Multichannel imager for littoral zone characterization

NASA Astrophysics Data System (ADS)

Podobna, Yuliya; Schoonmaker, Jon; Dirbas, Joe; Sofianos, James; Boucher, Cynthia; Gilbert, Gary

2010-04-01

This paper describes an approach to utilize a multi-channel, multi-spectral electro-optic (EO) system for littoral zone characterization. Advanced Coherent Technologies, LLC (ACT) presents their EO sensor systems for the surf zone environmental assessment and potential surf zone target detection. Specifically, an approach is presented to determine a Surf Zone Index (SZI) from the multi-spectral EO sensor system. SZI provides a single quantitative value of the surf zone conditions delivering an immediate understanding of the area and an assessment as to how well an airborne optical system might perform in a mine countermeasures (MCM) operation. Utilizing consecutive frames of SZI images, ACT is able to measure variability over time. A surf zone nomograph, which incorporates targets, sensor, and environmental data, including the SZI to determine the environmental impact on system performance, is reviewed in this work. ACT's electro-optical multi-channel, multi-spectral imaging system and test results are presented and discussed.

Multi-wall carbon nanotubes (MWCNTs)-doped polypyrrole DNA biosensor for label-free detection of genetically modified organisms by QCM and EIS.

PubMed

Truong, Thi Ngoc Lien; Tran, Dai Lam; Vu, Thi Hong An; Tran, Vinh Hoang; Duong, Tuan Quang; Dinh, Quang Khieu; Tsukahara, Toshifumi; Lee, Young Hoon; Kim, Jong Seung

2010-01-15

In this paper, we describe DNA electrochemical detection for genetically modified organism (GMO) based on multi-wall carbon nanotubes (MWCNTs)-doped polypyrrole (PPy). DNA hybridization is studied by quartz crystal microbalance (QCM) and electrochemical impedance spectroscopy (EIS). An increase in DNA complementary target concentration results in a decrease in the faradic charge transfer resistance (R(ct)) and signifying "signal-on" behavior of MWCNTs-PPy-DNA system. QCM and EIS data indicated that the electroanalytical MWCNTs-PPy films were highly sensitive (as low as 4pM of target can be detected with QCM technique). In principle, this system can be suitable not only for DNA but also for protein biosensor construction.

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.

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.

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 eliminate noise, improve signal-to-noise ratio, then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line ,so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background.

Distributed micro-radar system for detection and tracking of low-profile, low-altitude targets

NASA Astrophysics Data System (ADS)

Gorwara, Ashok; Molchanov, Pavlo

2016-05-01

Proposed airborne surveillance radar system can detect, locate, track, and classify low-profile, low-altitude targets: from traditional fixed and rotary wing aircraft to non-traditional targets like unmanned aircraft systems (drones) and even small projectiles. Distributed micro-radar system is the next step in the development of passive monopulse direction finder proposed by Stephen E. Lipsky in the 80s. To extend high frequency limit and provide high sensitivity over the broadband of frequencies, multiple angularly spaced directional antennas are coupled with front end circuits and separately connected to a direction finder processor by a digital interface. Integration of antennas with front end circuits allows to exclude waveguide lines which limits system bandwidth and creates frequency dependent phase errors. Digitizing of received signals proximate to antennas allows loose distribution of antennas and dramatically decrease phase errors connected with waveguides. Accuracy of direction finding in proposed micro-radar in this case will be determined by time accuracy of digital processor and sampling frequency. Multi-band, multi-functional antennas can be distributed around the perimeter of a Unmanned Aircraft System (UAS) and connected to the processor by digital interface or can be distributed between swarm/formation of mini/micro UAS and connected wirelessly. Expendable micro-radars can be distributed by perimeter of defense object and create multi-static radar network. Low-profile, lowaltitude, high speed targets, like small projectiles, create a Doppler shift in a narrow frequency band. This signal can be effectively filtrated and detected with high probability. Proposed micro-radar can work in passive, monostatic or bistatic regime.

Analysis of the development of missile-borne IR imaging detecting technologies

NASA Astrophysics Data System (ADS)

Fan, Jinxiang; Wang, Feng

2017-10-01

Today's infrared imaging guiding missiles are facing many challenges. With the development of targets' stealth, new-style IR countermeasures and penetrating technologies as well as the complexity of the operational environments, infrared imaging guiding missiles must meet the higher requirements of efficient target detection, capability of anti-interference and anti-jamming and the operational adaptability in complex, dynamic operating environments. Missileborne infrared imaging detecting systems are constrained by practical considerations like cost, size, weight and power (SWaP), and lifecycle requirements. Future-generation infrared imaging guiding missiles need to be resilient to changing operating environments and capable of doing more with fewer resources. Advanced IR imaging detecting and information exploring technologies are the key technologies that affect the future direction of IR imaging guidance missiles. Infrared imaging detecting and information exploring technologies research will support the development of more robust and efficient missile-borne infrared imaging detecting systems. Novelty IR imaging technologies, such as Infrared adaptive spectral imaging, are the key to effectively detect, recognize and track target under the complicated operating and countermeasures environments. Innovative information exploring techniques for the information of target, background and countermeasures provided by the detection system is the base for missile to recognize target and counter interference, jamming and countermeasure. Modular hardware and software development is the enabler for implementing multi-purpose, multi-function solutions. Uncooled IRFPA detectors and High-operating temperature IRFPA detectors as well as commercial-off-the-shelf (COTS) technology will support the implementing of low-cost infrared imaging guiding missiles. In this paper, the current status and features of missile-borne IR imaging detecting technologies are summarized. The key technologies and its development trends of missiles' IR imaging detecting technologies are analyzed.

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.

Multi-channel, passive, short-range anti-aircraft defence system

NASA Astrophysics Data System (ADS)

Gapiński, Daniel; Krzysztofik, Izabela; Koruba, Zbigniew

2018-01-01

The paper presents a novel method for tracking several air targets simultaneously. The developed concept concerns a multi-channel, passive, short-range anti-aircraft defence system based on the programmed selection of air targets and an algorithm of simultaneous synchronisation of several modified optical scanning seekers. The above system is supposed to facilitate simultaneous firing of several self-guided infrared rocket missiles at many different air targets. From the available information, it appears that, currently, there are no passive self-guided seekers that fulfil such tasks. This paper contains theoretical discussions and simulations of simultaneous detection and tracking of many air targets by mutually integrated seekers of several rocket missiles. The results of computer simulation research have been presented in a graphical form.

