Sample records for automatic target recognizer

  1. Unification of automatic target tracking and automatic target recognition

    Schachter, Bruce J.


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

  2. Digital-Electronic/Optical Apparatus Would Recognize Targets

    Scholl, Marija S.


    Proposed automatic target-recognition apparatus consists mostly of digital-electronic/optical cross-correlator that processes infrared images of targets. Infrared images of unknown targets correlated quickly with images of known targets. Apparatus incorporates some features of correlator described in "Prototype Optical Correlator for Robotic Vision System" (NPO-18451), and some of correlator described in "Compact Optical Correlator" (NPO-18473). Useful in robotic system; to recognize and track infrared-emitting, moving objects as variously shaped hot workpieces on conveyor belt.

  3. Physics of Automatic Target Recognition

    Sadjadi, Firooz


    Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

  4. The Automatic Measurement of Targets

    Höhle, Joachim


    The automatic measurement of targets is demonstrated by means of a theoretical example and by an interactive measuring program for real imagery from a réseau camera. The used strategy is a combination of two methods: the maximum correlation coefficient and the correlation in the subpixel range. F...... interactive software is also part of a computer-assisted learning program on digital photogrammetry....

  5. Automatic grunt detector and recognizer for Atlantic cod (Gadus morhua).

    Urazghildiiev, Ildar R; Van Parijs, Sofie M


    Northwest Atlantic cod (Gadus morhua) have been heavily overfished in recent years and have not yet recovered. Passive acoustic technology offers a new approach to identify the spatial location of spawning fish, as well as their seasonal and long term persistence in an area. To date, the lack of a species-specific detector has made searching for Atlantic cod grunts in large amounts of passive acoustic data cumbersome. To address this problem, an automatic grunt detection and recognition algorithm that processes yearlong passive acoustic data recordings was designed. The proposed technique is a two-stage hypothesis testing algorithm that includes detecting and recognizing all grunt-like sounds. Test results demonstrated that the algorithm provided a detection probability of 0.93 for grunts with a signal-to-noise ratio (SNR) higher than 10 dB, and a detection probability of 0.8 for grunts with the SNR ranging from 3 to 10 dB. This detector is being used to identify cod in current and historical data from U.S. waters. Its use has significantly reduced the time required to find and validate the presence of cod grunts. PMID:27250148

  6. Automatic recognizing of vocal fold disorders from glottis images.

    Huang, Chang-Chiun; Leu, Yi-Shing; Kuo, Chung-Feng Jeffrey; Chu, Wen-Lin; Chu, Yueng-Hsiang; Wu, Han-Cheng


    The laryngeal video stroboscope is an important instrument to test glottal diseases and read vocal fold images and voice quality for physician clinical diagnosis. This study is aimed to develop a medical system with functionality of automatic intelligent recognition of dynamic images. The static images of glottis opening to the largest extent and closing to the smallest extent were screened automatically using color space transformation and image preprocessing. The glottal area was also quantized. As the tongue base movements affected the position of laryngoscope and saliva would result in unclear images, this study used the gray scale adaptive entropy value to set the threshold in order to establish an elimination system. The proposed system can improve the effect of automatically captured images of glottis and achieve an accuracy rate of 96%. In addition, the glottal area and area segmentation threshold were calculated effectively. The glottis area segmentation was corrected, and the glottal area waveform pattern was drawn automatically to assist in vocal fold diagnosis. When developing the intelligent recognition system for vocal fold disorders, this study analyzed the characteristic values of four vocal fold patterns, namely, normal vocal fold, vocal fold paralysis, vocal fold polyp, and vocal fold cyst. It also used the support vector machine classifier to identify vocal fold disorders and achieved an identification accuracy rate of 98.75%. The results can serve as a very valuable reference for diagnosis. PMID:25313026

  7. Automatic target recognition apparatus and method

    Baumgart, Chris W. (Santa Fe, NM); Ciarcia, Christopher A. (Los Alamos, NM)


    An automatic target recognition apparatus (10) is provided, having a video camera/digitizer (12) for producing a digitized image signal (20) representing an image containing therein objects which objects are to be recognized if they meet predefined criteria. The digitized image signal (20) is processed within a video analysis subroutine (22) residing in a computer (14) in a plurality of parallel analysis chains such that the objects are presumed to be lighter in shading than the background in the image in three of the chains and further such that the objects are presumed to be darker than the background in the other three chains. In two of the chains the objects are defined by surface texture analysis using texture filter operations. In another two of the chains the objects are defined by background subtraction operations. In yet another two of the chains the objects are defined by edge enhancement processes. In each of the analysis chains a calculation operation independently determines an error factor relating to the probability that the objects are of the type which should be recognized, and a probability calculation operation combines the results of the analysis chains.

  8. 面向纸质胸环靶的自动识别报靶系统研究%Automatic Recognization Target-reading System for Chest Silhouette of Paper

    刘瑞香; 刘天时; 王洪伟


    为了克服在靶场射击训练中人工报靶消耗大量的人力和时间的同时还存在诸多隐患,如误报和谎报等,本文设计了一套硬件配置相对简单、性能稳定可靠、判靶精准快速的面向纸质胸环靶的自动识别报靶系统。该系统结合嵌入式技术、图像处理技术、有线以及无线网络传输技术,实现快速检测靶面信息以及弹孔坐标。在图像处理的基础上,对图像使用区域特征消除法对干扰背景进行了消除,同时采用灰度双向肖波投影确定靶心位置,提取出靶面图像的所有有效特征信息。通过嵌入式终端、wifi通信以及网络传输等完成了整个系统的搭建。本系统具有高效、快速和判靶精准等特点。%This paper proposes an automatic recognition target-scoring system for chest bitmap with simple hardware requirement, stable and reliable performance, precise and fast scoring in order to overcome the problems that the artificial counting consumes a lot of manpower, time and also there are many dangers in shooting training, such as the misinformation and the misrepresentation. Combining with the embedded technology, image processing technology, wired and wireless network transmission technology, the system implements the detecting of target surface information rapidly and the coordinates of bullet holes. The regional feature re⁃moving method is employed to eliminate background interference, and the grey two-direction clipping projection is also taken to de⁃termine bull's eye position based on the original picture processing. Finally, all characteristic information of the image is extracted effectively. The system is built through the embedded terminal, WiFi communication and network transmission. It has the charac⁃teristics of efficient, fast and good scoring precision.

  9. Automatic Recognization Target-reading System for Chest Silhouette of Paper%面向纸质胸环靶的自动识别报靶系统研究

    刘瑞香; 刘天时; 王洪伟


    为了克服在靶场射击训练中人工报靶消耗大量的人力和时间的同时还存在诸多隐患,如误报和谎报等,本文设计了一套硬件配置相对简单、性能稳定可靠、判靶精准快速的面向纸质胸环靶的自动识别报靶系统。该系统结合嵌入式技术、图像处理技术、有线以及无线网络传输技术,实现快速检测靶面信息以及弹孔坐标。在图像处理的基础上,对图像使用区域特征消除法对干扰背景进行了消除,同时采用灰度双向肖波投影确定靶心位置,提取出靶面图像的所有有效特征信息。通过嵌入式终端、wifi通信以及网络传输等完成了整个系统的搭建。本系统具有高效、快速和判靶精准等特点。%This paper proposes an automatic recognition target-scoring system for chest bitmap with simple hardware requirement, stable and reliable performance, precise and fast scoring in order to overcome the problems that the artificial counting consumes a lot of manpower, time and also there are many dangers in shooting training, such as the misinformation and the misrepresentation. Combining with the embedded technology, image processing technology, wired and wireless network transmission technology, the system implements the detecting of target surface information rapidly and the coordinates of bullet holes. The regional feature re⁃moving method is employed to eliminate background interference, and the grey two-direction clipping projection is also taken to de⁃termine bull's eye position based on the original picture processing. Finally, all characteristic information of the image is extracted effectively. The system is built through the embedded terminal, WiFi communication and network transmission. It has the charac⁃teristics of efficient, fast and good scoring precision.

  10. Self-assessing target with automatic feedback

    Larkin, Stephen W.; Kramer, Robert L.


    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.

  11. Automatic target tracking in FLIR image sequences

    Bal, Abdullah; Alam, Mohammad S.


    Moving target tracking is a challenging task and is increasingly becoming important for various applications. In this paper, we have presented target detection and tracking algorithm based on target intensity feature relative to surrounding background, and shape information of target. Proposed automatic target tracking algorithm includes two techniques: intensity variation function (IVF) and template modeling (TM). The intensity variation function is formulated by using target intensity feature while template modeling is based on target shape information. The IVF technique produces the maximum peak value whereas the reference target intensity variation is similar to the candidate target intensity variation. When IVF technique fails, due to background clutter, non-target object or other artifacts, the second technique, template modeling, is triggered by control module. By evaluating the outputs from the IVF and TM techniques, the tracker determines the real coordinates of the target. Performance of the proposed ATT is tested using real life forward-looking infrared (FLIR) image sequences taken from an airborne, moving platform.

  12. Robust automatic target recognition in FLIR imagery

    Soyman, Yusuf


    In this paper, a robust automatic target recognition algorithm in FLIR imagery is proposed. Target is first segmented out from the background using wavelet transform. Segmentation process is accomplished by parametric Gabor wavelet transformation. Invariant features that belong to the target, which is segmented out from the background, are then extracted via moments. Higher-order moments, while providing better quality for identifying the image, are more sensitive to noise. A trade-off study is then performed on a few moments that provide effective performance. Bayes method is used for classification, using Mahalanobis distance as the Bayes' classifier. Results are assessed based on false alarm rates. The proposed method is shown to be robust against rotations, translations and scale effects. Moreover, it is shown to effectively perform under low-contrast objects in FLIR images. Performance comparisons are also performed on both GPU and CPU. Results indicate that GPU has superior performance over CPU.

  13. Research on Automatic Target Tracking Based on PTZ System

    Ni Zhang


    Full Text Available This paper studies an algorithm of automatic target tracking based on PTZ system. Select the tracking target and set up the target motion trajectory in the video screen. Along the motion trajectory, the system controls the PTZ rotation automatically to track the target real-timely. At the same time, it adjusts the zoom to enlarge or reduce to make sure the target can display on the video screen center clearly at the suitable size. By testing on groups of video, verify the effectiveness of the automatic target tracking algorithm.

  14. Automatic target extraction in complicated background for camera calibration

    Guo, Xichao; Wang, Cheng; Wen, Chenglu; Cheng, Ming


    In order to perform high precise calibration of camera in complex background, a novel design of planar composite target and the corresponding automatic extraction algorithm are presented. Unlike other commonly used target designs, the proposed target contains the information of feature point coordinate and feature point serial number simultaneously. Then based on the original target, templates are prepared by three geometric transformations and used as the input of template matching based on shape context. Finally, parity check and region growing methods are used to extract the target as final result. The experimental results show that the proposed method for automatic extraction and recognition of the proposed target is effective, accurate and reliable.

  15. Automatic speech recognizer based on the Spanish spoken in Valdivia, Chile

    Sanchez, Maria L.; Poblete, Victor H.; Sommerhoff, Jorge


    The performance of an automatic speech recognizer is affected by training process (dependent on or independent of the speaker) and the size of the vocabulary. The language used in this study was the Spanish spoken in the city of Valdivia, Chile. A representative sample of 14 students and six professionals all natives of Valdivia (ten women and ten men) were used to complete the study. The sample ranged in age between 20 and 30 years old. Two systems were programmed based on the classical principles: digitalizing, end point detection, linear prediction coding, cepstral coefficients, dynamic time warping, and a final decision stage with a previous step of training: (i) one dependent speaker (15 words: five colors and ten numbers), (ii) one independent speaker (30 words: ten verbs, ten nouns, and ten adjectives). A simple didactical application, with options to choose colors, numbers and drawings of the verbs, nouns and adjectives, was designed to be used with a personal computer. In both programs, the tests carried out showed a tendency towards errors in short words with monosyllables like ``flor,'' and ``sol.'' The best results were obtained in words with three syllables like ``disparar'' and ``mojado.'' [Work supported by Proyecto DID UACh N S-200278.

  16. Automatic targeting of plasma spray gun

    A means for monitoring the material portion in the flame of a plasma spray gun during spraying operations is described. 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

  17. Automatic targeting of plasma spray gun

    Abbatiello, Leonard A.; Neal, Richard E.


    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.

  18. Automatic target validation based on neuroscientific literature mining for tractography

    Xavier Vasques; Renaud Richardet; Etienne Pralong; LAURA CIF


    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 t...

  19. Automatic Target Detection by Optimal Morphological Filters

    YU Nong(余农); WU Hao(吴昊); WU ChangYong(吴常泳); LI YuShu(李予蜀)


    It is widely accepted that the design of morphological filters, which are optimal in some sense, is a difficult task. In this paper a novel method for optimal learning of morphological filtering parameters (Genetic training algorithm for morphological filters, GTAMF) is presented.GTAMF adopts new crossover and mutation operators called the curved cylinder crossover and master-slave mutation to achieve optimal filtering parameters in a global searching. Experimental results show that this method is practical, easy to extend, and markedly improves the performances of morphological filters. The operation of a morphological filter can be divided into two basic problems including morphological operation and structuring element (SE) selection. The rules for morphological operations are predefined so that the filter's properties depend merely on the selection of SE. By means of adaptive optimization training, structuring elements possess the shape and structural characteristics of image targets, and give specific information to SE. Morphological filters formed in this way become certainly intelligent and can provide good filtering results and robust adaptability to image targets with clutter background.

  20. High Range Resolution Profile Automatic Target Recognition Using Sparse Representation

    Zhou Nuo; Chen Wei


    Sparse representation is a new signal analysis method which is receiving increasing attention in recent years.In this article,a novel scheme solving high range resolution profile automatic target recognition for ground moving targets is proposed.The sparse representation theory is applied to analyzing the components of high range resolution profiles and sparse coefficients are used to describe their features.Numerous experiments with the target type number ranging from 2 to 6 have been implemented.Results show that the proposed scheme not only provides higher recognition preciseness in real time,but also achieves more robust performance as the target type number increases.

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

    Blacknell, David


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

  2. Advanced automatic target recognition for police helicopter missions

    Stahl, Christoph; Schoppmann, Paul


    The results of a case study about the application of an advanced method for automatic target recognition to infrared imagery taken from police helicopter missions are presented. The method consists of the following steps: preprocessing, classification, fusion, postprocessing and tracking, and combines the three paradigms image pyramids, neural networks and bayesian nets. The technology has been developed using a variety of different scenes typical for military aircraft missions. Infrared cameras have been in use for several years at the Bavarian police helicopter forces and are highly valuable for night missions. Several object classes like 'persons' or 'vehicles' are tested and the possible discrimination between persons and animals is shown. The analysis of complex scenes with hidden objects and clutter shows the potentials and limitations of automatic target recognition for real-world tasks. Several display concepts illustrate the achievable improvement of the situation awareness. The similarities and differences between various mission types concerning object variability, time constraints, consequences of false alarms, etc. are discussed. Typical police actions like searching for missing persons or runaway criminals illustrate the advantages of automatic target recognition. The results demonstrate the possible operational benefits for the helicopter crew. Future work will include performance evaluation issues and a system integration concept for the target platform.

  3. Automatic radar target recognition of objects falling on railway tracks

    This paper presents an automatic radar target recognition procedure based on complex resonances using the signals provided by ultra-wideband radar. This procedure is dedicated to detection and identification of objects lying on railway tracks. For an efficient complex resonance extraction, a comparison between several pole extraction methods is illustrated. Therefore, preprocessing methods are presented aiming to remove most of the erroneous poles interfering with the discrimination scheme. Once physical poles are determined, a specific discrimination technique is introduced based on the Euclidean distances. Both simulation and experimental results are depicted showing an efficient discrimination of different targets including guided transport passengers

  4. Information fusion based on addition of unascertained rational numbers for recognization of spatial point targets

    张池平; 宋向勃; 崔祜涛


    A new uncertain information model, i.e. unascertainment, which is different from randomness,fuzziness and grayness, has been introduced into information fusion to give a reasoning method,which is basedon addition of unascertained rational number and can be used to recognize spatial point targets. The validity ofthe method proposed is verified through an example.

  5. Automatic target validation based on neuroscientific literature mining for tractography

    Xavier Vasques


    Full Text Available 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

  6. Recognizing cat-eye targets with dual criterions of shape and modulation frequency

    Ximing Ren; Li Li


    We present an image recognition method to distinguish targets with cat-eye effect from the dynamic background based on target shape and modulation frequency. Original image sequences to be processed are acquired through an imaging mechanism that utilizes a pulsed laser as active illuminator and an industrial camera as detection device. There are two criterions to recognize a target: one exploits shape priors and the other is the active illuminator's modulation frequency. The feasibility of the proposed method and its superiority over the single criterion method have been demonstrated by practical experiments.%@@ We present an image recognition method to distinguish targets with cat-eye effect from the dynamic background based on target 8hape and modulation frequency.Original image sequences to be processed are acquired through an imaging mechanism that utilizes a pulsed laser as active illuminator and an industrialcamera as detection device.There are two criterions to recognize a target: one exploits shape prior8 and the other is the active illuminator's modulation frequency.The feasibility of the proposed method and its superiority over the single criterion method have been demonstrated by practical experiments.

  7. Automatic detection of sea-sky horizon line and small targets in maritime infrared imagery

    Kong, Xiangyu; Liu, Lei; Qian, Yunsheng; Cui, Minjie


    It is usually difficult but important to extract distant targets from sea clutters and clouds since the targets are small compared to the pixel field of view. In this paper, an algorithm based on wavelet transformation is proposed for automatic detection of small targets under the maritime background. We recognize that the distant small targets generally appear near the sea-sky horizon line and noises lie along the direction of sea-sky horizon line. So the sea-sky horizon is located firstly by examining the approximate image of a Haar wavelet decomposition of the original image. And the equation of the sea-sky horizon is set up, no matter whether the sea-sky horizon is horizontal or not. Since the sea-sky horizon is located, not only the potential area but also the strip direction of noise is got. Then the modified mutual wavelet energy combination algorithm is applied to extract targets with targets being marked by red windows. Computer simulations are shown to validate the great adaptability of the sea-sky horizon line detection and the accuracy of the small targets detection. The algorithm should be useful to engineers and scientists to design precise guidance or maritime monitoring system.

  8. Deep transfer learning for automatic target classification: MWIR to LWIR

    Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun


    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.

  9. Recognizing subsurface target responses in ground penetrating radar data using convolutional neural networks

    Sakaguchi, Rayn T.; Morton, Kenneth D.; Collins, Leslie M.; Torrione, Peter A.


    Improved performance in the discrimination of buried threats using Ground Penetrating Radar (GPR) data has recently been achieved using features developed for applications in computer vision. These features, designed to characterize local shape information in images, have been utilized to recognize patches that contain a target signature in two-dimensional slices of GPR data. While these adapted features perform very well in this GPR application, they were not designed to specifically differentiate between target responses and background GPR data. One option for developing a feature specifically designed for target differentiation is to manually design a feature extractor based on the physics of GPR image formation. However, as seen in the historical progression of computer vision features, this is not a trivial task. Instead, this research evaluates the use of convolutional neural networks (CNNs) applied to two-dimensional GPR data. The benefit of using a CNN is that features extracted from the data are a learned parameter of the system. This has allowed CNN implementations to achieve state of the art performance across a variety of data types, including visual images, without the need for expert designed features. However, the implementation of a CNN must be done carefully for each application as network parameters can cause performance to vary widely. This paper presents results from using CNNs for object detection in GPR data and discusses proper parameter settings and other considerations.

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

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


    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.

  11. The benefit obtained from visually displayed text from an automatic speech recognizer during listening to speech presented in noise

    Zekveld, A.A.; Kramer, S.E.; Kessens, J.M.; Vlaming, M.S.M.G.; Houtgast, T.


    OBJECTIVES: The aim of this study was to evaluate the benefit that listeners obtain from visually presented output from an automatic speech recognition (ASR) system during listening to speech in noise. DESIGN: Auditory-alone and audiovisual speech reception thresholds (SRTs) were measured. The SRT i

  12. Gaussian process classification using automatic relevance determination for SAR target recognition

    Zhang, Xiangrong; Gou, Limin; Hou, Biao; Jiao, Licheng


    In this paper, a Synthetic Aperture Radar Automatic Target Recognition approach based on Gaussian process (GP) classification is proposed. It adopts kernel principal component analysis to extract sample features and implements target recognition by using GP classification with automatic relevance determination (ARD) function. Compared with k-Nearest Neighbor, Naïve Bayes classifier and Support Vector Machine, GP with ARD has the advantage of automatic model selection and hyper-parameter optimization. The experiments on UCI datasets and MSTAR database show that our algorithm is self-tuning and has better recognition accuracy as well.

  13. Automatic Attraction of Visual Attention by Supraletter Features of Former Target Strings

    Kyllingsbæk, Søren; Van Lommel, Sven; Sørensen, Thomas Alrik;


    Observers were trained to search for a particular horizontal string of 3 capital letters presented among similar strings consisting of exactly the same letters in different orders. The training was followed by a test in which the observers searched for a new target that was identical to one of the...... circumference of an imaginary circle around the fixation point. The training phase of Experiment 2 was similar, but in the test phase of the experiment, the strings were located in a vertical array centered on fixation, and in target-present arrays, the target always appeared at fixation. In both experiments......, performance (d’) degraded on trials in which former targets were present, suggesting that the former targets automatically drew processing resources away from the current targets. Apparently, the two experiments showed automatic attraction of visual attention by supraletter features of former target strings....

  14. Automatic target recognition of moving target based on empirical mode decomposition and genetic algorithm support vector machine

    张军; 欧建平; 占荣辉


    In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition (EMD) and support vector machine (SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions (IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm (GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28%for tank, vehicle and soldier, respectively.

  15. Automatic Detection and Decoding of Photogrammetric Coded Targets

    Wijenayake, Udaya; Choi, Sung-In; Park, Soon-Yong


    Close-range Photogrammetry is widely used in many industries because of the cost effectiveness and efficiency of the technique. In this research, we introduce an automated coded target detection method which can be used to enhance the efficiency of the Photogrammetry.

