Sample records for target detection techniques

  1. Detection technique of targets for missile defense system

    NASA Astrophysics Data System (ADS)

    Guo, Hua-ling; Deng, Jia-hao; Cai, Ke-rong

    2009-11-01

    Ballistic missile defense system (BMDS) is a weapon system for intercepting enemy ballistic missiles. It includes ballistic-missile warning system, target discrimination system, anti-ballistic-missile guidance systems, and command-control communication system. Infrared imaging detection and laser imaging detection are widely used in BMDS for surveillance, target detection, target tracking, and target discrimination. Based on a comprehensive review of the application of target-detection techniques in the missile defense system, including infrared focal plane arrays (IRFPA), ground-based radar detection technology, 3-dimensional imaging laser radar with a photon counting avalanche photodiode (APD) arrays and microchip laser, this paper focuses on the infrared and laser imaging detection techniques in missile defense system, as well as the trends for their future development.

  2. Study on a novel laser target detection system based on software radio technique

    NASA Astrophysics Data System (ADS)

    Song, Song; Deng, Jia-hao; Wang, Xue-tian; Gao, Zhen; Sun, Ji; Sun, Zhi-hui

    2008-12-01

    This paper presents that software radio technique is applied to laser target detection system with the pseudo-random code modulation. Based on the theory of software radio, the basic framework of the system, hardware platform, and the implementation of the software system are detailed. Also, the block diagram of the system, DSP circuit, block diagram of the pseudo-random code generator, and soft flow diagram of signal processing are designed. Experimental results have shown that the application of software radio technique provides a novel method to realize the modularization, miniaturization and intelligence of the laser target detection system, and the upgrade and improvement of the system will become simpler, more convenient, and cheaper.

  3. The design and implementation of radar clutter modelling and adaptive target detection techniques

    NASA Astrophysics Data System (ADS)

    Ali, Mohammed Hussain

    The analysis and reduction of radar clutter is investigated. Clutter is the term applied to unwanted radar reflections from land, sea, precipitation, and/or man-made objects. A great deal of useful information regarding the characteristics of clutter can be obtained by the application of frequency domain analytical methods. Thus, some considerable time was spent assessing the various techniques available and their possible application to radar clutter. In order to better understand clutter, use of a clutter model was considered desirable. There are many techniques which will enable a target to be detected in the presence of clutter. One of the most flexible of these is that of adaptive filtering. This technique was thoroughly investigated and a method for improving its efficacy was devised. The modified adaptive filter employed differential adaption times to enhance detectability. Adaptation time as a factor relating to target detectability is a new concept and was investigated in some detail. It was considered desirable to implement the theoretical work in dedicated hardware to confirm that the modified clutter model and the adaptive filter technique actually performed as predicted. The equipment produced is capable of operation in real time and provides an insight into real time DSP applications. This equipment is sufficiently rapid to produce a real time display on the actual PPI system. Finally a software package was also produced which would simulate the operation of a PPI display and thus ease the interpretation of the filter outputs.

  4. The application of IR detector with windowing technique in the small and dim target detection

    NASA Astrophysics Data System (ADS)

    Su, Xiaofeng; Chen, Fansheng; Dong, Yucui; Cui, Kun; Huang, Sijie

    2015-04-01

    The performance of small and dim IR target detection is mostly affected by the signal to noise ratio(SNR) and signal to clutter ratio(SCR), for the MWIR especially LWIR array detector, because of the background radiation and the optical system radiation, the SCR cannot be unlimited increased by using a longer integral time, so the frame rate of the detector was mainly limited by the data readout time especially in a large-scale infrared detector, in this paper a new MWIR array detector with windowing technique was used to do the experiment, which can get a faster frame rate around the target by using the windowing mode, so the redundant information could be ignore, and the background subtraction was used to remove the fixed pattern noise and adjust the dynamic range of the target, then a local NUC(non uniformity correction) technique was proposed to improve the SCR of the target, the advantage between local NUC and global NUC was analyzed in detail, finally the multi local window frame accumulation was adopted to enhance the target further, and the SNR of the target was improved. The experiment showed the SCR of the target can improved from 1.3 to 36 at 30 frames accumulation, which make the target detection and tracking become very easily by using the new method.

  5. Synthetic aperture radar target detection, feature extraction, and image formation techniques

    NASA Technical Reports Server (NTRS)

    Li, Jian

    1994-01-01

    This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

  6. Background characterization techniques for target detection using scene metrics and pattern recognition

    NASA Astrophysics Data System (ADS)

    Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

    1990-09-01

    The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

  7. Covariance descriptor fusion for target detection

    NASA Astrophysics Data System (ADS)

    Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

    2016-05-01

    Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

  8. Camouflage target detection via hyperspectral imaging plus information divergence measurement

    NASA Astrophysics Data System (ADS)

    Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

    2016-01-01

    Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

  9. A comparison of machine learning techniques for detection of drug target articles.

    PubMed

    Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

    2010-12-01

    Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

  10. Overview of hybridization and detection techniques.

    PubMed

    Hilario, Elena

    2007-01-01

    A misconception regarding the sensitivity of nonradioactive methods for screening genomic DNA libraries often hinders the establishment of these environmentally friendly techniques in molecular biology laboratories. Nonradioactive probes, properly prepared and quantified, can detect DNA target molecules to the femtomole range. However, appropriate hybridization techniques and detection methods should also be adopted for an efficient use of nonradioactive techniques. Detailed descriptions of genomic library handling before and during the nonradioactive hybridization and detection are often omitted from publications. This chapter aims to fill this void by providing a collection of technical tips on hybridization and detection techniques.

  11. A novel scattering switch-on detection technique for target-induced plasmon-coupling based sensing by single-particle optical anisotropy imaging.

    PubMed

    Peng, Lan; Cao, Xuan; Xiong, Bin; He, Yan; Yeung, Edward S

    2016-06-18

    We reported a novel scattering switch-on detection technique using flash-lamp polarization darkfield microscopy (FLPDM) for target-induced plasmon-coupling based sensing in homogeneous solution. With this method, we demonstrated sub-nM sensitivity for hydrogen sulfide (H2S) detection over a dynamic range of five orders of magnitude. This robust technique holds great promise for applications in toxic environmental pollutants and biological molecules.

  12. Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform

    NASA Astrophysics Data System (ADS)

    Binol, Hamidullah; Bal, Abdullah

    2016-05-01

    A novel hyperspectral target detection technique based on Fukunaga-Koontz transform (FKT) is presented. FKT offers significant properties for feature selection and ordering. However, it can only be used to solve multi-pattern classification problems. Target detection may be considered as a two-class classification problem, i.e., target versus background clutter. Nevertheless, background clutter typically contains different types of materials. That's why; target detection techniques are different than classification methods by way of modeling clutter. To avoid the modeling of the background clutter, we have improved one-class FKT (OC-FKT) for target detection. The statistical properties of target training samples are used to define tunnel-like boundary of the target class. Non-target samples are then created synthetically as to be outside of the boundary. Thus, only limited target samples become adequate for training of FKT. The hyperspectral image experiments confirm that the proposed OC-FKT technique provides an effective means for target detection.

  13. Outlier and target detection in aerial hyperspectral imagery: a comparison of traditional and percentage occupancy hit or miss transform techniques

    NASA Astrophysics Data System (ADS)

    Young, Andrew; Marshall, Stephen; Gray, Alison

    2016-05-01

    The use of aerial hyperspectral imagery for the purpose of remote sensing is a rapidly growing research area. Currently, targets are generally detected by looking for distinct spectral features of the objects under surveillance. For example, a camouflaged vehicle, deliberately designed to blend into background trees and grass in the visible spectrum, can be revealed using spectral features in the near-infrared spectrum. This work aims to develop improved target detection methods, using a two-stage approach, firstly by development of a physics-based atmospheric correction algorithm to convert radiance into re ectance hyperspectral image data and secondly by use of improved outlier detection techniques. In this paper the use of the Percentage Occupancy Hit or Miss Transform is explored to provide an automated method for target detection in aerial hyperspectral imagery.

  14. Biased normalized cuts for target detection in hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Xuewen; Dorado-Munoz, Leidy P.; Messinger, David W.; Cahill, Nathan D.

    2016-05-01

    The Biased Normalized Cuts (BNC) algorithm is a useful technique for detecting targets or objects in RGB imagery. In this paper, we propose modifying BNC for the purpose of target detection in hyperspectral imagery. As opposed to other target detection algorithms that typically encode target information prior to dimensionality reduction, our proposed algorithm encodes target information after dimensionality reduction, enabling a user to detect different targets in interactive mode. To assess the proposed BNC algorithm, we utilize hyperspectral imagery (HSI) from the SHARE 2012 data campaign, and we explore the relationship between the number and the position of expert-provided target labels and the precision/recall of the remaining targets in the scene.

  15. Detecting targets hidden in random forests

    NASA Astrophysics Data System (ADS)

    Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

    2009-05-01

    Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

  16. Multisensor fusion for the detection of mines and minelike targets

    NASA Astrophysics Data System (ADS)

    Hanshaw, Terilee

    1995-06-01

    The US Army's Communications and Electronics Command through the auspices of its Night Vision and Electronics Sensors Directorate (CECOM-NVESD) is actively applying multisensor techniques to the detection of mine targets. This multisensor research results from the 'detection activity' with its broad range of operational conditions and targets. Multisensor operation justifies significant attention by yielding high target detection and low false alarm statistics. Furthermore, recent advances in sensor and computing technologies make its practical application realistic and affordable. The mine detection field-of-endeavor has since its WWI baptismal investigated the known spectra for applicable mine observation phenomena. Countless sensors, algorithms, processors, networks, and other techniques have been investigated to determine candidacy for mine detection. CECOM-NVESD efforts have addressed a wide range of sensors spanning the spectrum from gravity field perturbations, magentic field disturbances, seismic sounding, electromagnetic fields, earth penetrating radar imagery, and infrared/visible/ultraviolet surface imaging technologies. Supplementary analysis has considered sensor candidate applicability by testing under field conditions (versus laboratory), in determination of fieldability. As these field conditions directly effect the probability of detection and false alarms, sensor employment and design must be considered. Consequently, as a given sensor's performance is influenced directly by the operational conditions, tradeoffs are necessary. At present, mass produced and fielded mine detection techniques are limited to those incorporating a single sensor/processor methodology such as, pulse induction and megnetometry, as found in hand held detectors. The most sensitive fielded systems can detect minute metal components in small mine targets but result in very high false alarm rates reducing velocity in operation environments. Furthermore, the actual speed of

  17. Penalty dynamic programming algorithm for dim targets detection in sensor systems.

    PubMed

    Huang, Dayu; Xue, Anke; Guo, Yunfei

    2012-01-01

    In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

  18. Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

    PubMed Central

    Huang, Dayu; Xue, Anke; Guo, Yunfei

    2012-01-01

    In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations. PMID:22666074

  19. Spectral Target Detection using Schroedinger Eigenmaps

    NASA Astrophysics Data System (ADS)

    Dorado-Munoz, Leidy P.

    Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and

  20. Detection of target-probe oligonucleotide hybridization using synthetic nanopore resistive pulse sensing.

    PubMed

    Booth, Marsilea Adela; Vogel, Robert; Curran, James M; Harbison, SallyAnn; Travas-Sejdic, Jadranka

    2013-07-15

    Despite the plethora of DNA sensor platforms available, a portable, sensitive, selective and economic sensor able to rival current fluorescence-based techniques would find use in many applications. In this research, probe oligonucleotide-grafted particles are used to detect target DNA in solution through a resistive pulse nanopore detection technique. Using carbodiimide chemistry, functionalized probe DNA strands are attached to carboxylated dextran-based magnetic particles. Subsequent incubation with complementary target DNA yields a change in surface properties as the two DNA strands hybridize. Particle-by-particle analysis with resistive pulse sensing is performed to detect these changes. A variable pressure method allows identification of changes in the surface charge of particles. As proof-of-principle, we demonstrate that target hybridization is selectively detected at micromolar concentrations (nanomoles of target) using resistive pulse sensing, confirmed by fluorescence and phase analysis light scattering as complementary techniques. The advantages, feasibility and limitations of using resistive pulse sensing for sample analysis are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. A Sensitive TLRH Targeted Imaging Technique for Ultrasonic Molecular Imaging

    PubMed Central

    Hu, Xiaowen; Zheng, Hairong; Kruse, Dustin E.; Sutcliffe, Patrick; Stephens, Douglas N.; Ferrara, Katherine W.

    2010-01-01

    The primary goals of ultrasound molecular imaging are the detection and imaging of ultrasound contrast agents (microbubbles), which are bound to specific vascular surface receptors. Imaging methods that can sensitively and selectively detect and distinguish bound microbubbles from freely circulating microbubbles (free microbubbles) and surrounding tissue are critically important for the practical application of ultrasound contrast molecular imaging. Microbubbles excited by low frequency acoustic pulses emit wide-band echoes with a bandwidth extending beyond 20 MHz; we refer to this technique as TLRH (transmission at a low frequency and reception at a high frequency). Using this wideband, transient echo, we have developed and implemented a targeted imaging technique incorporating a multi-frequency co-linear array and the Siemens Antares® imaging system. The multi-frequency co-linear array integrates a center 5.4 MHz array, used to receive echoes and produce radiation force, and two outer 1.5 MHz arrays used to transmit low frequency incident pulses. The targeted imaging technique makes use of an acoustic radiation force sub-sequence to enhance accumulation and a TLRH imaging sub-sequence to detect bound microbubbles. The radiofrequency (RF) data obtained from the TLRH imaging sub-sequence are processsed to separate echo signatures between tissue, free microbubbles, and bound microbubbles. By imaging biotin-coated microbubbles targeted to avidin-coated cellulose tubes, we demonstrate that the proposed method has a high contrast-to-tissue ratio (up to 34 dB) and a high sensitivity to bound microbubbles (with the ratio of echoes from bound microbubbles versus free microbubbles extending up to 23 dB). The effects of the imaging pulse acoustic pressure, the radiation force sub-sequence and the use of various slow-time filters on the targeted imaging quality are studied. The TLRH targeted imaging method is demonstrated in this study to provide sensitive and selective

  2. Detection of Moving Targets Using Soliton Resonance Effect

    NASA Technical Reports Server (NTRS)

    Kulikov, Igor K.; Zak, Michail

    2013-01-01

    The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

  3. An Automated Directed Spectral Search Methodology for Small Target Detection

    NASA Astrophysics Data System (ADS)

    Grossman, Stanley I.

    search techniques of spectral image based small target detection. It offers evidence of the functionality of the NNI visualization and also provides evidence that the increased spectral dimensionality of the 8-band Worldview-2 datasets provides noteworthy improvement in results over traditional 4-band multispectral datasets. The final experiment presents the results from a prototype fully automated target detection scheme in support of the overarching premise. This work establishes the analytic sweet spot as the optimum threshold defined as the point where error detection rate curves -- false detections vs. missing detections -- cross. At this point the errors are minimized while the detection rate is maximized. It then demonstrates that taking the first moment statistic of the histogram of calculated target detection values from a detection search with test threshold set arbitrarily high will estimate the analytic sweet spot for that image. It also demonstrates that directed search techniques -- when utilized with appropriate scene-specific modeled signatures and atmospheric compensations -- perform at least as well as in-scene search techniques 88% of the time and grossly under-performing only 11% of the time; the in-scene only performs as well or better 50% of the time. It further demonstrates the clear advantage increased multispectral dimensionality brings to detection searches improving performance in 50% of the cases while performing at least as well 72% of the time. Lastly, it presents evidence that a fully automated prototype performs as anticipated laying the groundwork for further research into fully automated processes for small target detection.

  4. Targeted Analyte Detection by Standard Addition Improves Detection Limits in MALDI Mass Spectrometry

    PubMed Central

    Eshghi, Shadi Toghi; Li, Xingde; Zhang, Hui

    2014-01-01

    Matrix-assisted laser desorption/ionization has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications. PMID:22877355

  5. [Progress of study on the detection technique of microRNA].

    PubMed

    Zhao, Hai-Feng; Yang, Ren-Chi

    2009-12-01

    MicroRNAs (miRNAs) are small noncoding RNA molecules that negatively regulate gene expression via degradation or translational repression of their targeted mRNAs. MiRNAs are involved in critical biologic processes, including development, cell differentiation, proliferation and the pathogenesis of disease. This review focuses on recent researches on the detection techniques of miRNA including micorarray technique, Northern blot, real-time quantitative PCR, detection technique of miRNA function and so on.

  6. Dim target trajectory-associated detection in bright earth limb background

    NASA Astrophysics Data System (ADS)

    Chen, Penghui; Xu, Xiaojian; He, Xiaoyu; Jiang, Yuesong

    2015-09-01

    The intensive emission of earth limb in the field of view of sensors contributes much to the observation images. Due to the low signal-to-noise ratio (SNR), it is a challenge to detect small targets in earth limb background, especially for the detection of point-like targets from a single frame. To improve the target detection, track before detection (TBD) based on the frame sequence is performed. In this paper, a new technique is proposed to determine the target associated trajectories, which jointly carries out background removing, maximum value projection (MVP) and Hough transform. The background of the bright earth limb in the observation images is removed according to the profile characteristics. For a moving target, the corresponding pixels in the MVP image are shifting approximately regularly in time sequence. And the target trajectory is determined by Hough transform according to the pixel characteristics of the target and the clutter and noise. Comparing with traditional frame-by-frame methods, determining associated trajectories from MVP reduces the computation load. Numerical simulations are presented to demonstrate the effectiveness of the approach proposed.

  7. Infrared moving small target detection based on saliency extraction and image sparse representation

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaomin; Ren, Kan; Gao, Jin; Li, Chaowei; Gu, Guohua; Wan, Minjie

    2016-10-01

    Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.

  8. Incorporating signal-dependent noise for hyperspectral target detection

    NASA Astrophysics Data System (ADS)

    Morman, Christopher J.; Meola, Joseph

    2015-05-01

    The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

  9. Sensor Compromise Detection in Multiple-Target Tracking Systems

    PubMed Central

    Doucette, Emily A.; Curtis, Jess W.

    2018-01-01

    Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. PMID:29466314

  10. An electromagnetic induction method for underground target detection and characterization

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

    Bartel, L.C.; Cress, D.H.

    1997-01-01

    An improved capability for subsurface structure detection is needed to support military and nonproliferation requirements for inspection and for surveillance of activities of threatening nations. As part of the DOE/NN-20 program to apply geophysical methods to detect and characterize underground facilities, Sandia National Laboratories (SNL) initiated an electromagnetic induction (EMI) project to evaluate low frequency electromagnetic (EM) techniques for subsurface structure detection. Low frequency, in this case, extended from kilohertz to hundreds of kilohertz. An EMI survey procedure had already been developed for borehole imaging of coal seams and had successfully been applied in a surface mode to detect amore » drug smuggling tunnel. The SNL project has focused on building upon the success of that procedure and applying it to surface and low altitude airborne platforms. Part of SNL`s work has focused on improving that technology through improved hardware and data processing. The improved hardware development has been performed utilizing Laboratory Directed Research and Development (LDRD) funding. In addition, SNL`s effort focused on: (1) improvements in modeling of the basic geophysics of the illuminating electromagnetic field and its coupling to the underground target (partially funded using LDRD funds) and (2) development of techniques for phase-based and multi-frequency processing and spatial processing to support subsurface target detection and characterization. The products of this project are: (1) an evaluation of an improved EM gradiometer, (2) an improved gradiometer concept for possible future development, (3) an improved modeling capability, (4) demonstration of an EM wave migration method for target recognition, and a demonstration that the technology is capable of detecting targets to depths exceeding 25 meters.« less

  11. Detection of Mycobacterium avium subspecies paratuberculosis in tie-stall dairy herds using a standardized environmental sampling technique and targeted pooled samples.

    PubMed

    Arango-Sabogal, Juan C; Côté, Geneviève; Paré, Julie; Labrecque, Olivia; Roy, Jean-Philippe; Buczinski, Sébastien; Doré, Elizabeth; Fairbrother, Julie H; Bissonnette, Nathalie; Wellemans, Vincent; Fecteau, Gilles

    2016-07-01

    Mycobacterium avium ssp. paratuberculosis (MAP) is the etiologic agent of Johne's disease, a chronic contagious enteritis of ruminants that causes major economic losses. Several studies, most involving large free-stall herds, have found environmental sampling to be a suitable method for detecting MAP-infected herds. In eastern Canada, where small tie-stall herds are predominant, certain conditions and management practices may influence the survival and transmission of MAP and recovery (isolation). Our objective was to estimate the performance of a standardized environmental and targeted pooled sampling technique for the detection of MAP-infected tie-stall dairy herds. Twenty-four farms (19 MAP-infected and 5 non-infected) were enrolled, but only 20 were visited twice in the same year, to collect 7 environmental samples and 2 pooled samples (sick cows and cows with poor body condition). Concurrent individual sampling of all adult cows in the herds was also carried out. Isolation of MAP was achieved using the MGIT Para TB culture media and the BACTEC 960 detection system. Overall, MAP was isolated in 7% of the environmental cultures. The sensitivity of the environmental culture was 44% [95% confidence interval (CI): 20% to 70%] when combining results from 2 different herd visits and 32% (95% CI: 13% to 57%) when results from only 1 random herd visit were used. The best sampling strategy was to combine samples from the manure pit, gutter, sick cows, and cows with poor body condition. The standardized environmental sampling technique and the targeted pooled samples presented in this study is an alternative sampling strategy to costly individual cultures for detecting MAP-infected tie-stall dairies. Repeated samplings may improve the detection of MAP-infected herds.

  12. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar

    PubMed Central

    Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

    2016-01-01

    The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications. PMID:27690051

  13. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.

    PubMed

    Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

    2016-09-29

    The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

  14. Targeted analyte detection by standard addition improves detection limits in matrix-assisted laser desorption/ionization mass spectrometry.

    PubMed

    Toghi Eshghi, Shadi; Li, Xingde; Zhang, Hui

    2012-09-18

    Matrix-assisted laser desorption/ionization (MALDI) has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications.

  15. A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

    NASA Astrophysics Data System (ADS)

    Lyu, Jiang-Tao; Zhou, Chen

    2017-12-01

    Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

  16. Infrared small target detection based on multiscale center-surround contrast measure

    NASA Astrophysics Data System (ADS)

    Fu, Hao; Long, Yunli; Zhu, Ran; An, Wei

    2018-04-01

    Infrared(IR) small target detection plays a critical role in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some difficulties remained to the clutter environment. According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for infrared small target detection called multiscale centersurround contrast measure (MCSCM). First, to determine the maximum neighboring window size, an entropy-based window selection technique is used. Then, we construct a novel multiscale center-surround contrast measure to calculate the saliency map. Compared with the original image, the MCSCM map has less background clutters and noise residual. Subsequently, a simple threshold is used to segment the target. Experimental results show our method achieves better performance.

  17. A novel, simple and rapid nondenaturing FISH (ND-FISH) technique for the detection of plant telomeres. Potential used and possible target structures detected.

    PubMed

    Cuadrado, Angeles; Golczyk, Hieronim; Jouve, Nicolás

    2009-01-01

    We report a new technique-nondenaturing FISH (ND-FISH)-for the rapid detection of plant telomeres without the need for prior denaturation of the chromosomes. In its development, two modified, synthetic oligonucleotides, 21 nt in length, fluorescently labelled at their 5' and 3' ends and complementary to either the cytidine-rich (C(3)TA(3)) or guanosine-rich (T(3)AG(3)) telomeric DNA strands, were used as probes. The high binding affinity of these probes and the short hybridization time required allows the visualization of plant telomeres in less than an hour. In tests, both probes gave strong signals visualized as double spots at both chromosome ends; this was true of both the mitotic and meiotic chromosomes of barley, wheat, rye, maize, Brachypodium distachyon and Rhoeo spathacea. They were also able to detect telomere motifs at certain intercalary sites in the chromosomes of R. spathacea. To investigate the nature of the target structures detected, the chromosomes were treated with RNase A and single strand-specific nuclease S1 before ND-FISH experiments. Signal formation was resistant to standard enzymatic treatment, but sensitive when much higher enzyme concentrations were used. The results are discussed in relation to current knowledge of telomere structure.

  18. Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

    NASA Astrophysics Data System (ADS)

    Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

    2017-04-01

    Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

  19. Camouflaged target detection based on polarized spectral features

    NASA Astrophysics Data System (ADS)

    Tan, Jian; Zhang, Junping; Zou, Bin

    2016-05-01

    The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

  20. Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

    2018-03-01

    In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

  1. Space moving target detection using time domain feature

    NASA Astrophysics Data System (ADS)

    Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

    2018-01-01

    The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

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

    NASA Astrophysics Data System (ADS)

    Riasati, Vahid R.

    2016-05-01

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

  3. Target discrimination strategies in optics detection

    NASA Astrophysics Data System (ADS)

    Sjöqvist, Lars; Allard, Lars; Henriksson, Markus; Jonsson, Per; Pettersson, Magnus

    2013-10-01

    Detection and localisation of optical assemblies used for weapon guidance or sniper rifle scopes has attracted interest for security and military applications. Typically a laser system is used to interrogate a scene of interest and the retro-reflected radiation is detected. Different system approaches for area coverage can be realised ranging from flood illumination to step-and-stare or continuous scanning schemes. Independently of the chosen approach target discrimination is a crucial issue, particularly if a complex scene such as in an urban environment and autonomous operation is considered. In this work target discrimination strategies in optics detection are discussed. Typical parameters affecting the reflected laser radiation from the target are the wavelength, polarisation properties, temporal effects and the range resolution. Knowledge about the target characteristics is important to predict the target discrimination capability. Two different systems were used to investigate polarisation properties and range resolution information from targets including e.g. road signs, optical reflexes, rifle sights and optical references. The experimental results and implications on target discrimination will be discussed. If autonomous operation is required target discrimination becomes critical in order to reduce the number of false alarms.

  4. A method for detecting small targets based on cumulative weighted value of target properties

    NASA Astrophysics Data System (ADS)

    Jin, Xing; Sun, Gang; Wang, Wei-hua; Liu, Fang; Chen, Zeng-ping

    2015-03-01

    Laser detection based on the "cat's eye effect" has become the hot research project for its initiative compared to the passivity of sound detection and infrared detection. And the target detection is one of the core technologies in this system. The paper puts forward a method for detecting small targets based on cumulative weighted value of target properties using given data. Firstly, we make a frame difference to the images, then make image processing based on Morphology Principles. Secondly, we segment images, and screen the targets; then find some interesting locations. Finally, comparing to a quantity of frames, we locate the target. We did an exam to 394 true frames, the experimental result shows that the mathod can detect small targets efficiently.

  5. Improving detection of low SNR targets using moment-based detection

    NASA Astrophysics Data System (ADS)

    Young, Shannon R.; Steward, Bryan J.; Hawks, Michael; Gross, Kevin C.

    2016-05-01

    Increases in the number of cameras deployed, frame rate, and detector array sizes have led to a dramatic increase in the volume of motion imagery data that is collected. Without a corresponding increase in analytical manpower, much of the data is not analyzed to full potential. This creates a need for fast, automated, and robust methods for detecting signals of interest. Current approaches fall into two categories: detect-before-track (DBT), which are fast but often poor at detecting dim targets, and track-before-detect (TBD) methods which can offer better performance but are typically much slower. This research seeks to contribute to the near real time detection of low SNR, unresolved moving targets through an extension of earlier work on higher order moments anomaly detection, a method that exploits both spatial and temporal information but is still computationally efficient and massively parallelizable. It was found that intelligent selection of parameters can improve probability of detection by as much as 25% compared to earlier work with higherorder moments. The present method can reduce detection thresholds by 40% compared to the Reed-Xiaoli anomaly detector for low SNR targets (for a given probability of detection and false alarm).

  6. Instrumentation of Molecular Imaging on Site-Specific Targeting Fluorescent Peptide for Early Detection of Breast Cancer

    NASA Astrophysics Data System (ADS)

    Yu, Ping; Ma, Lixin

    2012-02-01

    In this work we developed two biomedical imaging techniques for early detection of breast cancer. Both image modalities provide molecular imaging capability to probe site-specific targeting dyes. The first technique, heterodyne CCD fluorescence mediated tomography, is a non-invasive biomedical imaging that uses fluorescent photons from the targeted dye on the tumor cells inside human breast tissue. The technique detects a large volume of tissue (20 cm) with a moderate resolution (1 mm) and provides the high sensitivity. The second technique, dual-band spectral-domain optical coherence tomography, is a high-resolution tissue imaging modality. It uses a low coherence interferometer to detect coherent photons hidden in the incoherent background. Due to the coherence detection, a high resolution (20 microns) is possible. We have finished prototype imaging systems for the development of both image modalities and performed imaging experiments on tumor tissues. The spectroscopic/tomographic images show contrasts of dense tumor tissues and tumor necrotic regions. In order to correlate the findings from our results, a diffusion-weighted magnetic resonance imaging (MRI) of the tumors was performed using a small animal 7-Telsa MRI and demonstrated excellent agreement.

  7. Infrared dim target detection based on visual attention

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Lv, Guofang; Xu, Lizhong

    2012-11-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  8. Lifting wavelet method of target detection

    NASA Astrophysics Data System (ADS)

    Han, Jun; Zhang, Chi; Jiang, Xu; Wang, Fang; Zhang, Jin

    2009-11-01

    Image target recognition plays a very important role in the areas of scientific exploration, aeronautics and space-to-ground observation, photography and topographic mapping. Complex environment of the image noise, fuzzy, all kinds of interference has always been to affect the stability of recognition algorithm. In this paper, the existence of target detection in real-time, accuracy problems, as well as anti-interference ability, using lifting wavelet image target detection methods. First of all, the use of histogram equalization, the goal difference method to obtain the region, on the basis of adaptive threshold and mathematical morphology operations to deal with the elimination of the background error. Secondly, the use of multi-channel wavelet filter wavelet transform of the original image de-noising and enhancement, to overcome the general algorithm of the noise caused by the sensitive issue of reducing the rate of miscarriage of justice will be the multi-resolution characteristics of wavelet and promotion of the framework can be designed directly in the benefits of space-time region used in target detection, feature extraction of targets. The experimental results show that the design of lifting wavelet has solved the movement of the target due to the complexity of the context of the difficulties caused by testing, which can effectively suppress noise, and improve the efficiency and speed of detection.

  9. Multiple targets detection method in detection of UWB through-wall radar

    NASA Astrophysics Data System (ADS)

    Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

    2017-11-01

    In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

  10. Hyperspectral target detection using heavy-tailed distributions

    NASA Astrophysics Data System (ADS)

    Willis, Chris J.

    2009-09-01

    One promising approach to target detection in hyperspectral imagery exploits a statistical mixture model to represent scene content at a pixel level. The process then goes on to look for pixels which are rare, when judged against the model, and marks them as anomalies. It is assumed that military targets will themselves be rare and therefore likely to be detected amongst these anomalies. For the typical assumption of multivariate Gaussianity for the mixture components, the presence of the anomalous pixels within the training data will have a deleterious effect on the quality of the model. In particular, the derivation process itself is adversely affected by the attempt to accommodate the anomalies within the mixture components. This will bias the statistics of at least some of the components away from their true values and towards the anomalies. In many cases this will result in a reduction in the detection performance and an increased false alarm rate. This paper considers the use of heavy-tailed statistical distributions within the mixture model. Such distributions are better able to account for anomalies in the training data within the tails of their distributions, and the balance of the pixels within their central masses. This means that an improved model of the majority of the pixels in the scene may be produced, ultimately leading to a better anomaly detection result. The anomaly detection techniques are examined using both synthetic data and hyperspectral imagery with injected anomalous pixels. A range of results is presented for the baseline Gaussian mixture model and for models accommodating heavy-tailed distributions, for different parameterizations of the algorithms. These include scene understanding results, anomalous pixel maps at given significance levels and Receiver Operating Characteristic curves.

  11. Optoacoustic detection of viral antigens using targeted gold nanorods

    NASA Astrophysics Data System (ADS)

    Maswadi, Saher; Woodward, Lee; Glickman, Randolph D.; Barsalou, Norman

    2009-02-01

    We are detecting antigens (Ag), isolated from infectious organisms, utilizing laser optoacoustic spectroscopy and antibody-coupled gold nanorod (NR) contrast agents specifically targeted to the antigen of interest. We have detected, in clinical ocular samples, both Herpes Simplex Virus Type 1 and 2 (HSV-1 and HSV-2) . A monoclonal antibody (Ab) specific to both HSV-1 and HSV-2 was conjugated to gold nanorods to produce a targeted contrast agent with a strong optoacoustic signal. Elutions obtained from patient corneal swabs were adsorbed in standard plastic micro-wells. An immunoaffinity reaction was then performed with the functionalized gold nanorods, and the results were probed with an OPO laser, emitting wavelengths at the peak absorptions of the nanorods. Positive optoacoustic responses were obtained from samples containing authentic (microbiologically confirmed) HSV-1 and HSV-2. To obtain an estimate of the sensitivity of the technique, serial dilutions from 1 mg/ml to 1 pg/ml of a C. trachomatis surface Ag were prepared, and were probed with a monoclonal Ab, specific to the C. trachomatis surface Ag, conjugated to gold nanorods. An optoacoustic response was obtained, proportional to the concentration of antigen, and with a limit of detection of about 5 pg/ml. The optoacoustic signals generated from micro-wells containing albumin or saline were similar to those from blank wells. The potential benefit of this method is identify viral agents more rapidly than with existing techniques. In addition, the sensitivity of the assay is comparable or superior to existing colorimetric- or fluorometric-linked immunoaffinity assays.

  12. Infrared images target detection based on background modeling in the discrete cosine domain

    NASA Astrophysics Data System (ADS)

    Ye, Han; Pei, Jihong

    2018-02-01

    Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.

  13. A comparison of directed search target detection versus in-scene target detection in Worldview-2 datasets

    NASA Astrophysics Data System (ADS)

    Grossman, S.

    2015-05-01

    Since the events of September 11, 2001, the intelligence focus has moved from large order-of-battle targets to small targets of opportunity. Additionally, the business community has discovered the use of remotely sensed data to anticipate demand and derive data on their competition. This requires the finer spectral and spatial fidelity now available to recognize those targets. This work hypothesizes that directed searches using calibrated data perform at least as well as inscene manually intensive target detection searches. It uses calibrated Worldview-2 multispectral images with NEF generated signatures and standard detection algorithms to compare bespoke directed search capabilities against ENVI™ in-scene search capabilities. Multiple execution runs are performed at increasing thresholds to generate detection rates. These rates are plotted and statistically analyzed. While individual head-to-head comparison results vary, 88% of the directed searches performed at least as well as in-scene searches with 50% clearly outperforming in-scene methods. The results strongly support the premise that directed searches perform at least as well as comparable in-scene searches.

  14. A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

    PubMed

    Demidov, German; Simakova, Tamara; Vnuchkova, Julia; Bragin, Anton

    2016-10-22

    Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

  15. New target and detection methods: active detectors

    NASA Astrophysics Data System (ADS)

    Mittig, W.; Savajols, H.; Demonchy, C. E.; Giot, L.; Roussel-Chomaz, P.; Wang, H.; Ter-Akopian, G.; Fomichev, A.; Golovkov, M. S.; Stepansov, S.; Wolski, R.; Alamanos, N.; Drouart, A.; Gillibert, A.; Lapoux, V.; Pollacco, E.

    2003-07-01

    The study of nuclei far from stability interacting with simple target nuclei, such as protons, deuterons, 3He and 4He implies the use of inverse kinematics. The very special kinematics, together with the low intensities of the beams calls for special techniques. In july 2002 we tested a new detector, in which the detector gas is the target. This allows in principle a 4π solid angle of the detection, and a big effective target thickness without loss of resolution. The detector developped, called Maya, used isobuthane C4H10 as gas in present tests, and other gases are possible. The multiplexed electronics of more than 1000channels allows the reconstruction of the events occuring between the incoming particle and the detector gas atoms in 3D. Here we were interested in the elastic scattering of 8He on protons for the study of the isobaric analogue states (IAS) of 9He. The beam, in this case, is stopped in the detector. The resonance energy is determined by the place of interaction and the energy of the recoiling proton. The design of the detector is shown, together with some preliminary results are discussed.

  16. Evaluation of Targeted Next-Generation Sequencing for Detection of Bovine Pathogens in Clinical Samples.

    PubMed

    Anis, Eman; Hawkins, Ian K; Ilha, Marcia R S; Woldemeskel, Moges W; Saliki, Jeremiah T; Wilkes, Rebecca P

    2018-07-01

    The laboratory diagnosis of infectious diseases, especially those caused by mixed infections, is challenging. Routinely, it requires submission of multiple samples to separate laboratories. Advances in next-generation sequencing (NGS) have provided the opportunity for development of a comprehensive method to identify infectious agents. This study describes the use of target-specific primers for PCR-mediated amplification with the NGS technology in which pathogen genomic regions of interest are enriched and selectively sequenced from clinical samples. In the study, 198 primers were designed to target 43 common bovine and small-ruminant bacterial, fungal, viral, and parasitic pathogens, and a bioinformatics tool was specifically constructed for the detection of targeted pathogens. The primers were confirmed to detect the intended pathogens by testing reference strains and isolates. The method was then validated using 60 clinical samples (including tissues, feces, and milk) that were also tested with other routine diagnostic techniques. The detection limits of the targeted NGS method were evaluated using 10 representative pathogens that were also tested by quantitative PCR (qPCR), and the NGS method was able to detect the organisms from samples with qPCR threshold cycle ( C T ) values in the 30s. The method was successful for the detection of multiple pathogens in the clinical samples, including some additional pathogens missed by the routine techniques because the specific tests needed for the particular organisms were not performed. The results demonstrate the feasibility of the approach and indicate that it is possible to incorporate NGS as a diagnostic tool in a cost-effective manner into a veterinary diagnostic laboratory. Copyright © 2018 Anis et al.

  17. A manifold learning approach to target detection in high-resolution hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Ziemann, Amanda K.

    Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into

  18. Texture metric that predicts target detection performance

    NASA Astrophysics Data System (ADS)

    Culpepper, Joanne B.

    2015-12-01

    Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

  19. Marine Targets Detection in Pol-SAR Data

    NASA Astrophysics Data System (ADS)

    Chen, Peng; Yang, Jingsong

    2016-08-01

    In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.

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

    NASA Astrophysics Data System (ADS)

    Özertem, Kemal Arda

    2016-05-01

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

  1. Small target pre-detection with an attention mechanism

    NASA Astrophysics Data System (ADS)

    Wang, Yuehuan; Zhang, Tianxu; Wang, Guoyou

    2002-04-01

    We introduce the concept of predetection based on an attention mechanism to improve the efficiency of small-target detection by limiting the image region of detection. According to the characteristics of small-target detection, local contrast is taken as the only feature in predetection and a nonlinear sampling model is adopted to make the predetection adaptive to detect small targets with different area sizes. To simplify the predetection itself and decrease the false alarm probability, neighboring nodes in the sampling grid are used to generate a saliency map, and a short-term memory is adopted to accelerate the `pop-out' of targets. We discuss the fact that the proposed approach is simple enough in computational complexity. In addition, even in a cluttered background, attention can be led to targets in a satisfying few iterations, which ensures that the detection efficiency will not be decreased due to false alarms. Experimental results are presented to demonstrate the applicability of the approach.

  2. Detection and identification of human targets in radar data

    NASA Astrophysics Data System (ADS)

    Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

    2007-04-01

    Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

  3. Entanglement-enhanced Neyman-Pearson target detection using quantum illumination

    NASA Astrophysics Data System (ADS)

    Zhuang, Quntao; Zhang, Zheshen; Shapiro, Jeffrey H.

    2017-08-01

    Quantum illumination (QI) provides entanglement-based target detection---in an entanglement-breaking environment---whose performance is significantly better than that of optimum classical-illumination target detection. QI's performance advantage was established in a Bayesian setting with the target presumed equally likely to be absent or present and error probability employed as the performance metric. Radar theory, however, eschews that Bayesian approach, preferring the Neyman-Pearson performance criterion to avoid the difficulties of accurately assigning prior probabilities to target absence and presence and appropriate costs to false-alarm and miss errors. We have recently reported an architecture---based on sum-frequency generation (SFG) and feedforward (FF) processing---for minimum error-probability QI target detection with arbitrary prior probabilities for target absence and presence. In this paper, we use our results for FF-SFG reception to determine the receiver operating characteristic---detection probability versus false-alarm probability---for optimum QI target detection under the Neyman-Pearson criterion.

  4. Multispectral infrared target detection: phenomenology and modeling

    NASA Astrophysics Data System (ADS)

    Cederquist, Jack N.; Rogne, Timothy J.; Schwartz, Craig R.

    1993-10-01

    Many targets of interest provide only very small signature differences from the clutter background. The ability to detect these small difference targets should be improved by using data which is diverse in space, time, wavelength or some other observable. Target materials often differ from background materials in the variation of their reflectance or emittance with wavelength. A multispectral sensor is therefore considered as a means to improve detection of small signal targets. If this sensor operates in the thermal infrared, it will not need solar illumination and will be useful at night as well as during the day. An understanding of the phenomenology of the spectral properties of materials and an ability to model and simulate target and clutter signatures is needed to understand potential target detection performance from multispectral infrared sensor data. Spectral variations in material emittance are due to vibrational energy transitions in molecular bonds. The spectral emittances of many materials of interest have been measured. Examples are vegetation, soil, construction and road materials, and paints. A multispectral infrared signature model has been developed which includes target and background temperature and emissivity, sky, sun, cloud and background irradiance, multiple reflection effects, path radiance, and atmospheric attenuation. This model can be used to predict multispectral infrared signatures for small signal targets.

  5. High volume fabrication of laser targets using MEMS techniques

    NASA Astrophysics Data System (ADS)

    Spindloe, C.; Arthur, G.; Hall, F.; Tomlinson, S.; Potter, R.; Kar, S.; Green, J.; Higginbotham, A.; Booth, N.; Tolley, M. K.

    2016-04-01

    The latest techniques for the fabrication of high power laser targets, using processes developed for the manufacture of Micro-Electro-Mechanical System (MEMS) devices are discussed. These laser targets are designed to meet the needs of the increased shot numbers that are available in the latest design of laser facilities. Traditionally laser targets have been fabricated using conventional machining or coarse etching processes and have been produced in quantities of 10s to low 100s. Such targets can be used for high complexity experiments such as Inertial Fusion Energy (IFE) studies and can have many complex components that need assembling and characterisation with high precision. Using the techniques that are common to MEMS devices and integrating these with an existing target fabrication capability we are able to manufacture and deliver targets to these systems. It also enables us to manufacture novel targets that have not been possible using other techniques. In addition, developments in the positioning systems that are required to deliver these targets to the laser focus are also required and a system to deliver the target to a focus of an F2 beam at 0.1Hz is discussed.

  6. Manifold structure preservative for hyperspectral target detection

    NASA Astrophysics Data System (ADS)

    Imani, Maryam

    2018-05-01

    A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.

  7. Target Identification of Grape Seed Extract in Colorectal Cancer using Drug Affinity Responsive Target Stability (DARTS) Technique: Role of Endoplasmic Reticulum Stress Response Proteins

    PubMed Central

    Derry, Molly M.; Somasagara, Ranganatha; Raina, Komal; Kumar, Sushil; Gomez, Joe; Patel, Manisha; Agarwal, Rajesh; Agarwal, Chapla

    2014-01-01

    Various natural agents, including grape seed extract (GSE), have shown considerable chemopreventive and anti-cancer efficacy against different cancers in pre-clinical studies; however, their specific protein targets are largely unknown and thus, their clinical usefulness is marred by limited scientific evidences about their direct cellular targets. Accordingly, herein, employing, for the first time, the recently developed drug affinity responsive target stability (DARTS) technique, we aimed to profile the potential protein targets of GSE in human colorectal cancer (CRC) cells. Unlike other methods, which can cause chemical alteration of the drug components to allow for detection, this approach relies on the fact that a drug bound protein may become less susceptible to proteolysis and hence the enriched proteins can be detected by Mass Spectroscopy methods. Our results, utilizing the DARTS technique followed by examination of the spectral output by LC/MS and the MASCOT data, revealed that GSE targets endoplasmic reticulum (ER) stress response proteins resulting in overall down regulation of proteins involved in translation and that GSE also causes oxidative protein modifications, specifically on methionine amino acids residues on its protein targets. Corroborating these findings, mechanistic studies revealed that GSE indeed caused ER stress and strongly inhibited PI3k-Akt–mTOR pathway for its biological effects in CRC cells. Furthermore, bioenergetics studies indicated that GSE also interferes with glycolysis and mitochondrial metabolism in CRC cells. Together, the present study identifying GSE molecular targets in CRC cells, combined with its efficacy in vast pre-clinical CRC models, further supports its usefulness for CRC prevention and treatment. PMID:24724981

  8. Does working memory load facilitate target detection?

    PubMed

    Fruchtman-Steinbok, Tom; Kessler, Yoav

    2016-02-01

    Previous studies demonstrated that increasing working memory (WM) load delays performance of a concurrent task, by distracting attention and thus interfering with encoding and maintenance processes. The present study used a version of the change detection task with a target detection requirement during the retention interval. In contrast to the above prediction, target detection was faster following a larger set-size, specifically when presented shortly after the memory array (up to 400 ms). The effect of set-size on target detection was also evident when no memory retention was required. The set-size effect was also found using different modalities. Moreover, it was only observed when the memory array was presented simultaneously, but not sequentially. These results were explained by increased phasic alertness exerted by the larger visual display. The present study offers new evidence of ongoing attentional processes in the commonly-used change detection paradigm. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

    PubMed

    Zou, Zhengxia; Shi, Zhenwei

    2018-03-01

    We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

  10. Location detection and tracking of moving targets by a 2D IR-UWB radar system.

    PubMed

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-03-19

    In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.

  11. Dim target detection method based on salient graph fusion

    NASA Astrophysics Data System (ADS)

    Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

    2018-02-01

    Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

  12. Loop-mediated isothermal amplification (LAMP): a versatile technique for detection of micro-organisms.

    PubMed

    Wong, Y-P; Othman, S; Lau, Y-L; Radu, S; Chee, H-Y

    2018-03-01

    Loop-mediated isothermal amplification (LAMP) amplifies DNA with high specificity, efficiency and rapidity under isothermal conditions by using a DNA polymerase with high displacement strand activity and a set of specifically designed primers to amplify targeted DNA strands. Following its first discovery by Notomi et al. ( Nucleic Acids Res 28: E63), LAMP was further developed over the years which involved the combination of this technique with other molecular approaches, such as reverse transcription and multiplex amplification for the detection of infectious diseases caused by micro-organisms in humans, livestock and plants. In this review, available types of LAMP techniques will be discussed together with their applications in detection of various micro-organisms. Up to date, there are varieties of LAMP detection methods available including colorimetric and fluorescent detection, real-time monitoring using turbidity metre and detection using lateral flow device which will also be highlighted in this review. Apart from that, commercialization of LAMP technique had also been reported such as lyophilized form of LAMP reagents kit and LAMP primer sets for detection of pathogenic micro-organisms. On top of that, advantages and limitations of this molecular detection method are also described together with its future potential as a diagnostic method for infectious disease. © 2017 The Society for Applied Microbiology.

  13. Moving Target Techniques: Cyber Resilience throught Randomization, Diversity, and Dynamism

    DTIC Science & Technology

    2017-03-03

    Moving Target Techniques: Cyber Resilience through Randomization, Diversity, and Dynamism Hamed Okhravi and Howard Shrobe Overview: The static...nature of computer systems makes them vulnerable to cyber attacks. Consider a situation where an attacker wants to compromise a remote system running... cyber resilience that attempts to rebalance the cyber landscape is known as cyber moving target (MT) (or just moving target) techniques. Moving target

  14. A new imaging technique for detecting interstellar communications

    NASA Astrophysics Data System (ADS)

    Vallerga, John; Welsh, Barry; Kotze, Marissa; Siegmund, Oswald

    2017-01-01

    We report on a unique detection methodology using the Berkeley Visible Image Tube (BVIT) mounted on the 10m Southern African Large Telescope (SALT) to search for laser pulses originating in communications from advanced extraterrestrial (ET) civilizations residing on nearby Earth-like planets located within their habitability zones. The detection technique assumes that ET communicates through high powered pulsed lasers with pulse durations on the order of 5 nanoseconds, the signals thereby being brighter than that of the host star within this very short period of time. Our technique turns down the gain of the optically sensitive photon counting microchannel plate detector such that ~30 photons are required in a 5ns window to generate an imaged event. Picking a priori targets with planets in the habitable zone substantially reduces the false alarm rate. Interplanetary communication by optical masers was first postulated by Schwartz and Townes in 1961. Under the assumption that ET has access to a 10 m class telescope operated as a transmitter then we could detect lasers with a similar power to that of the Livermore Laboratory laser (~1.8Mj per pulse), to a distance of ~ 1000 pc. In this talk we present the results of 2400 seconds of BVIT observations on the SALT of the star Wolf 1061, which is known to harbor an Earth-sized exoplanet located in the habitability zone. At this distance (4.3 pc), BVIT on SALT could detect a 48 joule per pulse laser, now commercially available as tabletop devices.

  15. Spatial Probability Dynamically Modulates Visual Target Detection in Chickens

    PubMed Central

    Sridharan, Devarajan; Ramamurthy, Deepa L.; Knudsen, Eric I.

    2013-01-01

    The natural world contains a rich and ever-changing landscape of sensory information. To survive, an organism must be able to flexibly and rapidly locate the most relevant sources of information at any time. Humans and non-human primates exploit regularities in the spatial distribution of relevant stimuli (targets) to improve detection at locations of high target probability. Is the ability to flexibly modify behavior based on visual experience unique to primates? Chickens (Gallus domesticus) were trained on a multiple alternative Go/NoGo task to detect a small, briefly-flashed dot (target) in each of the quadrants of the visual field. When targets were presented with equal probability (25%) in each quadrant, chickens exhibited a distinct advantage for detecting targets at lower, relative to upper, hemifield locations. Increasing the probability of presentation in the upper hemifield locations (to 80%) dramatically improved detection performance at these locations to be on par with lower hemifield performance. Finally, detection performance in the upper hemifield changed on a rapid timescale, improving with successive target detections, and declining with successive detections at the diagonally opposite location in the lower hemifield. These data indicate the action of a process that in chickens, as in primates, flexibly and dynamically modulates detection performance based on the spatial probabilities of sensory stimuli as well as on recent performance history. PMID:23734188

  16. Heterogeneous CPU-GPU moving targets detection for UAV video

    NASA Astrophysics Data System (ADS)

    Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

    2017-07-01

    Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

  17. Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

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

    Sen, Satyabrata

    2013-01-01

    We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

  18. Hyperspectral target detection using manifold learning and multiple target spectra

    DOE PAGES

    Ziemann, Amanda K.; Theiler, James; Messinger, David W.

    2016-03-31

    Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less

  19. Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection.