Visual Detection and Tracking System for a Spherical Amphibious Robot

PubMed Central

Guo, Shuxiang; Pan, Shaowu; Shi, Liwei; Guo, Ping; He, Yanlin; Tang, Kun

2017-01-01

With the goal of supporting close-range observation tasks of a spherical amphibious robot, such as ecological observations and intelligent surveillance, a moving target detection and tracking system was designed and implemented in this study. Given the restrictions presented by the amphibious environment and the small-sized spherical amphibious robot, an industrial camera and vision algorithms using adaptive appearance models were adopted to construct the proposed system. To handle the problem of light scattering and absorption in the underwater environment, the multi-scale retinex with color restoration algorithm was used for image enhancement. Given the environmental disturbances in practical amphibious scenarios, the Gaussian mixture model was used to detect moving targets entering the field of view of the robot. A fast compressive tracker with a Kalman prediction mechanism was used to track the specified target. Considering the limited load space and the unique mechanical structure of the robot, the proposed vision system was fabricated with a low power system-on-chip using an asymmetric and heterogeneous computing architecture. Experimental results confirmed the validity and high efficiency of the proposed system. The design presented in this paper is able to meet future demands of spherical amphibious robots in biological monitoring and multi-robot cooperation. PMID:28420134

Visual Detection and Tracking System for a Spherical Amphibious Robot.

PubMed

Guo, Shuxiang; Pan, Shaowu; Shi, Liwei; Guo, Ping; He, Yanlin; Tang, Kun

2017-04-15

With the goal of supporting close-range observation tasks of a spherical amphibious robot, such as ecological observations and intelligent surveillance, a moving target detection and tracking system was designed and implemented in this study. Given the restrictions presented by the amphibious environment and the small-sized spherical amphibious robot, an industrial camera and vision algorithms using adaptive appearance models were adopted to construct the proposed system. To handle the problem of light scattering and absorption in the underwater environment, the multi-scale retinex with color restoration algorithm was used for image enhancement. Given the environmental disturbances in practical amphibious scenarios, the Gaussian mixture model was used to detect moving targets entering the field of view of the robot. A fast compressive tracker with a Kalman prediction mechanism was used to track the specified target. Considering the limited load space and the unique mechanical structure of the robot, the proposed vision system was fabricated with a low power system-on-chip using an asymmetric and heterogeneous computing architecture. Experimental results confirmed the validity and high efficiency of the proposed system. The design presented in this paper is able to meet future demands of spherical amphibious robots in biological monitoring and multi-robot cooperation.

MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

NASA Astrophysics Data System (ADS)

Huang, Weiqing; Hou, Erhang; Zheng, Liang; Feng, Weimiao

2018-05-01

In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes' effectiveness in Android malware detection.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

Research and development of a control system for multi axis cooperative motion based on PMAC

NASA Astrophysics Data System (ADS)

Guo, Xiao-xiao; Dong, Deng-feng; Zhou, Wei-hu

2017-10-01

Based on Programmable Multi-axes Controller (PMAC), a design of a multi axis motion control system for the simulator of spatial targets' dynamic optical properties is proposed. According to analysis the properties of spatial targets' simulator motion control system, using IPC as the main control layer, TurboPMAC2 as the control layer to meet coordinated motion control, data acquisition and analog output. A simulator using 5 servomotors which is connected with speed reducers to drive the output axis was implemented to simulate the motion of both the sun and the space target. Based on PMAC using PID and a notch filter algorithm, negative feedback, the speed and acceleration feed forward algorithm to satisfy the axis' requirements of the good stability and high precision at low speeds. In the actual system, it shows that the velocity precision is higher than 0.04 s ° and the precision of repetitive positioning is better than 0.006° when each axis is at a low-speed. Besides, the system achieves the control function of multi axis coordinated motion. The design provides an important technical support for detecting spatial targets, also promoting the theoretical research.

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

Intermolecular G-quadruplex structure-based fluorescent DNA detection system.

PubMed

Zhou, Hui; Wu, Zai-Sheng; Shen, Guo-Li; Yu, Ru-Qin

2013-03-15

Adopting multi-donors to pair with one acceptor could improve the performance of fluorogenic detection probes. However, common dyes (e.g., fluorescein) in close proximity to each other would self-quench the fluorescence, and the fluorescence is difficult to restore. In this contribution, we constructed a novel "multi-donors-to-one acceptor" fluorescent DNA detection system by means of the intermolecular G-quadruplex (IGQ) structure-based fluorescence signal enhancement combined with the hairpin oligonucleotide. The novel IGQ-hairpin system was characterized using the p53 gene as the model target DNA. The proposed system showed an improved assay performance due to the introduction of IGQ-structure into fluorescent signaling probes, which could inhibit the background fluorescence and increase fluorescence restoration amplitude of fluoresceins upon target DNA hybridization. The proof-of-concept scheme is expected to provide new insight into the potential of G-quadruplex structure and promote the application of fluorescent oligonucleotide probes in fundamental research, diagnosis, and treatment of genetic diseases. Copyright © 2012 Elsevier B.V. All rights reserved.

Improving resolution of dynamic communities in human brain networks through targeted node removal

PubMed Central

Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2017-01-01

Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662

Multiview face detection based on position estimation over multicamera surveillance system

NASA Astrophysics Data System (ADS)

Huang, Ching-chun; Chou, Jay; Shiu, Jia-Hou; Wang, Sheng-Jyh

2012-02-01

In this paper, we propose a multi-view face detection system that locates head positions and indicates the direction of each face in 3-D space over a multi-camera surveillance system. To locate 3-D head positions, conventional methods relied on face detection in 2-D images and projected the face regions back to 3-D space for correspondence. However, the inevitable false face detection and rejection usually degrades the system performance. Instead, our system searches for the heads and face directions over the 3-D space using a sliding cube. Each searched 3-D cube is projected onto the 2-D camera views to determine the existence and direction of human faces. Moreover, a pre-process to estimate the locations of candidate targets is illustrated to speed-up the searching process over the 3-D space. In summary, our proposed method can efficiently fuse multi-camera information and suppress the ambiguity caused by detection errors. Our evaluation shows that the proposed approach can efficiently indicate the head position and face direction on real video sequences even under serious occlusion.

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

NASA Astrophysics Data System (ADS)

Li, Yu; Xiao, Gang

2011-08-01

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

On-chip wavelength multiplexed detection of cancer DNA biomarkers in blood

PubMed Central

Cai, H.; Stott, M. A.; Ozcelik, D.; Parks, J. W.; Hawkins, A. R.; Schmidt, H.