  16. Automatic target recognition in SAR images using multilinear analysis

    Porgès, Tristan; Favier, Gérard


    International audience Multilinear analysis provides a powerful mathematical framework for analyzing synthetic aperture radar (SAR) images resulting from the interaction of multiple factors like sky luminosity and viewing angles, while preserving their original shape. In this paper, we propose a multilinear principal component analysis (MPCA) algorithm for target recognition in SAR images. First, we form a high order tensor with the training image set and we apply the higher-order singular...

  17. System for automatic x-ray-image analysis, measurement, and sorting of laser fusion targets

    This paper describes the Automatic X-Ray Image Analysis and Sorting (AXIAS) system which is designed to analyze and measure x-ray images of opaque hollow microspheres used as laser fusion targets. The x-ray images are first recorded on a high resolution film plate. The AXIAS system then digitizes and processes the images to accurately measure the target parameters and defects. The primary goals of the AXIAS system are: to provide extremely accurate and rapid measurements, to engineer a practical system for a routine production environment and to furnish the capability of automatically measuring an array of images for sorting and selection

  18. Automatic target recognition in synthetic aperture sonar images for autonomous mine hunting

    Quesson, B.A.J.; Sabel, J.C.; Bouma, H.; Dekker, R.J.; Lengrand-Lambert, J.


    The future of Mine Countermeasures (MCM) operations lies with unmanned platforms where Automatic Target Recognition (ATR) is an essential step in making the mine hunting process autonomous. At TNO, a new ATR method is currently being developed for use on an Autonomous Underwater Vehicle (AUV), using

  19. An integrated approach toward recognizing, locating and combating targets from a modern interceptor aircraft

    Meyhoff, E. G.; Kloeckner, H. W.


    Interceptor aircraft of the future will find themselves in an environment which will not only be significantly more hostile than today but also far more difficult to assess. On the one hand the requirement will be to reduce the detectability of the own aircraft and on the other to enhance the capability of destroying enemy targets. Reduction of detectability can be achieved through a variety of measures such as lowering the radar cross section, the IR emission or the RF emission. Enhancement of the capability to destroy enemy target requires, next to better weapons, longer detection and identification ranges as well as quicker reaction times. Faster reaction times are not only required to gain advantages in combating the designated enemy targets but also to respond to threat situations which may emanate from sources other than the targets. The requirement will exist for an avionic system capable of correlating all relevant data and either reaching decisions itself or presenting the pilot with information in such a way that they support his own making process. This paper describes a typical set of aircraft equipments which would be involved in the data acquisition and decision making processes; it quantifies data volumes and rates and, based on these figures, attempts to define processing and correlation requirements. It then proposes a system architecture which might be suitable for the tasks at hand. The emphasis of the paper will be on assessing the impact of LSI/VHSIC technology on those portions of the avionics system which are utilized in the processes described above.

  20. Automatic target recognition on land using three dimensional (3D laser radar and artificial neural networks

    Göztepe, K.


    Full Text Available During combat, measuring the dimensions of targets is extremely important for knowing when to fire on the enemy. The importance of identifying a known target on land emphasizes the importance of techniques devoted to automatic target recognition. Although a number of object-recognition techniques have been developed in the past, none of them have provided the desired specifics for unidentified target recognition. Studies on target recognition are largely based on images that assume that images of a known target can be readily viewed under any circumstance. But this is not true for military operations conducted on various terrains under specific circumstances. Usually it is not possible to capture images of unidentified objects because of weather, inadequate equipment, or concealment. In this study, a new approach that integrates neural networks and laser radar has been developed for automatic target recognition in order to reduce the above-mentioned problems. Unlike current studies, the proposed model uses the geometric dimensions of unidentified targets in order to detect and recognise them under severe weather conditions.

  1. Linking Single Domain Antibodies that Recognize Different Epitopes on the Same Target.

    Glaven, Richard H; Anderson, George P; Zabetakis, Dan; Liu, Jinny L; Long, Nina C; Goldman, Ellen R


    Single domain antibodies (sdAb) are the recombinantly expressed variable regions from the heavy-chain-only antibodies found in camelids and sharks. SdAb are able to bind antigens with high affinity, and most are capable of refolding after heat or chemical denaturation to bind antigen again. Starting with our previously isolated ricin binding sdAb determined to bind to four non-overlapping epitopes, we constructed a series of sdAb pairs, which were genetically linked through peptides of different length. We designed the series so that the sdAb are linked in both orientations with respect to the joining peptide. We confirmed that each of the sdAb in the constructs was able to bind to the ricin target, and have evidence that they are both binding ricin simultaneously. Through this work we determined that the order of genetically linked sdAb seems more important than the linker length. The genetically linked sdAb allowed for improved ricin detection with better limits of detection than the best anti-ricin monoclonal we evaluated, however they were not able to refold as well as unlinked component sdAb. PMID:25585631

  2. Pseudo-Zernike Based Multi-Pass Automatic Target Recognition From Multi-Channel SAR

    Carmine CLEMENTE; Pallotta, Luca; Proudler, Ian; De Maio, Antonio; John J. Soraghan; Farina, Alfonso


    The capability to exploit multiple sources of information is of fundamental importance in a battlefield scenario. Information obtained from different sources, and separated in space and time, provide the opportunity to exploit diversities in order to mitigate uncertainty. For the specific challenge of Automatic Target Recognition (ATR) from radar platforms, both channel (e.g. polarization) and spatial diversity can provide useful information for such a specific and critical task. In this pape...

  3. Automatic target recognition performance losses in the presence of atmospheric and camera effects

    Chen, Xiaohan; Schmid, Natalia A.


    The importance of networked automatic target recognition systems for surveillance applications is continuously increasing. Because of the requirement of a low cost and limited payload, these networks are traditionally equipped with lightweight, low-cost sensors such as electro-optical (EO) or infrared sensors. The quality of imagery acquired by these sensors critically depends on the environmental conditions, type and characteristics of sensors, and absence of occluding or concealing objects. In the past, a large number of efficient detection, tracking, and recognition algorithms have been designed to operate on imagery of good quality. However, detection and recognition limits under nonideal environmental and/or sensor-based distortions have not been carefully evaluated. We introduce a fully automatic target recognition system that involves a Haar-based detector to select potential regions of interest within images, performs adjustment of detected regions, segments potential targets using a region-based approach, identifies targets using Bessel K form-based encoding, and performs clutter rejection. We investigate the effects of environmental and camera conditions on target detection and recognition performance. Two databases are involved. One is a simulated database generated using a 3-D tool. The other database is formed by imaging 10 die-cast models of military vehicles from different elevation and orientation angles. The database contains imagery acquired both indoors and outdoors. The indoors data set is composed of clear and distorted images. The distortions include defocus blur, sided illumination, low contrast, shadows, and occlusions. All images in this database, however, have a uniform (blue) background. The indoors database is applied to evaluate the degradations of recognition performance due to camera and illumination effects. The database collected outdoors includes a real background and is much more complex to process. The numerical results

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

    Shijun Zhang; Zhongliang Jing; Jianxun Li


    @@ 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 realworld 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.


    Wang Yimin; An Jinwen


    The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar(SAR) images based on Maximum A Posteriori(MAP). The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = {target,shadow, background}. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.

  6. Study of an automatized experimental device for the irradiation of a radioactive target

    In order to solve the enigma of solar neutrinos, a team of physicians of the nuclear research center of Bordeaux-Gradignan and of the center of nuclear spectroscopy and mass spectroscopy of Orsay (France) decided to measure again the cross section of the beryllium-proton nuclear reaction at the lowest possible energies. This measurement requires the design of an automatized experimental device to irradiate in a specific way a beryllium target with an accelerated proton beam. The aim of this work is the study of such a device for an energy range of 800 to 300 KeV. This device comprises a particle multi-detector and a shutter for the irradiation of the target and the counting of the reaction products according to a programmable time sequence. The advantage of this setup is to allow an important bombardment of the target and to ensure its cooling. This device is automatically controlled thanks to a micro-controller, actuators (step motors and electrostatic deflector). It includes some beam diagnosis elements controlled by step motors and a target temperature monitoring system controlling a safety valve. The management of the experiment cell vacuum has led to the design of a vacuum monitor allowing the precise follow up of the vacuum and the control of the safety valves of the device. The nuclear instrumentation necessary to be implemented for this measurement is also presented. (J.S.)

  7. Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery

    Shukla, P. K.; Goel, S.; Singh, P.; Lohani, B.


    Tracking of targets from aerial platforms is an important activity in several applications, especially surveillance. Knowled ge of geolocation of these targets adds additional significant and useful information to the application. This paper determines the geolocation of a target being tracked from an aerial platform using the technique of image registration. Current approaches utilize a POS to determine the location of the aerial platform and then use the same for geolocation of the targets using the principle of photogrammetry. The constraints of cost and low-payload restrict the applicability of this approach using UAV platforms. This paper proposes a methodology for determining the geolocation of a target tracked from an aerial platform in a partially GPS devoid environment. The method utilises automatic feature based registration technique of a georeferenced satellite image with an ae rial image which is already stored in UAV's database to retrieve the geolocation of the target. Since it is easier to register subsequent aerial images due to similar viewing parameters, the subsequent overlapping images are registered together sequentially thus resulting in the registration of each of the images with georeferenced satellite image thus leading to geolocation of the target under interest. Using the proposed approach, the target can be tracked in all the frames in which it is visible. The proposed concept is verified experimentally and the results are found satisfactory. Using the proposed method, a user can obtain location of target of interest as well features on ground without requiring any POS on-board the aerial platform. The proposed approach has applications in surveillance for target tracking, target geolocation as well as in disaster management projects like search and rescue operations.

  8. Analgorithmic Framework for Automatic Detection and Tracking Moving Point Targets in IR Image Sequences

    R. Anand Raji


    Full Text Available Imaging sensors operating in infrared (IR region of electromagnetic spectrum are gaining importance in airborne automatic target recognition (ATR applications due to their passive nature of operation. IR imaging sensors exploit the unintended IR radiation emitted by the targets of interest for detection. The ATR systems based on the passive IR imaging sensors employ a set of signal processing algorithms for processing the image information in real-time. The real-time execution of signal processing algorithms provides the sufficient reaction time to the platform carrying ATR system to react upon the target of interest. These set of algorithms include detection, tracking, and classification of low-contrast, small sized-targets. Paper explained a signal processing framework developed to detect and track moving point targets from the acquired IR image sequences in real-time.Defence Science Journal, Vol. 65, No. 3, May 2015, pp.208-213, DOI:

  9. Automatic determination of the number of targets present when using the time reversal operator.

    Quinlan, Angela; Barbot, Jean-Pierre; Larzabal, Pascal


    Acoustical time reversal mirrors have been shown to provide a highly accurate means of studying and focusing on acoustical sources. The DORT method is a derivation of the time reversal process, which allows for focusing on multiple targets. An important step in this process is the determination of the number of targets or sources present. This is achieved by examining the eigenvalues of the time reversal operator (TRO). The number of significant eigenvalues is then chosen as the number of sources present. However, as mentioned in [N. Mordant, C. Prada, and M. Fink, J. Acoust. Soc. Am. 105, 2634-2642 (1999) and C. Prada, M. Tanter, and M. Fink, in Proceedings of the IEEE Symposium, 1997, pp. 679-683], factors such as low signal to noise ratio (SNR), small data sample, array configuration and the target location may result in the eigenvalues corresponding to the targets no longer being distinguishable from the background noise eigenvalues. This paper proposes a robust method of automatically determining the number of targets even in the presence of a small number of snapshots. For white Gaussian noise, the profile of the ordered eigenvalues is seen to fit an exponential law. The observed eigenvalues are then compared to this model and a mismatch is detected between the observed profile and the noise-only model. The index of the mismatch gives the number of scatterers present. PMID:16642836

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

    Daisne, Jean-François; Blumhofer, Andreas


    Background 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. Methods The updated Brai...

  11. Dynamic Data Driven Applications Systems (DDDAS) modeling for automatic target recognition

    Blasch, Erik; Seetharaman, Guna; Darema, Frederica


    The Dynamic Data Driven Applications System (DDDAS) concept uses applications modeling, mathematical algorithms, and measurement systems to work with dynamic systems. A dynamic systems such as Automatic Target Recognition (ATR) is subject to sensor, target, and the environment variations over space and time. We use the DDDAS concept to develop an ATR methodology for multiscale-multimodal analysis that seeks to integrated sensing, processing, and exploitation. In the analysis, we use computer vision techniques to explore the capabilities and analogies that DDDAS has with information fusion. The key attribute of coordination is the use of sensor management as a data driven techniques to improve performance. In addition, DDDAS supports the need for modeling from which uncertainty and variations are used within the dynamic models for advanced performance. As an example, we use a Wide-Area Motion Imagery (WAMI) application to draw parallels and contrasts between ATR and DDDAS systems that warrants an integrated perspective. This elementary work is aimed at triggering a sequence of deeper insightful research towards exploiting sparsely sampled piecewise dense WAMI measurements - an application where the challenges of big-data with regards to mathematical fusion relationships and high-performance computations remain significant and will persist. Dynamic data-driven adaptive computations are required to effectively handle the challenges with exponentially increasing data volume for advanced information fusion systems solutions such as simultaneous target tracking and ATR.

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

    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 (GTVP) and involved lymph nodes (GTVLN) to simulate the localization process in image-guided 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 GTVP and GTVLN, respectively. Compared to bony alignment, transitive-based and seeded registrations significantly reduced GTVP centroid LE to 4.7 ± 3.7 mm (p = 0.011) and 4.3 ± 2.5 mm (p -3), respectively, but the smallest GTVP LE of 2.4 ± 2.1 mm was provided by rereferenced registration (p -6). Standard registration significantly reduced GTVLN centroid LE to 3.2 ± 2.5 mm (p -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 GTVP and GTVLN, respectively, using

  13. Automatic target classification of man-made objects in synthetic aperture radar images using Gabor wavelet and neural network

    Vasuki, Perumal; Roomi, S. Mohamed Mansoor


    Processing of synthetic aperture radar (SAR) images has led to the development of automatic target classification approaches. These approaches help to classify individual and mass military ground vehicles. This work aims to develop an automatic target classification technique to classify military targets like truck/tank/armored car/cannon/bulldozer. The proposed method consists of three stages via preprocessing, feature extraction, and neural network (NN). The first stage removes speckle noise in a SAR image by the identified frost filter and enhances the image by histogram equalization. The second stage uses a Gabor wavelet to extract the image features. The third stage classifies the target by an NN classifier using image features. The proposed work performs better than its counterparts, like K-nearest neighbor (KNN). The proposed work performs better on databases like moving and stationary target acquisition and recognition against the earlier methods by KNN.

  14. Hardware bitstream sequence recognizer

    Karpin, Oleksandr; Sokil, Volodymyr


    This paper describes how to implement in hardware a bistream sequence recognizer using the PSoC Pseudo Random Sequence Generator (PRS) User Module. The PRS can be used in digital communication systems with the serial data interface for automatic preamble detection and extraction, control words selection, etc.

  15. A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

    Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle


    On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual con-tours of the kidney, bladder, duodenum, and a liver tumor by an experienced radia-tion oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (< 1 ms) with a satisfying accuracy (Dice = 0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of

  16. Automatic identification of bird targets with radar via patterns produced by wing flapping.

    Zaugg, Serge; Saporta, Gilbert; van Loon, Emiel; Schmaljohann, Heiko; Liechti, Felix


    Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extracted (via continuous wavelet transform). We used support vector classifiers to build predictive models. We estimated classification performance via cross validation on four datasets. When data from the same dataset were used for training and testing the classifier, the classification performance was extremely to moderately high. When data from one dataset were used for training and the three remaining datasets were used as test sets, the performance was lower but still extremely to moderately high. This shows that the method generalizes well across different locations or times. Our method provides a substantial gain of time when birds must be identified in large collections of radar signals and it represents the first substantial step in developing a real time bird identification radar system. We provide some guidelines and ideas for future research. PMID:18331979

  17. Automatic gas-levitation system for vacuum deposition of laser-fusion targets

    An improved simple system has been developed to gas-levitate microspheres during vacuum-deposition processes. The automatic operation relies on two effects: a lateral stabilizing force provided by a centering-ring; and an automatically incremented gas metering system to offset weight increases during coating

  18. Recognizing Cataracts

    ... please review our exit disclaimer . Subscribe Recognizing Cataracts Watch for Vision Changes as You Age As life ... your eyes from harmful ultraviolet rays from the sun. Try wearing sunglasses or a hat with a ...

  19. Using locality-constrained linear coding in automatic target detection of HRS images

    Rezaee, M.; Mirikharaji, Z.; Zhang, Y.


    Automatic target detection with complicated shapes in high spatial resolution images is an ongoing challenge in remote sensing image processing. This is because most methods use spectral or texture information, which are not sufficient for detecting complex shapes. In this paper, a new detection framework, based on Spatial Pyramid Matching (SPM) and Locality- constraint Linear Coding (LLC), is proposed to solve this problem, and exemplified using airplane shapes. The process starts with partitioning the image into sub-regions and generating a unique histogram for local features of each sub-region. Then, linear Support Vector Machines (SVMs) are used to detect objects based on a pyramid-matching kernel, which analyses the descriptors inside patches in different resolution. In order to generate the histogram, first a point feature detector (e.g. SIFT) is applied on the patches, and then a quantization process is used to select local features. In this step, the k-mean method is used in conjunction with the locality-constrained linear coding method. The LLC forces the coefficient matrix in the quantization process to be local and sparse as well. As a result, the speed of the method improves around 24 times in comparison to using sparse coding for quantization. Quantitative analysis also shows improvement in comparison to just using k-mean, but the accuracy in comparison to using sparse coding is similar. Rotation and shift of the desired object has no effect on the obtained results. The speed and accuracy of this algorithm for high spatial resolution images make it capable for use in real-world applications.

  20. Automatic online adaptive radiation therapy techniques for targets with significant shape change: a feasibility study

    Court, Laurence E; Tishler, Roy B; Petit, Joshua; Cormack, Robert; Chin Lee [Department of Radiation Oncology, Dana-Farber/Brigham and Women' s Hospital Cancer Center, 75 Francis Street, ASBI-L2, Boston, MA 02115 (United States)


    This work looks at the feasibility of an online adaptive radiation therapy concept that would detect the daily position and shape of the patient, and would then correct the daily treatment to account for any changes compared with planning position. In particular, it looks at the possibility of developing algorithms to correct for large complicated shape change. For co-planar beams, the dose in an axial plane is approximately associated with the positions of a single multi-leaf collimator (MLC) pair. We start with a primary plan, and automatically generate several secondary plans with gantry angles offset by regular increments. MLC sequences for each plan are calculated keeping monitor units (MUs) and number of segments constant for a given beam (fluences are different). Bulk registration (3D) of planning and daily CT images gives global shifts. Slice-by-slice (2D) registration gives local shifts and rotations about the longitudinal axis for each axial slice. The daily MLC sequence is then created for each axial slice/MLC leaf pair combination, by taking the MLC positions from the pre-calculated plan with the nearest rotation, and shifting using a beam's-eye-view calculation to account for local linear shifts. A planning study was carried out using two head and neck region MR images of a healthy volunteer which were contoured to simulate a base-of-tongue treatment: one with the head straight (used to simulate the planning image) and the other with the head tilted to the left (the daily image). Head and neck treatment was chosen to evaluate this technique because of its challenging nature, with varying internal and external contours, and multiple degrees of freedom. Shape change was significant: on a slice-by-slice basis, local rotations in the daily image varied from 2 to 31 deg, and local shifts ranged from -0.2 to 0.5 cm and -0.4 to 0.0 cm in right-left and posterior-anterior directions, respectively. The adapted treatment gave reasonable target coverage (100

  1. Dolphin: a tool for automatic targeted metabolite profiling using 1D and 2D (1)H-NMR data.

    Gómez, Josep; Brezmes, Jesús; Mallol, Roger; Rodríguez, Miguel A; Vinaixa, Maria; Salek, Reza M; Correig, Xavier; Cañellas, Nicolau


    One of the main challenges in nuclear magnetic resonance (NMR) metabolomics is to obtain valuable metabolic information from large datasets of raw NMR spectra in a high throughput, automatic, and reproducible way. To date, established software packages used to match and quantify metabolites in NMR spectra remain mostly manually operated, leading to low resolution results and subject to inconsistencies not attributable to the NMR technique itself. Here, we introduce a new software package, called Dolphin, able to automatically quantify a set of target metabolites in multiple sample measurements using an approach based on 1D and 2D NMR techniques to overcome the inherent limitations of 1D (1)H-NMR spectra in metabolomics. Dolphin takes advantage of the 2D J-resolved NMR spectroscopy signal dispersion to avoid inconsistencies in signal position detection, enhancing the reliability and confidence in metabolite matching. Furthermore, in order to improve accuracy in quantification, Dolphin uses 2D NMR spectra to obtain additional information on all neighboring signals surrounding the target metabolite. We have compared the targeted profiling results of Dolphin, recorded from standard biological mixtures, with those of two well established approaches in NMR metabolomics. Overall, Dolphin produced more accurate results with the added advantage of being a fully automated and high throughput processing package. PMID:25370160

  2. Automatic localization of target vertebrae in spine surgery using fast CT-to-fluoroscopy (3D-2D) image registration

    Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.


    Localization of target vertebrae is an essential step in minimally invasive spine surgery, with conventional methods relying on "level counting" - i.e., manual counting of vertebrae under fluoroscopy starting from readily identifiable anatomy (e.g., the sacrum). The approach requires an undesirable level of radiation, time, and is prone to counting errors due to the similar appearance of vertebrae in projection images; wrong-level surgery occurs in 1 of every ~3000 cases. This paper proposes a method to automatically localize target vertebrae in x-ray projections using 3D-2D registration between preoperative CT (in which vertebrae are preoperatively labeled) and intraoperative fluoroscopy. The registration uses an intensity-based approach with a gradient-based similarity metric and the CMA-ES algorithm for optimization. Digitally reconstructed radiographs (DRRs) and a robust similarity metric are computed on GPU to accelerate the process. Evaluation in clinical CT data included 5,000 PA and LAT projections randomly perturbed to simulate human variability in setup of mobile intraoperative C-arm. The method demonstrated 100% success for PA view (projection error: 0.42mm) and 99.8% success for LAT view (projection error: 0.37mm). Initial implementation on GPU provided automatic target localization within about 3 sec, with further improvement underway via multi-GPU. The ability to automatically label vertebrae in fluoroscopy promises to streamline surgical workflow, improve patient safety, and reduce wrong-site surgeries, especially in large patients for whom manual methods are time consuming and error prone.