    PubMed

    Soudy, R; Byeon, N; Raghuwanshi, Y; Ahmed, S; Lavasanifar, A; Kaur, K

    2017-01-01

    Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide- receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. Remote Leak Detection: Indirect Thermal Technique

    NASA Technical Reports Server (NTRS)

    Clements, Sandra

    2002-01-01

    Remote sensing technologies are being considered for efficient, low cost gas leak detection. Eleven specific techniques have been identified for further study and evaluation of several of these is underway. The Indirect Thermal Technique is one of the techniques that is being explored. For this technique, an infrared camera is used to detect the temperature change of a pipe or fitting at the site of a gas leak. This temperature change is caused by the change in temperature of the gas expanding from the leak site. During the 10-week NFFP program, the theory behind the technique was further developed, experiments were performed to determine the conditions for which the technique might be viable, and a proof-of-concept system was developed and tested in the laboratory.

  1. Target-specific NMR detection of protein-ligand interactions with antibody-relayed 15N-group selective STD.

    PubMed

    Hetényi, Anasztázia; Hegedűs, Zsófia; Fajka-Boja, Roberta; Monostori, Éva; Kövér, Katalin E; Martinek, Tamás A

    2016-12-01

    Fragment-based drug design has been successfully applied to challenging targets where the detection of the weak protein-ligand interactions is a key element. 1 H saturation transfer difference (STD) NMR spectroscopy is a powerful technique for this work but it requires pure homogeneous proteins as targets. Monoclonal antibody (mAb)-relayed 15 N-GS STD spectroscopy has been developed to resolve the problem of protein mixtures and impure proteins. A 15 N-labelled target-specific mAb is selectively irradiated and the saturation is relayed through the target to the ligand. Tests on the anti-Gal-1 mAb/Gal-1/lactose system showed that the approach is experimentally feasible in a reasonable time frame. This method allows detection and identification of binding molecules directly from a protein mixture in a multicomponent system.

  2. Subpixel target detection and enhancement in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Tiwari, K. C.; Arora, M.; Singh, D.

    2011-06-01

    Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

  3. Hyperspectral data collection for the assessment of target detection algorithms: the Viareggio 2013 trial

    NASA Astrophysics Data System (ADS)

    Rossi, Alessandro; Acito, Nicola; Diani, Marco; Corsini, Giovanni; De Ceglie, Sergio Ugo; Riccobono, Aldo; Chiarantini, Leandro

    2014-10-01

    Airborne hyperspectral imagery is valuable for military and civilian applications, such as target identification, detection of anomalies and changes within multiple acquisitions. In target detection (TD) applications, the performance assessment of different algorithms is an important and critical issue. In this context, the small number of public available hyperspectral data motivated us to perform an extensive measurement campaign including various operating scenarios. The campaign was organized by CISAM in cooperation with University of Pisa, Selex ES and CSSN-ITE, and it was conducted in Viareggio, Italy in May, 2013. The Selex ES airborne hyperspectral sensor SIM.GA was mounted on board of an airplane to collect images over different sites in the morning and afternoon of two subsequent days. This paper describes the hyperspectral data collection of the trial. Four different sites were set up, representing a complex urban scenario, two parking lots and a rural area. Targets with dimensions comparable to the sensor ground resolution were deployed in the sites to reproduce different operating situations. An extensive ground truth documentation completes the data collection. Experiments to test anomalous change detection techniques were set up changing the position of the deployed targets. Search and rescue scenarios were simulated to evaluate the performance of anomaly detection algorithms. Moreover, the reflectance signatures of the targets were measured on the ground to perform spectral matching in varying atmospheric and illumination conditions. The paper presents some preliminary results that show the effectiveness of hyperspectral data exploitation for the object detection tasks of interest in this work.

  4. Texture orientation-based algorithm for detecting infrared maritime targets.

    PubMed

    Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

    2015-05-20

    Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

  5. Automatic target detection using binary template matching

    NASA Astrophysics Data System (ADS)

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

    2005-03-01

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

  6. Initial study of Schroedinger eigenmaps for spectral target detection

    NASA Astrophysics Data System (ADS)

    Dorado-Munoz, Leidy P.; Messinger, David W.

    2016-08-01

    Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.

  7. Imaging of targeted lipid microbubbles to detect cancer cells using third harmonic generation microscopy

    PubMed Central

    Harpel, Kaitlin; Baker, Robert Dawson; Amirsolaimani, Babak; Mehravar, Soroush; Vagner, Josef; Matsunaga, Terry O.; Banerjee, Bhaskar; Kieu, Khanh

    2016-01-01

    The use of receptor-targeted lipid microbubbles imaged by ultrasound is an innovative method of detecting and localizing disease. However, since ultrasound requires a medium between the transducer and the object being imaged, it is impractical to apply to an exposed surface in a surgical setting where sterile fields need be maintained and ultrasound gel may cause the bubbles to collapse. Multiphoton microscopy (MPM) is an emerging tool for accurate, label-free imaging of tissues and cells with high resolution and contrast. We have recently determined a novel application of MPM to be used for detecting targeted microbubble adherence to the upregulated plectin-receptor on pancreatic tumor cells. Specifically, the third-harmonic generation response can be used to detect bound microbubbles to various cell types presenting MPM as an alternative and useful imaging method. This is an interesting technique that can potentially be translated as a diagnostic tool for the early detection of cancer and inflammatory disorders. PMID:27446711

  8. A new method of small target detection based on neural network

    NASA Astrophysics Data System (ADS)

    Hu, Jing; Hu, Yongli; Lu, Xinxin

    2018-02-01

    The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.

  9. The simulation study on optical target laser active detection performance

    NASA Astrophysics Data System (ADS)

    Li, Ying-chun; Hou, Zhao-fei; Fan, Youchen

    2014-12-01

    According to the working principle of laser active detection system, the paper establishes the optical target laser active detection simulation system, carry out the simulation study on the detection process and detection performance of the system. For instance, the performance model such as the laser emitting, the laser propagation in the atmosphere, the reflection of optical target, the receiver detection system, the signal processing and recognition. We focus on the analysis and modeling the relationship between the laser emitting angle and defocus amount and "cat eye" effect echo laser in the reflection of optical target. Further, in the paper some performance index such as operating range, SNR and the probability of the system have been simulated. The parameters including laser emitting parameters, the reflection of the optical target and the laser propagation in the atmosphere which make a great influence on the performance of the optical target laser active detection system. Finally, using the object-oriented software design methods, the laser active detection system with the opening type, complete function and operating platform, realizes the process simulation that the detection system detect and recognize the optical target, complete the performance simulation of each subsystem, and generate the data report and the graph. It can make the laser active detection system performance models more intuitive because of the visible simulation process. The simulation data obtained from the system provide a reference to adjust the structure of the system parameters. And it provides theoretical and technical support for the top level design of the optical target laser active detection system and performance index optimization.

  10. Infrared small target detection based on Danger Theory

    NASA Astrophysics Data System (ADS)

    Lan, Jinhui; Yang, Xiao

    2009-11-01

    To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

  11. Infrared small target detection technology based on OpenCV

    NASA Astrophysics Data System (ADS)

    Liu, Lei; Huang, Zhijian

    2013-05-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  12. Infrared small target detection technology based on OpenCV

    NASA Astrophysics Data System (ADS)

    Liu, Lei; Huang, Zhijian

    2013-09-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  13. Infrared small target detection with kernel Fukunaga Koontz transform

    NASA Astrophysics Data System (ADS)

    Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin

    2007-09-01

    The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.

  14. Small maritime target detection through false color fusion

    NASA Astrophysics Data System (ADS)

    Toet, Alexander; Wu, Tirui

    2008-04-01

    We present an algorithm that produces a fused false color representation of a combined multiband IR and visual imaging system for maritime applications. Multispectral IR imaging techniques are increasingly deployed in maritime operations, to detect floating mines or to find small dinghies and swimmers during search and rescue operations. However, maritime backgrounds usually contain a large amount of clutter that severely hampers the detection of small targets. Our new algorithm deploys the correlation between the target signatures in two different IR frequency bands (3-5 and 8-12 μm) to construct a fused IR image with a reduced amount of clutter. The fused IR image is then combined with a visual image in a false color RGB representation for display to a human operator. The algorithm works as follows. First, both individual IR bands are filtered with a morphological opening top-hat transform to extract small details. Second, a common image is extracted from the two filtered IR bands, and assigned to the red channel of an RGB image. Regions of interest that appear in both IR bands remain in this common image, while most uncorrelated noise details are filtered out. Third, the visual band is assigned to the green channel and, after multiplication with a constant (typically 1.6) also to the blue channel. Fourth, the brightness and colors of this intermediate false color image are renormalized by adjusting its first order statistics to those of a representative reference scene. The result of these four steps is a fused color image, with naturalistic colors (bluish sky and grayish water), in which small targets are clearly visible.

  15. [Comparison between rapid detection method of enzyme substrate technique and multiple-tube fermentation technique in water coliform bacteria detection].

    PubMed

    Sun, Zong-ke; Wu, Rong; Ding, Pei; Xue, Jin-Rong

    2006-07-01

    To compare between rapid detection method of enzyme substrate technique and multiple-tube fermentation technique in water coliform bacteria detection. Using inoculated and real water samples to compare the equivalence and false positive rate between two methods. Results demonstrate that enzyme substrate technique shows equivalence with multiple-tube fermentation technique (P = 0.059), false positive rate between the two methods has no statistical difference. It is suggested that enzyme substrate technique can be used as a standard method for water microbiological safety evaluation.

  16. Modeling peripheral vision for moving target search and detection.

    PubMed

    Yang, Ji Hyun; Huston, Jesse; Day, Michael; Balogh, Imre

    2012-06-01

    Most target search and detection models focus on foveal vision. In reality, peripheral vision plays a significant role, especially in detecting moving objects. There were 23 subjects who participated in experiments simulating target detection tasks in urban and rural environments while their gaze parameters were tracked. Button responses associated with foveal object and peripheral object (PO) detection and recognition were recorded. In an urban scenario, pedestrians appearing in the periphery holding guns were threats and pedestrians with empty hands were non-threats. In a rural scenario, non-U.S. unmanned aerial vehicles (UAVs) were considered threats and U.S. UAVs non-threats. On average, subjects missed detecting 2.48 POs among 50 POs in the urban scenario and 5.39 POs in the rural scenario. Both saccade reaction time and button reaction time can be predicted by peripheral angle and entrance speed of POs. Fast moving objects were detected faster than slower objects and POs appearing at wider angles took longer to detect than those closer to the gaze center. A second-order mixed-effect model was applied to provide each subject's prediction model for peripheral target detection performance as a function of eccentricity angle and speed. About half the subjects used active search patterns while the other half used passive search patterns. An interactive 3-D visualization tool was developed to provide a representation of macro-scale head and gaze movement in the search and target detection task. An experimentally validated stochastic model of peripheral vision in realistic target detection scenarios was developed.

  17. Detection of Hepatitis A Virus by the Nucleic Acid Sequence-Based Amplification Technique and Comparison with Reverse Transcription-PCR

    PubMed Central

    Jean, Julie; Blais, Burton; Darveau, André; Fliss, Ismaïl

    2001-01-01

    A nucleic acid sequence-based amplification (NASBA) technique for the detection of hepatitis A virus (HAV) in foods was developed and compared to the traditional reverse transcription (RT)-PCR technique. Oligonucleotide primers targeting the VP1 and VP2 genes encoding the major HAV capsid proteins were used for the amplification of viral RNA in an isothermal process resulting in the accumulation of RNA amplicons. Amplicons were detected by hybridization with a digoxigenin-labeled oligonucleotide probe in a dot blot assay format. Using the NASBA, as little as 0.4 ng of target RNA/ml was detected per comparison to 4 ng/ml for RT-PCR. When crude HAV viral lysate was used, a detection limit of 2 PFU (4 × 102 PFU/ml) was obtained with NASBA, compared to 50 PFU (1 × 104 PFU/ml) obtained with RT-PCR. No interference was encountered in the amplification of HAV RNA in the presence of excess nontarget RNA or DNA. The NASBA system successfully detected HAV recovered from experimentally inoculated samples of waste water, lettuce, and blueberries. Compared to RT-PCR and other amplification techniques, the NASBA system offers several advantages in terms of sensitivity, rapidity, and simplicity. This technique should be readily adaptable for detection of other RNA viruses in both foods and clinical samples. PMID:11722911

  18. Detection of hepatitis A virus by the nucleic acid sequence-based amplification technique and comparison with reverse transcription-PCR.

    PubMed

    Jean, J; Blais, B; Darveau, A; Fliss, I

    2001-12-01

    A nucleic acid sequence-based amplification (NASBA) technique for the detection of hepatitis A virus (HAV) in foods was developed and compared to the traditional reverse transcription (RT)-PCR technique. Oligonucleotide primers targeting the VP1 and VP2 genes encoding the major HAV capsid proteins were used for the amplification of viral RNA in an isothermal process resulting in the accumulation of RNA amplicons. Amplicons were detected by hybridization with a digoxigenin-labeled oligonucleotide probe in a dot blot assay format. Using the NASBA, as little as 0.4 ng of target RNA/ml was detected per comparison to 4 ng/ml for RT-PCR. When crude HAV viral lysate was used, a detection limit of 2 PFU (4 x 10(2) PFU/ml) was obtained with NASBA, compared to 50 PFU (1 x 10(4) PFU/ml) obtained with RT-PCR. No interference was encountered in the amplification of HAV RNA in the presence of excess nontarget RNA or DNA. The NASBA system successfully detected HAV recovered from experimentally inoculated samples of waste water, lettuce, and blueberries. Compared to RT-PCR and other amplification techniques, the NASBA system offers several advantages in terms of sensitivity, rapidity, and simplicity. This technique should be readily adaptable for detection of other RNA viruses in both foods and clinical samples.

  19. Performing target specific band reduction using artificial neural networks and assessment of its efficacy using various target detection algorithms

    NASA Astrophysics Data System (ADS)

    Yadav, Deepti; Arora, M. K.; Tiwari, K. C.; Ghosh, J. K.

    2016-04-01

    Hyperspectral imaging is a powerful tool in the field of remote sensing and has been used for many applications like mineral detection, detection of landmines, target detection etc. Major issues in target detection using HSI are spectral variability, noise, small size of the target, huge data dimensions, high computation cost, complex backgrounds etc. Many of the popular detection algorithms do not work for difficult targets like small, camouflaged etc. and may result in high false alarms. Thus, target/background discrimination is a key issue and therefore analyzing target's behaviour in realistic environments is crucial for the accurate interpretation of hyperspectral imagery. Use of standard libraries for studying target's spectral behaviour has limitation that targets are measured in different environmental conditions than application. This study uses the spectral data of the same target which is used during collection of the HSI image. This paper analyze spectrums of targets in a way that each target can be spectrally distinguished from a mixture of spectral data. Artificial neural network (ANN) has been used to identify the spectral range for reducing data and further its efficacy for improving target detection is verified. The results of ANN proposes discriminating band range for targets; these ranges were further used to perform target detection using four popular spectral matching target detection algorithm. Further, the results of algorithms were analyzed using ROC curves to evaluate the effectiveness of the ranges suggested by ANN over full spectrum for detection of desired targets. In addition, comparative assessment of algorithms is also performed using ROC.

  20. Edge detection techniques for iris recognition system

    NASA Astrophysics Data System (ADS)

    Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

    2013-12-01

    Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

  1. A lightweight network anomaly detection technique

    DOE PAGES

    Kim, Jinoh; Yoo, Wucherl; Sim, Alex; ...

    2017-03-13

    While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less

  2. A lightweight network anomaly detection technique

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

    Kim, Jinoh; Yoo, Wucherl; Sim, Alex

    While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less

  3. Current trends in explosive detection techniques.

    PubMed

    Caygill, J Sarah; Davis, Frank; Higson, Seamus P J

    2012-01-15

    The detection of explosives and explosive-related compounds has become a heightened priority in recent years for homeland security and counter-terrorism applications. There has been a huge increase in research within this area-through both the development of new, innovative detection approaches and the improvement of existing techniques. Developments for miniaturisation, portability, field-ruggedisation and improvements in stand-off distances, selectivity and sensitivity have been necessary to develop and improve techniques. This review provides a consolidation of information relating to recent advances in explosive detection techniques without being limited to one specific research area or explosive type. The focus of this review will be towards advances in the last 5 years, with the reader being referred to earlier reviews where appropriate. Copyright © 2011. Published by Elsevier B.V.

  4. Comparison of human and algorithmic target detection in passive infrared imagery

    NASA Astrophysics Data System (ADS)

    Weber, Bruce A.; Hutchinson, Meredith

    2003-09-01

    We have designed an experiment that compares the performance of human observers and a scale-insensitive target detection algorithm that uses pixel level information for the detection of ground targets in passive infrared imagery. The test database contains targets near clutter whose detectability ranged from easy to very difficult. Results indicate that human observers detect more "easy-to-detect" targets, and with far fewer false alarms, than the algorithm. For "difficult-to-detect" targets, human and algorithm detection rates are considerably degraded, and algorithm false alarms excessive. Analysis of detections as a function of observer confidence shows that algorithm confidence attribution does not correspond to human attribution, and does not adequately correlate with correct detections. The best target detection score for any human observer was 84%, as compared to 55% for the algorithm for the same false alarm rate. At 81%, the maximum detection score for the algorithm, the same human observer had 6 false alarms per frame as compared to 29 for the algorithm. Detector ROC curves and observer-confidence analysis benchmarks the algorithm and provides insights into algorithm deficiencies and possible paths to improvement.

  5. Infrared dim and small target detecting and tracking method inspired by Human Visual System

    NASA Astrophysics Data System (ADS)

    Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Shen, Lurong; Bai, Shengjian

    2014-01-01

    Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.

  6. Kepler Planet Detection Metrics: Per-Target Detection Contours for Data Release 25

    NASA Technical Reports Server (NTRS)

    Burke, Christopher J.; Catanzarite, Joseph

    2017-01-01

    A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).

  7. Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

    PubMed

    Gao, Jingli; Wen, Chenglin; Liu, Meiqin

    2017-09-29

    In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

  8. Dual signal amplification for highly sensitive electrochemical detection of uropathogens via enzyme-based catalytic target recycling.

    PubMed

    Su, Jiao; Zhang, Haijie; Jiang, Bingying; Zheng, Huzhi; Chai, Yaqin; Yuan, Ruo; Xiang, Yun

    2011-11-15

    We report an ultrasensitive electrochemical approach for the detection of uropathogen sequence-specific DNA target. The sensing strategy involves a dual signal amplification process, which combines the signal enhancement by the enzymatic target recycling technique with the sensitivity improvement by the quantum dot (QD) layer-by-layer (LBL) assembled labels. The enzyme-based catalytic target DNA recycling process results in the use of each target DNA sequence for multiple times and leads to direct amplification of the analytical signal. Moreover, the LBL assembled QD labels can further enhance the sensitivity of the sensing system. The coupling of these two effective signal amplification strategies thus leads to low femtomolar (5fM) detection of the target DNA sequences. The proposed strategy also shows excellent discrimination between the target DNA and the single-base mismatch sequences. The advantageous intrinsic sequence-independent property of exonuclease III over other sequence-dependent enzymes makes our new dual signal amplification system a general sensing platform for monitoring ultralow level of various types of target DNA sequences. Copyright © 2011 Elsevier B.V. All rights reserved.

  9. An Experiment Quantifying The Effect Of Clutter On Target Detection

    NASA Astrophysics Data System (ADS)

    Weathersby, Marshall R.; Schmieder, David E.

    1985-01-01

    Experiments were conducted to determine the influence of background clutter on target detection criteria. The experiment consisted of placing observers in front of displayed images on a TV monitor. Observer ability to detect military targets embedded in simulated natural and manmade background clutter was measured when there was unlimited viewing time. Results were described in terms of detection probability versus target resolution for various signal to clutter ratios (SCR). The experiments were preceded by a search for a meaningful clutter definition. The selected definition was a statistical measure computed by averaging the standard deviation of contiguous scene cells over the whole scene. The cell size was comparable to the target size. Observer test results confirmed the expectation that the resolution required for a given detection probability was a continuum function of the clutter level. At the lower SCRs the resolution required for a high probability of detection was near 6 lines pairs per target (LP/TGT), while at the higher SCRs it was found that a resolution of less than 0.25 LP/TGT would yield a high probability of detection. These results are expected to aid in target acquisition performance modeling and to lead to improved specifications for imaging automatic target screeners.

  10. Small target detection using objectness and saliency

    NASA Astrophysics Data System (ADS)

    Zhang, Naiwen; Xiao, Yang; Fang, Zhiwen; Yang, Jian; Wang, Li; Li, Tao

    2017-10-01

    We are motived by the need for generic object detection algorithm which achieves high recall for small targets in complex scenes with acceptable computational efficiency. We propose a novel object detection algorithm, which has high localization quality with acceptable computational cost. Firstly, we obtain the objectness map as in BING[1] and use NMS to get the top N points. Then, k-means algorithm is used to cluster them into K classes according to their location. We set the center points of the K classes as seed points. For each seed point, an object potential region is extracted. Finally, a fast salient object detection algorithm[2] is applied to the object potential regions to highlight objectlike pixels, and a series of efficient post-processing operations are proposed to locate the targets. Our method runs at 5 FPS on 1000*1000 images, and significantly outperforms previous methods on small targets in cluttered background.

  11. Camouflage, detection and identification of moving targets

    PubMed Central

    Hall, Joanna R.; Cuthill, Innes C.; Baddeley, Roland; Shohet, Adam J.; Scott-Samuel, Nicholas E.

    2013-01-01

    Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely ‘break’ camouflage. PMID:23486439

  12. Camouflage, detection and identification of moving targets.

    PubMed

    Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

    2013-05-07

    Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

  13. Investigating the probability of detection of typical cavity shapes through modelling and comparison of geophysical techniques

    NASA Astrophysics Data System (ADS)

    James, P.

    2011-12-01

    With a growing need for housing in the U.K., the government has proposed increased development of brownfield sites. However, old mine workings and natural cavities represent a potential hazard before, during and after construction on such sites, and add further complication to subsurface parameters. Cavities are hence a limitation to certain redevelopment and their detection is an ever important consideration. The current standard technique for cavity detection is a borehole grid, which is intrusive, non-continuous, slow and expensive. A new robust investigation standard in the detection of cavities is sought and geophysical techniques offer an attractive alternative. Geophysical techniques have previously been utilised successfully in the detection of cavities in various geologies, but still has an uncertain reputation in the engineering industry. Engineers are unsure of the techniques and are inclined to rely on well known techniques than utilise new technologies. Bad experiences with geophysics are commonly due to the indiscriminate choice of particular techniques. It is imperative that a geophysical survey is designed with the specific site and target in mind at all times, and the ability and judgement to rule out some, or all, techniques. To this author's knowledge no comparative software exists to aid technique choice. Also, previous modelling software limit the shapes of bodies and hence typical cavity shapes are not represented. Here, we introduce 3D modelling software (Matlab) which computes and compares the response to various cavity targets from a range of techniques (gravity, gravity gradient, magnetic, magnetic gradient and GPR). Typical near surface cavity shapes are modelled including shafts, bellpits, various lining and capping materials, and migrating voids. The probability of cavity detection is assessed in typical subsurface and noise conditions across a range of survey parameters. Techniques can be compared and the limits of detection distance

  14. Whole body MRI: Improved Lesion Detection and Characterization With Diffusion Weighted Techniques

    PubMed Central

    Attariwala, Rajpaul; Picker, Wayne

    2013-01-01

    Diffusion-weighted imaging (DWI) is an established functional imaging technique that interrogates the delicate balance of water movement at the cellular level. Technological advances enable this technique to be applied to whole-body MRI. Theory, b-value selection, common artifacts and target to background for optimized viewing will be reviewed for applications in the neck, chest, abdomen, and pelvis. Whole-body imaging with DWI allows novel applications of MRI to aid in evaluation of conditions such as multiple myeloma, lymphoma, and skeletal metastases, while the quantitative nature of this technique permits evaluation of response to therapy. Persisting signal at high b-values from restricted hypercellular tissue and viscous fluid also permits applications of DWI beyond oncologic imaging. DWI, when used in conjunction with routine imaging, can assist in detecting hemorrhagic degradation products, infection/abscess, and inflammation in colitis, while aiding with discrimination of free fluid and empyema, while limiting the need for intravenous contrast. DWI in conjunction with routine anatomic images provides a platform to improve lesion detection and characterization with findings rivaling other combined anatomic and functional imaging techniques, with the added benefit of no ionizing radiation. PMID:23960006

  15. Target attribute-based false alarm rejection in small infrared target detection

    NASA Astrophysics Data System (ADS)

    Kim, Sungho

    2012-11-01

    Infrared search and track is an important research area in military applications. Although there are a lot of works on small infrared target detection methods, we cannot apply them in real field due to high false alarm rate caused by clutters. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. Eight kinds of target features are extracted and analyzed statistically. Learning-based classifiers such as SVM and Adaboost are developed and compared with conventional classifiers for real infrared images. In addition, the generalization capability is also inspected for various infrared clutters.

  16. Top-attack modeling and automatic target detection using synthetic FLIR scenery

    NASA Astrophysics Data System (ADS)

    Weber, Bruce A.; Penn, Joseph A.

    2004-09-01

    A series of experiments have been performed to verify the utility of algorithmic tools for the modeling and analysis of cold-target signatures in synthetic, top-attack, FLIR video sequences. The tools include: MuSES/CREATION for the creation of synthetic imagery with targets, an ARL target detection algorithm to detect imbedded synthetic targets in scenes, and an ARL scoring algorithm, using Receiver-Operating-Characteristic (ROC) curve analysis, to evaluate detector performance. Cold-target detection variability was examined as a function of target emissivity, surrounding clutter type, and target placement in non-obscuring clutter locations. Detector metrics were also individually scored so as to characterize the effect of signature/clutter variations. Results show that using these tools, a detailed, physically meaningful, target detection analysis is possible and that scenario specific target detectors may be developed by selective choice and/or weighting of detector metrics. However, developing these tools into a reliable predictive capability will require the extension of these results to the modeling and analysis of a large number of data sets configured for a wide range of target and clutter conditions. Finally, these tools should also be useful for the comparison of competitive detection algorithms by providing well defined, and controllable target detection scenarios, as well as for the training and testing of expert human observers.

  17. Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

    PubMed Central

    Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

    2018-01-01

    Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

  18. Assessment of target detection limits in hyperspectral data

    NASA Astrophysics Data System (ADS)

    Gross, W.; Boehler, J.; Schilling, H.; Middelmann, W.; Weyermann, J.; Wellig, P.; Oechslin, R.; Kneubuehler, M.

    2015-10-01

    Hyperspectral remote sensing data can be used for civil and military applications to detect and classify target objects that cannot be reliably separated using broadband sensors. The comparably low spatial resolution is compensated by the fact that small targets, even below image resolution, can still be classified. The goal of this paper is to determine the target size to spatial resolution ratio for successful classification of different target and background materials. Airborne hyperspectral data is used to simulate data with known mixture ratios and to estimate the detection threshold for given false alarm rates. The data was collected in July 2014 over Greding, Germany, using airborne aisaEAGLE and aisaHAWK hyperspectral sensors. On the ground, various target materials were placed on natural background. The targets were four quadratic molton patches with an edge length of 7 meters in the colors black, white, grey and green. Also, two different types of polyethylene (camouflage nets) with an edge length of approximately 5.5 meters were deployed. Synthetic data is generated from the original data using spectral mixtures. Target signatures are linearly combined with different background materials in specific ratios. The simulated mixtures are appended to the original data and the target areas are removed for evaluation. Commonly used classification algorithms, e.g. Matched Filtering, Adaptive Cosine Estimator are used to determine the detection limit. Fixed false alarm rates are employed to find and analyze certain regions where false alarms usually occur first. A combination of 18 targets and 12 backgrounds is analyzed for three VNIR and two SWIR data sets of the same area.

  19. Target detection cycle criteria when using the targeting task performance metric

    NASA Astrophysics Data System (ADS)

    Hixson, Jonathan G.; Jacobs, Eddie L.; Vollmerhausen, Richard H.

    2004-12-01

    The US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate of the US Army (NVESD) has developed a new target acquisition metric to better predict the performance of modern electro-optical imagers. The TTP metric replaces the Johnson criteria. One problem with transitioning to the new model is that the difficulty of searching in a terrain has traditionally been quantified by an "N50." The N50 is the number of Johnson criteria cycles needed for the observer to detect the target half the time, assuming that the observer is not time limited. In order to make use of this empirical data base, a conversion must be found relating Johnson cycles for detection to TTP cycles for detection. This paper describes how that relationship is established. We have found that the relationship between Johnson and TTP is 1:2.7 for the recognition and identification tasks.

  20. Biosensing Using Magnetic Particle Detection Techniques

    PubMed Central

    Chen, Yi-Ting; Kolhatkar, Arati G.; Zenasni, Oussama; Xu, Shoujun

    2017-01-01

    Magnetic particles are widely used as signal labels in a variety of biological sensing applications, such as molecular detection and related strategies that rely on ligand-receptor binding. In this review, we explore the fundamental concepts involved in designing magnetic particles for biosensing applications and the techniques used to detect them. First, we briefly describe the magnetic properties that are important for bio-sensing applications and highlight the associated key parameters (such as the starting materials, size, functionalization methods, and bio-conjugation strategies). Subsequently, we focus on magnetic sensing applications that utilize several types of magnetic detection techniques: spintronic sensors, nuclear magnetic resonance (NMR) sensors, superconducting quantum interference devices (SQUIDs), sensors based on the atomic magnetometer (AM), and others. From the studies reported, we note that the size of the MPs is one of the most important factors in choosing a sensing technique. PMID:28994727

  1. Ambient air contamination: Characterization and detection techniques

    NASA Technical Reports Server (NTRS)

    Nulton, C. P.; Silvus, H. S.

    1985-01-01

    Techniques to characterize and detect sources of ambient air contamination are described. Chemical techniques to identify indoor contaminants are outlined, they include gas chromatography, or colorimetric detection. Organics generated from indoor materials at ambient conditions and upon combustion are characterized. Piezoelectric quartz crystals are used as precision frequency determining elements in electronic oscillators.

  2. SERS detection and targeted ablation of lymphoma cells using functionalized Ag nanoparticles

    NASA Astrophysics Data System (ADS)

    Yao, Qian; Cao, Fei; Feng, Chao; Zhao, Yan; Wang, Xiuhong

    2016-03-01

    Lymphoma is a heterogeneous group of malignancies of the lymphoid tissue, and is prevalent worldwide affecting both children and adults with a high mortality rate. There is in dire need of accurate and noninvasive approaches for early detection of the disease. Herein, we report a facile way to fabricate silver nanoparticle based nanoprobe by incorporating the corner-stone immunotherapeutic drug Rituxan for simultaneous detection and ablation of lymphoma cells in vitro. The fabricated nanoprobe can detect CD20 positive single lymphoma cell by surface enhanced Raman scattering technique with high specificity. The engineered nanoprobe retains the same antibody property as intact drug via Antibody-Dependent Cell-mediated Cytotoxicity (ADCC) analysis. The nanoprobe efficiently eradicates lymphoma cells in vitro. By integrating the advantages of sensitive SERS detection with targeted ablation capabilities of immunotherapeutic drug through site specificity, this nanoprobe can be applied as outstanding tools in living imaging, cancer diagnosis and treatment.

  3. Wavelength band selection method for multispectral target detection.

    PubMed

    Karlholm, Jörgen; Renhorn, Ingmar

    2002-11-10

    A framework is proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data. Using the results from the detection theory we derive a cost function that is minimized by a set of spectral bands optimal in terms of detection performance for discrimination between a class of small rare targets and clutter with known spectral distribution. The method may be used, e.g., in the design of multispectral infrared search and track and electro-optical missile warning sensors, where a low false-alarm rate and a high-detection probability for detection of small targets against a clutter background are of critical importance, but the required high frame rate prevents the use of hyperspectral sensors.

  4. Detection and Tracking of Moving Targets Behind Cluttered Environments Using Compressive Sensing

    NASA Astrophysics Data System (ADS)

    Dang, Vinh Quang

    Detection and tracking of moving targets (target's motion, vibration, etc.) in cluttered environments have been receiving much attention in numerous applications, such as disaster search-and-rescue, law enforcement, urban warfare, etc. One of the popular techniques is the use of stepped frequency continuous wave radar due to its low cost and complexity. However, the stepped frequency radar suffers from long data acquisition time. This dissertation focuses on detection and tracking of moving targets and vibration rates of stationary targets behind cluttered medium such as wall using stepped frequency radar enhanced by compressive sensing. The application of compressive sensing enables the reconstruction of the target space using fewer random frequencies, which decreases the acquisition time. Hardware-accelerated parallelization on GPU is investigated for the Orthogonal Matching Pursuit reconstruction algorithm. For simulation purpose, two hybrid methods have been developed to calculate the scattered fields from the targets through the wall approaching the antenna system, and to convert the incoming fields into voltage signals at terminals of the receive antenna. The first method is developed based on the plane wave spectrum approach for calculating the scattered fields of targets behind the wall. The method uses Fast Multiple Method (FMM) to calculate scattered fields on a particular source plane, decomposes them into plane wave components, and propagates the plane wave spectrum through the wall by integrating wall transmission coefficients before constructing the fields on a desired observation plane. The second method allows one to calculate the complex output voltage at terminals of a receiving antenna which fully takes into account the antenna effects. This method adopts the concept of complex antenna factor in Electromagnetic Compatibility (EMC) community for its calculation.

  5. Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

    NASA Astrophysics Data System (ADS)

    Bal, A.; Alam, M. S.; Aslan, M. S.

    2006-05-01

    Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

  6. Targeted detection of murine colonic dysplasia in vivo with flexible multispectral scanning fiber endoscopy

    NASA Astrophysics Data System (ADS)

    Joshi, Bishnu P.; Miller, Sharon J.; Lee, Cameron; Gustad, Adam; Seibel, Eric J.; Wang, Thomas D.

    2012-02-01

    We demonstrate a multi-spectral scanning fiber endoscope (SFE) that collects fluorescence images in vivo from three target peptides that bind specifically to murine colonic adenomas. This ultrathin endoscope was demonstrated in a genetically engineered mouse model of spontaneous colorectal adenomas based on somatic Apc (adenomatous polyposis coli) gene inactivation. The SFE delivers excitation at 440, 532, 635 nm with <2 mW per channel. The target 7-mer peptides were conjugated to visible organic dyes, including 7-Diethylaminocoumarin-3-carboxylic acid (DEAC) (λex=432 nm, λem=472 nm), 5-Carboxytetramethylrhodamine (5-TAMRA) (λex=535 nm, λem=568 nm), and CF-633 (λex=633 nm, λem=650 nm). Target peptides were first validated using techniques of pfu counting, flow cytometry and previously established methods of fluorescence endoscopy. Peptides were applied individually or in combination and detected with fluorescence imaging. The ability to image multiple channels of fluorescence concurrently was successful for all three channels in vitro, while two channels were resolved simultaneously in vivo. Selective binding of the peptide was evident to adenomas and not to adjacent normal-appearing mucosa. Multispectral wide-field fluorescence detection using the SFE is achievable, and this technology has potential to advance early cancer detection and image-guided therapy in human patients by simultaneously visualizing multiple over expressed molecular targets unique to dysplasia.

  7. Single molecule targeted sequencing for cancer gene mutation detection.

    PubMed

    Gao, Yan; Deng, Liwei; Yan, Qin; Gao, Yongqian; Wu, Zengding; Cai, Jinsen; Ji, Daorui; Li, Gailing; Wu, Ping; Jin, Huan; Zhao, Luyang; Liu, Song; Ge, Liangjin; Deem, Michael W; He, Jiankui

    2016-05-19

    With the rapid decline in cost of sequencing, it is now affordable to examine multiple genes in a single disease-targeted clinical test using next generation sequencing. Current targeted sequencing methods require a separate step of targeted capture enrichment during sample preparation before sequencing. Although there are fast sample preparation methods available in market, the library preparation process is still relatively complicated for physicians to use routinely. Here, we introduced an amplification-free Single Molecule Targeted Sequencing (SMTS) technology, which combined targeted capture and sequencing in one step. We demonstrated that this technology can detect low-frequency mutations using artificially synthesized DNA sample. SMTS has several potential advantages, including simple sample preparation thus no biases and errors are introduced by PCR reaction. SMTS has the potential to be an easy and quick sequencing technology for clinical diagnosis such as cancer gene mutation detection, infectious disease detection, inherited condition screening and noninvasive prenatal diagnosis.

  8. Historical Techniques of Lie Detection

    PubMed Central

    Vicianova, Martina

    2015-01-01

    Since time immemorial, lying has been a part of everyday life. For this reason, it has become a subject of interest in several disciplines, including psychology. The purpose of this article is to provide a general overview of the literature and thinking to date about the evolution of lie detection techniques. The first part explores ancient methods recorded circa 1000 B.C. (e.g., God’s judgment in Europe). The second part describes technical methods based on sciences such as phrenology, polygraph and graphology. This is followed by an outline of more modern-day approaches such as FACS (Facial Action Coding System), functional MRI, and Brain Fingerprinting. Finally, after the familiarization with the historical development of techniques for lie detection, we discuss the scope for new initiatives not only in the area of designing new methods, but also for the research into lie detection itself, such as its motives and regulatory issues related to deception. PMID:27247675

  9. Infrared small target detection based on directional zero-crossing measure

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangyue; Ding, Qinghai; Luo, Haibo; Hui, Bin; Chang, Zheng; Zhang, Junchao

    2017-12-01

    Infrared small target detection under complex background and low signal-to-clutter ratio (SCR) condition is of great significance to the development on precision guidance and infrared surveillance. In order to detect targets precisely and extract targets from intricate clutters effectively, a detection method based on zero-crossing saliency (ZCS) map is proposed. The original map is first decomposed into different first-order directional derivative (FODD) maps by using FODD filters. Then the ZCS map is obtained by fusing all directional zero-crossing points. At last, an adaptive threshold is adopted to segment targets from the ZCS map. Experimental results on a series of images show that our method is effective and robust for detection under complex backgrounds. Moreover, compared with other five state-of-the-art methods, our method achieves better performance in terms of detection rate, SCR gain and background suppression factor.

  10. Ultra-Wideband EMI Sensing: Non-Metallic Target Detection and Automatic Classification of Unexploded Ordnance

    NASA Astrophysics Data System (ADS)

    Sigman, John Brevard

    Buried explosive hazards present a pressing problem worldwide. Millions of acres and thousands of sites are contaminated in the United States alone [1, 2]. There are three categories of explosive hazards: metallic, intermediate-electrical conducting (IEC), and non-conducting targets. Metallic target detection and classification by electromagnetic (EM) signature has been the subject of research for many years. Key to the success of this research is modern multi-static Electromagnetic Induction (EMI) sensors, which are able to measure the wideband EMI response from metallic buried targets. However, no hardware solutions exist which can characterize IEC and non-conducting targets. While high-conducting metallic targets exhibit a quadrature peak response for frequencies in a traditional EMI regime under 100 kHz, the response of intermediate-conducting objects manifests at higher frequencies, between 100 kHz and 15 MHz. In addition to high-quality electromagnetic sensor data and robust electromagnetic models, a classification procedure is required to discriminate Targets of Interest (TOI) from clutter. Currently, costly human experts are used for this task. This expense and effort can be spared by using statistical signal processing and machine learning. This thesis has two main parts. In the first part, we explore using the high frequency EMI (HFEMI) band (100 kHz-15 MHz) for detection of carbon fiber UXO, voids, and of materials with characteristics that may be associated with improvised explosive devices (IED). We constructed an HFEMI sensing instrument, and apply the techniques of metal detection to sensing in a band of frequencies which are the transition between the induction and radar bands. In this transition domain, physical considerations and technological issues arise that cannot be solved via the approaches used in either of the bracketing lower and higher frequency ranges. In the second half of this thesis, we present a procedure for automatic

  11. Study of time-reversal-based signal processing applied to polarimetric GPR detection of elongated targets

    NASA Astrophysics Data System (ADS)

    Santos, Vinicius Rafael N.; Teixeira, Fernando L.

    2017-04-01

    Ground penetrating radar (GPR) is a useful sensing modality for mapping and identification of underground infrastructure networks, such as metal and concrete pipes (gas, water or sewer), phone conduits or cables, and other buried objects. Due to the polarization-dependent response of typical targets, it is of interest to investigate the optimum antenna arrangement and/or combination of arrangements that maximize the detection and classification capabilities of polarimetric GPR imaging systems. Here, we provide a preliminary study of time-reversal-based techniques applied to target detection by GPR utilizing different relative orientations of linear-polarized antenna elements (with respect to each other, as well as to the targets). We modeled three different pipe materials (metallic, plastic and concrete) and GPR systems operating at center frequencies of 100 MHz and 200 MHz. Full-wave numerical simulations are adopted to account for mutual coupling between targets. This type of assessment study may contribute to the improvement of GPR data interpretation of infrastructure networks in urban area surveys and in other engineering studies.

  12. Detection of genetically modified organisms (GMOs) using isothermal amplification of target DNA sequences.

    PubMed

    Lee, David; La Mura, Maurizio; Allnutt, Theo R; Powell, Wayne

    2009-02-02

    The most common method of GMO detection is based upon the amplification of GMO-specific DNA amplicons using the polymerase chain reaction (PCR). Here we have applied the loop-mediated isothermal amplification (LAMP) method to amplify GMO-related DNA sequences, 'internal' commonly-used motifs for controlling transgene expression and event-specific (plant-transgene) junctions. We have tested the specificity and sensitivity of the technique for use in GMO studies. Results show that detection of 0.01% GMO in equivalent background DNA was possible and dilutions of template suggest that detection from single copies of the template may be possible using LAMP. This work shows that GMO detection can be carried out using LAMP for routine screening as well as for specific events detection. Moreover, the sensitivity and ability to amplify targets, even with a high background of DNA, here demonstrated, highlights the advantages of this isothermal amplification when applied for GMO detection.

  13. Statistical sensor fusion analysis of near-IR polarimetric and thermal imagery for the detection of minelike targets

    NASA Astrophysics Data System (ADS)

    Weisenseel, Robert A.; Karl, William C.; Castanon, David A.; DiMarzio, Charles A.

    1999-02-01

    We present an analysis of statistical model based data-level fusion for near-IR polarimetric and thermal data, particularly for the detection of mines and mine-like targets. Typical detection-level data fusion methods, approaches that fuse detections from individual sensors rather than fusing at the level of the raw data, do not account rationally for the relative reliability of different sensors, nor the redundancy often inherent in multiple sensors. Representative examples of such detection-level techniques include logical AND/OR operations on detections from individual sensors and majority vote methods. In this work, we exploit a statistical data model for the detection of mines and mine-like targets to compare and fuse multiple sensor channels. Our purpose is to quantify the amount of knowledge that each polarimetric or thermal channel supplies to the detection process. With this information, we can make reasonable decisions about the usefulness of each channel. We can use this information to improve the detection process, or we can use it to reduce the number of required channels.

  14. Automated multiple target detection and tracking in UAV videos

    NASA Astrophysics Data System (ADS)

    Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

    2010-04-01

    In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

  15. Visual attention distracter insertion for improved EEG rapid serial visual presentation (RSVP) target stimuli detection

    NASA Astrophysics Data System (ADS)

    Khosla, Deepak; Huber, David J.; Martin, Kevin

    2017-05-01

    This paper† describes a technique in which we improve upon the prior performance of the Rapid Serial Visual Presentation (RSVP) EEG paradigm for image classification though the insertion of visual attention distracters and overall sequence reordering based upon the expected ratio of rare to common "events" in the environment and operational context. Inserting distracter images maintains the ratio of common events to rare events at an ideal level, maximizing the rare event detection via P300 EEG response to the RSVP stimuli. The method has two steps: first, we compute the optimal number of distracters needed for an RSVP stimuli based on the desired sequence length and expected number of targets and insert the distracters into the RSVP sequence, and then we reorder the RSVP sequence to maximize P300 detection. We show that by reducing the ratio of target events to nontarget events using this method, we can allow RSVP sequences with more targets without sacrificing area under the ROC curve (azimuth).

  16. Detection of Accelerating Targets in Clutter Using a De-Chirping Technique

    DTIC Science & Technology

    2014-06-01

    Academy, also in Canberra, working on the the- ory and simulation of spatial optical solitons and light-induced optical switching in nonlinear...signal gain in the receiver. UNCLASSIFIED 1 DSTO–RR–0399 UNCLASSIFIED target along the velocity vector , or equivalently by radar platform. The change of...the tracker uses range rate in its track initiation logic. (2) Lateral acceleration perpendicular to the velocity vector - the target is turning and

  17. Development of a microcapillary column for detecting targeted messenger RNA molecules.

    PubMed

    Ohnishi, Michihiro

    2006-03-24

    A capillary column in a rapid-flow system has been developed for detecting targeted messenger RNA (mRNA) molecules. The column has a structure made of two beds-one bed of porous microbeads and one bed of microbeads with a polythymidine base sequence. The targeted eukaryotic mRNA molecules are detected by two-step hybridization (sandwich hybridization) composed of polyadenosine selection of mRNA molecules and formation of a probe-target (targeted mRNA) hybrid. The sandwich hybridization, which is accomplished within 1 h, was tested using synthetic polydeoxynucleotides. Ten picomoles of the targeted polydeoxynucleotide were detected.

  18. Target molecules detection by waveguiding in a photonic silicon membrane

    DOEpatents

    Letant, Sonia E [Livermore, CA; Van Buuren, Anthony [Livermore, CA; Terminello, Louis [Danville, CA; Hart, Bradley R [Brentwood, CA

    2006-12-26

    Disclosed herein is a porous silicon filter capable of binding and detecting biological and chemical target molecules in liquid or gas samples. A photonic waveguiding silicon filter with chemical and/or biological anchors covalently attached to the pore walls bind target molecules. The system uses transmission curve engineering principles to allow measurements to be made in situ and in real time to detect the presence of various target molecules and calculate the concentration of bound target.

  19. Target molecules detection by waveguiding in a photonic silicon membrane

    DOEpatents

    Letant, Sonia; Van Buuren, Anthony; Terminello, Louis

    2004-08-31

    Disclosed herein is a photonic silicon filter capable of binding and detecting biological and chemical target molecules in liquid or gas samples. A photonic waveguiding silicon filter with chemical and/or biological anchors covalently attached to the pore walls selectively bind target molecules. The system uses transmission curve engineering principles to allow measurements to be made in situ and in real time to detect the presence of various target molecules and determine the concentration of bound target.

  20. Molecular detection of pathogens in water--the pros and cons of molecular techniques.

    PubMed

    Girones, Rosina; Ferrús, Maria Antonia; Alonso, José Luis; Rodriguez-Manzano, Jesus; Calgua, Byron; Corrêa, Adriana de Abreu; Hundesa, Ayalkibet; Carratala, Anna; Bofill-Mas, Sílvia

    2010-08-01

    Pollution of water by sewage and run-off from farms produces a serious public health problem in many countries. Viruses, along with bacteria and protozoa in the intestine or in urine are shed and transported through the sewer system. Even in highly industrialized countries, pathogens, including viruses, are prevalent throughout the environment. Molecular methods are used to monitor viral, bacterial, and protozoan pathogens, and to track pathogen- and source-specific markers in the environment. Molecular techniques, specifically polymerase chain reaction-based methods, provide sensitive, rapid, and quantitative analytical tools with which to study such pathogens, including new or emerging strains. These techniques are used to evaluate the microbiological quality of food and water, and to assess the efficiency of virus removal in drinking and wastewater treatment plants. The range of methods available for the application of molecular techniques has increased, and the costs involved have fallen. These developments have allowed the potential standardization and automation of certain techniques. In some cases they facilitate the identification, genotyping, enumeration, viability assessment, and source-tracking of human and animal contamination. Additionally, recent improvements in detection technologies have allowed the simultaneous detection of multiple targets in a single assay. However, the molecular techniques available today and those under development require further refinement in order to be standardized and applicable to a diversity of matrices. Water disinfection treatments may have an effect on the viability of pathogens and the numbers obtained by molecular techniques may overestimate the quantification of infectious microorganisms. The pros and cons of molecular techniques for the detection and quantification of pathogens in water are discussed. (c) 2010 Elsevier Ltd. All rights reserved.

  1. Target detection in insects: optical, neural and behavioral optimizations.

    PubMed

    Gonzalez-Bellido, Paloma T; Fabian, Samuel T; Nordström, Karin

    2016-12-01

    Motion vision provides important cues for many tasks. Flying insects, for example, may pursue small, fast moving targets for mating or feeding purposes, even when these are detected against self-generated optic flow. Since insects are small, with size-constrained eyes and brains, they have evolved to optimize their optical, neural and behavioral target visualization solutions. Indeed, even if evolutionarily distant insects display different pursuit strategies, target neuron physiology is strikingly similar. Furthermore, the coarse spatial resolution of the insect compound eye might actually be beneficial when it comes to detection of moving targets. In conclusion, tiny insects show higher than expected performance in target visualization tasks. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Effects of age and eccentricity on visual target detection.

    PubMed

    Gruber, Nicole; Müri, René M; Mosimann, Urs P; Bieri, Rahel; Aeschimann, Andrea; Zito, Giuseppe A; Urwyler, Prabitha; Nyffeler, Thomas; Nef, Tobias

    2013-01-01

    The aim of this study was to examine the effects of aging and target eccentricity on a visual search task comprising 30 images of everyday life projected into a hemisphere, realizing a ±90° visual field. The task performed binocularly allowed participants to freely move their eyes to scan images for an appearing target or distractor stimulus (presented at 10°; 30°, and 50° eccentricity). The distractor stimulus required no response, while the target stimulus required acknowledgment by pressing the response button. One hundred and seventeen healthy subjects (mean age = 49.63 years, SD = 17.40 years, age range 20-78 years) were studied. The results show that target detection performance decreases with age as well as with increasing eccentricity, especially for older subjects. Reaction time also increases with age and eccentricity, but in contrast to target detection, there is no interaction between age and eccentricity. Eye movement analysis showed that younger subjects exhibited a passive search strategy while older subjects exhibited an active search strategy probably as a compensation for their reduced peripheral detection performance.

  3. A saliency-based approach to detection of infrared target

    NASA Astrophysics Data System (ADS)

    Chen, Yanfei; Sang, Nong; Dan, Zhiping

    2013-10-01

    Automatic target detection in infrared images is a hot research field of national defense technology. We propose a new saliency-based infrared target detection model in this paper, which is based on the fact that human focus of attention is directed towards the relevant target to interpret the most promising information. For a given image, the convolution of the image log amplitude spectrum with a low-pass Gaussian kernel of an appropriate scale is equivalent to an image saliency detector in the frequency domain. At the same time, orientation and shape features extracted are combined into a saliency map in the spatial domain. Our proposed model decides salient targets based on a final saliency map, which is generated by integration of the saliency maps in the frequency and spatial domain. At last, the size of each salient target is obtained by maximizing entropy of the final saliency map. Experimental results show that the proposed model can highlight both small and large salient regions in infrared image, as well as inhibit repeated distractors in cluttered image. In addition, its detecting efficiency has improved significantly.

