ZnO/Au-antibody probe could specifically recognize and bind to the complex of the target protein and secondary antibody. Our measurements using the resonant Raman scattering signal of ZnO nanoparticles showed good selectivity and sensitivity for the target protein.

Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition

PubMed Central

Lybarger, Kevin; Ostendorf, Mari; Yetisgen, Meliha

2017-01-01

The use of automatic speech recognition (ASR) to create clinical notes has the potential to reduce costs associated with note creation for electronic medical records, but at current system accuracy levels, post-editing by practitioners is needed to ensure note quality. Aiming to reduce the time required to edit ASR transcripts, this paper investigates novel methods for automatic detection of edit regions within the transcripts, including both putative ASR errors but also regions that are targets for cleanup or rephrasing. We create detection models using logistic regression and conditional random field models, exploring a variety of text-based features that consider the structure of clinical notes and exploit the medical context. Different medical text resources are used to improve feature extraction. Experimental results on a large corpus of practitioner-edited clinical notes show that 67% of sentence-level edits and 45% of word-level edits can be detected with a false detection rate of 15%. PMID:29854187

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

PubMed

Liu, Yan; Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lau, Steven; Lu, Weiguo; Yan, Yulong; Jiang, Steve B; Zhen, Xin; Timmerman, Robert; Nedzi, Lucien; Gu, Xuejun

2017-01-01

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.

Program Synthesizes UML Sequence Diagrams

NASA Technical Reports Server (NTRS)

Barry, Matthew R.; Osborne, Richard N.

2006-01-01

A computer program called "Rational Sequence" generates Universal Modeling Language (UML) sequence diagrams of a target Java program running on a Java virtual machine (JVM). Rational Sequence thereby performs a reverse engineering function that aids in the design documentation of the target Java program. Whereas previously, the construction of sequence diagrams was a tedious manual process, Rational Sequence generates UML sequence diagrams automatically from the running Java code.

Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Tran, Daniel Q.; Doubleday, Joshua R.; Doggett, Thomas

2013-01-01

A generic software framework analyzes data from broad coverage sweeps or general larger areas of interest. Change detection methods are used to extract subsets of directed swath areas that intersect areas of change. These areas are prioritized and allocated to targetable assets. This method is deployed in an automatic fashion, and has operated without human monitoring or intervention for sustained periods of time (months).

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

Intracranial Pressure-Guided Shunt Valve Adjustments with the Miethke Sensor Reservoir.

PubMed

Antes, Sebastian; Stadie, Axel; Müller, Simon; Linsler, Stefan; Breuskin, David; Oertel, Joachim

2018-01-01

Telemetric intracranial pressure (ICP) monitoring seems to be a promising therapy-supporting option in shunt-treated patients. Benefits become obvious when headaches are unspecific and clinical symptoms cannot be related to possible overdrainage or underdrainage. In this study, we evaluated a new telemetric device to individually adjust shunt valves according to ICP measurements. Between December 2015 and November 2016, 25 patients with suspected suboptimal shunt valve settings underwent insertion of a telemetric ICP sensor (Sensor Reservoir; Christoph Miethke, Potsdam, Germany). Over a 1-year period, a total of 183 telemetric ICP measurements and 85 shunt valve adjustments were carried out. Retrospective statistic analyses focused on valve adjustments, ICP values, and clinical outcomes. ICP-guided valve adjustments positively changed the clinical state in 18 out of 25 patients. Clinical improvement over time was associated with significant changes of the valve settings and ICP values. Interestingly, a therapeutically normalized ICP profile was not automatically associated with clinical improvement. The Sensor Reservoir is an important and valuable tool for shunt-treated patients suffering from drainage-related problems. The possibility to simultaneously recognize and solve shunt problems represents the decisive advantage. Nevertheless, measurements with the Sensor Reservoir did not allow for the determination of default valve settings or universal target ICP values. Copyright © 2017 Elsevier Inc. All rights reserved.

Detection of coal mine workings using high-resolution earth resistivity techniques. Final technical report, September 1979-September 1980

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

Peters, W.R.; Campbell, T.M.; Sturdivant, V.R.

1980-09-26

Shallow underground voids resulting from early coal mining and other resource recovery activities over the past several decades are now being recognized as a significant cause of ground subsidence problems in developing urban areas. Uncertain knowledge of abandoned coal mines also imposes potential hazards in coal excavation operations since water inundation or the release of methane gas is a principal hazard when mine excavation operations break into an abandoned mine. US Army requirements for an effective method for detecting and mapping subversive abandoned tunnels have resulted in a surface-operated automatic earth resistivity survey system with a digital computer data processingmore » system. Field tests aimed at demonstrating the system performance resulted in successful detection of tunnels having depth-to-diameter ratios up to 15 to 1. Under the sponsorship of the Bureau of Mines, a similar system was designed and constructed for use in the detection of coal mine workings. This report discusses the hardware and software aspects of the system and the application of the high-resolution earth resistivity method to the survey and mapping of abandoned coal mine workings. In the field tests reported, the targets of interest were both air- and water-filled workings.« less

Recognizing chemicals in patents: a comparative analysis.