  3. Automatic Shape-Based Target Extraction for Close-Range Photogrammetry

    Guo, X.; Chen, Y.; Wang, C.; Cheng, M.; Wen, C.; Yu, J.


    In order to perform precise identification and location of artificial coded targets in natural scenes, a novel design of circle-based coded target and the corresponding coarse-fine extraction algorithm are presented. The designed target separates the target box and coding box totally and owns an advantage of rotation invariance. Based on the original target, templates are prepared by three geometric transformations and are used as the input of shape-based template matching. Finally, region growing and parity check methods are used to extract the coded targets as final results. No human involvement is required except for the preparation of templates and adjustment of thresholds in the beginning, which is conducive to the automation of close-range photogrammetry. The experimental results show that the proposed recognition method for the designed coded target is robust and accurate.

  4. Plasma membrane associated, virus-specific polypeptides required for the formation of target antigen complexes recognized by virus-specific cytotoxic T lymphocytes

    These studies were undertaken to define some of the poxvirus-specific target antigens which are synthesized in infected cells and recognized by vaccinia virus-specific CTLs (VV-CTLs). Since vaccinia virus infected, unmanipulated target cells express numerous virus-specific antigens on the plasma membrane, attempts were made to manipulate expression of the poxvirus genome after infection so that one or a few defined virus-specified antigens were expressed on the surface of infected cells. In vitro [51Cr]-release assays determined that viral DNA synthesis and expression of late viral proteins were not necessary to form a target cell which was fully competent for lysis by VV-CTLs. Under the conditions employed in these experiments, 90-120 minutes of viral protein synthesis were necessary to produce a competent cell for lysis by VV-CTLs. In order to further inhibit the expression of early viral proteins in infected cells, partially UV-inactivated vaccinia virus was employed to infect target cells. It was determined that L-cells infected with virus preparations which had been UV-irradiated for 90 seconds were fully competent for lysis by VV-CTLs. Cells infected with 90 second UV-irr virus expressed 3 predominant, plasma membrane associated antigens of 36-37K, 27-28K, and 19-17K. These 3 viral antigens represent the predominant membrane-associated viral antigens available for interaction with class I, major histocompatibility antigens and hence are potential target antigens for VV-CTLs

  5. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

    J. Del Rio Vera; Coiras, E.; Groen, J; Evans, B.


    This paper presents a new supervised classification approach for automated target recognition (ATR) in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving...

  6. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

    Del Rio Vera, J.; Coiras, E.; Groen, J.; Evans, B.


    This paper presents a new supervised classification approach for automated target recognition (ATR) in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving up to 95% classification accuracy.

  7. Recognizing Facial Expressions Automatically from Video

    Shan, Caifeng; Braspenning, Ralph

    Facial expressions, resulting from movements of the facial muscles, are the face changes in response to a person's internal emotional states, intentions, or social communications. There is a considerable history associated with the study on facial expressions. Darwin [22] was the first to describe in details the specific facial expressions associated with emotions in animals and humans, who argued that all mammals show emotions reliably in their faces. Since that, facial expression analysis has been a area of great research interest for behavioral scientists [27]. Psychological studies [48, 3] suggest that facial expressions, as the main mode for nonverbal communication, play a vital role in human face-to-face communication. For illustration, we show some examples of facial expressions in Fig. 1.

  8. Validation of experts versus atlas-based and automatic registration methods for subthalamic nucleus targeting on MRI

    Objects: In functional stereotactic neurosurgery, one of the cornerstones upon which the success and the operating time depends is an accurate targeting. The subthalamic nucleus (STN) is the usual target involved when applying deep brain stimulation for Parkinson's disease (PD). Unfortunately, STN is usually not clearly visible in common medical imaging modalities, which justifies the use of atlas-based segmentation techniques to infer the STN location. Materials and methods: Eight bilaterally implanted PD patients were included in this study. A three-dimensional T1-weighted sequence and inversion recovery T2-weighted coronal slices were acquired pre-operatively. We propose a methodology for the construction of a ground truth of the STN location and a scheme that allows both, to perform a comparison between different non-rigid registration algorithms and to evaluate their usability to locate the STN automatically. Results: The intra-expert variability in identifying the STN location is 1.06±0.61 mm while the best non-rigid registration method gives an error of 1.80±0.62 mm. On the other hand, statistical tests show that an affine registration with only 12 degrees of freedom is not enough for this application. Conclusions: Using our validation-evaluation scheme, we demonstrate that automatic STN localization is possible and accurate with non-rigid registration algorithms. (orig.)

  9. I-TevI, the endonuclease encoded by the mobile td intron, recognizes binding and cleavage domains on its DNA target.

    Bell-Pedersen, D; Quirk, S M; Bryk, M; Belfort, M


    Mobility of the phage T4 td intron depends on activity of an intron-encoded endonuclease (I-TevI), which cleaves a homologous intronless (delta In) target gene. The double-strand break initiates a recombination event that leads to intron transfer. We found previously that I-TevI cleaves td delta In target DNA 23-26 nucleotides upstream of the intron insertion site. DNase I-footprinting experiments and gel-shift assays indicate that I-TevI makes primary contacts around the intron insertion site. A synthetic DNA duplex spanning the insertion site but lacking the cleavage site was shown to bind I-TevI specifically, and when cloned, to direct cleavage into vector sequences. The behavior of the cloned duplex and that of deletion and insertion mutants support a primary role for sequences surrounding the insertion site in directing I-TevI binding, conferring cleavage ability, and determining cleavage polarity. On the other hand, sequences around the cleavage site were shown to influence cleavage efficiency and cut-site selection. The role of cleavage-site sequences in determining cleavage distance argues against a strict "ruler" mechanism for cleavage by I-TevI. The complex nature of the homing site recognized by this unusual type of endonuclease is considered in the context of intron spread. PMID:1881913

  10. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

    J. Del Rio Vera


    Full Text Available This paper presents a new supervised classification approach for automated target recognition (ATR in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving up to 95% classification accuracy.

  11. Morphological neural networks for automatic target detection by simulated annealing learning algorithm

    余农; 吴昊; 吴常泳; 李范鸣; 吴立德


    A practical neural network model for morphological filtering and a simulated annealing optimal algorithm for the network parameters training are proposed in this paper. It is pointed out that the optimal designing process of the morphological filtering network in fact is the optimal learning process of adjusting network parameters (structuring element, or SE for short) to accommodate image environment. Then the network structure may possess the characteristics ofimage targets, and so give specific infor- mation to the SE. Morphological filters formed in this way become certainly intelligent and can provide good filtering results and robust adaptability to complex changing image. For application tomotional image target detection, dynamic training algorithm is applied to the designing process using asymptotic shrinking error and appropriate network weights adjusting. Experimental results show that the algorithm has invariant propertywith respect to shift, scale and rotation of moving target in continuing detection of moving targets.

  12. Real-time tumor tracking: Automatic compensation of target motion using the Siemens 160 MLC

    Purpose: Advanced high quality radiation therapy techniques such as IMRT require an accurate delivery of precisely modulated radiation fields to the target volume. Interfractional and intrafractional motion of the patient's anatomy, however, may considerably deteriorate the accuracy of the delivered dose to the planned dose distributions. In order to compensate for these potential errors, a dynamic real-time capable MLC control system was designed. Methods: The newly developed adaptive MLC control system contains specialized algorithms which are capable of continuous optimization and correction of the aperture of the MLC according to the motion of the target volume during the dose delivery. The algorithms calculate the new leaf positions based on target information provided online to the system. The algorithms were implemented in a dynamic target tracking control system designed for a Siemens 160 MLC. To assess the quality of the new target tracking system in terms of dosimetric accuracy, experiments with various types of motion patterns using different phantom setups were performed. The phantoms were equipped with radiochromic films placed between solid water slabs. Dosimetric results of exemplary deliveries to moving targets with and without dynamic MLC tracking applied were compared in terms of the gamma criterion to the reference dose delivered to a static phantom. Results: Our measurements indicated that dose errors for clinically relevant two-dimensional target motion can be compensated by the new control system during the dose delivery of open fields. For a clinical IMRT dose distribution, the gamma success rate was increased from 19% to 77% using the new tracking system. Similar improvements were achieved for the delivery of a complete IMRT treatment fraction to a moving lung phantom. However, dosimetric accuracy was limited by the system's latency of 400 ms and the finite leaf width of 5 mm in the isocenter plane. Conclusions: Different experimental setups

  13. Experimental new automatic tools for robotic stereotactic neurosurgery: towards "no hands" procedure of leads implantation into a brain target.

    Mazzone, P; Arena, P; Cantelli, L; Spampinato, G; Sposato, S; Cozzolino, S; Demarinis, P; Muscato, G


    The use of robotics in neurosurgery and, particularly, in stereotactic neurosurgery, is becoming more and more adopted because of the great advantages that it offers. Robotic manipulators easily allow to achieve great precision, reliability, and rapidity in the positioning of surgical instruments or devices in the brain. The aim of this work was to experimentally verify a fully automatic "no hands" surgical procedure. The integration of neuroimaging to data for planning the surgery, followed by application of new specific surgical tools, permitted the realization of a fully automated robotic implantation of leads in brain targets. An anthropomorphic commercial manipulator was utilized. In a preliminary phase, a software to plan surgery was developed, and the surgical tools were tested first during a simulation and then on a skull mock-up. In such a way, several tools were developed and tested, and the basis for an innovative surgical procedure arose. The final experimentation was carried out on anesthetized "large white" pigs. The determination of stereotactic parameters for the correct planning to reach the intended target was performed with the same technique currently employed in human stereotactic neurosurgery, and the robotic system revealed to be reliable and precise in reaching the target. The results of this work strengthen the possibility that a neurosurgeon may be substituted by a machine, and may represent the beginning of a new approach in the current clinical practice. Moreover, this possibility may have a great impact not only on stereotactic functional procedures but also on the entire domain of neurosurgery. PMID:27194228

  14. Stereographic Targeting in Prostate Radiotherapy: Speed and Precision by Daily Automatic Positioning Corrections Using Kilovoltage/Megavoltage Image Pairs

    Purpose: A fully automated, fast, on-line prostate repositioning scheme using implanted markers, kilovoltage/megavoltage imaging, and remote couch movements has been developed and clinically applied. The initial clinical results of this stereographic targeting (SGT) method, as well as phantom evaluations, are presented. Methods and Materials: Using the SGT method, portal megavoltage images are acquired with the first two to six monitor units of a treatment beam, immediately followed by acquisition of an orthogonal kilovoltage image without gantry motion. The image pair is automatically analyzed to obtain the marker positions and three-dimensional prostate displacement and rotation. Remote control couch shifts are applied to correct for the displacement. The SGT performance was measured using both phantom images and images from 10 prostate cancer patients treated using SGT. Results: With phantom measurements, the accuracy of SGT was 0.5, 0.2, and 0.3 mm (standard deviation [SD]) for the left-right, craniocaudal, and anteroposterior directions, respectively, for translations and 0.5o (SD) for the rotations around all axes. Clinically, the success rate for automatic marker detection was 99.5%, and the accuracy was 0.3, 0.5 and 0.8 mm (SD) in the left-right, craniocaudal, and anteroposterior axes. The SDs of the systematic center-of-mass positioning errors (Σ) were reduced from 4.0 mm to <0.5 mm for all axes. The corresponding SD of the random (σ) errors was reduced from 3.0 to <0.8 mm. These small residual errors were achieved with a treatment time extension of <1 min. Conclusion: Stereographic targeting yields systematic and random prostate positioning errors of <1 mm with <1 min of added treatment time

  15. Iaser gun automatic shoting target and reporting%激光枪自动射击报靶装置

    陈启昂; 潘瑶麟; 楼奇力


    This article is an automatic shooting indication of shots device design, largely by the Laser Gun and aiming, chest round target, correction detection circuit that some parts.The entire system is to control the k60 microcontroller core, through the camera, on the chest round target for image acquisition, processing, feedback to the SCM, determine where the correction, and can use the keyboard to change the wave pwm servo motor turns the appropriate angle, thus controlling laser correction.In addition to basic requirements met, the system designed to expand links : graphic dot matrix displays on the monitor chest round target graphics, and flash display correction.Automatic control of laser guns, the laser beam spot in 15 seconds from the rapid aiming at the specified location on the chest round target and hit the bull’s -eye ( that is, 10 Loop area ), other : Any number to ring, laser pointer to the appropriate place, is quite precise, and be able to voice indication of shots.%  本文设计的是一个自动射击报靶装置,主要由激光枪及瞄准机构、胸环靶、弹着点检测电路这几个部分构成。整个系统是以K60单片机为控制核心,通过摄像头,对胸环靶进行图像采集、处理,反馈给单片机,判断出弹着点所在位置,并且能通过键盘来改变PWM波使伺服电机转动相应角度,从而调控激光枪的弹着点。除基本要求满足外,本系统设计了一些拓展环节:图形点阵显示器上显示胸环靶的相应图形,并闪烁显示弹着点。自动控制激光枪,在15秒内将激光束光斑从胸环靶上的指定位置迅速瞄准并击中靶心(即10环区域),其他:任意给环数,激光笔打到相应位置,相当精确,并且能够语音报靶。

  16. Performance portability study of an automatic target detection and classification algorithm for hyperspectral image analysis using OpenCL

    Bernabe, Sergio; Igual, Francisco D.; Botella, Guillermo; Garcia, Carlos; Prieto-Matias, Manuel; Plaza, Antonio


    Recent advances in heterogeneous high performance computing (HPC) have opened new avenues for demanding remote sensing applications. Perhaps one of the most popular algorithm in target detection and identification is the automatic target detection and classification algorithm (ATDCA) widely used in the hyperspectral image analysis community. Previous research has already investigated the mapping of ATDCA on graphics processing units (GPUs) and field programmable gate arrays (FPGAs), showing impressive speedup factors that allow its exploitation in time-critical scenarios. Based on these studies, our work explores the performance portability of a tuned OpenCL implementation across a range of processing devices including multicore processors, GPUs and other accelerators. This approach differs from previous papers, which focused on achieving the optimal performance on each platform. Here, we are more interested in the following issues: (1) evaluating if a single code written in OpenCL allows us to achieve acceptable performance across all of them, and (2) assessing the gap between our portable OpenCL code and those hand-tuned versions previously investigated. Our study includes the analysis of different tuning techniques that expose data parallelism as well as enable an efficient exploitation of the complex memory hierarchies found in these new heterogeneous devices. Experiments have been conducted using hyperspectral data sets collected by NASA's Airborne Visible Infra- red Imaging Spectrometer (AVIRIS) and the Hyperspectral Digital Imagery Collection Experiment (HYDICE) sensors. To the best of our knowledge, this kind of analysis has not been previously conducted in the hyperspectral imaging processing literature, and in our opinion it is very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

  17. A semantic approach to the efficient integration of interactive and automatic target recognition systems for the analysis of complex infrastructure from aerial imagery

    Bauer, A.; Peinsipp-Byma, E.


    The analysis of complex infrastructure from aerial imagery, for instance a detailed analysis of an airfield, requires the interpreter, besides to be familiar with the sensor's imaging characteristics, to have a detailed understanding of the infrastructure domain. The required domain knowledge includes knowledge about the processes and functions involved in the operation of the infrastructure, the potential objects used to provide those functions and their spatial and functional interrelations. Since it is not possible yet to provide reliable automatic object recognition (AOR) for the analysis of such complex scenes, we developed systems to support a human interpreter with either interactive approaches, able to assist the interpreter with previously acquired expert knowledge about the domain in question, or AOR methods, capable of detecting, recognizing or analyzing certain classes of objects for certain sensors. We believe, to achieve an optimal result at the end of an interpretation process in terms of efficiency and effectivity, it is essential to integrate both interactive and automatic approaches to image interpretation. In this paper we present an approach inspired by the advancing semantic web technology to represent domain knowledge, the capabilities of available AOR modules and the image parameters in an explicit way. This enables us to seamlessly extend an interactive image interpretation environment with AOR modules in a way that we can automatically select suitable AOR methods for the current subtask, focus them on an appropriate area of interest and reintegrate their results into the environment.

  18. Improved clutter rejection in automatic target recognition and tracking using eigen-extended maximum average correlation height (EEMACH) filter and polynomial distance classifier correlation filter (PDCCF)

    Islam, M. F.; Alam, M. S.


    Various correlation based techniques for detection and classification of targets in forward looking infrared (FLIR) imagery have been developed in last two decades. Correlation filters are attractive for automatic target recognition (ATR) because of their distortion tolerance and shift invariance capabilities. The extended maximum average correlation height (EMACH) filter was developed to detect a target with low false alarm rate while providing good distortion tolerance using a trade off parameter (beta). By decomposing the EMACH filter using the eigen-analysis, another generalized filter, called the eigen-EMACH (EEMACH) filter was developed. The EEMACH filter exhibits consistent performance over a wide range which controls the trade-off between distortion tolerance and clutter rejection. In this paper, a new technique is proposed to combine the EEMACH and polynomial distance classifier correlation filter (PDCCF) for detecting and tracking both single and multiple targets in real life FLIR sequences. At first, EEMACH filter was used to select regions of interest (ROI) from input images and then PDCCF is applied to identify targets using thresholds and distance measures. Both the EEMACH and PDCCF filters are trained with different sizes and orientations corresponding to the target to be detected. This method provides improved clutter rejection capability by exploiting the eigen vectors of the desired class. Both single and multiple targets were identified in each frame by independently using EEMACH-PDCCF algorithm to avoid target disappearance problems under complicated scenarios.

  19. I-TevI, the endonuclease encoded by the mobile td intron, recognizes binding and cleavage domains on its DNA target.

    Bell-Pedersen, D; Quirk, S M; Bryk, M; Belfort, M


    Mobility of the phage T4 td intron depends on activity of an intron-encoded endonuclease (I-TevI), which cleaves a homologous intronless (delta In) target gene. The double-strand break initiates a recombination event that leads to intron transfer. We found previously that I-TevI cleaves td delta In target DNA 23-26 nucleotides upstream of the intron insertion site. DNase I-footprinting experiments and gel-shift assays indicate that I-TevI makes primary contacts around the intron insertion sit...

  20. A Model for Quick Searching and Recognizing Path of a Moving Target%运动目标快速搜索辨识的路径规划

    袁俊华; 年福耿; 刘李楠


    运动目标快速搜索辨识问题属于路径规划,与背包问题以及推销员最佳路线问题相似,但又存在明显区别:前者问题目标是运动的,后者是静止的;当运动目标是待辨识可疑船只时,还要考虑多种因素和资源.基于此,提出“动静结合”,在利用Hamilton回路算法和Kruskal避圈法的基础上,设计截相遇迭代算法,并根据目标的威胁等级以及聚集程度建立最优搜索策略.%The problem to search and identify the path of a moving is a path planning problem.It is similar to knappack problem and best saleman route,but with significant differences:problem targets at moving objects,while other problems deal with static situation.Especially when the target is a suspicious ship,the safety of convoy should be also considered.Based on this,a model combining target movement and static condition are proposd.Model use the Hamilton loop optimal algorithm and Kruskal’s algorithm to establish a optimal search strategy,with a cut-off encounter algorithm to solving the problem.

  1. Monitoring targeted therapy using dual-energy CT: semi-automatic RECIST plus supplementary functional information by quantifying iodine uptake of melanoma metastases

    Sedlmair, M.; Schlemmer, H.P.; Hassel, J.C.; Ganten, M.


    Abstract Aim: Supplementary functional information can contribute to assess response in targeted therapies. The aim of this study was to evaluate semi-automatic RECIST plus iodine uptake (IU) determination in melanoma metastases under BRAF inhibitor (vemurafenib) therapy using dual-energy computed tomography (DECT). Methods: Nine patients with stage IV melanoma treated with a BRAF inhibitor were included. Contrast-enhanced DECT was performed before and twice after treatment onset. Changes in tumor size were assessed according to RECIST. Quantification of IU (absolute value for total IU (mg) and volume-normalized IU (mg/ml)) was based on semi-automatic tumor volume segmentation. The decrease compared with baseline was calculated. Results: The mean change of RECIST diameter sum per patient was −47% at the first follow-up (FU), −56% at the second FU (P < 0.01). The mean normalized IU per patient was −21% at the first FU (P < 0.2) and −45% at the second FU (P < 0.01). Total IU per patient, combining both normalized IU and volume, showed the most pronounced decrease: −89% at the first FU and −90% at the second FU (P < 0.01). Conclusion: Semi-automatic RECIST plus IU quantification in DECT enables objective, easy and fast parameterization of tumor size and contrast medium uptake, thus providing 2 complementary pieces of information for response monitoring applicable in daily routine. PMID:23876444

  2. Air Mouse Solution Based on the IR Small Target Recognize%基于红外小目标识别的空中鼠标解决方案

    李震; 郑建宝; 朱振驰; 林耀聪


    该文提出一种基于运动物体DBT(detect before track)背景消除法识别红外小目标,并将其应用于空中鼠标中。实验主要经过色彩空间转换、阈值分割、图像开运算、连通分析后进行目标识别,并通过摄像头标定获取识别目标在视野中的相对位置。通过单片机以及2.4G通信模块,将除位置信息以外的控制信息传递到电脑。以电脑进行位置运算,单片机进行控制。实验结果表明,该方案识别的目标精度较高,价格低廉,具有一定应用前景。%In this paper, we have proposed one method to identify the infrared small target based on moving object DBT (detect before track) background elimination, and applied it to the air mouse. The target is recognized mainly through the steps below:color space conversion, threshold segmentation, image open operation, connection area analysis, and then identify the target rela-tive position in the field of vision captured .By MCU(micro-controller unit) and 2.4G communication module, the control infor-mation will be transmitted to the computer. Recognized the position by computer and control by the MCU. The result shows that the proposed scheme has higher target accuracy, lower price and a certain application prospect.

  3. Automatic Number Plate Recognition System

    Rajshree Dhruw; Dharmendra Roy


    Automatic Number Plate Recognition (ANPR) is a mass surveillance system that captures the image of vehicles and recognizes their license number. The objective is to design an efficient automatic authorized vehicle identification system by using the Indian vehicle number plate. In this paper we discus different methodology for number plate localization, character segmentation & recognition of the number plate. The system is mainly applicable for non standard Indian number plates by recognizing...