2016-01-01

We have developed an optofluidic analysis system that processes biomolecular samples starting from whole blood and then analyzes and identifies multiple targets on a silicon-based molecular detection platform. We demonstrate blood filtration, sample extraction, target enrichment, and fluorescent labeling using programmable microfluidic circuits. We detect and identify multiple targets using a spectral multiplexing technique based on wavelength-dependent multi-spot excitation on an antiresonant reflecting optical waveguide chip. Specifically, we extract two types of melanoma biomarkers, mutated cell-free nucleic acids —BRAFV600E and NRAS, from whole blood. We detect and identify these two targets simultaneously using the spectral multiplexing approach with up to a 96% success rate. These results point the way toward a full front-to-back chip-based optofluidic compact system for high-performance analysis of complex biological samples. PMID:28058082

The Performance Analysis Based on SAR Sample Covariance Matrix

PubMed Central

Erten, Esra

2012-01-01

Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given. PMID:22736976

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.

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

A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

NASA Astrophysics Data System (ADS)

Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan

2018-03-01

False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

PubMed

Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J

2014-02-01

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

Robust pedestrian detection and tracking from a moving vehicle

NASA Astrophysics Data System (ADS)

Tuong, Nguyen Xuan; Müller, Thomas; Knoll, Alois

2011-01-01

In this paper, we address the problem of multi-person detection, tracking and distance estimation in a complex scenario using multi-cameras. Specifically, we are interested in a vision system for supporting the driver in avoiding any unwanted collision with the pedestrian. We propose an approach using Histograms of Oriented Gradients (HOG) to detect pedestrians on static images and a particle filter as a robust tracking technique to follow targets from frame to frame. Because the depth map requires expensive computation, we extract depth information of targets using Direct Linear Transformation (DLT) to reconstruct 3D-coordinates of correspondent points found by running Speeded Up Robust Features (SURF) on two input images. Using the particle filter the proposed tracker can efficiently handle target occlusions in a simple background environment. However, to achieve reliable performance in complex scenarios with frequent target occlusions and complex cluttered background, results from the detection module are integrated to create feedback and recover the tracker from tracking failures due to the complexity of the environment and target appearance model variability. The proposed approach is evaluated on different data sets both in a simple background scenario and a cluttered background environment. The result shows that, by integrating detector and tracker, a reliable and stable performance is possible even if occlusion occurs frequently in highly complex environment. A vision-based collision avoidance system for an intelligent car, as a result, can be achieved.

Investigation of the detection of shallow tunnels using electromagnetic and seismic waves

NASA Astrophysics Data System (ADS)

Counts, Tegan; Larson, Gregg; Gürbüz, Ali Cafer; McClellan, James H.; Scott, Waymond R., Jr.

2007-04-01

Multimodal detection of subsurface targets such as tunnels, pipes, reinforcement bars, and structures has been investigated using both ground-penetrating radar (GPR) and seismic sensors with signal processing techniques to enhance localization capabilities. Both systems have been tested in bi-static configurations but the GPR has been expanded to a multi-static configuration for improved performance. The use of two compatible sensors that sense different phenomena (GPR detects changes in electrical properties while the seismic system measures mechanical properties) increases the overall system's effectiveness in a wider range of soils and conditions. Two experimental scenarios have been investigated in a laboratory model with nearly homogeneous sand. Images formed from the raw data have been enhanced using beamforming inversion techniques and Hough Transform techniques to specifically address the detection of linear targets. The processed data clearly indicate the locations of the buried targets of various sizes at a range of depths.

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.

Calibration Method for IATS and Application in Multi-Target Monitoring Using Coded Targets

NASA Astrophysics Data System (ADS)

Zhou, Yueyin; Wagner, Andreas; Wunderlich, Thomas; Wasmeier, Peter

2017-06-01

The technique of Image Assisted Total Stations (IATS) has been studied for over ten years and is composed of two major parts: one is the calibration procedure which combines the relationship between the camera system and the theodolite system; the other is the automatic target detection on the image by various methods of photogrammetry or computer vision. Several calibration methods have been developed, mostly using prototypes with an add-on camera rigidly mounted on the total station. However, these prototypes are not commercially available. This paper proposes a calibration method based on Leica MS50 which has two built-in cameras each with a resolution of 2560 × 1920 px: an overview camera and a telescope (on-axis) camera. Our work in this paper is based on the on-axis camera which uses the 30-times magnification of the telescope. The calibration consists of 7 parameters to estimate. We use coded targets, which are common tools in photogrammetry for orientation, to detect different targets in IATS images instead of prisms and traditional ATR functions. We test and verify the efficiency and stability of this monitoring method with multi-target.

A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

2011-06-01

We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

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.

Development and human factors analysis of an augmented reality interface for multi-robot tele-operation and control

NASA Astrophysics Data System (ADS)

Lee, Sam; Lucas, Nathan P.; Ellis, R. Darin; Pandya, Abhilash

2012-06-01

This paper presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semiautonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor's ability to control multiple robots. The role of this human multi-robot interface is to allow an operator to control groups of heterogeneous robots in real time in a collaborative manner. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. Each robot knows the environment and obstacles and can automatically generate a collision-free path to any user-selected target. It displayed sensor information from each individual robot directly on the robot in the video view. In addition, a sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks. Results show that the novel Augmented Reality multi-robot control (Point-and-Go and Path Planning) reduced mission completion times compared to the traditional joystick control for target detection missions. Usability tests and operator workload analysis are also investigated.

Detection and identification of 700 drugs by multi-target screening with a 3200 Q TRAP LC-MS/MS system and library searching.

PubMed

Dresen, S; Ferreirós, N; Gnann, H; Zimmermann, R; Weinmann, W

2010-04-01

The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

Electromagnetic packable technology (EMPACT) for detection and characterization of ordnance in post-conflict areas

NASA Astrophysics Data System (ADS)

Schultz, Gregory; Miller, Jonathan; Keranen, Joe

2013-06-01

Land reclamation efforts in post-conflict regions are often hampered by the presence of Unexploded Ordnance (UXO) or other Explosive Remnants of War (ERW). Surface geophysical methods, such as Electromagnetic Induction (EMI) and magnetometry, are typically applied to screen rehabilitation areas for UXO prior to excavation; however, the prevalence of innocuous magnetic clutter related to indigenous scrap, fragmentation, or geology can severely impede the progress and efficiency of these remediation efforts. Additionally, the variability in surface conditions and local topography necessitates the development of sensor technologies that can be applied to a range of sites including those that prohibit the use of vehicle-mounted or large array systems. We present a man-portable EMI sensor known as the Electromagnetic Packable Technology (EMPACT) system that features a multi-axis sensor configuration in a compact form factor. The system is designed for operation in challenging site conditions and can be used in low ground-standoff modes to detect small and low-metal content objects. The EMPACT acquires high spatial density, multi-axis data that enable high resolution of small objects. This high density data can also be used to provide characterization of target physical features, such as size, material content, and shape. We summarize the development of this system for humanitarian demining operations and present results from preliminary system evaluations against a range of target types. Specifically, we assess the general detection capabilities of the EMPACT system and we evaluate the potential for target classification based on analysis of data and target model features.