PubMed

Habibi, Maryam; Wiegandt, David Luis; Schmedding, Florian; Leser, Ulf

2016-01-01

Recently, methods for Chemical Named Entity Recognition (NER) have gained substantial interest, driven by the need for automatically analyzing todays ever growing collections of biomedical text. Chemical NER for patents is particularly essential due to the high economic importance of pharmaceutical findings. However, NER on patents has essentially been neglected by the research community for long, mostly because of the lack of enough annotated corpora. A recent international competition specifically targeted this task, but evaluated tools only on gold standard patent abstracts instead of full patents; furthermore, results from such competitions are often difficult to extrapolate to real-life settings due to the relatively high homogeneity of training and test data. Here, we evaluate the two state-of-the-art chemical NER tools, tmChem and ChemSpot, on four different annotated patent corpora, two of which consist of full texts. We study the overall performance of the tools, compare their results at the instance level, report on high-recall and high-precision ensembles, and perform cross-corpus and intra-corpus evaluations. Our findings indicate that full patents are considerably harder to analyze than patent abstracts and clearly confirm the common wisdom that using the same text genre (patent vs. scientific) and text type (abstract vs. full text) for training and testing is a pre-requisite for achieving high quality text mining results.

Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

NASA Astrophysics Data System (ADS)

Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

2018-05-01

Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

Mining Software Usage with the Automatic Library Tracking Database (ALTD)

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

Hadri, Bilel; Fahey, Mark R

2013-01-01

Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batchmore » job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.« less

Brief Report: Attentional Cueing to Images of Social Interactions is Automatic for Neurotypical Individuals But Not Those with ASC.

PubMed

Morrisey, Marcus Neil; Reed, Catherine L; McIntosh, Daniel N; Rutherford, M D

2018-04-25

Human actions induce attentional orienting toward the target of the action. We examined the influence of action cueing in social (man throwing toward a human) and non-social (man throwing toward a tree) contexts in observers with and without autism spectrum condition (ASC). Results suggested that a social interaction enhanced the cueing effect for neurotypical participants. Participants with ASC did not benefit from non-predictive cues and were slower in social contexts, although they benefitted from reliably predictive cues. Social orienting appears to be automatic in the context of an implied social interaction for neurotypical observers, but not those with ASC. Neurotypical participants' behavior may be driven by automatic processing, while participants with ASC use an alternative, effortful strategy.

A Semantic Analysis Method for Scientific and Engineering Code

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.

1998-01-01

This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Physical and Instrumental Considerations in the Use of Lithium Phthalocyanine for Measurements of the Concentration of the Oxygen

NASA Astrophysics Data System (ADS)

Smirnov, A. I.; Norby, S. W.; Walczak, T.; Liu, K. J.; Swartz, H. M.

The use of crystals of lithium phthalocyanine (LiPc) to measure the concentration of oxygen in vivo and in vitro by electron paramagnetic resonance leads to experimental constraints due to the very narrow EPR lines that may occur (as narrow as 11-13 mG in the absence of O 2), distortions induced by the automatic frequency control system, anisotropy in the spectra (orientation-dependent linewidth is 11-17 mG in the absence of O 2), microwave power saturation, and the effect of physiological motion. These constraints can be overcome if recognized. This article highlights the experimental and theoretical basis of these properties of the EPR signal of LiPc and suggests some technical solutions. It is most important to recognize that paramagnetic species such as LiPc present problems that are not commonly encountered in EPR spectroscopy.

Computer-Interpreted Electrocardiograms: Benefits and Limitations.

PubMed

Schläpfer, Jürg; Wellens, Hein J

2017-08-29

Computerized interpretation of the electrocardiogram (CIE) was introduced to improve the correct interpretation of the electrocardiogram (ECG), facilitating health care decision making and reducing costs. Worldwide, millions of ECGs are recorded annually, with the majority automatically analyzed, followed by an immediate interpretation. Limitations in the diagnostic accuracy of CIE were soon recognized and still persist, despite ongoing improvement in ECG algorithms. Unfortunately, inexperienced physicians ordering the ECG may fail to recognize interpretation mistakes and accept the automated diagnosis without criticism. Clinical mismanagement may result, with the risk of exposing patients to useless investigations or potentially dangerous treatment. Consequently, CIE over-reading and confirmation by an experienced ECG reader are essential and are repeatedly recommended in published reports. Implementation of new ECG knowledge is also important. The current status of automated ECG interpretation is reviewed, with suggestions for improvement. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Automatic Focus Adjustment of a Microscope

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2005-01-01

AUTOFOCUS is a computer program for use in a control system that automatically adjusts the position of an instrument arm that carries a microscope equipped with an electronic camera. In the original intended application of AUTOFOCUS, the imaging microscope would be carried by an exploratory robotic vehicle on a remote planet, but AUTOFOCUS could also be adapted to similar applications on Earth. Initially control software other than AUTOFOCUS brings the microscope to a position above a target to be imaged. Then the instrument arm is moved to lower the microscope toward the target: nominally, the target is approached from a starting distance of 3 cm in 10 steps of 3 mm each. After each step, the image in the camera is subjected to a wavelet transform, which is used to evaluate the texture in the image at multiple scales to determine whether and by how much the microscope is approaching focus. A focus measure is derived from the transform and used to guide the arm to bring the microscope to the focal height. When the analysis reveals that the microscope is in focus, image data are recorded and transmitted.

Split Flow Online Solid-Phase Extraction Coupled with Inductively Coupled Plasma Mass Spectrometry System for One-Shot Data Acquisition of Quantification and Recovery Efficiency.