  4. An Approach for Automatic Orientation of Big Point Clouds from the Stationary Scanners Based on the Spherical Targets

    YAO Jili


    Full Text Available Terrestrial laser scanning (TLS technology has high speed of data acquisition, large amount of point cloud, long distance of measuring. However, there are some disadvantages such as distance limitation in target detecting, hysteresis in point clouds processing, low automation and weaknesses of adapting long-distance topographic survey. In this case, we put forward a method on long-range targets detecting in big point clouds orientation. The method firstly searches point cloud rings that contain targets according to their engineering coordinate system. Then the detected rings are divided into sectors to detect targets in a very short time so as to obtain central coordinates of these targets. Finally, the position and orientation parameters of scanner are calculated and point clouds in scanner's own coordinate system(SOCS are converted into engineering coordinate system. The method is able to be applied in ordinary computers for long distance topographic(the distance between scanner and targets ranges from 180 to 700 m survey in mountainous areas with targets radius of 0.162m.

  5. 基于回光强度的平面标靶自动识别方法%Automatic recognition method of planar target based on return light intensity

    王力; 李广云; 张洪新


    平面标靶在中长距离三维激光扫描仪的检校、数据采集、单点测量等环节中发挥着重要作用,而平面标靶的高精度、自动化识别是在其使用中面临的一个关键问题.在分析扫描数据特点的基础上,提出一种基于回光强度的平面标靶自动识别方法.具体的步骤为:改正回光强度以消除距离的影响;基于回光强度进行阈值分割以得到平面标靶点云;提出一种基于扫描线的聚类算法,将平面标靶点云聚集在一起;采用形状检测技术排除非标靶对象;采用回光强度加权法计算平面标靶中心的三维坐标.通过对Riegl公司的三维激光扫描仪LMS Z620获取的实测数据进行实验,结果表明:此方法能完成标靶的快速、全自动识别,点位精度优于2mm,能够满足测量任务的需要.%Planar target plays an important role in the calibration, data collection and single point measurement of 3D laser scanner of middle and long range. The high precision and automatic recognition of planar targets is a key problem in application of laser scanner. A new recognizing method was put forward by using return light intensity based on analyzing the character of scan data. The steps are as follows: the return light intensity was corrected to eliminate the effects of distance. The point cloud of planar target was obtained by threshold segmenting based on return light intensity. A cluster method was proposed to gather the point cloud of planar target. The area detection was adopted to eliminate those objects which were not real target. 3D coordinate of planar target center was computed by adopting return light intensity weighting method. Experimental results obtained by using Riegl's LMS Z620 show that this method can realize the full automatic recognition quickly with the accuracy of point position better than 2 mm and meet the needs of survey task.

  6. FDA Recognized Consensus Standards

    U.S. Department of Health & Human Services — This database consists of those national and international standards recognized by FDA which manufacturers can declare conformity to and is part of the information...

  7. Recognizing teen depression

    ... page: // Recognizing teen depression To use the sharing features on this ... teen's life. Be Aware of the Risk for Teen Depression Your teen is more at risk for ...

  8. A continuous Putonghua recognizer

    Wong, PK; Chan, C.


    A multi-speaker continuous Putonghua recognizer has been developed composing of 20 speaker-dependent recognizer as sub-systems. Each sub-system is a network of hidden Markov models modeling triphones as the fundamental speech units. Over 3 GB of speech data have been collected for training from twenty native Putonghua speakers reading carefully designed tests trying to include all phone-to-phone transitions in Putonghua. A Viterbi path search yields the best speech unit sequence over the HMMn...

  9. Impact of planning CT slice thickness on the accuracy of automatic target registration using the on-board cone-beam CT

    We have evaluated relationship between planning CT slice thickness and the accuracy of automatic target registration using cone-beam CT (CBCT). Planning CT images were acquired with reconstructed slice thickness of 1, 2, 3, 5, and 10 mm for three different phantoms: Penta-Guide phantom, acrylic ball phantom, and pelvic phantom. After correctly placing the phantom at the isocenter using an in-room laser, we purposely displaced it by moving the treatment couch and then obtained CBCT images. Registration between the planning CT and the CBCT was performed using automatic target registration software, and the registration errors were recorded for each planning CT data set with different slice thickness. The respective average and standard deviation of errors for 10 mm slice thickness CT in the lateral, longitudinal, and vertical directions (n=15 data sets) were: 0.7±0.2 mm, 0.8±0.2 mm, and 0.2±0.2 mm for the Penta-Guide phantom; 0.5±0.4 mm, 0.6±0.3 mm, and 0.4±0.3 mm for the acrylic ball phantom and 0.6±0.2 mm, 0.9±0.2 mm, and 0.2±0.2 mm for the pelvic phantom. We found that the mean registration errors were always less than 1 mm regardless of the slice thickness tested. The results suggest that there is no obvious correlation between the planning CT slice thickness and the registration errors. (author)

  10. Recognizing Strokes in Tennis Videos Using Hidden Markov Models

    Petkovic, M.; Jonker, W.; Zivkovic, Z.


    This paper addresses content-based video retrieval with an emphasis on recognizing events in tennis game videos. In particular, we aim at recognizing different classes of tennis strokes using automatic learning capability of Hidden Markov Models. Driven by our domain knowledge, a robust player segme

  11. ROBIN: a platform for evaluating automatic target recognition algorithms: I. Overview of the project and presentation of the SAGEM DS competition

    Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.


    The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set

  12. Recognizing Computational Science

    Bland-Hawthorn, J.


    There are prestigious international awards that recognize the role of theory and experiment in science and mathematics, but there are no awards of a similar stature that explicitly recognize the role of computational science in a scientific field. In 1945, John von Neumann noted that "many branches of both pure and applied mathematics are in great need of computing instruments to break the present stalemate created by the failure of the purely analytical approach to nonlinear problems." In the past few decades, great strides in mathematics and in the applied sciences can be linked to computational science.

  13. Automatic sequences

    Haeseler, Friedrich


    Automatic sequences are sequences which are produced by a finite automaton. Although they are not random they may look as being random. They are complicated, in the sense of not being not ultimately periodic, they may look rather complicated, in the sense that it may not be easy to name the rule by which the sequence is generated, however there exists a rule which generates the sequence. The concept automatic sequences has special applications in algebra, number theory, finite automata and formal languages, combinatorics on words. The text deals with different aspects of automatic sequences, in particular:· a general introduction to automatic sequences· the basic (combinatorial) properties of automatic sequences· the algebraic approach to automatic sequences· geometric objects related to automatic sequences.

  14. Conformation-specific antibodies targeting the trimer-of-hairpins motif of the human T-cell leukemia virus type 1 transmembrane glycoprotein recognize the viral envelope but fail to neutralize viral entry.

    Mirsaliotis, Antonis; Nurkiyanova, Kulpash; Lamb, Daniel; Woof, Jenny M; Brighty, David W


    Human T-cell leukemia virus type 1 (HTLV-1) entry into cells is dependent upon the viral envelope glycoprotein-catalyzed fusion of the viral and cellular membranes. Following receptor activation of the envelope, the transmembrane glycoprotein (TM) is thought to undergo a series of fusogenic conformational transitions through a rod-like prehairpin intermediate to a compact trimer-of-hairpins structure. Importantly, synthetic peptides that interfere with the conformational changes of TM are potent inhibitors of membrane fusion and HTLV-1 entry, suggesting that TM is a valid target for antiviral therapy. To assess the utility of TM as a vaccine target and to explore further the function of TM in HTLV-1 pathogenesis, we have begun to examine the immunological properties of TM. Here we demonstrate that a recombinant trimer-of-hairpins form of the TM ectodomain is strongly immunogenic. Monoclonal antibodies raised against the TM immunogen specifically bind to trimeric forms of TM, including structures thought to be important for membrane fusion. Importantly, these antibodies recognize the envelope on virally infected cells but, surprisingly, fail to neutralize envelope-mediated membrane fusion or infection by pseudotyped viral particles. Our data imply that, even in the absence of overt membrane fusion, there are multiple forms of TM on virally infected cells and that some of these display fusion-associated structures. Finally, we demonstrate that many of the antibodies possess the ability to recruit complement to TM, suggesting that envelope-derived immunogens capable of eliciting a combination of neutralizing and complement-fixing antibodies would be of value as subunit vaccines for intervention in HTLV infections. PMID:17376912

  15. Automatic Parallelization Using OpenMP Based on STL Semantics

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


    Automatic parallelization of sequential applications using OpenMP as a target has been attracting significant attention recently because of the popularity 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 are largely ignored due to the lack of research compilers that are readily able to recognize high level object-oriented abstractions of STL. In this paper, we use ROSE, a multiple-language source-to-source compiler infrastructure, to build a parallelizer that can recognize such high level semantics and parallelize C++ applications using certain STL containers. The idea of our work is to automatically insert OpenMP constructs using extended conventional dependence analysis and the known domain-specific semantics of high-level abstractions with optional assistance from source code annotations. In addition, the parallelizer is followed by an OpenMP translator to translate the generated OpenMP programs into multi-threaded code targeted to a popular OpenMP runtime library. Our work extends the applicability of automatic parallelization and provides another way to take advantage of multicore processors.

  16. Recognize and classify pneumoconiosis

    In the year 2012, out of the 10 most frequently recognized occupational diseases 6 were forms of pneumoconiosis. With respect to healthcare and economic aspects, silicosis and asbestos-associated diseases are of foremost importance. The latter are to be found everywhere and are not restricted to large industrial areas. Radiology has a central role in the diagnosis and evaluation of occupational lung disorders. In cases of known exposure mainly to asbestos and quartz, the diagnosis of pneumoconiosis, with few exceptions will be established primarily by the radiological findings. As these disorders are asymptomatic for a long time they are quite often detected as incidental findings in examinations for other reasons. Therefore, radiologists have to be familiar with the pattern of findings of the most frequent forms of pneumoconiosis and the differential diagnoses. For reasons of equal treatment of the insured a quality-based, standardized performance, documentation and evaluation of radiological examinations is required in preventive procedures and evaluations. Above all, a standardized low-dose protocol has to be used in computed tomography (CT) examinations, although individualized concerning the dose, in order to keep radiation exposure as low as possible for the patient. The International Labour Office (ILO) classification for the coding of chest X-rays and the international classification of occupational and environmental respiratory diseases (ICOERD) classification used since 2004 for CT examinations meet the requirements of the insured and the occupational insurance associations as a means of reproducible and comparable data for decision-making. (orig.)


    Ge Guangying; Chen Lili; Xu Jianjian


    Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving targets pattern recognition on the combination of inter-frame difference and wavelet neural network is presented. The experimental results indicate that the designed BP wavelet network using this algorithm can recognize and classify moving targets rapidly and effectively.

  18. Recognizing one's own face.

    Kircher, T T; Senior, C; Phillips, M L; Rabe-Hesketh, S; Benson, P J; Bullmore, E T; Brammer, M; Simmons, A; Bartels, M; David, A S


    We report two studies of facial self-perception using individually tailored, standardized facial photographs of a group of volunteers and their partners. A computerized morphing procedure was used to merge each target face with an unknown control face. In the first set of experiments, a discrimination task revealed a delayed response time for the more extensively morphed self-face stimuli. In a second set of experiments, functional magnetic resonance imaging (fMRI) was used to measure brain activation while subjects viewed morphed versions of either their own or their partner's face, alternating in blocks with presentation of an unknown face. When subjects viewed themselves (minus activation for viewing an unknown face), increased blood oxygenation was detected in right limbic (hippocampal formation, insula, anterior cingulate), left prefrontal cortex and superior temporal cortex. In the partner (versus unknown) experiment, only the right insula was activated. We suggest that a neural network involving the right hemisphere in conjunction with left-sided associative and executive regions underlies the process of visual self-recognition. Together, this combination produces the unique experience of self-awareness. PMID:11062324

  19. Automatic Speaker Recognition System

    Parul,R. B. Dubey


    Full Text Available Spoken language is used by human to convey many types of information. Primarily, speech convey message via words. Owing to advanced speech technologies, people's interactions with remote machines, such as phone banking, internet browsing, and secured information retrieval by voice, is becoming popular today. Speaker verification and speaker identification are important for authentication and verification in security purpose. Speaker identification methods can be divided into text independent and text-dependent. Speaker recognition is the process of automatically recognizing speaker voice on the basis of individual information included in the input speech waves. It consists of comparing a speech signal from an unknown speaker to a set of stored data of known speakers. This process recognizes who has spoken by matching input signal with pre- stored samples. The work is focussed to improve the performance of the speaker verification under noisy conditions.

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

    Tse, Chi-Shing; Neely, James H.


    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…

  1. Automatic integration of social information in emotion recognition.

    Mumenthaler, Christian; Sander, David


    This study investigated the automaticity of the influence of social inference on emotion recognition. Participants were asked to recognize dynamic facial expressions of emotion (fear or anger in Experiment 1 and blends of fear and surprise or of anger and disgust in Experiment 2) in a target face presented at the center of a screen while a subliminal contextual face appearing in the periphery expressed an emotion (fear or anger) or not (neutral) and either looked at the target face or not. Results of Experiment 1 revealed that recognition of the target emotion of fear was improved when a subliminal angry contextual face gazed toward-rather than away from-the fearful face. We replicated this effect in Experiment 2, in which facial expression blends of fear and surprise were more often and more rapidly categorized as expressing fear when the subliminal contextual face expressed anger and gazed toward-rather than away from-the target face. With the contextual face appearing for 30 ms in total, including only 10 ms of emotion expression, and being immediately masked, our data provide the first evidence that social influence on emotion recognition can occur automatically. PMID:25688908

  2. Infrared Targeting System (IRTS) demonstration

    Ohair, Mark A.; Eucker, Shelly S.; Eucker, Brad A.; Lewis, Tim


    The objective of the Infrared Targeting System (IRTS) is to successfully demonstrate the mission performance that can be achieved in manned air-to-ground targeting applications utilizing a synergistic combination of state of the art active/passive infrared sensor and automatic target recognizer (ATR) technologies. The IRTS program is centered around a demonstration FLIR/Laser Radar/ATR (FLASHER). The FLASHER consists of a dual field of view (2 x 2 degree and 6 x 6 degree) second generation FLIR pixel mapped to a CO2 laser radar, with a FLIR ATR processor, a laser radar ATR processor, and a sensor fusion ATR processor. Following construction and laboratory testing of the IRTS, the system will be installed on a test aircraft and demonstrated in flight against realistic tactical, strategic, and special operations scenarios.

  3. Using automatic programming for simulating reliability network models

    Tseng, Fan T.; Schroer, Bernard J.; Zhang, S. X.; Wolfsberger, John W.


    This paper presents the development of an automatic programming system for assisting modelers of reliability networks to define problems and then automatically generate the corresponding code in the target simulation language GPSS/PC.

  4. Multi-Mode Radar Target Detection and Recognition Using Neural Networks

    Briones, Janette C.; Benjamin Flores; Raul Cruz-Cano


    In typical radar systems, the process of recognizing a target requires human involvement. This human element makes radar systems not fully reliable due to unstable performance that varies between operators. This paper describes an intelligent radar system which addresses this problem in a border surveillance environment. The proposed radar system is capable of automatically detecting and then classifying different targets using an artificial neural network trained with the Levenberg‐Marquardt...

  5. Do You Recognize This Parent?

    Wallace, Edna


    Suggests effective ways to work with parents who may be permissive, busy, detached, overprotective, or negative. Recommends that child care professionals be sensitive and understanding, recognize other demands on parents' time and communicate competitively with them, use terms parents understand, accept various levels of parental involvement, be…

  6. Automatic readout micrometer

    A measuring system is disclosed for surveying and very accurately positioning objects with respect to a reference line. A principal use of this surveying system is for accurately aligning the electromagnets which direct a particle beam emitted from a particle accelerator. Prior art surveying systems require highly skilled surveyors. Prior art systems include, for example, optical surveying systems which are susceptible to operator reading errors, and celestial navigation-type surveying systems, with their inherent complexities. The present invention provides an automatic readout micrometer which can very accurately measure distances. The invention has a simplicity of operation which practically eliminates the possibilities of operator optical reading error, owning to the elimination of traditional optical alignments for making measurements. The invention has an extendable arm which carries a laser surveying target. The extendable arm can be continuously positioned over its entire length of travel by either a coarse or fine adjustment without having the fine adjustment outrun the coarse adjustment until a reference laser beam is centered on the target as indicated by a digital readout. The length of the micrometer can then be accurately and automatically read by a computer and compared with a standardized set of alignment measurements. Due to its construction, the micrometer eliminates any errors due to temperature changes when the system is operated within a standard operating temperature range

  7. Recognizing Prefixes in Scientific Quantities

    Sokolowski, Andrzej


    Although recognizing prefixes in physical quantities is inherent for practitioners, it might not be inherent for students, who do not use prefixes in their everyday life experiences. This deficiency surfaces in AP Physics exams. For example, readers of an AP Physics exam reported "a common mistake of incorrectly converting nanometers to meters." Similar students' mistakes were reported also by AP Chemistry readers "as in previous years, students still had difficulty converting kJ to J." While traditional teaching focuses on memorizing the symbols of prefixes, little attention is given to helping learners recognize a prefix in a given quantity. I noticed in my teaching practice that by making the processes of identifying prefixes more explicit, students make fewer mistakes on unit conversion. Thus, this paper presents an outline of a lesson that focuses on prefix recognition. It is designed for a first-year college physics class; however, its key points can be addressed to any group of physics students.

  8. Recognizing body dysmorphic disorder (dysmorphophobia

    Anukriti Varma


    Full Text Available Dysmorphophobia is a psychiatric condition which frequently presents in the clinics of dermatologists and plastic surgeons. This disorder (also called body dysmorphic disorder is troublesome to the patient whilst being confusing for the doctor. This commonly undiagnosed condition can be detected by a few simple steps. Timely referral to a psychiatrist benefits most patients suffering from it. This article describes with a case vignette, how to recognize body dysmorphic disorder presenting in the dermatological or aesthetic surgery set up. Diagnostic criteria, eitiology, approach to patient, management strategy and when to refer are important learning points. The importance of recognizing this disorder timely and referring the patient to the psychiatrist for appropriate treatment is crucial.This article covers all aspects of body dysmorphic disorder relevant to dermatologists and plastic surgeons and hopes to be useful in a better understanding of this disorder.

  9. Recognizing Body Dysmorphic Disorder (Dysmorphophobia).

    Varma, Anukriti; Rastogi, Rajesh


    Dysmorphophobia is a psychiatric condition which frequently presents in the clinics of dermatologists and plastic surgeons. This disorder (also called body dysmorphic disorder) is troublesome to the patient whilst being confusing for the doctor. This commonly undiagnosed condition can be detected by a few simple steps. Timely referral to a psychiatrist benefits most patients suffering from it. This article describes with a case vignette, how to recognize body dysmorphic disorder presenting in the dermatological or aesthetic surgery set up. Diagnostic criteria, eitiology, approach to patient, management strategy and when to refer are important learning points. The importance of recognizing this disorder timely and referring the patient to the psychiatrist for appropriate treatment is crucial. This article covers all aspects of body dysmorphic disorder relevant to dermatologists and plastic surgeons and hopes to be useful in a better understanding of this disorder. PMID:26644741

  10. Recognizing Body Dysmorphic Disorder (Dysmorphophobia)

    Anukriti Varma; Rajesh Rastogi


    Dysmorphophobia is a psychiatric condition which frequently presents in the clinics of dermatologists and plastic surgeons. This disorder (also called body dysmorphic disorder) is troublesome to the patient whilst being confusing for the doctor. This commonly undiagnosed condition can be detected by a few simple steps. Timely referral to a psychiatrist benefits most patients suffering from it. This article describes with a case vignette, how to recognize body dysmorphic disorder presenting in...

  11. Recognizing Anaphora Reference in Persian Sentences

    Farshid Fallahi


    Full Text Available Finding the reference of pronouns in a piece of text, which is a type of co-reference resolution, is an important task in discourse analysis and processing natural language texts.Pronoun reference is the noun that is replaced by the pronoun.In this paper, we propose a rule-based method for pronoun reference resolution in Persian texts. Our method exploits rules to recognize the reference of various types of pronouns in a 3-sentences interval. An automatic reference resolution system is developed based on the proposed method as the first pronoun reference resolution system for the Persian language. The experimental results show admissible accuracy in test cases. In this paper firstly we will describe some problems and challenges in detecting pronoun references and have an overview of related works in this field. In the next sections, after a brief description of the proposed method and the developed system, its features and architecture, we will discuss its components in detail. Then we will explain the experimental results and discuss further works to improve the system.