Enhanced optical fiber fluorometer using a periodic perturbation in the fiber core

NASA Astrophysics Data System (ADS)

Chiniforooshan, Yasser; Bock, Wojtek J.; Ma, Jianjun

2013-10-01

Tracing of the specific chemicals and biological agents in a solution is becoming a vital interest in health, security and safety industries. Although a number of standard laboratory-based testing systems exists for detecting such targets, but the fast, real-time and on-site methods could be more efficient and cost-effective. One of the most common ways to detect a target in the solution is to use the fluorophore molecules which will be selectively attached to the targets and will emit or quench the fluorescence in presence of the target. The fiber-optic fluorometers are developed for inexpensive and portable detection. In this paper, we explain a novel multi-segment fiber structure which uses the periodic perturbation on the side-wall of a highly multi-mode fiber to enhance collecting the fluorescent light. This periodic perturbation is fabricated and optimized on the core of the fiber using a CO2 laser. The theoretical explanation to show the physical principle of the structure is followed by the experimental evidence of its functioning.

Handheld microwave bomb-detecting imaging system

NASA Astrophysics Data System (ADS)

Gorwara, Ashok; Molchanov, Pavlo

2017-05-01

Proposed novel imaging technique will provide all weather high-resolution imaging and recognition capability for RF/Microwave signals with good penetration through highly scattered media: fog, snow, dust, smoke, even foliage, camouflage, walls and ground. Image resolution in proposed imaging system is not limited by diffraction and will be determined by processor and sampling frequency. Proposed imaging system can simultaneously cover wide field of view, detect multiple targets and can be multi-frequency, multi-function. Directional antennas in imaging system can be close positioned and installed in cell phone size handheld device, on small aircraft or distributed around protected border or object. Non-scanning monopulse system allows dramatically decrease in transmitting power and at the same time provides increased imaging range by integrating 2-3 orders more signals than regular scanning imaging systems.

Study of multi-channel optical system based on the compound eye

NASA Astrophysics Data System (ADS)

Zhao, Yu; Fu, Yuegang; Liu, Zhiying; Dong, Zhengchao

2014-09-01

As an important part of machine vision, compound eye optical systems have the characteristics of high resolution and large FOV. By applying the compound eye optical systems to target detection and recognition, the contradiction between large FOV and high resolution in the traditional single aperture optical systems could be solved effectively and also the parallel processing ability of the optical systems could be sufficiently shown. In this paper, the imaging features of the compound eye optical systems are analyzed. After discussing the relationship between the FOV in each subsystem and the contact ratio of the FOV in the whole system, a method to define the FOV of the subsystem is presented. And a compound eye optical system is designed, which is based on the large FOV synthesized of multi-channels. The compound eye optical system consists with a central optical system and array subsystem, in which the array subsystem is used to capture the target. The high resolution image of the target could be achieved by the central optical system. With the advantage of small volume, light weight and rapid response speed, the optical system could detect the objects which are in 3km and FOV of 60°without any scanning device. The objects in the central field 2w=5.1°could be imaged with high resolution so that the objects could be recognized.

Neural Network Target Identification System for False Alarm Reduction

NASA Technical Reports Server (NTRS)

Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

Optimization of Adaboost Algorithm for Sonar Target Detection in a Multi-Stage ATR System

NASA Technical Reports Server (NTRS)

Lin, Tsung Han (Hank)

2011-01-01

JPL has developed a multi-stage Automated Target Recognition (ATR) system to locate objects in images. First, input images are preprocessed and sent to a Grayscale Optical Correlator (GOC) filter to identify possible regions-of-interest (ROIs). Second, feature extraction operations are performed using Texton filters and Principal Component Analysis (PCA). Finally, the features are fed to a classifier, to identify ROIs that contain the targets. Previous work used the Feed-forward Back-propagation Neural Network for classification. In this project we investigate a version of Adaboost as a classifier for comparison. The version we used is known as GentleBoost. We used the boosted decision tree as the weak classifier. We have tested our ATR system against real-world sonar images using the Adaboost approach. Results indicate an improvement in performance over a single Neural Network design.

Camouflage target reconnaissance based on hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Hua, Wenshen; Guo, Tong; Liu, Xun

2015-08-01

Efficient camouflaged target reconnaissance technology makes great influence on modern warfare. Hyperspectral images can provide large spectral range and high spectral resolution, which are invaluable in discriminating between camouflaged targets and backgrounds. Hyperspectral target detection and classification technology are utilized to achieve single class and multi-class camouflaged targets reconnaissance respectively. Constrained energy minimization (CEM), a widely used algorithm in hyperspectral target detection, is employed to achieve one class camouflage target reconnaissance. Then, support vector machine (SVM), a classification method, is proposed to achieve multi-class camouflage target reconnaissance. Experiments have been conducted to demonstrate the efficiency of the proposed method.

Development and validation of a 48-target analytical method for high-throughput monitoring of genetically modified organisms.

PubMed

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-05

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection.

Development and Validation of A 48-Target Analytical Method for High-throughput Monitoring of Genetically Modified Organisms

PubMed Central

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-01

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection. PMID:25556930

Low power multi-camera system and algorithms for automated threat detection

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak; Chen, Yang; Van Buer, Darrel J.; Martin, Kevin

2013-05-01

A key to any robust automated surveillance system is continuous, wide field-of-view sensor coverage and high accuracy target detection algorithms. Newer systems typically employ an array of multiple fixed cameras that provide individual data streams, each of which is managed by its own processor. This array can continuously capture the entire field of view, but collecting all the data and back-end detection algorithm consumes additional power and increases the size, weight, and power (SWaP) of the package. This is often unacceptable, as many potential surveillance applications have strict system SWaP requirements. This paper describes a wide field-of-view video system that employs multiple fixed cameras and exhibits low SWaP without compromising the target detection rate. We cycle through the sensors, fetch a fixed number of frames, and process them through a modified target detection algorithm. During this time, the other sensors remain powered-down, which reduces the required hardware and power consumption of the system. We show that the resulting gaps in coverage and irregular frame rate do not affect the detection accuracy of the underlying algorithms. This reduces the power of an N-camera system by up to approximately N-fold compared to the baseline normal operation. This work was applied to Phase 2 of DARPA Cognitive Technology Threat Warning System (CT2WS) program and used during field testing.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-01

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation. Electronic supplementary information (ESI) available: Additional figures (Tables S1-S3 and Fig. S1-S6). See DOI: 10.1039/c6nr01072e

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

NASA Astrophysics Data System (ADS)

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

2009-10-01

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

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.