PubMed

Furukawa, Makoto; Takagai, Yoshitaka

2016-10-04

Online solid-phase extraction (SPE) coupled with inductively coupled plasma mass spectrometry (ICPMS) is a useful tool in automatic sequential analysis. However, it cannot simultaneously quantify the analytical targets and their recovery percentages (R%) in one-shot samples. We propose a system that simultaneously acquires both data in a single sample injection. The main flowline of the online solid-phase extraction is divided into main and split flows. The split flow line (i.e., bypass line), which circumvents the SPE column, was placed on the main flow line. Under program-controlled switching of the automatic valve, the ICPMS sequentially measures the targets in a sample before and after column preconcentration and determines the target concentrations and the R% on the SPE column. This paper describes the system development and two demonstrations to exhibit the analytical significance, i.e., the ultratrace amounts of radioactive strontium ( 90 Sr) using commercial Sr-trap resin and multielement adsorbability on the SPE column. This system is applicable to other flow analyses and detectors in online solid phase extraction.

Heliostat calibration using attached cameras and artificial targets

NASA Astrophysics Data System (ADS)

Burisch, Michael; Sanchez, Marcelino; Olarra, Aitor; Villasante, Cristobal

2016-05-01

The efficiency of the solar field greatly depends on the ability of the heliostats to precisely reflect solar radiation onto a central receiver. To control the heliostats with such a precision requires the accurate knowledge of the motion of each of them. The motion of each heliostat can be described by a set of parameters, most notably the position and axis configuration. These parameters have to be determined individually for each heliostat during a calibration process. With the ongoing development of small sized heliostats, the ability to automatically perform such a calibration becomes more and more crucial as possibly hundreds of thousands of heliostats are involved. Furthermore, efficiency becomes an important factor as small sized heliostats potentially have to be recalibrated far more often, due to the limited stability of the components. In the following we present an automatic calibration procedure using cameras attached to each heliostat which are observing different targets spread throughout the solar field. Based on a number of observations of these targets under different heliostat orientations, the parameters describing the heliostat motion can be estimated with high precision.

The research of automatic speed control algorithm based on Green CBTC

NASA Astrophysics Data System (ADS)

Lin, Ying; Xiong, Hui; Wang, Xiaoliang; Wu, Youyou; Zhang, Chuanqi

2017-06-01

Automatic speed control algorithm is one of the core technologies of train operation control system. It’s a typical multi-objective optimization control algorithm, which achieve the train speed control for timing, comfort, energy-saving and precise parking. At present, the train speed automatic control technology is widely used in metro and inter-city railways. It has been found that the automatic speed control technology can effectively reduce the driver’s intensity, and improve the operation quality. However, the current used algorithm is poor at energy-saving, even not as good as manual driving. In order to solve the problem of energy-saving, this paper proposes an automatic speed control algorithm based on Green CBTC system. Based on the Green CBTC system, the algorithm can adjust the operation status of the train to improve the efficient using rate of regenerative braking feedback energy while ensuring the timing, comfort and precise parking targets. Due to the reason, the energy-using of Green CBTC system is lower than traditional CBTC system. The simulation results show that the algorithm based on Green CBTC system can effectively reduce the energy-using due to the improvement of the using rate of regenerative braking feedback energy.

The Automaticity of Affordance of Dangerous Object.

PubMed

Zhao, Liang

2016-11-03

Objects observation automatically elicits the activation of a reach-to-grasp response specifically directed to interact with the object, which is termed affordance. Murphy, van Velzen, and de Fockert (2012) found that only when an irrelevant object receives sufficient attention, it can potentiate an action. However, it remains unclear whether the dangerous object would afford an action when it receives insufficient attention. In this study, we manipulated the perceptual load in a letter identification task. Participants were required to identify a target letter with the right or left hand while ignoring a neutral or dangerous graspable object. The target letter was presented either on its own (low perceptual load), alongside five non-target letters (high load), or alongside eight non-target letters (super high load). Under the low perceptual load, for both neutral and dangerous object, responses were faster when the action afforded by the ignored object was congruent (vs. incongruent) with the current target response (t(27) = 4.44, p < .001; t(27) = 7.99, p < .001, respectively). However, during the high perceptual load, for dangerous object, responses were slower when the action afforded by the ignored object was congruent (vs. incongruent) with the current target response (t(27) = 4.97, p < .001). There was not any effect for both neutral object and dangerous object under super high perceptual load. These results suggest the affordance of dangerous object is also sensitive to the perceptual load. An irrelevant dangerous object can't potentiate an action if it receives insufficient attention.

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.

Robust autofocus algorithm for ISAR imaging of moving targets

NASA Astrophysics Data System (ADS)

Li, Jian; Wu, Renbiao; Chen, Victor C.

2000-08-01

A robust autofocus approach, referred to as AUTOCLEAN (AUTOfocus via CLEAN), is proposed for the motion compensation in ISAR (inverse synthetic aperture radar) imaging of moving targets. It is a parametric algorithm based on a very flexible data model which takes into account arbitrary range migration and arbitrary phase errors across the synthetic aperture that may be induced by unwanted radial motion of the target as well as propagation or system instability. AUTOCLEAN can be classified as a multiple scatterer algorithm (MSA), but it differs considerably from other existing MSAs in several aspects: (1) dominant scatterers are selected automatically in the two-dimensional (2-D) image domain; (2) scatterers may not be well-isolated or very dominant; (3) phase and RCS (radar cross section) information from each selected scatterer are combined in an optimal way; (4) the troublesome phase unwrapping step is avoided. AUTOCLEAN is computationally efficient and involves only a sequence of FFTs (fast Fourier Transforms). Another good feature associated with AUTOCLEAN is that its performance can be progressively improved by assuming a larger number of dominant scatterers for the target. Hence it can be easily configured for real-time applications including, for example, ATR (automatic target recognition) of non-cooperative moving targets, and for some other applications where the image quality is of the major concern but not the computational time including, for example, for the development and maintenance of low observable aircrafts. Numerical and experimental results have shown that AUTOCLEAN is a very robust autofocus tool for ISAR imaging.