  12. Antarctic skuas recognize individual humans.

    Lee, Won Young; Han, Yeong-Deok; Lee, Sang-Im; Jablonski, Piotr G; Jung, Jin-Woo; Kim, Jeong-Hoon


    Recent findings report that wild animals can recognize individual humans. To explain how the animals distinguish humans, two hypotheses are proposed. The high cognitive abilities hypothesis implies that pre-existing high intelligence enabled animals to acquire such abilities. The pre-exposure to stimuli hypothesis suggests that frequent encounters with humans promote the acquisition of discriminatory abilities in these species. Here, we examine individual human recognition abilities in a wild Antarctic species, the brown skua (Stercorarius antarcticus), which lives away from typical human settlements and was only recently exposed to humans due to activities at Antarctic stations. We found that, as nest visits were repeated, the skua parents responded at further distances and were more likely to attack the nest intruder. Also, we demonstrated that seven out of seven breeding pairs of skuas selectively responded to a human nest intruder with aggression and ignored a neutral human who had not previously approached the nest. The results indicate that Antarctic skuas, a species that typically inhabited in human-free areas, are able to recognize individual humans who disturbed their nests. Our findings generally support the high cognitive abilities hypothesis, but this ability can be acquired during a relatively short period in the life of an individual as a result of interactions between individual birds and humans. PMID:26939544

  13. Around the laboratories: Rutherford: Successful tests on bubble chamber target technique; Stanford (SLAC): New storage rings proposal; Berkeley: The HAPPE project to examine cosmic rays with superconducting magnets; The 60th birthday of Professor N.N. Bogolyubov; Argonne: Performance of the automatic film measuring system POLLY II


    Around the laboratories: Rutherford: Successful tests on bubble chamber target technique; Stanford (SLAC): New storage rings proposal; Berkeley: The HAPPE project to examine cosmic rays with superconducting magnets; The 60th birthday of Professor N.N. Bogolyubov; Argonne: Performance of the automatic film measuring system POLLY II

  14. Recognizing child maltreatment in Bangladesh.

    Khan, N Z; Lynch, M A


    Concern is increasing in Bangladesh over child abuse, neglect, and exploitation. Children from all walks of life are being treated at the Child Development Center (CDC) Dhaka Shishu Hospital for neurodevelopmental problems resulting from abuse and neglect. Efforts to protect children from sexual harassment result in girls being isolated at home or married at an early age. Some young brides are eventually abandoned and forced into prostitution. Early marriage reflects the lack of acknowledgement of a period of adolescence and the belief that puberty is a marker of adulthood. Many girls aged 8-16 are employed as live-in domestic servants, and many suffer sexual as well as emotional abuse. Garment factories, on the other hand, offer girls an escape from extreme poverty, domestic service, and early marriage but are threatened by forces that condemn child labor. Rather than ending such opportunities, employers should be encouraged to provide employees with educational and welfare facilities. The CDC seeks to explore the extent and depth of the problem of child abuse while recognizing the special circumstances at work in Bangladesh. It is also necessary to raise awareness of these issues and of the discrepancies between the law and cultural practices. For example, the legal marriage age of 18 years for a woman and 21 years for a man is often ignored. Additional forms of abuse receiving the attention of women's organizations and human rights groups include the trafficking of children. A network of concerned organizations should be created to work against the child abuse, neglect, and exploitation that Bangladesh has pledged to overcome by signing the UN Convention on the Rights of the Child. PMID:9280385

  15. Automatic processing of dominance and submissiveness

    Moors, Agnes; De Houwer, Jan


    We investigated whether people are able to detect in a relatively automatic manner the dominant or submissive status of persons engaged in social interactions. Using a variant of the affective Simon task (De Houwer & Eelen, 1998), we demonstrated that the verbal response DOMINANT or SUBMISSIVE was facilitated when it had to be made to a target person that was respectively dominant or submissive. These results provide new information about the automatic nature of appraisals and ...

  16. Recognizing foreground-background interaction

    Jenkins, Jeffrey; Szu, Harold


    Can the background affect a foreground target in distant, low-quality imagery? If it does, it might occur in our mind, or perhaps it may represent a snapshot of our early vision. An affirmative answer, one way or another, may affect our current understanding of this phenomena and potentially for related applications. How can we be sure about this in the psycho-physical sense? We begin with the physiology of our brain's homeostasis, of which an isothermal equilibrium is characterized by the minimum of Helmholtz isothermal Free Energy: A = U - T0S >= 0, where T0 = 37°C, the Boltzmann Entropy S = KB1n(W), and U is the unknown internal energy to be computed.

  17. Distributed image processing for automatic target recognition

    Cozien, Roger F.


    Our purpose is, in medium term, to detect in air images, characteristic shapes and objects such as airports, industrial plants, planes, tanks, trucks, . with great accuracy and low rate of mistakes. However, we also want to value whether the link between neural networks and multi-agents systems is relevant and effective. If it appears to be really effective, we hope to use this kind of technology in other fields. That would be an easy and convenient way to depict and to use the agents' knowledge which is distributed and fragmented. After a first phase of preliminary tests to know if agents are able to give relevant information to a neural network, we verify that only a few agents running on an image are enough to inform the network and let it generalize the agents' distributed and fragmented knowledge. In a second phase, we developed a distributed architecture allowing several multi-agents systems running at the same time on different computers with different images. All those agents send information to a "multi neural networks system" whose job is to identify the shapes detected by the agents. The name we gave to our project is Jarod.

  18. Arabic word recognizer for mobile applications

    Khanna, Nitin; Abdollahian, Golnaz; Brame, Ben; Boutin, Mireille; Delp, Edward J.


    When traveling in a region where the local language is not written using a "Roman alphabet," translating written text (e.g., documents, road signs, or placards) is a particularly difficult problem since the text cannot be easily entered into a translation device or searched using a dictionary. To address this problem, we are developing the "Rosetta Phone," a handheld device (e.g., PDA or mobile telephone) capable of acquiring an image of the text, locating the region (word) of interest within the image, and producing both an audio and a visual English interpretation of the text. This paper presents a system targeted for interpreting words written in Arabic script. The goal of this work is to develop an autonomous, segmentation-free Arabic phrase recognizer, with computational complexity low enough to deploy on a mobile device. A prototype of the proposed system has been deployed on an iPhone with a suitable user interface. The system was tested on a number of noisy images, in addition to the images acquired from the iPhone's camera. It identifies Arabic words or phrases by extracting appropriate features and assigning "codewords" to each word or phrase. On a dictionary of 5,000 words, the system uniquely mapped (word-image to codeword) 99.9% of the words. The system has a 82% recognition accuracy on images of words captured using the iPhone's built-in camera.

  19. Automatic input rectification

    Long, Fan; Ganesh, Vijay; Carbin, Michael James; Sidiroglou, Stelios; Rinard, Martin


    We present a novel technique, automatic input rectification, and a prototype implementation, SOAP. SOAP learns a set of constraints characterizing typical inputs that an application is highly likely to process correctly. When given an atypical input that does not satisfy these constraints, SOAP automatically rectifies the input (i.e., changes the input so that it satisfies the learned constraints). The goal is to automatically convert potentially dangerous inputs into typical inputs that the ...

  20. Automatic Fiscal Stabilizers

    Narcis Eduard Mitu


    Full Text Available Policies or institutions (built into an economic system that automatically tend to dampen economic cycle fluctuations in income, employment, etc., without direct government intervention. For example, in boom times, progressive income tax automatically reduces money supply as incomes and spendings rise. Similarly, in recessionary times, payment of unemployment benefits injects more money in the system and stimulates demand. Also called automatic stabilizers or built-in stabilizers.

  1. Recognizing Variable Environments The Theory of Cognitive Prism

    Dong, Tiansi


    Normal adults do not have any difficulty in recognizing their homes. But can artificial systems do in the same way as humans? This book collects interdisciplinary evidences and presents an answer from the perspective of computing, namely, the theory of cognitive prism. To recognize an environment, an intelligent system only needs to classify objects, structures them based on the connection relation (not through measuring!), subjectively orders the objects, and compares with the target environment, whose knowledge is similarly structured. The intelligent system works, therefore, like a prism: when a beam of light (a scene) reaches (is perceived) to an optical prism (by an intelligent system), some light (objects) is reflected (are neglected), those passed through (the recognized objects) are distorted (are ordered differently). So comes the term 'cognitive prism'! Two fundamental propositions used in the theory can be informally stated as follow: an orientation relation is a kind of distance comparison relatio...

  2. Automatic differentiation bibliography

    Corliss, G.F. (comp.)


    This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

  3. Automatic contrast: evidence that automatic comparison with the social self affects evaluative responses.

    Ruys, Kirsten I; Spears, Russell; Gordijn, Ernestine H; de Vries, Nanne K


    The aim of the present research was to investigate whether unconsciously presented affective information may cause opposite evaluative responses depending on what social category the information originates from. We argue that automatic comparison processes between the self and the unconscious affective information produce this evaluative contrast effect. Consistent with research on automatic behaviour, we propose that when an intergroup context is activated, an automatic comparison to the social self may determine the automatic evaluative responses, at least for highly visible categories (e.g. sex, ethnicity). Contrary to previous research on evaluative priming, we predict automatic contrastive responses to affective information originating from an outgroup category such that the evaluative response to neutral targets is opposite to the valence of the suboptimal primes. Two studies using different intergroup contexts provide support for our hypotheses. PMID:17705936

  4. Techniques for automatic speech recognition

    Moore, R. K.


    A brief insight into some of the algorithms that lie behind current automatic speech recognition system is provided. Early phonetically based approaches were not particularly successful, due mainly to a lack of appreciation of the problems involved. These problems are summarized, and various recognition techniques are reviewed in the contect of the solutions that they provide. It is pointed out that the majority of currently available speech recognition equipments employ a "whole-word' pattern matching approach which, although relatively simple, has proved particularly successful in its ability to recognize speech. The concepts of time-normalizing plays a central role in this type of recognition process and a family of such algorithms is described in detail. The technique of dynamic time warping is not only capable of providing good performance for isolated word recognition, but how it is also extended to the recognition of connected speech (thereby removing one of the most severe limitations of early speech recognition equipment).

  5. Application Accuracy of Automatic Registration in Frameless Stereotaxy

    Rachinger, Jens; Keller, Boris von; Ganslandt, Oliver; Fahlbusch, Rudolf; Nimsky, Christopher


    Objective: We compared the application accuracy of an infrared- based neuronavigation system when used with a novel automatic registration with its application accuracy when standard fiducial-based registration is performed. Methods: The automatic referencing tool is based on markers that are integrated in the headrest holder we routinely use in our intraoperative magnetic resonance imaging (MRI) setting and can be detected by the navigation software automatically. For navigation targeting we...

  6. Annual review in automatic programming

    Goodman, Richard


    Annual Review in Automatic Programming, Volume 2 is a collection of papers that discusses the controversy about the suitability of COBOL as a common business oriented language, and the development of different common languages for scientific computation. A couple of papers describes the use of the Genie system in numerical calculation and analyzes Mercury autocode in terms of a phrase structure language, such as in the source language, target language, the order structure of ATLAS, and the meta-syntactical language of the assembly program. Other papers explain interference or an ""intermediate

  7. Using Nanoinformatics Methods for Automatically Identifying Relevant Nanotoxicology Entities from the Literature

    Miguel García-Remesal


    Full Text Available Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets to 93.0% (routes of exposure, while recall values range from 82.6% (routes of exposure to 87.4% (toxic effects. These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER-dependent tasks, such as for instance augmented reading or semantic searches. This research is a “proof of concept” that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine.

  8. Using nanoinformatics methods for automatically identifying relevant nanotoxicology entities from the literature.

    García-Remesal, Miguel; García-Ruiz, Alejandro; Pérez-Rey, David; de la Iglesia, Diana; Maojo, Víctor


    Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets) to 93.0% (routes of exposure), while recall values range from 82.6% (routes of exposure) to 87.4% (toxic effects). These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER)-dependent tasks, such as for instance augmented reading or semantic searches. This research is a "proof of concept" that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine. PMID:23509721

  9. The Developmental Dimensions of Recognizing Racist Thoughts

    Torres, Vasti


    This study focuses on understanding the developmental process that occurs when racist ideas are recognized as a part of college students' thought processes. Longitudinal data were collected from 29 Latino/a college students in order to illustrate how these students made meaning of racist thoughts when they began to recognize it. The framework of…

  10. Vitrification: Machines learn to recognize glasses

    Ceriotti, Michele; Vitelli, Vincenzo


    The dynamics of a viscous liquid undergo a dramatic slowdown when it is cooled to form a solid glass. Recognizing the structural changes across such a transition remains a major challenge. Machine-learning methods, similar to those Facebook uses to recognize groups of friends, have now been applied to this problem.

  11. Neuroanatomical automatic segmentation in brain cancer patients

    D’Haese, P.; Niermann, K; Cmelak, A.; Donnelly, E.; Duay, V.; Li, R; Dawant, B.


    Conformally prescribed radiation therapy for brain cancer requires precisely defining the target treatment area, as well as delineating vital brain structures which must be spared from radiotoxicity. The current clinical practice of manually segmenting brain structures can be complex and exceedingly time consuming. Automatic computeraided segmentation methods have been proposed to increase efficiency and reproducibility in developing radiation treatment plans. Previous studies have establishe...

  12. Anti-peptide aptamers recognize amino acid sequence and bind a protein epitope.

    Xu, W; Ellington, A. D.


    In vitro selection of nucleic acid binding species (aptamers) is superficially similar to the immune response. Both processes produce biopolymers that can recognize targets with high affinity and specificity. While antibodies are known to recognize the sequence and conformation of protein surface features (epitopes), very little is known about the precise interactions between aptamers and their epitopes. Therefore, aptamers that could recognize a particular epitope, a peptide fragment of huma...

  13. Immune Cells in Blood Recognize Tumors

    NCI scientists have developed a novel strategy for identifying immune cells circulating in the blood that recognize specific proteins on tumor cells, a finding they believe may have potential implications for immune-based therapies.

  14. Automatic Implantable Cardiac Defibrillator

    Full Text Available Automatic Implantable Cardiac Defibrillator February 19, 2009 Halifax Health Medical Center, Daytona Beach, FL Welcome to Halifax Health Daytona Beach, Florida. Over the next hour you' ...

  15. Automatic Payroll Deposit System.

    Davidson, D. B.


    The Automatic Payroll Deposit System in Yakima, Washington's Public School District No. 7, directly transmits each employee's salary amount for each pay period to a bank or other financial institution. (Author/MLF)

  16. Automatic Arabic Text Classification

    Al-harbi, S; Almuhareb, A.; Al-Thubaity , A; Khorsheed, M. S.; Al-Rajeh, A.


    Automated document classification is an important text mining task especially with the rapid growth of the number of online documents present in Arabic language. Text classification aims to automatically assign the text to a predefined category based on linguistic features. Such a process has different useful applications including, but not restricted to, e-mail spam detection, web page content filtering, and automatic message routing. This paper presents the results of experiments on documen...

  17. Automatic graphene transfer system for improved material quality and efficiency

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


    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 proce...

  18. Recognizing Thousands of Legal Entities through Instance-based Visual Classification

    Leveau, Valentin; Joly, Alexis; Buisson, Olivier; Letessier, Pierre; Valduriez, Patrick


    This paper considers the problem of recognizing legal en-tities in visual contents in a similar way to named-entity recognizers for text documents. Whereas previous works were restricted to the recognition of a few tens of logotypes, we generalize the problem to the recognition of thousands of legal persons, each being modeled by a rich corporate identity automatically built from web images. We intro-duce a new geometrically-consistent instance-based classifi-cation method that is shown to ou...

  19. Automatic recognition of lactating sow behaviors through depth image processing

    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...

  20. Survey of evaluation methods in image complexity of target and background

    Xiao, Bo; Duan, Jin; Zhu, Yong; Chen, Yanqin; Li, Guangming


    In the domain of target recognition, the image complexity of target and background is used to describe the difficult degree of extracting and recognizing target from complex background, which has important guiding significance and widely application prospect in a lot of domains such as biological medical, information encrypt, image compression, meteorological analysis, automatic target recognition. This paper comprehensively took the innate characteristics of target and the target local background characteristic into consideration, which affected the algorithm performance of target extraction and recognition, then made generalizations of three classes of evaluation methods: methods based on the target characteristic, including the target shape characteristic, the gray standard deviation of target pixels, the target Local background entropy difference, etc; methods based on the target similitude, including the edge profile and structural characteristic similitude between target and phony target; methods based on the background characteristic, including texture characteristic edge ratio, etc. And on this basis, we made research on the relationship of structural features and evaluation parameters, and analyzed the foundation and properties of each method by contrast. Thoughts and foresights of this field are given at the end of this paper.

  1. Weakly Supervised Models For Recognizing And Clustering High-level Complex Events In Video

    Vahdat, Arash


    In the last decade, we have witnessed exponential growth of visual content in internet social media such as YouTube or Facebook. Developing automatic analysis tools is becoming essential to summarize and retrieve desired videos from a large collection on the internet. In this thesis, we propose frameworks for recognizing and clustering high-level events in unconstrained internet videos. The events considered here are complex events such as ``wedding ceremony'' or ``getting a vehicle unstuck''...

  2. Setswana Speech Recognizer for Computer Based Applications

    Oratile Leteane


    Full Text Available This study is the development and adaptation of Setswana speech recognizer into computer applications. Setswana database is used together with sphinx decoder to build a generic Setswana speech recognizer. The recognizer is then adapted into a developed game called General Knowledge Game (GKG in which the user plays the game using Setswana speech. The developed recognizers level of accuracy was 60 percent on the worst case. The recognizer improves to more than 80 percent when shorter words are used to drive the application. Participants have shown that they prefer using speech driven applications over traditional approach of using mouse and keyboard. Analysis shows that though it is more effective to use keyboard and mouse to drive computer applications, users still prefer speech interaction because HCI method is easy to learn particularly for the users who are semi-literate and illiterate. It shows that using traditional approach (mouse and keyboard requires some degree of literacy for someone to be competent while with speech interaction, anyone can use

  3. Recognizing, Confronting, and Eliminating Workplace Bullying.

    Berry, Peggy Ann; Gillespie, Gordon L; Fisher, Bonnie S; Gormley, Denise K


    Workplace bullying (WPB) behaviors negatively affect nurse productivity, satisfaction, and retention, and hinder safe patient care. The purpose of this article is to define WPB, differentiate between incivility and WPB, and recommend actions to prevent WPB behaviors. Informed occupational and environmental health nurses and nurse leaders must recognize, confront, and eliminate WPB in their facilities and organizations. Recognizing, confronting, and eliminating WPB behaviors in health care is a crucial first step toward sustained improvements in patient care quality and the health and safety of health care employees. PMID:27053288

  4. Recognizing textual entailment models and applications

    Dagan, Ido; Sammons, Mark


    In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any sp

  5. Two Systems for Automatic Music Genre Recognition

    Sturm, Bob L.


    trials of cross-validation. Second, we test the robustness of each system to spectral equalization. Finally, we test how well human subjects recognize the genres of music excerpts composed by each system to be highly genre representative. Our results suggest that neither high-performing system has a......We re-implement and test two state-of-the-art systems for automatic music genre classification; but unlike past works in this area, we look closer than ever before at their behavior. First, we look at specific instances where each system consistently applies the same wrong label across multiple...

  6. Automatic Program Development

    Automatic Program Development is a tribute to Robert Paige (1947-1999), our accomplished and respected colleague, and moreover our good friend, whose untimely passing was a loss to our academic and research community. We have collected the revised, updated versions of the papers published in his...... honor in the Higher-Order and Symbolic Computation Journal in the years 2003 and 2005. Among them there are two papers by Bob: (i) a retrospective view of his research lines, and (ii) a proposal for future studies in the area of the automatic program derivation. The book also includes some papers by...... members of the IFIP Working Group 2.1 of which Bob was an active member. All papers are related to some of the research interests of Bob and, in particular, to the transformational development of programs and their algorithmic derivation from formal specifications. Automatic Program Development offers a...

  7. Automatic utilities auditing

    Smith, Colin Boughton [Energy Metering Technology (United Kingdom)


    At present, energy audits represent only snapshot situations of the flow of energy. The normal pattern of energy audits as seen through the eyes of an experienced energy auditor is described. A brief history of energy auditing is given. It is claimed that the future of energy auditing lies in automatic meter reading with expert data analysis providing continuous automatic auditing thereby reducing the skill element. Ultimately, it will be feasible to carry out auditing at intervals of say 30 minutes rather than five years.

  8. Automatic Camera Control

    Burelli, Paolo; Preuss, Mike


    Automatically generating computer animations is a challenging and complex problem with applications in games and film production. In this paper, we investigate howto translate a shot list for a virtual scene into a series of virtual camera configurations — i.e automatically controlling the virtual...... camera. We approach this problem by modelling it as a dynamic multi-objective optimisation problem and show how this metaphor allows a much richer expressiveness than a classical single objective approach. Finally, we showcase the application of a multi-objective evolutionary algorithm to generate a shot...

  9. Automatic text summarization

    Torres Moreno, Juan Manuel


    This new textbook examines the motivations and the different algorithms for automatic document summarization (ADS). We performed a recent state of the art. The book shows the main problems of ADS, difficulties and the solutions provided by the community. It presents recent advances in ADS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several exemples are included in order to clarify the theoretical concepts.  The books currently available in the area of Automatic Document Summarization are not recent. Powerful algorithms have been develop

  10. Engineering alumnus John Sparks recognized for contributions

    Nystrom, Lynn A.


    Virginia Tech's College of Engineering presented its 2008 Distinguished Service Award to mechanical engineering alumnus John Sparks, director of engineering and technology programs at Aerojet, a GenCorp Inc. company, recognized as a major space and defense leader specializing in missile and space propulsion as well as defense and armaments.

  11. Automatic Implantable Cardiac Defibrillator

    Full Text Available ... chronic obstructive lung disease or emphysema, automobile or accidents of all kind, diabetes -- all combined. You put ... up in an emergency room -- say an automobile accident or something -- and somebody recognizes there’s a pacemaker ...

  12. Special hydrogen target (Prop. 210)

    This guide contains a description of the electrical control and automatic vacuum systems for the Special Hydrogen Target (Prop. 210) together with the flow diagram and the mimic control panel layout for the system. (U.K.)

  13. Automatic Dance Lesson Generation

    Yang, Yang; Leung, H.; Yue, Lihua; Deng, LiQun


    In this paper, an automatic lesson generation system is presented which is suitable in a learning-by-mimicking scenario where the learning objects can be represented as multiattribute time series data. The dance is used as an example in this paper to illustrate the idea. Given a dance motion sequence as the input, the proposed lesson generation…

  14. Automatic Complexity Analysis

    Rosendahl, Mads


    One way to analyse programs is to to derive expressions for their computational behaviour. A time bound function (or worst-case complexity) gives an upper bound for the computation time as a function of the size of input. We describe a system to derive such time bounds automatically using abstract...

  15. Automatic detection of abnormalities in mammograms

    Suhail, Zobia; Sarwar, Mansoor; Murtaza, Kashif


    Background In recent years, an increased interest has been seen in the area of medical image processing and, as a consequence, Computer Aided Diagnostic (CAD) systems. The basic purpose of CAD systems is to assist doctors in the process of diagnosis. CAD systems, however, are quite expensive, especially, in most of the developing countries. Our focus is on developing a low-cost CAD system. Today, most of the CAD systems regarding mammogram classification target automatic detection of calcific...

  16. Recognizing frequency characteristics of gas sensor array


    A novel method based on independent component analyzing (ICA) in frequency domain to distinguish the frequency characteristics of multi-sensor system is presented. The conditions of this type of ICA are considered and each step of resolving the problem is discussed. For a two gas sensor array, the frequency characteristics including amplitude-frequency and phase-frequency are recognized by this method, and cross-sensitivity between them is also eliminated. From the principle of similarity, the recognition m...

  17. How does a dictation machine recognize speech?

    Dutoit, T.; Couvreur, L.; Bourlard, Hervé


    There is magic (or is it witchcraft?) in a speech recognizer that transcribes continuous radio speech into text with a word accuracy of even not more than 50%. The extreme difficulty of this task, tough, is usually not perceived by the general public. This is because we are almost deaf to the infinite acoustic variations that accompany the production of vocal sounds, which arise from physiological constraints (co-articulation), but also from the acoustic environment (additive or convolutional...