  4. An infrared small target detection method based on multiscale local homogeneity measure

    NASA Astrophysics Data System (ADS)

    Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen

    2018-05-01

    Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.

  5. Targeted next generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes

    DTIC Science & Technology

    2016-07-06

    1 Targeted next-generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes Christopher P...development and evaluation of a panel of 44 single-stranded molecular inversion probes (MIPs) coupled to next-generation sequencing (NGS) for the...padlock and molecular inversion probes as upfront enrichment steps for use with NGS showed the specificity and multiplexability of these techniques

  6. A computational imaging target specific detectivity metric

    NASA Astrophysics Data System (ADS)

    Preece, Bradley L.; Nehmetallah, George

    2017-05-01

    Due to the large quantity of low-cost, high-speed computational processing available today, computational imaging (CI) systems are expected to have a major role for next generation multifunctional cameras. The purpose of this work is to quantify the performance of theses CI systems in a standardized manner. Due to the diversity of CI system designs that are available today or proposed in the near future, significant challenges in modeling and calculating a standardized detection signal-to-noise ratio (SNR) to measure the performance of these systems. In this paper, we developed a path forward for a standardized detectivity metric for CI systems. The detectivity metric is designed to evaluate the performance of a CI system searching for a specific known target or signal of interest, and is defined as the optimal linear matched filter SNR, similar to the Hotelling SNR, calculated in computational space with special considerations for standardization. Therefore, the detectivity metric is designed to be flexible, in order to handle various types of CI systems and specific targets, while keeping the complexity and assumptions of the systems to a minimum.

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

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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

  8. A new method for detecting small and dim targets in starry background

    NASA Astrophysics Data System (ADS)

    Yao, Rui; Zhang, Yanning; Jiang, Lei

    2011-08-01

    Small visible optical space targets detection is one of the key issues in the research of long-range early warning and space debris surveillance. The SNR(Signal to Noise Ratio) of the target is very low because of the self influence of image device. Random noise and background movement also increase the difficulty of target detection. In order to detect small visible optical space targets effectively and rapidly, we bring up a novel detecting method based on statistic theory. Firstly, we get a reasonable statistical model of visible optical space image. Secondly, we extract SIFT(Scale-Invariant Feature Transform) feature of the image frames, and calculate the transform relationship, then use the transform relationship to compensate whole visual field's movement. Thirdly, the influence of star was wiped off by using interframe difference method. We find segmentation threshold to differentiate candidate targets and noise by using OTSU method. Finally, we calculate statistical quantity to judge whether there is the target for every pixel position in the image. Theory analysis shows the relationship of false alarm probability and detection probability at different SNR. The experiment result shows that this method could detect target efficiently, even the target passing through stars.

  9. Detection and quantification of bacterial biofilms combining high-frequency acoustic microscopy and targeted lipid microparticles

    PubMed Central

    2014-01-01

    matrices difficult. The combination of ultrasound and targeted UCAs can be used to enhance biofilm imaging and early detection. Our findings suggest that the combination of targeted UCAs and ultrasound is a novel molecular imaging technique for the detection of biofilms. We show that high-frequency acoustic microscopy provides sufficient spatial resolution for quantification of biofilm mechanoelastic properties. PMID:24997588

  10. Detection and quantification of bacterial biofilms combining high-frequency acoustic microscopy and targeted lipid microparticles.

    PubMed

    Anastasiadis, Pavlos; Mojica, Kristina D A; Allen, John S; Matter, Michelle L

    2014-07-06

    . The combination of ultrasound and targeted UCAs can be used to enhance biofilm imaging and early detection. Our findings suggest that the combination of targeted UCAs and ultrasound is a novel molecular imaging technique for the detection of biofilms. We show that high-frequency acoustic microscopy provides sufficient spatial resolution for quantification of biofilm mechanoelastic properties.

  11. Clever eye algorithm for target detection of remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Geng, Xiurui; Ji, Luyan; Sun, Kang

    2016-04-01

    Target detection algorithms for hyperspectral remote sensing imagery, such as the two most commonly used remote sensing detection algorithms, the constrained energy minimization (CEM) and matched filter (MF), can usually be attributed to the inner product between a weight filter (or detector) and a pixel vector. CEM and MF have the same expression except that MF requires data centralization first. However, this difference leads to a difference in the target detection results. That is to say, the selection of the data origin could directly affect the performance of the detector. Therefore, does there exist another data origin other than the zero and mean-vector points for a better target detection performance? This is a very meaningful issue in the field of target detection, but it has not been paid enough attention yet. In this study, we propose a novel objective function by introducing the data origin as another variable, and the solution of the function is corresponding to the data origin with the minimal output energy. The process of finding the optimal solution can be vividly regarded as a clever eye automatically searching the best observing position and direction in the feature space, which corresponds to the largest separation between the target and background. Therefore, this new algorithm is referred to as the clever eye algorithm (CE). Based on the Sherman-Morrison formula and the gradient ascent method, CE could derive the optimal target detection result in terms of energy. Experiments with both synthetic and real hyperspectral data have verified the effectiveness of our method.

  12. Detection of target phonemes in spontaneous and read speech.

    PubMed

    Mehta, G; Cutler, A

    1988-01-01

    Although spontaneous speech occurs more frequently in most listeners' experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalise to the recognition of spontaneous speech. In the present study listeners were presented with both spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Responses were, overall, equally fast in each speech mode. However, analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than in unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claims from previous work that listeners pay great attention to prosodic information in the process of recognising speech.

  13. Automatic small target detection in synthetic infrared images

    NASA Astrophysics Data System (ADS)

    Yardımcı, Ozan; Ulusoy, Ä.°lkay

    2017-05-01

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

  14. Comparison of two target classification techniques

    NASA Astrophysics Data System (ADS)

    Chen, J. S.; Walton, E. K.

    1986-01-01

    Radar target classification techniques based on backscatter measurements in the resonance region (1.0-20.0 MHz) are discussed. Attention is given to two novel methods currently being tested at the radar range of Ohio State University. The methods include: (1) the nearest neighbor (NN) algorithm for determining the radar cross section (RCS) magnitude and range corrected phase at various operating frequencies; and (2) an inverse Fourier transformation of the complex multifrequency radar returns of the time domain, followed by cross correlation analysis. Comparisons are made of the performance of the two techniques as a function of signal-to-error noise ratio for different types of processing. The results of the comparison are discussed in detail.

  15. Integration of bio-inspired, control-based visual and olfactory data for the detection of an elusive target

    NASA Astrophysics Data System (ADS)

    Duong, Tuan A.; Duong, Nghi; Le, Duong

    2017-01-01

    In this paper, we present an integration technique using a bio-inspired, control-based visual and olfactory receptor system to search for elusive targets in practical environments where the targets cannot be seen obviously by either sensory data. Bio-inspired Visual System is based on a modeling of extended visual pathway which consists of saccadic eye movements and visual pathway (vertebrate retina, lateral geniculate nucleus and visual cortex) to enable powerful target detections of noisy, partial, incomplete visual data. Olfactory receptor algorithm, namely spatial invariant independent component analysis, that was developed based on data of old factory receptor-electronic nose (enose) of Caltech, is adopted to enable the odorant target detection in an unknown environment. The integration of two systems is a vital approach and sets up a cornerstone for effective and low-cost of miniaturized UAVs or fly robots for future DOD and NASA missions, as well as for security systems in Internet of Things environments.

  16. Improved target detection by IR dual-band image fusion

    NASA Astrophysics Data System (ADS)

    Adomeit, U.; Ebert, R.

    2009-09-01

    Dual-band thermal imagers acquire information simultaneously in both the 8-12 μm (long-wave infrared, LWIR) and the 3-5 μm (mid-wave infrared, MWIR) spectral range. Compared to single-band thermal imagers they are expected to have several advantages in military applications. These advantages include the opportunity to use the best band for given atmospheric conditions (e. g. cold climate: LWIR, hot and humid climate: MWIR), the potential to better detect camouflaged targets and an improved discrimination between targets and decoys. Most of these advantages have not yet been verified and/or quantified. It is expected that image fusion allows better exploitation of the information content available with dual-band imagers especially with respect to detection of targets. We have developed a method for dual-band image fusion based on the apparent temperature differences in the two bands. This method showed promising results in laboratory tests. In order to evaluate its performance under operational conditions we conducted a field trial in an area with high thermal clutter. In such areas, targets are hardly to detect in single-band images because they vanish in the clutter structure. The image data collected in this field trial was used for a perception experiment. This perception experiment showed an enhanced target detection range and reduced false alarm rate for the fused images compared to the single-band images.

  17. High-Speed Incoming Infrared Target Detection by Fusion of Spatial and Temporal Detectors

    PubMed Central

    Kim, Sungho

    2015-01-01

    This paper presents a method for detecting high-speed incoming targets by the fusion of spatial and temporal detectors to achieve a high detection rate for an active protection system (APS). The incoming targets have different image velocities according to the target-camera geometry. Therefore, single-target detector-based approaches, such as a 1D temporal filter, 2D spatial filter and 3D matched filter, cannot provide a high detection rate with moderate false alarms. The target speed variation was analyzed according to the incoming angle and target velocity. The speed of the distant target at the firing time is almost stationary and increases slowly. The speed varying targets are detected stably by fusing the spatial and temporal filters. The stationary target detector is activated by an almost zero temporal contrast filter (TCF) and identifies targets using a spatial filter called the modified mean subtraction filter (M-MSF). A small motion (sub-pixel velocity) target detector is activated by a small TCF value and finds targets using the same spatial filter. A large motion (pixel-velocity) target detector works when the TCF value is high. The final target detection is terminated by fusing the three detectors based on the threat priority. The experimental results of the various target sequences show that the proposed fusion-based target detector produces the highest detection rate with an acceptable false alarm rate. PMID:25815448

  18. ARPA surveillance technology for detection of targets hidden in foliage

    NASA Astrophysics Data System (ADS)

    Hoff, Lawrence E.; Stotts, Larry B.

    1994-02-01

    The processing of large quantities of synthetic aperture radar data in real time is a complex problem. Even the image formation process taxes today's most advanced computers. The use of complex algorithms with multiple channels adds another dimension to the computational problem. Advanced Research Projects Agency (ARPA) is currently planning on using the Paragon parallel processor for this task. The Paragon is small enough to allow its use in a sensor aircraft. Candidate algorithms will be implemented on the Paragon for evaluation for real time processing. In this paper ARPA technology developments for detecting targets hidden in foliage are reviewed and examples of signal processing techniques on field collected data are presented.

  19. A Novel Detection Method for Underwater Moving Targets by Measuring Their ELF Emissions with Inductive Sensors

    PubMed Central

    Li, Bin; Chen, Lianping; Li, Li

    2017-01-01

    In this article, we propose a novel detection method for underwater moving targets by detecting their extremely low frequency (ELF) emissions with inductive sensors. The ELF field source of the targets is modeled by a horizontal electric dipole at distances more than several times of the targets’ length. The formulas for the fields produced in air are derived with a three-layer model (air, seawater and seafloor) and are evaluated with a complementary numerical integration technique. A proof of concept measurement is presented. The ELF emissions from a surface ship were detected by inductive electronic and magnetic sensors as the ship was leaving a harbor. ELF signals are of substantial strength and have typical characteristic of harmonic line spectrum, and the fundamental frequency has a direct relationship with the ship’s speed. Due to the high sensitivity and low noise level of our sensors, it is capable of resolving weak ELF signals at long distance. In our experiment, a detection distance of 1300 m from the surface ship above the sea surface was realized, which shows that this method would be an appealing complement to the usual acoustic detection and magnetic anomaly detection capability. PMID:28788097

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

    NASA Astrophysics Data System (ADS)

    Zhang, Mo; Jin, Weiqi; Li, Li

    2016-10-01

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

  1. Electrochemical techniques on sequence-specific PCR amplicon detection for point-of-care applications.

    PubMed

    Luo, Xiaoteng; Hsing, I-Ming

    2009-10-01

    Nucleic acid based analysis provides accurate differentiation among closely affiliated species and this species- and sequence-specific detection technique would be particularly useful for point-of-care (POC) testing for prevention and early detection of highly infectious and damaging diseases. Electrochemical (EC) detection and polymerase chain reaction (PCR) are two indispensable steps, in our view, in a nucleic acid based point-of-care testing device as the former, in comparison with the fluorescence counterpart, provides inherent advantages of detection sensitivity, device miniaturization and operation simplicity, and the latter offers an effective way to boost the amount of targets to a detectable quantity. In this mini-review, we will highlight some of the interesting investigations using the combined EC detection and PCR amplification approaches for end-point detection and real-time monitoring. The promise of current approaches and the direction for future investigations will be discussed. It would be our view that the synergistic effect of the combined EC-PCR steps in a portable device provides a promising detection technology platform that will be ready for point-of-care applications in the near future.

  2. Investigating effects of communications modulation technique on targeting performance

    NASA Astrophysics Data System (ADS)

    Blasch, Erik; Eusebio, Gerald; Huling, Edward

    2006-05-01

    One of the key challenges facing the global war on terrorism (GWOT) and urban operations is the increased need for rapid and diverse information from distributed sources. For users to get adequate information on target types and movements, they would need reliable data. In order to facilitate reliable computational intelligence, we seek to explore the communication modulation tradeoffs affecting information distribution and accumulation. In this analysis, we explore the modulation techniques of Orthogonal Frequency Division Multiplexing (OFDM), Direct Sequence Spread Spectrum (DSSS), and statistical time-division multiple access (TDMA) as a function of the bit error rate and jitter that affect targeting performance. In the analysis, we simulate a Link 16 with a simple bandpass frequency shift keying (PSK) technique using different Signal-to-Noise ratios. The communications transfer delay and accuracy tradeoffs are assessed as to the effects incurred in targeting performance.

  3. Target Detection Using an AOTF Hyperspectral Imager

    NASA Technical Reports Server (NTRS)

    Cheng, L-J.; Mahoney, J.; Reyes, F.; Suiter, H.

    1994-01-01

    This paper reports results of a recent field experiment using a prototype system to evaluate the acousto-optic tunable filter polarimetric hyperspectral imaging technology for target detection applications.

  4. Quantum Illumination-Based Target Detection and Discrimination

    DTIC Science & Technology

    2014-06-30

    amplifier (EDFA) was combined with the signal to simulate a high-noise environment, with a noise photon number per mode NB in the range 40–300. The...Research Triangle Park, NC 27709-2211 quantum communication, target detection, entanglement , parametric downconversion, optical parametric amplifiers...laser system of the same average transmitted photon number, when the target return has random-amplitude behavior. Receiver operating characteristic

  5. Evaluation of change detection techniques for monitoring coastal zone environments

    NASA Technical Reports Server (NTRS)

    Weismiller, R. A. (Principal Investigator); Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.

    1977-01-01

    The author has identified the following significant results. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. The post classification comparison technique reliably identified areas of change and was used as the standard for qualitatively evaluating the other three techniques. The layered spectral/temporal change classification and the delta data change detection results generally agreed with the post classification comparison technique results; however, many small areas of change were not identified. Major discrepancies existed between the post classification comparison and spectral/temporal change detection results.

  6. Portable apparatus for separating sample and detecting target analytes

    DOEpatents

    Renzi, Ronald F.; Wally, Karl; Crocker, Robert W.; Stamps, James F.; Griffiths; Stewart K. ,; Fruetel, Julia A.; Horn, Brent A.; Shokair, Isaac R.; Yee, Daniel D.; VanderNoot, Victoria A.; Wiedenman, Boyd J.; West, Jason A. A.; Ferko, Scott M.

    2008-11-18

    Portable devices and methods for determining the presence of a target analyte using a portable device are provided. The portable device is preferably hand-held. A sample is injected to the portable device. A microfluidic separation is performed within the portable device and at least one separated component detected by a detection module within the portable device, in embodiments of the invention. A target analyte is identified, based on the separated component, and the presence of the target analyte is indicated on an output interface of the portable device, in accordance with embodiments of the invention.

  7. Invariant target detection by a correlation radiometer

    NASA Astrophysics Data System (ADS)

    Murza, L. P.

    1986-12-01

    The paper is concerned with the problem of the optimal detection of a heat-emitting target by a two-channel radiometer with an unstable amplification circuit. An expression is obtained for an asymptotically sufficient detection statistic which is invariant to changes in the amplification coefficients of the channels. The algorithm proposed here can be implemented numerically using a relatively simple program.

  8. Ultrasensitive detection of target analyte-induced aggregation of gold nanoparticles using laser-induced nanoparticle Rayleigh scattering.

    PubMed

    Lin, Jia-Hui; Tseng, Wei-Lung

    2015-01-01

    Detection of salt- and analyte-induced aggregation of gold nanoparticles (AuNPs) mostly relies on costly and bulky analytical instruments. To response this drawback, a portable, miniaturized, sensitive, and cost-effective detection technique is urgently required for rapid field detection and monitoring of target analyte via the use of AuNP-based sensor. This study combined a miniaturized spectrometer with a 532-nm laser to develop a laser-induced Rayleigh scattering technique, allowing the sensitive and selective detection of Rayleigh scattering from the aggregated AuNPs. Three AuNP-based sensing systems, including salt-, thiol- and metal ion-induced aggregation of the AuNPs, were performed to examine the sensitivity of laser-induced Rayleigh scattering technique. Salt-, thiol-, and metal ion-promoted NP aggregation were exemplified by the use of aptamer-adsorbed, fluorosurfactant-stabilized, and gallic acid-capped AuNPs for probing K(+), S-adenosylhomocysteine hydrolase-induced hydrolysis of S-adenosylhomocysteine, and Pb(2+), in sequence. Compared to the reported methods for monitoring the aggregated AuNPs, the proposed system provided distinct advantages of sensitivity. Laser-induced Rayleigh scattering technique was improved to be convenient, cheap, and portable by replacing a diode laser and a miniaturized spectrometer with a laser pointer and a smart-phone. Using this smart-phone-based detection platform, we can determine whether or not the Pb(2+) concentration exceed the maximum allowable level of Pb(2+) in drinking water. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Glint-induced false alarm reduction in signature adaptive target detection

    NASA Astrophysics Data System (ADS)

    Crosby, Frank J.

    2002-07-01

    The signal adaptive target detection algorithm developed by Crosby and Riley uses target geometry to discern anomalies in local backgrounds. Detection is not restricted based on specific target signatures. The robustness of the algorithm is limited by an increased false alarm potential. The base algorithm is extended to eliminate one common source of false alarms in a littoral environment. This common source is glint reflected on the surface of water. The spectral and spatial transience of glint prevent straightforward characterization and complicate exclusion. However, the statistical basis of the detection algorithm and its inherent computations allow for glint discernment and the removal of its influence.

  10. A long-term target detection approach in infrared image sequence

    NASA Astrophysics Data System (ADS)

    Li, Hang; Zhang, Qi; Wang, Xin; Hu, Chao

    2016-10-01

    An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on POME(the principle of maximum entropy), target candidates are iteratively segmented. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

  11. Targeting New Teachers & Teaching by Novel Techniques.

    ERIC Educational Resources Information Center

    Hopkins, Patricia; And Others

    In 1988-89, the Science Academy, a magnet program at LBJ High School (Austin, Texas), was awarded a two-year grant called Double TNT to "target new teachers" and "teach by novel techniques." The purposes of the program include: (1) interesting minority and female students in science; (2) attracting minority and female students…

  12. LWIR hyperspectral change detection for target acquisition and situation awareness in urban areas

    NASA Astrophysics Data System (ADS)

    Dekker, Rob J.; Schwering, Piet B. W.; Benoist, Koen W.; Pignatti, Stefano; Santini, Federico; Friman, Ola

    2013-05-01

    This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect to conventional techniques. Hyperspectral and conventional broadband high-spatial-resolution data were collected during the DUCAS trials in Zeebrugge, Belgium, in June 2011. LWIR data were acquired using the ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates in the spectral range of 8.0-11.5 μm (32 band configuration). Broadband data were acquired using two aeroplanemounted FLIR SC7000 MWIR cameras. Acquisition of the images was around noon. To limit the number of false alarms due to atmospheric changes, the time interval between the images is less than 2 hours. Local co-registration adjustment was applied to compensate for misregistration errors in the order of a few pixels. The targets in the data that will be analysed in this paper are different kinds of vehicles. Change detection algorithms that were applied and evaluated are Euclidean distance, Mahalanobis distance, Chronochrome (CC), Covariance Equalisation (CE), and Hyperbolic Anomalous Change Detection (HACD). Based on Receiver Operating Characteristics (ROC) we conclude that LWIR hyperspectral has an advantage over MWIR broadband change detection. The best hyperspectral detector is HACD because it is most robust to noise. MWIR high spatial-resolution broadband results show that it helps to apply a false alarm reduction strategy based on spatial processing.

  13. Joint sparsity based heterogeneous data-level fusion for target detection and estimation

    NASA Astrophysics Data System (ADS)

    Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

    2017-05-01

    Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

  14. Detection and classification of underwater targets by echolocating dolphins

    NASA Astrophysics Data System (ADS)

    Au, Whitlow

    2003-10-01

    Many experiments have been performed with echolocating dolphins to determine their target detection and discrimination capabilities. Target detection experiments have been performed in a naturally noisy environment, with masking noise and with both phantom echoes and masking noise, and in reverberation. The echo energy to rms noise spectral density for the Atlantic bottlenose dolphin (Tursiops truncatus) at the 75% correct response threshold is approximately 7.5 dB whereas for the beluga whale (Delphinapterus leucas) the threshold is approximately 1 dB. The dolphin's detection threshold in reverberation is approximately 2.5 dB vs 2 dB for the beluga. The difference in performance between species can probably be ascribed to differences in how both species perceived the task. The bottlenose dolphin may be performing a combination detection/discrimination task whereas the beluga may be performing a simple detection task. Echolocating dolphins also have the capability to make fine discriminate of target properties such as wall thickness difference of water-filled cylinders and material differences in metallic plates. The high resolution property of the animal's echolocation signals and the high dynamic range of its auditory system are important factors in their outstanding discrimination capabilities.

  15. Development of ion beam sputtering techniques for actinide target preparation

    NASA Astrophysics Data System (ADS)

    Aaron, W. S.; Zevenbergen, L. A.; Adair, H. L.

    1985-06-01

    Ion beam sputtering is a routine method for the preparation of thin films used as targets because it allows the use of a minimum quantity of starting material, and losses are much lower than most other vacuum deposition techniques. Work is underway in the Isotope Research Materials Laboratory (IRML) at ORNL to develop the techniques that will make the preparation of actinide targets up to 100 μg/cm 2 by ion beam sputtering a routinely available service from IRML. The preparation of the actinide material in a form suitable for sputtering is a key to this technique, as is designing a sputtering system that allows the flexibility required for custom-ordered target production. At present, development work is being conducted on low-activity actinides in a bench-top system. The system will then be installed in a hood or glove box approved for radioactive materials handling where processing of radium, actinium, and plutonium isotopes among others will be performed.

  16. Target detection portal

    DOEpatents

    Linker, Kevin L.; Brusseau, Charles A.

    2002-01-01

    A portal apparatus for screening persons or objects for the presence of trace amounts of target substances such as explosives, narcotics, radioactive materials, and certain chemical materials. The portal apparatus can have a one-sided exhaust for an exhaust stream, an interior wall configuration with a concave-shape across a horizontal cross-section for each of two facing sides to result in improved airflow and reduced washout relative to a configuration with substantially flat parallel sides; air curtains to reduce washout; ionizing sprays to collect particles bound by static forces, as well as gas jet nozzles to dislodge particles bound by adhesion to the screened person or object. The portal apparatus can be included in a detection system with a preconcentrator and a detector.

  17. Challenging loop-mediated isothermal amplification (LAMP) technique for molecular detection of Toxoplasma gondii.

    PubMed

    Fallahi, Shirzad; Mazar, Zahra Arab; Ghasemian, Mehrdad; Haghighi, Ali

    2015-05-01

    To compare analytical sensitivity and specificity of a newly described DNA amplification technique, LAMP and nested PCR assay targeting the RE and B1 genes for the detection of Toxoplasma gondii (T. gondii) DNA. The analytical sensitivity of LAMP and nested-PCR was obtained against10-fold serial dilutions of T. gondii DNA ranging from 1 ng to 0.01 fg. DNA samples of other parasites and human chromosomal DNA were used to determine the specificity of molecular assays. After testing LAMP and nested-PCR in duplicate, the detection limit of RE-LAMP, B1-LAMP, RE-nested PCR and B1-nested PCR assays was one fg, 100 fg, 1 pg and 10 pg of T. gondii DNA respectively. All the LAMP assays and nested PCRs were 100% specific. The RE-LAMP assay revealed the most sensitivity for the detection of T. gondii DNA. The obtained results demonstrate that the LAMP technique has a greater sensitivity for detection of T. gondii. Furthermore, these findings indicate that primers based on the RE are more suitable than those based on the B1 gene. However, the B1-LAMP assay has potential as a diagnostic tool for detection of T. gondii. Copyright © 2015 Hainan Medical College. Production and hosting by Elsevier B.V. All rights reserved.

  18. Assessing the Rayleigh Intensity Remote Leak Detection Technique

    NASA Technical Reports Server (NTRS)

    Clements, Sandra

    2001-01-01

    Remote sensing technologies are being considered for efficient, low cost gas leak detection. An exploratory project to identify and evaluate remote sensing technologies for application to gas leak detection is underway. During Phase 1 of the project, completed last year, eleven specific techniques were identified for further study. One of these, the Rayleigh Intensity technique, would make use of changes in the light scattered off of gas molecules to detect and locate a leak. During the 10-week Summer Faculty Fellowship Program, the scatter of light off of gas molecules was investigated. The influence of light scattered off of aerosols suspended in the atmosphere was also examined to determine if this would adversely affect leak detection. Results of this study indicate that in unconditioned air, it will be difficult, though perhaps not impossible, to distinguish between a gas leak and natural variations in the aerosol content of the air. Because information about the particle size distribution in clean room environments is incomplete, the applicability in clean rooms is uncertain though more promising than in unconditioned environments. It is suggested that problems caused by aerosols may be overcome by using the Rayleigh Intensity technique in combination with another remote sensing technique, the Rayleigh Doppler technique.

  19. Applying the log-normal distribution to target detection

    NASA Astrophysics Data System (ADS)

    Holst, Gerald C.

    1992-09-01

    Holst and Pickard experimentally determined that MRT responses tend to follow a log-normal distribution. The log normal distribution appeared reasonable because nearly all visual psychological data is plotted on a logarithmic scale. It has the additional advantage that it is bounded to positive values; an important consideration since probability of detection is often plotted in linear coordinates. Review of published data suggests that the log-normal distribution may have universal applicability. Specifically, the log-normal distribution obtained from MRT tests appears to fit the target transfer function and the probability of detection of rectangular targets.

  20. Contrast, size, and orientation-invariant target detection in infrared imagery

    NASA Astrophysics Data System (ADS)

    Zhou, Yi-Tong; Crawshaw, Richard D.

    1991-08-01

    Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

  1. Adaptive Filter Techniques for Optical Beam Jitter Control and Target Tracking

    DTIC Science & Technology

    2008-12-01

    OPTICAL BEAM JITTER CONTROL AND TARGET TRACKING Michael J. Beerer Civilian, United States Air Force B.S., University of California Irvine, 2006...TECHNIQUES FOR OPTICAL BEAM JITTER CONTROL AND TARGET TRACKING by Michael J. Beerer December 2008 Thesis Advisor: Brij N. Agrawal Co...DATE December 2008 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Adaptive Filter Techniques for Optical Beam Jitter

  2. Directional detection of dark matter with two-dimensional targets

    NASA Astrophysics Data System (ADS)

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela; Tully, Christopher G.; Zurek, Kathryn M.

    2017-09-01

    We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. We show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. This proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.

  3. Directional detection of dark matter with two-dimensional targets

    DOE PAGES

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela; ...

    2017-09-01

    We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. Here, we show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. Ourmore » proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.« less

  4. Directional detection of dark matter with two-dimensional targets

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

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela

    We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. Here, we show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. Ourmore » proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.« less

  5. A novel data-driven learning method for radar target detection in nonstationary environments

    DOE PAGES

    Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

    2016-04-12

    Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

  6. Detection of dual-band infrared small target based on joint dynamic sparse representation

    NASA Astrophysics Data System (ADS)

    Zhou, Jinwei; Li, Jicheng; Shi, Zhiguang; Lu, Xiaowei; Ren, Dongwei

    2015-10-01

    Infrared small target detection is a crucial and yet still is a difficult issue in aeronautic and astronautic applications. Sparse representation is an important mathematic tool and has been used extensively in image processing in recent years. Joint sparse representation is applied in dual-band infrared dim target detection in this paper. Firstly, according to the characters of dim targets in dual-band infrared images, 2-dimension Gaussian intensity model was used to construct target dictionary, then the dictionary was classified into different sub-classes according to different positions of Gaussian function's center point in image block; The fact that dual-band small targets detection can use the same dictionary and the sparsity doesn't lie in atom-level but in sub-class level was utilized, hence the detection of targets in dual-band infrared images was converted to be a joint dynamic sparse representation problem. And the dynamic active sets were used to describe the sparse constraint of coefficients. Two modified sparsity concentration index (SCI) criteria was proposed to evaluate whether targets exist in the images. In experiments, it shows that the proposed algorithm can achieve better detecting performance and dual-band detection is much more robust to noise compared with single-band detection. Moreover, the proposed method can be expanded to multi-spectrum small target detection.

  7. Signal-on electrochemical detection of antibiotics at zeptomole level based on target-aptamer binding triggered multiple recycling amplification.

    PubMed

    Wang, Hongzhi; Wang, Yu; Liu, Su; Yu, Jinghua; Guo, Yuna; Xu, Ying; Huang, Jiadong

    2016-06-15

    In the work, a signal-on electrochemical DNA sensor based on multiple amplification for ultrasensitive detection of antibiotics has been reported. In the presence of target, the ingeniously designed hairpin probe (HP1) is opened and the polymerase-assisted target recycling amplification is triggered, resulting in autonomous generation of secondary target. It is worth noting that the produced secondary target could not only hybridize with other HP1, but also displace the Helper from the electrode. Consequently, methylene blue labeled HP2 forms a "close" probe structure, and the increase of signal is monitored. The increasing current provides an ultrasensitive electrochemical detection for antibiotics down to 1.3 fM. To our best knowledge, such work is the first report about multiple recycling amplification combing with signal-on sensing strategy, which has been utilized for quantitative determination of antibiotics. It would be further used as a general strategy associated with more analytical techniques toward the detection of a wide spectrum of analytes. Thus, it holds great potential for the development of ultrasensitive biosensing platform for the applications in bioanalysis, disease diagnostics, and clinical biomedicine. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Neural Dynamics Underlying Target Detection in the Human Brain

    PubMed Central

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

    2014-01-01

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

  9. Comparative Effectiveness of Targeted Prostate Biopsy Using Magnetic Resonance Imaging Ultrasound Fusion Software and Visual Targeting: a Prospective Study.

    PubMed

    Lee, Daniel J; Recabal, Pedro; Sjoberg, Daniel D; Thong, Alan; Lee, Justin K; Eastham, James A; Scardino, Peter T; Vargas, Hebert Alberto; Coleman, Jonathan; Ehdaie, Behfar

    2016-09-01

    We compared the diagnostic outcomes of magnetic resonance-ultrasound fusion and visually targeted biopsy for targeting regions of interest on prostate multiparametric magnetic resonance imaging. Patients presenting for prostate biopsy with regions of interest on multiparametric magnetic resonance imaging underwent magnetic resonance imaging targeted biopsy. For each region of interest 2 visually targeted cores were obtained, followed by 2 cores using a magnetic resonance-ultrasound fusion device. Our primary end point was the difference in the detection of high grade (Gleason 7 or greater) and any grade cancer between visually targeted and magnetic resonance-ultrasound fusion, investigated using McNemar's method. Secondary end points were the difference in detection rate by biopsy location using a logistic regression model and the difference in median cancer length using the Wilcoxon signed rank test. We identified 396 regions of interest in 286 men. The difference in the detection of high grade cancer between magnetic resonance-ultrasound fusion biopsy and visually targeted biopsy was -1.4% (95% CI -6.4 to 3.6, p=0.6) and for any grade cancer the difference was 3.5% (95% CI -1.9 to 8.9, p=0.2). Median cancer length detected by magnetic resonance-ultrasound fusion and visually targeted biopsy was 5.5 vs 5.8 mm, respectively (p=0.8). Magnetic resonance-ultrasound fusion biopsy detected 15% more cancers in the transition zone (p=0.046) and visually targeted biopsy detected 11% more high grade cancer at the prostate base (p=0.005). Only 52% of all high grade cancers were detected by both techniques. We found no evidence of a significant difference in the detection of high grade or any grade cancer between visually targeted and magnetic resonance-ultrasound fusion biopsy. However, the performance of each technique varied in specific biopsy locations and the outcomes of both techniques were complementary. Combining visually targeted biopsy and magnetic resonance

  10. Sparsity based target detection for compressive spectral imagery

    NASA Astrophysics Data System (ADS)

    Boada, David Alberto; Arguello Fuentes, Henry

    2016-09-01

    Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

  11. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    PubMed Central

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  12. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

    PubMed

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-07-19

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  13. Scan statistics with local vote for target detection in distributed system

    NASA Astrophysics Data System (ADS)

    Luo, Junhai; Wu, Qi

    2017-12-01

    Target detection has occupied a pivotal position in distributed system. Scan statistics, as one of the most efficient detection methods, has been applied to a variety of anomaly detection problems and significantly improves the probability of detection. However, scan statistics cannot achieve the expected performance when the noise intensity is strong, or the signal emitted by the target is weak. The local vote algorithm can also achieve higher target detection rate. After the local vote, the counting rule is always adopted for decision fusion. The counting rule does not use the information about the contiguity of sensors but takes all sensors' data into consideration, which makes the result undesirable. In this paper, we propose a scan statistics with local vote (SSLV) method. This method combines scan statistics with local vote decision. Before scan statistics, each sensor executes local vote decision according to the data of its neighbors and its own. By combining the advantages of both, our method can obtain higher detection rate in low signal-to-noise ratio environment than the scan statistics. After the local vote decision, the distribution of sensors which have detected the target becomes more intensive. To make full use of local vote decision, we introduce a variable-step-parameter for the SSLV. It significantly shortens the scan period especially when the target is absent. Analysis and simulations are presented to demonstrate the performance of our method.

  14. UWB radar technique for arc detection in coaxial cables and waveguides

    NASA Astrophysics Data System (ADS)

    Maggiora, R.; Salvador, S.

    2009-11-01

    As spread spectrum technology has revolutionized the communications industry, Ultra Wide Band (UWB) technology is dramatically improving radar performances. These advanced signal processing techniques have been adapted to coaxial cables and waveguides to provide new features and enhanced performance on arc detection. UWB signals constituted by a sequence of chips (properly chosen to reduce side lobes and to improve detection accuracy) are transmitted along the transmission lines at a specified Pulse Repetition Frequency (PRF) and their echoes are received by means of directional couplers. The core of the receiver is an ultra high-speed correlator implemented in a Digital Signal Processor (DSP). When a target (arc) is detected, its position and its "radar cross section" are calculated to be able to provide the arc position along the transmission line and to be able to classify the type of detected arc. The "background scattering" is routinely extracted from the received signal at any pulse. This permits to be resilient to the background structure of transmission lines (bends, junctions, windows, etc.). Thanks to the localization feature, segmentation is also possible for creating sensed and non-sensed zones (for example, to be insensitive to antenna load variations).

  15. A Novel Technique to Detect Code for SAC-OCDMA System

    NASA Astrophysics Data System (ADS)

    Bharti, Manisha; Kumar, Manoj; Sharma, Ajay K.

    2018-04-01

    The main task of optical code division multiple access (OCDMA) system is the detection of code used by a user in presence of multiple access interference (MAI). In this paper, new method of detection known as XOR subtraction detection for spectral amplitude coding OCDMA (SAC-OCDMA) based on double weight codes has been proposed and presented. As MAI is the main source of performance deterioration in OCDMA system, therefore, SAC technique is used in this paper to eliminate the effect of MAI up to a large extent. A comparative analysis is then made between the proposed scheme and other conventional detection schemes used like complimentary subtraction detection, AND subtraction detection and NAND subtraction detection. The system performance is characterized by Q-factor, BER and received optical power (ROP) with respect to input laser power and fiber length. The theoretical and simulation investigations reveal that the proposed detection technique provides better quality factor, security and received power in comparison to other conventional techniques. The wide opening of eye in case of proposed technique also proves its robustness.

  16. A long-term target detection approach in infrared image sequence

    NASA Astrophysics Data System (ADS)

    Li, Hang; Zhang, Qi; Li, Yuanyuan; Wang, Liqiang

    2015-12-01

    An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on non-linear histogram equalization, target candidates are coarse-to-fine segmented by using two self-adapt thresholds generated in the intensity space. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to iteratively estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

  17. Towards real-time detection of tumor margins using photothermal imaging of immune-targeted gold nanoparticles

    PubMed Central

    Jakobsohn, Kobi; Motiei, Menachem; Sinvani, Moshe; Popovtzer, Rachela

    2012-01-01

    Background One of the critical problems in cancer management is local recurrence of disease. Between 20% and 30% of patients who undergo tumor resection surgery require reoperation due to incomplete excision. Currently, there are no validated methods for intraoperative tumor margin detection. In the present work, we demonstrate the potential use of gold nanoparticles (GNPs) as a novel contrast agent for photothermal molecular imaging of cancer. Methods Phantoms containing different concentrations of GNPs were irradiated with continuous-wave laser and measured with a thermal imaging camera which detected the temperature field of the irradiated phantoms. Results The results clearly demonstrate the ability to distinguish between cancerous cells specifically targeted with GNPs and normal cells. This technique, which allows highly sensitive discrimination between adjacent low GNP concentrations, will allow tumor margin detection while the temperature increases by only a few degrees Celsius (for GNPs in relevant biological concentrations). Conclusion We expect this real-time intraoperative imaging technique to assist surgeons in determining clear tumor margins and to maximize the extent of tumor resection while sparing normal background tissue. PMID:22956871

  18. Beyond the margins: real-time detection of cancer using targeted fluorophores

    PubMed Central

    Zhang, Ray R.; Schroeder, Alexandra B.; Grudzinski, Joseph J.; Rosenthal, Eben L.; Warram, Jason M.; Pinchuk, Anatoly N.; Eliceiri, Kevin W.; Kuo, John S.; Weichert, Jamey P.

    2017-01-01

    Over the past two decades, synergistic innovations in imaging technology have resulted in a revolution in which a range of biomedical applications are now benefiting from fluorescence imaging. Specifically, advances in fluorophore chemistry and imaging hardware, and the identification of targetable biomarkers have now positioned intraoperative fluorescence as a highly specific real-time detection modality for surgeons in oncology. In particular, the deeper tissue penetration and limited autofluorescence of near-infrared (NIR) fluorescence imaging improves the translational potential of this modality over visible-light fluorescence imaging. Rapid developments in fluorophores with improved characteristics, detection instrumentation, and targeting strategies led to the clinical testing in the early 2010s of the first targeted NIR fluorophores for intraoperative cancer detection. The foundations for the advances that underline this technology continue to be nurtured by the multidisciplinary collaboration of chemists, biologists, engineers, and clinicians. In this Review, we highlight the latest developments in NIR fluorophores, cancer-targeting strategies, and detection instrumentation for intraoperative cancer detection, and consider the unique challenges associated with their effective application in clinical settings. PMID:28094261

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

    NASA Astrophysics Data System (ADS)

    Shuxin, Li; Zhilong, Zhang; Biao, Li

    2018-01-01

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

  20. Adaptive waveform optimization design for target detection in cognitive radar

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

    2017-01-01

    The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

  1. UGS video target detection and discrimination

    NASA Astrophysics Data System (ADS)

    Roberts, G. Marlon; Fitzgerald, James; McCormack, Michael; Steadman, Robert; Vitale, Joseph D.

    2007-04-01

    This project focuses on developing electro-optic algorithms which rank images by their likelihood of containing vehicles and people. These algorithms have been applied to images obtained from Textron's Terrain Commander 2 (TC2) Unattended Ground Sensor system. The TC2 is a multi-sensor surveillance system used in military applications. It combines infrared, acoustic, seismic, magnetic, and electro-optic sensors to detect nearby targets. When targets are detected by the seismic and acoustic sensors, the system is triggered and images are taken in the visible and infrared spectrum. The original Terrain Commander system occasionally captured and transmitted an excessive number of images, sometimes triggered by undesirable targets such as swaying trees. This wasted communications bandwidth, increased power consumption, and resulted in a large amount of end-user time being spent evaluating unimportant images. The algorithms discussed here help alleviate these problems. These algorithms are currently optimized for infra-red images, which give the best visibility in a wide range of environments, but could be adapted to visible imagery as well. It is important that the algorithms be robust, with minimal dependency on user input. They should be effective when tracking varying numbers of targets of different sizes and orientations, despite the low resolutions of the images used. Most importantly, the algorithms must be appropriate for implementation on a low-power processor in real time. This would enable us to maintain frame rates of 2 Hz for effective surveillance operations. Throughout our project we have implemented several algorithms, and used an appropriate methodology to quantitatively compare their performance. They are discussed in this paper.

  2. Clinical Validation of Copy Number Variant Detection from Targeted Next-Generation Sequencing Panels.

    PubMed

    Kerkhof, Jennifer; Schenkel, Laila C; Reilly, Jack; McRobbie, Sheri; Aref-Eshghi, Erfan; Stuart, Alan; Rupar, C Anthony; Adams, Paul; Hegele, Robert A; Lin, Hanxin; Rodenhiser, David; Knoll, Joan; Ainsworth, Peter J; Sadikovic, Bekim

    2017-11-01

    Next-generation sequencing (NGS) technology has rapidly replaced Sanger sequencing in the assessment of sequence variations in clinical genetics laboratories. One major limitation of current NGS approaches is the ability to detect copy number variations (CNVs) approximately >50 bp. Because these represent a major mutational burden in many genetic disorders, parallel CNV assessment using alternate supplemental methods, along with the NGS analysis, is normally required, resulting in increased labor, costs, and turnaround times. The objective of this study was to clinically validate a novel CNV detection algorithm using targeted clinical NGS gene panel data. We have applied this approach in a retrospective cohort of 391 samples and a prospective cohort of 2375 samples and found a 100% sensitivity (95% CI, 89%-100%) for 37 unique events and a high degree of specificity to detect CNVs across nine distinct targeted NGS gene panels. This NGS CNV pipeline enables stand-alone first-tier assessment for CNV and sequence variants in a clinical laboratory setting, dispensing with the need for parallel CNV analysis using classic techniques, such as microarray, long-range PCR, or multiplex ligation-dependent probe amplification. This NGS CNV pipeline can also be applied to the assessment of complex genomic regions, including pseudogenic DNA sequences, such as the PMS2CL gene, and to mitochondrial genome heteroplasmy detection. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  3. Visual and efficient immunosensor technique for advancing biomedical applications of quantum dots on Salmonella detection and isolation

    NASA Astrophysics Data System (ADS)

    Tang, Feng; Pang, Dai-Wen; Chen, Zhi; Shao, Jian-Bo; Xiong, Ling-Hong; Xiang, Yan-Ping; Xiong, Yan; Wu, Kai; Ai, Hong-Wu; Zhang, Hui; Zheng, Xiao-Li; Lv, Jing-Rui; Liu, Wei-Yong; Hu, Hong-Bing; Mei, Hong; Zhang, Zhen; Sun, Hong; Xiang, Yun; Sun, Zi-Yong

    2016-02-01

    It is a great challenge in nanotechnology for fluorescent nanobioprobes to be applied to visually detect and directly isolate pathogens in situ. A novel and visual immunosensor technique for efficient detection and isolation of Salmonella was established here by applying fluorescent nanobioprobes on a specially-designed cellulose-based swab (a solid-phase enrichment system). The selective and chromogenic medium used on this swab can achieve the ultrasensitive amplification of target bacteria and form chromogenic colonies in situ based on a simple biochemical reaction. More importantly, because this swab can serve as an attachment site for the targeted pathogens to immobilize and immunologically capture nanobioprobes, our mAb-conjugated QD bioprobes were successfully applied on the solid-phase enrichment system to capture the fluorescence of targeted colonies under a designed excitation light instrument based on blue light-emitting diodes combined with stereomicroscopy or laser scanning confocal microscopy. Compared with the traditional methods using 4-7 days to isolate Salmonella from the bacterial mixture, this method took only 2 days to do this, and the process of initial screening and preliminary diagnosis can be completed in only one and a half days. Furthermore, the limit of detection can reach as low as 101 cells per mL Salmonella on the background of 105 cells per mL non-Salmonella (Escherichia coli, Proteus mirabilis or Citrobacter freundii, respectively) in experimental samples, and even in human anal ones. The visual and efficient immunosensor technique may be proved to be a favorable alternative for screening and isolating Salmonella in a large number of samples related to public health surveillance.It is a great challenge in nanotechnology for fluorescent nanobioprobes to be applied to visually detect and directly isolate pathogens in situ. A novel and visual immunosensor technique for efficient detection and isolation of Salmonella was established here

  4. Multi-target Detection, Tracking, and Data Association on Road Networks Using Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Barkley, Brett E.

    A cooperative detection and tracking algorithm for multiple targets constrained to a road network is presented for fixed-wing Unmanned Air Vehicles (UAVs) with a finite field of view. Road networks of interest are formed into graphs with nodes that indicate the target likelihood ratio (before detection) and position probability (after detection). A Bayesian likelihood ratio tracker recursively assimilates target observations until the cumulative observations at a particular location pass a detection criterion. At this point, a target is considered detected and a position probability is generated for the target on the graph. Data association is subsequently used to route future measurements to update the likelihood ratio tracker (for undetected target) or to update a position probability (a previously detected target). Three strategies for motion planning of UAVs are proposed to balance searching for new targets with tracking known targets for a variety of scenarios. Performance was tested in Monte Carlo simulations for a variety of mission parameters, including tracking on road networks with varying complexity and using UAVs at various altitudes.

  5. Development and field application of a nonlinear ultrasonic modulation technique for fatigue crack detection without reference data from an intact condition

    NASA Astrophysics Data System (ADS)

    Lim, Hyung Jin; Kim, Yongtak; Koo, Gunhee; Yang, Suyoung; Sohn, Hoon; Bae, In-hwan; Jang, Jeong-Hwan

    2016-09-01

    In this study, a fatigue crack detection technique, which detects a fatigue crack without relying on any reference data obtained from the intact condition of a target structure, is developed using nonlinear ultrasonic modulation and applied to a real bridge structure. Using two wafer-type lead zirconate titanate (PZT) transducers, ultrasonic excitations at two distinctive frequencies are applied to a target inspection spot and the corresponding ultrasonic response is measured by another PZT transducer. Then, the nonlinear modulation components produced by a breathing-crack are extracted from the measured ultrasonic response, and a statistical classifier, which can determine if the nonlinear modulation components are statistically significant in comparison with the background noise level, is proposed. The effectiveness of the proposed fatigue crack detection technique is experimentally validated using the data obtained from aluminum plates and aircraft fitting-lug specimens under varying temperature and loading conditions, and through a field testing of Yeongjong Grand Bridge in South Korea. The uniqueness of this study lies in that (1) detection of a micro fatigue crack with less than 1 μm width and fatigue cracks in the range of 10-20 μm in width using nonlinear ultrasonic modulation, (2) automated detection of fatigue crack formation without using reference data obtained from an intact condition, (3) reliable and robust diagnosis under varying temperature and loading conditions, (4) application of a local fatigue crack detection technique to online monitoring of a real bridge.

  6. Experiments on Adaptive Techniques for Host-Based Intrusion Detection

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

    DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.

    2001-09-01

    This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerablemore » preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.« less

  7. Method of detecting luminescent target ions with modified magnetic microspheres

    DOEpatents

    Shkrob, Ilya A; Kaminski, Michael D

    2014-05-13

    This invention provides methods of using modified magnetic microspheres to extract target ions from a sample in order to detect their presence in a microfluidic environment. In one or more embodiments, the microspheres are modified with molecules on the surface that allow the target ions in the sample to form complexes with specific ligand molecules on the microsphere surface. In one or more embodiments, the microspheres are modified with molecules that sequester the target ions from the sample, but specific ligand molecules in solution subsequently re-extract the target ions from the microspheres into the solution, where the complexes form independent of the microsphere surface. Once the complexes form, they are exposed to an excitation wavelength light source suitable for exciting the target ion to emit a luminescent signal pattern. Detection of the luminescent signal pattern allows for determination of the presence of the target ions in the sample.

  8. Remote sensing image ship target detection method based on visual attention model

    NASA Astrophysics Data System (ADS)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  9. The detection of bulk explosives using nuclear-based techniques

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

    Morgado, R.E.; Gozani, T.; Seher, C.C.

    1988-01-01

    In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals;more » new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.« less

  10. The influence of the earth radiation on space target detection system

    NASA Astrophysics Data System (ADS)

    Su, Xiaofeng; Chen, FanSheng; Cuikun, .; Liuyan, .

    2017-05-01

    In the view of space remote sensing such as satellite detection space debris detection etc. visible band is usually used in order to have the all-weather detection capability, long wavelength infrared (LWIR) detection is also an important supplement. However, in the tow wave band, the earth can be a very strong interference source, especially in the dim target detecting. When the target is close to the earth, especially the LEO target, the background radiation of the earth will also enter into the baffle, and became the stray light through reflection, the stray light can reduce the signal to clutter ratio (SCR) of the target and make it difficult to be detected. In the visible band, the solar albedo by the earth is the main clutter source while in the LWIR band the radiation of the earth is the main clutter source. So, in this paper, we establish the energy transformation from the earth background radiation to the detection system to assess the effects of the stray light. Firstly, we discretize the surface of the earth to different unit, and using MODTRAN to calculate the radiation of the discrete point in different light and climate conditions, then, we integral all the radiation which can reach the baffle in the same observation angles to get the energy distribution, finally, according the target energy and the non-uniformity of the detector, we can calculate the design requirement of the system stray light suppression, which provides the design basis for the optical system.