Spontaneous Facial Mimicry Is Enhanced by the Goal of Inferring Emotional States: Evidence for Moderation of "Automatic" Mimicry by Higher Cognitive Processes.

PubMed

Murata, Aiko; Saito, Hisamichi; Schug, Joanna; Ogawa, Kenji; Kameda, Tatsuya

2016-01-01

A number of studies have shown that individuals often spontaneously mimic the facial expressions of others, a tendency known as facial mimicry. This tendency has generally been considered a reflex-like "automatic" response, but several recent studies have shown that the degree of mimicry may be moderated by contextual information. However, the cognitive and motivational factors underlying the contextual moderation of facial mimicry require further empirical investigation. In this study, we present evidence that the degree to which participants spontaneously mimic a target's facial expressions depends on whether participants are motivated to infer the target's emotional state. In the first study we show that facial mimicry, assessed by facial electromyography, occurs more frequently when participants are specifically instructed to infer a target's emotional state than when given no instruction. In the second study, we replicate this effect using the Facial Action Coding System to show that participants are more likely to mimic facial expressions of emotion when they are asked to infer the target's emotional state, rather than make inferences about a physical trait unrelated to emotion. These results provide convergent evidence that the explicit goal of understanding a target's emotional state affects the degree of facial mimicry shown by the perceiver, suggesting moderation of reflex-like motor activities by higher cognitive processes.

Reliable motion detection of small targets in video with low signal-to-clutter ratios

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

Nichols, S.A.; Naylor, R.B.

1995-07-01

Studies show that vigilance decreases rapidly after several minutes when human operators are required to search live video for infrequent intrusion detections. Therefore, there is a need for systems which can automatically detect targets in live video and reserve the operator`s attention for assessment only. Thus far, automated systems have not simultaneously provided adequate detection sensitivity, false alarm suppression, and ease of setup when used in external, unconstrained environments. This unsatisfactory performance can be exacerbated by poor video imagery with low contrast, high noise, dynamic clutter, image misregistration, and/or the presence of small, slow, or erratically moving targets. This papermore » describes a highly adaptive video motion detection and tracking algorithm which has been developed as part of Sandia`s Advanced Exterior Sensor (AES) program. The AES is a wide-area detection and assessment system for use in unconstrained exterior security applications. The AES detection and tracking algorithm provides good performance under stressing data and environmental conditions. Features of the algorithm include: reliable detection with negligible false alarm rate of variable velocity targets having low signal-to-clutter ratios; reliable tracking of targets that exhibit motion that is non-inertial, i.e., varies in direction and velocity; automatic adaptation to both infrared and visible imagery with variable quality; and suppression of false alarms caused by sensor flaws and/or cutouts.« less

ATR applications of minimax entropy models of texture and shape

NASA Astrophysics Data System (ADS)

Zhu, Song-Chun; Yuille, Alan L.; Lanterman, Aaron D.

2001-10-01

Concepts from information theory have recently found favor in both the mainstream computer vision community and the military automatic target recognition community. In the computer vision literature, the principles of minimax entropy learning theory have been used to generate rich probabilitistic models of texture and shape. In addition, the method of types and large deviation theory has permitted the difficulty of various texture and shape recognition tasks to be characterized by 'order parameters' that determine how fundamentally vexing a task is, independent of the particular algorithm used. These information-theoretic techniques have been demonstrated using traditional visual imagery in applications such as simulating cheetah skin textures and such as finding roads in aerial imagery. We discuss their application to problems in the specific application domain of automatic target recognition using infrared imagery. We also review recent theoretical and algorithmic developments which permit learning minimax entropy texture models for infrared textures in reasonable timeframes.

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.

PubMed

Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu

2017-07-18

Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.

User acceptance of intelligent avionics: A study of automatic-aided target recognition

NASA Technical Reports Server (NTRS)

Becker, Curtis A.; Hayes, Brian C.; Gorman, Patrick C.

1991-01-01

User acceptance of new support systems typically was evaluated after the systems were specified, designed, and built. The current study attempts to assess user acceptance of an Automatic-Aided Target Recognition (ATR) system using an emulation of such a proposed system. The detection accuracy and false alarm level of the ATR system were varied systematically, and subjects rated the tactical value of systems exhibiting different performance levels. Both detection accuracy and false alarm level affected the subjects' ratings. The data from two experiments suggest a cut-off point in ATR performance below which the subjects saw little tactical value in the system. An ATR system seems to have obvious tactical value only if it functions at a correct detection rate of 0.7 or better with a false alarm level of 0.167 false alarms per square degree or fewer.