  18. Textual Entailment Recognizing by Theorem Proving Approach

    Tatar, Doina


    In this paper we present two original methods for recognizing textual inference. First one is a modified resolution method such that some linguistic considerations are introduced in the unification of two atoms. The approach is possible due to the recent methods of transforming texts in logic formulas. Second one is based on semantic relations in text, as presented in WordNet. Some similarities between these two methods are remarked.

  19. Siamangs (Hylobates syndactylus) Recognize their Mirror Image

    Heschl, Adolf; Fuchsbichler, Conny


    The ability to recognize oneself in the mirror is assumed to represent an important step towards a higher level of animal intelligence that, ultimately, can lead to human-like self-awareness and empathy. Even though rarely successful in the classical mark test, the siamang’s spontaneous behavior in front of the mirror, a visually controlled manipulation of its face, suggests that it interprets the reflection as belonging to itself. As a consequence, the cognitive status of the gibbons may nee...

  20. Recognizing team formation in american football

    Atmosukarto, Indriyati


    Most existing software packages for sports video analysis require manual annotation of important events in the video. Despite being the most popular sport in the United States, most American football game analysis is still done manually. Line of scrimmage and offensive team formation recognition are two statistics that must be tagged by American Football coaches when watching and evaluating past play video clips, a process which takesmanyman hours per week. These two statistics are the building blocks for more high-level analysis such as play strategy inference and automatic statistic generation. In this chapter, we propose a novel framework where given an American football play clip, we automatically identify the video frame in which the offensive team lines in formation (formation frame), the line of scrimmage for that play, and the type of player formation the offensive team takes on. The proposed framework achieves 95% accuracy in detecting the formation frame, 98% accuracy in detecting the line of scrimmage, and up to 67%accuracy in classifying the offensive team’s formation. To validate our framework, we compiled a large dataset comprising more than 800 play-clips of standard and high definition resolution from real-world football games. This dataset will be made publicly available for future comparison.

  1. Automatic indexing, compiling and classification

    A review of the principles of automatic indexing, is followed by a comparison and summing-up of work by the authors and by a Soviet staff from the Moscou INFORM-ELECTRO Institute. The mathematical and linguistic problems of the automatic building of thesaurus and automatic classification are examined

  2. The automatic NMR gaussmeter

    The paper describes the automatic gaussmeter operating according to the principle of nuclear magnetic resonance. There have been discussed the operating principle, the block diagram and operating parameters of the meter. It can be applied to measurements of induction in electromagnets of wide-line radio-spectrometers EPR and NMR and in calibration stands of magnetic induction values. Frequency range of an autodyne oscillator from 0,6 up to 86 MHz for protons is corresponding to the field range from 0.016 up to 2T. Applicaton of other nuclei, such as 7Li and 2D is also foreseen. The induction measurement is carried over automatically, and the NMR signal and value of measured induction are displayed on a monitor screen. (author)

  3. Automatic trend estimation

    Vamos¸, C˘alin


    Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificial time series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementing these original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the proper interpretation of their results. We illustrate the functioning of the analyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in our book is already in common use in computational and statistical physics.

  4. Automatic Wall Painting Robot



    The Primary Aim Of The Project Is To Design, Develop And Implement Automatic Wall Painting Robot Which Helps To Achieve Low Cost Painting Equipment. Despite The Advances In Robotics And Its Wide Spreading Applications, Interior Wall Painting Has Shared Little In Research Activities. The Painting Chemicals Can Cause Hazards To The Human Painters Such As Eye And Respiratory System Problems. Also The Nature Of Painting Procedure That Requires Repeated Work And Hand Rising Makes It Boring, Time A...

  5. Automatic Program Reports

    Lígia Maria da Silva Ribeiro; Gabriel de Sousa Torcato David


    To profit from the data collected by the SIGARRA academic IS, a systematic setof graphs and statistics has been added to it and are available on-line. Thisanalytic information can be automatically included in a flexible yearly report foreach program as well as in a synthesis report for the whole school. Somedifficulties in the interpretation of some graphs led to the definition of new keyindicators and the development of a data warehouse across the university whereeffective data consolidation...

  6. Automatic Inductive Programming Tutorial

    Aler, Ricardo


    Computers that can program themselves is an old dream of Artificial Intelligence, but only nowadays there is some progress of remark. In relation to Machine Learning, a computer program is the most powerful structure that can be learned, pushing the final goal well beyond neural networks or decision trees. There are currently many separate areas, working independently, related to automatic programming, both deductive and inductive. The first goal of this tutorial is to give to the attendants ...

  7. Automatic food decisions

    Mueller Loose, Simone

    Consumers' food decisions are to a large extent shaped by automatic processes, which are either internally directed through learned habits and routines or externally influenced by context factors and visual information triggers. Innovative research methods such as eye tracking, choice experiments...... and food diaries allow us to better understand the impact of unconscious processes on consumers' food choices. Simone Mueller Loose will provide an overview of recent research insights into the effects of habit and context on consumers' food choices....

  8. Automatic Differentiation Variational Inference

    Kucukelbir, Alp; Tran, Dustin; Ranganath, Rajesh; Gelman, Andrew; Blei, David M.


    Probabilistic modeling is iterative. A scientist posits a simple model, fits it to her data, refines it according to her analysis, and repeats. However, fitting complex models to large data is a bottleneck in this process. Deriving algorithms for new models can be both mathematically and computationally challenging, which makes it difficult to efficiently cycle through the steps. To this end, we develop automatic differentiation variational inference (ADVI). Using our method, the scientist on...

  9. Automaticity or active control

    Tudoran, Ana Alina; Olsen, Svein Ottar

    This study addresses the quasi-moderating role of habit strength in explaining action loyalty. A model of loyalty behaviour is proposed that extends the traditional satisfaction–intention–action loyalty network. Habit strength is conceptualised as a cognitive construct to refer to the psychologic......, respectively, between intended loyalty and action loyalty. At high levels of habit strength, consumers are more likely to free up cognitive resources and incline the balance from controlled to routine and automatic-like responses....

  10. Automatic digital image registration

    Goshtasby, A.; Jain, A. K.; Enslin, W. R.


    This paper introduces a general procedure for automatic registration of two images which may have translational, rotational, and scaling differences. This procedure involves (1) segmentation of the images, (2) isolation of dominant objects from the images, (3) determination of corresponding objects in the two images, and (4) estimation of transformation parameters using the center of gravities of objects as control points. An example is given which uses this technique to register two images which have translational, rotational, and scaling differences.

  11. Real-time automatic registration in optical surgical navigation

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


    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.


    Schroer, B. J.


    Development of some of the space program's large simulation projects -- like the project which involves simulating the countdown sequence prior to spacecraft liftoff -- requires the support of automated tools and techniques. The number of preconditions which must be met for a successful spacecraft launch and the complexity of their interrelationship account for the difficulty of creating an accurate model of the countdown sequence. Researchers developed ANPS for the Nasa Marshall Space Flight Center to assist programmers attempting to model the pre-launch countdown sequence. Incorporating the elements of automatic programming as its foundation, ANPS aids the user in defining the problem and then automatically writes the appropriate simulation program in GPSS/PC code. The program's interactive user dialogue interface creates an internal problem specification file from user responses which includes the time line for the countdown sequence, the attributes for the individual activities which are part of a launch, and the dependent relationships between the activities. The program's automatic simulation code generator receives the file as input and selects appropriate macros from the library of software modules to generate the simulation code in the target language GPSS/PC. The user can recall the problem specification file for modification to effect any desired changes in the source code. ANPS is designed to write simulations for problems concerning the pre-launch activities of space vehicles and the operation of ground support equipment and has potential for use in developing network reliability models for hardware systems and subsystems. ANPS was developed in 1988 for use on IBM PC or compatible machines. The program requires at least 640 KB memory and one 360 KB disk drive, PC DOS Version 2.0 or above, and GPSS/PC System Version 2.0 from Minuteman Software. The program is written in Turbo Prolog Version 2.0. GPSS/PC is a trademark of Minuteman Software. Turbo Prolog

  13. An Efficient Approach to Recognize Fingerprints

    Muhammad Sheikh Sadi


    Full Text Available Fingerprint analysis is typically based on the position and pattern of detected singular points in the fingerprint images. These singular points (cores and deltas represent the characteristics of local ridge patterns, determine the topological structure (i.e., fingerprint type and largely influence the orientation field. A core-delta relation is used as a global constraint for the final selection of singular points. This paper proposed an approach for singular points detection and then recognizes fingerprints based on singular points position and their relative distances. Experimental results show that the approach is efficient and robust, giving better results than existing dominant approaches.

  14. Recognizing frequency characteristics of gas sensor array


    A novel method based on independent component analyzing (ICA) in frequency domain to distinguish the frequency characteristics of multi-sensor system is presented. The conditions of this type of ICA are considered and each step of resolving the problem is discussed. For a two gas sensor array, the frequency characteristics including amplitude-frequency and phase-frequency are recognized by this method, and cross-sensitivity between them is also eliminated. From the principle of similarity, the recognition mean square error is no more than 0.085.

  15. Automatic Implantable Cardiac Defibrillator

    Full Text Available ... metal device again. And when you walk through security you'll set off the security alarms probably. And so somebody wants to know ... are recognized and honored very, very clearly at security checkpoints. And you just present them, explain the ...

  16. Automatic registration of laser-scanned point clouds based on planar features

    Li, Minglei; Gao, Xinyuan; Wang, Li; Li, Guangyun


    Automatic multistation registration of laser-scanned point clouds is a research hotspot in laser-scanned point clouds registration. Some targets such as common buildings have plenty of planar features, and using these features as constraints properly can bring about high accuracy registration results. Starting from this, a new automatic multistation registration method using homologous planar features of two scan stations was proposed. In order to recognize planes from different scan stations and get plane equations in corresponding scan station coordinate systems, k-means dynamic clustering method was improved to be adaptive and robust. And to match the homologous planes of the two scan stations, two different procedures were proposed, respectively, one of which was based on the "common" relationship between planes and the other referenced RANSAC algorithm. And the transformation parameters of the two scan station coordinate systems were calculated after homologous plane matching. Finally, the transformation parameters based on the optimal match of planes was adopted as the final registration result. Comparing with ICP algorithm in experiment, the method is proved to be effective.

  17. Traceability Through Automatic Program Generation

    Richardson, Julian; Green, Jeff


    Program synthesis is a technique for automatically deriving programs from specifications of their behavior. One of the arguments made in favour of program synthesis is that it allows one to trace from the specification to the program. One way in which traceability information can be derived is to augment the program synthesis system so that manipulations and calculations it carries out during the synthesis process are annotated with information on what the manipulations and calculations were and why they were made. This information is then accumulated throughout the synthesis process, at the end of which, every artifact produced by the synthesis is annotated with a complete history relating it to every other artifact (including the source specification) which influenced its construction. This approach requires modification of the entire synthesis system - which is labor-intensive and hard to do without influencing its behavior. In this paper, we introduce a novel, lightweight technique for deriving traceability from a program specification to the corresponding synthesized code. Once a program has been successfully synthesized from a specification, small changes are systematically made to the specification and the effects on the synthesized program observed. We have partially automated the technique and applied it in an experiment to one of our program synthesis systems, AUTOFILTER, and to the GNU C compiler, GCC. The results are promising: 1. Manual inspection of the results indicates that most of the connections derived from the source (a specification in the case of AUTOFILTER, C source code in the case of GCC) to its generated target (C source code in the case of AUTOFILTER, assembly language code in the case of GCC) are correct. 2. Around half of the lines in the target can be traced to at least one line of the source. 3. Small changes in the source often induce only small changes in the target.

  18. High pressure gas target

    Gelbart, W.; Johnson, R. R.; Abeysekera, B.


    Compact, high pressure, high current gas target features all metal construction and semi-automatic window assembly change. The unique aspect of this target is the domed-shaped window. The Havar alloy window is electron beam welded to a metal ring, thus forming one, interchangeable assembly. The window assembly is sealed by knife-edges locked by a pneumatic toggle allowing a quick, in situ window change.

  19. Automatic Facial Expression Recognition Based on Hybrid Approach

    Ali K. K. Bermani


    Full Text Available The topic of automatic recognition of facial expressions deduce a lot of researchers in the late last century and has increased a great interest in the past few years. Several techniques have emerged in order to improve the efficiency of the recognition by addressing problems in face detection and extraction features in recognizing expressions. This paper has proposed automatic system for facial expression recognition which consists of hybrid approach in feature extraction phase which represent a combination between holistic and analytic approaches by extract 307 facial expression features (19 features by geometric, 288 feature by appearance. Expressions recognition is performed by using radial basis function (RBF based on artificial neural network to recognize the six basic emotions (anger, fear, disgust, happiness, surprise, sadness in addition to the natural.The system achieved recognition rate 97.08% when applying on person-dependent database and 93.98% when applying on person-independent.

  20. Novel Moment Features Extraction for Recognizing Handwritten Arabic Letters

    Gheith Abandah


    Full Text Available Problem statement: Offline recognition of handwritten Arabic text awaits accurate recognition solutions. Most of the Arabic letters have secondary components that are important in recognizing these letters. However these components have large writing variations. We targeted enhancing the feature extraction stage in recognizing handwritten Arabic text. Approach: In this study, we proposed a novel feature extraction approach of handwritten Arabic letters. Pre-segmented letters were first partitioned into main body and secondary components. Then moment features were extracted from the whole letter as well as from the main body and the secondary components. Using multi-objective genetic algorithm, efficient feature subsets were selected. Finally, various feature subsets were evaluated according to their classification error using an SVM classifier. Results: The proposed approach improved the classification error in all cases studied. For example, the improvements of 20-feature subsets of normalized central moments and Zernike moments were 15 and 10%, respectively. Conclusion/Recommendations: Extracting and selecting statistical features from handwritten Arabic letters, their main bodies and their secondary components provided feature subsets that give higher recognition accuracies compared to the subsets of the whole letters alone.

  1. Rule Based System for Recognizing Emotions Using Multimodal Approach

    Preeti Khanna


    Full Text Available Emotion is assuming increasing importance in human computer interaction (HCI, in general, with the growing feeling that emotion is central to human communication and intelligence. Users expect not just functionality as a factor of usability, but experiences, matched to their expectations, emotional states, and interaction goals. Endowing computers with this kind of intelligence for HCI is a complex task. It becomes more complex with the fact that the interaction of humans with their environment (including other humans is naturally multimodal. In reality, one uses a combination of modalities and they are not treated independently. In an attempt to render HCI more similar to human-human communication and enhance its naturalness, research on multiple modalities of human expressions has seen ongoing progress in the past few years. As compared to unimodal approaches, various problems arise in case of multimodal emotion recognition especially concerning fusion architecture of multimodal information. In this paper we will be proposing a rule based hybrid approach to combine the information from various sources for recognizing the target emotions. The results presented in this paper shows that it is feasible to recognize human affective states with a reasonable accuracy by combining the modalities together using rule based system.

  2. Automatic radioactive waste recycling

    The production of a plutonium ingot by calcium reduction process at CEA/Valduc generates a residue called 'slag'. This article introduces the recycling unit which is dedicated to the treatment of slags. The aim is to separate and to recycle the plutonium trapped in this bulk on the one hand, and to generate a disposable waste from the slag on the other hand. After a general introduction of the facilities, some elements will be enlightened, particularly the dissolution step, the filtration and the drying equipment. Reflections upon technological constraints will be proposed, and the benefits of a fully automatic recycling unit of nuclear waste will also be stressed. (authors)

  3. Automatic Configuration in NTP

    Jiang Zongli(蒋宗礼); Xu Binbin


    NTP is nowadays the most widely used distributed network time protocol, which aims at synchronizing the clocks of computers in a network and keeping the accuracy and validation of the time information which is transmitted in the network. Without automatic configuration mechanism, the stability and flexibility of the synchronization network built upon NTP protocol are not satisfying. P2P's resource discovery mechanism is used to look for time sources in a synchronization network, and according to the network environment and node's quality, the synchronization network is constructed dynamically.

  4. 46 CFR 160.049-8 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.049-8 Section 160.049-8... Recognized laboratory. (a) A manufacturer seeking Coast Guard approval of a product under this subpart shall... to a recognized independent laboratory. The following laboratories are recognized under §...

  5. 46 CFR 162.039-5 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 162.039-5 Section 162.039-5... Recognized laboratory. (a) A recognized laboratory is one which is regularly engaged in the examination... motorboats. The following laboratories are recognized, and the semiportable fire extinguishers bearing...

  6. 46 CFR 160.048-8 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.048-8 Section 160.048-8... Recognized laboratory. (a) A manufacturer seeking Coast Guard approval of a product under this subpart shall... to a recognized independent laboratory. The following laboratories are recognized under §...

  7. 46 CFR 160.077-9 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.077-9 Section 160.077-9... Recognized laboratory. (a) A manufacturer seeking Coast Guard approval of a product under this subpart shall... to a recognized independent laboratory. The following laboratories are recognized under §...

  8. Design and realization of dynamic target tracking and automatic close-up snapshot%动态目标跟踪与自动特写快照系统的设计及实现

    盛平; 倪冬玮; 张净


    The existing dynamic target tracking and snapshot system is difficult to meet the requirements of clear, reliable, real-time and accurate tracking capture simultaneously. To solve the problem , this paper proposes a new dynamic target tracking and snapshot system which is more practical and less complex. A fast mixture Gaussian background difference method is adopted to segment the moving object, and accurate target positioning is obtained by the project method. Besides, in order to achieve the purpose of dynamic tracking, the methods of Kalman filter and template matching are both applied by combining with the method of pan-tilt-zoom (PTZ) camera calibration. Meanwhile, in the PTZ tracking process, on the basis of the extreme value of gradient and the actual motion vector of the target, a method to realize the adaptive capture of clear snapshot of objectives is proposed. In VC + +environment, the human body is taken as the moving target for testing. The experimental results indicate that this system has realized the purpose of dynamic target tracking and snapshot, and also has advantages of real-time, clarity and robustness.%针对现有动态跟踪和快照系统难以同时满足清晰、可靠、实时、准确的跟踪抓拍要求的缺点,提出了一种复杂度较低的新型实用动态跟踪和快照系统.采用一种快速的混合高斯背景差分法分割出运动目标,并使用投影法实现目标的精确定位;然后采用Kalman滤波与模板匹配的方法,结合摄像机标定结果进行云台控制实现动态跟踪;同时,在PTZ跟踪过程中,提出一种基于梯度极值结合目标实际运动矢量的方法实现目标快照的抓拍.在VC ++环境中,以人体为运动目标进行测试,实验结果表明该系统实现了运动目标的动态跟踪与快照,并且具有很好的鲁棒性、实时性和清晰度.

  9. Recognizing limitations in eddy current testing

    This paper addresses known limitations and constraints in eddy current nondestructive testing. Incomplete appreciation for eddy current limitations is believed to have contributed to both under-utilization and misapplication of the technique. Neither situation need arise if known limitations are recognized. Some, such as the skin depth effect, are inherent to electromagnetic test methods and define the role of eddy current testing. Others can be overcome with available technology such as surface probes to find circumferential cracks in tubes and magnetic saturation of ferromagnetic alloys to eliminate permeability effects. The variables responsible for limitations in eddy current testing are discussed and where alternative approaches exist, these are presented. Areas with potential for further research and development are also identified

  10. Automatic personnel contamination monitor

    United Nuclear Industries, Inc. (UNI) has developed an automatic personnel contamination monitor (APCM), which uniquely combines the design features of both portal and hand and shoe monitors. In addition, this prototype system also has a number of new features, including: micro computer control and readout, nineteen large area gas flow detectors, real-time background compensation, self-checking for system failures, and card reader identification and control. UNI's experience in operating the Hanford N Reactor, located in Richland, Washington, has shown the necessity of automatically monitoring plant personnel for contamination after they have passed through the procedurally controlled radiation zones. This final check ensures that each radiation zone worker has been properly checked before leaving company controlled boundaries. Investigation of the commercially available portal and hand and shoe monitors indicated that they did not have the sensitivity or sophistication required for UNI's application, therefore, a development program was initiated, resulting in the subject monitor. Field testing shows good sensitivity to personnel contamination with the majority of alarms showing contaminants on clothing, face and head areas. In general, the APCM has sensitivity comparable to portal survey instrumentation. The inherit stand-in, walk-on feature of the APCM not only makes it easy to use, but makes it difficult to bypass. (author)

  11. Pattern-Driven Automatic Parallelization

    Christoph W. Kessler


    Full Text Available This article describes a knowledge-based system for automatic parallelization of a wide class of sequential numerical codes operating on vectors and dense matrices, and for execution on distributed memory message-passing multiprocessors. Its main feature is a fast and powerful pattern recognition tool that locally identifies frequently occurring computations and programming concepts in the source code. This tool also works for dusty deck codes that have been "encrypted" by former machine-specific code transformations. Successful pattern recognition guides sophisticated code transformations including local algorithm replacement such that the parallelized code need not emerge from the sequential program structure by just parallelizing the loops. It allows access to an expert's knowledge on useful parallel algorithms, available machine-specific library routines, and powerful program transformations. The partially restored program semantics also supports local array alignment, distribution, and redistribution, and allows for faster and more exact prediction of the performance of the parallelized target code than is usually possible.