  11. Real Time Intelligent Target Detection and Analysis with Machine Vision

    NASA Technical Reports Server (NTRS)

    Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

    2000-01-01

    We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

  12. Attention to baseline: does orienting visuospatial attention really facilitate target detection?

    PubMed

    Albares, Marion; Criaud, Marion; Wardak, Claire; Nguyen, Song Chi Trung; Ben Hamed, Suliann; Boulinguez, Philippe

    2011-08-01

    Standard protocols testing the orientation of visuospatial attention usually present spatial cues before targets and compare valid-cue trials with invalid-cue trials. The valid/invalid contrast results in a relative behavioral or physiological difference that is generally interpreted as a benefit of attention orientation. However, growing evidence suggests that inhibitory control of response is closely involved in this kind of protocol that requires the subjects to withhold automatic responses to cues, probably biasing behavioral and physiological baselines. Here, we used two experiments to disentangle the inhibitory control of automatic responses from orienting of visuospatial attention in a saccadic reaction time task in humans, a variant of the classical cue-target detection task and a sustained visuospatial attentional task. Surprisingly, when referring to a simple target detection task in which there is no need to refrain from reacting to avoid inappropriate responses, we found no consistent evidence of facilitation of target detection at the attended location. Instead, we observed a cost at the unattended location. Departing from the classical view, our results suggest that reaction time measures of visuospatial attention probably relie on the attenuation of elementary processes involved in visual target detection and saccade initiation away from the attended location rather than on facilitation at the attended location. This highlights the need to use proper control conditions in experimental designs to disambiguate relative from absolute cueing benefits on target detection reaction times, both in psychophysical and neurophysiological studies.

  13. Visual performance on detection tasks with double-targets of the same and different difficulty.

    PubMed

    Chan, Alan H S; Courtney, Alan J; Ma, C W

    2002-10-20

    This paper reports a study of measurement of horizontal visual sensitivity limits for 16 subjects in single-target and double-targets detection tasks. Two phases of tests were conducted in the double-targets task; targets of the same difficulty were tested in phase one while targets of different difficulty were tested in phase two. The range of sensitivity for the double-targets test was found to be smaller than that for single-target in both the same and different target difficulty cases. The presence of another target was found to affect performance to a marked degree. Interference effect of the difficult target on detection of the easy one was greater than that of the easy one on the detection of the difficult one. Performance decrement was noted when correct percentage detection was plotted against eccentricity of target in both the single-target and double-targets tests. Nevertheless, the non-significant correlation found between the performance for the two tasks demonstrated that it was impossible to predict quantitatively ability for detection of double targets from the data for single targets. This indicated probable problems in generalizing data for single target visual lobes to those for multiple targets. Also lobe area values obtained from measurements using a single-target task cannot be applied in a mathematical model for situations with multiple occurrences of targets.

  14. Search Radar Track-Before-Detect Using the Hough Transform.

    DTIC Science & Technology

    1995-03-01

    before - detect processing method which allows previous data to help in target detection. The technique provides many advantages compared to...improved target detection scheme, applicable to search radars, using the Hough transform image processing technique. The system concept involves a track

  15. Techniques for fire detection

    NASA Technical Reports Server (NTRS)

    Bukowski, Richard W.

    1987-01-01

    An overview is given of the basis for an analysis of combustable materials and potential ignition sources in a spacecraft. First, the burning process is discussed in terms of the production of the fire signatures normally associated with detection devices. These include convected and radiated thermal energy, particulates, and gases. Second, the transport processes associated with the movement of these from the fire to the detector, along with the important phenomena which cause the level of these signatures to be reduced, are described. Third, the operating characteristics of the individual types of detectors which influence their response to signals, are presented. Finally, vulnerability analysis using predictive fire modeling techniques is discussed as a means to establish the necessary response of the detection system to provide the level of protection required in the application.

  16. Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces

    NASA Technical Reports Server (NTRS)

    Sabol, Donald E., Jr.; Adams, John B.; Smith, Milton O.

    1992-01-01

    The conditions that affect the spectral detection of target materials at the subpixel scale are examined. Two levels of spectral mixture analysis for determining threshold detection limits of target materials in a spectral mixture are presented, the cases where the target is detected as: (1) a component of a spectral mixture (continuum threshold analysis) and (2) residuals (residual threshold analysis). The results of these two analyses are compared under various measurement conditions. The examples illustrate the general approach that can be used for evaluating the spectral detectability of terrestrial and planetary targets at the subpixel scale.

  17. A particle filter for multi-target tracking in track before detect context

    NASA Astrophysics Data System (ADS)

    Amrouche, Naima; Khenchaf, Ali; Berkani, Daoud

    2016-10-01

    The track-before-detect (TBD) approach can be used to track a single target in a highly noisy radar scene. This is because it makes use of unthresholded observations and incorporates a binary target existence variable into its target state estimation process when implemented as a particle filter (PF). This paper proposes the recursive PF-TBD approach to detect multiple targets in low-signal-to noise ratios (SNR). The algorithm's successful performance is demonstrated using a simulated two target example.

  18. Space moving target detection and tracking method in complex background

    NASA Astrophysics Data System (ADS)

    Lv, Ping-Yue; Sun, Sheng-Li; Lin, Chang-Qing; Liu, Gao-Rui

    2018-06-01

    The background of the space-borne detectors in real space-based environment is extremely complex and the signal-to-clutter ratio is very low (SCR ≈ 1), which increases the difficulty for detecting space moving targets. In order to solve this problem, an algorithm combining background suppression processing based on two-dimensional least mean square filter (TDLMS) and target enhancement based on neighborhood gray-scale difference (GSD) is proposed in this paper. The latter can filter out most of the residual background clutter processed by the former such as cloud edge. Through this procedure, both global and local SCR have obtained substantial improvement, indicating that the target has been greatly enhanced. After removing the detector's inherent clutter region through connected domain processing, the image only contains the target point and the isolated noise, in which the isolated noise could be filtered out effectively through multi-frame association. The proposed algorithm in this paper has been compared with some state-of-the-art algorithms for moving target detection and tracking tasks. The experimental results show that the performance of this algorithm is the best in terms of SCR gain, background suppression factor (BSF) and detection results.

  19. Target vessel detection by epicardial ultrasound in off-pump coronary bypass surgery.

    PubMed

    Hayakawa, Masato; Asai, Tohru; Kinoshita, Takeshi; Suzuki, Tomoaki; Shiraishi, Shoichiro

    2013-01-01

    The detection of embedded coronary arteries is difficult especially in off-pump coronary bypass surgery. From June 2010, we introduced high-frequency epicardial ultrasound (ECUS) to assess and evaluate embedded arteries during off-pump coronary bypass surgery. Between June 2010 and June 2011, a total of 89 consecutive patients underwent isolated coronary bypass surgery at our institution. The patients consisted of 72 men and 17 women with a mean age of 67.9 years. We routinely use the VeriQC system (MediStim, Oslo, Norway) to detect the target vessels in the operation. The patients were assigned to one of two groups, depending on whether ECUS was used in the operation (n = 10, ECUS group) or not (n = 79, non-ECUS group). We analyzed the impact of introducing the ECUS in terms of operative outcome. All patients underwent revascularization using the off-pump technique without emergent conversion to cardiopulmonary bypass during surgery. The total number of distal anastomoses was 299, and 12 target vessels could not be identified either visually or on palpation. Thus, the frequency of the embedded coronary arteries was 4.01% (12/299 cases). The preoperative profiles of the two groups were not significantly different. Operation time was significantly longer in the ECUS group (P = 0.02). There were no significant differences in postoperative outcome between the two groups. In the present study, in which the target coronary arteries could not be detected either visually or on palpation in 12 (4.01%) of 299 cases, the use of high-frequency ECUS allowed all patients to undergo off-pump coronary bypass surgery without conversion to cardiopulmonary bypass during the operation. High-frequency ECUS is therefore useful in off-pump coronary bypass surgery.

  20. Differential Sources for 2 Neural Signatures of Target Detection: An Electrocorticography Study.

    PubMed

    Kam, J W Y; Szczepanski, S M; Canolty, R T; Flinker, A; Auguste, K I; Crone, N E; Kirsch, H E; Kuperman, R A; Lin, J J; Parvizi, J; Knight, R T

    2018-01-01

    Electrophysiology and neuroimaging provide conflicting evidence for the neural contributions to target detection. Scalp electroencephalography (EEG) studies localize the P3b event-related potential component mainly to parietal cortex, whereas neuroimaging studies report activations in both frontal and parietal cortices. We addressed this discrepancy by examining the sources that generate the target-detection process using electrocorticography (ECoG). We recorded ECoG activity from cortex in 14 patients undergoing epilepsy monitoring, as they performed an auditory or visual target-detection task. We examined target-related responses in 2 domains: high frequency band (HFB) activity and the P3b. Across tasks, we observed a greater proportion of electrodes that showed target-specific HFB power relative to P3b over frontal cortex, but their proportions over parietal cortex were comparable. Notably, there was minimal overlap in the electrodes that showed target-specific HFB and P3b activity. These results revealed that the target-detection process is characterized by at least 2 different neural markers with distinct cortical distributions. Our findings suggest that separate neural mechanisms are driving the differential patterns of activity observed in scalp EEG and neuroimaging studies, with the P3b reflecting EEG findings and HFB activity reflecting neuroimaging findings, highlighting the notion that target detection is not a unitary phenomenon. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Research on Aircraft Target Detection Algorithm Based on Improved Radial Gradient Transformation

    NASA Astrophysics Data System (ADS)

    Zhao, Z. M.; Gao, X. M.; Jiang, D. N.; Zhang, Y. Q.

    2018-04-01

    Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied, and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.

  2. Joint detection and tracking of size-varying infrared targets based on block-wise sparse decomposition

    NASA Astrophysics Data System (ADS)

    Li, Miao; Lin, Zaiping; Long, Yunli; An, Wei; Zhou, Yiyu

    2016-05-01

    The high variability of target size makes small target detection in Infrared Search and Track (IRST) a challenging task. A joint detection and tracking method based on block-wise sparse decomposition is proposed to address this problem. For detection, the infrared image is divided into overlapped blocks, and each block is weighted on the local image complexity and target existence probabilities. Target-background decomposition is solved by block-wise inexact augmented Lagrange multipliers. For tracking, label multi-Bernoulli (LMB) tracker tracks multiple targets taking the result of single-frame detection as input, and provides corresponding target existence probabilities for detection. Unlike fixed-size methods, the proposed method can accommodate size-varying targets, due to no special assumption for the size and shape of small targets. Because of exact decomposition, classical target measurements are extended and additional direction information is provided to improve tracking performance. The experimental results show that the proposed method can effectively suppress background clutters, detect and track size-varying targets in infrared images.

  3. Development of a qualitative real-time PCR method to detect 19 targets for identification of genetically modified organisms.

    PubMed

    Peng, Cheng; Wang, Pengfei; Xu, Xiaoli; Wang, Xiaofu; Wei, Wei; Chen, Xiaoyun; Xu, Junfeng

    2016-01-01

    As the amount of commercially available genetically modified organisms (GMOs) grows recent years, the diversity of target sequences for molecular detection techniques are eagerly needed. Considered as the gold standard for GMO analysis, the real-time PCR technology was optimized to produce a high-throughput GMO screening method. With this method we can detect 19 transgenic targets. The specificity of the assays was demonstrated to be 100 % by the specific amplification of DNA derived from reference material from 20 genetically modified crops and 4 non modified crops. Furthermore, most assays showed a very sensitive detection, reaching the limit of ten copies. The 19 assays are the most frequently used genetic elements present in GM crops and theoretically enable the screening of the known GMO described in Chinese markets. Easy to use, fast and cost efficient, this method approach fits the purpose of GMO testing laboratories.

  4. Time-Resolved Spectroscopy and Near Infrared Imaging for Prostate Cancer Detection: Receptor-targeted and Native Biomarker

    NASA Astrophysics Data System (ADS)

    Pu, Yang

    Optical spectroscopy and imaging using near-infrared (NIR) light provides powerful tools for non-invasive detection of cancer in tissue. Optical techniques are capable of quantitative reconstructions maps of tissue absorption and scattering properties, thus can map in vivo the differences in the content of certain marker chromophores and/or fluorophores in normal and cancerous tissues (for example: water, tryptophan, collagen and NADH contents). Potential clinical applications of optical spectroscopy and imaging include functional tumor detection and photothermal therapeutics. Optical spectroscopy and imaging apply contrasts from intrinsic tissue chromophores such as water, collagen and NADH, and extrinsic optical contrast agents such as Indocyanine Green (ICG) to distinguish disease tissue from the normal one. Fluorescence spectroscopy and imaging also gives high sensitivity and specificity for biomedical diagnosis. Recent developments on specific-targeting fluorophores such as small receptor-targeted dye-peptide conjugate contrast agent offer high contrast between normal and cancerous tissues hence provide promising future for early tumour detection. This thesis focus on a study to distinguish the cancerous prostate tissue from the normal prostate tissues with enhancement of specific receptor-targeted prostate cancer contrast agents using optical spectroscopy and imaging techniques. The scattering and absorption coefficients, and anisotropy factor of cancerous and normal prostate tissues were investigated first as the basis for the biomedical diagnostic and optical imaging. Understanding the receptors over-expressed prostate cancer cells and molecular target mechanism of ligand, two small ICG-derivative dye-peptides, namely Cypate-Bombesin Peptide Analogue Conjugate (Cybesin) and Cypate-Octreotate Peptide Conjugate (Cytate), were applied to study their clinical potential for human prostate cancer detection. In this work, the steady-state and time

  5. Technique for measurement of energy loss of proton in target medium

    NASA Astrophysics Data System (ADS)

    Khadke, U. V.

    2018-05-01

    Energy loss (EL) of charged particles in target medium needs special attention, when measurements are required to be done repeatedly over periods of couple of days. It is imperative to ensure that the measurements are not affected by the long term drifts of the accelerator beam energy and the associated electronic modules. For one such situation in measurement of EL of proton beam in thick target, we optimised and standardized the technique of measuring most probable energy loss of 24.774 MeV proton in aluminium target of thickness 330 mg/cm2. The paper described the method that we developed to ensure that our EL measurements were free from effects of drifts due to any associated electronic modules. The details of the energy spectrometer, basic principle and technique for energy loss measurements in target medium are described in this paper.

  6. Detection of Marine Radar Targets

    NASA Astrophysics Data System (ADS)

    Briggs, John N.

    A radar must detect targets before it can display them. Yet manufacturers' data sheets rarely tell us what the products will detect at what range. Many of the bigger radars are Type Approved so we consult the relevant IMO performance standard A 477 (XII). Paraphrasing Section 3.1 of the draft forthcoming revision (NAV 41/6): under normal propagation conditions with the scanner at height of 15 m, in the absence of clutter, the radar is required to give clear indication of an object such as a navigational buoy having a radar cross section area (RCS) of 10 m2 at 2 n.m. and, as examples, coastlines whose ground rises to 60/6 m at ranges of 20/7 n.m., a ship of 5000 tons at any aspect at 7 n.m. and a small vessel 10 m long at 3 n.m.This helps, but suppose we must pick up a 5 m2 buoy at g km? What happens in clutter? Should we prefer S- or X-band? To answer such questions we use equations which define the performance of surveillance radars, but the textbooks and specialist papers containing them often generalize with aeronautical and defence topics, making life difficult for the nonspecialist.This paper attempts a concise and self-contained engineering account of all main factors affecting detection of passive and active targets on civil marine and vessel traffic service (VTS) radars. We develop a set of equations for X- and S-band (3 and 10 cm, centred on 9400 and 3000 MHz respectively), suited for spreadsheet calculation.Sufficient theory is sketched in to indicate where results should be valid. Some simplifications of conventional treatments have been identified.

  7. Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

    PubMed Central

    Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.

    2016-01-01

    Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709

  8. Signal analysis techniques for incipient failure detection in turbomachinery

    NASA Technical Reports Server (NTRS)

    Coffin, T.

    1985-01-01

    Signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery were developed, implemented and evaluated. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques were implemented on a computer and applied to dynamic signals. A laboratory evaluation of the methods with respect to signal detection capability is described. Plans for further technique evaluation and data base development to characterize turbopump incipient failure modes from Space Shuttle main engine (SSME) hot firing measurements are outlined.

  9. Detection and tracking of a moving target using SAR images with the particle filter-based track-before-detect algorithm.

    PubMed

    Gao, Han; Li, Jingwen

    2014-06-19

    A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB.

  10. Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

    PubMed Central

    Gao, Han; Li, Jingwen

    2014-01-01

    A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. PMID:24949640

  11. In-situ vacuum deposition technique of lithium on neutron production target for BNCT

    NASA Astrophysics Data System (ADS)

    Ishiyama, S.; Baba, Y.; Fujii, R.; Nakamura, M.; Imahori, Y.

    2012-10-01

    For the purpose of avoiding the radiation blistering of the lithium target for neutron production in BNCT (Boron Neutron Capture Therapy) device, trilaminar Li target, of which palladium thin layer was inserted between cupper substrate and Li layer, was newly designed. In-situ vacuum deposition and electrolytic coating techniques were applied to validate the method of fabrication of the Li/Pd/Cu target, and the layered structures of the synthesized target were characterized. In-situ vacuum re-deposition technique was also established for repairing and maintenance for lithium target damaged. Following conclusions were derived; (1) Uniform lithium layers with the thickness from 1.6 nm to a few hundreds nanometer were formed on Pd/Cu multilayer surface by in situ vacuum deposition technique using metallic lithium as a source material. (2) Re-deposition of lithium layer on Li surface can be achieved by in situ vacuum deposition technique. (3) Small amount of water and carbonate was observed on the top surface of Li. But the thickness of the adsorbed layer was less than monolayer, which will not affect the quality of the Li target. (4) The formation of Pd-Li alloy layer was observed at the Pd and Li interface. The alloy layer would contribute to the stability of the Li layer.

  12. Right hemisphere dominance during spatial selective attention and target detection occurs outside the dorsal fronto-parietal network

    PubMed Central

    Shulman, Gordon L.; Pope, Daniel L. W.; Astafiev, Serguei V.; McAvoy, Mark P.; Snyder, Abraham Z.; Corbetta, Maurizio

    2010-01-01

    Spatial selective attention is widely considered to be right hemisphere dominant. Previous functional magnetic resonance imaging (fMRI) studies, however, have reported bilateral blood-oxygenation-level-dependent (BOLD) responses in dorsal fronto-parietal regions during anticipatory shifts of attention to a location (Kastner et al., 1999; Corbetta et al., 2000; Hopfinger et al., 2000). Right-lateralized activity has mainly been reported in ventral fronto-parietal regions for shifts of attention to an unattended target stimulus (Arrington et al., 2000; Corbetta et al., 2000). However, clear conclusions cannot be drawn from these studies because hemispheric asymmetries were not assessed using direct voxel-wise comparisons of activity in left and right hemispheres. Here, we used this technique to measure hemispheric asymmetries during shifts of spatial attention evoked by a peripheral cue stimulus and during target detection at the cued location. Stimulus-driven shifts of spatial attention in both visual fields evoked right-hemisphere dominant activity in temporo-parietal junction (TPJ). Target detection at the attended location produced a more widespread right hemisphere dominance in frontal, parietal, and temporal cortex, including the TPJ region asymmetrically activated during shifts of spatial attention. However, hemispheric asymmetries were not observed during either shifts of attention or target detection in the dorsal fronto-parietal regions (anterior precuneus, medial intraparietal sulcus, frontal eye fields) that showed the most robust activations for shifts of attention. Therefore, right hemisphere dominance during stimulus-driven shifts of spatial attention and target detection reflects asymmetries in cortical regions that are largely distinct from the dorsal fronto-parietal network involved in the control of selective attention. PMID:20219998

  13. Sea-Based Infrared Scene Interpretation by Background Type Classification and Coastal Region Detection for Small Target Detection

    PubMed Central

    Kim, Sungho

    2015-01-01

    Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection. PMID:26404308

  14. Direct detection of RNA in vitro and in situ by target-primed RCA: The impact of E. coli RNase III on the detection efficiency of RNA sequences distanced far from the 3'-end.

    PubMed

    Merkiene, Egle; Gaidamaviciute, Edita; Riauba, Laurynas; Janulaitis, Arvydas; Lagunavicius, Arunas

    2010-08-01

    We improved the target RNA-primed RCA technique for direct detection and analysis of RNA in vitro and in situ. Previously we showed that the 3' --> 5' single-stranded RNA exonucleolytic activity of Phi29 DNA polymerase converts the target RNA into a primer and uses it for RCA initiation. However, in some cases, the single-stranded RNA exoribonucleolytic activity of the polymerase is hindered by strong double-stranded structures at the 3'-end of target RNAs. We demonstrate that in such hampered cases, the double-stranded RNA-specific Escherichia coli RNase III efficiently assists Phi29 DNA polymerase in converting the target RNA into a primer. These observations extend the target RNA-primed RCA possibilities to test RNA sequences distanced far from the 3'-end and customize this technique for the inner RNA sequence analysis.

  15. NONDESTRUCTIVE TESTING (NDT) TECHNIQUES TO DETECT CONTAINED SUBSURFACE HAZARDOUS WASTE

    EPA Science Inventory

    The project involves the detection of buried containers with NDT (remote-sensing) techniques. Seventeen techniques were considered and four were ultimately decided upon. They were: electromagnetic induction (EMI); metal detection (MD); magnetometer (MAG); and ground penetrating r...

  16. Flood Detection/Monitoring Using Adjustable Histogram Equalization Technique

    PubMed Central

    Riaz, Muhammad Mohsin; Ghafoor, Abdul

    2014-01-01

    Flood monitoring technique using adjustable histogram equalization is proposed. The technique overcomes the limitations (overenhancement, artifacts, and unnatural look) of existing technique by adjusting the contrast of images. The proposed technique takes pre- and postimages and applies different processing steps for generating flood map without user interaction. The resultant flood maps can be used for flood monitoring and detection. Simulation results show that the proposed technique provides better output quality compared to the state of the art existing technique. PMID:24558332

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  18. Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

    DTIC Science & Technology

    2010-11-01

    pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

  19. Point target detection utilizing super-resolution strategy for infrared scanning oversampling system

    NASA Astrophysics Data System (ADS)

    Wang, Longguang; Lin, Zaiping; Deng, Xinpu; An, Wei

    2017-11-01

    To improve the resolution of remote sensing infrared images, infrared scanning oversampling system is employed with information amount quadrupled, which contributes to the target detection. Generally the image data from double-line detector of infrared scanning oversampling system is shuffled to a whole oversampled image to be post-processed, whereas the aliasing between neighboring pixels leads to image degradation with a great impact on target detection. This paper formulates a point target detection method utilizing super-resolution (SR) strategy concerning infrared scanning oversampling system, with an accelerated SR strategy proposed to realize fast de-aliasing of the oversampled image and an adaptive MRF-based regularization designed to achieve the preserving and aggregation of target energy. Extensive experiments demonstrate the superior detection performance, robustness and efficiency of the proposed method compared with other state-of-the-art approaches.

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  1. Detection of multiple airborne targets from multisensor data

    NASA Astrophysics Data System (ADS)

    Foltz, Mark A.; Srivastava, Anuj; Miller, Michael I.; Grenander, Ulf

    1995-08-01

    Previously we presented a jump-diffusion based random sampling algorithm for generating conditional mean estimates of scene representations for the tracking and recongition of maneuvering airborne targets. These representations include target positions and orientations along their trajectories and the target type associated with each trajectory. Taking a Bayesian approach, a posterior measure is defined on the parameter space by combining sensor models with a sophisticated prior based on nonlinear airplane dynamics. The jump-diffusion algorithm constructs a Markov process which visits the elements of the parameter space with frequencies proportional to the posterior probability. It consititutes both the infinitesimal, local search via a sample path continuous diffusion transform and the larger, global steps through discrete jump moves. The jump moves involve the addition and deletion of elements from the scene configuration or changes in the target type assoviated with each target trajectory. One such move results in target detection by the addition of a track seed to the inference set. This provides initial track data for the tracking/recognition algorithm to estimate linear graph structures representing tracks using the other jump moves and the diffusion process, as described in our earlier work. Target detection ideally involves a continuous research over a continuum of the observation space. In this work we conclude that for practical implemenations the search space must be discretized with lattice granularity comparable to sensor resolution, and discuss how fast Fourier transforms are utilized for efficient calcuation of sufficient statistics given our array models. Some results are also presented from our implementation on a networked system including a massively parallel machine architecture and a silicon graphics onyx workstation.

  2. A Parallel Finite Set Statistical Simulator for Multi-Target Detection and Tracking

    NASA Astrophysics Data System (ADS)

    Hussein, I.; MacMillan, R.

    2014-09-01

    Finite Set Statistics (FISST) is a powerful Bayesian inference tool for the joint detection, classification and tracking of multi-target environments. FISST is capable of handling phenomena such as clutter, misdetections, and target birth and decay. Implicit within the approach are solutions to the data association and target label-tracking problems. Finally, FISST provides generalized information measures that can be used for sensor allocation across different types of tasks such as: searching for new targets, and classification and tracking of known targets. These FISST capabilities have been demonstrated on several small-scale illustrative examples. However, for implementation in a large-scale system as in the Space Situational Awareness problem, these capabilities require a lot of computational power. In this paper, we implement FISST in a parallel environment for the joint detection and tracking of multi-target systems. In this implementation, false alarms and misdetections will be modeled. Target birth and decay will not be modeled in the present paper. We will demonstrate the success of the method for as many targets as we possibly can in a desktop parallel environment. Performance measures will include: number of targets in the simulation, certainty of detected target tracks, computational time as a function of clutter returns and number of targets, among other factors.

  3. High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

    PubMed

    Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

    2012-01-01

    The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

  4. RNase H-assisted RNA-primed rolling circle amplification for targeted RNA sequence detection.

    PubMed

    Takahashi, Hirokazu; Ohkawachi, Masahiko; Horio, Kyohei; Kobori, Toshiro; Aki, Tsunehiro; Matsumura, Yukihiko; Nakashimada, Yutaka; Okamura, Yoshiko

    2018-05-17

    RNA-primed rolling circle amplification (RPRCA) is a useful laboratory method for RNA detection; however, the detection of RNA is limited by the lack of information on 3'-terminal sequences. We uncovered that conventional RPRCA using pre-circularized probes could potentially detect the internal sequence of target RNA molecules in combination with RNase H. However, the specificity for mRNA detection was low, presumably due to non-specific hybridization of non-target RNA with the circular probe. To overcome this technical problem, we developed a method for detecting a sequence of interest in target RNA molecules via RNase H-assisted RPRCA using padlocked probes. When padlock probes are hybridized to the target RNA molecule, they are converted to the circular form by SplintR ligase. Subsequently, RNase H creates nick sites only in the hybridized RNA sequence, and single-stranded DNA is finally synthesized from the nick site by phi29 DNA polymerase. This method could specifically detect at least 10 fmol of the target RNA molecule without reverse transcription. Moreover, this method detected GFP mRNA present in 10 ng of total RNA isolated from Escherichia coli without background DNA amplification. Therefore, this method can potentially detect almost all types of RNA molecules without reverse transcription and reveal full-length sequence information.

  5. Computational optimisation of targeted DNA sequencing for cancer detection

    NASA Astrophysics Data System (ADS)

    Martinez, Pierre; McGranahan, Nicholas; Birkbak, Nicolai Juul; Gerlinger, Marco; Swanton, Charles

    2013-12-01

    Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing circulating tumour DNA (ctDNA) might represent a non-invasive method to detect mutations in patients, facilitating early detection. In this article, we define reduced gene panels from publicly available datasets as a first step to assess and optimise the potential of targeted ctDNA scans for early tumour detection. Dividing 4,467 samples into one discovery and two independent validation cohorts, we show that up to 76% of 10 cancer types harbour at least one mutation in a panel of only 25 genes, with high sensitivity across most tumour types. Our analyses demonstrate that targeting ``hotspot'' regions would introduce biases towards in-frame mutations and would compromise the reproducibility of tumour detection.

  6. Targeted Metabolomics Approach To Detect the Misuse of Steroidal Aromatase Inhibitors in Equine Sports by Biomarker Profiling.

    PubMed

    Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming

    2016-01-05

    The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups

  7. Characterization of image heterogeneity using 2D Minkowski functionals increases the sensitivity of detection of a targeted MRI contrast agent.

    PubMed

    Canuto, Holly C; McLachlan, Charles; Kettunen, Mikko I; Velic, Marko; Krishnan, Anant S; Neves, Andre' A; de Backer, Maaike; Hu, D-E; Hobson, Michael P; Brindle, Kevin M

    2009-05-01

    A targeted Gd(3+)-based contrast agent has been developed that detects tumor cell death by binding to the phosphatidylserine (PS) exposed on the plasma membrane of dying cells. Although this agent has been used to detect tumor cell death in vivo, the differences in signal intensity between treated and untreated tumors was relatively small. As cell death is often spatially heterogeneous within tumors, we investigated whether an image analysis technique that parameterizes heterogeneity could be used to increase the sensitivity of detection of this targeted contrast agent. Two-dimensional (2D) Minkowski functionals (MFs) provided an automated and reliable method for parameterization of image heterogeneity, which does not require prior assumptions about the number of regions or features in the image, and were shown to increase the sensitivity of detection of the contrast agent as compared to simple signal intensity analysis. (c) 2009 Wiley-Liss, Inc.

  8. Microwave Technique for Detecting and Locating Concealed Weapons

    DOT National Transportation Integrated Search

    1971-12-01

    The subject of this report is the evaluation of a microwave technique for detecting and locating weapons concealed under clothing. The principal features of this technique are: persons subjected to search are not exposed to 'objectional' microwave ra...

  9. Analysis of Infrared Signature Variation and Robust Filter-Based Supersonic Target Detection

    PubMed Central

    Sun, Sun-Gu; Kim, Kyung-Tae

    2014-01-01

    The difficulty of small infrared target detection originates from the variations of infrared signatures. This paper presents the fundamental physics of infrared target variations and reports the results of variation analysis of infrared images acquired using a long wave infrared camera over a 24-hour period for different types of backgrounds. The detection parameters, such as signal-to-clutter ratio were compared according to the recording time, temperature and humidity. Through variation analysis, robust target detection methodologies are derived by controlling thresholds and designing a temporal contrast filter to achieve high detection rate and low false alarm rate. Experimental results validate the robustness of the proposed scheme by applying it to the synthetic and real infrared sequences. PMID:24672290

  10. Moving target detection method based on improved Gaussian mixture model

    NASA Astrophysics Data System (ADS)

    Ma, J. Y.; Jie, F. R.; Hu, Y. J.

    2017-07-01

    Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

  11. A new imaging technique to detect recurrent prostate cancer is tested in new clinical trial | Center for Cancer Research

    Cancer.gov

    Standard imaging techniques cannot accurately locate sites of prostate cancer metastasis. The use of 18F-DCFPyL, a second-generation PET agent, aims to improve doctors’ ability to assess high-risk primary tumors, detect sites of recurrent prostate cancer and target therapies to specific sites of recurrence. Read more...

  12. Adaptive early detection ML/PDA estimator for LO targets with EO sensors

    NASA Astrophysics Data System (ADS)

    Chummun, Muhammad R.; Kirubarajan, Thiagalingam; Bar-Shalom, Yaakov

    2000-07-01

    The batch Maximum Likelihood Estimator, combined with Probabilistic Data (ML-PDA), has been shown to be effective in acquiring low observable (LO) - low SNR - non-maneuvering targets in the presence of heavy clutter. The use of signal strength or amplitude information (AI) in the ML-PDA estimator with AI in a sliding-window fashion, to detect high- speed targets in heavy clutter using electro-optical (EO) sensors. The initial time and the length of the sliding-window are adjusted adaptively according to the information content of the received measurements. A track validation scheme via hypothesis testing is developed to confirm the estimated track, that is, the presence of a target, in each window. The sliding-window ML-PDA approach, together with track validation, enables early detection by rejecting noninformative scans, target reacquisition in case of temporary target disappearance and the handling of targets with speeds evolving over time. The proposed algorithm is shown to detect the target, which is hidden in as many as 600 false alarms per scan, 10 frames earlier than the Multiple Hypothesis Tracking (MHT) algorithm.

  13. Research on infrared dim-point target detection and tracking under sea-sky-line complex background

    NASA Astrophysics Data System (ADS)

    Dong, Yu-xing; Li, Yan; Zhang, Hai-bo

    2011-08-01

    Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system, the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties .There are some traditional point target detection algorithms, such as adaptive background prediction detecting method. When background has dispersion-decreasing structure, the traditional target detection algorithms would be more useful. But when the background has large gray gradient, such as sea-sky-line, sea waves etc .The bigger false-alarm rate will be taken in these local area .It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature ,in our opinion , from the perspective of mathematics, the detection of dim-point targets in image is about singular function analysis .And from the perspective image processing analysis , the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection, its essence is a separation of target and background of different singularity characteristics .The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore, the purpose of the image preprocessing is to reduce the effects from noise, also to raise the SNR of image, and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics , the median filter is used to

  14. Passive Coherent Detection and Target Location with Multiple Non-Cooperative Transmitters

    DTIC Science & Technology

    2015-06-01

    to detect, separate, classify, locate, and track sources of emissions in multi-target environments—triggered the development of passive radar...radar capitalizes on transmitters of opportunity to detect and locate sources of transmission or targets without deliberate emissions . The...equipment as all necessary hardware is currently available on most naval ships. 3 Bistatic radar geometry. Figure 1. B. HISTORY The concept of

  15. Optimization of prostate biopsy: the role of magnetic resonance imaging targeted biopsy in detection, localization and risk assessment.

    PubMed

    Bjurlin, Marc A; Meng, Xiaosong; Le Nobin, Julien; Wysock, James S; Lepor, Herbert; Rosenkrantz, Andrew B; Taneja, Samir S

    2014-09-01

    Optimization of prostate biopsy requires addressing the shortcomings of standard systematic transrectal ultrasound guided biopsy, including false-negative rates, incorrect risk stratification, detection of clinically insignificant disease and the need for repeat biopsy. Magnetic resonance imaging is an evolving noninvasive imaging modality that increases the accurate localization of prostate cancer at the time of biopsy, and thereby enhances clinical risk assessment and improves the ability to appropriately counsel patients regarding therapy. In this review we 1) summarize the various sequences that comprise a prostate multiparametric magnetic resonance imaging examination along with its performance characteristics in cancer detection, localization and reporting standards; 2) evaluate potential applications of magnetic resonance imaging targeting in prostate biopsy among men with no previous biopsy, a negative previous biopsy and those with low stage cancer; and 3) describe the techniques of magnetic resonance imaging targeted biopsy and comparative study outcomes. A bibliographic search covering the period up to October 2013 was conducted using MEDLINE®/PubMed®. Articles were reviewed and categorized based on which of the 3 objectives of this review was addressed. Data were extracted, analyzed and summarized. Multiparametric magnetic resonance imaging consists of anatomical T2-weighted imaging coupled with at least 2 functional imaging techniques. It has demonstrated improved prostate cancer detection sensitivity up to 80% in the peripheral zone and 81% in the transition zone. A prostate cancer magnetic resonance imaging suspicion score has been developed, and is depicted using the Likert or PI-RADS (Prostate Imaging Reporting and Data System) scale for better standardization of magnetic resonance imaging interpretation and reporting. Among men with no previous biopsy, magnetic resonance imaging increases the frequency of significant cancer detection to 50

  16. Tumor detection and elimination by a targeted gallium corrole

    PubMed Central

    Agadjanian, Hasmik; Ma, Jun; Rentsendorj, Altan; Valluripalli, Vinod; Hwang, Jae Youn; Mahammed, Atif; Farkas, Daniel L.; Gray, Harry B.; Gross, Zeev; Medina-Kauwe, Lali K.

    2009-01-01

    Sulfonated gallium(III) corroles are intensely fluorescent macrocyclic compounds that spontaneously assemble with carrier proteins to undergo cell entry. We report in vivo imaging and therapeutic efficacy of a tumor-targeted corrole noncovalently assembled with a heregulin-modified protein directed at the human epidermal growth factor receptor (HER). Systemic delivery of this protein-corrole complex results in tumor accumulation, which can be visualized in vivo owing to intensely red corrole fluorescence. Targeted delivery in vivo leads to tumor cell death while normal tissue is spared. These findings contrast with the effects of doxorubicin, which can elicit cardiac damage during therapy and required direct intratumoral injection to yield similar levels of tumor shrinkage compared with the systemically delivered corrole. The targeted complex ablated tumors at >5 times a lower dose than untargeted systemic doxorubicin, and the corrole did not damage heart tissue. Complexes remained intact in serum and the carrier protein elicited no detectable immunogenicity. The sulfonated gallium(III) corrole functions both for tumor detection and intervention with safety and targeting advantages over standard chemotherapeutic agents. PMID:19342490

  17. Detection of Fast Moving and Accelerating Targets Compensating Range and Doppler Migration

    DTIC Science & Technology

    2014-06-01

    Radon -Fourier transform has been introduced to realize long- term coherent integration of the moving targets with range migration [8, 9]. Radon ...2010) Long-time coherent integration for radar target detection base on Radon -Fourier transform, in Proceedings of the IEEE Radar Conference, pp...432–436. 9. Xu, J., Yu, J., Peng, Y. & Xia, X. (2011) Radon -Fourier transform for radar target detection, I: Generalized Doppler filter bank, IEEE

  18. Uranium Detection - Technique Validation Report

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

    Colletti, Lisa Michelle; Garduno, Katherine; Lujan, Elmer J.

    As a LANL activity for DOE/NNSA in support of SHINE Medical Technologies™ ‘Accelerator Technology’ we have been investigating the application of UV-vis spectroscopy for uranium analysis in solution. While the technique has been developed specifically for sulfate solutions, the proposed SHINE target solutions, it can be adapted to a range of different solution matrixes. The FY15 work scope incorporated technical development that would improve accuracy, specificity, linearity & range, precision & ruggedness, and comparative analysis. Significant progress was achieved throughout FY 15 addressing these technical challenges, as is summarized in this report. In addition, comparative analysis of unknown samples usingmore » the Davies-Gray titration technique highlighted the importance of controlling temperature during analysis (impacting both technique accuracy and linearity/range). To fully understand the impact of temperature, additional experimentation and data analyses were performed during FY16. The results from this FY15/FY16 work were presented in a detailed presentation, LA-UR-16-21310, and an update of this presentation is included with this short report summarizing the key findings. The technique is based on analysis of the most intense U(VI) absorbance band in the visible region of the uranium spectra in 1 M H 2SO 4, at λ max = 419.5 nm.« less

  19. Indoor detection of passive targets recast as an inverse scattering problem

    NASA Astrophysics Data System (ADS)

    Gottardi, G.; Moriyama, T.

    2017-10-01

    The wireless local area networks represent an alternative to custom sensors and dedicated surveillance systems for target indoor detection. The availability of the channel state information has opened the exploitation of the spatial and frequency diversity given by the orthogonal frequency division multiplexing. Such a fine-grained information can be used to solve the detection problem as an inverse scattering problem. The goal of the detection is to reconstruct the properties of the investigation domain, namely to estimate if the domain is empty or occupied by targets, starting from the measurement of the electromagnetic perturbation of the wireless channel. An innovative inversion strategy exploiting both the frequency and the spatial diversity of the channel state information is proposed. The target-dependent features are identified combining the Kruskal-Wallis test and the principal component analysis. The experimental validation points out the detection performance of the proposed method when applied to an existing wireless link of a WiFi architecture deployed in a real indoor scenario. False detection rates lower than 2 [%] have been obtained.

  20. Hierarchical effects on target detection and conflict monitoring

    PubMed Central

    Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong

    2016-01-01

    Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989

  1. Targets Mask U-Net for Wind Turbines Detection in Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Han, M.; Wang, H.; Wang, G.; Liu, Y.

    2018-04-01

    To detect wind turbines precisely and quickly in very high resolution remote sensing images (VHRRSI) we propose target mask U-Net. This convolution neural network (CNN), which is carefully designed to be a wide-field detector, models the pixel class assignment to wind turbines and their context information. The shadow, which is the context information of the target in this study, has been regarded as part of a wind turbine instance. We have trained the target mask U-Net on training dataset, which is composed of down sampled image blocks and instance mask blocks. Some post-processes have been integrated to eliminate wrong spots and produce bounding boxes of wind turbine instances. The evaluation metrics prove the reliability and effectiveness of our method for the average F1-score of our detection method is up to 0.97. The comparison of detection accuracy and time consuming with the weakly supervised targets detection method based on CNN illustrates the superiority of our method.

  2. An Underwater Target Detection System for Electro-Optical Imagery Data

    DTIC Science & Technology

    2010-06-01

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

  3. Salient target detection based on pseudo-Wigner-Ville distribution and Rényi entropy.

    PubMed

    Xu, Yuannan; Zhao, Yuan; Jin, Chenfei; Qu, Zengfeng; Liu, Liping; Sun, Xiudong

    2010-02-15

    We present what we believe to be a novel method based on pseudo-Wigner-Ville distribution (PWVD) and Rényi entropy for salient targets detection. In the foundation of studying the statistical property of Rényi entropy via PWVD, the residual entropy-based saliency map of an input image can be obtained. From the saliency map, target detection is completed by the simple and convenient threshold segmentation. Experimental results demonstrate the proposed method can detect targets effectively in complex ground scenes.

  4. Comparison of survey techniques on detection of northern flying squirrels

    USGS Publications Warehouse

    Diggins, Corinne A.; Gilley, L. Michelle; Kelly, Christine A.; Ford, W. Mark

    2016-01-01

    The ability to detect a species is central to the success of monitoring for conservation and management purposes, especially if the species is rare or endangered. Traditional methods, such as live capture, can be labor-intensive, invasive, and produce low detection rates. Technological advances and new approaches provide opportunities to more effectively survey for species both in terms of accuracy and efficiency than previous methods. We conducted a pilot comparison study of a traditional technique (live-trapping) and 2 novel noninvasive techniques (camera-trapping and ultrasonic acoustic surveys) on detection rates of the federally endangered Carolina northern flying squirrel (Glaucomys sabrinus coloratus) in occupied habitat within the Roan Mountain Highlands of North Carolina, USA. In 2015, we established 3 5 × 5 live-trapping grids (6.5 ha) with 4 camera traps and 4 acoustic detectors systematically embedded in each grid. All 3 techniques were used simultaneously during 2 4-day survey periods. We compared techniques by assessing probability of detection (POD), latency to detection (LTD; i.e., no. of survey nights until initial detection), and survey effort. Acoustics had the greatest POD (0.37 ± 0.06 SE), followed by camera traps (0.30 ± 0.06) and live traps (0.01 ± 0.005). Acoustics had a lower LTD than camera traps (P = 0.017), where average LTD was 1.5 nights for acoustics and 3.25 nights for camera traps. Total field effort was greatest with live traps (111.9 hr) followed by acoustics (8.4 hr) and camera traps (9.6 hr), although processing and examination for data of noninvasive techniques made overall effort similar among the 3 methods. This pilot study demonstrated that both noninvasive methods were better rapid-assessment detection techniques for flying squirrels than live traps. However, determining seasonal effects between survey techniques and further development of protocols for both noninvasive techniques is

  5. Application of Data Mining and Knowledge Discovery Techniques to Enhance Binary Target Detection and Decision-Making for Compromised Visual Images

    DTIC Science & Technology

    2004-11-01

    affords exciting opportunities in target detection. The input signal may be a sum of sine waves, it could be an auditory signal, or possibly a visual...rendering of a scene. Since image processing is an area in which the original data are stationary in some sense ( auditory signals suffer from...11 Example 1 of SR - Identification of a Subliminal Signal below a Threshold .......................... 13 Example 2 of SR

  6. System considerations for detection and tracking of small targets using passive sensors

    NASA Astrophysics Data System (ADS)

    DeBell, David A.

    1991-08-01

    Passive sensors provide only a few discriminants to assist in threat assessment of small targets. Tracking of the small targets provides additional discriminants. This paper discusses the system considerations for tracking small targets using passive sensors, in particular EO sensors. Tracking helps establish good versus bad detections. Discussed are the requirements to be placed on the sensor system's accuracy, with respect to knowledge of the sightline direction. The detection of weak targets sets a requirement for two levels of tracking in order to reduce processor throughput. A system characteristic is the need to track all detections. For low thresholds, this can mean a heavy track burden. Therefore, thresholds must be adaptive in order not to saturate the processors. Second-level tracks must develop a range estimate in order to assess threat. Sensor platform maneuvers are required if the targets are moving. The need for accurate pointing, good stability, and a good update rate will be shown quantitatively, relating to track accuracy and track association.

  7. Detection of Glaucoma Using Image Processing Techniques: A Critique.

    PubMed

    Kumar, B Naveen; Chauhan, R P; Dahiya, Nidhi

    2018-01-01

    The primary objective of this article is to present a summary of different types of image processing methods employed for the detection of glaucoma, a serious eye disease. Glaucoma affects the optic nerve in which retinal ganglion cells become dead, and this leads to loss of vision. The principal cause is the increase in intraocular pressure, which occurs in open-angle and angle-closure glaucoma, the two major types affecting the optic nerve. In the early stages of glaucoma, no perceptible symptoms appear. As the disease progresses, vision starts to become hazy, leading to blindness. Therefore, early detection of glaucoma is needed for prevention. Manual analysis of ophthalmic images is fairly time-consuming and accuracy depends on the expertise of the professionals. Automatic analysis of retinal images is an important tool. Automation aids in the detection, diagnosis, and prevention of risks associated with the disease. Fundus images obtained from a fundus camera have been used for the analysis. Requisite pre-processing techniques have been applied to the image and, depending upon the technique, various classifiers have been used to detect glaucoma. The techniques mentioned in the present review have certain advantages and disadvantages. Based on this study, one can determine which technique provides an optimum result.

  8. Matched Filter Stochastic Background Characterization for Hyperspectral Target Detection

    DTIC Science & Technology

    2005-09-30

    and Pre- Clustering MVN Test.....................126 4.2.3 Pre- Clustering Detection Results.................................................130...4.2.4 Pre- Clustering Target Influence..................................................134 4.2.5 Statistical Distance Exclusion and Low Contrast...al, 2001] Figure 2.7 ROC Curve Comparison of RX, K-Means, and Bayesian Pre- Clustering Applied to Anomaly Detection [Ashton, 1998] Figure 2.8 ROC

  9. Modern Approaches to the Computation of the Probability of Target Detection in Cluttered Environments

    NASA Astrophysics Data System (ADS)

    Meitzler, Thomas J.

    The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.

  10. Seismic Techniques for Subsurface Voids Detection

    NASA Astrophysics Data System (ADS)

    Gritto, Roland; Korneev, Valeri; Elobaid Elnaiem, Ali; Mohamed, Fathelrahman; Sadooni, Fadhil

    2016-04-01

    A major hazards in Qatar is the presence of karst, which is ubiquitous throughout the country including depressions, sinkholes, and caves. Causes for the development of karst include faulting and fracturing where fluids find pathways through limestone and dissolve the host rock to form caverns. Of particular concern in rapidly growing metropolitan areas that expand in heretofore unexplored regions are the collapse of such caverns. Because Qatar has seen a recent boom in construction, including the planning and development of complete new sub-sections of metropolitan areas, the development areas need to be investigated for the presence of karst to determine their suitability for the planned project. In this paper, we present the results of a study to demonstrate a variety of seismic techniques to detect the presence of a karst analog in form of a vertical water-collection shaft located on the campus of Qatar University, Doha, Qatar. Seismic waves are well suited for karst detection and characterization. Voids represent high-contrast seismic objects that exhibit strong responses due to incident seismic waves. However, the complex geometry of karst, including shape and size, makes their imaging nontrivial. While karst detection can be reduced to the simple problem of detecting an anomaly, karst characterization can be complicated by the 3D nature of the problem of unknown scale, where irregular surfaces can generate diffracted waves of different kind. In our presentation we employ a variety of seismic techniques to demonstrate the detection and characterization of a vertical water collection shaft analyzing the phase, amplitude and spectral information of seismic waves that have been scattered by the object. We used the reduction in seismic wave amplitudes and the delay in phase arrival times in the geometrical shadow of the vertical shaft to independently detect and locate the object in space. Additionally, we use narrow band-pass filtered data combining two

  11. Detection of buried mines with seismic sonar

    NASA Astrophysics Data System (ADS)

    Muir, Thomas G.; Baker, Steven R.; Gaghan, Frederick E.; Fitzpatrick, Sean M.; Hall, Patrick W.; Sheetz, Kraig E.; Guy, Jeremie

    2003-10-01

    Prior research on seismo-acoustic sonar for detection of buried targets [J. Acoust. Soc. Am. 103, 2333-2343 (1998)] has continued with examination of the target strengths of buried test targets as well as targets of interest, and has also examined detection and confirmatory classification of these, all using arrays of seismic sources and receivers as well as signal processing techniques to enhance target recognition. The target strengths of two test targets (one a steel gas bottle, the other an aluminum powder keg), buried in a sand beach, were examined as a function of internal mass load, to evaluate theory developed for seismic sonar target strength [J. Acoust. Soc. Am. 103, 2344-2353 (1998)]. The detection of buried naval and military targets of interest was achieved with an array of 7 shaker sources and 5, three-axis seismometers, at a range of 5 m. Vector polarization filtering was the main signal processing technique for detection. It capitalizes on the fact that the vertical and horizontal components in Rayleigh wave echoes are 90 deg out of phase, enabling complex variable processing to obtain the imaginary component of the signal power versus time, which is unique to Rayleigh waves. Gabor matrix processing of this signal component was the main technique used to determine whether the target was man-made or just a natural target in the environment. [Work sponsored by ONR.

  12. Comparing efficiency of American Fisheries Society standard snorkeling techniques to environmental DNA sampling techniques

    USGS Publications Warehouse

    Ulibarri, Roy M.; Bonar, Scott A.; Rees, Christopher B.; Amberg, Jon J.; Ladell, Bridget; Jackson, Craig

    2017-01-01

    Analysis of environmental DNA (eDNA) is an emerging technique used to detect aquatic species through water sampling and the extraction of biological material for amplification. Our study compared the efficacy of eDNA methodology to American Fisheries Society (AFS) standard snorkeling surveys with regard to detecting the presence of rare fish species. Knowing which method is more efficient at detecting target species will help managers to determine the best way to sample when both traditional sampling methods and eDNA sampling are available. Our study site included three Navajo Nation streams that contained Navajo Nation Genetic Subunit Bluehead Suckers Catostomus discobolus and Zuni Bluehead Suckers C. discobolus yarrowi. We first divided the entire wetted area of streams into consecutive 100-m reaches and then systematically selected 10 reaches/stream for snorkel and eDNA surveys. Surface water samples were taken in 10-m sections within each 100-m reach, while fish presence was noted via snorkeling in each 10-m section. Quantitative PCR was run on each individual water sample in quadruplicate to test for the presence or absence of the target species. With eDNA sampling techniques, we were able to positively detect both species in two out of the three streams. Snorkeling resulted in positive detection of both species in all three streams. In streams where the target species were detected with eDNA sampling, snorkeling detected fish at 11–29 sites/stream, whereas eDNA detected fish at 3–12 sites/stream. Our results suggest that AFS standard snorkeling is more effective than eDNA for detecting target fish species. To improve our eDNA procedures, the amount of water collected and tested should be increased. Additionally, filtering water on-site may improve eDNA techniques for detecting fish. Future research should focus on standardization of eDNA sampling to provide a widely operational sampling tool.