Results from Automated Cloud and Dust Devil Detection Onboard the MER

NASA Technical Reports Server (NTRS)

Chien, Steve; Castano, Rebecca; Bornstein, Benjamin; Fukunaga, Alex; Castano, Andres; Biesiadecki, Jeffrey; Greeley, Ron; Whelley, Patrick; Lemmon, Mark

2008-01-01

We describe a new capability to automatically detect dust devils and clouds in imagery onboard rovers, enabling downlink of just the images with the targets or only portions of the images containing the targets. Previously, the MER rovers conducted campaigns to image dust devils and clouds by commanding a set of images be collected at fixed times and downloading the entire image set. By increasing the efficiency of the campaigns, more campaigns can be executed. Software for these new capabilities was developed, tested, integrated, uploaded, and operationally checked out on both rovers as part of the R9.2 software upgrade. In April 2007 on Sol 1147 a dust devil was automatically detected onboard the Spirit rover for the first time. We discuss the operational usage of the capability and present initial dust devil results showing how this preliminary application has demonstrated the feasibility and potential benefits of the approach.

Do perceived context pictures automatically activate their phonological code?

PubMed

Jescheniak, Jörg D; Oppermann, Frank; Hantsch, Ansgar; Wagner, Valentin; Mädebach, Andreas; Schriefers, Herbert

2009-01-01

Morsella and Miozzo (Morsella, E., & Miozzo, M. (2002). Evidence for a cascade model of lexical access in speech production. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 555-563) have reported that the to-be-ignored context pictures become phonologically activated when participants name a target picture, and took this finding as support for cascaded models of lexical retrieval in speech production. In a replication and extension of their experiment in German, we failed to obtain priming effects from context pictures phonologically related to a to-be-named target picture. By contrast, corresponding context words (i.e., the names of the respective pictures) and the same context pictures, when used in an identity condition, did reliably facilitate the naming process. This pattern calls into question the generality of the claim advanced by Morsella and Miozzo that perceptual processing of pictures in the context of a naming task automatically leads to the activation of corresponding lexical-phonological codes.

Deep transfer learning for automatic target classification: MWIR to LWIR

NASA Astrophysics Data System (ADS)

Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

2016-05-01

Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras.

PubMed

Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki

2016-06-24

Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system.

A Pressure Plate-Based Method for the Automatic Assessment of Foot Strike Patterns During Running.

PubMed

Santuz, Alessandro; Ekizos, Antonis; Arampatzis, Adamantios

2016-05-01

The foot strike pattern (FSP, description of how the foot touches the ground at impact) is recognized to be a predictor of both performance and injury risk. The objective of the current investigation was to validate an original foot strike pattern assessment technique based on the numerical analysis of foot pressure distribution. We analyzed the strike patterns during running of 145 healthy men and women (85 male, 60 female). The participants ran on a treadmill with integrated pressure plate at three different speeds: preferred (shod and barefoot 2.8 ± 0.4 m/s), faster (shod 3.5 ± 0.6 m/s) and slower (shod 2.3 ± 0.3 m/s). A custom-designed algorithm allowed the automatic footprint recognition and FSP evaluation. Incomplete footprints were simultaneously identified and corrected from the software itself. The widely used technique of analyzing high-speed video recordings was checked for its reliability and has been used to validate the numerical technique. The automatic numerical approach showed a good conformity with the reference video-based technique (ICC = 0.93, p < 0.01). The great improvement in data throughput and the increased completeness of results allow the use of this software as a powerful feedback tool in a simple experimental setup.

Anatomical entity mention recognition at literature scale

PubMed Central

Pyysalo, Sampo; Ananiadou, Sophia

2014-01-01

Motivation: Anatomical entities ranging from subcellular structures to organ systems are central to biomedical science, and mentions of these entities are essential to understanding the scientific literature. Despite extensive efforts to automatically analyze various aspects of biomedical text, there have been only few studies focusing on anatomical entities, and no dedicated methods for learning to automatically recognize anatomical entity mentions in free-form text have been introduced. Results: We present AnatomyTagger, a machine learning-based system for anatomical entity mention recognition. The system incorporates a broad array of approaches proposed to benefit tagging, including the use of Unified Medical Language System (UMLS)- and Open Biomedical Ontologies (OBO)-based lexical resources, word representations induced from unlabeled text, statistical truecasing and non-local features. We train and evaluate the system on a newly introduced corpus that substantially extends on previously available resources, and apply the resulting tagger to automatically annotate the entire open access scientific domain literature. The resulting analyses have been applied to extend services provided by the Europe PubMed Central literature database. Availability and implementation: All tools and resources introduced in this work are available from http://nactem.ac.uk/anatomytagger. Contact: sophia.ananiadou@manchester.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:24162468

Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki

2016-01-01

Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system. PMID:27347961

The BRAMS Zoo, a citizen science project

NASA Astrophysics Data System (ADS)

Calders, S.

2015-01-01

Currently, the BRAMS network comprises around 30 receiving stations, and each station collects 24 hours of data per day. With such a large number of raw data, automatic detection of meteor echoes is mandatory. Several algorithms have been developed, using different techniques. (They are discussed in the Proceedings of IMC 2014.) This task is complicated because of the presence of parasitic signals (mostly airplane echoes) on one hand and the fact that some meteor echoes (overdense) exhibit complex shapes that are hard to recognize on the other hand. Currently, none of the algorithms can perfectly mimic the human eye which stays the best detector. Therefore we plan to collaborate with Citizen Science in order to create a "BRAMS zoo". The idea is to ask their very large community of users to draw boxes around meteor echoes in spectrograms. The results will be used to assess the accuracy of the automatic detection algorithms on a large data set. We will focus on a few selected meteor showers which are always more fascinating for the large public than the sporadic background. Moreover, during meteor showers, many more complex overdense echoes are observed for which current automatic detection methods might fail. Finally, the dataset of manually detected meteors can also be useful e.g. for IMCCE to study the dynamic evolution of cometary dust.