Multi-Target Camera Tracking, Hand-off and Display LDRD 158819 Final Report

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

Anderson, Robert J.

2014-10-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn’t lead to more alarms, moremore » monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identify individual moving targets from the background imagery, and then display the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.« less

Multi-target camera tracking, hand-off and display LDRD 158819 final report

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

Anderson, Robert J.

2014-10-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn't lead to more alarms, moremore » monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identifies individual moving targets from the background imagery, and then displays the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.« less

Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

PubMed Central

Joshi, Bishnu P.; Wang, Thomas D.

2010-01-01

Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research. PMID:22180839

Using queuing models to aid design and guide research effort for multimodality buried target detection systems

NASA Astrophysics Data System (ADS)

Malof, Jordan M.; Collins, Leslie M.

2016-05-01

Many remote sensing modalities have been developed for buried target detection (BTD), each one offering relative advantages over the others. There has been interest in combining several modalities into a single BTD system that benefits from the advantages of each constituent sensor. Recently an approach was developed, called multi-state management (MSM), that aims to achieve this goal by separating BTD system operation into discrete states, each with different sensor activity and system velocity. Additionally, a modeling approach, called Q-MSM, was developed to quickly analyze multi-modality BTD systems operating with MSM. This work extends previous work by demonstrating how Q-MSM modeling can be used to design BTD systems operating with MSM, and to guide research to yield the most performance benefits. In this work an MSM system is considered that combines a forward-looking infrared (FLIR) camera and a ground penetrating radar (GPR). Experiments are conducted using a dataset of real, field-collected, data which demonstrates how the Q-MSM model can be used to evaluate performance benefits of altering, or improving via research investment, various characteristics of the GPR and FLIR systems. Q-MSM permits fast analysis that can determine where system improvements will have the greatest impact, and can therefore help guide BTD research.

Research on the strategy of underwater united detection fusion and communication using multi-sensor

NASA Astrophysics Data System (ADS)

Xu, Zhenhua; Huang, Jianguo; Huang, Hai; Zhang, Qunfei

2011-09-01

In order to solve the distributed detection fusion problem of underwater target detection, when the signal to noise ratio (SNR) of the acoustic channel is low, a new strategy for united detection fusion and communication using multiple sensors was proposed. The performance of detection fusion was studied and compared based on the Neyman-Pearson principle when the binary phase shift keying (BPSK) and on-off keying (OOK) modes were used by the local sensors. The comparative simulation and analysis between the optimal likelihood ratio test and the proposed strategy was completed, and both the theoretical analysis and simulation indicate that using the proposed new strategy could improve the detection performance effectively. In theory, the proposed strategy of united detection fusion and communication is of great significance to the establishment of an underwater target detection system.

Development of a real time multiple target, multi camera tracker for civil security applications

NASA Astrophysics Data System (ADS)

Åkerlund, Hans

2009-09-01

A surveillance system has been developed that can use multiple TV-cameras to detect and track personnel and objects in real time in public areas. The document describes the development and the system setup. The system is called NIVS Networked Intelligent Video Surveillance. Persons in the images are tracked and displayed on a 3D map of the surveyed area.

Multimode electromagnetic target discriminator: preliminary data results

NASA Astrophysics Data System (ADS)

Black, Christopher J.; McMichael, Ian T.; Nelson, Carl V.

2004-09-01

This paper describes the Multi-mode Electromagnetic Target Discriminator (METD) sensor and presents preliminary results from recent field experiments. The METD sensor was developed for the US Army RDECOM NVESD by The Johns Hopkins University Applied Physics Laboratory. The METD, based on the technology of the previously developed Electromagnetic Target Discriminator (ETD), is a spatial scanning electromagnetic induction (EMI) sensor that uses both the time-domain (TD) and the frequency-domain (FD) for target detection and classification. Data is collected with a custom data acquisition system and wirelessly transmitted to a base computer. We show that the METD has a high signal-to-noise ratio (SNR), the ability to detect voids created by plastic anti-tank (AT) mines, and is practical for near real-time data processing.

Fiber optic gas detection system for health monitoring of oil-filled transformer

NASA Astrophysics Data System (ADS)

Ho, H. L.; Ju, J.; Jin, W.

2009-10-01

This paper reports the development of a fiber-optic gas detection system capable of detecting three types of dissolved fault gases in oil-filled power transformers or equipment. The system is based on absorption spectroscopy and the target gases include acetylene (C2H2), methane (CH4) and ethylene (C2H4). Low-cost multi-pass sensor heads using fiber coupled micro-optic cells are employed for which the interaction length is up to 4m. Also, reference gas cells made of photonic bandgap (PBG) fiber are implemented. The minimum detectable gas concentrations for methane, acetylene and ethylene are 5ppm, 2ppm and 50ppm respectively.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly.

PubMed

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-28

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.

Use of the SAR (Synthetic Aperture Radar) P band for detection of the Moche and Lambayeque canal networks in the Apurlec region, Perù

NASA Astrophysics Data System (ADS)

Ilaria Pannaccione Apa, Maria; Santovito, Maria Rosaria; Pica, Giulia; Catapano, Ilaria; Fornaro, Gianfranco; Lanari, Riccardo; Soldovieri, Francesco; Wester La Torre, Carlos; Fernandez Manayalle, Marco Antonio; Longo, Francesco; Facchinetti, Claudia; Formaro, Roberto