  13. MutScan: fast detection and visualization of target mutations by scanning FASTQ data.

    PubMed

    Chen, Shifu; Huang, Tanxiao; Wen, Tiexiang; Li, Hong; Xu, Mingyan; Gu, Jia

    2018-01-22

    Some types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data. We developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way. MutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan.

  14. Moving target detection in flash mode against stroboscopic mode by active range-gated laser imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Xuanyu; Wang, Xinwei; Sun, Liang; Fan, Songtao; Lei, Pingshun; Zhou, Yan; Liu, Yuliang

    2018-01-01

    Moving target detection is important for the application of target tracking and remote surveillance in active range-gated laser imaging. This technique has two operation modes based on the difference of the number of pulses per frame: stroboscopic mode with the accumulation of multiple laser pulses per frame and flash mode with a single shot of laser pulse per frame. In this paper, we have established a range-gated laser imaging system. In the system, two types of lasers with different frequency were chosen for the two modes. Electric fan and horizontal sliding track were selected as the moving targets to compare the moving blurring between two modes. Consequently, the system working in flash mode shows more excellent performance in motion blurring against stroboscopic mode. Furthermore, based on experiments and theoretical analysis, we presented the higher signal-to-noise ratio of image acquired by stroboscopic mode than flash mode in indoor and underwater environment.

  15. Apollo experience report: Development of guidance targeting techniques for the command module and launch vehicle

    NASA Technical Reports Server (NTRS)

    Yencharis, J. D.; Wiley, R. F.; Davis, R. S.; Holmes, Q. A.; Zeiler, K. T.

    1972-01-01

    The development of the guidance targeting techniques for the Apollo command module and launch vehicle is discussed for four types of maneuvers: (1) translunar injection, (2) translunar midcourse, (3) lunar orbit insertion, and (4) return to earth. The development of real-time targeting programs for these maneuvers and the targeting procedures represented are discussed. The material is intended to convey historically the development of the targeting techniques required to meet the defined target objectives and to illustrate the solutions to problems encountered during that development.

  16. Detection and recognition of targets by using signal polarization properties

    NASA Astrophysics Data System (ADS)

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

    1999-08-01

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

  17. Study on the influence factors of camouflage target polarization detection

    NASA Astrophysics Data System (ADS)

    Huang, Yanhua; Chen, Lei; Li, Xia; Wu, Wenyuan

    2016-10-01

    The degree of linear polarization (DOLP) expressions at any polarizer direction (PD) was deduced based on the Stokes vector and Mueller matrix. The outdoors experiments were carried out to demonstrate the expressions. This paper mainly explored the DOLP-image-Contrast (DOLPC) between the target image and the background image, and the PD and RGB waveband that be considered two important influence factors were studied for camouflage target polarization detection. It was found that the DOLPC of target and background was obviously higher than intensity image. When setting the reference direction that polarizer was perpendicular to the incident face, the DOLP image of interval angle 60 degree between PD and reference direction had relatively high DOLPC, the interval angle 45 degree was the second, and the interval angle 35 degree was the third. The outdoors polarization detection experiment of controlling waveband showed that the DOLPC results was significantly different to use 650nm, 550nm and 450nm waveband, and the polarization detection performance by using 650nm band was an optimization method.

  18. A New Methodology for 3D Target Detection in Automotive Radar Applications

    PubMed Central

    Baselice, Fabio; Ferraioli, Giampaolo; Lukin, Sergyi; Matuozzo, Gianfranco; Pascazio, Vito; Schirinzi, Gilda

    2016-01-01

    Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach. PMID:27136558

  19. Projective techniques and the detection of child sexual abuse.

    PubMed

    Garb, H N; Wood, J M; Nezworski, M T

    2000-05-01

    Projective techniques (e.g., the Rorschach, Human Figure Drawings) are sometimes used to detect child sexual abuse. West recently conducted a meta-analysis on this topic, but she systematically excluded nonsignificant results. In this article, a reanalysis of her data is presented. The authors conclude that projective techniques should not be used to detect child sexual abuse. Many of the studies purportedly demonstrating validity are flawed, and none of the projective test scores have been well replicated.

  20. Investigating different computed tomography techniques for internal target volume definition.

    PubMed

    Yoganathan, S A; Maria Das, K J; Subramanian, V Siva; Raj, D Gowtham; Agarwal, Arpita; Kumar, Shaleen

    2017-01-01

    The aim of this work was to evaluate the various computed tomography (CT) techniques such as fast CT, slow CT, breath-hold (BH) CT, full-fan cone beam CT (FF-CBCT), half-fan CBCT (HF-CBCT), and average CT for delineation of internal target volume (ITV). In addition, these ITVs were compared against four-dimensional CT (4DCT) ITVs. Three-dimensional target motion was simulated using dynamic thorax phantom with target insert of diameter 3 cm for ten respiration data. CT images were acquired using a commercially available multislice CT scanner, and the CBCT images were acquired using On-Board-Imager. Average CT was generated by averaging 10 phases of 4DCT. ITVs were delineated for each CT by contouring the volume of the target ball; 4DCT ITVs were generated by merging all 10 phases target volumes. Incase of BH-CT, ITV was derived by boolean of CT phases 0%, 50%, and fast CT target volumes. ITVs determined by all CT and CBCT scans were significantly smaller (P < 0.05) than the 4DCT ITV, whereas there was no significant difference between average CT and 4DCT ITVs (P = 0.17). Fast CT had the maximum deviation (-46.1% ± 20.9%) followed by slow CT (-34.3% ± 11.0%) and FF-CBCT scans (-26.3% ± 8.7%). However, HF-CBCT scans (-12.9% ± 4.4%) and BH-CT scans (-11.1% ± 8.5%) resulted in almost similar deviation. On the contrary, average CT had the least deviation (-4.7% ± 9.8%). When comparing with 4DCT, all the CT techniques underestimated ITV. In the absence of 4DCT, the HF-CBCT target volumes with appropriate margin may be a reasonable approach for defining the ITV.

  1. Multishot Targeted PROPELLER Magnetic Resonance Imaging: Description of the Technique and Initial Applications

    PubMed Central

    Deng, Jie; Larson, Andrew C.

    2010-01-01

    Objectives To test the feasibility of combining inner-volume imaging (IVI) techniques with conventional multishot periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) techniques for targeted-PROPELLER magnetic resonance imaging. Materials and Methods Perpendicular section-selective gradients for spatially selective excitation and refocusing RF pulses were applied to limit the refocused field-of-view (FOV) along the phase-encoding direction for each rectangular blade image. We performed comparison studies in phantoms and normal volunteers by using targeted-PROPELLER methods for a wide range of imaging applications that commonly use turbo-spin-echo (TSE) approaches (brain, abdominal, vessel wall, cardiac). Results In these initial studies, we demonstrated the feasibility of using targeted-PROPELLER approaches to limit the imaging FOV thereby reducing the number of blades or permitting increased spatial resolution without commensurate increases in scan time. Both phantom and in vivo motion studies demonstrated the potential for more robust regional self-navigated motion correction compared with conventional full FOV PROPELLER methods. Conclusion We demonstrated that the reduced FOV targeted-PROPELLER technique offers the potential for reducing imaging time, increasing spatial resolution, and targeting specific areas for robust regional motion correction. PMID:19465860

  2. Cortical Spatio-Temporal Dynamics Underlying Phonological Target Detection in Humans

    ERIC Educational Resources Information Center

    Chang, Edward F.; Edwards, Erik; Nagarajan, Srikantan S.; Fogelson, Noa; Dalal, Sarang S.; Canolty, Ryan T.; Kirsch, Heidi E.; Barbaro, Nicholas M.; Knight, Robert T.

    2011-01-01

    Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential…

  3. Sample detection and analysis techniques for electrophoretic separation

    NASA Technical Reports Server (NTRS)

    Falb, R. D.; Hughes, K. E.; Powell, T. R.

    1975-01-01

    Methods for detecting and analyzing biological agents suitable for space flight operations were studied primarily by literature searches which were conducted of cell separation techniques. Detection methods discussed include: photometrometric, electric, radiometric, micrometry, ultrasonic, microscopic, and photographic. A bibliography, and a directory of vendors are included along with an index of commercial hardware.

  4. Rare targets are less susceptible to attention capture once detection has begun.

    PubMed

    Hon, Nicholas; Ng, Gavin; Chan, Gerald

    2016-04-01

    Rare or low probability targets are detected more slowly and/ or less accurately than higher probability counterparts. Various proposals have implicated perceptual and response-based processes in this deficit. Recent evidence, however, suggests that it is attentional in nature, with low probability targets requiring more attentional resources than high probability ones to detect. This difference in attentional requirements, in turn, suggests the possibility that low and high probability targets may have different susceptibilities to attention capture, which is also known to be resource-dependent. Supporting this hypothesis, we found that, once attentional resources have begun to be engaged by detection processes, low, but not high, probability targets have a reduced susceptibility to capture. Our findings speak to several issues. First, they indicate that the likelihood of attention capture occurring when a given task-relevant stimulus is being processed is dependent, to some extent, on how said stimulus is represented within mental task sets. Second, they provide added support for the idea that the behavioural deficit associated with low probability targets is attention-based. Finally, the current data point to reduced top-down biasing of target templates as a likely mechanism underlying the attentional locus of the deficit in question.

  5. Dolphin biosonar target detection in noise: wrap up of a past experiment.

    PubMed

    Au, Whitlow W L

    2014-07-01

    The target detection capability of bottlenose dolphins in the presence of artificial masking noise was first studied by Au and Penner [J. Acoust. Soc. Am. 70, 687-693 (1981)] in which the dolphins' target detection threshold was determined as a function of the ratio of the echo energy flux density and the estimated received noise spectral density. Such a metric was commonly used in human psychoacoustics despite the fact that the echo energy flux density is not compatible with noise spectral density which is averaged intensity per Hz. Since the earlier detection in noise studies, two important parameters, the dolphin integration time applicable to broadband clicks and the dolphin's auditory filter shape, were determined. The inclusion of these two parameters allows for the estimation of the received energy flux density of the masking noise so that the dolphin target detection can now be determined as a function of the ratio of the received energy of the echo over the received noise energy. Using an integration time of 264 μs and an auditory bandwidth of 16.7 kHz, the ratio of the echo energy to noise energy at the target detection threshold is approximately 1 dB.

  6. A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

    NASA Astrophysics Data System (ADS)

    Sharma, Anuj; Kumar Panigrahi, Prabin

    2012-02-01

    With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries. The failure of internal auditing system of the organization in identifying the accounting frauds has lead to use of specialized procedures to detect financial accounting fraud, collective known as forensic accounting. Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques based accounting fraud detection. The systematic and comprehensive literature review of the data mining techniques applicable to financial accounting fraud detection may provide a foundation to future research in this field. The findings of this review show that data mining techniques like logistic models, neural networks, Bayesian belief network, and decision trees have been applied most extensively to provide primary solutions to the problems inherent in the detection and classification of fraudulent data.

  7. Technique for ship/wake detection

    DOEpatents

    Roskovensky, John K [Albuquerque, NM

    2012-05-01

    An automated ship detection technique includes accessing data associated with an image of a portion of Earth. The data includes reflectance values. A first portion of pixels within the image are masked with a cloud and land mask based on spectral flatness of the reflectance values associated with the pixels. A given pixel selected from the first portion of pixels is unmasked when a threshold number of localized pixels surrounding the given pixel are not masked by the cloud and land mask. A spatial variability image is generated based on spatial derivatives of the reflectance values of the pixels which remain unmasked by the cloud and land mask. The spatial variability image is thresholded to identify one or more regions within the image as possible ship detection regions.

  8. Master training course for detection techniques

    NASA Astrophysics Data System (ADS)

    Kern, P.

    2013-11-01

    The LabEx FOCUS proposes a training course to the detection techniques. It will be proposed yearly to the students of master or of engineering school . This theoretical and practical training will be given during a full week at the Observatoire de Haute Provence. The teachers are members from the laboratories of the FOCUS consortium.

  9. Determination of target detection limits in hyperspectral data using band selection and dimensionality reduction

    NASA Astrophysics Data System (ADS)

    Gross, W.; Boehler, J.; Twizer, K.; Kedem, B.; Lenz, A.; Kneubuehler, M.; Wellig, P.; Oechslin, R.; Schilling, H.; Rotman, S.; Middelmann, W.

    2016-10-01

    Hyperspectral remote sensing data can be used for civil and military applications to robustly detect and classify target objects. High spectral resolution of hyperspectral data can compensate for the comparatively low spatial resolution, which allows for detection and classification of small targets, even below image resolution. Hyperspectral data sets are prone to considerable spectral redundancy, affecting and limiting data processing and algorithm performance. As a consequence, data reduction strategies become increasingly important, especially in view of near-real-time data analysis. The goal of this paper is to analyze different strategies for hyperspectral band selection algorithms and their effect on subpixel classification for different target and background materials. Airborne hyperspectral data is used in combination with linear target simulation procedures to create a representative amount of target-to-background ratios for evaluation of detection limits. Data from two different airborne hyperspectral sensors, AISA Eagle and Hawk, are used to evaluate transferability of band selection when using different sensors. The same target objects were recorded to compare the calculated detection limits. To determine subpixel classification results, pure pixels from the target materials are extracted and used to simulate mixed pixels with selected background materials. Target signatures are linearly combined with different background materials in varying ratios. The commonly used classification algorithms Adaptive Coherence Estimator (ACE) is used to compare the detection limit for the original data with several band selection and data reduction strategies. The evaluation of the classification results is done by assuming a fixed false alarm ratio and calculating the mean target-to-background ratio of correctly detected pixels. The results allow drawing conclusions about specific band combinations for certain target and background combinations. Additionally

  10. A Comparative Study of Unsupervised Anomaly Detection Techniques Using Honeypot Data

    NASA Astrophysics Data System (ADS)

    Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Inoue, Daisuke; Eto, Masashi; Nakao, Koji

    Intrusion Detection Systems (IDS) have been received considerable attention among the network security researchers as one of the most promising countermeasures to defend our crucial computer systems or networks against attackers on the Internet. Over the past few years, many machine learning techniques have been applied to IDSs so as to improve their performance and to construct them with low cost and effort. Especially, unsupervised anomaly detection techniques have a significant advantage in their capability to identify unforeseen attacks, i.e., 0-day attacks, and to build intrusion detection models without any labeled (i.e., pre-classified) training data in an automated manner. In this paper, we conduct a set of experiments to evaluate and analyze performance of the major unsupervised anomaly detection techniques using real traffic data which are obtained at our honeypots deployed inside and outside of the campus network of Kyoto University, and using various evaluation criteria, i.e., performance evaluation by similarity measurements and the size of training data, overall performance, detection ability for unknown attacks, and time complexity. Our experimental results give some practical and useful guidelines to IDS researchers and operators, so that they can acquire insight to apply these techniques to the area of intrusion detection, and devise more effective intrusion detection models.

  11. Measurement techniques investigated for detection of hydrogen chloride gas in ambient air

    NASA Technical Reports Server (NTRS)

    Gregory, G. L.

    1976-01-01

    Nine basic techniques are discussed, ranging from concentration (parts per million) to dosage only (parts per million-seconds) measurement techniques. Data for each technique include lower detection limit, response time, instrument status, and in some cases, specificity. Several techniques discussed can detect ambient hydrogen chloride concentrations below 1 part per million with a response time of seconds.

  12. The 'sniffer-patch' technique for detection of neurotransmitter release.

    PubMed

    Allen, T G

    1997-05-01

    A wide variety of techniques have been employed for the detection and measurement of neurotransmitter release from biological preparations. Whilst many of these methods offer impressive levels of sensitivity, few are able to combine sensitivity with the necessary temporal and spatial resolution required to study quantal release from single cells. One detection method that is seeing a revival of interest and has the potential to fill this niche is the so-called 'sniffer-patch' technique. In this article, specific examples of the practical aspects of using this technique are discussed along with the procedures involved in calibrating these biosensors to extend their applications to provide quantitative, in addition to simple qualitative, measurements of quantal transmitter release.

  13. Benchtop Antigen Detection Technique using Nanofiltration and Fluorescent Dyes

    NASA Technical Reports Server (NTRS)

    Scardelletti, Maximilian C.; Varaljay, Vanessa

    2009-01-01

    The designed benchtop technique is primed to detect bacteria and viruses from antigenic surface marker proteins in solutions, initially water. This inclusive bio-immunoassay uniquely combines nanofiltration and near infrared (NIR) dyes conjugated to antibodies to isolate and distinguish microbial antigens, using laser excitation and spectrometric analysis. The project goals include detecting microorganisms aboard the International Space Station, space shuttle, Crew Exploration Vehicle (CEV), and human habitats on future Moon and Mars missions, ensuring astronaut safety. The technique is intended to improve and advance water contamination testing both commercially and environmentally as well. Lastly, this streamlined technique poses to greatly simplify and expedite testing of pathogens in complex matrices, such as blood, in hospital and laboratory clinics.

  14. Detecting ship targets in spaceborne infrared image based on modeling radiation anomalies

    NASA Astrophysics Data System (ADS)

    Wang, Haibo; Zou, Zhengxia; Shi, Zhenwei; Li, Bo

    2017-09-01

    Using infrared imaging sensors to detect ship target in the ocean environment has many advantages compared to other sensor modalities, such as better thermal sensitivity and all-weather detection capability. We propose a new ship detection method by modeling radiation anomalies for spaceborne infrared image. The proposed method can be decomposed into two stages, where in the first stage, a test infrared image is densely divided into a set of image patches and the radiation anomaly of each patch is estimated by a Gaussian Mixture Model (GMM), and thereby target candidates are obtained from anomaly image patches. In the second stage, target candidates are further checked by a more discriminative criterion to obtain the final detection result. The main innovation of the proposed method is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous patches among complex background. The experimental result on short wavelength infrared band (1.560 - 2.300 μm) and long wavelength infrared band (10.30 - 12.50 μm) of Landsat-8 satellite shows the proposed method achieves a desired ship detection accuracy with higher recall than other classical ship detection methods.

  15. Target detection using the background model from the topological anomaly detection algorithm

    NASA Astrophysics Data System (ADS)

    Dorado Munoz, Leidy P.; Messinger, David W.; Ziemann, Amanda K.

    2013-05-01

    The Topological Anomaly Detection (TAD) algorithm has been used as an anomaly detector in hyperspectral and multispectral images. TAD is an algorithm based on graph theory that constructs a topological model of the background in a scene, and computes an anomalousness ranking for all of the pixels in the image with respect to the background in order to identify pixels with uncommon or strange spectral signatures. The pixels that are modeled as background are clustered into groups or connected components, which could be representative of spectral signatures of materials present in the background. Therefore, the idea of using the background components given by TAD in target detection is explored in this paper. In this way, these connected components are characterized in three different approaches, where the mean signature and endmembers for each component are calculated and used as background basis vectors in Orthogonal Subspace Projection (OSP) and Adaptive Subspace Detector (ASD). Likewise, the covariance matrix of those connected components is estimated and used in detectors: Constrained Energy Minimization (CEM) and Adaptive Coherence Estimator (ACE). The performance of these approaches and the different detectors is compared with a global approach, where the background characterization is derived directly from the image. Experiments and results using self-test data set provided as part of the RIT blind test target detection project are shown.

  16. Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

    PubMed Central

    Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

    2014-01-01

    In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

  17. Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

    PubMed

    Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

    2014-10-27

    In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

  18. Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor.

    PubMed

    Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

    2016-12-29

    When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications.

  19. Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor

    PubMed Central

    Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

    2016-01-01

    When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications. PMID:28036073

  20. Detection technology of polarization target based on curvelet transform in turbid liquid

    NASA Astrophysics Data System (ADS)

    Zhang, Su; Duan, Jin; Fu, Qiang; Zhan, Juntong; Ma, Wanzhuo

    2015-08-01

    To suppress the interference of the target detecting in the turbid medium, a kind of polarization detection technology based on Curvelet transform was applied. This method firstly adjusts the angles of polarizing film to get the intensity images of the situations at 0°,60° and 120°, then deduces the images of Stokes vectors, degree of polarization (DOP) and polarization angle (PA) according to the Mueller matrix. At last the DOP and intensity images can be decomposed by Curvelet transform to realize the fusion of the high and low coefficients respectively, after the processed coefficients are reconstructed, the target which is easier to detect can be achieved. To prove this method, many targets in turbid medium have been detected by polarization method and fused their DOP and intensity images with Curvelet transform algorithm. As an example screws in moderate and high concentration liquid are presented respectively, from which we can see the unpolarized targets are less obvious in higher concentration liquid. When the DOP and intensity images are fused by Curvelet transform, the targets are emerged clearly out of the turbid medium, and the values of the quality evaluation parameters in clarity, degree of contract and spatial frequency are prominently enhanced comparing with the unpolarized images, which can show the feasibility of this method.

  1. A novel spatial-temporal detection method of dim infrared moving small target

    NASA Astrophysics Data System (ADS)

    Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

    2014-09-01

    Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

  2. Electromagnetic Induction Spectroscopy for the Detection of Subsurface Targets

    DTIC Science & Technology

    2012-12-01

    curves of the proposed method and that of Fails et al.. For the kNN ROC curve, k = 7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81...et al. [6] and Ramachandran et al. [7] both demonstrated success in detecting mines using the k-nearest-neighbor ( kNN ) algorithm based on the EMI...error is also included in the feature vector. The kNN labels an unknown target based on the closest targets in a training set. Collins et al. [2] and

  3. Ultrasonic Imaging Techniques for Breast Cancer Detection

    NASA Astrophysics Data System (ADS)

    Goulding, N. R.; Marquez, J. D.; Prewett, E. M.; Claytor, T. N.; Nadler, B. R.

    2008-02-01

    Improving the resolution and specificity of current ultrasonic imaging technology is needed to enhance its relevance to breast cancer detection. A novel ultrasonic imaging reconstruction method is described that exploits classical straight-ray migration. This novel method improves signal processing for better image resolution and uses novel staging hardware options using a pulse-echo approach. A breast phantom with various inclusions is imaged using the classical migration method and is compared to standard computed tomography (CT) scans. These innovative ultrasonic methods incorporate ultrasound data acquisition, beam profile characterization, and image reconstruction. For an ultrasonic frequency of 2.25 MHz, imaged inclusions of approximately 1 cm are resolved and identified. Better resolution is expected with minor modifications. Improved image quality and resolution enables earlier detection and more accurate diagnoses of tumors thus reducing the number of biopsies performed, increasing treatment options, and lowering remission percentages. Using these new techniques the inclusions in the phantom are resolved and compared to the results of standard methods. Refinement of this application using other imaging techniques such as time-reversal mirrors (TRM), synthetic aperture focusing technique (SAFT), decomposition of the time reversal operator (DORT), and factorization methods is also discussed.

  4. Tumor margin detection using optical biopsy techniques

    NASA Astrophysics Data System (ADS)

    Zhou, Yan; Liu, Cheng-hui; Li, Jiyou; Li, Zhongwu; Zhou, Lixin; Chen, Ke; Pu, Yang; He, Yong; Zhu, Ke; Li, Qingbo; Alfano, Robert R.

    2014-03-01

    The aim of this study is to use the Resonance Raman (RR) and fluorescence spectroscopic technique for tumor margin detection with high accuracy based on native molecular fingerprints of breast and gastrointestinal (GI) tissues. This tumor margins detection method utilizes advantages of RR spectroscopic technique in situ and in real-time to diagnose tumor changes providing powerful tools for clinical guiding intraoperative margin assessments and postoperative treatments. The tumor margin detection procedures by RR spectroscopy were taken by scanning lesion from center or around tumor region in ex-vivo to find the changes in cancerous tissues with the rim of normal tissues using the native molecular fingerprints. The specimens used to analyze tumor margins include breast and GI carcinoma and normal tissues. The sharp margin of the tumor was found by the changes of RR spectral peaks within 2 mm distance. The result was verified using fluorescence spectra with 300 nm, 320 nm and 340 nm excitation, in a typical specimen of gastric cancerous tissue within a positive margin in comparison with normal gastric tissues. This study demonstrates the potential of RR and fluorescence spectroscopy as new approaches with labeling free to determine the intraoperative margin assessment.

  5. Evaluation of two molecular techniques for rapid detection of the main dermatophytic agents of tinea capitis.

    PubMed

    Deng, S; Zhou, Z; de Hoog, G S; Wang, X; Abliz, P; Sun, J; Najafzadeh, M J; Pan, W; Lei, W; Zhu, S; Hasimu, H; Zhang, P; Guo, Y; Deng, D; Liao, W

    2015-12-01

    Tinea capitis is very common in Western China, with the most widespread aetiological agent being Trichophyton violaceum, while Microsporum canis is prevalent in the remainder of China. Conventional diagnostics and internal transcribed spacer (ITS) sequencing analyses have proven relatively limited due to the close phylogenetic relationship of anthropophilic dermatophytes. Therefore, alternative molecular tools with sufficient specificity, reproducibility and sensitivity are necessary. To evaluate two molecular techniques [multiplex ligation-dependent probe amplification (MLPA) and rolling circle amplification (RCA)] for rapid detection of the aetiological agents of tinea capitis, T. violaceum and M. canis. Probes of RCA and MLPA were designed with target sequences in the rDNA ITS gene region. Strains tested consist of 31 T. violaceum, 22 M. canis and 24 reference strains of species that are taxonomically close to the target species. The specificity and reproducibility of RCA and MLPA in detection of T. violaceum and M. canis were both 100% in both species. Sensitivity testing showed that RCA was positive at concentrations down to 1·68 × 10(6) copies of DNA in the TvioRCA probe, and 2·7 × 10(8) copies of DNA in McRCA. MLPA yielded positive results at concentrations of DNA down to 1·68 × 10(1) copies in the TvioMLPA probe and 2·7 × 10(2) in McMLPA. The two techniques were sufficiently specific and sensitive for discriminating the target DNA of T. violaceum and M. canis from that of closely related dermatophytes. RCA and MLPA are advantageous in their reliability and ease of operation compared with standard polymerase chain reaction and conventional methods. © 2015 British Association of Dermatologists.

  6. Fire flame detection based on GICA and target tracking

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  7. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.

    PubMed

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina

    2008-10-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.

  8. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs

    PubMed Central

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Žel, Jana; Gruden, Kristina

    2008-01-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1–25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification. PMID:18710880

  9. Assessment of Schrodinger Eigenmaps for target detection

    NASA Astrophysics Data System (ADS)

    Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek

    2014-06-01

    Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.

  10. Neuroimaging techniques for memory detection: scientific, ethical, and legal issues.

    PubMed

    Meegan, Daniel V

    2008-01-01

    There is considerable interest in the use of neuroimaging techniques for forensic purposes. Memory detection techniques, including the well-publicized Brain Fingerprinting technique (Brain Fingerprinting Laboratories, Inc., Seattle WA), exploit the fact that the brain responds differently to sensory stimuli to which it has been exposed before. When a stimulus is specifically associated with a crime, the resulting brain activity should differentiate between someone who was present at the crime and someone who was not. This article reviews the scientific literature on three such techniques: priming, old/new, and P300 effects. The forensic potential of these techniques is evaluated based on four criteria: specificity, automaticity, encoding flexibility, and longevity. This article concludes that none of the techniques are devoid of forensic potential, although much research is yet to be done. Ethical issues, including rights to privacy and against self-incrimination, are discussed. A discussion of legal issues concludes that current memory detection techniques do not yet meet United States standards of legal admissibility.

  11. Targeted Muscle Reinnervation for Transradial Amputation: Description of Operative Technique.

    PubMed

    Morgan, Emily N; Kyle Potter, Benjamin; Souza, Jason M; Tintle, Scott M; Nanos, George P

    2016-12-01

    Targeted muscle reinnervation (TMR) is a revolutionary surgical technique that, together with advances in upper extremity prostheses and advanced neuromuscular pattern recognition, allows intuitive and coordinated control in multiple planes of motion for shoulder disarticulation and transhumeral amputees. TMR also may provide improvement in neuroma-related pain and may represent an opportunity for sensory reinnervation as advances in prostheses and haptic feedback progress. Although most commonly utilized following shoulder disarticulation and transhumeral amputations, TMR techniques also represent an exciting opportunity for improvement in integrated prosthesis control and neuroma-related pain improvement in patients with transradial amputations. As there are no detailed descriptions of this technique in the literature to date, we provide our surgical technique for TMR in transradial amputations.

  12. Fundamentals of electrochemical detection techniques for CE and MCE.

    PubMed

    Kubán, Pavel; Hauser, Peter C

    2009-10-01

    The electroanalytical techniques of amperometry, conductometry and potentiometry match well with the instrumental simplicity of CE. Indeed, all three detection approaches have been reported for electrophoretic separations. However, the characteristics of the three methods are quite distinct and these are not related to the optical methods more commonly employed. A detailed discussion of the underlying principles of each is given. The issue of possible effects of the separation voltage on the electrochemical detection techniques is considered in depth, and approaches to the elimination of such interferences are also discussed for each case.

  13. Windowing technique in FM radar realized by FPGA for better target resolution

    NASA Astrophysics Data System (ADS)

    Ponomaryov, Volodymyr I.; Escamilla-Hernandez, Enrique; Kravchenko, Victor F.

    2006-09-01

    Remote sensing systems, such as SAR usually apply FM signals to resolve nearly placed targets (objects) and improve SNR. Main drawbacks in the pulse compression of FM radar signal that it can add the range side-lobes in reflectivity measurements. Using weighting window processing in time domain it is possible to decrease significantly the side-lobe level (SLL) of output radar signal that permits to resolve small or low power targets those are masked by powerful ones. There are usually used classical windows such as Hamming, Hanning, Blackman-Harris, Kaiser-Bessel, Dolph-Chebyshev, Gauss, etc. in window processing. Additionally to classical ones in here we also use a novel class of windows based on atomic functions (AF) theory. For comparison of simulation and experimental results we applied the standard parameters, such as coefficient of amplification, maximum level of side-lobe, width of main lobe, etc. In this paper we also proposed to implement the compression-windowing model on a hardware level employing Field Programmable Gate Array (FPGA) that offers some benefits like instantaneous implementation, dynamic reconfiguration, design, and field programmability. It has been investigated the pulse compression design on FPGA applying classical and novel window technique to reduce the SLL in absence and presence of noise. The paper presents simulated and experimental examples of detection of small or nearly placed targets in the imaging radar. Paper also presents the experimental hardware results of windowing in FM radar demonstrating resolution of the several targets for classical rectangular, Hamming, Kaiser-Bessel, and some novel ones: Up(x), fup 4(x)•D 3(x), fup 6(x)•G 3(x), etc. It is possible to conclude that windows created on base of the AFs offer better decreasing of the SLL in cases of presence or absence of noise and when we move away of the main lobe in comparison with classical windows.

  14. Aerial surveillance based on hierarchical object classification for ground target detection

    NASA Astrophysics Data System (ADS)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  15. Design-for-Hardware-Trust Techniques, Detection Strategies and Metrics for Hardware Trojans

    DTIC Science & Technology

    2015-12-14

    down  both  rising  and  falling  transitions.  For  Trojan   detection ,   one   fault ,   slow-­‐to-­‐rise  or   slow-­‐to...in Jan. 2016. Through the course of this project we developed novel hardware Trojan detection techniques based on clock sweeping. The technique takes...algorithms to detect minor changes due to Trojan and compared them with those changes made by process variations. This technique was implemented on

  16. Feature-based RNN target recognition

    NASA Astrophysics Data System (ADS)

    Bakircioglu, Hakan; Gelenbe, Erol

    1998-09-01

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

  17. Lip boundary detection techniques using color and depth information

    NASA Astrophysics Data System (ADS)

    Kim, Gwang-Myung; Yoon, Sung H.; Kim, Jung H.; Hur, Gi Taek

    2002-01-01

    This paper presents our approach to using a stereo camera to obtain 3-D image data to be used to improve existing lip boundary detection techniques. We show that depth information as provided by our approach can be used to significantly improve boundary detection systems. Our system detects the face and mouth area in the image by using color, geometric location, and additional depth information for the face. Initially, color and depth information can be used to localize the face. Then we can determine the lip region from the intensity information and the detected eye locations. The system has successfully been used to extract approximate lip regions using RGB color information of the mouth area. Merely using color information is not robust because the quality of the results may vary depending on light conditions, background, and the human race. To overcome this problem, we used a stereo camera to obtain 3-D facial images. 3-D data constructed from the depth information along with color information can provide more accurate lip boundary detection results as compared to color only based techniques.

  18. Integrated detection, estimation, and guidance in pursuit of a maneuvering target

    NASA Astrophysics Data System (ADS)

    Dionne, Dany

    The thesis focuses on efficient solutions of non-cooperative pursuit-evasion games with imperfect information on the state of the system. This problem is important in the context of interception of future maneuverable ballistic missiles. However, the theoretical developments are expected to find application to a broad class of hybrid control and estimation problems in industry. The validity of the results is nevertheless confirmed using a benchmark problem in the area of terminal guidance. A specific interception scenario between an incoming target with no information and a single interceptor missile with noisy measurements is analyzed in the form of a linear hybrid system subject to additive abrupt changes. The general research is aimed to achieve improved homing accuracy by integrating ideas from detection theory, state estimation theory and guidance. The results achieved can be summarized as follows. (i) Two novel maneuver detectors are developed to diagnose abrupt changes in a class of hybrid systems (detection and isolation of evasive maneuvers): a new implementation of the GLR detector and the novel adaptive- H0 GLR detector. (ii) Two novel state estimators for target tracking are derived using the novel maneuver detectors. The state estimators employ parameterized family of functions to described possible evasive maneuvers. (iii) A novel adaptive Bayesian multiple model predictor of the ballistic miss is developed which employs semi-Markov models and ideas from detection theory. (iv) A novel integrated estimation and guidance scheme that significantly improves the homing accuracy is also presented. The integrated scheme employs banks of estimators and guidance laws, a maneuver detector, and an on-line governor; the scheme is adaptive with respect to the uncertainty affecting the probability density function of the filtered state. (v) A novel discretization technique for the family of continuous-time, game theoretic, bang-bang guidance laws is introduced. The

  19. A speeded-up saliency region-based contrast detection method for small targets

    NASA Astrophysics Data System (ADS)

    Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang

    2018-04-01

    To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

  20. Planetary Gearbox Fault Detection Using Vibration Separation Techniques

    NASA Technical Reports Server (NTRS)

    Lewicki, David G.; LaBerge, Kelsen E.; Ehinger, Ryan T.; Fetty, Jason

    2011-01-01

    Studies were performed to demonstrate the capability to detect planetary gear and bearing faults in helicopter main-rotor transmissions. The work supported the Operations Support and Sustainment (OSST) program with the U.S. Army Aviation Applied Technology Directorate (AATD) and Bell Helicopter Textron. Vibration data from the OH-58C planetary system were collected on a healthy transmission as well as with various seeded-fault components. Planetary fault detection algorithms were used with the collected data to evaluate fault detection effectiveness. Planet gear tooth cracks and spalls were detectable using the vibration separation techniques. Sun gear tooth cracks were not discernibly detectable from the vibration separation process. Sun gear tooth spall defects were detectable. Ring gear tooth cracks were only clearly detectable by accelerometers located near the crack location or directly across from the crack. Enveloping provided an effective method for planet bearing inner- and outer-race spalling fault detection.

  1. Application of neutron interrogation techniques to corrosion detection

    NASA Technical Reports Server (NTRS)

    Birt, E. A.; Namkung, M.; Vulcan, W.; Welsh, R. E.

    1991-01-01

    This paper discusses a technique which may be able to detect corrosion by determining the presence of oxygen at the corroded site via a neutron inelastic gamma reaction. Initial experiments have been performed using a Pu-239/Be neutron source and a NaI(T1) gamma-ray detector. From the results it was concluded that a 1 mm thickness of aluminum oxide would not be detected.

  2. Apple Mealiness Detection Using Hyperspectral Scattering Technique

    USDA-ARS?s Scientific Manuscript database

    Mealiness is a symptom of internal fruit disorder, which is characterized by abnormal softness and lack of free juice in the fruit. This research investigated the potential of hyperspectral scattering technique for detecting mealy apples. Spectral scattering profiles between 600 nm and 1,000 nm were...

  3. Detection and quantification of angiogenesis in experimental valve disease with integrin-targeted nanoparticles and 19-fluorine MRI/MRS

    PubMed Central

    Waters, Emily A; Chen, Junjie; Allen, John S; Zhang, Huiying; Lanza, Gregory M; Wickline, Samuel A

    2008-01-01

    animals. Nanoparticles were successfully detected in all samples scanned at 3.0T. PECAM endothelial staining and ανβ3 integrin staining revealed the presence of neovasculature within the valve leaflets. Conclusion Integrin-targeted PFC nanoparticles specifically detect early angiogenesis in sclerotic aortic valves of cholesterol fed rabbits. These techniques may be useful for assessing atherosclerotic components of preclinical aortic valve disease in patients and could assist in defining efficacy of medical therapies. PMID:18817557

  4. Effects of Alzheimer's Disease on Visual Target Detection: A "Peripheral Bias".

    PubMed

    Vallejo, Vanessa; Cazzoli, Dario; Rampa, Luca; Zito, Giuseppe A; Feuerstein, Flurin; Gruber, Nicole; Müri, René M; Mosimann, Urs P; Nef, Tobias

    2016-01-01

    Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer's Disease (AD). The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and 20 healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ±90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view.

  5. Detecting drug-target binding in cells using fluorescence-activated cell sorting coupled with mass spectrometry analysis.

    PubMed

    Wilson, Kris; Webster, Scott P; Iredale, John P; Zheng, Xiaozhong; Homer, Natalie Z; Pham, Nhan T; Auer, Manfred; Mole, Damian J

    2017-12-15

    The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

  6. Detecting drug-target binding in cells using fluorescence-activated cell sorting coupled with mass spectrometry analysis

    NASA Astrophysics Data System (ADS)

    Wilson, Kris; Webster, Scott P.; Iredale, John P.; Zheng, Xiaozhong; Homer, Natalie Z.; Pham, Nhan T.; Auer, Manfred; Mole, Damian J.

    2018-01-01

    The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

  7. Target-responsive DNA hydrogel mediated "stop-flow" microfluidic paper-based analytic device for rapid, portable and visual detection of multiple targets.

    PubMed

    Wei, Xiaofeng; Tian, Tian; Jia, Shasha; Zhu, Zhi; Ma, Yanli; Sun, Jianjun; Lin, Zhenyu; Yang, Chaoyong James

    2015-04-21

    A versatile point-of-care assay platform was developed for simultaneous detection of multiple targets based on a microfluidic paper-based analytic device (μPAD) using a target-responsive hydrogel to mediate fluidic flow and signal readout. An aptamer-cross-linked hydrogel was used as a target-responsive flow regulator in the μPAD. In the absence of a target, the hydrogel is formed in the flow channel, stopping the flow in the μPAD and preventing the colored indicator from traveling to the final observation spot, thus yielding a "signal off" readout. In contrast, in the presence of a target, no hydrogel is formed because of the preferential interaction of target and aptamer. This allows free fluidic flow in the μPAD, carrying the indicator to the observation spot and producing a "signal on" readout. The device is inexpensive to fabricate, easy to use, and disposable after detection. Testing results can be obtained within 6 min by the naked eye via a simple loading operation without the need for any auxiliary equipment. Multiple targets, including cocaine, adenosine, and Pb(2+), can be detected simultaneously, even in complex biological matrices such as urine. The reported method offers simple, low cost, rapid, user-friendly, point-of-care testing, which will be useful in many applications.

  8. Small target detection using bilateral filter and temporal cross product in infrared images

    NASA Astrophysics Data System (ADS)

    Bae, Tae-Wuk

    2011-09-01

    We introduce a spatial and temporal target detection method using spatial bilateral filter (BF) and temporal cross product (TCP) of temporal pixels in infrared (IR) image sequences. At first, the TCP is presented to extract the characteristics of temporal pixels by using temporal profile in respective spatial coordinates of pixels. The TCP represents the cross product values by the gray level distance vector of a current temporal pixel and the adjacent temporal pixel, as well as the horizontal distance vector of the current temporal pixel and a temporal pixel corresponding to potential target center. The summation of TCP values of temporal pixels in spatial coordinates makes the temporal target image (TTI), which represents the temporal target information of temporal pixels in spatial coordinates. And then the proposed BF filter is used to extract the spatial target information. In order to predict background without targets, the proposed BF filter uses standard deviations obtained by an exponential mapping of the TCP value corresponding to the coordinate of a pixel processed spatially. The spatial target image (STI) is made by subtracting the predicted image from the original image. Thus, the spatial and temporal target image (STTI) is achieved by multiplying the STI and the TTI, and then targets finally are detected in STTI. In experimental result, the receiver operating characteristics (ROC) curves were computed experimentally to compare the objective performance. From the results, the proposed algorithm shows better discrimination of target and clutters and lower false alarm rates than the existing target detection methods.

  9. Infrared small target detection in heavy sky scene clutter based on sparse representation

    NASA Astrophysics Data System (ADS)

    Liu, Depeng; Li, Zhengzhou; Liu, Bing; Chen, Wenhao; Liu, Tianmei; Cao, Lei

    2017-09-01

    A novel infrared small target detection method based on sky clutter and target sparse representation is proposed in this paper to cope with the representing uncertainty of clutter and target. The sky scene background clutter is described by fractal random field, and it is perceived and eliminated via the sparse representation on fractal background over-complete dictionary (FBOD). The infrared small target signal is simulated by generalized Gaussian intensity model, and it is expressed by the generalized Gaussian target over-complete dictionary (GGTOD), which could describe small target more efficiently than traditional structured dictionaries. Infrared image is decomposed on the union of FBOD and GGTOD, and the sparse representation energy that target signal and background clutter decomposed on GGTOD differ so distinctly that it is adopted to distinguish target from clutter. Some experiments are induced and the experimental results show that the proposed approach could improve the small target detection performance especially under heavy clutter for background clutter could be efficiently perceived and suppressed by FBOD and the changing target could also be represented accurately by GGTOD.

  10. Morphological operators for enhanced polarimetric image target detection

    NASA Astrophysics Data System (ADS)

    Romano, João. M.; Rosario, Dalton S.

    2015-09-01

    We introduce an algorithm based on morphological filters with the Stokes parameters that augments the daytime and nighttime detection of weak-signal manmade objects immersed in a predominant natural background scene. The approach features a tailored sequence of signal-enhancing filters, consisting of core morphological operators (dilation, erosion) and higher level morphological operations (e.g., spatial gradient, opening, closing) to achieve a desired overarching goal. Using representative data from the SPICE database, the results show that the approach was able to automatically and persistently detect with a high confidence level the presence of three mobile military howitzer surrogates (targets) in natural clutter.

  11. Comparison of human observer and algorithmic target detection in nonurban forward-looking infrared imagery

    NASA Astrophysics Data System (ADS)

    Weber, Bruce A.

    2005-07-01

    We have performed an experiment that compares the performance of human observers with that of a robust algorithm for the detection of targets in difficult, nonurban forward-looking infrared imagery. Our purpose was to benchmark the comparison and document performance differences for future algorithm improvement. The scale-insensitive detection algorithm, used as a benchmark by the Night Vision Electronic Sensors Directorate for algorithm evaluation, employed a combination of contrastlike features to locate targets. Detection receiver operating characteristic curves and observer-confidence analyses were used to compare human and algorithmic responses and to gain insight into differences. The test database contained ground targets, in natural clutter, whose detectability, as judged by human observers, ranged from easy to very difficult. In general, as compared with human observers, the algorithm detected most of the same targets, but correlated confidence with correct detections poorly and produced many more false alarms at any useful level of performance. Though characterizing human performance was not the intent of this study, results suggest that previous observational experience was not a strong predictor of human performance, and that combining individual human observations by majority vote significantly reduced false-alarm rates.

  12. Small target detection based on difference accumulation and Gaussian curvature under complex conditions

    NASA Astrophysics Data System (ADS)

    Zhang, He; Niu, Yanxiong; Zhang, Hao

    2017-12-01

    Small target detection is a significant subject in infrared search and track and other photoelectric imaging systems. The small target is imaged under complex conditions, which contains clouds, horizon and bright part. In this paper, a novel small target detection method is proposed based on difference accumulation, clustering and Gaussian curvature. Difference accumulation varies from regions. Therefore, after obtaining difference accumulations, clustering is applied to determine whether the pixel belongs to the heterogeneous region, and eliminate heterogeneous region. Then Gaussian curvature is used to separate target from the homogeneous region. Experiments are conducted for verification, along with comparisons to several other methods. The experimental results demonstrate that our method has an advantage of 1-2 orders of magnitude on SCRG and BSF than others. Given that the false alarm rate is 1, the detection probability can be approximately 0.9 by using proposed method.

  13. Insect Detection of Small Targets Moving in Visual Clutter

    PubMed Central

    Barnett, Paul D; O'Carroll, David C

    2006-01-01

    Detection of targets that move within visual clutter is a common task for animals searching for prey or conspecifics, a task made even more difficult when a moving pursuer needs to analyze targets against the motion of background texture (clutter). Despite the limited optical acuity of the compound eye of insects, this challenging task seems to have been solved by their tiny visual system. Here we describe neurons found in the male hoverfly,Eristalis tenax, that respond selectively to small moving targets. Although many of these target neurons are inhibited by the motion of a background pattern, others respond to target motion within the receptive field under a surprisingly large range of background motion stimuli. Some neurons respond whether or not there is a speed differential between target and background. Analysis of responses to very small targets (smaller than the size of the visual field of single photoreceptors) or those targets with reduced contrast shows that these neurons have extraordinarily high contrast sensitivity. Our data suggest that rejection of background motion may result from extreme selectivity for small targets contrasting against local patches of the background, combined with this high sensitivity, such that background patterns rarely contain features that satisfactorily drive the neuron. PMID:16448249

  14. Combined mutation and copy-number variation detection by targeted next-generation sequencing in uveal melanoma.

    PubMed

    Smit, Kyra N; van Poppelen, Natasha M; Vaarwater, Jolanda; Verdijk, Robert; van Marion, Ronald; Kalirai, Helen; Coupland, Sarah E; Thornton, Sophie; Farquhar, Neil; Dubbink, Hendrikus-Jan; Paridaens, Dion; de Klein, Annelies; Kiliç, Emine

    2018-05-01

    Uveal melanoma is a highly aggressive cancer of the eye, in which nearly 50% of the patients die from metastasis. It is the most common type of primary eye cancer in adults. Chromosome and mutation status have been shown to correlate with the disease-free survival. Loss of chromosome 3 and inactivating mutations in BAP1, which is located on chromosome 3, are strongly associated with 'high-risk' tumors that metastasize early. Other genes often involved in uveal melanoma are SF3B1 and EIF1AX, which are found to be mutated in intermediate- and low-risk tumors, respectively. To obtain genetic information of all genes in one test, we developed a targeted sequencing method that can detect mutations in uveal melanoma genes and chromosomal anomalies in chromosome 1, 3, and 8. With as little as 10 ng DNA, we obtained enough coverage on all genes to detect mutations, such as substitutions, deletions, and insertions. These results were validated with Sanger sequencing in 28 samples. In >90% of the cases, the BAP1 mutation status corresponded to the BAP1 immunohistochemistry. The results obtained in the Ion Torrent single-nucleotide polymorphism assay were confirmed with several other techniques, such as fluorescence in situ hybridization, multiplex ligation-dependent probe amplification, and Illumina SNP array. By validating our assay in 27 formalin-fixed paraffin-embedded and 43 fresh uveal melanomas, we show that mutations and chromosome status can reliably be obtained using targeted next-generation sequencing. Implementing this technique as a diagnostic pathology application for uveal melanoma will allow prediction of the patients' metastatic risk and potentially assess eligibility for new therapies.

  15. Gastric cancer target detection using near-infrared hyperspectral imaging with chemometrics

    NASA Astrophysics Data System (ADS)

    Yi, Weisong; Zhang, Jian; Jiang, Houmin; Zhang, Niya

    2014-09-01

    Gastric cancer is one of the leading causes of cancer death in the world due to its high morbidity and mortality. Hyperspectral imaging (HSI) is an emerging, non-destructive, cutting edge analytical technology that combines conventional imaging and spectroscopy in one single system. The manuscript has investigated the application of near-infrared hyperspectral imaging (900-1700 nm) (NIR-HSI) for gastric cancer detection with algorithms. Major spectral differences were observed in three regions (950-1050, 1150-1250, and 1400-1500 nm). By inspecting cancerous mean spectrum three major absorption bands were observed around 975, 1215 and 1450 nm. Furthermore, the cancer target detection results are consistent and conformed with histopathological examination results. These results suggest that NIR-HSI is a simple, feasible and sensitive optical diagnostic technology for gastric cancer target detection with chemometrics.

  16. Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

    DTIC Science & Technology

    2010-01-01

    target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

  17. Multimodal technique to eliminate humidity interference for specific detection of ethanol.

    PubMed

    Jalal, Ahmed Hasnain; Umasankar, Yogeswaran; Gonzalez, Pablo J; Alfonso, Alejandro; Bhansali, Shekhar

    2017-01-15

    Multimodal electrochemical technique incorporating both open circuit potential (OCP) and amperometric techniques have been conceptualized and implemented to improve the detection of specific analyte in systems where more than one analyte is present. This approach has been demonstrated through the detection of ethanol while eliminating the contribution of water in a micro fuel cell sensor system. The sensor was interfaced with LMP91000 potentiostat, controlled through MSP430F5529LP microcontroller to implement an auto-calibration algorithm tailored to improve the detection of alcohol. The sensor was designed and fabricated as a three electrode system with Nafion as a proton exchange membrane (PEM). The electrochemical signal of the interfering phase (water) was eliminated by implementing the multimodal electrochemical detection technique. The results were validated by comparing sensor and potentiostat performances with a commercial sensor and potentiostat respectively. The results suggest that such a sensing system can detect ethanol at concentrations as low as 5ppm. The structure and properties such as low detection limit, selectivity and miniaturized size enables potential application of this device in wearable transdermal alcohol measurements. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Identifying Minefields and Verifying Clearance: Adapting Statistical Methods for UXO Target Detection

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

    Gilbert, Richard O.; O'Brien, Robert F.; Wilson, John E.

    2003-09-01

    It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development ofmore » statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.« less

  19. Design and Evaluation of Perceptual-based Object Group Selection Techniques

    NASA Astrophysics Data System (ADS)

    Dehmeshki, Hoda

    Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

  20. [Development of sample pretreatment techniques-rapid detection coupling methods for food security analysis].

    PubMed

    Huang, Yichun; Ding, Weiwei; Zhang, Zhuomin; Li, Gongke

    2013-07-01

    This paper summarizes the recent developments of the rapid detection methods for food security, such as sensors, optical techniques, portable spectral analysis, enzyme-linked immunosorbent assay, portable gas chromatograph, etc. Additionally, the applications of these rapid detection methods coupled with sample pretreatment techniques in real food security analysis are reviewed. The coupling technique has the potential to provide references to establish the selective, precise and quantitative rapid detection methods in food security analysis.