  12. Recognizing obesity and comorbidities in sparse data.

    Uzuner, Ozlem


    In order to survey, facilitate, and evaluate studies of medical language processing on clinical narratives, i2b2 (Informatics for Integrating Biology to the Bedside) organized its second challenge and workshop. This challenge focused on automatically extracting information on obesity and fifteen of its most common comorbidities from patient discharge summaries. For each patient, obesity and any of the comorbidities could be Present, Absent, or Questionable (i.e., possible) in the patient, or Unmentioned in the discharge summary of the patient. i2b2 provided data for, and invited the development of, automated systems that can classify obesity and its comorbidities into these four classes based on individual discharge summaries. This article refers to obesity and comorbidities as diseases. It refers to the categories Present, Absent, Questionable, and Unmentioned as classes. The task of classifying obesity and its comorbidities is called the Obesity Challenge. The data released by i2b2 was annotated for textual judgments reflecting the explicitly reported information on diseases, and intuitive judgments reflecting medical professionals' reading of the information presented in discharge summaries. There were very few examples of some disease classes in the data. The Obesity Challenge paid particular attention to the performance of systems on these less well-represented classes. A total of 30 teams participated in the Obesity Challenge. Each team was allowed to submit two sets of up to three system runs for evaluation, resulting in a total of 136 submissions. The submissions represented a combination of rule-based and machine learning approaches. Evaluation of system runs shows that the best predictions of textual judgments come from systems that filter the potentially noisy portions of the narratives, project dictionaries of disease names onto the remaining text, apply negation extraction, and process the text through rules. Information on disease-related concepts

  13. Development of NATO's recognized environmental picture

    Teufert, John F.; Trabelsi, Mourad


    An important element for the fielding of a viable, effective NATO Response Force (NRF) is access to meteorological, oceanographic, geospatial data (GEOMETOC) and imagery. Currently, the available GEOMETOC information suffers from being very fragmented. NATO defines the Recognised Environmental Picture as controlled information base for GEOMETOC data. The NATO REP proposes an architecture that is both flexible and open. The focus lies on enabling a network-centric approach. The key into achieving this is relying on using open, well recognized standards that apply to both the data exchange protocols and the data formats. Communication and information exchange based on open standards enables system interoperability. Diverse systems, each with unique, specialized contributions to an increased understanding of the battlespace, can now cooperate to a manageable information sphere. By clearly defining responsibilities in the generation of information, a reduction in data transfer overhead is achieved . REP identifies three main stages in the dissemination of GEOMETOC data. These are Collection, Fusion (and Analysis) and Publication. A REP architecture has been successfully deployed during the NATO Coalition Warrior Interoperability Demonstration (CWID) in Lillehammer, Norway during June 2005. CWID is an annual event to validate and improve the interoperability of NATO and national Consultation and command, control, communications, computers, intelligence, surveillance, and reconnaissance (C4ISR) systems. With a test case success rate of 84%, it was able to provide relevant GEOMETOC support to the main NRF component headquarters. In 2006, the REP architecture will be deployed and validated during the NATO NRF Steadfast live exercises.

  14. Recognizing and identifying people: A neuropsychological review.

    Barton, Jason J S; Corrow, Sherryse L


    Recognizing people is a classic example of a cognitive function that involves multiple processing stages and parallel routes of information. Neuropsychological data have provided important evidence for models of this process, particularly from case reports; however, the quality and extent of the data varies widely between studies. In this review we first discuss the requirements and logical basis of the types of neuropsychological evidence to support conclusions about the modules in this process. We then survey the adequacy of the current body of reports to address two key issues. First is the question of which cognitive operation generates a sense of familiarity: the current debate revolves around whether familiarity arises in modality-specific recognition units or later amodal processes. Key evidence on this point comes from the search for dissociations between familiarity for faces, voices and names. The second question is whether lesions can differentially affect the abilities to link diverse sources of person information (e.g., face, voice, name, biographic data). Dissociations of these linkages may favor a 'distributed-only' model of the organization of semantic knowledge, whereas a 'person-hub' model would predict uniform impairments of all linkages. While we conclude that there is reasonable evidence for dissociations in name, voice and face familiarity in regards to the first question, the evidence for or against dissociated linkages between information stores in regards to the second question is tenuous at best. We identify deficiencies in the current literature that should motivate and inform the design of future studies. PMID:26773237

  15. Artificial Immune System for Recognizing Patterns

    Huntsberger, Terrance


    A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

  16. Matching and Clustering: Two Steps Towards Automatic Model Generation in Computer Vision

    Gros, Patrick


    International audience In this paper, we present a general frame for a system of automatic modelling and recognition of 3D polyhedral objects. Such a system has many applications for robotics : recognition, localization, grasping,...Here we focus upon one main aspect of the system : when many images of one 3D object are taken from different unknown viewpoints, how to recognize those of them which represent the same aspect of the object ? Briefly, it is possible to determine automatically i...

  17. Automatic Wall Painting Robot



    Full Text Available The Primary Aim Of The Project Is To Design, Develop And Implement Automatic Wall Painting Robot Which Helps To Achieve Low Cost Painting Equipment. Despite The Advances In Robotics And Its Wide Spreading Applications, Interior Wall Painting Has Shared Little In Research Activities. The Painting Chemicals Can Cause Hazards To The Human Painters Such As Eye And Respiratory System Problems. Also The Nature Of Painting Procedure That Requires Repeated Work And Hand Rising Makes It Boring, Time And Effort Consuming. When Construction Workers And Robots Are Properly Integrated In Building Tasks, The Whole Construction Process Can Be Better Managed And Savings In Human Labour And Timing Are Obtained As A Consequence. In Addition, It Would Offer The Opportunity To Reduce Or Eliminate Human Exposure To Difficult And Hazardous Environments, Which Would Solve Most Of The Problems Connected With Safety When Many Activities Occur At The Same Time. These Factors Motivate The Development Of An Automated Robotic Painting System.

  18. Automatic alkaloid removal system.

    Yahaya, Muhammad Rizuwan; Hj Razali, Mohd Hudzari; Abu Bakar, Che Abdullah; Ismail, Wan Ishak Wan; Muda, Wan Musa Wan; Mat, Nashriyah; Zakaria, Abd


    This alkaloid automated removal machine was developed at Instrumentation Laboratory, Universiti Sultan Zainal Abidin Malaysia that purposely for removing the alkaloid toxicity from Dioscorea hispida (DH) tuber. It is a poisonous plant where scientific study has shown that its tubers contain toxic alkaloid constituents, dioscorine. The tubers can only be consumed after it poisonous is removed. In this experiment, the tubers are needed to blend as powder form before inserting into machine basket. The user is need to push the START button on machine controller for switching the water pump ON by then creating turbulence wave of water in machine tank. The water will stop automatically by triggering the outlet solenoid valve. The powders of tubers are washed for 10 minutes while 1 liter of contaminated water due toxin mixture is flowing out. At this time, the controller will automatically triggered inlet solenoid valve and the new water will flow in machine tank until achieve the desire level that which determined by ultra sonic sensor. This process will repeated for 7 h and the positive result is achieved and shows it significant according to the several parameters of biological character ofpH, temperature, dissolve oxygen, turbidity, conductivity and fish survival rate or time. From that parameter, it also shows the positive result which is near or same with control water and assuming was made that the toxin is fully removed when the pH of DH powder is near with control water. For control water, the pH is about 5.3 while water from this experiment process is 6.0 and before run the machine the pH of contaminated water is about 3.8 which are too acid. This automated machine can save time for removing toxicity from DH compared with a traditional method while less observation of the user. PMID:24783795

  19. Automatic Loop Parallelization via Compiler Guided Refactoring

    Larsen, Per; Ladelsky, Razya; Lidman, Jacob;

    For many parallel applications, performance relies not on instruction-level parallelism, but on loop-level parallelism. Unfortunately, many modern applications are written in ways that obstruct automatic loop parallelization. Since we cannot identify sufficient parallelization opportunities for t...... the OpenMP code (within 75-111%). The second benchmark outperforms hand-parallelized and optimized OpenMP code (within 109-242%)....... be combined with target-specific optimizations. Furthermore, comparing the first benchmark to hand-parallelized, hand-optimized pthreads and OpenMP versions, we find that code generated using our approach typically outperforms the pthreads code (within 93-339%). It also performs competitively against...

  20. Mental imagery affects subsequent automatic defense responses

    Muriel A Hagenaars


    Full Text Available Automatic defense responses promote survival and appropriate action under threat. They have also been associated with the development of threat-related psychiatric syndromes. Targeting such automatic responses during threat may be useful in populations with frequent threat exposure. Here, two experiments explored whether mental imagery as a pre-trauma manipulation could influence fear bradycardia (a core characteristic of freezing during subsequent analogue trauma (affective picture viewing. Image-based interventions have proven successful in the treatment of threat-related disorders, and are easily applicable. In Experiment 1 43 healthy participants were randomly assigned to an imagery script condition. Participants executed a passive viewing task with blocks of neutral, pleasant and unpleasant pictures after listening to an auditory script that was either related (with a positive or a negative outcome or unrelated to the unpleasant pictures from the passive viewing task. Heart rate was assessed during script listening and during passive viewing. Imagining negative related scripts resulted in greater bradycardia (neutral-unpleasant contrast than imagining positive scripts, especially unrelated. This effect was replicated in Experiment 2 (N = 51, again in the neutral-unpleasant contrast. An extra no-script condition showed that bradycardia was not induced by the negative related script, but rather that a positive script attenuated bradycardia. These preliminary results might indicate reduced vigilance after unrelated positive events. Future research should replicate these findings using a larger sample. Either way, the findings show that highly automatic defense behavior can be influenced by relatively simple mental imagery manipulations.

  1. Target detection and recognition in SAR imagery based on KFDA

    Fei Gao; Jingyuan Mei; Jinping Sun; Jun Wang; Erfu Yang; Amir Hussain


    Current research on target detection and recognition from synthetic aperture radar (SAR) images is usual y carried out separately. It is difficult to verify the ability of a target recognition algorithm for adapting to changes in the environment. To realize the whole process of SAR automatic target recognition (ATR), es-pecial y for the detection and recognition of vehicles, an algorithm based on kernel fisher discriminant analysis (KFDA) is proposed. First, in order to make a better description of the difference be-tween the background and the target, KFDA is extended to the detection part. Image samples are obtained with a dual-window approach and features of the inner and outer window samples are extracted by using KFDA. The difference between the features of inner and outer window samples is compared with a threshold to determine whether a vehicle exists. Second, for the target area, we propose an improved KFDA-IMED (image Euclidean distance) combined with a support vector machine (SVM) to recognize the vehicles. Experimental results validate the performance of our method. On the detection task, our proposed method obtains not only a high detection rate but also a low false alarm rate without using any prior information. For the recognition task, our method overcomes the SAR image aspect angle sensitivity, reduces the requirements for image preprocessing and improves the recogni-tion rate.

  2. Design and recognition of three dimensional calibration target based on coded marker

    Zhai, You; Xiong, Wei; Zeng, Luan; Gu, Dalong


    Traditional three-dimensional (3D) calibration targets consist of two or three mutual orthogonal planes (each of the planes contains several control points constituted by corners or circular points) that cannot be captured simultaneously by cameras in front view. Therefore, large perspective distortions exist in the images of the calibration targets resulting in inaccurate image coordinate detection of the control points. Besides, in order to eliminate mismatches, recognition of the control points usually needs manual intervention consuming large amount of time. A new design of 3D calibration target is presented for automatic and accurate camera calibration. The target employs two parallel planes instead of orthogonal planes to reduce perspective distortion, which can be captured simultaneously by cameras in front view. Control points of the target are constituted by carefully designed circular coded markers, which can be used to realize automatic recognition without manual intervention. Due to perspective projection, projections of the circular coded markers' centers deviate from the centers of their corresponding imaging ellipses. Colinearity of the control points is used to correct perspective distortions of the imaging ellipses. Experiment results show that the calibration target can be automatically and correctly recognized under large illumination and viewpoint change. The image extraction errors of the control points are under 0.1 pixels. When applied to binocular cameras calibration, the mean reprojection errors are less than 0.15 pixels and the 3D measurement errors are less than 0.2mm in x and y axis and 0.5mm in z axis respectively.

  3. Bayesian multiple target tracking

    Streit, Roy L


    This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements

  4. Design of Automatic Detection and Tracking System for Ground Forest Fire Targets Based on Infrared Detection%基于红外探测的地面林火目标自动检测与追踪系统设计

    赵亚凤; 凌滨; 刘立臣


    针对红外林火图像的特点,从实际应用的角度出发,在FPGA+DSP构建的硬件平台上,实现了森林灰度图像的正确采集和进行有无火点的判断,并提出了图像边缘检测和自适应阈值相结合提取林火目标的方法,达到了林火目标的自动检测;然后利用通信协议和算法控制云台转动,使热像仪的光学系统主光轴始终对准最大灰度值点,达到追踪的效果.在多种环境下对此方法进行了验证,结果表明,这一方法的实用效果、实时性和可靠性均达到了要求.%A practical method for fire target detection was proposed through grayscale image collection and analysis on a FPGA-based DSP hardware platform, in view of the characteristics of infrared forest-fire images. The automatic detection of forest fire targets could be realized by target extraction based on image edge detection and adaptive threshold. The software depends on the communication protocol and algorithm to realize the tracking by controlling the circular movement of the tripod head and making the optical axis of the thermal imager aim at the maximum gray value. Validation experiments were conducted under a series of different environments. Results show that the effectiveness, timeliness and reliability of the method all meet the design requirements.

  5. Making automatic differentiation truly automatic : coupling PETSc with ADIC

    Despite its name, automatic differentiation (AD) is often far from an automatic process. often one must specify independent and dependent variables, indicate the derivative quantities to be computed, and perhaps even provide information about the structure of the Jacobians or Hessians being computed. However, when AD is used in conjunction with a toolkit with well-defined interfaces, many of these issues do not arise. They describe recent research into coupling the ADIC automatic differentiation tool with PETSc, a toolkit for the parallel numerical solution of PDEs. This research leverages the interfaces and objects of PETSc to make the AD process very nearly transparent

  6. An application of nuclear emulsions with automatic scanning

    It will be shown that emulsions can be mass produced and automatically scanned in large quantities. CHORUS demonstrated the first large-scale application. Emulsions can be used to search for rare events in a high track density environment like DONUT. Heavy target masses as in OPERA are possible. The use of emulsions is getting more and more easier

  7. 46 CFR 42.05-60 - Recognized classification society.


    ... 46 Shipping 2 2010-10-01 2010-10-01 false Recognized classification society. 42.05-60 Section 42... society. The term recognized classification society means the American Bureau of Shipping or other classification society recognized by the Commandant, as provided in 46 U.S.C. 5107, and who also may be...

  8. 46 CFR 90.10-35 - Recognized classification society.


    ... 46 Shipping 4 2010-10-01 2010-10-01 false Recognized classification society. 90.10-35 Section 90... classification society. The term recognized classification society means the American Bureau of Shipping or other classification society recognized by the Commandant....

  9. 46 CFR 164.012-12 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 164.012-12 Section 164.012-12...: SPECIFICATIONS AND APPROVAL MATERIALS Interior Finishes for Merchant Vessels § 164.012-12 Recognized laboratory. A recognized laboratory is one which is operated as a nonprofit public service and is...

  10. 46 CFR 160.047-7 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.047-7 Section 160.047-7... and Child § 160.047-7 Recognized laboratory. (a) A manufacturer seeking Coast Guard approval of a... shall apply for approval directly to a recognized independent laboratory. The following laboratories...

  11. 46 CFR 164.019-17 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 164.019-17 Section 164.019-17...: SPECIFICATIONS AND APPROVAL MATERIALS Personal Flotation Device Components § 164.019-17 Recognized laboratory. (a) General. A laboratory may be designated as a recognized laboratory under this subpart if it is—...

  12. 46 CFR 160.060-9 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.060-9 Section 160.060-9..., Adult and Child § 160.060-9 Recognized laboratory. (a) A manufacturer seeking Coast Guard approval of a... shall apply for approval directly to a recognized independent laboratory. The following laboratories...

  13. 46 CFR 160.064-7 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.064-7 Section 160.064-7...: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Marine Buoyant Devices § 160.064-7 Recognized laboratory. (a) A... laboratory. The following laboratories are recognized under § 159.010-7 of this part, to perform testing...

  14. 46 CFR 160.052-9 - Recognized laboratory.


    ... 46 Shipping 6 2010-10-01 2010-10-01 false Recognized laboratory. 160.052-9 Section 160.052-9..., Adult and Child § 160.052-9 Recognized laboratory. (a) A manufacturer seeking Coast Guard approval of a... shall apply for approval directly to a recognized independent laboratory. The following laboratories...

  15. Automatic Kurdish Dialects Identification

    Hossein Hassani


    Full Text Available Automatic dialect identification is a necessary Lan guage Technology for processing multi- dialect languages in which the dialects are linguis tically far from each other. Particularly, this becomes crucial where the dialects are mutually uni ntelligible. Therefore, to perform computational activities on these languages, the sy stem needs to identify the dialect that is the subject of the process. Kurdish language encompasse s various dialects. It is written using several different scripts. The language lacks of a standard orthography. This situation makes the Kurdish dialectal identification more interesti ng and required, both form the research and from the application perspectives. In this research , we have applied a classification method, based on supervised machine learning, to identify t he dialects of the Kurdish texts. The research has focused on two widely spoken and most dominant Kurdish dialects, namely, Kurmanji and Sorani. The approach could be applied to the other Kurdish dialects as well. The method is also applicable to the languages which are similar to Ku rdish in their dialectal diversity and differences.

  16. Automatic Detect and Trace of Solar Filaments

    Fang, Cheng; Chen, P. F.; Tang, Yu-hua; Hao, Qi; Guo, Yang

    We developed a series of methods to automatically detect and trace solar filaments in solar Hα images. The programs are able to not only recognize filaments and determine their properties, such as the position, the area and other relevant parameters, but also to trace the daily evolution of the filaments. For solar full disk Hα images, the method consists of three parts: first, preprocessing is applied to correct the original images; second, the Canny edge-detection method is used to detect the filaments; third, filament properties are recognized through the morphological operators. For each Hα filament and its barb features, we introduced the unweighted undirected graph concept and adopted Dijkstra shortest-path algorithm to recognize the filament spine; then, using polarity inversion line shift method for measuring the polarities in both sides of the filament to determine the filament axis chirality; finally, employing connected components labeling method to identify the barbs and calculating the angle between each barb and spine to indicate the barb chirality. Our algorithms are applied to the observations from varied observatories, including the Optical & Near Infrared Solar Eruption Tracer (ONSET) in Nanjing University, Mauna Loa Solar Observatory (MLSO) and Big Bear Solar Observatory (BBSO). The programs are demonstrated to be effective and efficient. We used our method to automatically process and analyze 3470 images obtained by MLSO from January 1998 to December 2009, and a butterfly diagram of filaments is obtained. It shows that the latitudinal migration of solar filaments has three trends in the Solar Cycle 23: The drift velocity was fast from 1998 to the solar maximum; after the solar maximum, it became relatively slow and after 2006, the migration became divergent, signifying the solar minimum. About 60% filaments with the latitudes larger than 50 degree migrate towards the Polar Regions with relatively high velocities, and the latitudinal migrating

  17. Electronic amplifiers for automatic compensators

    Polonnikov, D Ye


    Electronic Amplifiers for Automatic Compensators presents the design and operation of electronic amplifiers for use in automatic control and measuring systems. This book is composed of eight chapters that consider the problems of constructing input and output circuits of amplifiers, suppression of interference and ensuring high sensitivity.This work begins with a survey of the operating principles of electronic amplifiers in automatic compensator systems. The succeeding chapters deal with circuit selection and the calculation and determination of the principal characteristics of amplifiers, as

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

    Chao, Tien-Hsin


    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.

  19. Automatic laser tracking and ranging system.

    Cooke, C R


    An automatic laser tracking and ranging system has been developed for use with cooperative retroreflective targets. Target position is determined with high precision at ranges out to 19 km and sample rates up to one hundred measurements per second. The data are recorded on a magnetic tape in the form of azimuth, elevation, range, and standard time and are computer-compatible. The system is fully automatic with the exception of the initial acquisition sequence, which is performed manually. This eliminates the need for expensive and time-consuming photographic data reduction. Also, position is uniquely determined by a single instrument. To provide convenient operation at remote sites, the system is van-mounted and operates off a portable power generator. The transmitter is a flash-pumped Q-spoiled Nd:YAG laser developing 1 MW peak power in a 10-mrad beam at a rate of 100 pps. The beam, which is coaxial with the receiver, is directed to the target by an azimuth-elevation mirror mount. The return beam is imaged o separate ranging and tracking receivers. The ranging receiver measures time of flight of the 25-nsec laser pulse with range accuracies of +/-15 cm. The tracking receiver uses a quadrant photodiode followed by matched log video amplifiers and achieves a tracking accuracy of +/-0.1 mrad. An optical dynamic range of 30 dB is provided to minimize error due to scintillation. Also, 80 dB of optical dynamic range is provided by adjustable neutral density filters to compensate for changes in target range. PMID:20111495

  20. Automatic Knowledge Extraction and Knowledge Structuring for a National Term Bank

    Lassen, Tine; Madsen, Bodil Nistrup; Erdman Thomsen, Hanne


    This paper gives an introduction to the plans and ongoing work in a project, the aim of which is to develop methods for automatic knowledge extraction and automatic construction and updating of ontologies. The project also aims at developing methods for automatic merging of terminological data from...... various existing sources, as well as methods for target group oriented knowledge dissemination. In this paper, we mainly focus on the plans for automatic knowledge extraction and knowledge structuring that will result in ontologies for a national term bank....

  1. Victimization: a newly recognized outcome of prematurity.

    Nadeau, Line; Tessier, Réjean; Lefebvre, Francine; Robaey, Philippe


    Victimization by peers affects 10 to 20% of school children under the age of 12 years. Physical, verbal, and psychological victimization (being pushed, hit, called names, teased, being the target of rumours, theft, extortion) is associated with short- and long-term adjustment problems, such as peer rejection, social withdrawal, low self-esteem, anxiety, loneliness, and depression, as well as academic problems and school drop-out. Research on populations of school children (primary and secondary) has associated victimization with personal risk factors (the victim's characteristics and behaviour) and interpersonal risk factors (social relationships between peers). Studies on the social adjustment of preterm children at school age show that, even in the absence of a major motor or cognitive disability, this population has several personal risk factors associated with victimization. The objective of this study was to compare the level of victimization experienced by a group of 96 seven-year-old children born extremely preterm (EP, born EP had a mean gestational age of 27.3 weeks (SD 1.2) and a mean birthweight of 1001.1g (SD 223) and normal birthweight children had a mean gestational age of 39.5 weeks (SD 1.5) and a mean birthweight of 3468.7g (SD 431). Physical and verbal victimization were assessed in a school setting by peers with individual sociometric interviews (Modified Peer Nomination Inventory). After controlling for physical growth (height and weight) at the age of 7 years, the data indicate two independent effects: males were more victimized than females, and children born preterm experienced more verbal victimization by their peers than their term classmates, even when participants with a visible motor, intellectual, or sensory disability were excluded. Several hypotheses are presented to account for the higher incidence of verbal victimization of preterm children. PMID:15287240

  2. Clothes Dryer Automatic Termination Evaluation

    TeGrotenhuis, Ward E.