Arraycount, an algorithm for automatic cell counting in microwell arrays.

PubMed

Kachouie, Nezamoddin; Kang, Lifeng; Khademhosseini, Ali

2009-09-01

Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of approximately 1-2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5-13%.

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

Predicting Epileptic Seizures in Advance

PubMed Central

Moghim, Negin; Corne, David W.

2014-01-01

Epilepsy is the second most common neurological disorder, affecting 0.6–0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs) are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG) data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling), is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity) of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance. PMID:24911316

Protein-targeted corona phase molecular recognition

PubMed Central

Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

2016-01-01

Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

Hierarchically Structured Non-Intrusive Sign Language Recognition. Chapter 2

NASA Technical Reports Server (NTRS)

Zieren, Jorg; Zieren, Jorg; Kraiss, Karl-Friedrich

2007-01-01

This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.

Implantable Heart Aid

NASA Technical Reports Server (NTRS)

1980-01-01

Medrad utilized NASA's Apollo technology to develop a new device called the AID implantable automatic pulse generator which monitors the heart continuously, recognizes the onset of ventricular fibrillation and delivers a corrective electrical shock. AID pulse generator is, in effect, a miniaturized version of the defibrillator used by emergency squads and hospitals to restore rhythmic heartbeat after fibrillation, but has the unique advantage of being permanently available to the patient at risk. Once implanted, it needs no specially trained personnel or additional equipment. AID system consists of a microcomputer, a power source and two electrodes which sense heart activity.

SIGPROC: Pulsar Signal Processing Programs

NASA Astrophysics Data System (ADS)

Lorimer, D. R.

2011-07-01

SIGPROC is a package designed to standardize the initial analysis of the many types of fast-sampled pulsar data. Currently recognized machines are the Wide Band Arecibo Pulsar Processor (WAPP), the Penn State Pulsar Machine (PSPM), the Arecibo Observatory Fourier Transform Machine (AOFTM), the Berkeley Pulsar Processors (BPP), the Parkes/Jodrell 1-bit filterbanks (SCAMP) and the filterbank at the Ooty radio telescope (OOTY). The SIGPROC tools should help users look at their data quickly, without the need to write (yet) another routine to read data or worry about big/little endian compatibility (byte swapping is handled automatically).

[Application of iodine metabolism analysis methods in thyroid diseases].

PubMed

Han, Jian-hua; Qiu, Ling

2013-08-01

The main physiological role of iodine in the body is to synthesize thyroid hormone. Both iodine deficiency and iodine excess can lead to severe thyroid diseases. While its role in thyroid diseases has increasingly been recognized, few relevant platforms and techniques for iodine detection have been available in China. This paper summarizes the advantages and disadvantages of currently iodine detection methods including direct titration, arsenic cerium catalytic spectrophotometry, chromatography with pulsed amperometry, colorimetry based on automatic biochemistry, inductively coupled plasma mass spectrometry, so as to optimize the iodine nutrition for patients with thyroid diseases.

Space Derived Health Aids (AID, Heart Monitor)

NASA Technical Reports Server (NTRS)

1981-01-01

CPI's spinoff from miniaturized pace circuitry is the new heart-assist device, the AID implantable automatic pulse generator. AID pulse generator monitors the heart continuously, recognizes onset of fibrillation, then administers a corrective electrical shock. A mini- computer, a power source, and two electrodes which sense heart activity are included in the unit. An associated system was also developed. It includes an external recorder to be worn by AID patients and a physician's console to display the data stored by the recorder. System provides a record of fibrillation occurrences and the ensuing defibrillation.

Automatic and deliberate affective associations with sexual stimuli in women with lifelong vaginismus before and after therapist-aided exposure treatment.

PubMed

Melles, Reinhilde J; ter Kuile, Moniek M; Dewitte, Marieke; van Lankveld, Jacques J D M; Brauer, Marieke; de Jong, Peter J

2014-03-01

The intense fear response to vaginal penetration in women with lifelong vaginismus, who have never been able to experience coitus, may reflect negative automatic and deliberate appraisals of vaginal penetration stimuli which might be modified by exposure treatment. The aim of this study is to examine whether (i) sexual stimuli elicit relatively strong automatic and deliberate threat associations in women with vaginismus, as well as relatively negative automatic and deliberate global affective associations, compared with symptom-free women; and (ii) these automatic and more deliberate attitudes can be modified by therapist-aided exposure treatment. A single target Implicit Association Test (st-IAT) was used to index automatic threat associations, and an Affective Simon Task (AST) to index global automatic affective associations. Participants were women with lifelong vaginismus (N = 68) and women without sexual problems (N = 70). The vaginismus group was randomly allocated to treatment (n = 34) and a waiting list control condition (n = 34). Indices of automatic threat were obtained by the st-IAT and automatic global affective associations by the AST, visual analogue scales (VAS) were used to assess deliberate appraisals of the sexual pictures (fear and global positive affect). More deliberate fear and less global positive affective associations with sexual stimuli were found in women with vaginismus. Following therapist-aided exposure treatment, the strength of fear was strongly reduced, whereas global positive affective associations were strengthened. Automatic associations did not differ between women with and without vaginismus and did not change following treatment. Relatively stronger negative (threat or global affect) associations with sexual stimuli in vaginismus appeared restricted to the deliberate level. Therapist-aided exposure treatment was effective in reducing subjective fear of sexual penetration stimuli and led to more global positive affective associations with sexual stimuli. The impact of exposure might be further improved by strengthening the association between vaginal penetration and positive affect (e.g., by using counter-conditioning techniques). © 2013 International Society for Sexual Medicine.