2016-04-01

In recent years, research attention has been devoted to the development of a new class of airborne radar systems using low frequency bands ranging from VHF/UHF to P and L ones. In this frame, the Italian Space Agency (ASI) has promoted the development of a new multi-mode and multi-band airborne radar system, which can be considered even a "proof-of-concept" for the next space-borne missions. In particular, in agreement with the ASI, the research consortium CO.RI.S.T.A. has in charge the design, development and flight validation of such a kind of system, which is the first airborne radar entirely built in Italy. The aim was to design and realize a radar system able to work in different modalities as: nadir-looking sounder at VHF band (163 MHz); side-looking imager (SAR) at P band with two channels at 450 MHz and 900 MHz. The P-band is a penetration radar. Exploiting penetration features of low frequency electromagnetic waves, dielectric discontinuities of observed scene due to inhomogeneous materials rise up and can be detected on the resulting image. Therefore buried objects or targets placed under vegetation may be detected. Penetration capabilities essentially depend on microwave frequency. Typically, penetration distance is inversely proportional to microwave frequency. The higher the frequency, the lower the penetration depth. Terrain characteristics affect penetration capabilities. Humidity acts as a shield to microwave penetration. Hence terrain with high water content are not good targets for P-band applicability. Science community, governments and space agencies have increased their interest about low frequency radar for their useful applicability in climatology, ecosystem monitoring, glaciology, archaeology. The combination of low frequency and high relative bandwidth of such a systems has a large applicability in both military and civilian applications, ranging from forestry applications, biomass measuring, archaeological and geological exploration, glaciers investigation, biomass monitoring, detection of buried targets. Its extension to non-civil application concerns sub-surface target detection and foliage penetration (FOPEN). In order to achieve the flexibility to face all the above mentioned fields of application, the CORISTA system has been designed as a multi-mode and multi-frequency radar. Multimode stands for the functionality of the system both as Sounder and Imager. In addition, P-band radar is a multi-frequency instrument, since it is designed to work in three different frequency bands, as mentioned above: lower frequency band is used in sounder operative mode, higher frequency in imager operative mode. In the Imager operative mode, low resolution and high resolution capabilities are implemented. The data collected by the radar system have been processed using a model-based microwave tomographic approach, recently developed by IREA-CNR, with the aim to enhance the interpretability of the raw-data radar images. Currently, the non-invasive SAR P band application is under evaluation for testing in the Northern Coast of Perù, in collaboration with the Museo Arqueológico Nacional Brüning. The project will aim to recognize the subsurface ancient Moche (100-700 d.C.) and Lambayeque (700-1375 d.C.) canal networks, whose water supply comes from the Canal Taymi, started to be dug by the Mochicas, still in use by local communities.

Multi-Phenomenology Explosion Monitoring (Multi-PEM). Signal Detection. Research to target smaller sources for tomorrow’s missions

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

Carmichael, Joshua Daniel

2015-12-12

This a guide on how to detect and identify explosions from various sources. For example, nuclear explosions produce acoustic, optical, and EMP outputs. Each signal can be buried in noise, but fusing detection statistics from seismic, acoustic, and electromagnetic signals results in clear detection otherwise unobtainable.

A bio-inspired swarm robot coordination algorithm for multiple target searching

NASA Astrophysics Data System (ADS)

Meng, Yan; Gan, Jing; Desai, Sachi

2008-04-01

The coordination of a multi-robot system searching for multi targets is challenging under dynamic environment since the multi-robot system demands group coherence (agents need to have the incentive to work together faithfully) and group competence (agents need to know how to work together well). In our previous proposed bio-inspired coordination method, Local Interaction through Virtual Stigmergy (LIVS), one problem is the considerable randomness of the robot movement during coordination, which may lead to more power consumption and longer searching time. To address these issues, an adaptive LIVS (ALIVS) method is proposed in this paper, which not only considers the travel cost and target weight, but also predicting the target/robot ratio and potential robot redundancy with respect to the detected targets. Furthermore, a dynamic weight adjustment is also applied to improve the searching performance. This new method a truly distributed method where each robot makes its own decision based on its local sensing information and the information from its neighbors. Basically, each robot only communicates with its neighbors through a virtual stigmergy mechanism and makes its local movement decision based on a Particle Swarm Optimization (PSO) algorithm. The proposed ALIVS algorithm has been implemented on the embodied robot simulator, Player/Stage, in a searching target. The simulation results demonstrate the efficiency and robustness in a power-efficient manner with the real-world constraints.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

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 a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. 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.

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

A High Performance Computing Study of a Scalable FISST-Based Approach to Multi-Target, Multi-Sensor Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; Wilkins, M.; Roscoe, C.; Faber, W.; Chakravorty, S.; Schumacher, P.

2016-09-01

Finite Set Statistics (FISST) is a rigorous Bayesian multi-hypothesis management tool for the joint detection, classification and tracking of multi-sensor, multi-object systems. Implicit within the approach are solutions to the data association and target label-tracking problems. The full FISST filtering equations, however, are intractable. While FISST-based methods such as the PHD and CPHD filters are tractable, they require heavy moment approximations to the full FISST equations that result in a significant loss of information contained in the collected data. In this paper, we review Smart Sampling Markov Chain Monte Carlo (SSMCMC) that enables FISST to be tractable while avoiding moment approximations. We study the effect of tuning key SSMCMC parameters on tracking quality and computation time. The study is performed on a representative space object catalog with varying numbers of RSOs. The solution is implemented in the Scala computing language at the Maui High Performance Computing Center (MHPCC) facility.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

PubMed

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis.

PubMed

Liu, Jinjun; Leng, Yonggang; Lai, Zhihui; Fan, Shengbo

2018-04-25

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method.

STARR: shortwave-targeted agile Raman robot for the detection and identification of emplaced explosives

NASA Astrophysics Data System (ADS)

Gomer, Nathaniel R.; Gardner, Charles W.

2014-05-01

In order to combat the threat of emplaced explosives (land mines, etc.), ChemImage Sensor Systems (CISS) has developed a multi-sensor, robot mounted sensor capable of identification and confirmation of potential threats. The system, known as STARR (Shortwave-infrared Targeted Agile Raman Robot), utilizes shortwave infrared spectroscopy for the identification of potential threats, combined with a visible short-range standoff Raman hyperspectral imaging (HSI) system for material confirmation. The entire system is mounted onto a Talon UGV (Unmanned Ground Vehicle), giving the sensor an increased area search rate and reducing the risk of injury to the operator. The Raman HSI system utilizes a fiber array spectral translator (FAST) for the acquisition of high quality Raman chemical images, allowing for increased sensitivity and improved specificity. An overview of the design and operation of the system will be presented, along with initial detection results of the fusion sensor.

Design of an FMCW radar baseband signal processing system for automotive application.