  1. Fluorescence hyperspectral imaging technique for foreign substance detection on fresh-cut lettuce.

    PubMed

    Mo, Changyeun; Kim, Giyoung; Kim, Moon S; Lim, Jongguk; Cho, Hyunjeong; Barnaby, Jinyoung Yang; Cho, Byoung-Kwan

    2017-09-01

    Non-destructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed to detect worms on fresh-cut lettuce. The optimal wavebands for detecting the worms were investigated using the one-way ANOVA and correlation analyses. The worm detection imaging algorithms, RSI-I (492-626)/492 , provided a prediction accuracy of 99.0%. The fluorescence HSI techniques indicated that the spectral images with a pixel size of 1 × 1 mm had the best classification accuracy for worms. The overall results demonstrate that fluorescence HSI techniques have the potential to detect worms on fresh-cut lettuce. In the future, we will focus on developing a multi-spectral imaging system to detect foreign substances such as worms, slugs and earthworms on fresh-cut lettuce. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  2. Effect of inherent location uncertainty on detection of stationary targets in noisy image sequences.

    PubMed

    Manjeshwar, R M; Wilson, D L

    2001-01-01

    The effect of inherent location uncertainty on the detection of stationary targets was determined in noisy image sequences. Targets were thick and thin projected cylinders mimicking arteries, catheters, and guide wires in medical imaging x-ray fluoroscopy. With the use of an adaptive forced-choice method, detection contrast sensitivity (the inverse of contrast) was measured both with and without marker cues that directed the attention of observers to the target location. With the probability correct clamped at 80%, contrast sensitivity increased an average of 77% when the marker was added to the thin-cylinder target. There was an insignificant effect on the thick cylinder. The large enhancement with the thin cylinder was obtained even though the target was located exactly in the center of a small panel, giving observers the impression that it was well localized. Psychometric functions consisting of d' plotted as a function of the square root of the signal-energy-to-noise-ratio gave a positive x intercept for the case of the thin cylinder without a marker. This x intercept, characteristic of uncertainty in other types of detection experiments, disappeared when the marker was added or when the thick cylinder was used. Inherent location uncertainty was further characterized by using four different markers with varying proximity to the target. Visual detection by human observers increased monotonically as the markers better localized the target. Human performance was modeled as a matched-filter detector with an uncertainty in the placement of the template. The removal of a location cue was modeled by introducing a location uncertainty of approximately equals 0.4 mm on the display device or only 7 microm on the retina, a size on the order of a single photoreceptor field. We conclude that detection is affected by target location uncertainty on the order of cellular dimensions, an observation with important implications for detection mechanisms in humans. In medical

  3. A new EMI system for detection and classification of challenging targets

    NASA Astrophysics Data System (ADS)

    Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.

    2013-06-01

    Advanced electromagnetic induction (EMI) sensors currently feature multi-axis illumination of targets and tri-axial vector sensing (e.g., MetalMapper), or exploit multi-static array data acquisition (e.g., TEMTADS). They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance relative to the previous generation of single-axis, monostatic sensors. However, these advances yet have to improve significantly our ability to classify small, deep, and otherwise challenging targets. Particularly, recent live-site discrimination studies at Camp Butner, NC and Camp Beale, CA have revealed that it is more challenging to detect and discriminate small munitions (with calibers ranging from 20 mm to 60 mm) than larger ones. In addition, a live-site test at the Massachusetts Military Reservation, MA highlighted the difficulties for current sensors to classify large, deep, and overlapping targets with high confidence. There are two main approaches to overcome these problems: 1) adapt advanced EMI models to the existing systems and 2) improve the detection limits of current sensors by modifying their hardware. In this paper we demonstrate a combined software/hardware approach that will provide extended detection range and spatial resolution to next-generation EMI systems; we analyze and invert EMI data to extract classification features for small and deep targets; and we propose a new system that features a large transmitter coil.

  4. A novel infrared small moving target detection method based on tracking interest points under complicated background

    NASA Astrophysics Data System (ADS)

    Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Bai, Shengjian; Xu, Wanying

    2014-07-01

    Infrared moving target detection is an important part of infrared technology. We introduce a novel infrared small moving target detection method based on tracking interest points under complicated background. Firstly, Difference of Gaussians (DOG) filters are used to detect a group of interest points (including the moving targets). Secondly, a sort of small targets tracking method inspired by Human Visual System (HVS) is used to track these interest points for several frames, and then the correlations between interest points in the first frame and the last frame are obtained. Last, a new clustering method named as R-means is proposed to divide these interest points into two groups according to the correlations, one is target points and another is background points. In experimental results, the target-to-clutter ratio (TCR) and the receiver operating characteristics (ROC) curves are computed experimentally to compare the performances of the proposed method and other five sophisticated methods. From the results, the proposed method shows a better discrimination of targets and clutters and has a lower false alarm rate than the existing moving target detection methods.

  5. Biosensor-based microRNA detection: techniques, design, performance, and challenges.

    PubMed

    Johnson, Blake N; Mutharasan, Raj

    2014-04-07

    The current state of biosensor-based techniques for amplification-free microRNA (miRNA) detection is critically reviewed. Comparison with non-sensor and amplification-based molecular techniques (MTs), such as polymerase-based methods, is made in terms of transduction mechanism, associated protocol, and sensitivity. Challenges associated with miRNA hybridization thermodynamics which affect assay selectivity and amplification bias are briefly discussed. Electrochemical, electromechanical, and optical classes of miRNA biosensors are reviewed in terms of transduction mechanism, limit of detection (LOD), time-to-results (TTR), multiplexing potential, and measurement robustness. Current trends suggest that biosensor-based techniques (BTs) for miRNA assay will complement MTs due to the advantages of amplification-free detection, LOD being femtomolar (fM)-attomolar (aM), short TTR, multiplexing capability, and minimal sample preparation requirement. Areas of future importance in miRNA BT development are presented which include focus on achieving high measurement confidence and multiplexing capabilities.

  6. An Efficient Moving Target Detection Algorithm Based on Sparsity-Aware Spectrum Estimation

    PubMed Central

    Shen, Mingwei; Wang, Jie; Wu, Di; Zhu, Daiyin

    2014-01-01

    In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results. PMID:25222035

  7. Reliable motion detection of small targets in video with low signal-to-clutter ratios

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

    Nichols, S.A.; Naylor, R.B.

    1995-07-01

    Studies show that vigilance decreases rapidly after several minutes when human operators are required to search live video for infrequent intrusion detections. Therefore, there is a need for systems which can automatically detect targets in live video and reserve the operator`s attention for assessment only. Thus far, automated systems have not simultaneously provided adequate detection sensitivity, false alarm suppression, and ease of setup when used in external, unconstrained environments. This unsatisfactory performance can be exacerbated by poor video imagery with low contrast, high noise, dynamic clutter, image misregistration, and/or the presence of small, slow, or erratically moving targets. This papermore » describes a highly adaptive video motion detection and tracking algorithm which has been developed as part of Sandia`s Advanced Exterior Sensor (AES) program. The AES is a wide-area detection and assessment system for use in unconstrained exterior security applications. The AES detection and tracking algorithm provides good performance under stressing data and environmental conditions. Features of the algorithm include: reliable detection with negligible false alarm rate of variable velocity targets having low signal-to-clutter ratios; reliable tracking of targets that exhibit motion that is non-inertial, i.e., varies in direction and velocity; automatic adaptation to both infrared and visible imagery with variable quality; and suppression of false alarms caused by sensor flaws and/or cutouts.« less

  8. Aspartate Aminotransferase (AST/GOT) and Alanine Aminotransferase (ALT/GPT) Detection Techniques

    PubMed Central

    Huang, Xing-Jiu; Choi, Yang-Kyu; Im, Hyung-Soon; Yarimaga, Oktay; Yoon, Euisik; Kim, Hak-Sung

    2006-01-01

    The levels of aspartate aminotransferase (AST/GOT) and alanine aminotransferase (ALT/GPT) in serum can help people diagnose body tissues especially the heart and the liver are injured or not. This article provides a comprehensive review of research activities that concentrate on AST/GOT and ALT/GPT detection techniques due to their clinical importance. The detection techniques include colorimetric, spectrophotometric, chemiluminescence, chromatography, fluorescence and UV absorbance, radiochemical, and electrochemical techniques. We devote the most attention on experimental principle. In some methods a few representative devices and important conclusions are presented.

  9. Intercomparison of gamma scattering, gammatography, and radiography techniques for mild steel nonuniform corrosion detection

    NASA Astrophysics Data System (ADS)

    Priyada, P.; Margret, M.; Ramar, R.; Shivaramu, Menaka, M.; Thilagam, L.; Venkataraman, B.; Raj, Baldev

    2011-03-01

    This paper focuses on the mild steel (MS) corrosion detection and intercomparison of results obtained by gamma scattering, gammatography, and radiography techniques. The gamma scattering non-destructive evaluation (NDE) method utilizes scattered gamma radiation for the detection of corrosion, and the scattering experimental setup is an indigenously designed automated personal computer (PC) controlled scanning system consisting of computerized numerical control (CNC) controlled six-axis source detector system and four-axis job positioning system. The system has been successfully used to quantify the magnitude of corrosion and the thickness profile of a MS plate with nonuniform corrosion, and the results are correlated with those obtained from the conventional gammatography and radiography imaging measurements. A simple and straightforward reconstruction algorithm to reconstruct the densities of the objects under investigation and an unambiguous interpretation of the signal as a function of material density at any point of the thick object being inspected is described. In this simple and straightforward method the density of the target need not be known and only the knowledge of the target material's mass attenuation coefficients (composition) for the incident and scattered energies is enough to reconstruct the density of the each voxel of the specimen being studied. The Monte Carlo (MC) numerical simulation of the phenomena is done using the Monte Carlo N-Particle Transport Code (MCNP) and the quantitative estimates of the values of signal-to-noise ratio for different percentages of MS corrosion derived from these simulations are presented and the spectra are compared with the experimental data. The gammatography experiments are carried out using the same PC controlled scanning system in a narrow beam, good geometry setup, and the thickness loss is estimated from the measured transmitted intensity. Radiography of the MS plates is carried out using 160 kV x

  10. Detection of genetically modified organisms in foods by DNA amplification techniques.

    PubMed

    García-Cañas, Virginia; Cifuentes, Alejandro; González, Ramón

    2004-01-01

    In this article, the different DNA amplification techniques that are being used for detecting genetically modified organisms (GMOs) in foods are examined. This study intends to provide an updated overview (including works published till June 2002) on the principal applications of such techniques together with their main advantages and drawbacks in GMO detection in foods. Some relevant facts on sampling, DNA isolation, and DNA amplification methods are discussed. Moreover; these analytical protocols are discuissed from a quantitative point of view, including the newest investigations on multiplex detection of GMOs in foods and validation of methods.

  11. Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

    PubMed Central

    Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

    2014-01-01

    Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

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

    NASA Astrophysics Data System (ADS)

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

    2017-06-01

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

  13. A survey of landmine detection using hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Makki, Ihab; Younes, Rafic; Francis, Clovis; Bianchi, Tiziano; Zucchetti, Massimo

    2017-02-01

    Hyperspectral imaging is a trending technique in remote sensing that finds its application in many different areas, such as agriculture, mapping, target detection, food quality monitoring, etc. This technique gives the ability to remotely identify the composition of each pixel of the image. Therefore, it is a natural candidate for the purpose of landmine detection, thanks to its inherent safety and fast response time. In this paper, we will present the results of several studies that employed hyperspectral imaging for the purpose of landmine detection, discussing the different signal processing techniques used in this framework for hyperspectral image processing and target detection. Our purpose is to highlight the progresses attained in the detection of landmines using hyperspectral imaging and to identify possible perspectives for future work, in order to achieve a better detection in real-time operation mode.

  14. A technique for thick polymer coating of inertial-confinement-fusion targets

    NASA Technical Reports Server (NTRS)

    Lee, M. C.; Feng, I.-A.; Wang, T. G.; Kim, H.-G.

    1983-01-01

    A technique to coat a stalk-mounted inertial-confinement fusion (ICF) target with a thick polymer layer has been successfully demonstrated. The polymer solution is first atomized, allowed to coalesce into a droplet, and positioned in a stable acoustic levitating field. The stalk-mounted ICF target is then moved into the acoustic field by manipulating a 3-D positioner to penetrate the surface membrane of the droplet, thus immersing the target in the levitated coating solution. The target inside the droplet is maintained at the center of the levitated liquid using the 3-D positional information provided by two orthogonally placed TV cameras until the drying process is completed. The basic components of the experimental apparatus, including an acoustic levitator, liquid sample deployment device, image acquisition instrumentation, and 3-D positioner, are briefly described.

  15. Detection of foliage-obscured vehicle using a multiwavelength polarimetric lidar

    USGS Publications Warehouse

    Tan, S.; Stoker, J.; Greenlee, S.

    2008-01-01

    Foliage obscured man-made targets detection and identification is of great interest to many applications. In this paper, the backscattered laser signals from a multiwavelength polarimetric lidar were used to detect a vehicle hidden inside a vegetated area. The Polarimetric reflectance data from the lidar at two separate laser wavelengths at 1064 nm and 532 nm revealed distinct target characteristics from both the vehicle and the vegetation. The results from this case study demonstrated the validity of the proposed lidar detection technique. Furthermore, the results could potentially lead to a lidar detection and identification technique for a wide variety of foliage-obscured man-made targets under various application scenarios. ?? 2007 IEEE.

  16. Measuring target detection performance in paradigms with high event rates.

    PubMed

    Bendixen, Alexandra; Andersen, Søren K

    2013-05-01

    Combining behavioral and neurophysiological measurements inevitably implies mutual constraints, such as when the neurophysiological measurement requires fast-paced stimulus presentation and hence the attribution of a behavioral response to a particular preceding stimulus becomes ambiguous. We develop and test a method for validly assessing behavioral detection performance in spite of this ambiguity. We examine four approaches taken in the literature to treat such situations. We analytically derive a new variant of computing the classical parameters of signal detection theory, hit and false alarm rates, adapted to fast-paced paradigms. Each of the previous approaches shows specific shortcomings (susceptibility towards response window choice, biased estimates of behavioral detection performance). Superior performance of our new approach is demonstrated for both simulated and empirical behavioral data. Further evidence is provided by reliable correspondence between behavioral performance and the N2b component as an electrophysiological indicator of target detection. The appropriateness of our approach is substantiated by both theoretical and empirical arguments. We demonstrate an easy-to-implement solution for measuring target detection performance independent of the rate of event presentation. Thus overcoming the measurement bias of previous approaches, our method will help to clarify the behavioral relevance of different measures of cortical activation. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  17. Reactive impinging-flow technique for polymer-electrolyte-fuel-cell electrode-defect detection

    NASA Astrophysics Data System (ADS)

    Zenyuk, Iryna V.; Englund, Nicholas; Bender, Guido; Weber, Adam Z.; Ulsh, Michael

    2016-11-01

    Reactive impinging flow (RIF) is a novel quality-control method for defect detection (i.e., reduction in Pt catalyst loading) in gas-diffusion electrodes (GDEs) on weblines. The technique uses infrared thermography to detect temperature of a nonflammable (<4% H2) reactive mixture of H2/O2 in N2 impinging and reacting on a Pt catalytic surface. In this paper, different GDE size defects (with catalyst-loading reductions of 25, 50, and 100%) are detected at various webline speeds (3.048 and 9.144 m min-1) and gas flowrates (32.5 or 50 standard L min-1). Furthermore, a model is developed and validated for the technique, and it is subsequently used to optimize operating conditions and explore the applicability of the technique to a range of defects. The model suggests that increased detection can be achieved by recting more of the impinging H2, which can be accomplished by placing blocking substrates on the top, bottom, or both of the GDE; placing a substrate on both results in a factor of four increase in the temperature differential, which is needed for smaller defect detection. Overall, the RIF technique is shown to be a promising route for in-line, high-speed, large-area detection of GDE defects on moving weblines.

  18. Drop-off Detection with the Long Cane: Effects of Different Cane Techniques on Performance

    PubMed Central

    Kim, Dae Shik; Emerson, Robert Wall; Curtis, Amy

    2010-01-01

    This study compared the drop-off detection performance with the two-point touch and constant contact cane techniques using a repeated-measures design with a convenience sample of 15 cane users with visual impairments. The constant contact technique was superior to the two-point touch technique in the drop-off detection rate and the 50% detection threshold. The findings may help an orientation and mobility instructor select an appropriate technique for a particular client or training situation. PMID:21209791

  19. From Pacemaker to Wearable: Techniques for ECG Detection Systems.

    PubMed

    Kumar, Ashish; Komaragiri, Rama; Kumar, Manjeet

    2018-01-11

    With the alarming rise in the deaths due to cardiovascular diseases (CVD), present medical research scenario places notable importance on techniques and methods to detect CVDs. As adduced by world health organization, technological proceeds in the field of cardiac function assessment have become the nucleus and heart of all leading research studies in CVDs in which electrocardiogram (ECG) analysis is the most functional and convenient tool used to test the range of heart-related irregularities. Most of the approaches present in the literature of ECG signal analysis consider noise removal, rhythm-based analysis, and heartbeat detection to improve the performance of a cardiac pacemaker. Advancements achieved in the field of ECG segments detection and beat classification have a limited evaluation and still require clinical approvals. In this paper, approaches on techniques to implement on-chip ECG detector for a cardiac pacemaker system are discussed. Moreover, different challenges regarding the ECG signal morphology analysis deriving from medical literature is extensively reviewed. It is found that robustness to noise, wavelet parameter choice, numerical efficiency, and detection performance are essential performance indicators required by a state-of-the-art ECG detector. Furthermore, many algorithms described in the existing literature are not verified using ECG data from the standard databases. Some ECG detection algorithms show very high detection performance with the total number of detected QRS complexes. However, the high detection performance of the algorithm is verified using only a few datasets. Finally, gaps in current advancements and testing are identified, and the primary challenge remains to be implementing bullseye test for morphology analysis evaluation.

  20. Key parameters design of an aerial target detection system on a space-based platform

    NASA Astrophysics Data System (ADS)

    Zhu, Hanlu; Li, Yejin; Hu, Tingliang; Rao, Peng

    2018-02-01

    To ensure flight safety of an aerial aircraft and avoid recurrence of aircraft collisions, a method of multi-information fusion is proposed to design the key parameter to realize aircraft target detection on a space-based platform. The key parameters of a detection wave band and spatial resolution using the target-background absolute contrast, target-background relative contrast, and signal-to-clutter ratio were determined. This study also presented the signal-to-interference ratio for analyzing system performance. Key parameters are obtained through the simulation of a specific aircraft. And the simulation results show that the boundary ground sampling distance is 30 and 35 m in the mid- wavelength infrared (MWIR) and long-wavelength infrared (LWIR) bands for most aircraft detection, and the most reasonable detection wavebands is 3.4 to 4.2 μm and 4.35 to 4.5 μm in the MWIR bands, and 9.2 to 9.8 μm in the LWIR bands. We also found that the direction of detection has a great impact on the detection efficiency, especially in MWIR bands.

  1. A Simple Ultrasonic Experiment Using a Phase Shift Detection Technique.

    ERIC Educational Resources Information Center

    Yunus, W. Mahmood Mat; Ahmad, Maulana

    1996-01-01

    Describes a simple ultrasonic experiment that can be used to measure the purity of liquid samples by detecting variations in the velocity of sound. Uses a phase shift detection technique that incorporates the use of logic gates and a piezoelectric transducer. (JRH)

  2. Underwater Turbulence Detection Using Gated Wavefront Sensing Technique

    PubMed Central

    Bi, Ying; Xu, Xiping; Chow, Eddy Mun Tik

    2018-01-01

    Laser sensing has been applied in various underwater applications, ranging from underwater detection to laser underwater communications. However, there are several great challenges when profiling underwater turbulence effects. Underwater detection is greatly affected by the turbulence effect, where the acquired image suffers excessive noise, blurring, and deformation. In this paper, we propose a novel underwater turbulence detection method based on a gated wavefront sensing technique. First, we elaborate on the operating principle of gated wavefront sensing and wavefront reconstruction. We then setup an experimental system in order to validate the feasibility of our proposed method. The effect of underwater turbulence on detection is examined at different distances, and under different turbulence levels. The experimental results obtained from our gated wavefront sensing system indicate that underwater turbulence can be detected and analyzed. The proposed gated wavefront sensing system has the advantage of a simple structure and high detection efficiency for underwater environments. PMID:29518889

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

    DTIC Science & Technology

    2016-06-01

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

  4. Targeted Feature Detection for Data-Dependent Shotgun Proteomics.

    PubMed

    Weisser, Hendrik; Choudhary, Jyoti S

    2017-08-04

    Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification ("FFId"), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between "internal" and "external" (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the "uncertain" feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards that provide a known

  5. Intrinsic Tryptophan Fluorescence in the Detection and Analysis of Proteins: A Focus on Förster Resonance Energy Transfer Techniques

    PubMed Central

    Ghisaidoobe, Amar B. T.; Chung, Sang J.

    2014-01-01

    Förster resonance energy transfer (FRET) occurs when the distance between a donor fluorophore and an acceptor is within 10 nm, and its application often necessitates fluorescent labeling of biological targets. However, covalent modification of biomolecules can inadvertently give rise to conformational and/or functional changes. This review describes the application of intrinsic protein fluorescence, predominantly derived from tryptophan (λEX ∼ 280 nm, λEM ∼ 350 nm), in protein-related research and mainly focuses on label-free FRET techniques. In terms of wavelength and intensity, tryptophan fluorescence is strongly influenced by its (or the protein’s) local environment, which, in addition to fluorescence quenching, has been applied to study protein conformational changes. Intrinsic Förster resonance energy transfer (iFRET), a recently developed technique, utilizes the intrinsic fluorescence of tryptophan in conjunction with target-specific fluorescent probes as FRET donors and acceptors, respectively, for real time detection of native proteins. PMID:25490136

  6. Quantitative methods and detection techniques in hyperspectral imaging involving medical and other applications

    NASA Astrophysics Data System (ADS)

    Roy, Ankita

    2007-12-01

    like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the deoxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while beta-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease.

  7. Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

    NASA Astrophysics Data System (ADS)

    Zhou, Anran; Xie, Weixin; Pei, Jihong

    2018-06-01

    Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

  8. Advanced Doppler radar physiological sensing technique for drone detection

    NASA Astrophysics Data System (ADS)

    Yoon, Ji Hwan; Xu, Hao; Garcia Carrillo, Luis R.

    2017-05-01

    A 24 GHz medium-range human detecting sensor, using the Doppler Radar Physiological Sensing (DRPS) technique, which can also detect unmanned aerial vehicles (UAVs or drones), is currently under development for potential rescue and anti-drone applications. DRPS systems are specifically designed to remotely monitor small movements of non-metallic human tissues such as cardiopulmonary activity and respiration. Once optimized, the unique capabilities of DRPS could be used to detect UAVs. Initial measurements have shown that DRPS technology is able to detect moving and stationary humans, as well as largely non-metallic multi-rotor drone helicopters. Further data processing will incorporate pattern recognition to detect multiple signatures (motor vibration and hovering patterns) of UAVs.

  9. DNA hybridization detection on electrical microarrays using coulostatic pulse technique.

    PubMed

    Dharuman, V; Nebling, E; Grunwald, T; Albers, J; Blohm, L; Elsholz, B; Wörl, R; Hintsche, R

    2006-12-15

    We demonstrated a novel application of transient coulostatic pulse technique for the detection of label free DNA hybridization on nm-sized gold interdigitated ultramicroelectrode arrays (Au-IDA) made in silicon technology. The array consists of eight different positions with an Au-IDA pair at each position arranged on the Si-based Biochip. Immobilization of capture probes onto the Au-IDA was accomplished by self-assembling of thiol-modified oligonucleotides. Target hybridization was indicated by a change in the magnitude of the time dependant potential relaxation curve in presence of electroactive Fe(CN)(6)(3-) in the phosphate buffer solution. While complementary DNA hybridization showed 50% increase in the relaxation potential, the non-complementary DNA showed a negligible change. A constant behaviour was noted for all positions. The dsDNA specific intercalating molecule, methylene blue, was found to be enhancing the discrimination effect. The changes in the relaxation potential curves were further corroborated following the ELISA like experiments using ExtraAvidine alkaline phosphatase labelling and redox recycling of para-aminophenol phosphate at IDAs. The coulostatic pulse technique was shown to be useful for identifying DNA sequences from brain tumour gene CK20, human herpes simplex virus, cytomegalovirus, Epstein-Barr virus and M13 phage. Compared to the hybridization of short chain ONTs (27 mers), the hybridization of long chain M13 phage DNA showed three times higher increase in the relaxation curves. The method is fast enough to monitor hybridization interactions in milli or microsecond time scales and is well suitable for miniaturization and integration compared to the common impedance techniques for developing capacitative DNA sensors.

  10. Staircase-scene-based nonuniformity correction in aerial point target detection systems.

    PubMed

    Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

    2016-09-01

    Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections.

  11. A Multi-object Exoplanet Detecting Technique

    NASA Astrophysics Data System (ADS)

    Zhang, K.

    2011-05-01

    Exoplanet exploration is not only a meaningful astronomical action, but also has a close relation with the extra-terrestrial life. High resolution echelle spectrograph is the key instrument for measuring stellar radial velocity (RV). But with higher precision, better environmental stability and higher cost are required. An improved technique of RV means invented by David J. Erskine in 1997, External Dispersed Interferometry (EDI), can increase the RV measuring precision by combining the moderate resolution spectrograph with a fixed-delay Michelson interferometer. LAMOST with large aperture and large field of view is equipped with 16 multi-object low resolution fiber spectrographs. And these spectrographs are capable to work in medium resolution mode (R=5{K}˜10{K}). LAMOST will be one of the most powerful exoplanet detecting systems over the world by introducing EDI technique. The EDI technique is a new technique for developing astronomical instrumentation in China. The operating theory of EDI was generally verified by a feasibility experiment done in 2009. And then a multi-object exoplanet survey system based on LAMOST spectrograph was proposed. According to this project, three important tasks have been done as follows: Firstly, a simulation of EDI operating theory contains the stellar spectrum model, interferometer transmission model, spectrograph mediation model and RV solution model. In order to meet the practical situation, two detecting modes, temporal and spatial phase-stepping methods, are separately simulated. The interference spectrum is analyzed with Fourier transform algorithm and a higher resolution conventional spectrum is resolved. Secondly, an EDI prototype is composed of a multi-object interferometer prototype and the LAMOST spectrograph. Some ideas are used in the design to reduce the effect of central obscuration, for example, modular structure and external/internal adjusting frames. Another feasibility experiment was done at Xinglong Station in

  12. Three plot correlation-based small infrared target detection in dense sun-glint environment for infrared search and track

    NASA Astrophysics Data System (ADS)

    Kim, Sungho; Choi, Byungin; Kim, Jieun; Kwon, Soon; Kim, Kyung-Tae

    2012-05-01

    This paper presents a separate spatio-temporal filter based small infrared target detection method to address the sea-based infrared search and track (IRST) problem in dense sun-glint environment. It is critical to detect small infrared targets such as sea-skimming missiles or asymmetric small ships for national defense. On the sea surface, sun-glint clutters degrade the detection performance. Furthermore, if we have to detect true targets using only three images with a low frame rate camera, then the problem is more difficult. We propose a novel three plot correlation filter and statistics based clutter reduction method to achieve robust small target detection rate in dense sun-glint environment. We validate the robust detection performance of the proposed method via real infrared test sequences including synthetic targets.

  13. A passive infrared ice detection technique for helicopter applications

    NASA Technical Reports Server (NTRS)

    Dershowitz, Adam L.; Hansman, R. John, Jr.

    1991-01-01

    A technique has been developed, and successfully tested, to detect icing remotely on helicopter rotor blades. Using passive infrared (IR) thermometry it is possible to detect the warming caused by latent heat released as supercooled water freezes. During icing, the ice accretion region on the leading edge of the blade is found to be warmer than the uniced trailing edge resulting in a chordwise temperature profile characteristic of icing. Preliminary tests, using an IR Thermal video system, were conducted on a static model in the NASA Icing Research Tunnel (IRT) for a variety of wet (glaze) and dry (rime) ice conditions. A prototype detector system was built consisting of a single point IR pyrometer, and experiments were run on a small scale rotor model. Using this prototype detector, the characteristic chordwise temperature profiles were again observed for a range of icing conditions. Several signal processing methods were investigated, to allow automatic recognition of the icing signature. Additionally, several implementation issues were considered. Based on both the static and subscale rotor tests, where ice was successfully detected, the passive IR technique appears to be promising for rotor ice detection.

  14. Reactive impinging-flow technique for polymer-electrolyte-fuel-cell electrode-defect detection

    DOE PAGES

    Zenyuk, Iryna V.; Englund, Nicholas; Bender, Guido; ...

    2016-09-29

    Reactive impinging flow (RIF) is a novel quality-control method for defect detection (i.e., reduction in Pt catalyst loading) in gas-diffusion electrodes (GDEs) on weblines. The technique uses infrared thermography to detect temperature of a nonflammable (<4% H 2) reactive mixture of H 2/O 2 in N 2 impinging and reacting on a Pt catalytic surface. In this article, different GDE size defects (with catalyst-loading reductions of 25, 50, and 100%) are detected at various webline speeds (3.048 and 9.144 m min -1) and gas flowrates (32.5 or 50 standard L min -1). Furthermore, a model is developed and validated formore » the technique, and it is subsequently used to optimize operating conditions and explore the applicability of the technique to a range of defects. The model suggests that increased detection can be achieved by recting more of the impinging H 2, which can be accomplished by placing blocking substrates on the top, bottom, or both of the GDE; placing a substrate on both results in a factor of four increase in the temperature differential, which is needed for smaller defect detection. Lastly, overall, the RIF technique is shown to be a promising route for in-line, high-speed, large-area detection of GDE defects on moving weblines.« less

  15. Target-protecting dumbbell molecular probe against exonucleases digestion for sensitive detection of ATP and streptavidin.

    PubMed

    Chen, Jinyang; Liu, Yucheng; Ji, Xinghu; He, Zhike

    2016-09-15

    In this work, a versatile dumbbell molecular (DM) probe was designed and employed in the sensitively homogeneous bioassay. In the presence of target molecule, the DM probe was protected from the digestion of exonucleases. Subsequently, the protected DM probe specifically bound to the intercalation dye and resulted in obvious fluorescence signal which was used to determine the target molecule in return. This design allows specific and versatile detection of diverse targets with easy operation and no sophisticated fluorescence labeling. Integrating the idea of target-protecting DM probe with adenosine triphosphate (ATP) involved ligation reaction, the DM probe with 5'-end phosphorylation was successfully constructed for ATP detection, and the limitation of detection was found to be 4.8 pM. Thanks to its excellent selectivity and sensitivity, this sensing strategy was used to detect ATP spiked in human serum as well as cellular ATP. Moreover, the proposed strategy was also applied in the visual detection of ATP in droplet-based microfluidic platform with satisfactory results. Similarly, combining the principle of target-protecting DM probe with streptavidin (SA)-biotin interaction, the DM probe with 3'-end biotinylation was developed for selective and sensitive SA determination, which demonstrated the robustness and versatility of this design. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2007-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-11-01

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

  18. New detection targets for amyloid-reactive probes: spectroscopic recognition of bacterial spores

    NASA Astrophysics Data System (ADS)

    Jones, Guilford, II; Landsman, Pavel

    2005-05-01

    We report characteristic changes in fluorescence of amyloid-binding dyes Thioflavin T (TfT), pinacyanol (PIN) and related dyes, caused by their interaction with suspended Bacillus spore cultures (B. subtilis, B thuringiensis). The gain in TfT emission in the presence of spores allowed their immediate detection in aqueous suspensions, with a sensitivity limit of < 105 spores per ml. The spectroscopic signatures are consistent with a large number of binding sites for the two dyes on spore coats. The possible structural relationship of these dye binding loci with characteristic motifs (β-stacks) of amyloid deposits and other misfolded protein formations suggests new designs for probing biocontamination and also for clinical studies of non-microbial human pathogens (e.g., amyloid-related protein aggregates in prion-related transmissible encephalopathies or in Alzheimer's disease). Also reported is a special screening technique that was designed and used herein for calibration of new detection probes and assays for spore detection. It employed spectroscopic interactions between the candidate amyloid stains and poly(vinylpyrrolidone)-coated colloid silica (Percoll) nanoparticles that also display remarkable parallelism with the corresponding dye-amyloid and dye-spore reactivities. Percoll may thus find new applications as a convenient non-biological structural model mimicking the putative probe-targeted motifs in both classes of bioanalytes. These findings are important in the design of new probes and assays for important human pathogens (i.e. bacterial spores and amyloidogenic protein aggregates).

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

    NASA Astrophysics Data System (ADS)

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

    2008-10-01

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

  20. Hand-held optical imager (Gen-2): improved instrumentation and target detectability

    PubMed Central

    Gonzalez, Jean; DeCerce, Joseph; Erickson, Sarah J.; Martinez, Sergio L.; Nunez, Annie; Roman, Manuela; Traub, Barbara; Flores, Cecilia A.; Roberts, Seigbeh M.; Hernandez, Estrella; Aguirre, Wenceslao; Kiszonas, Richard

    2012-01-01

    Abstract. Hand-held optical imagers are developed by various researchers towards reflectance-based spectroscopic imaging of breast cancer. Recently, a Gen-1 handheld optical imager was developed with capabilities to perform two-dimensional (2-D) spectroscopic as well as three-dimensional (3-D) tomographic imaging studies. However, the imager was bulky with poor surface contact (∼30%) along curved tissues, and limited sensitivity to detect targets consistently. Herein, a Gen-2 hand-held optical imager that overcame the above limitations of the Gen-1 imager has been developed and the instrumentation described. The Gen-2 hand-held imager is less bulky, portable, and has improved surface contact (∼86%) on curved tissues. Additionally, the forked probe head design is capable of simultaneous bilateral reflectance imaging of both breast tissues, and also transillumination imaging of a single breast tissue. Experimental studies were performed on tissue phantoms to demonstrate the improved sensitivity in detecting targets using the Gen-2 imager. The improved instrumentation of the Gen-2 imager allowed detection of targets independent of their location with respect to the illumination points, unlike in Gen-1 imager. The developed imager has potential for future clinical breast imaging with enhanced sensitivity, via both reflectance and transillumination imaging. PMID:23224163

  1. Effect of radar frequency on the detection of shaped (low RCS) targets

    NASA Astrophysics Data System (ADS)

    Moraitis, D.; Alland, S.

    The use of shaping to reduce the radar cross-section (RCS) of aircraft and missiles can result in the RCS varying significantly with radar operating frequency. This RCS sensitivity to frequency should be considered when selecting radar frequency and should be accounted for when evaluating radar performance. A detection range increase for shaped (low RCS) targets of a factor of two or greater can be realized for lower frequency radar (e.g., UHF-Band or L-Band) when compared to higher frequency radar (C-Band or X-Band). For low flying (sea skimming) targets, the RCS variation with frequency for shaped (low RCS) targets neutralizes the advantage that higher radar frequencies realize in multipath propagation resulting in approximately the same detection range across the radar bands from UHF to X-Band.

  2. Early Oscillation Detection Technique for Hybrid DC/DC Converters

    NASA Technical Reports Server (NTRS)

    Wang, Bright L.

    2011-01-01

    Oscillation or instability is a situation that must be avoided for reliable hybrid DC/DC converters. A real-time electronics measurement technique was developed to detect catastrophic oscillations at early stages for hybrid DC/DC converters. It is capable of identifying low-level oscillation and determining the degree of the oscillation at a unique frequency for every individual model of the converters without disturbing their normal operations. This technique is specially developed for space-used hybrid DC/DC converters, but it is also suitable for most of commercial and military switching-mode power supplies. This is a weak-electronic-signal detection technique to detect hybrid DC/DC converter oscillation presented as a specific noise signal at power input pins. It is based on principles of feedback control loop oscillation and RF signal modulations, and is realized by using signal power spectral analysis. On the power spectrum, a channel power amplitude at characteristic frequency (CPcf) and a channel power amplitude at switching frequency (CPsw) are chosen as oscillation level indicators. If the converter is stable, the CPcf is a very small pulse and the CPsw is a larger, clear, single pulse. At early stage of oscillation, the CPcf increases to a certain level and the CPsw shows a small pair of sideband pulses around it. If the converter oscillates, the CPcf reaches to a higher level and the CPsw shows more high-level sideband pulses. A comprehensive stability index (CSI) is adopted as a quantitative measure to accurately assign a degree of stability to a specific DC/DC converter. The CSI is a ratio of normal and abnormal power spectral density, and can be calculated using specified and measured CPcf and CPsw data. The novel and unique feature of this technique is the use of power channel amplitudes at characteristic frequency and switching frequency to evaluate stability and identify oscillations at an early stage without interfering with a DC/DC converter s

  3. Drivers' detection of roadside targets when driving vehicles with three headlight systems during high beam activation.

    PubMed

    Reagan, Ian J; Brumbelow, Matthew L

    2017-02-01

    A previous open-road experiment indicated that curve-adaptive HID headlights driven with low beams improved drivers' detection of low conspicuity targets compared with fixed halogen and fixed HID low beam systems. The current study used the same test environment and targets to assess whether drivers' detection of targets was affected by the same three headlight systems when using high beams. Twenty drivers search and responded for 60 8×12inch targets of high or low reflectance that were distributed evenly across straight and curved road sections as they drove at 30 mph on an unlit two-lane rural road. The results indicate that target detection performance was generally similar across the three systems. However, one interaction indicated that drivers saw low reflectance targets on straight road sections from further away when driving with the fixed halogen high beam condition compared with curve-adaptive HID high beam headlights and also indicated a possible benefit for the curve-adaptive HID high beams for high reflectance targets placed on the inside of curves. The results of this study conflict with the previous study of low beams, which showed a consistent benefit for the curve-adaptive HID low beams for targets placed on curves compared with fixed HID and fixed halogen low beam conditions. However, a comparison of mean detection distances from the two studies indicated uniformly longer mean target detection distances for participants driving with high beams and implicates the potential visibility benefits for systems that optimize proper high beam use. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Detecting Proxima b’s Atmosphere with JWST Targeting CO2 at 15 μm Using a High-pass Spectral Filtering Technique

    NASA Astrophysics Data System (ADS)

    Snellen, I. A. G.; Désert, J.-M.; Waters, L. B. F. M.; Robinson, T.; Meadows, V.; van Dishoeck, E. F.; Brandl, B. R.; Henning, T.; Bouwman, J.; Lahuis, F.; Min, M.; Lovis, C.; Dominik, C.; Van Eylen, V.; Sing, D.; Anglada-Escudé, G.; Birkby, J. L.; Brogi, M.

    2017-08-01

    Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μm using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope (JWST). At superior conjunction, the planet is expected to show a contrast of up to 100 ppm with respect to the star. At a spectral resolving power of R = 1790-2640, about 100 spectral CO2 features are visible within the 13.2-15.8 μm (3B) band, which can be combined to boost the planet atmospheric signal by a factor of 3-4, depending on the atmospheric temperature structure and CO2 abundance. If atmospheric conditions are favorable (assuming an Earth-like atmosphere), with this new application to the cross-correlation technique, carbon dioxide can be detected within a few days of JWST observations. However, this can only be achieved if both the instrumental spectral response and the stellar spectrum can be determined to a relative precision of ≤1 × 10-4 between adjacent spectral channels. Absolute flux calibration is not required, and the method is insensitive to the strong broadband variability of the host star. Precise calibration of the spectral features of the host star may only be attainable by obtaining deep observations of the system during inferior conjunction that serve as a reference. The high-pass filter spectroscopic technique with the MIRI MRS can be tested on warm Jupiters, Neptunes, and super-Earths with significantly higher planet/star contrast ratios than the Proxima system.

  5. Wear Detection of Drill Bit by Image-based Technique

    NASA Astrophysics Data System (ADS)

    Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

    2018-03-01

    Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

  6. Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

    PubMed

    Li, Miao; Li, Jun; Zhou, Yiyu

    2015-12-08

    The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

  7. Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

    PubMed Central

    Li, Miao; Li, Jun; Zhou, Yiyu

    2015-01-01

    The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

  8. Clustering Categorical Data Using Community Detection Techniques

    PubMed Central

    2017-01-01

    With the advent of the k-modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in k-modes makes it hard to reach a good clustering without resorting to many trials. Recently proposed methods for better initialization are deterministic and reduce the clustering cost considerably. A variety of initialization methods differ in how the heuristics chooses the set of initial centers. In this paper, we address the clustering problem for categorical data from the perspective of community detection. Instead of initializing k modes and running several iterations, our scheme, CD-Clustering, builds an unweighted graph and detects highly cohesive groups of nodes using a fast community detection technique. The top-k detected communities by size will define the k modes. Evaluation on ten real categorical datasets shows that our method outperforms the existing initialization methods for k-modes in terms of accuracy, precision, and recall in most of the cases. PMID:29430249

  9. A comparison of robust principal component analysis techniques for buried object detection in downward looking GPR sensor data

    NASA Astrophysics Data System (ADS)

    Pinar, Anthony; Havens, Timothy C.; Rice, Joseph; Masarik, Matthew; Burns, Joseph; Thelen, Brian

    2016-05-01

    Explosive hazards are a deadly threat in modern conflicts; hence, detecting them before they cause injury or death is of paramount importance. One method of buried explosive hazard discovery relies on data collected from ground penetrating radar (GPR) sensors. Threat detection with downward looking GPR is challenging due to large returns from non-target objects and clutter. This leads to a large number of false alarms (FAs), and since the responses of clutter and targets can form very similar signatures, classifier design is not trivial. One approach to combat these issues uses robust principal component analysis (RPCA) to enhance target signatures while suppressing clutter and background responses, though there are many versions of RPCA. This work applies some of these RPCA techniques to GPR sensor data and evaluates their merit using the peak signal-to-clutter ratio (SCR) of the RPCA-processed B-scans. Experimental results on government furnished data show that while some of the RPCA methods yield similar results, there are indeed some methods that outperform others. Furthermore, we show that the computation time required by the different RPCA methods varies widely, and the selection of tuning parameters in the RPCA algorithms has a major effect on the peak SCR.

  10. A new method for QRS detection in ECG signals using QRS-preserving filtering techniques.

    PubMed

    Sharma, Tanushree; Sharma, Kamalesh K

    2018-03-28

    Detection of QRS complexes in ECG signals is required for various purposes such as determination of heart rate, feature extraction and classification. The problem of automatic QRS detection in ECG signals is complicated by the presence of noise spectrally overlapping with the QRS frequency range. As a solution to this problem, we propose the use of least-squares-optimisation-based smoothing techniques that suppress the noise peaks in the ECG while preserving the QRS complexes. We also propose a novel nonlinear transformation technique that is applied after the smoothing operations, which equalises the QRS amplitudes without boosting the supressed noise peaks. After these preprocessing operations, the R-peaks can finally be detected with high accuracy. The proposed technique has a low computational load and, therefore, it can be used for real-time QRS detection in a wearable device such as a Holter monitor or for fast offline QRS detection. The offline and real-time versions of the proposed technique have been evaluated on the standard MIT-BIH database. The offline implementation is found to perform better than state-of-the-art techniques based on wavelet transforms, empirical mode decomposition, etc. and the real-time implementation also shows improved performance over existing real-time QRS detection techniques.

  11. Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

    NASA Astrophysics Data System (ADS)

    Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

    2015-09-01

    As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

  12. Target Detection of Quantum Illumination Receiver Based on Photon-subtracted Entanglement State

    NASA Astrophysics Data System (ADS)

    Chi, Jiao; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

    2017-12-01

    We theoretically propose a quantum illumination receiver based on the ideal photon-subtracted two-mode squeezed state (PSTMSS) to efficiently detect the noise-hidden target. This receiver is generated by applying an optical parametric amplifier (OPA) to the cross correlation detection. With analyzing the output performance, it is found that OPA as a preposition technology of the receiver can contribute to the PSTMSS by significantly reducing the error probability than that of the general two-mode squeezed state (TMSS). Comparing with TMSS, the signal-to-noise ratio of quantum illumination based on ideal PSTMSS and OPA is improved more than 4 dB under an optimal gain of OPA. This work may provide a potential improvement in the application of accurate target detection when two kinds of resource have the identical real squeezing parameter.

  13. Synchronous detection of miRNAs, their targets and downstream proteins in transferred FFPE sections: applications in clinical and basic research.

    PubMed

    Zhao, Jin-yao; Liu, Chun-qing; Zhao, He-nan; Ding, Yan-Fang; Bi, Tie; Wang, Bo; Lin, Xing-chi; Guo, Gordon; Cui, Shi-ying

    2012-10-01

    After discovering new miRNAs, it is often difficult to determine their targets and effects on downstream protein expression. In situ hybridization (ISH) and immunohistochemistry (IHC) are two commonly used methods for clinical diagnosis and basic research. We used an optimized technique that simultaneously detects miRNAs, their binding targets and corresponding proteins on transferred serial formalin fixed paraffin embedded (FFPE) sections from patients. Combined with bioinformatics, this method was used to validate the reciprocal expression of specific miRNAs and targets that were detected by ISH, as well as the expression of downstream proteins that were detected by IHC. A complete analysis was performed using a limited number of transferred serial FFPE sections that had been stored for 1-4 years at room temperature. Some sections had even been previously stained with H&E. We identified a miRNA that regulates epithelial ovarian cancer, along with its candidate target and related downstream protein. These findings were directly validated using sub-cellular components obtained from the same patient sample. In addition, the expression of Nephrin (a podocyte marker) and Stmn1 (a recently identified marker related to glomerular development) were confirmed in transferred FFPE sections of mouse kidney. This procedure may be adapted for clinical diagnosis and basic research, providing a qualitative and efficient method to dissect the detailed spatial expression patterns of miRNA pathways in FFPE tissue, especially in cases where only a small biopsy sample can be obtained. Copyright © 2012 Elsevier Inc. All rights reserved.

  14. Fault detection techniques for complex cable shield topologies

    NASA Astrophysics Data System (ADS)

    Coonrod, Kurt H.; Davis, Stuart L.; McLemore, Donald P.

    1994-09-01

    This document presents the results of a basic principles study which investigated technical approaches for developing fault detection techniques for use on cables with complex shielding topologies. The study was limited to those approaches which could realistically be implemented on a fielded cable, i.e., approaches which would require partial disassembly of a cable were not pursued. The general approach used was to start with present transfer impedance measurement techniques and modify their use to achieve the best possible measurement range. An alternative test approach, similar to a sniffer type test, was also investigated.

  15. Application of Geologic Mapping Techniques and Autonomous Feature Detection to Future Exploration of Europa

    NASA Astrophysics Data System (ADS)

    Bunte, M. K.; Tanaka, K. L.; Doggett, T.; Figueredo, P. H.; Lin, Y.; Greeley, R.; Saripalli, S.; Bell, J. F.

    2013-12-01

    Europa's extremely young surface age, evidence for extensive resurfacing, and indications of a sub-surface ocean elevate its astrobiological potential for habitable environments and make it a compelling focus for study. Knowledge of the global distribution and timing of Europan geologic units is a key step in understanding the history of the satellite and for identifying areas relevant for exploration. I have produced a 1:15M scale global geologic map of Europa which represents a proportionate distribution of four unit types and associated features: plains, linea, chaos, and crater materials. Mapping techniques differ somewhat from other planetary maps but do provide a method to establish stratigraphic markers and to illustrate the surface history through four periods of formation as a function of framework lineament cross-cutting relationships. Correlations of observed features on Europa with Earth analogs enforce a multi-process theory for formation rather than the typical reliance on the principle of parsimony. Lenticulae and microchaos are genetically similar and most likely form by diapirism. Platy and blocky chaos units, endmembers of archetypical chaos, are best explained by brine mobilization. Ridges account for the majority of lineaments and may form by a number of methods indicative of local conditions; most form by either tidal pumping or shear heating. The variety of morphologies exhibited by bands indicates that multiple formation mechanisms apply once fracturing of the brittle surface over a ductile subsurface is initiated. Mapping results support the interpretation that Europa's shell has thickened over time resulting in changes in the style and intensity of deformation. Mapping serves as an index for change detection and classification, aids in pre-encounter targeting, and supports the selection of potential landing sites. Highest priority target areas are those which indicate geophysical activity by the presence of volcanic plumes, outgassing, or

  16. Multisensor fusion for 3D target tracking using track-before-detect particle filter

    NASA Astrophysics Data System (ADS)

    Moshtagh, Nima; Romberg, Paul M.; Chan, Moses W.

    2015-05-01

    This work presents a novel fusion mechanism for estimating the three-dimensional trajectory of a moving target using images collected by multiple imaging sensors. The proposed projective particle filter avoids the explicit target detection prior to fusion. In projective particle filter, particles that represent the posterior density (of target state in a high-dimensional space) are projected onto the lower-dimensional observation space. Measurements are generated directly in the observation space (image plane) and a marginal (sensor) likelihood is computed. The particles states and their weights are updated using the joint likelihood computed from all the sensors. The 3D state estimate of target (system track) is then generated from the states of the particles. This approach is similar to track-before-detect particle filters that are known to perform well in tracking dim and stealthy targets in image collections. Our approach extends the track-before-detect approach to 3D tracking using the projective particle filter. The performance of this measurement-level fusion method is compared with that of a track-level fusion algorithm using the projective particle filter. In the track-level fusion algorithm, the 2D sensor tracks are generated separately and transmitted to a fusion center, where they are treated as measurements to the state estimator. The 2D sensor tracks are then fused to reconstruct the system track. A realistic synthetic scenario with a boosting target was generated, and used to study the performance of the fusion mechanisms.

  17. High-Throughput, Protein-Targeted Biomolecular Detection Using Frequency-Domain Faraday Rotation Spectroscopy.

    PubMed

    Murdock, Richard J; Putnam, Shawn A; Das, Soumen; Gupta, Ankur; Chase, Elyse D Z; Seal, Sudipta

    2017-03-01

    A clinically relevant magneto-optical technique (fd-FRS, frequency-domain Faraday rotation spectroscopy) for characterizing proteins using antibody-functionalized magnetic nanoparticles (MNPs) is demonstrated. This technique distinguishes between the Faraday rotation of the solvent, iron oxide core, and functionalization layers of polyethylene glycol polymers (spacer) and model antibody-antigen complexes (anti-BSA/BSA, bovine serum albumin). A detection sensitivity of ≈10 pg mL -1 and broad detection range of 10 pg mL -1 ≲ c BSA ≲ 100 µg mL -1 are observed. Combining this technique with predictive analyte binding models quantifies (within an order of magnitude) the number of active binding sites on functionalized MNPs. Comparative enzyme-linked immunosorbent assay (ELISA) studies are conducted, reproducing the manufacturer advertised BSA ELISA detection limits from 1 ng mL -1 ≲ c BSA ≲ 500 ng mL -1 . In addition to the increased sensitivity, broader detection range, and similar specificity, fd-FRS can be conducted in less than ≈30 min, compared to ≈4 h with ELISA. Thus, fd-FRS is shown to be a sensitive optical technique with potential to become an efficient diagnostic in the chemical and biomolecular sciences. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

    NASA Astrophysics Data System (ADS)

    Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

    2017-02-01

    Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

  19. Two-dimensional hidden semantic information model for target saliency detection and eyetracking identification

    NASA Astrophysics Data System (ADS)

    Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao

    2018-01-01

    Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.