    Volume 2: Improved Sensor and Control Designs Many residential clothes dryers on the market today provide automatic cycles that are intended to stop when the clothes are dry, as determined by the final remaining moisture content (RMC). However, testing of automatic termination cycles has shown that many dryers are susceptible to over-drying of loads, leading to excess energy consumption. In particular, tests performed using the DOE Test Procedure in Appendix D2 of 10 CFR 430 subpart B have shown that as much as 62% of the energy used in a cycle may be from over-drying. Volume 1 of this report shows an average of 20% excess energy from over-drying when running automatic cycles with various load compositions and dryer settings. Consequently, improving automatic termination sensors and algorithms has the potential for substantial energy savings in the U.S.

  3. Prospects for de-automatization.

    Kihlstrom, John F


    Research by Raz and his associates has repeatedly found that suggestions for hypnotic agnosia, administered to highly hypnotizable subjects, reduce or even eliminate Stroop interference. The present paper sought unsuccessfully to extend these findings to negative priming in the Stroop task. Nevertheless, the reduction of Stroop interference has broad theoretical implications, both for our understanding of automaticity and for the prospect of de-automatizing cognition in meditation and other altered states of consciousness. PMID:20356765

  4. Process automatization in system administration

    Petauer, Janja


    The aim of the thesis is to present automatization of user management in company Studio Moderna. The company has grown exponentially in recent years, that is why we needed to find faster, easier and cheaper way of man- aging user accounts. We automatized processes of creating, changing and removing user accounts within Active Directory. We prepared user interface inside of existing application, used Java Script for drop down menus, wrote script in scripting programming langu...

  5. Eating as an Automatic Behavior

    Deborah A. Cohen, MD, MPH; Thomas A. Farley, MD, MPH


    The continued growth of the obesity epidemic at a time when obesity is highly stigmatizing should make us question the assumption that, given the right information and motivation, people can successfully reduce their food intake over the long term. An alternative view is that eating is an automatic behavior over which the environment has more control than do individuals. Automatic behaviors are those that occur without awareness, are initiated without intention, tend to continue without contr...

  6. Structural basis of Zika virus helicase in recognizing its substrates.

    Tian, Hongliang; Ji, Xiaoyun; Yang, Xiaoyun; Zhang, Zhongxin; Lu, Zuokun; Yang, Kailin; Chen, Cheng; Zhao, Qi; Chi, Heng; Mu, Zhongyu; Xie, Wei; Wang, Zefang; Lou, Huiqiang; Yang, Haitao; Rao, Zihe


    The recent explosive outbreak of Zika virus (ZIKV) infection has been reported in South and Central America and the Caribbean. Neonatal microcephaly associated with ZIKV infection has already caused a public health emergency of international concern. No specific vaccines or drugs are currently available to treat ZIKV infection. The ZIKV helicase, which plays a pivotal role in viral RNA replication, is an attractive target for therapy. We determined the crystal structures of ZIKV helicase-ATP-Mn(2+) and ZIKV helicase-RNA. This is the first structure of any flavivirus helicase bound to ATP. Comparisons with related flavivirus helicases have shown that although the critical P-loop in the active site has variable conformations among different species, it adopts an identical mode to recognize ATP/Mn(2+). The structure of ZIKV helicase-RNA has revealed that upon RNA binding, rotations of the motor domains can cause significant conformational changes. Strikingly, although ZIKV and dengue virus (DENV) apo-helicases share conserved residues for RNA binding, their different manners of motor domain rotations result in distinct individual modes for RNA recognition. It suggests that flavivirus helicases could have evolved a conserved engine to convert chemical energy from nucleoside triphosphate to mechanical energy for RNA unwinding, but different motor domain rotations result in variable RNA recognition modes to adapt to individual viral replication. PMID:27430951

  7. The advanced linked extended reconnaissance and targeting technology demonstration project

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


    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.

  8. Performance of automatic scanning microscope for nuclear emulsion experiments

    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

  9. Performance of automatic scanning microscope for nuclear emulsion experiments

    Güler, A. Murat; Altınok, Özgür


    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.

  10. Tracking control mechanisms for positioning automatic CRD exchanger

    Purpose: To enable completely automatic positioning for the automatic CRD (control rod drives) exchanger, as well as shorten the time for the exchanging operation and save the operator's labour. Constitution: Images of a target attached to the lower flange face of CRD are picked up by a fiber scope mounted to a mounting head. The images are converted through I.T.V. into electrical signals, passed through a cable and then sent to a pattern recognition mechanism. The position for the images of the target is calculated and the calculated position is sent to a drive control section, where the position for the images of the target is compared with a reference position for the images (exactly aligned position) and the moving amount of the mounting head is calculated to move the driving section and thereby complete the positioning. (Kawakami, Y.)

  11. From motion to faces: 3D-assisted automatic analysis of people

    Iacopo Masi


    From motion to faces: 3D-assisted automatic analysis of people. This work proposes new computer vision algorithms about recognizing people by exploiting the face and the imaged appearance of the body. Many computer vision algorithms are covered: tracking, face recognition and person re-identification.

  12. AROMA-AIRWICK: a CHLOE/CDC-3600 system for the automatic identification of spark images and their association into tracks

    Clark, R K


    The AROMA-AIRWICK System for CHLOE, an automatic film scanning equipment built at Argonne by Donald Hodges, and the CDC-3600 computer is a system for the automatic identification of spark images and their association into tracks. AROMA-AIRWICK has been an outgrowth of the generally recognized need for the automatic processing of high energy physics data and the fact that the Argonne National Laboratory has been a center of serious spark chamber development in recent years.

  13. AROMA-AIRWICK: a CHLOE/CDC-3600 system for the automatic identification of spark images and their association into tracks

    The AROMA-AIRWICK System for CHLOE, an automatic film scanning equipment built at Argonne by Donald Hodges, and the CDC-3600 computer is a system for the automatic identification of spark images and their association into tracks. AROMA-AIRWICK has been an outgrowth of the generally recognized need for the automatic processing of high energy physics data and the fact that the Argonne National Laboratory has been a center of serious spark chamber development in recent years

  14. Accelerating convergence in automatic lens design

    Among the various factors that slow lens optimization-insufficient performance targets, the absence of a unique solution, false local minima, a poorly scaled change vector, failure to find the optimum damping number, and failure to equalize the parameter gradients-the importance of parameter gradient equalization has been insufficiently recognized. Gradients can be approximately equalized by scaling the lens to a suitable size while it is being optimized. For best results, the size of the damping number should also be optimized during each iteration. If these two procedures are followed, scaling the change vector is usually not crucial. To illustrate the importance of parameter equalization, a lens optimization is analyzed

  15. Automatic Identification of Human Erythrocytes in Microscopic Fecal Specimens.

    Liu, Lin; Lei, Haoting; Zhang, Jing; Yuan, Yang; Zhang, Zhenglong; Liu, Juanxiu; Xie, Yu; Ni, Guangming; Liu, Yong


    Traditional fecal erythrocyte detection is performed via a manual operation that is unsuitable because it depends significantly on the expertise of individual inspectors. To recognize human erythrocytes automatically and precisely, automatic segmentation is very important for extraction of characteristics. In addition, multiple recognition algorithms are also essential. This paper proposes an algorithm based on morphological segmentation and a fuzzy neural network. The morphological segmentation process comprises three operational steps: top-hat transformation, Otsu's method, and image binarization. Following initial screening by area and circularity, fuzzy c-means clustering and the neural network algorithms are used for secondary screening. Subsequently, the erythrocytes are screened by combining the results of five images obtained at different focal lengths. Experimental results show that even when the illumination, noise pollution, and position of the erythrocytes are different, they are all segmented and labeled accurately by the proposed method. Thus, the proposed method is robust even in images with significant amounts of noise. PMID:26349804

  16. The RNA world, automatic sequences and oncogenetics

    We construct a model of the RNA world in terms of naturally evolving nucleotide sequences assuming only Crick-Watson base pairing and self-cleaving/splicing capability. These sequences have the following properties. 1) They are recognizable by an automation (or automata). That is, to each k-sequence, there exist a k-automation which accepts, recognizes or generates the k-sequence. These are known as automatic sequences. Fibonacci and Morse-Thue sequences are the most natural outcome of pre-biotic chemical conditions. 2) Infinite (resp. large) sequences are self-similar (resp. nearly self-similar) under certain rewrite rules and consequently give rise to fractal (resp.fractal-like) structures. Computationally, such sequences can also be generated by their corresponding deterministic parallel re-write system, known as a DOL system. The self-similar sequences are fixed points of their respective rewrite rules. Some of these automatic sequences have the capability that they can read or 'accept' other sequences while others can detect errors and trigger error-correcting mechanisms. They can be enlarged and have block and/or palindrome structure. Linear recurring sequences such as Fibonacci sequence are simply Feed-back Shift Registers, a well know model of information processing machines. We show that a mutation of any rewrite rule can cause a combinatorial explosion of error and relates this to oncogenetical behavior. On the other hand, a mutation of sequences that are not rewrite rules, leads to normal evolutionary change. Known experimental results support our hypothesis. (author). Refs

  17. DNA Aptamers against Taiwan Banded Krait α-Bungarotoxin Recognize Taiwan Cobra Cardiotoxins

    Ying-Jung Chen; Chia-Yu Tsai; Wan-Ping Hu; Long-Sen Chang


    Bungarus multicinctus α-bungarotoxin (α-Bgt) and Naja atra cardiotoxins (CTXs) share a common structural scaffold, and their tertiary structures adopt three-fingered loop motifs. Four DNA aptamers against α-Bgt have been reported previously. Given that the binding of aptamers with targeted proteins depends on structural complementarity, in this study, we investigated whether DNA aptamers against α-Bgt could also recognize CTXs. It was found that N. atra cardiotoxin 3 (CTX3) reduced the electr...

  18. Automatic Control of Configuration of Web Anonymization

    Tomas Sochor


    Full Text Available Anonymization of the Internet traffic usually hides details about the request originator from the target server. Such a disguise might be required in some situations, especially in the case of web browsing. Although the web traffic anonymization is not a part of the http specification, it could be achieved using a certain extra tool. Significant deceleration of anonymized traffic compared to normal traffic is inevitable but it can be controlled in some cases as this article suggests. The results presented here focus on measuring the parameters of such deceleration in terms of response time, transmission speed and latency and proposing the way how to control it. This study focuses on TOR primarily because recent studies have concluded that other tools (like I2P and JAP provide worse service. Sets of 14 file locations and 30 web pages have been formed and the latency, response time and transmission speed during the page or file download were measured repeatedly both with TOR active in various configurations and without TOR. The main result presented here comprises several ways how to improve the TOR anonymization efficiency and the proposal for its automatic control. In spite of the fact that efficiency still remains too low compared to normal web traffic for ordinary use, its automatic control could make TOR a useful tool in special cases.

  19. Automatic abundance analysis of high resolution spectra

    Bonifacio, P; Bonifacio, Piercarlo; Caffau, Elisabetta


    We describe an automatic procedure for determining abundances from high resolution spectra. Such procedures are becoming increasingly important as large amounts of data are delivered from 8m telescopes and their high-multiplexing fiber facilities, such as FLAMES on ESO-VLT. The present procedure is specifically targeted for the analysis of spectra of giants in the Sgr dSph; however, the procedure may be, in principle, tailored to analyse stars of any type. Emphasis is placed on the algorithms and on the stability of the method; the external accuracy rests, ultimately, on the reliability of the theoretical models (model-atmospheres, synthetic spectra) used to interpret the data. Comparison of the results of the procedure with the results of a traditional analysis for 12 Sgr giants shows that abundances accurate at the level of 0.2 dex, comparable with that of traditional analysis of the same spectra, may be derived in a fast and efficient way. Such automatic procedures are not meant to replace the traditional ...

  20. Automatic Lumbar Spondylolisthesis Measurement in CT Images.

    Liao, Shu; Zhan, Yiqiang; Dong, Zhongxing; Yan, Ruyi; Gong, Liyan; Zhou, Xiang Sean; Salganicoff, Marcos; Fei, Jun


    Lumbar spondylolisthesis is one of the most common spinal diseases. It is caused by the anterior shift of a lumbar vertebrae relative to subjacent vertebrae. In current clinical practices, staging of spondylolisthesis is often conducted in a qualitative way. Although meyerding grading opens the door to stage spondylolisthesis in a more quantitative way, it relies on the manual measurement, which is time consuming and irreproducible. Thus, an automatic measurement algorithm becomes desirable for spondylolisthesis diagnosis and staging. However, there are two challenges. 1) Accurate detection of the most anterior and posterior points on the superior and inferior surfaces of each lumbar vertebrae. Due to the small size of the vertebrae, slight errors of detection may lead to significant measurement errors, hence, wrong disease stages. 2) Automatic localize and label each lumbar vertebrae is required to provide the semantic meaning of the measurement. It is difficult since different lumbar vertebraes have high similarity of both shape and image appearance. To resolve these challenges, a new auto measurement framework is proposed with two major contributions: First, a learning based spine labeling method that integrates both the image appearance and spine geometry information is designed to detect lumbar vertebrae. Second, a hierarchical method using both the population information from atlases and domain-specific information in the target image is proposed for most anterior and posterior points positioning. Validated on 258 CT spondylolisthesis patients, our method shows very similar results to manual measurements by radiologists and significantly increases the measurement efficiency. PMID:26849859

  1. Automatic transcription of Turkish microtonal music.

    Benetos, Emmanouil; Holzapfel, André


    Automatic music transcription, a central topic in music signal analysis, is typically limited to equal-tempered music and evaluated on a quartertone tolerance level. A system is proposed to automatically transcribe microtonal and heterophonic music as applied to the makam music of Turkey. Specific traits of this music that deviate from properties targeted by current transcription tools are discussed, and a collection of instrumental and vocal recordings is compiled, along with aligned microtonal reference pitch annotations. An existing multi-pitch detection algorithm is adapted for transcribing music with 20 cent resolution, and a method for converting a multi-pitch heterophonic output into a single melodic line is proposed. Evaluation metrics for transcribing microtonal music are applied, which use various levels of tolerance for inaccuracies with respect to frequency and time. Results show that the system is able to transcribe microtonal instrumental music at 20 cent resolution with an F-measure of 56.7%, outperforming state-of-the-art methods for the same task. Case studies on transcribed recordings are provided, to demonstrate the shortcomings and the strengths of the proposed method. PMID:26520294

  2. Automatic anatomy recognition of sparse objects

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


    A general body-wide automatic anatomy recognition (AAR) methodology was proposed in our previous work based on hierarchical fuzzy models of multitudes of objects which was not tied to any specific organ system, body region, or image modality. That work revealed the challenges encountered in modeling, recognizing, and delineating sparse objects throughout the body (compared to their non-sparse counterparts) if the models are based on the object's exact geometric representations. The challenges stem mainly from the variation in sparse objects in their shape, topology, geographic layout, and relationship to other objects. That led to the idea of modeling sparse objects not from the precise geometric representations of their samples but by using a properly designed optimal super form. This paper presents the underlying improved methodology which includes 5 steps: (a) Collecting image data from a specific population group G and body region Β and delineating in these images the objects in Β to be modeled; (b) Building a super form, S-form, for each object O in Β; (c) Refining the S-form of O to construct an optimal (minimal) super form, S*-form, which constitutes the (fuzzy) model of O; (d) Recognizing objects in Β using the S*-form; (e) Defining confounding and background objects in each S*-form for each object and performing optimal delineation. Our evaluations based on 50 3D computed tomography (CT) image sets in the thorax on four sparse objects indicate that substantially improved performance (FPVF~2%, FNVF~10%, and success where the previous approach failed) can be achieved using the new approach.

  3. Annual review in automatic programming

    Goodman, Richard


    Annual Review in Automatic Programming focuses on the techniques of automatic programming used with digital computers. Topics covered range from the design of machine-independent programming languages to the use of recursive procedures in ALGOL 60. A multi-pass translation scheme for ALGOL 60 is described, along with some commercial source languages. The structure and use of the syntax-directed compiler is also considered.Comprised of 12 chapters, this volume begins with a discussion on the basic ideas involved in the description of a computing process as a program for a computer, expressed in

  4. Recognizing molecular patterns by machine learning: an agnostic structural definition of the hydrogen bond

    Gasparotto, Piero


    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding -- a central concept to our understanding of the physical chemistry of water, biological systems and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a ...

  5. Automatically processing physical data from LHD experiments

    Emoto, M., E-mail:; Ida, K.; Suzuki, C.; Yoshida, M.; Akiyama, T.; Nakamura, Y.; Sakamoto, R.; Yokoyama, M.; Yoshinuma, M.


    Physical data produced by large helical device (LHD) experiments is supplied by the Kaiseki server, and registers more than 200 types of diagnostic data. Dependencies exist amongst the data; i.e., in many cases, the calculation of one data requires other data. Therefore, to obtain unregistered data, one needs to calculate not only the diagnostic data itself but also the dependent data; however, because the data is registered by different scientists, each scientist must separately calculate and register their respective data. To simplify this complicated procedure, we have developed an automatic calculation system called AutoAna. The calculation programs of AutoAna are distributed on a network, and the number of such programs can be easily increased dynamically. Our system is therefore scalable and ready for substantial increases in the size of the target data.

  6. Using immobilized G-protein coupled receptors to screen bioactive traditional Chinese medicine compounds with multiple targets.

    Zhao, Xinfeng; Li, Qian; Bian, Liujiao; Zheng, Xiaohui; Zheng, Jianbin; Zhang, Youyi; Li, Zijian


    Demand on high-throughput methods for multi-target compounds screening continues to increase nowadays due to the decline of new drugs on the market. Two kinds of G-protein-coupled receptors, alpha1-adrenoceptor (α(1A)-AR) and beta2-adrenoceptor (β(2)-AR), were purified and immobilized on the surface of macroporous silica gel to prepare new chromatographic stationary phases. Control drugs (e.g., prazosin, terazosin, salbutamol, and terbutaline) were used to characterize the retention behavior of the obtained α(1A)-AR and β(2)-AR columns. This study also coupled both columns with a six-way switching valve to construct an automatic two-dimensional system for multi-target compounds screening in complex mixtures. Adrenaline hydrochloride was used as a representative drug to evaluate the chromatographic performance of the two dimensional system. The aqueous extracts from Salvia miltiorrhiza and Coptis chinensis were also analyzed by the automatic system. The compounds in S. miltiorrhiza had no binding to both α(1A)-AR and β(2)-AR columns. But berberine, palmatine and jatrorrhizine were screened as the bioactive compounds in C. chinensis, targeting both the receptors. The proposed method is an alternative for recognizing and separating the compounds targeting different proteins from a complex matrix. PMID:22651959

  7. Automatic Arabic Hand Written Text Recognition System

    I. A. Jannoud


    Full Text Available Despite of the decent development of the pattern recognition science applications in the last decade of the twentieth century and this century, text recognition remains one of the most important problems in pattern recognition. To the best of our knowledge, little work has been done in the area of Arabic text recognition compared with those for Latin, Chins and Japanese text. The main difficulty encountered when dealing with Arabic text is the cursive nature of Arabic writing in both printed and handwritten forms. An Automatic Arabic Hand-Written Text Recognition (AHTR System is proposed. An efficient segmentation stage is required in order to divide a cursive word or sub-word into its constituting characters. After a word has been extracted from the scanned image, it is thinned and its base line is calculated by analysis of horizontal density histogram. The pattern is then followed through the base line and the segmentation points are detected. Thus after the segmentation stage, the cursive word is represented by a sequence of isolated characters. The recognition problem thus reduces to that of classifying each character. A set of features extracted from each individual characters. A minimum distance classifier is used. Some approaches are used for processing the characters and post processing added to enhance the results. Recognized characters will be appended directly to a word file which is editable form.

  8. Automatic Radiation Monitoring in Slovenia

    Full text: The automatic radiation monitoring system in Slovenia started in early nineties and now it comprises measurements of: 1. External gamma radiation: For the time being there are forty-three probes with GM tubes integrated into a common automatic network, operated at the SNSA. The probes measure dose rate in 30 minute intervals. 2. Aerosol radioactivity: Three automatic aerosol stations measure the concentration of artificial alpha and beta activity in the air, gamma emitting radionuclides, radioactive iodine 131 in the air (in all chemical forms, - natural radon and thoron progeny, 3. Radon progeny concentration: Radon progeny concentration is measured hourly and results are displayed as the equilibrium equivalent concentrations (EEC), 4. Radioactive deposition measurements: As a support to gamma dose rate measurements - the SNSA developed and installed an automatic measuring station for surface contamination equipped with gamma spectrometry system (with 3x3' NaI(Tl) detector). All data are transferred through the different communication pathways to the SNSA. They are collected in 30 minute intervals. Within these intervals the central computer analyses and processes the collected data, and creates different reports. Every month QA/QC analysis of data is performed, showing the statistics of acquisition errors and availability of measuring results. All results are promptly available at the our WEB pages. The data are checked and daily sent to the EURDEP system at Ispra (Italy) and also to the Austrian, Croatian and Hungarian authorities. (author)

  9. Eating as an Automatic Behavior

    Deborah A. Cohen, MD, MPH


    Full Text Available The continued growth of the obesity epidemic at a time when obesity is highly stigmatizing should make us question the assumption that, given the right information and motivation, people can successfully reduce their food intake over the long term. An alternative view is that eating is an automatic behavior over which the environment has more control than do individuals. Automatic behaviors are those that occur without awareness, are initiated without intention, tend to continue without control, and operate efficiently or with little effort. The concept that eating is an automatic behavior is supported by studies that demonstrate the impact of the environmental context and food presentation on eating. The amount of food eaten is strongly influenced by factors such as portion size, food visibility and salience, and the ease of obtaining food. Moreover, people are often unaware of the amount of food they have eaten or of the environmental influences on their eating. A revised view of eating as an automatic behavior, as opposed to one that humans can self-regulate, has profound implications for our response to the obesity epidemic, suggesting that the focus should be less on nutrition education and more on shaping the food environment.

  10. Automatic Association of News Items.

    Carrick, Christina; Watters, Carolyn


    Discussion of electronic news delivery systems and the automatic generation of electronic editions focuses on the association of related items of different media type, specifically photos and stories. The goal is to be able to determine to what degree any two news items refer to the same news event. (Author/LRW)