Recognition of Glioma Stem Cells by Genetically Modified T Cells Targeting EGFRvIII and Development of Adoptive Cell Therapy for Glioma

PubMed Central

Johnson, Laura A.; Davis, Jeremy L.; Zheng, Zhili; Woolard, Kevin D.; Reap, Elizabeth A.; Feldman, Steven A.; Chinnasamy, Nachimuthu; Kuan, Chien-Tsun; Song, Hua; Zhang, Wei; Fine, Howard A.; Rosenberg, Steven A.

2012-01-01

Abstract No curative treatment exists for glioblastoma, with median survival times of less than 2 years from diagnosis. As an approach to develop immune-based therapies for glioblastoma, we sought to target antigens expressed in glioma stem cells (GSCs). GSCs have multiple properties that make them significantly more representative of glioma tumors than established glioma cell lines. Epidermal growth factor receptor variant III (EGFRvIII) is the result of a novel tumor-specific gene rearrangement that produces a unique protein expressed in approximately 30% of gliomas, and is an ideal target for immunotherapy. Using PCR primers spanning the EGFRvIII-specific deletion, we found that this tumor-specific gene is expressed in three of three GCS lines. Based on the sequence information of seven EGFRvIII-specific monoclonal antibodies (mAbs), we assembled chimeric antigen receptors (CARs) and evaluated the ability of CAR-engineered T cells to recognize EGFRvIII. Three of these anti-EGFRvIII CAR-engineered T cells produced the effector cytokine, interferon-γ, and lysed antigen-expressing target cells. We concentrated development on a CAR produced from human mAb 139, which specifically recognized GSC lines and glioma cell lines expressing mutant EGFRvIII, but not wild-type EGFR and did not recognize any normal human cell tested. Using the 139-based CAR, T cells from glioblastoma patients could be genetically engineered to recognize EGFRvIII-expressing tumors and could be expanded ex vivo to large numbers, and maintained their antitumor activity. Based on these observations, a γ-retroviral vector expressing this EGFRvIII CAR was produced for clinical application. PMID:22780919

Recognition of glioma stem cells by genetically modified T cells targeting EGFRvIII and development of adoptive cell therapy for glioma.

PubMed

Morgan, Richard A; Johnson, Laura A; Davis, Jeremy L; Zheng, Zhili; Woolard, Kevin D; Reap, Elizabeth A; Feldman, Steven A; Chinnasamy, Nachimuthu; Kuan, Chien-Tsun; Song, Hua; Zhang, Wei; Fine, Howard A; Rosenberg, Steven A

2012-10-01

No curative treatment exists for glioblastoma, with median survival times of less than 2 years from diagnosis. As an approach to develop immune-based therapies for glioblastoma, we sought to target antigens expressed in glioma stem cells (GSCs). GSCs have multiple properties that make them significantly more representative of glioma tumors than established glioma cell lines. Epidermal growth factor receptor variant III (EGFRvIII) is the result of a novel tumor-specific gene rearrangement that produces a unique protein expressed in approximately 30% of gliomas, and is an ideal target for immunotherapy. Using PCR primers spanning the EGFRvIII-specific deletion, we found that this tumor-specific gene is expressed in three of three GCS lines. Based on the sequence information of seven EGFRvIII-specific monoclonal antibodies (mAbs), we assembled chimeric antigen receptors (CARs) and evaluated the ability of CAR-engineered T cells to recognize EGFRvIII. Three of these anti-EGFRvIII CAR-engineered T cells produced the effector cytokine, interferon-γ, and lysed antigen-expressing target cells. We concentrated development on a CAR produced from human mAb 139, which specifically recognized GSC lines and glioma cell lines expressing mutant EGFRvIII, but not wild-type EGFR and did not recognize any normal human cell tested. Using the 139-based CAR, T cells from glioblastoma patients could be genetically engineered to recognize EGFRvIII-expressing tumors and could be expanded ex vivo to large numbers, and maintained their antitumor activity. Based on these observations, a γ-retroviral vector expressing this EGFRvIII CAR was produced for clinical application.

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.

Pattern recognition and classification of vibrational spectra by artificial neural networks

NASA Astrophysics Data System (ADS)

Yang, Husheng

1999-10-01

A drawback of current open-path Fourier transform infrared (OP/FT-IR) systems is that they need a human expert to determine those compounds that may be quantified from a given spectrum. In this study, three types of artificial neural networks were used to alleviate this problem. Firstly, multi-layer feed-forward neural networks were used to automatically recognize compounds in an OP/FT-IR spectrum. Each neural network was trained to recognize one compound in the presence of up to ten interferents in an OP/FT-IR spectrum. The networks were successfully used to recognize five alcohols and two chlorinated compounds in field-measured controlled-release OP/FT-IR spectra of mixtures of these compounds. It has also been demonstrated that a neural network could correctly identify a spectrum in the presence of an interferent that was not included in the training set and could also reject interferents it has not seen before. Secondly, the possibility of using one- and two- dimensional Kohonen self-organizing maps (SOMs) to recognize similarities in low-resolution vapor-phase infrared spectra without any additional information has been investigated. Both full-range reference spectra and open-path window reference spectra were used to train the networks and the trained networks were then used to classify the reference spectra into several groups. The results showed that the SOMs obtained from the two different training sets were quite different, and it is more appropriate to use the second SOM in OP/FT-IR spectrometry. Thirdly, vapor-phase FT-IR reference spectra of five alcohols along with four baseline spectra were encoded as prototype vectors for a Hopfield network. Inclusion of the baseline spectra allowed the network to classify spectra as unknowns, when the reference spectra of these compounds were not stored as prototype vectors in the network. The network could identify each of the 5 alcohols correctly even in the presence of noise and interfering compounds. Finally, one- and two-dimensional Kohonen SOMs were also successfully used for the unsupervised differentiation of the Fourier transform Raman spectra of hardwoods from softwoods. A semi-quantitative method that is based on the Euclidean distances of the weight matrix has been developed to assist the automatic clustering of the neurons in a two-dimensional SOM.