PubMed

Lin, Jau-Jr; Li, Yuan-Ping; Hsu, Wei-Chiang; Lee, Ta-Sung

2016-01-01

For a typical FMCW automotive radar system, a new design of baseband signal processing architecture and algorithms is proposed to overcome the ghost targets and overlapping problems in the multi-target detection scenario. To satisfy the short measurement time constraint without increasing the RF front-end loading, a three-segment waveform with different slopes is utilized. By introducing a new pairing mechanism and a spatial filter design algorithm, the proposed detection architecture not only provides high accuracy and reliability, but also requires low pairing time and computational loading. This proposed baseband signal processing architecture and algorithms balance the performance and complexity, and are suitable to be implemented in a real automotive radar system. Field measurement results demonstrate that the proposed automotive radar signal processing system can perform well in a realistic application scenario.

A Multi-Region Magnetoimpedance-Based Bio-Analytical System for Ultrasensitive Simultaneous Determination of Cardiac Biomarkers Myoglobin and C-Reactive Protein.

PubMed

Yang, Zhen; Wang, Huanhuan; Guo, Pengfei; Ding, Yuanyuan; Lei, Chong; Luo, Yongsong

2018-06-01

Cardiac biomarkers (CBs) are substances that appear in the blood when the heart is damaged or stressed. Measurements of the level of CBs can be used in course of diagnostics or monitoring the state of the health of group risk persons. A multi-region bio-analytical system (MRBAS) based on magnetoimpedance (MI) changes was proposed for ultrasensitive simultaneous detection of CBs myoglobin (Mb) and C-reactive protein (CRP). The microfluidic device was designed and developed using standard microfabrication techniques for their usage in different regions, which were pre-modified with specific antibody for specified detection. Mb and CRP antigens labels attached to commercial Dynabeads with selected concentrations were trapped in different detection regions. The MI response of the triple sensitive element was carefully evaluated in initial state and in the presence of biomarkers. The results showed that the MI-based bio-sensing system had high selectivity and sensitivity for detection of CBs. Compared with the control region, ultrasensitive detections of CRP and Mb were accomplished with the detection limits of 1.0 pg/mL and 0.1 pg/mL, respectively. The linear detection range contained low concentration detection area and high concentration detection area, which were 1 pg/mL⁻10 ng/mL, 10⁻100 ng/mL for CRP, and 0.1 pg/mL⁻1 ng/mL, 1 n/mL⁻80 ng/mL for Mb. The measurement technique presented here provides a new methodology for multi-target biomolecules rapid testing.

A Multi-Receptor and Multi-Species Assay for Potential Endocrine Disruptor Targets (SLAS meeting)

EPA Science Inventory

Screening methods for detecting potential endocrine disrupting chemicals rely chiefly on transactivation assays targeting nuclear receptors such as the estrogen (ER) and androgen receptors (AR). These assays are predominately human-based; yet environmental exposure can affect div...

Single-fiber multi-color pyrometry

DOEpatents

Small, IV, Ward; Celliers, Peter

2004-01-27

This invention is a fiber-based multi-color pyrometry set-up for real-time non-contact temperature and emissivity measurement. The system includes a single optical fiber to collect radiation emitted by a target, a reflective rotating chopper to split the collected radiation into two or more paths while modulating the radiation for lock-in amplification (i.e., phase-sensitive detection), at least two detectors possibly of different spectral bandwidths with or without filters to limit the wavelength regions detected and optics to direct and focus the radiation onto the sensitive areas of the detectors. A computer algorithm is used to calculate the true temperature and emissivity of a target based on blackbody calibrations. The system components are enclosed in a light-tight housing, with provision for the fiber to extend outside to collect the radiation. Radiation emitted by the target is transmitted through the fiber to the reflective chopper, which either allows the radiation to pass straight through or reflects the radiation into one or more separate paths. Each path includes a detector with or without filters and corresponding optics to direct and focus the radiation onto the active area of the detector. The signals are recovered using lock-in amplification. Calibration formulas for the signals obtained using a blackbody of known temperature are used to compute the true temperature and emissivity of the target. The temperature range of the pyrometer system is determined by the spectral characteristics of the optical components.

Single-fiber multi-color pyrometry

DOEpatents

Small, IV, Ward; Celliers, Peter

2000-01-01

This invention is a fiber-based multi-color pyrometry set-up for real-time non-contact temperature and emissivity measurement. The system includes a single optical fiber to collect radiation emitted by a target, a reflective rotating chopper to split the collected radiation into two or more paths while modulating the radiation for lock-in amplification (i.e., phase-sensitive detection), at least two detectors possibly of different spectral bandwidths with or without filters to limit the wavelength regions detected and optics to direct and focus the radiation onto the sensitive areas of the detectors. A computer algorithm is used to calculate the true temperature and emissivity of a target based on blackbody calibrations. The system components are enclosed in a light-tight housing, with provision for the fiber to extend outside to collect the radiation. Radiation emitted by the target is transmitted through the fiber to the reflective chopper, which either allows the radiation to pass straight through or reflects the radiation into one or more separate paths. Each path includes a detector with or without filters and corresponding optics to direct and focus the radiation onto the active area of the detector. The signals are recovered using lock-in amplification. Calibration formulas for the signals obtained using a blackbody of known temperature are used to compute the true temperature and emissivity of the target. The temperature range of the pyrometer system is determined by the spectral characteristics of the optical components.

Physical Security Against Explosive Threats: Standoff Magnetic and Electro-optical Sensing and Target Characterization

DTIC Science & Technology

2012-10-21

PBIEDS ). Coupled with recent suicide bomb events in unstable regions of Southwest Asia and Africa, long-standing Urgent Operation Need Statements for...explosives and shrapnel (metal screws, bolts, ball bearings). A PBIED detection capability is critically needed not only for operations during open...produce magnetic signals above a certain threshold. We have developed a simple and robust multi- modal sensing system to detect PBIEDs and metal

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

Robust Targeting for the Smartphone Video Guidance Sensor

NASA Technical Reports Server (NTRS)

Carter, Christopher

2017-01-01

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However, it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level accuracy at a range of two meters with a 1U target.

Robust Targeting for the Smartphone Video Guidance Sensor

NASA Technical Reports Server (NTRS)

Carter, C.

2017-01-01

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level precision at a range of two meters with a 1U target.

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.

Providing data science support for systems pharmacology and its implications to drug discovery.

PubMed

Hart, Thomas; Xie, Lei

2016-01-01

The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations.

Multi-microphone adaptive array augmented with visual cueing.