  20. Clustering analysis of moving target signatures

    NASA Astrophysics Data System (ADS)

    Martone, Anthony; Ranney, Kenneth; Innocenti, Roberto

    2010-04-01

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

  1. Target Detection and Classification Using Seismic and PIR Sensors

    DTIC Science & Technology

    2012-06-01

    time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

  2. Comparative evaluation of PCR amplification of RLEP, 16S rRNA, rpoT and Sod A gene targets for detection of M. leprae DNA from clinical and environmental samples.

    PubMed

    Turankar, Ravindra P; Pandey, Shradha; Lavania, Mallika; Singh, Itu; Nigam, Astha; Darlong, Joydeepa; Darlong, Fam; Sengupta, Utpal

    2015-03-01

    PCR assay is a highly sensitive, specific and reliable diagnostic tool for the identification of pathogens in many infectious diseases. Genome sequencing Mycobacterium leprae revealed several gene targets that could be used for the detection of DNA from clinical and environmental samples. The PCR sensitivity of particular gene targets for specific clinical and environmental isolates has not yet been established. The present study was conducted to compare the sensitivity of RLEP, rpoT, Sod A and 16S rRNA gene targets in the detection of M. leprae in slit skin smear (SSS), blood, soil samples of leprosy patients and their surroundings. Leprosy patients were classified into Paucibacillary (PB) and Multibacillary (MB) types. Ziehl-Neelsen (ZN) staining method for all the SSS samples and Bacteriological Index (BI) was calculated for all patients. Standard laboratory protocol was used for DNA extraction from SSS, blood and soil samples. PCR technique was performed for the detection of M. leprae DNA from all the above-mentioned samples. RLEP gene target was able to detect the presence of M. leprae in 83% of SSS, 100% of blood samples and in 36% of soil samples and was noted to be the best out of all other gene targets (rpoT, Sod A and 16S rRNA). It was noted that the RLEP gene target was able to detect the highest number (53%) of BI-negative leprosy patients amongst all the gene targets used in this study. Amongst all the gene targets used in this study, PCR positivity using RLEP gene target was the highest in all the clinical and environmental samples. Further, the RLEP gene target was able to detect 53% of blood samples as positive in BI-negative leprosy cases indicating its future standardization and use for diagnostic purposes. Copyright © 2015 Asian African Society for Mycobacteriology. Published by Elsevier Ltd. All rights reserved.

  3. Negative-ion formation in the explosives RDX, PETN, and TNT by using the reversal electron attachment detection technique

    NASA Technical Reports Server (NTRS)

    Boumsellek, S.; Alajajian, S. H.; Chutjian, A.

    1992-01-01

    First results of a beam-beam, single-collision study of negative-ion mass spectra produced by attachment of zero-energy electrons to the molecules of the explosives RDX, PETN, and TNT are presented. The technique used is reversal electron attachment detection (READ) wherein the zero-energy electrons are produced by focusing an intense electron beam into a shaped electrostatic field which reverses the trajectory of electrons. The target beam is introduced at the reversal point, and attachment occurs because the electrons have essentially zero longitudinal and radial velocity. The READ technique is used to obtain the 'signature' of molecular ion formation and/or fragmentation for each explosive. Present data are compared with results from atmospheric-pressure ionization and negative-ion chemical ionization methods.

  4. Switchable DNA interfaces for the highly sensitive detection of label-free DNA targets.

    PubMed

    Rant, Ulrich; Arinaga, Kenji; Scherer, Simon; Pringsheim, Erika; Fujita, Shozo; Yokoyama, Naoki; Tornow, Marc; Abstreiter, Gerhard

    2007-10-30

    We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 x 10(8) bound targets per cm(2) sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format.

  5. Switchable DNA interfaces for the highly sensitive detection of label-free DNA targets

    PubMed Central

    Rant, Ulrich; Arinaga, Kenji; Scherer, Simon; Pringsheim, Erika; Fujita, Shozo; Yokoyama, Naoki; Tornow, Marc; Abstreiter, Gerhard

    2007-01-01

    We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 × 108 bound targets per cm2 sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format. PMID:17951434

  6. Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection

    DOE PAGES

    Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max; ...

    2016-08-04

    This work proposes a hyperspherical sparse approximation framework for detecting jump discontinuities in functions in high-dimensional spaces. The need for a novel approach results from the theoretical and computational inefficiencies of well-known approaches, such as adaptive sparse grids, for discontinuity detection. Our approach constructs the hyperspherical coordinate representation of the discontinuity surface of a function. Then sparse approximations of the transformed function are built in the hyperspherical coordinate system, with values at each point estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of the hypersurface, the new technique can identify jump discontinuities with significantly reduced computationalmore » cost, compared to existing methods. Several approaches are used to approximate the transformed discontinuity surface in the hyperspherical system, including adaptive sparse grid and radial basis function interpolation, discrete least squares projection, and compressed sensing approximation. Moreover, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. In conclusion, rigorous complexity analyses of the new methods are provided, as are several numerical examples that illustrate the effectiveness of our approach.« less

  7. Twin target self-amplification-based DNA machine for highly sensitive detection of cancer-related gene.

    PubMed

    Xu, Huo; Jiang, Yifan; Liu, Dengyou; Liu, Kai; Zhang, Yafeng; Yu, Suhong; Shen, Zhifa; Wu, Zai-Sheng

    2018-06-29

    The sensitive detection of cancer-related genes is of great significance for early diagnosis and treatment of human cancers, and previous isothermal amplification sensing systems were often based on the reuse of target DNA, the amplification of enzymatic products and the accumulation of reporting probes. However, no reporting probes are able to be transformed into target species and in turn initiate the signal of other probes. Herein we reported a simple, isothermal and highly sensitive homogeneous assay system for tumor suppressor p53 gene detection based on a new autonomous DNA machine, where the signaling probe, molecular beacon (MB), was able to execute the function similar to target DNA besides providing the common signal. In the presence of target p53 gene, the operation of DNA machine can be initiated, and cyclical nucleic acid strand-displacement polymerization (CNDP) and nicking/polymerization cyclical amplification (NPCA) occur, during which the MB was opened by target species and cleaved by restriction endonuclease. In turn, the cleaved fragments could activate the next signaling process as target DNA did. According to the functional similarity, the cleaved fragment was called twin target, and the corresponding fashion to amplify the signal was named twin target self-amplification. Utilizing this newly-proposed DNA machine, the target DNA could be detected down to 0.1 pM with a wide dynamic range (6 orders of magnitude) and single-base mismatched targets were discriminated, indicating a very high assay sensitivity and good specificity. In addition, the DNA machine was not only used to screen the p53 gene in complex biological matrix but also was capable of practically detecting genomic DNA p53 extracted from A549 cell line. This indicates that the proposed DNA machine holds the potential application in biomedical research and early clinical diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. Oxygen detection using the laser diode absorption technique

    NASA Technical Reports Server (NTRS)

    Disimile, P. J.; Fox, C. W.

    1991-01-01

    Accurate measurement of the concentration and flow rate of gaseous oxygen is becoming of greater importance. The detection technique presented is based on the principal of light absorption by the Oxygen A-Band. Oxygen molecules have characteristics which attenuate radiation in the 759-770 nm wavelength range. With an ability to measure changes in the relative light transmission to less than 0.01 percent, a sensitive optical gas detection system was configured. This system is smaller in size and light in weight, has low energy requirements and has a rapid response time. In this research program, the application of temperature tuning laser diodes and their ability to be wavelength shifted to a selected absorption spectral peak has allowed concentrations as low as 1300 ppm to be detected.

  9. Void detection beneath reinforced concrete sections: The practical application of ground-penetrating radar and ultrasonic techniques

    NASA Astrophysics Data System (ADS)

    Cassidy, Nigel J.; Eddies, Rod; Dods, Sam

    2011-08-01

    Ground-penetrating radar (GPR) and ultrasonic 'pulse echo' techniques are well-established methods for the imaging, investigation and analysis of steel reinforced concrete structures and are important civil engineering survey tools. GPR is, arguably, the more widely-used technique as it is suitable for a greater range of problem scenarios (i.e., from rebar mapping to moisture content determination). Ultrasonic techniques are traditionally associated with the engineering-based, non-destructive testing of concrete structures and their integrity analyses (e.g., flaw detection, shear/longitudinal velocity determination, etc). However, when used in an appropriate manner, both techniques can be considered complementary and provide a unique way of imaging the sub-surface that is suited to a range of geotechnical problems. In this paper, we present a comparative study between mid-to-high frequency GPR (450 MHz and 900 MHz) and array-based, shear wave, pulse-echo ultrasonic surveys using proprietary instruments and conventional GPR data processing and visualisation techniques. Our focus is the practical detection of sub-metre scale voids located under steel reinforced concrete sections in realistic survey conditions (e.g., a capped, relict mine shaft or vent). Representative two-dimensional (2D) sections are presented for both methods illustrating the similarities/differences in signal response and the temporal-spatial target resolutions achieved with each technique. The use of three-dimensional data volumes and time slices (or 'C-scans') for advanced interpretation is also demonstrated, which although common in GPR applications is under-utilised as a technique in general ultrasonic surveys. The results show that ultrasonic methods can perform as well as GPR for this specific investigation scenario and that they have the potential of overcoming some of the inherent limitations of GPR investigations (i.e., the need for careful antenna frequency selection and survey design in

  10. Updating Landsat-derived land-cover maps using change detection and masking techniques

    NASA Technical Reports Server (NTRS)

    Likens, W.; Maw, K.

    1982-01-01

    The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

  11. Targeted Feature Detection for Data-Dependent Shotgun Proteomics

    PubMed Central

    2017-01-01

    Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification (“FFId”), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between “internal” and “external” (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the “uncertain” feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards

  12. Fishing Technique of Long-Fingered Bats Was Developed from a Primary Reaction to Disappearing Target Stimuli.

    PubMed

    Aizpurua, Ostaizka; Alberdi, Antton; Aihartza, Joxerra; Garin, Inazio

    2016-01-01

    Behavioral plasticity is a key feature allowing animals to broaden their dietary niche when novel food resources become available, and long-fingered bats provide an appropriate model system to study the underpinnings of behavioral plasticity, since although generally being an insectivorous species, some individuals have been reported to catch fish. Aiming to get insight into the origin of fishing behavior in long-fingered bats, we studied in the field the differences in sensorial and mechanical reactions to insect-like (stationary) and fish-like (temporary) prey stimuli between well-known piscivorous and strictly insectivorous individuals. Both piscivorous and insectivorous individuals exhibited a qualitatively similar reaction to temporary target stimuli (longer and deeper dips and terminal echolocation phase skewed towards buzz I compared to stationary stimuli). Nevertheless, the quantitative differences observed in the sensorial and mechanical features (the intensity of the shift was significantly greater in piscivorous than in insectivorous individuals) show that piscivorous individuals have honed their capture technique likely enhancing the fishing success. Thus, our results suggest that the fishing technique was developed from a primary reaction shared by all long-fingered bats. All individuals seem to be mechanically and sensorially adapted to detect and capture fish, although under appropriate environmental conditions, they would further improve their technique by experience and/or social learning.

  13. Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

    ERIC Educational Resources Information Center

    Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

    2017-01-01

    In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

  14. Multispectral photoacoustic decomposition with localized regularization for detecting targeted contrast agent

    NASA Astrophysics Data System (ADS)

    Tavakoli, Behnoosh; Chen, Ying; Guo, Xiaoyu; Kang, Hyun Jae; Pomper, Martin; Boctor, Emad M.

    2015-03-01

    Targeted contrast agents can improve the sensitivity of imaging systems for cancer detection and monitoring the treatment. In order to accurately detect contrast agent concentration from photoacoustic images, we developed a decomposition algorithm to separate photoacoustic absorption spectrum into components from individual absorbers. In this study, we evaluated novel prostate-specific membrane antigen (PSMA) targeted agents for imaging prostate cancer. Three agents were synthesized through conjugating PSMA-targeting urea with optical dyes ICG, IRDye800CW and ATTO740 respectively. In our preliminary PA study, dyes were injected in a thin wall plastic tube embedded in water tank. The tube was illuminated with pulsed laser light using a tunable Q-switch ND-YAG laser. PA signal along with the B-mode ultrasound images were detected with a diagnostic ultrasound probe in orthogonal mode. PA spectrums of each dye at 0.5 to 20 μM concentrations were estimated using the maximum PA signal extracted from images which are obtained at illumination wavelengths of 700nm-850nm. Subsequently, we developed nonnegative linear least square optimization method along with localized regularization to solve the spectral unmixing. The algorithm was tested by imaging mixture of those dyes. The concentration of each dye was estimated with about 20% error on average from almost all mixtures albeit the small separation between dyes spectrums.

  15. Indirect fluorometric detection techniques on thin layer chromatography and effect of ultrasound on gel electrophoresis

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

    Yinfa, Ma.

    Thin-layer chromatography (TLC) is a broadly applicable separation technique. It offers many advantages over high performance liquid chromatography (HPLC), such as easily adapted for two-dimensional separation, for whole-column'' detection and for handling multiple samples, etc. However, due to its draggy development of detection techniques comparing with HPLC, TLC has not received the attention it deserves. Therefore, exploring new detection techniques is very important to the development of TLC. It is the principal of this dissertation to present a new detection method for TLC -- indirect fluorometric detection method. This detection technique is universal sensitive, nondestructive, and simple. This will bemore » described in detail from Sections 1 through Section 5. Section 1 and 3 describe the indirect fluorometric detection of anions and nonelectrolytes in TLC. In Section 2, a detection method for cations based on fluorescence quenching of ethidium bromide is presented. In Section 4, a simple and interesting TLC experiment is designed, three different fluorescence detection principles are used for the determination of caffeine, saccharin and sodium benzoate in beverages. A laser-based indirect fluorometric detection technique in TLC is developed in Section 5. Section 6 is totally different from Sections 1 through 5. An ultrasonic effect on the separation of DNA fragments in agarose gel electrophoresis is investigated. 262 refs.« less

  16. Electronic nose for detecting multiple targets

    NASA Astrophysics Data System (ADS)

    Chakraborty, Anirban; Parthasarathi, Ganga; Poddar, Rakesh; Zhao, Weiqiang; Luo, Cheng

    2006-05-01

    The discovery of high conductivity in doped polyacetylene in 1977 (garnering the 2000 Nobel Prize in Chemistry for the three discovering scientists) has attracted considerable interest in the application of polymers as the semiconducting and conducting materials due to their promising potential to replace silicon and metals in building devices. Previous and current efforts in developing conducting polymer microsystems mainly focus on generating a device of a single function. When multiple micropatterns made of different conducting polymers are produced on the same substrate, many microsystems of multiple functions can be envisioned. For example, analogous to the mammalian olfactory system which includes over 1,000 receptor genes in detecting various odors (e.g., beer, soda etc.), a sensor consisting of multiple distinct conducting polymer sensing elements will be capable of detecting a number of analytes simultaneously. However, existing techniques present significant technical challenges of degradation, low throughput, low resolution, depth of field, and/or residual layer in producing conducting polymer microstructures. To circumvent these challenges, an intermediate-layer lithography method developed in our group is used to generate multiple micropatterns made of different, commonly used conducting polymers, Polypyrrole (PPy), Poly(3,4-ethylenedioxy)thiophene (PEDOT) and Polyaniline (PANI). The generated multiple micropatterns are further used in an "electronic nose" to detect water vapor, glucose, toluene and acetone.

  17. Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

    NASA Astrophysics Data System (ADS)

    Balaji, Bhashyam; Sithiravel, Rajiv; Daya, Zahir; Kirubarajan, Thiagalingam

    2015-05-01

    An airborne EO/IR (electro-optical/infrared) camera system comprises of a suite of sensors, such as a narrow and wide field of view (FOV) EO and mid-wave IR sensors. EO/IR camera systems are regularly employed on military and search and rescue aircrafts. The EO/IR system can be used to detect and identify objects rapidly in daylight and at night, often with superior performance in challenging conditions such as fog. There exist several algorithms for detecting potential targets in the bearing elevation grid. The nonlinear filtering problem is one of estimation of the kinematic parameters from bearing and elevation measurements from a moving platform. In this paper, we developed a complete model for the state of a target as detected by an airborne EO/IR system and simulated a typical scenario with single target with 1 or 2 airborne sensors. We have demonstrated the ability to track the target with `high precision' and noted the improvement from using two sensors on a single platform or on separate platforms. The performance of the Extended Kalman filter (EKF) is investigated on simulated data. Image/video data collected from an IR sensor on an airborne platform are processed using an image tracking by detection algorithm.

  18. Lesion detectability in 2D-mammography and digital breast tomosynthesis using different targets and observers

    NASA Astrophysics Data System (ADS)

    Elangovan, Premkumar; Mackenzie, Alistair; Dance, David R.; Young, Kenneth C.; Wells, Kevin

    2018-05-01

    This work investigates the detection performance of specialist and non-specialist observers for different targets in 2D-mammography and digital breast tomosynthesis (DBT) using the OPTIMAM virtual clinical trials (VCT) Toolbox and a 4-alternative forced choice (4AFC) assessment paradigm. Using 2D-mammography and DBT images of virtual breast phantoms, we compare the detection limits of simple uniform spherical targets and irregular solid masses. Target diameters of 4 mm and 6 mm have been chosen to represent target sizes close to the minimum detectable size found in breast screening, across a range of controlled contrast levels. The images were viewed by a set of specialist observers (five medical physicists and six experienced clinical readers) and five non-specialists. Combined results from both observer groups indicate that DBT has a significantly lower detectable threshold contrast than 2D-mammography for small masses (4 mm: 2.1% [DBT] versus 6.9% [2D]; 6 mm: 0.7% [DBT] versus 3.9% [2D]) and spheres (4 mm: 2.9% [DBT] versus 5.3% [2D]; 6 mm: 0.3% [DBT] versus 2.2% [2D]) (p  <  0.0001). Both observer groups found spheres significantly easier to detect than irregular solid masses for both sizes and modalities (p  <  0.0001) (except 4 mm DBT). The detection performances of specialist and non-specialist observers were generally found to be comparable, where each group marginally outperformed the other in particular detection tasks. Within the specialist group, the clinical readers performed better than the medical physicists with irregular masses (p  <  0.0001). The results indicate that using spherical targets in such studies may produce over-optimistic detection thresholds compared to more complex masses, and that the superiority of DBT for detecting masses over 2D-mammography has been quantified. The results also suggest specialist observers may be supplemented by non-specialist observers (with training) in some types of 4AFC studies.

  19. Co-detection: ultra-reliable nanoparticle-based electrical detection of biomolecules in the presence of large background interference.

    PubMed

    Liu, Yang; Gu, Ming; Alocilja, Evangelyn C; Chakrabartty, Shantanu

    2010-11-15

    An ultra-reliable technique for detecting trace quantities of biomolecules is reported. The technique called "co-detection" exploits the non-linear redundancy amongst synthetically patterned biomolecular logic circuits for deciphering the presence or absence of target biomolecules in a sample. In this paper, we verify the "co-detection" principle on gold-nanoparticle-based conductimetric soft-logic circuits which use a silver-enhancement technique for signal amplification. Using co-detection, we have been able to demonstrate a great improvement in the reliability of detecting mouse IgG at concentration levels that are 10(5) lower than the concentration of rabbit IgG which serves as background interference. Copyright © 2010 Elsevier B.V. All rights reserved.

  20. Drop-Off Detection with the Long Cane: Effects of Different Cane Techniques on Performance

    ERIC Educational Resources Information Center

    Kim, Dae Shik; Emerson, Robert Wall; Curtis, Amy

    2009-01-01

    This study compared the drop-off detection performance with the two-point touch and constant contact cane techniques using a repeated-measures design with a convenience sample of 15 cane users with visual impairments. The constant contact technique was superior to the two-point touch technique in the drop-off detection rate and the 50% detection…

  1. Development of 99mTc-radiolabeled nanosilica for targeted detection of HER2-positive breast cancer

    PubMed Central

    Rainone, Paolo; Riva, Benedetta; Belloli, Sara; Sudati, Francesco; Ripamonti, Marilena; Verderio, Paolo; Colombo, Miriam; Colzani, Barbara; Gilardi, Maria Carla; Moresco, Rosa Maria; Prosperi, Davide

    2017-01-01

    The human epidermal growth factor receptor 2 (HER2) is normally associated with a highly aggressive and infiltrating phenotype in breast cancer lesions with propensity to spread into metastases. In clinic, the detection of HER2 in primary tumors and in their metastases is currently based on invasive methods. Recently, nuclear molecular imaging techniques, including positron emission tomography and single photon emission computed tomography (SPECT), allowed the detection of HER2 lesions in vivo. We have developed a 99mTc-radiolabeled nanosilica system, functionalized with a trastuzumab half-chain, able to act as drug carrier and SPECT radiotracer for the identification of HER2-positive breast cancer cells. To this aim, nanoparticles functionalized or not with trastuzumab half-chain, were radiolabeled using the 99mTc-tricarbonyl approach and evaluated in HER2 positive and negative breast cancer models. Cell uptake experiments, combined with flow cytometry and fluorescence imaging, suggested that active targeting provides higher efficiency and selectivity in tumor detection compared to passive diffusion, indicating that our radiolabeling strategy did not affect the nanoconjugate binding efficiency. Ex vivo biodistribution of 99mTc-nanosilica in a SK-BR-3 (HER2+) tumor xenograft at 4 h postinjection was higher in targeted compared to nontargeted nanosilica, confirming the in vitro data. In addition, viability and toxicity tests provided evidence on nanoparticle safety in cell cultures. Our results encourage further assessment of silica 99mTc-nanoconjugates to validate a safe and versatile nanoreporter system for both diagnosis and treatment of aggressive breast cancer. PMID:28496321

  2. Recent mycotoxin survey data and advanced mycotoxin detection techniques reported from China: a review.

    PubMed

    Selvaraj, Jonathan Nimal; Wang, Yan; Zhou, Lu; Zhao, Yueju; Xing, Fuguo; Dai, Xiaofeng; Liu, Yang

    2015-01-01

    Mycotoxin contamination in agro-food systems has been a serious concern over the last few decades in China, where the Ministry of Health has set maximum limits for mycotoxins in different agro-products. Overall survey data show that aflatoxin contamination in infant cereals, edible oils, raw milk, ginger and its related products are far below Chinese regulatory limits. The absence of aflatoxin M1 contamination in infant milk powders indicates a high standard of control. Aflatoxins in liquorice roots and lotus seeds have been reported for the first time. For deoxynivalenol, high levels were found in wheat grown in the Yangtze Delta region, which is more prone to rainfall, supporting Fusarium infection. The emerging mycotoxins beauvericins and enniatins have been reported in the medicinal herbs in China. Ochratoxin A in wine was below the European Union regulatory limits, but fumonisins in maize need to be monitored and future regulatory control considered. Overall from all the survey data analysed in this review, it can be concluded that 92% of the samples analysed had mycotoxin levels below the Chinese regulatory limits. In terms of detection techniques in recent years, immuno-based assays have been developed largely due to their excellent sensitivity and ease of use. Assays targeting multiple mycotoxins like aflatoxins, ochratoxin A, zearalenone and deoxynivalenol have been reported using microarrays and suspension arrays targeting in particular maize, rice and peanuts. Aptamer-based assays against ochratoxin A and aflatoxins B1 and B2 have been developed involving fluorescence detection; and surface plasmon resonance immunosensors have been developed targeting wine, maize, wheat, wild rye, hay and peanut oil with high sensitivity (> 0.025 ng l(-1)). Commercialisation of these technologies is much needed for wider usage in the coming years.

  3. Detecting Moving Targets by Use of Soliton Resonances

    NASA Technical Reports Server (NTRS)

    Zak, Michael; Kulikov, Igor

    2003-01-01

    A proposed method of detecting moving targets in scenes that include cluttered or noisy backgrounds is based on a soliton-resonance mathematical model. The model is derived from asymptotic solutions of the cubic Schroedinger equation for a one-dimensional system excited by a position-and-time-dependent externally applied potential. The cubic Schroedinger equation has general significance for time-dependent dispersive waves. It has been used to approximate several phenomena in classical as well as quantum physics, including modulated beams in nonlinear optics, and superfluids (in particular, Bose-Einstein condensates). In the proposed method, one would take advantage of resonant interactions between (1) a soliton excited by the position-and-time-dependent potential associated with a moving target and (2) eigen-solitons, which represent dispersive waves and are solutions of the cubic Schroedinger equation for a time-independent potential.

  4. Epileptic seizure detection in EEG signal using machine learning techniques.

    PubMed

    Jaiswal, Abeg Kumar; Banka, Haider

    2018-03-01

    Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

  5. Development of Eddy Current Techniques for Detection of Deep Fatigue Cracks in Multi-Layer Airframe Components

    NASA Technical Reports Server (NTRS)

    Wincheski, Russell A.

    2008-01-01

    Thick, multi-layer aluminum structure has been widely used in aircraft design in critical wing splice areas. The multi-layer structure generally consists of three or four aluminum layers with different geometry and varying thickness, which are held together with fasteners. The detection of cracks under fasteners with ultrasonic techniques in subsurface layers away from the skin is impeded primarily by interlayer bonds and faying sealant condition. Further, assessment of such sealant condition is extremely challenging in terms of complexity of structure, limited access, and inspection cost. Although Eddy current techniques can be applied on in-service aircraft from the exterior of the skin without knowing sealant condition, the current eddy current techniques are not able to detect defects with wanted sensitivity. In this work a series of low frequency eddy current probes have been designed, fabricated and tested for this application. A probe design incorporating a shielded magnetic field sensor concentrically located in the interior of a drive coil has been employed to enable a localized deep diffusion of the electromagnetic field into the part under test. Due to the required low frequency inspections, probes have been testing using a variety of magnetic field sensors (pickup coil, giant magneto-resistive, anisotropic magneto-resistive, and spin-dependent tunneling). The probe designs as well as capabilities based upon a target inspection for sub-layer cracking in an airframe wing spar joint is presented.

  6. Universal, colorimetric microRNA detection strategy based on target-catalyzed toehold-mediated strand displacement reaction

    NASA Astrophysics Data System (ADS)

    Park, Yeonkyung; Lee, Chang Yeol; Kang, Shinyoung; Kim, Hansol; Park, Ki Soo; Park, Hyun Gyu

    2018-02-01

    In this work, we developed a novel, label-free, and enzyme-free strategy for the colorimetric detection of microRNA (miRNA), which relies on a target-catalyzed toehold-mediated strand displacement (TMSD) reaction. The system employs a detection probe that specifically binds to the target miRNA and sequentially releases a catalyst strand (CS) intended to trigger the subsequent TMSD reaction. Thus, the presence of target miRNA releases the CS that mediates the formation of an active G-quadruplex DNAzyme which is initially caged and inactivated by a blocker strand. In addition, a fuel strand that is supplemented for the recycling of the CS promotes another TMSD reaction, consequently generating a large number of active G-quadruplex DNAzymes. As a result, a distinct colorimetric signal is produced by the ABTS oxidation promoted by the peroxidase mimicking activity of the released G-quadruplex DNAzymes. Based on this novel strategy, we successfully detected miR-141, a promising biomarker for human prostate cancer, with high selectivity. The diagnostic capability of this system was also demonstrated by reliably determining target miR-141 in human serum, showing its great potential towards real clinical applications. Importantly, the proposed approach is composed of separate target recognition and signal transduction modules. Thus, it could be extended to analyze different target miRNAs by simply redesigning the detection probe while keeping the same signal transduction module as a universal signal amplification unit, which was successfully demonstrated by analyzing another target miRNA, let-7d.

  7. Universal, colorimetric microRNA detection strategy based on target-catalyzed toehold-mediated strand displacement reaction.

    PubMed

    Park, Yeonkyung; Lee, Chang Yeol; Kang, Shinyoung; Kim, Hansol; Park, Ki Soo; Park, Hyun Gyu

    2018-02-23

    In this work, we developed a novel, label-free, and enzyme-free strategy for the colorimetric detection of microRNA (miRNA), which relies on a target-catalyzed toehold-mediated strand displacement (TMSD) reaction. The system employs a detection probe that specifically binds to the target miRNA and sequentially releases a catalyst strand (CS) intended to trigger the subsequent TMSD reaction. Thus, the presence of target miRNA releases the CS that mediates the formation of an active G-quadruplex DNAzyme which is initially caged and inactivated by a blocker strand. In addition, a fuel strand that is supplemented for the recycling of the CS promotes another TMSD reaction, consequently generating a large number of active G-quadruplex DNAzymes. As a result, a distinct colorimetric signal is produced by the ABTS oxidation promoted by the peroxidase mimicking activity of the released G-quadruplex DNAzymes. Based on this novel strategy, we successfully detected miR-141, a promising biomarker for human prostate cancer, with high selectivity. The diagnostic capability of this system was also demonstrated by reliably determining target miR-141 in human serum, showing its great potential towards real clinical applications. Importantly, the proposed approach is composed of separate target recognition and signal transduction modules. Thus, it could be extended to analyze different target miRNAs by simply redesigning the detection probe while keeping the same signal transduction module as a universal signal amplification unit, which was successfully demonstrated by analyzing another target miRNA, let-7d.

  8. Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

    PubMed

    Wang, Zhengfang; Jablonski, Joseph E

    2016-01-01

    Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

  9. Does Angling Technique Selectively Target Fishes Based on Their Behavioural Type?

    PubMed Central

    Wilson, Alexander D. M.; Brownscombe, Jacob W.; Sullivan, Brittany; Jain-Schlaepfer, Sofia; Cooke, Steven J.

    2015-01-01

    Recently, there has been growing recognition that fish harvesting practices can have important impacts on the phenotypic distributions and diversity of natural populations through a phenomenon known as fisheries-induced evolution. Here we experimentally show that two common recreational angling techniques (active crank baits versus passive soft plastics) differentially target wild largemouth bass (Micropterus salmoides) and rock bass (Ambloplites rupestris) based on variation in their behavioural tendencies. Fish were first angled in the wild using both techniques and then brought back to the laboratory and tested for individual-level differences in common estimates of personality (refuge emergence, flight-initiation-distance, latency-to-recapture and with a net, and general activity) in an in-lake experimental arena. We found that different angling techniques appear to selectively target these species based on their boldness (as characterized by refuge emergence, a standard measure of boldness in fishes) but not other assays of personality. We also observed that body size was independently a significant predictor of personality in both species, though this varied between traits and species. Our results suggest a context-dependency for vulnerability to capture relative to behaviour in these fish species. Ascertaining the selective pressures angling practices exert on natural populations is an important area of fisheries research with significant implications for ecology, evolution, and resource management. PMID:26284779

  10. Sensitive Technique For Detecting Alignment Of Seed Laser

    NASA Technical Reports Server (NTRS)

    Barnes, Norman P.

    1994-01-01

    Frequency response near resonance measured. Improved technique for detection and quantification of alignment of injection-seeding laser with associated power-oscillator laser proposed. Particularly useful in indicating alignment at spectral purity greater than 98 percent because it becomes more sensitive as perfect alignment approached. In addition, implemented relatively easily, without turning on power-oscillator laser.

  11. Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks

    NASA Astrophysics Data System (ADS)

    Zhang, Huibin; Wang, Yuqiao; Chen, Haoran; Zhao, Yongli; Zhang, Jie

    2017-12-01

    In software defined optical networks (SDON), the centralized control plane may encounter numerous intrusion threatens which compromise the security level of provisioned services. In this paper, the issue of control plane security is studied and two machine-learning-based control plane intrusion detection techniques are proposed for SDON with properly selected features such as bandwidth, route length, etc. We validate the feasibility and efficiency of the proposed techniques by simulations. Results show an accuracy of 83% for intrusion detection can be achieved with the proposed machine-learning-based control plane intrusion detection techniques.

  12. The Outlier Detection for Ordinal Data Using Scalling Technique of Regression Coefficients

    NASA Astrophysics Data System (ADS)

    Adnan, Arisman; Sugiarto, Sigit

    2017-06-01

    The aims of this study is to detect the outliers by using coefficients of Ordinal Logistic Regression (OLR) for the case of k category responses where the score from 1 (the best) to 8 (the worst). We detect them by using the sum of moduli of the ordinal regression coefficients calculated by jackknife technique. This technique is improved by scalling the regression coefficients to their means. R language has been used on a set of ordinal data from reference distribution. Furthermore, we compare this approach by using studentised residual plots of jackknife technique for ANOVA (Analysis of Variance) and OLR. This study shows that the jackknifing technique along with the proper scaling may lead us to reveal outliers in ordinal regression reasonably well.

  13. Standoff detection: classification of biological aerosols using laser induced fluorescence (LIF) technique

    NASA Astrophysics Data System (ADS)

    Hausmann, Anita; Duschek, Frank; Fischbach, Thomas; Pargmann, Carsten; Aleksejev, Valeri; Poryvkina, Larisa; Sobolev, Innokenti; Babichenko, Sergey; Handke, Jürgen

    2014-05-01

    The challenges of detecting hazardous biological materials are manifold: Such material has to be discriminated from other substances in various natural surroundings. The detection sensitivity should be extremely high. As living material may reproduce itself, already one single bacterium may represent a high risk. Of course, identification should be quite fast with a low false alarm rate. Up to now, there is no single technique to solve this problem. Point sensors may collect material and identify it, but the problems of fast identification and especially of appropriate positioning of local collectors are sophisticated. On the other hand, laser based standoff detection may instantaneously provide the information of some accidental spillage of material by detecting the generated thin cloud. LIF technique may classify but hardly identify the substance. A solution can be the use of LIF technique in a first step to collect primary data and - if necessary- followed by utilizing these data for an optimized positioning of point sensors. We perform studies on an open air laser test range at distances between 20 and 135 m applying LIF technique to detect and classify aerosols. In order to employ LIF capability, we use a laser source emitting two wavelengths alternatively, 280 and 355 nm, respectively. Moreover, the time dependence of fluorescence spectra is recorded by a gated intensified CCD camera. Signal processing is performed by dedicated software for spectral pattern recognition. The direct comparison of all results leads to a basic classification of the various compounds.

  14. Target detection, shape discrimination, and signal characteristics of an echolocating false killer whale (Pseudorca crassidens).

    PubMed

    Brill, R L; Pawloski, J L; Helweg, D A; Au, W W; Moore, P W

    1992-09-01

    This study demonstrated the ability of a false killer whale (Pseudorca crassidens) to discriminate between two targets and investigated the parameters of the whale's emitted signals for changes related to test conditions. Target detection performance comparable to the bottlenose dolphin's (Tursiops truncatus) has previously been reported for echolocating false killer whales. No other echolocation capabilities have been reported. A false killer whale, naive to conditioned echolocation tasks, was initially trained to detect a cylinder in a "go/no-go" procedure over ranges of 3 to 8 m. The transition from a detection task to a discrimination task was readily achieved by introducing a spherical comparison target. Finally, the cylinder was successfully compared to spheres of two different sizes and target strengths. Multivariate analyses were used to evaluate the parameters of emitted signals. Duncan's multiple range tests showed significant decreases (df = 185, p less than 0.05) in both source level and bandwidth in the transition from detection to discrimination. Analysis of variance revealed a significant decrease in the number of clicks over test conditions [F(5.26) = 5.23, p less than 0.0001]. These data suggest that the whale relied on cues relevant to target shape as well as target strength, that changes in source level and bandwidth were task-related, that the decrease in clicks was associated with learning experience, and that Pseudorca's ability to discriminate shapes using echolocation may be comparable to that of Tursiops truncatus.

  15. Effects of Alzheimer’s Disease on Visual Target Detection: A “Peripheral Bias”

    PubMed Central

    Vallejo, Vanessa; Cazzoli, Dario; Rampa, Luca; Zito, Giuseppe A.; Feuerstein, Flurin; Gruber, Nicole; Müri, René M.; Mosimann, Urs P.; Nef, Tobias

    2016-01-01

    Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer’s Disease (AD). The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and 20 healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ±90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view. PMID:27582704

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

    PubMed Central

    Li, Na

    2010-01-01

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

  17. Mitochondrial DNA Targets Increase Sensitivity of Malaria Detection Using Loop-Mediated Isothermal Amplification ▿

    PubMed Central

    Polley, Spencer D.; Mori, Yasuyoshi; Watson, Julie; Perkins, Mark D.; González, Iveth J.; Notomi, Tsugunori; Chiodini, Peter L.; Sutherland, Colin J.

    2010-01-01

    Loop-mediated isothermal amplification (LAMP) of DNA offers the ability to detect very small quantities of pathogen DNA following minimal tissue sample processing and is thus an attractive methodology for point-of-care diagnostics. Previous attempts to diagnose malaria by the use of blood samples and LAMP have targeted the parasite small-subunit rRNA gene, with a resultant sensitivity for Plasmodium falciparum of around 100 parasites per μl. Here we describe the use of mitochondrial targets for LAMP-based detection of any Plasmodium genus parasite and of P. falciparum specifically. These new targets allow routine amplification from samples containing as few as five parasites per μl of blood. Amplification is complete within 30 to 40 min and is assessed by real-time turbidimetry, thereby offering rapid diagnosis with greater sensitivity than is achieved by the most skilled microscopist or antigen detection using lateral flow immunoassays. PMID:20554824

  18. The Population of Small Comets: Optimum Techniques for Detection

    NASA Technical Reports Server (NTRS)

    Brandt, John C.

    1997-01-01

    The goals of this project were: (1) to present evidence to the scientific community for the importance of the small comet population and (2) to develop techniques for optimum detection in order to characterize the population. Our work on techniques has been to develop algorithms for searching images for SCs based on the distinctive properties of comets; (1) motion with respect to background stars; (2) extended source with most light coming from the coma rather than the nucleus; and characteristic spectral signature.

  19. Fast iterative censoring CFAR algorithm for ship detection from SAR images

    NASA Astrophysics Data System (ADS)

    Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

    2017-11-01

    Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

  20. Highly sensitive and specific colorimetric detection of cancer cells via dual-aptamer target binding strategy.

    PubMed

    Wang, Kun; Fan, Daoqing; Liu, Yaqing; Wang, Erkang

    2015-11-15

    Simple, rapid, sensitive and specific detection of cancer cells is of great importance for early and accurate cancer diagnostics and therapy. By coupling nanotechnology and dual-aptamer target binding strategies, we developed a colorimetric assay for visually detecting cancer cells with high sensitivity and specificity. The nanotechnology including high catalytic activity of PtAuNP and magnetic separation & concentration plays a vital role on the signal amplification and improvement of detection sensitivity. The color change caused by small amount of target cancer cells (10 cells/mL) can be clearly distinguished by naked eyes. The dual-aptamer target binding strategy guarantees the detection specificity that large amount of non-cancer cells and different cancer cells (10(4) cells/mL) cannot cause obvious color change. A detection limit as low as 10 cells/mL with detection linear range from 10 to 10(5) cells/mL was reached according to the experimental detections in phosphate buffer solution as well as serum sample. The developed enzyme-free and cost effective colorimetric assay is simple and no need of instrument while still provides excellent sensitivity, specificity and repeatability, having potential application on point-of-care cancer diagnosis. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Moving target detection for frequency agility radar by sparse reconstruction

    NASA Astrophysics Data System (ADS)

    Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

    2016-09-01

    Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

  2. Moving target detection for frequency agility radar by sparse reconstruction.

    PubMed

    Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

    2016-09-01

    Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

  3. Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

    PubMed Central

    Bayır, Şafak

    2016-01-01

    With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC. PMID:27110272

  4. Failure detection and fault management techniques for flush airdata sensing systems

    NASA Technical Reports Server (NTRS)

    Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

    1992-01-01

    Methods based on chi-squared analysis are presented for detecting system and individual-port failures in the high-angle-of-attack flush airdata sensing system on the NASA F-18 High Alpha Research Vehicle. The HI-FADS hardware is introduced, and the aerodynamic model describes measured pressure in terms of dynamic pressure, angle of attack, angle of sideslip, and static pressure. Chi-squared analysis is described in the presentation of the concept for failure detection and fault management which includes nominal, iteration, and fault-management modes. A matrix of pressure orifices arranged in concentric circles on the nose of the aircraft indicate the parameters which are applied to the regression algorithms. The sensing techniques are applied to the F-18 flight data, and two examples are given of the computed angle-of-attack time histories. The failure-detection and fault-management techniques permit the matrix to be multiply redundant, and the chi-squared analysis is shown to be useful in the detection of failures.

  5. DNA-based species detection capabilities using laser transmission spectroscopy

    PubMed Central

    Mahon, A. R.; Barnes, M. A.; Li, F.; Egan, S. P.; Tanner, C. E.; Ruggiero, S. T.; Feder, J. L.; Lodge, D. M.

    2013-01-01

    Early detection of invasive species is critical for effective biocontrol to mitigate potential ecological and economic damage. Laser transmission spectroscopy (LTS) is a powerful solution offering real-time, DNA-based species detection in the field. LTS can measure the size, shape and number of nanoparticles in a solution and was used here to detect size shifts resulting from hybridization of the polymerase chain reaction product to nanoparticles functionalized with species-specific oligonucleotide probes or with the species-specific oligonucleotide probes alone. We carried out a series of DNA detection experiments using the invasive freshwater quagga mussel (Dreissena bugensis) to evaluate the capability of the LTS platform for invasive species detection. Specifically, we tested LTS sensitivity to (i) DNA concentrations of a single target species, (ii) the presence of a target species within a mixed sample of other closely related species, (iii) species-specific functionalized nanoparticles versus species-specific oligonucleotide probes alone, and (iv) amplified DNA fragments versus unamplified genomic DNA. We demonstrate that LTS is a highly sensitive technique for rapid target species detection, with detection limits in the picomolar range, capable of successful identification in multispecies samples containing target and non-target species DNA. These results indicate that the LTS DNA detection platform will be useful for field application of target species. Additionally, we find that LTS detection is effective with species-specific oligonucleotide tags alone or when they are attached to polystyrene nanobeads and with both amplified and unamplified DNA, indicating that the technique may also have versatility for broader applications. PMID:23015524

  6. A coherent detection technique via optically biased field for broadband terahertz radiation.

    PubMed

    Du, Hai-Wei; Dong, Jia-Meng; Liu, Yi; Shi, Chang-Cheng; Wu, Jing-Wei; Peng, Xiao-Yu

    2017-09-01

    We demonstrate theoretically and experimentally a coherent terahertz detection technique based on an optically biased field functioning as a local oscillator and a second harmonic induced by the terahertz electric field in the air sensor working in free space. After optimizing the polarization angle and the energy of the probe pulse, and filling the system with dry nitrogen, the terahertz radiation generated from a two-color-femtosecond-laser-pulses induced plasma filament is measured by this technique with a bandwidth of 0.1-10 THz and a signal-to-noise ratio of 48 dB. Our technique provides an alternative simple method for coherent broadband terahertz detection.

  7. Simulation of target interpretation based on infrared image features and psychology principle

    NASA Astrophysics Data System (ADS)

    Lin, Wei; Chen, Yu-hua; Gao, Hong-sheng; Wang, Zhan-feng; Wang, Ji-jun; Su, Rong-hua; Huang, Yan-ping

    2009-07-01

    It's an important and complicated process in target interpretation that target features extraction and identification, which effect psychosensorial quantity of interpretation person to target infrared image directly, and decide target viability finally. Using statistical decision theory and psychology principle, designing four psychophysical experiment, the interpretation model of the infrared target is established. The model can get target detection probability by calculating four features similarity degree between target region and background region, which were plotted out on the infrared image. With the verification of a great deal target interpretation in practice, the model can simulate target interpretation and detection process effectively, get the result of target interpretation impersonality, which can provide technique support for target extraction, identification and decision-making.

  8. Geophysical background and as-built target characteristics

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

    Allen, J.W.

    1994-09-01

    The US Department of Energy (DOE) Grand Junction Projects Office (GJPO) has provided a facility for DOE, other Government agencies, and the private sector to evaluate and document the utility of specific geophysical measurement techniques for detecting and defining cultural and environmental targets. This facility is the Rabbit Valley Geophysics Performance Evaluation Range (GPER). Geophysical surveys prior to the fiscal year (FY) 1994 construction of new test cells showed the primary test area to be relatively homogeneous and free from natural or man-made artifacts, which would generate spurious responses in performance evaluation data. Construction of nine new cell areas inmore » Rabbit Valley was completed in June 1994 and resulted in the emplacement of approximately 150 discrete targets selected for their physical and electrical properties. These targets and their geophysical environment provide a broad range of performance evaluation parameters from ``very easy to detect`` to ``challenging to the most advanced systems.`` Use of nonintrusive investigative techniques represents a significant improvement over intrusive characterization methods, such as drilling or excavation, because there is no danger of exposing personnel to possible hazardous materials and no risk of releasing or spreading contamination through the characterization activity. Nonintrusive geophysical techniques provide the ability to infer near-surface structure and waste characteristics from measurements of physical properties associated with those targets.« less

  9. Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter

    NASA Astrophysics Data System (ADS)

    Elbakary, M. I.; Alam, M. S.; Aslan, M. S.

    2008-03-01

    In a FLIR image sequence, a target may disappear permanently or may reappear after some frames and crucial information such as direction, position and size related to the target are lost. If the target reappears at a later frame, it may not be tracked again because the 3D orientation, size and location of the target might be changed. To obtain information about the target before disappearing and to detect the target after reappearing, distance classifier correlation filter (DCCF) is trained manualy by selecting a number of chips randomly. This paper introduces a novel idea to eliminates the manual intervention in training phase of DCCF. Instead of selecting the training chips manually and selecting the number of the training chips randomly, we adopted the K-means algorithm to cluster the training frames and based on the number of clusters we select the training chips such that a training chip for each cluster. To detect and track the target after reappearing in the field-ofview ,TBF and DCCF are employed. The contduced experiemnts using real FLIR sequences show results similar to the traditional agorithm but eleminating the manual intervention is the advantage of the proposed algorithm.

  10. Detection of cavitation vortex in hydraulic turbines using acoustic techniques

    NASA Astrophysics Data System (ADS)

    Candel, I.; Bunea, F.; Dunca, G.; Bucur, D. M.; Ioana, C.; Reeb, B.; Ciocan, G. D.

    2014-03-01

    Cavitation phenomena are known for their destructive capacity in hydraulic machineries and are caused by the pressure decrease followed by an implosion when the cavitation bubbles find an adverse pressure gradient. A helical vortex appears in the turbine diffuser cone at partial flow rate operation and can be cavitating in its core. Cavity volumes and vortex frequencies vary with the under-pressure level. If the vortex frequency comes close to one of the eigen frequencies of the turbine, a resonance phenomenon may occur, the unsteady fluctuations can be amplified and lead to important turbine and hydraulic circuit damage. Conventional cavitation vortex detection techniques are based on passive devices (pressure sensors or accelerometers). Limited sensor bandwidths and low frequency response limit the vortex detection and characterization information provided by the passive techniques. In order to go beyond these techniques and develop a new active one that will remove these drawbacks, previous work in the field has shown that techniques based on acoustic signals using adapted signal content to a particular hydraulic situation, can be more robust and accurate. The cavitation vortex effects in the water flow profile downstream hydraulic turbines runner are responsible for signal content modifications. Basic signal techniques use narrow band signals traveling inside the flow from an emitting transducer to a receiving one (active sensors). Emissions of wide band signals in the flow during the apparition and development of the vortex embeds changes in the received signals. Signal processing methods are used to estimate the cavitation apparition and evolution. Tests done in a reduced scale facility showed that due to the increasing flow rate, the signal -- vortex interaction is seen as modifications on the received signal's high order statistics and bandwidth. Wide band acoustic transducers have a higher dynamic range over mechanical elements; the system's reaction time

  11. In situ targeted MRI detection of Helicobacter pylori with stable magnetic graphitic nanocapsules

    PubMed Central

    Li, Yunjie; Hu, Xiaoxiao; Ding, Ding; Zou, Yuxiu; Xu, Yiting; Wang, Xuewei; Zhang, Yin; Chen, Long; Chen, Zhuo; Tan, Weihong

    2017-01-01

    Helicobacter pylori infection is implicated in the aetiology of many diseases. Despite numerous studies, a painless, fast and direct method for the in situ detection of H. pylori remains a challenge, mainly due to the strong acidic/enzymatic environment of the gastric mucosa. Herein, we report the use of stable magnetic graphitic nanocapsules (MGNs), for in situ targeted magnetic resonance imaging (MRI) detection of H. pylori. Several layers of graphene as the shell effectively protect the magnetic core from corrosion while retaining the superior contrast effect for MRI in the gastric environment. Boronic-polyethylene glycol molecules were synthesized and modified on the MGN surface for targeted MRI detection. In a mouse model of H. pylori-induced infection, H. pylori was specifically detected through both T2-weighted MR imaging and Raman gastric mucosa imaging using functionalized MGNs. These results indicated that enhancement of MRI using MGNs may be a promising diagnostic and bioimaging platform for very harsh conditions. PMID:28643777

  12. In situ targeted MRI detection of Helicobacter pylori with stable magnetic graphitic nanocapsules

    NASA Astrophysics Data System (ADS)

    Li, Yunjie; Hu, Xiaoxiao; Ding, Ding; Zou, Yuxiu; Xu, Yiting; Wang, Xuewei; Zhang, Yin; Chen, Long; Chen, Zhuo; Tan, Weihong

    2017-06-01

    Helicobacter pylori infection is implicated in the aetiology of many diseases. Despite numerous studies, a painless, fast and direct method for the in situ detection of H. pylori remains a challenge, mainly due to the strong acidic/enzymatic environment of the gastric mucosa. Herein, we report the use of stable magnetic graphitic nanocapsules (MGNs), for in situ targeted magnetic resonance imaging (MRI) detection of H. pylori. Several layers of graphene as the shell effectively protect the magnetic core from corrosion while retaining the superior contrast effect for MRI in the gastric environment. Boronic-polyethylene glycol molecules were synthesized and modified on the MGN surface for targeted MRI detection. In a mouse model of H. pylori-induced infection, H. pylori was specifically detected through both T2-weighted MR imaging and Raman gastric mucosa imaging using functionalized MGNs. These results indicated that enhancement of MRI using MGNs may be a promising diagnostic and bioimaging platform for very harsh conditions.