Automated low-thrust guidance for the orbital maneuvering vehicle

NASA Technical Reports Server (NTRS)

Rose, Richard E.; Schmeichel, Harry; Shortwell, Charles P.; Werner, Ronald A.

1988-01-01

This paper describes the highly autonomous OMV Guidance Navigation and Control system. Emphasis is placed on a key feature of the design, the low thrust guidance algorithm. The two guidance modes, orbit change guidance and rendezvous guidance, are discussed in detail. It is shown how OMV will automatically transfer from its initial orbit to an arbitrary target orbit and reach a specified rendezvous position relative to the target vehicle.

Automatic generation of endocardial surface meshes with 1-to-1 correspondence from cine-MR images

NASA Astrophysics Data System (ADS)

Su, Yi; Teo, S.-K.; Lim, C. W.; Zhong, L.; Tan, R. S.

2015-03-01

In this work, we develop an automatic method to generate a set of 4D 1-to-1 corresponding surface meshes of the left ventricle (LV) endocardial surface which are motion registered over the whole cardiac cycle. These 4D meshes have 1- to-1 point correspondence over the entire set, and is suitable for advanced computational processing, such as shape analysis, motion analysis and finite element modelling. The inputs to the method are the set of 3D LV endocardial surface meshes of the different frames/phases of the cardiac cycle. Each of these meshes is reconstructed independently from border-delineated MR images and they have no correspondence in terms of number of vertices/points and mesh connectivity. To generate point correspondence, the first frame of the LV mesh model is used as a template to be matched to the shape of the meshes in the subsequent phases. There are two stages in the mesh correspondence process: (1) a coarse matching phase, and (2) a fine matching phase. In the coarse matching phase, an initial rough matching between the template and the target is achieved using a radial basis function (RBF) morphing process. The feature points on the template and target meshes are automatically identified using a 16-segment nomenclature of the LV. In the fine matching phase, a progressive mesh projection process is used to conform the rough estimate to fit the exact shape of the target. In addition, an optimization-based smoothing process is used to achieve superior mesh quality and continuous point motion.

When Synchronizing to Rhythms Is Not a Good Thing: Modulations of Preparatory and Post-Target Neural Activity When Shifting Attention Away from On-Beat Times of a Distracting Rhythm.

PubMed

Breska, Assaf; Deouell, Leon Y

2016-07-06

Environmental rhythms potently drive predictive resource allocation in time, typically leading to perceptual and motor benefits for on-beat, relative to off-beat, times, even if the rhythmic stream is not intentionally used. In two human EEG experiments, we investigated the behavioral and electrophysiological expressions of using rhythms to direct resources away from on-beat times. This allowed us to distinguish goal-directed attention from the automatic capture of attention by rhythms. The following three conditions were compared: (1) a rhythmic stream with targets appearing frequently at a fixed off-beat position; (2) a rhythmic stream with targets appearing frequently at on-beat times; and (3) a nonrhythmic stream with matched target intervals. Shifting resources away from on-beat times was expressed in the slowing of responses to on-beat targets, but not in the facilitation of off-beat targets. The shifting of resources was accompanied by anticipatory adjustment of the contingent negative variation (CNV) buildup toward the expected off-beat time. In the second experiment, off-beat times were jittered, resulting in a similar CNV adjustment and also in preparatory amplitude reduction of beta-band activity. Thus, the CNV and beta activity track the relevance of time points and not the rhythm, given sufficient incentive. Furthermore, the effects of task relevance (appearing in a task-relevant vs irrelevant time) and rhythm (appearing on beat vs off beat) had additive behavioral effects and also dissociable neural manifestations in target-evoked activity: rhythm affected the target response as early as the P1 component, while relevance affected only the later N2 and P3. Thus, these two factors operate by distinct mechanisms. Rhythmic streams are widespread in our environment, and are typically conceptualized as automatic, bottom-up resource attractors to on-beat times-preparatory neural activity peaks at rhythm-on-beat times and behavioral benefits are seen to on-beat compared with off-beat targets. We show that this behavioral benefit is reversed when targets are more frequent at off-beat compared with on-beat times, and that preparatory neural activity, previously thought to be driven by the rhythm to on-beat times, is adjusted toward off-beat times. Furthermore, the effect of this relevance-based shifting on target-evoked brain activity was dissociable from the automatic effect of rhythms. Thus, rhythms can act as cues for flexible resource allocation according to the goal relevance of each time point, instead of being obligatory resource attractors. Copyright © 2016 the authors 0270-6474/16/367154-13$15.00/0.