  13. Highly sensitive detection of target molecules using a new fluorescence-based bead assay

    NASA Astrophysics Data System (ADS)

    Scheffler, Silvia; Strauß, Denis; Sauer, Markus

    2007-07-01

    Development of immunoassays with improved sensitivity, specificity and reliability are of major interest in modern bioanalytical research. We describe the development of a new immunomagnetic fluorescence detection (IM-FD) assay based on specific antigen/antibody interactions and on accumulation of the fluorescence signal on superparamagnetic PE beads in combination with the use of extrinsic fluorescent labels. IM-FD can be easily modified by varying the order of coatings and assay conditions. Depending on the target molecule, antibodies (ABs), entire proteins, or small protein epitopes can be used as capture molecules. The presence of target molecules is detected by fluorescence microscopy using fluorescently labeled secondary or detection antibodies. Here, we demonstrate the potential of the new assay detecting the two tumor markers IGF-I and p53 antibodies in the clinically relevant concentration range. Our data show that the fluorescence-based bead assay exhibits a large dynamic range and a high sensitivity down to the subpicomolar level.

  14. The detectability of archaeological structures beneath the soil using the ground penetrating radar technique

    NASA Astrophysics Data System (ADS)

    Ferrara, C.; Barone, P. M.; Pajewski, L.; Pettinelli, E.; Rossi, G.

    2012-04-01

    The traditional excavation tools applied to Archaeology (i.e. trowels, shovels, bulldozers, etc.) produce, generally, a fast and invasive reconstruction of the ancient past. The geophysical instruments, instead, seem to go in the opposite direction giving, rapidly and non-destructively, geo-archaeological information. Moreover, the economic aspect should not be underestimated: where the former invest a lot of money in order to carry out an excavation or restoration, the latter spend much less to manage a geophysical survey, locating precisely the targets. Survey information gathered using non-invasive methods contributes to the creation of site strategies, conservation, preservation and, if necessary, accurate location of excavation and restoration units, without destructive testing methods, also in well-known archaeological sites [1]-[3]. In particular, Ground Penetrating Radar (GPR) has, recently, become the most important physical technique in archaeological investigations, allowing the detection of targets with both very high vertical and horizontal resolution, and has been successfully applied both to archaeological and diagnostic purposes in historical and monumental sites [4]. GPR configuration, antenna frequency and survey modality can be different, depending on the scope of the measurements, the nature of the site or the type of targets. Two-dimensional (2D) time/depth slices and radargrams should be generated and integrated with information obtained from other buried or similar artifacts to provide age, structure and context of the surveyed sites. In the present work, we present three case-histories on well-known Roman archaeological sites in Rome, in which GPR technique has been successfully used. To obtain 2D maps of the explored area, a bistatic GPR (250MHz and 500MHz antennas) was applied, acquiring data along several parallel profiles. The GPR results reveal the presence of similar circular anomalies in all the investigated archaeological sites. In

  15. In field application of differential Die-Away time technique for detecting gram quantities of fissile materials

    NASA Astrophysics Data System (ADS)

    Remetti, Romolo; Gandolfo, Giada; Lepore, Luigi; Cherubini, Nadia

    2017-10-01

    In the frame of Chemical, Biological, Radiological, and Nuclear defense European activities, the ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development, is proposing the Neutron Active Interrogation system (NAI), a device designed to find transuranic-based Radioactive Dispersal Devices hidden inside suspected packages. It is based on Differential Die-Away time Analysis, an active neutron technique targeted in revealing the presence of fissile material through detection of induced fission neutrons. Several Monte Carlo simulations, carried out by MCNPX code, and the development of ad-hoc design methods, have led to the realization of a first prototype based on a 14 MeV d-t neutron generator coupled with a tailored moderating structure, and an array of helium-3 neutron detectors. The complete system is characterized by easy transportability, light weight, and real-time response. First results have shown device's capability to detect gram quantities of fissile materials.

  16. Target-triggering multiple-cycle signal amplification strategy for ultrasensitive detection of DNA based on QCM and SPR.

    PubMed

    Song, Weiling; Yin, Wenshuo; Sun, Wenbo; Guo, Xiaoyan; He, Peng; Yang, Xiaoyan; Zhang, Xiaoru

    2018-04-24

    Detection of ultralow concentrations of nucleic acid sequences is a central challenge in the early diagnosis of genetic diseases. Herein, we developed a target-triggering cascade multiple cycle amplification for ultrasensitive DNA detection using quartz crystal microbalance (QCM) and surface plasmon resonance (SPR). It was based on the exonuclease Ⅲ (Exo Ⅲ)-assisted signal amplification and the hybridization chain reaction (HCR). The streptavidin-coated Au-NPs (Au-NPs-SA) were assembled on the HCR products as recognition element. Upon sensing of target DNA, the duplex DNA probe triggered the Exo Ⅲ cleavage process, accompanied by generating a new secondary target DNA and releasing target DNA. The released target DNA and the secondary target DNA were recycled. Simultaneously, numerous single strands were liberated and acted as the trigger of HCR to generate further signal amplification, resulting in the immobilization of abundant Au-NPs-SA on the gold substrate. The QCM sensor results were found to be comparable to that achieved using a SPR sensor platform. This method exhibited a high sensitivity toward target DNA with a detection limit of 0.70 fM. The high sensitivity and specificity make this method a great potential for detecting DNA with trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier Inc. All rights reserved.

  17. Multiplex detection of quality indicator molecule targets in urine using programmable hairpin probes based on a simple double-T type microchip electrophoresis platform and isothermal polymerase-catalyzed target recycling.

    PubMed

    Zhou, Lingying; Gan, Ning; Wu, Yongxiang; Hu, Futao; Lin, Jianyuan; Cao, Yuting; Wu, Dazhen

    2018-05-29

    Recently, it has been crucial to be able to detect and quantify small molecular targets simultaneously in biological samples. Herein, a simple and conventional double-T type microchip electrophoresis (MCE) based platform for the multiplex detection of quality indicator molecule targets in urine, using ampicillin (AMPI), adenosine triphosphate (ATP) and estradiol (E2) as models, was developed. Several programmable hairpin probes (PHPs) were designed for detecting different targets and triggering isothermal polymerase-catalyzed target recycling (IPCTR) for signal amplification. Based on the target-responsive aptamer structure of PHP (Domain I), target recognition can induce PHP conformational transition and produce extension duplex DNA (dsDNA), assisted by primers & Bst polymerase. Afterwards, the target can be displaced to react with another PHP and initiate the next cycle. After several rounds of reaction, the dsDNA can be produced in large amounts by IPCTR. Three targets can be simultaneously converted to dsDNA fragments with different lengths, which can be separated and detected using MCE. Thus, a simple double-T type MCE based platform was successfully built for the homogeneous detection of multiplex targets in one channel. Under optimal conditions, the assay exhibited high throughput (48 samples per hour at most, not including reaction time) and sensitivity to three targets in urine with a detection limit of 1 nM (ATP), 0.05 nM (AMPI) and 0.1 nM (E2) respectively. The multiplex assay was successfully employed for the above three targets in several urine samples and combined the advantages of the high specificity of programmable hairpin probes, the excellent signal amplification of IPCTR, and the high through-put of MCE which can be employed for screening in biochemical analysis.

  18. Investigation of a Moire Based Crack Detection Technique for Propulsion Health Monitoring

    NASA Technical Reports Server (NTRS)

    Woike, Mark R.; Abudl-Aziz, Ali; Fralick, Gustave C.; Wrbanek, John D.

    2012-01-01

    The development of techniques for the health monitoring of the rotating components in gas turbine engines is of major interest to NASA s Aviation Safety Program. As part of this on-going effort several experiments utilizing a novel optical Moir based concept along with external blade tip clearance and shaft displacement instrumentation were conducted on a simulated turbine engine disk as a means of demonstrating a potential optical crack detection technique. A Moir pattern results from the overlap of two repetitive patterns with slightly different periods. With this technique, it is possible to detect very small differences in spacing and hence radial growth in a rotating disk due to a flaw such as a crack. The experiment involved etching a circular reference pattern on a subscale engine disk that had a 50.8 mm (2 in.) long notch machined into it to simulate a crack. The disk was operated at speeds up to 12 000 rpm and the Moir pattern due to the shift with respect to the reference pattern was monitored as a means of detecting the radial growth of the disk due to the defect. In addition, blade displacement data were acquired using external blade tip clearance and shaft displacement sensors as a means of confirming the data obtained from the optical technique. The results of the crack detection experiments and its associated analysis are presented in this paper.

  19. A Search Model for Imperfectly Detected Targets

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert

    2012-01-01

    Under the assumptions that 1) the search region can be divided up into N non-overlapping sub-regions that are searched sequentially, 2) the probability of detection is unity if a sub-region is selected, and 3) no information is available to guide the search, there are two extreme case models. The search can be done perfectly, leading to a uniform distribution over the number of searches required, or the search can be done with no memory, leading to a geometric distribution for the number of searches required with a success probability of 1/N. If the probability of detection P is less than unity, but the search is done otherwise perfectly, the searcher will have to search the N regions repeatedly until detection occurs. The number of searches is thus the sum two random variables. One is N times the number of full searches (a geometric distribution with success probability P) and the other is the uniform distribution over the integers 1 to N. The first three moments of this distribution were computed, giving the mean, standard deviation, and the kurtosis of the distribution as a function of the two parameters. The model was fit to the data presented last year (Ahumada, Billington, & Kaiwi, 2 required to find a single pixel target on a simulated horizon. The model gave a good fit to the three moments for all three observers.

  20. An examination of along-track interferometry for detecting ground moving targets

    NASA Technical Reports Server (NTRS)

    Chen, Curtis W.; Chapin, Elaine; Muellerschoen, Ron; Hensley, Scott

    2005-01-01

    Along-track interferometry (ATI) is an interferometric synthetic aperture radar technique primarily used to measure Earth-surface velocities. We present results from an airborne experiment demonstrating phenomenology specific to the context of observing discrete ground targets moving admidst a stationary clutter background.

  1. Thermographic techniques and adapted algorithms for automatic detection of foreign bodies in food

    NASA Astrophysics Data System (ADS)

    Meinlschmidt, Peter; Maergner, Volker

    2003-04-01

    At the moment foreign substances in food are detected mainly by using mechanical and optical methods as well as ultrasonic technique and than they are removed from the further process. These techniques detect a large portion of the foreign substances due to their different mass (mechanical sieving), their different colour (optical method) and their different surface density (ultrasonic detection). Despite the numerous different methods a considerable portion of the foreign substances remain undetected. In order to recognise materials still undetected, a complementary detection method would be desirable removing the foreign substances not registered by the a.m. methods from the production process. In a project with 13 partner from the food industry, the Fraunhofer - Institut für Holzforschung (WKI) and the Technische Unsiversität are trying to adapt thermography for the detection of foreign bodies in the food industry. After the initial tests turned out to be very promising for the differentiation of food stuffs and foreign substances, more and detailed investigation were carried out to develop suitable algorithms for automatic detection of foreign bodies. In order to achieve -besides the mere visual detection of foreign substances- also an automatic detection under production conditions, numerous experiences in image processing and pattern recognition are exploited. Results for the detection of foreign bodies will be presented at the conference showing the different advantages and disadvantages of using grey - level, statistical and morphological image processing techniques.

  2. Quantum illumination for enhanced detection of Rayleigh-fading targets

    NASA Astrophysics Data System (ADS)

    Zhuang, Quntao; Zhang, Zheshen; Shapiro, Jeffrey H.

    2017-08-01

    Quantum illumination (QI) is an entanglement-enhanced sensing system whose performance advantage over a comparable classical system survives its usage in an entanglement-breaking scenario plagued by loss and noise. In particular, QI's error-probability exponent for discriminating between equally likely hypotheses of target absence or presence is 6 dB higher than that of the optimum classical system using the same transmitted power. This performance advantage, however, presumes that the target return, when present, has known amplitude and phase, a situation that seldom occurs in light detection and ranging (lidar) applications. At lidar wavelengths, most target surfaces are sufficiently rough that their returns are speckled, i.e., they have Rayleigh-distributed amplitudes and uniformly distributed phases. QI's optical parametric amplifier receiver—which affords a 3 dB better-than-classical error-probability exponent for a return with known amplitude and phase—fails to offer any performance gain for Rayleigh-fading targets. We show that the sum-frequency generation receiver [Zhuang et al., Phys. Rev. Lett. 118, 040801 (2017), 10.1103/PhysRevLett.118.040801]—whose error-probability exponent for a nonfading target achieves QI's full 6 dB advantage over optimum classical operation—outperforms the classical system for Rayleigh-fading targets. In this case, QI's advantage is subexponential: its error probability is lower than the classical system's by a factor of 1 /ln(M κ ¯NS/NB) , when M κ ¯NS/NB≫1 , with M ≫1 being the QI transmitter's time-bandwidth product, NS≪1 its brightness, κ ¯ the target return's average intensity, and NB the background light's brightness.

  3. Added value of second biopsy target in screen-detected widespread suspicious breast calcifications.

    PubMed

    Falkner, Nathalie M; Hince, Dana; Porter, Gareth; Dessauvagie, Ben; Jeganathan, Sanjay; Bulsara, Max; Lo, Glen

    2018-06-01

    There is controversy on the optimal work-up of screen-detected widespread breast calcifications: whether to biopsy a single target or multiple targets. This study evaluates agreement between multiple biopsy targets within the same screen-detected widespread (≥25 mm) breast calcification to determine if the second biopsy adds value. Retrospective observational study of women screened in a statewide general population risk breast cancer mammographic screening program from 2009 to 2016. Screening episodes recalled for widespread calcifications where further views indicated biopsy, and two or more separate target areas were sampled within the same lesion were included. Percentage agreement and Cohen's Kappa were calculated. A total of 293317 women were screened during 761124 separate episodes with recalls for widespread calcifications in 2355 episodes. In 171 women, a second target was biopsied within the same lesion. In 149 (86%) cases, the second target biopsy result agreed with the first biopsy (κ = 0.6768). Agreement increased with increasing mammography score (85%, 86% and 92% for score 3, 4 and 5 lesions). Same day multiple biopsied lesions were three times more likely to yield concordant results compared to post-hoc second target biopsy cases. While a single target biopsy is sufficient to discriminate a benign vs. malignant diagnosis in most cases, in 14% there is added value in performing a second target biopsy. Biopsies performed prospectively are more likely to yield concordant results compared to post-hoc second target biopsy cases, suggesting a single prospective biopsy may be sufficient when results are radiological-pathological concordant; discordance still requires repeat sampling. © 2018 The Royal Australian and New Zealand College of Radiologists.

  4. A retrospective detection algorithm for extraction of weak targets in clutter and interference environments

    NASA Astrophysics Data System (ADS)

    Prengaman, R. J.; Thurber, R. E.; Bath, W. G.

    The usefulness of radar systems depends on the ability to distinguish between signals returned from desired targets and noise. A retrospective processor uses all contacts (or 'plots') from several past radar scans, taking into account all possible target trajectories formed from stored contacts for each input detection. The processor eliminates many false alarms, while retaining those contacts describing resonable trajectories. The employment of a retrospective processor makes it, therefore, possible to obtain large improvements in detection sensitivity in certain important clutter environments. Attention is given to the retrospective processing concept, a theoretical analysis of the multiscan detection process, the experimental evaluation of retrospective data filter, and aspects of retrospective data filter hardware implementation.

  5. A Real-Time Earthquake Precursor Detection Technique Using TEC from a GPS Network

    NASA Astrophysics Data System (ADS)

    Alp Akyol, Ali; Arikan, Feza; Arikan, Orhan

    2016-07-01

    Anomalies have been observed in the ionospheric electron density distribution prior to strong earthquakes. However, most of the reported results are obtained by earthquake analysis. Therefore, their implementation in practice is highly problematic. Recently, a novel earthquake precursor detection technique based on spatio-temporal analysis of Total Electron Content (TEC) data obtained from Turkish National Permanent GPS Network (TNPGN) is developed by IONOLAB group (www.ionolab.org). In the present study, the developed detection technique is implemented in a causal setup over the available data set in test phase that enables the real time implementation. The performance of the developed earthquake prediction technique is evaluated by using 10 fold cross validation over the data obtained in 2011. Among the 23 earthquakes that have magnitudes higher than 5, the developed technique can detect precursors of 14 earthquakes while producing 8 false alarms. This study is supported by TUBITAK 115E915 and Joint TUBITAK 114E092 and AS CR 14/001 projects.

  6. Detecting Proxima b’s Atmosphere with JWST Targeting CO{sub 2} at 15 μ m Using a High-pass Spectral Filtering Technique

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

    Snellen, I. A. G.; Van Dishoeck, E. F.; Brandl, B. R.

    Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μ m using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope ( JWST ). At superior conjunction, the planet is expected to show a contrast of up to 100 ppm with respect to the star. At a spectral resolving power of R  = 1790–2640, about 100 spectral CO{sub 2} features are visible within the 13.2–15.8 μ m (3B)more » band, which can be combined to boost the planet atmospheric signal by a factor of 3–4, depending on the atmospheric temperature structure and CO{sub 2} abundance. If atmospheric conditions are favorable (assuming an Earth-like atmosphere), with this new application to the cross-correlation technique, carbon dioxide can be detected within a few days of JWST observations. However, this can only be achieved if both the instrumental spectral response and the stellar spectrum can be determined to a relative precision of ≤1 × 10{sup −4} between adjacent spectral channels. Absolute flux calibration is not required, and the method is insensitive to the strong broadband variability of the host star. Precise calibration of the spectral features of the host star may only be attainable by obtaining deep observations of the system during inferior conjunction that serve as a reference. The high-pass filter spectroscopic technique with the MIRI MRS can be tested on warm Jupiters, Neptunes, and super-Earths with significantly higher planet/star contrast ratios than the Proxima system.« less

  7. Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

    NASA Technical Reports Server (NTRS)

    Coffin, Thomas; Jong, Jen-Yi

    1986-01-01

    An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

  8. Accuracy of software-assisted detection of tumour feeders in transcatheter hepatic chemoembolization using three target definition protocols.

    PubMed

    Iwazawa, J; Ohue, S; Hashimoto, N; Mitani, T

    2014-02-01

    To compare the accuracy of computer software analysis using three different target-definition protocols to detect tumour feeder vessels for transarterial chemoembolization of hepatocellular carcinoma. C-arm computed tomography (CT) data were analysed for 81 tumours from 57 patients who had undergone chemoembolization using software-assisted detection of tumour feeders. Small, medium, and large-sized targets were manually defined for each tumour. The tumour feeder was verified when the target tumour was enhanced on selective C-arm CT of the investigated vessel during chemoembolization. The sensitivity, specificity, and accuracy of the three protocols were evaluated and compared. One hundred and eight feeder vessels supplying 81 lesions were detected. The sensitivity of the small, medium, and large target protocols was 79.8%, 91.7%, and 96.3%, respectively; specificity was 95%, 88%, and 50%, respectively; and accuracy was 87.5%, 89.9%, and 74%, respectively. The sensitivity was significantly higher for the medium (p = 0.003) and large (p < 0.001) target protocols than for the small target protocol. The specificity and accuracy were higher for the small (p < 0.001 and p < 0.001, respectively) and medium (p < 0.001 and p < 0.001, respectively) target protocols than for the large target protocol. The overall accuracy of software-assisted automated feeder analysis in transarterial chemoembolization for hepatocellular carcinoma is affected by the target definition size. A large target definition increases sensitivity and decreases specificity in detecting tumour feeders. A target size equivalent to the tumour size most accurately predicts tumour feeders. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  9. Coherent beam combining of collimated fiber array based on target-in-the-loop technique

    NASA Astrophysics Data System (ADS)

    Li, Xinyang; Geng, Chao; Zhang, Xiaojun; Rao, Changhui

    2011-11-01

    Coherent beam combining (CBC) of fiber array is a promising way to generate high power and high quality laser beams. Target-in-the-loop (TIL) technique might be an effective way to ensure atmosphere propagation compensation without wavefront sensors. In this paper, we present very recent research work about CBC of collimated fiber array using TIL technique at the Key Lab on Adaptive Optics (KLAO), CAS. A novel Adaptive Fiber Optics Collimator (AFOC) composed of phase-locking module and tip/tilt control module was developed. CBC experimental setup of three-element fiber array was established. Feedback control is realized using stochastic parallel gradient descent (SPGD) algorithm. The CBC based on TIL with piston and tip/tilt correction simultaneously is demonstrated. And the beam pointing to locate or sweep position of combined spot on target was achieved through TIL technique too. The goal of our work is achieve multi-element CBC for long-distance transmission in atmosphere.

  10. Laser heterodyne detection techniques. [for atmospheric monitoring applications

    NASA Technical Reports Server (NTRS)

    Menzies, R. T.

    1976-01-01

    The principles of heterodyne radiometry are examined, taking into account thermal radiation, the Dicke microwave radiometer, photomixing in the infrared, and signal-to-noise considerations. The passive heterodyne radiometer is considered and a description is presented of heterodyne techniques in active monitoring systems. Attention is given to gas emissivities in the infrared, component requirements, experimental heterodyne detection of gases, a comparison of the passive heterodyne radiometer with the Michelson interferometer-spectrometer, airborne monitoring applications, turbulence effects on passive heterodyne radiometry, sensitivity improvements with heterodyning, atmosphere-induced degradation of bistatic system performance, pollutant detection experiments with a bistatic system, and the airborne laser absorption spectrometer. Future improvements in spectral flexibility are also discussed.

  11. Anatomical Regional Targeted (ART) BOTOX Injection Technique: A Novel Paradigm for Migraines and Chronic Headaches

    PubMed Central

    Sanniec, Kyle; Pezeshk, Ronnie; Chung, Michael

    2016-01-01

    Summary: Migraine headaches are a debilitating disease that causes significant socioeconomic problems. One of the speculated etiologies of the generation of migraines is peripheral nerve irritation at different trigger points. The use of Onabotulinum toxin A (BOTOX), although initially a novel approach, has now been determined to be a valid treatment for chronic headaches and migraines as described in the Phase III Research Evaluating Migraine Prophylaxis Therapy trials that prompted the approval by the Food and Drug Administration for treatment of chronic migraines. The injection paradigm established by this trial was one of a broad injection pattern across large muscle groups that did not always correspond to the anatomical locations of nerves. The senior author developed the Anatomical Regional Targeted BOTOX injection paradigm as an alternative to the current injection model. This technique targets both the anatomical location of nerves known to have causal effects with migraines and the region where the pain localizes, to provide relief across a wide distribution of the peripheral nerve. This article serves as a guide to the Anatomical Regional Targeted injection technique, which, to our knowledge, is the first comprehensive BOTOX injection paradigm described in the literature for treatment of migraines that targets nerves and nerve areas rather than purely muscle groups. This technique is based on the most up-to-date anatomical and scientific studies and large-volume migraine surgery experience. PMID:28293532

  12. Fluorescence turn-on detection of target sequence DNA based on silicon nanodot-mediated quenching.

    PubMed

    Zhang, Yanan; Ning, Xinping; Mao, Guobin; Ji, Xinghu; He, Zhike

    2018-05-01

    We have developed a new enzyme-free method for target sequence DNA detection based on the dynamic quenching of fluorescent silicon nanodots (SiNDs) toward Cy5-tagged DNA probe. Fascinatingly, the water-soluble SiNDs can quench the fluorescence of cyanine (Cy5) in Cy5-tagged DNA probe in homogeneous solution, and the fluorescence of Cy5-tagged DNA probe can be restored in the presence of target sequence DNA (the synthetic target miRNA-27a). Based on this phenomenon, a SiND-featured fluorescent sensor has been constructed for "turn-on" detection of the synthetic target miRNA-27a for the first time. This newly developed approach possesses the merits of low cost, simple design, and convenient operation since no enzymatic reaction, toxic reagents, or separation procedures are involved. The established method achieves a detection limit of 0.16 nM, and the relative standard deviation of this method is 9% (1 nM, n = 5). The linear range is 0.5-20 nM, and the recoveries in spiked human fluids are in the range of 90-122%. This protocol provides a new tactic in the development of the nonenzymic miRNA biosensors and opens a promising avenue for early diagnosis of miRNA-associated disease. Graphical abstract The SiND-based fluorescent sensor for detection of S-miR-27a.

  13. Prostate cancer detection in patients with prior negative biopsy undergoing cognitive-, robotic- or in-bore MRI target biopsy.

    PubMed

    Kaufmann, Sascha; Russo, Giorgio I; Bamberg, Fabian; Löwe, Lorenz; Morgia, Giuseppe; Nikolaou, Konstantin; Stenzl, Arnulf; Kruck, Stephan; Bedke, Jens

    2018-05-01

    To evaluate the detection rate among three different targeted biopsy approaches of robot-assisted MRI/TRUS fusion (RA-TB), mpMRI in-bore (MRGB), cognitive fusion guidance biopsy (COG-TB) for the detection of prostate cancer (PC) and clinically significant PC (csPC). Between 2014 and 2016, 156 patients with a lesion on mpMRI, performed in accordance with ESUR guidelines, due to cancer suspicion or on-going cancer suspicion after prior negative prostate biopsy, underwent targeted biopsy with RA-TB, MRGB or COG-TB. All lesions were rated according to PI-RADS v2. We compared detection rates between techniques. Models were constructed to predict the detection of overall PC and csPC and using a 1000 boot-strap sample. In the all cohort, 73, 45 and 38 patients underwent RA-TB, MRGB or COG-TB, respectively. Overall PC was found in 39 (52.42%), 23 (51.11%) and 11 (28.95%) (p = 0.04) patients of RA-TB, MRGB and COG-TB arm, respectively. As concerning the detection of csPC, it was found in 26 (35.62%),18 (40.0%) and 9 (23.68%) patients of RA-TB, MRGB and COG-TB arm (p = 0.27). Model 1 showed that RA-TB [OR: 10.08 (95% CI 1.95-51.97); p < 0.01] and MRGB [OR: 12.88 (95% CI 2.36-70.25); p < 0.01] were associated with overall PC detection in TB, while only MRGB was associated with csPC at TB (model 2) [OR: 5.72; (95% CI 1.40-23.35); p < 0.01]. The c-index for model 1 and model 2 was 0.86 and 0.85, respectively. We did not report significant complications between groups. In-bore biopsy and MRI/TRUS fusion-guided biopsy showed greater accuracy in detecting PC compared to cognitive fusion as modeled in a newly established normogram.

  14. Fractal analysis of seafloor textures for target detection in synthetic aperture sonar imagery

    NASA Astrophysics Data System (ADS)

    Nabelek, T.; Keller, J.; Galusha, A.; Zare, A.

    2018-04-01

    Fractal analysis of an image is a mathematical approach to generate surface related features from an image or image tile that can be applied to image segmentation and to object recognition. In undersea target countermeasures, the targets of interest can appear as anomalies in a variety of contexts, visually different textures on the seafloor. In this paper, we evaluate the use of fractal dimension as a primary feature and related characteristics as secondary features to be extracted from synthetic aperture sonar (SAS) imagery for the purpose of target detection. We develop three separate methods for computing fractal dimension. Tiles with targets are compared to others from the same background textures without targets. The different fractal dimension feature methods are tested with respect to how well they can be used to detect targets vs. false alarms within the same contexts. These features are evaluated for utility using a set of image tiles extracted from a SAS data set generated by the U.S. Navy in conjunction with the Office of Naval Research. We find that all three methods perform well in the classification task, with a fractional Brownian motion model performing the best among the individual methods. We also find that the secondary features are just as useful, if not more so, in classifying false alarms vs. targets. The best classification accuracy overall, in our experimentation, is found when the features from all three methods are combined into a single feature vector.

  15. Detection of cracks beneath rivet heads via pulsed eddy current technique

    NASA Astrophysics Data System (ADS)

    Giguère, J. S. R.; Lepine, B. A.; Dubois, J. M. S.

    2002-05-01

    Improving the detectability of fatigue cracks under installed fasteners is one of the many goals of the aging aircraft nondestructive evaluation (NDE) community. The pulsed eddy current offers new capabilities to address this requirement. The aim of the paper is to evaluate the potential of this technique for detecting and quantifying notches under installed fasteners.

  16. Risk maps for targeting exotic plant pest detection programs in the United States

    Treesearch

    R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al

    2011-01-01

    In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...

  17. Time reversal optical tomography and decomposition methods for detection and localization of targets in highly scattering turbid media

    NASA Astrophysics Data System (ADS)

    Wu, Binlin

    New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that

  18. Target-responsive DNAzyme cross-linked hydrogel for visual quantitative detection of lead.

    PubMed

    Huang, Yishun; Ma, Yanli; Chen, Yahong; Wu, Xuemeng; Fang, Luting; Zhu, Zhi; Yang, Chaoyong James

    2014-11-18

    Because of the severe health risks associated with lead pollution, rapid, sensitive, and portable detection of low levels of Pb(2+) in biological and environmental samples is of great importance. In this work, a Pb(2+)-responsive hydrogel was prepared using a DNAzyme and its substrate as cross-linker for rapid, sensitive, portable, and quantitative detection of Pb(2+). Gold nanoparticles (AuNPs) were first encapsulated in the hydrogel as an indicator for colorimetric analysis. In the absence of lead, the DNAzyme is inactive, and the substrate cross-linker maintains the hydrogel in the gel form. In contrast, the presence of lead activates the DNAzyme to cleave the substrate, decreasing the cross-linking density of the hydrogel and resulting in dissolution of the hydrogel and release of AuNPs for visual detection. As low as 10 nM Pb(2+) can be detected by the naked eye. Furthermore, to realize quantitative visual detection, a volumetric bar-chart chip (V-chip) was used for quantitative readout of the hydrogel system by replacing AuNPs with gold-platinum core-shell nanoparticles (Au@PtNPs). The Au@PtNPs released from the hydrogel upon target activation can efficiently catalyze the decomposition of H2O2 to generate a large volume of O2. The gas pressure moves an ink bar in the V-chip for portable visual quantitative detection of lead with a detection limit less than 5 nM. The device was able to detect lead in digested blood with excellent accuracy. The method developed can be used for portable lead quantitation in many applications. Furthermore, the method can be further extended to portable visual quantitative detection of a variety of targets by replacing the lead-responsive DNAzyme with other DNAzymes.

  19. The 'robustness' of vocabulary intervention in the public schools: targets and techniques employed in speech-language therapy.

    PubMed

    Justice, Laura M; Schmitt, Mary Beth; Murphy, Kimberly A; Pratt, Amy; Biancone, Tricia

    2014-01-01

    This study examined vocabulary intervention-in terms of targets and techniques-for children with language impairment receiving speech-language therapy in public schools (i.e., non-fee-paying schools) in the United States. Vocabulary treatments and targets were examined with respect to their alignment with the empirically validated practice of rich vocabulary intervention. Participants were forty-eight 5-7-year-old children participating in kindergarten or the first-grade year of school, all of whom had vocabulary-specific goals on their individualized education programmes. Two therapy sessions per child were coded to determine what vocabulary words were being directly targeted and what techniques were used for each. Study findings showed that the majority of words directly targeted during therapy were lower-level basic vocabulary words (87%) and very few (1%) were academically relevant. On average, three techniques were used per word to promote deep understanding. Interpreting findings against empirical descriptions of rich vocabulary intervention indicates that children were exposed to some but not all aspects of this empirically supported practice. © 2013 Royal College of Speech and Language Therapists.

  20. A New Strategy to Reduce Influenza Escape: Detecting Therapeutic Targets Constituted of Invariance Groups

    PubMed Central

    Lao, Julie; Vanet, Anne

    2017-01-01

    The pathogenicity of the different flu species is a real public health problem worldwide. To combat this scourge, we established a method to detect drug targets, reducing the possibility of escape. Besides being able to attach a drug candidate, these targets should have the main characteristic of being part of an essential viral function. The invariance groups that are sets of residues bearing an essential function can be detected genetically. They consist of invariant and synthetic lethal residues (interdependent residues not varying or slightly varying when together). We analyzed an alignment of more than 10,000 hemagglutinin sequences of influenza to detect six invariance groups, close in space, and on the protein surface. In parallel we identified five potential pockets on the surface of hemagglutinin. By combining these results, three potential binding sites were determined that are composed of invariance groups located respectively in the vestigial esterase domain, in the bottom of the stem and in the fusion area. The latter target is constituted of residues involved in the spring-loaded mechanism, an essential step in the fusion process. We propose a model describing how this potential target could block the reorganization of the hemagglutinin HA2 secondary structure and prevent viral entry into the host cell. PMID:28257108

  1. Colorimetric Detection of Small Molecules in Complex Matrixes via Target-Mediated Growth of Aptamer-Functionalized Gold Nanoparticles.

    PubMed

    Soh, Jun Hui; Lin, Yiyang; Rana, Subinoy; Ying, Jackie Y; Stevens, Molly M

    2015-08-04

    A versatile and sensitive colorimetric assay that allows the rapid detection of small-molecule targets using the naked eye is demonstrated. The working principle of the assay integrates aptamer-target recognition and the aptamer-controlled growth of gold nanoparticles (Au NPs). Aptamer-target interactions modulate the amount of aptamer strands adsorbed on the surface of aptamer-functionalized Au NPs via desorption of the aptamer strands when target molecules bind with the aptamer. Depending on the resulting aptamer coverage, Au NPs grow into morphologically varied nanostructures, which give rise to different colored solutions. Au NPs with low aptamer coverage grow into spherical NPs, which produce red-colored solutions, whereas Au NPs with high aptamer coverage grow into branched NPs, which produce blue-colored solutions. We achieved visible colorimetric response and nanomolar detection limits for the detection of ochratoxin A (1 nM) in red wine samples, as well as cocaine (1 nM) and 17β-estradiol (0.2 nM) in spiked synthetic urine and saliva, respectively. The detection limits were well within clinically and physiologically relevant ranges, and below the maximum food safety limits. The assay is highly sensitive, specific, and able to detect an array of analytes rapidly without requiring sophisticated equipment, making it relevant for many applications, such as high-throughput drug and clinical screening, food sampling, and diagnostics. Furthermore, the assay is easily adapted as a chip-based platform for rapid and portable target detection.

  2. Thermoacoustic molecular tomography with magnetic nanoparticle contrast agents for targeted tumor detection.

    PubMed

    Nie, Liming; Ou, Zhongmin; Yang, Sihua; Xing, Da

    2010-08-01

    The primary feasibility steps of demonstrating the ability of microwave-induced thermoacoustic (TA) in phantoms have been previously reported. However, none were shown to target a diseased site in living subjects in thermoacoustic tomography (TAT) field so far. To determine the expressions of oncogenic surface molecules, it is quite necessary to image tumor lesions and acquire pathogenic status on them via TAT. Compared to biological tissues, iron oxide nanoparticles have a much higher microwave absorbance. Fe3O4/polyaniline (PANI) nanoparticles were prepared via polymerization of aniline in the Fe304 superparamagnetic fluids. Then Fe3O4/PANI was conjugated to folic acid (FA), which can bind specifically to the surface of the folate receptor used as a tumor marker. FA-Fe3O4/PANI targeted tumor was irradiated by pulsed microwave at 6 GHz for thermoacoustic detection and imaging. The effect of the Fe3O4/PANI superparamagnetic nanoparticles for enhancing TAT images was successfully investigated in ex vivo human blood and in vivo mouse tail. Intravenous administration of the targeted nanoparticles to mice bearing tumors showed fivefold greater thermoacoustic signal and much longer elimination time than that of mice injected with nontargeted nanoparticles in the tumor. The specific targeting ability of FA-Fe3O4/PANI to tumor was also verified on fluorescence microscopy. Fabricated iron oxide nanoparticles conjugated with tumor ligands for targeted TAT tumor detection at the molecular level was reported for the first time. The results indicate that thermoacoustic molecular imaging with functionalized iron oxide nanoparticles may contribute to targeted and functional early cancer imaging. Also, the modified iron oxide nanoparticles combined with suitable tumor markers may also be used as novel nanomaterials for targeted and guided cancer thermal therapy.

  3. A leakage-free resonance sparse decomposition technique for bearing fault detection in gearboxes

    NASA Astrophysics Data System (ADS)

    Osman, Shazali; Wang, Wilson

    2018-03-01

    Most of rotating machinery deficiencies are related to defects in rolling element bearings. Reliable bearing fault detection still remains a challenging task, especially for bearings in gearboxes as bearing-defect-related features are nonstationary and modulated by gear mesh vibration. A new leakage-free resonance sparse decomposition (LRSD) technique is proposed in this paper for early bearing fault detection of gearboxes. In the proposed LRSD technique, a leakage-free filter is suggested to remove strong gear mesh and shaft running signatures. A kurtosis and cosine distance measure is suggested to select appropriate redundancy r and quality factor Q. The signal residual is processed by signal sparse decomposition for highpass and lowpass resonance analysis to extract representative features for bearing fault detection. The effectiveness of the proposed technique is verified by a succession of experimental tests corresponding to different gearbox and bearing conditions.

  4. Robust technique using an imaging plate to detect environmental radioactivity.

    PubMed

    Isobe, Tomonori; Mori, Yutaro; Takada, Kenta; Sato, Eisuke; Sakurai, Hideyuki; Sakae, Takeji

    2013-04-01

    The Fukushima Daiichi Nuclear Power Plant was severely damaged by the Great East Japan Earthquake on 11 March 2011. Consequently, a large amount of radioactive material was accidentally released. Recently, the focus has been on quantification of environmental radioactive material. However, conventional techniques require complicated and expensive measurement equipment. In this research, the authors developed a simple method to detect environmental radioactive material with an imaging plate (IP). Two specific measurement subjects were targeted: measurements for the depth distribution of radioactive material in soil and surface contamination of a building roof. For the measurement of depth distribution of radioactive material in soil, the authors ascertained that the concentration of environmental radioactivity was highest at 5 cm below the surface, and it decreased with depth. For the measurement of surface contamination of the building roof, the authors created a contamination map of the building roof. The detector developed could contact the ground directly, and unlike other survey meters, it was not influenced by peripheral radioactivity. In this study, the authors verified the feasibility of measurement of environmental radioactivity with an IP. Although the measured values of the IP were relative, further work is planned to perform evaluations of absolute quantities of radioactive material.

  5. Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

    NASA Astrophysics Data System (ADS)

    Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin

    2017-10-01

    Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

  6. A target detection multi-layer matched filter for color and hyperspectral cameras

    NASA Astrophysics Data System (ADS)

    Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

    2018-05-01

    In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

  7. Multispectral image fusion for target detection

    NASA Astrophysics Data System (ADS)

    Leviner, Marom; Maltz, Masha

    2009-09-01

    Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

  8. Statistical Techniques For Real-time Anomaly Detection Using Spark Over Multi-source VMware Performance Data

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

    Solaimani, Mohiuddin; Iftekhar, Mohammed; Khan, Latifur

    Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. Asmore » a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.« less

  9. Multiplexed target detection using DNA-binding dye chemistry in droplet digital PCR.

    PubMed

    McDermott, Geoffrey P; Do, Duc; Litterst, Claudia M; Maar, Dianna; Hindson, Christopher M; Steenblock, Erin R; Legler, Tina C; Jouvenot, Yann; Marrs, Samuel H; Bemis, Adam; Shah, Pallavi; Wong, Josephine; Wang, Shenglong; Sally, David; Javier, Leanne; Dinio, Theresa; Han, Chunxiao; Brackbill, Timothy P; Hodges, Shawn P; Ling, Yunfeng; Klitgord, Niels; Carman, George J; Berman, Jennifer R; Koehler, Ryan T; Hiddessen, Amy L; Walse, Pramod; Bousse, Luc; Tzonev, Svilen; Hefner, Eli; Hindson, Benjamin J; Cauly, Thomas H; Hamby, Keith; Patel, Viresh P; Regan, John F; Wyatt, Paul W; Karlin-Neumann, George A; Stumbo, David P; Lowe, Adam J

    2013-12-03

    Two years ago, we described the first droplet digital PCR (ddPCR) system aimed at empowering all researchers with a tool that removes the substantial uncertainties associated with using the analogue standard, quantitative real-time PCR (qPCR). This system enabled TaqMan hydrolysis probe-based assays for the absolute quantification of nucleic acids. Due to significant advancements in droplet chemistry and buoyed by the multiple benefits associated with dye-based target detection, we have created a "second generation" ddPCR system compatible with both TaqMan-probe and DNA-binding dye detection chemistries. Herein, we describe the operating characteristics of DNA-binding dye based ddPCR and offer a side-by-side comparison to TaqMan probe detection. By partitioning each sample prior to thermal cycling, we demonstrate that it is now possible to use a DNA-binding dye for the quantification of multiple target species from a single reaction. The increased resolution associated with partitioning also made it possible to visualize and account for signals arising from nonspecific amplification products. We expect that the ability to combine the precision of ddPCR with both DNA-binding dye and TaqMan probe detection chemistries will further enable the research community to answer complex and diverse genetic questions.

  10. Detection of irradiated spices using photo-stimulated luminescence technique (PSL)

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

    Ramli, Ros Anita Ahmad; Yasir, Muhamad Samudi; Othman, Zainon

    2014-09-03

    Photo-stimulated luminescence (PSL) technique was applied to detect irradiated black pepper (Piper nigrum), cinnamon (Cinnamomum verum) and turmeric (Curcuma longa) after dark storage for 1 day, 3 and 6 months. Using screening and calibrated PSL, all samples were correctly discriminated between non-irradiated and spices irradiated with doses 1, 5 and 10 kGy. The PSL photon counts (PCs) of irradiated spices increased with increasing dose, with turmeric showing highest sensitivity index to irradiation compared to black pepper and cinnamon. The differences in response are possibly attributed to the varying quantity and quality of silicate minerals present in each spice sample. PSLmore » signals of all irradiated samples reduced after 3 and 6 months storage. The results of this study provide a useful database on the applicability of PSL technique for the detection of Malaysian irradiated spices.« less

  11. Detection of irradiated spices using photo-stimulated luminescence technique (PSL)

    NASA Astrophysics Data System (ADS)

    Ramli, Ros Anita Ahmad; Yasir, Muhamad Samudi; Othman, Zainon; Abdullah, Wan Saffiey Wan

    2014-09-01

    Photo-stimulated luminescence (PSL) technique was applied to detect irradiated black pepper (Piper nigrum), cinnamon (Cinnamomum verum) and turmeric (Curcuma longa) after dark storage for 1 day, 3 and 6 months. Using screening and calibrated PSL, all samples were correctly discriminated between non-irradiated and spices irradiated with doses 1, 5 and 10 kGy. The PSL photon counts (PCs) of irradiated spices increased with increasing dose, with turmeric showing highest sensitivity index to irradiation compared to black pepper and cinnamon. The differences in response are possibly attributed to the varying quantity and quality of silicate minerals present in each spice sample. PSL signals of all irradiated samples reduced after 3 and 6 months storage. The results of this study provide a useful database on the applicability of PSL technique for the detection of Malaysian irradiated spices.

  12. Background Characterization Techniques For Pattern Recognition Applications

    NASA Astrophysics Data System (ADS)

    Noah, Meg A.; Noah, Paul V.; Schroeder, John W.; Kessler, Bernard V.; Chernick, Julian A.

    1989-08-01

    The Department of Defense has a requirement to investigate technologies for the detection of air and ground vehicles in a clutter environment. The use of autonomous systems using infrared, visible, and millimeter wave detectors has the potential to meet DOD's needs. In general, however, the hard-ware technology (large detector arrays with high sensitivity) has outpaced the development of processing techniques and software. In a complex background scene the "problem" is as much one of clutter rejection as it is target detection. The work described in this paper has investigated a new, and innovative, methodology for background clutter characterization, target detection and target identification. The approach uses multivariate statistical analysis to evaluate a set of image metrics applied to infrared cloud imagery and terrain clutter scenes. The techniques are applied to two distinct problems: the characterization of atmospheric water vapor cloud scenes for the Navy's Infrared Search and Track (IRST) applications to support the Infrared Modeling Measurement and Analysis Program (IRAMMP); and the detection of ground vehicles for the Army's Autonomous Homing Munitions (AHM) problems. This work was sponsored under two separate Small Business Innovative Research (SBIR) programs by the Naval Surface Warfare Center (NSWC), White Oak MD, and the Army Material Systems Analysis Activity at Aberdeen Proving Ground MD. The software described in this paper will be available from the respective contract technical representatives.

  13. Point Target Detection in IR Image Sequences using Spatio-Temporal Hypotheses Testing

    DTIC Science & Technology

    1999-02-01

    incorporate temporal as well as spatial infor- mation, they are often referred to as \\ track before detect " algorithms. The standard approach was to pose the...6, 3]. A drawback of these track - before - detect techniques is that they are very computationally intensive since the entire 3-D space must be ltered

  14. Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

    NASA Astrophysics Data System (ADS)

    Goel, Amit; Montgomery, Michele

    2015-08-01

    Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

  15. Surveillance theory applied to virus detection: a case for targeted discovery

    USGS Publications Warehouse

    Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

    2013-01-01

    Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

  16. Direct detection of sub-GeV dark matter with semiconductor targets

    DOE PAGES

    Essig, Rouven; Fernández-Serra, Marivi; Mardon, Jeremy; ...

    2016-05-09

    Dark matter in the sub-GeV mass range is a theoretically motivated but largely unexplored paradigm. Such light masses are out of reach for conventional nuclear recoil direct detection experiments, but may be detected through the small ionization signals caused by dark matter-electron scattering. Semiconductors are well-studied and are particularly promising target materials because their O(1 eV) band gaps allow for ionization signals from dark matter particles as light as a few hundred keV. Current direct detection technologies are being adapted for dark matter-electron scattering. In this paper, we provide the theoretical calculations for dark matter-electron scattering rate in semiconductors, overcomingmore » several complications that stem from the many-body nature of the problem. We use density functional theory to numerically calculate the rates for dark matter-electron scattering in silicon and germanium, and estimate the sensitivity for upcoming experiments such as DAMIC and SuperCDMS. We find that the reach for these upcoming experiments has the potential to be orders of magnitude beyond current direct detection constraints and that sub-GeV dark matter has a sizable modulation signal. We also give the first direct detection limits on sub-GeV dark matter from its scattering off electrons in a semiconductor target (silicon) based on published results from DAMIC. We make available publicly our code, QEdark, with which we calculate our results. Our results can be used by experimental collaborations to calculate their own sensitivities based on their specific setup. In conclusion, the searches we propose will probe vast new regions of unexplored dark matter model and parameter space.« less

  17. Toward automated selective retina treatment (SRT): an optical microbubble detection technique

    NASA Astrophysics Data System (ADS)

    Seifert, Eric; Park, Young-Gun; Theisen-Kunde, Dirk; Roh, Young-Jung; Brinkmann, Ralf

    2018-02-01

    Selective retina therapy (SRT) is an ophthalmological laser technique, targeting the retinal pigment epithelium (RPE) with repetitive microsecond laser pulses, while causing no thermal damage to the neural retina, the photoreceptors as well as the choroid. The RPE cells get damaged mechanically by microbubbles originating, at the intracellular melanosomes. Beneficial effects of SRT on Central Serous Retinopathy (CSR) and Diabetic Macula Edema (DME) have already been shown. Variations in the transmission of the anterior eye media and pigmentation variation of RPE yield in intra- and inter- individual thresholds of the pulse energy required for selective RPE damage. Those selective RPE lesions are not visible. Thus, dosimetry-systems, designed to detect microbubbles as an indicator for RPE cell damage, are demanded elements to facilitate SRT application. Therefore, a technique based on the evaluation of backscattered treatment light has been developed. Data of 127 spots, acquired during 10 clinical treatments of CSR patients, were assigned to a RPE cell damage class, validated by fluorescence angiography (FLA). An algorithm has been designed to match the FLA based information. A sensitivity of 0.9 with a specificity close to 1 is achieved. The data can be processed within microseconds. Thus, the process can be implemented in existing SRT lasers with an automatic pulse wise increasing energy and an automatic irradiation ceasing ability to enable automated treatment close above threshold to prevent adverse effects caused by too high pulse energy. Alternatively, a guidance procedure, informing the treating clinician about the adequacy of the actual settings, is possible.

  18. Detecting and visualizing weak signatures in hyperspectral data

    NASA Astrophysics Data System (ADS)

    MacPherson, Duncan James

    This thesis evaluates existing techniques for detecting weak spectral signatures from remotely sensed hyperspectral data. Algorithms are presented that successfully detect hard-to-find 'mystery' signatures in unknown cluttered backgrounds. The term 'mystery' is used to describe a scenario where the spectral target and background endmembers are unknown. Sub-Pixel analysis and background suppression are used to find deeply embedded signatures which can be less than 10% of the total signal strength. Existing 'mystery target' detection algorithms are derived and compared. Several techniques are shown to be superior both visually and quantitatively. Detection performance is evaluated using confidence metrics that are developed. A multiple algorithm approach is shown to improve detection confidence significantly. Although the research focuses on remote sensing applications, the algorithms presented can be applied to a wide variety of diverse fields such as medicine, law enforcement, manufacturing, earth science, food production, and astrophysics. The algorithms are shown to be general and can be applied to both the reflective and emissive parts of the electromagnetic spectrum. The application scope is a broad one and the final results open new opportunities for many specific applications including: land mine detection, pollution and hazardous waste detection, crop abundance calculations, volcanic activity monitoring, detecting diseases in food, automobile or airplane target recognition, cancer detection, mining operations, extracting galactic gas emissions, etc.

  19. Investigations of remote sensing techniques for early detection of Dutch elm disease

    NASA Technical Reports Server (NTRS)

    Hammerschlag, R. S.; Sopstyle, W. J.

    1975-01-01

    Several forms of aerial photography were pursued in quest of a technique which could provide early detection of Dutch elm disease. The two most promising techniques tested were multispectral photography with object enhancement and biband ratioing coupled with scanning microdensitometry. For practical purposes the multispectral system has the advantage of providing a readily interpretable image in a relatively short time. Laboratory studies indicated that less emphasis should be placed on the use of a red filter or the near infrared beyond 750 mm for early detection of stress within a single plant species. Color infrared film would be optimal when used for a long term detection of loss of plant vigor which results in a physical change in a plant canopy, but should find minimal practicality for early detection of specific sources of plant stress such as Dutch elm disease. Considerable discretion should be used when interpreting imagery on copy film because of loss of resolution and color definition.

  20. Selective tuning of the right inferior frontal gyrus during target detection

    PubMed Central

    Hampshire, Adam; Thompson, Russell; Duncan, John; Owen, Adrian M.

    2010-01-01

    In the human brain, a network of frontal and parietal regions is commonly recruited during tasks that demand the deliberate, focused control of thought and action. Previously, using a simple target detection task, we reported striking differences in the selectivity of the BOLD response in anatomically distinct subregions of this network. In particular, it was observed that the right inferior frontal gyrus (IFG) followed a tightly tuned function, selectively responding only to the current target object. Here, we examine this functional specialization further, using adapted versions of our original task. Our results demonstrate that the response of the right IFG to targets is a strong and replicable phenomenon. It occurs under increased attentional load, when targets and distractors are equally frequent, and when controlling for inhibitory processes. These findings support the hypothesis that the right IFG responds selectively to those items that are of the most relevance to the currently intended task schema. PMID:19246331