PubMed

Gibson, Paul L; Hedin, Dan S; Davies-Venn, Evelyn E; Nelson, Peggy; Kramer, Kevin

2012-01-01

We present the development of an audiovisual array that enables hearing aid users to converse with multiple speakers in reverberant environments with significant speech babble noise where their hearing aids do not function well. The system concept consists of a smartphone, a smartphone accessory, and a smartphone software application. The smartphone accessory concept is a multi-microphone audiovisual array in a form factor that allows attachment to the back of the smartphone. The accessory will also contain a lower power radio by which it can transmit audio signals to compatible hearing aids. The smartphone software application concept will use the smartphone's built in camera to acquire images and perform real-time face detection using the built-in face detection support of the smartphone. The audiovisual beamforming algorithm uses the location of talking targets to improve the signal to noise ratio and consequently improve the user's speech intelligibility. Since the proposed array system leverages a handheld consumer electronic device, it will be portable and low cost. A PC based experimental system was developed to demonstrate the feasibility of an audiovisual multi-microphone array and these results are presented.

Reduced complexity of multi-track joint 2-D Viterbi detectors for bit-patterned media recording channel

NASA Astrophysics Data System (ADS)

Myint, L. M. M.; Warisarn, C.

2017-05-01

Two-dimensional (2-D) interference is one of the prominent challenges in ultra-high density recording system such as bit patterned media recording (BPMR). The multi-track joint 2-D detection technique with the help of the array-head reading can tackle this problem effectively by jointly processing the multiple readback signals from the adjacent tracks. Moreover, it can robustly alleviate the impairments due to track mis-registration (TMR) and media noise. However, the computational complexity of such detectors is normally too high and hard to implement in a reality, even for a few multiple tracks. Therefore, in this paper, we mainly focus on reducing the complexity of multi-track joint 2-D Viterbi detector without paying a large penalty in terms of the performance. We propose a simplified multi-track joint 2-D Viterbi detector with a manageable complexity level for the BPMR's multi-track multi-head (MTMH) system. In the proposed method, the complexity of detector's trellis is reduced with the help of the joint-track equalization method which employs 1-D equalizers and 2-D generalized partial response (GPR) target. Moreover, we also examine the performance of a full-fledged multi-track joint 2-D detector and the conventional 2-D detection. The results show that the simplified detector can perform close to the full-fledge detector, especially when the system faces high media noise, with the significant low complexity.

Theory and practical application of out of sequence measurements with results for multi-static tracking

NASA Astrophysics Data System (ADS)

Iny, David

2007-09-01

This paper addresses the out-of-sequence measurement (OOSM) problem associated with multiple platform tracking systems. The problem arises due to different transmission delays in communication of detection reports across platforms. Much of the literature focuses on the improvement to the state estimate by incorporating the OOSM. As the time lag increases, there is diminishing improvement to the state estimate. However, this paper shows that optimal processing of OOSMs may still be beneficial by improving data association as part of a multi-target tracker. This paper derives exact multi-lag algorithms with the property that the standard log likelihood track scoring is independent of the order in which the measurements are processed. The orthogonality principle is applied to generalize the method of Bar- Shalom in deriving the exact A1 algorithm for 1-lag estimation. Theory is also developed for optimal filtering of time averaged measurements and measurements correlated through periodic updates of a target aim-point. An alternative derivation of the multi-lag algorithms is also achieved using an efficient variant of the augmented state Kalman filter (AS-KF). This results in practical and reasonably efficient multi-lag algorithms. Results are compared to a well known ad hoc algorithm for incorporating OOSMs. Finally, the paper presents some simulated multi-target multi-static scenarios where there is a benefit to processing the data out of sequence in order to improve pruning efficiency.

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis

PubMed Central

Leng, Yonggang; Fan, Shengbo

2018-01-01

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method. PMID:29693577

System-level multi-target drug discovery from natural products with applications to cardiovascular diseases.

PubMed

Zheng, Chunli; Wang, Jinan; Liu, Jianling; Pei, Mengjie; Huang, Chao; Wang, Yonghua

2014-08-01

The term systems pharmacology describes a field of study that uses computational and experimental approaches to broaden the view of drug actions rooted in molecular interactions and advance the process of drug discovery. The aim of this work is to stick out the role that the systems pharmacology plays across the multi-target drug discovery from natural products for cardiovascular diseases (CVDs). Firstly, based on network pharmacology methods, we reconstructed the drug-target and target-target networks to determine the putative protein target set of multi-target drugs for CVDs treatment. Secondly, we reintegrated a compound dataset of natural products and then obtained a multi-target compounds subset by virtual-screening process. Thirdly, a drug-likeness evaluation was applied to find the ADME-favorable compounds in this subset. Finally, we conducted in vitro experiments to evaluate the reliability of the selected chemicals and targets. We found that four of the five randomly selected natural molecules can effectively act on the target set for CVDs, indicating the reasonability of our systems-based method. This strategy may serve as a new model for multi-target drug discovery of complex diseases.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles

PubMed Central

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-01-01

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. PMID:28029145

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles.

PubMed

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-12-25

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.

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

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.

Novel maximum likelihood approach for passive detection and localisation of multiple emitters

NASA Astrophysics Data System (ADS)

Hernandez, Marcel

2017-12-01

In this paper, a novel target acquisition and localisation algorithm (TALA) is introduced that offers a capability for detecting and localising multiple targets using the intermittent "signals-of-opportunity" (e.g. acoustic impulses or radio frequency transmissions) they generate. The TALA is a batch estimator that addresses the complex multi-sensor/multi-target data association problem in order to estimate the locations of an unknown number of targets. The TALA is unique in that it does not require measurements to be of a specific type, and can be implemented for systems composed of either homogeneous or heterogeneous sensors. The performance of the TALA is demonstrated in simulated scenarios with a network of 20 sensors and up to 10 targets. The sensors generate angle-of-arrival (AOA), time-of-arrival (TOA), or hybrid AOA/TOA measurements. It is shown that the TALA is able to successfully detect 83-99% of the targets, with a negligible number of false targets declared. Furthermore, the localisation errors of the TALA are typically within 10% of the errors generated by a "genie" algorithm that is given the correct measurement-to-target associations. The TALA also performs well in comparison with an optimistic Cramér-Rao lower bound, with typical differences in performance of 10-20%, and differences in performance of 40-50% in the most difficult scenarios considered. The computational expense of the TALA is also controllable, which allows the TALA to maintain computational feasibility even in the most challenging scenarios considered. This allows the approach to be implemented in time-critical scenarios, such as in the localisation of artillery firing events. It is concluded that the TALA provides a powerful situational awareness aid for passive surveillance operations.

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

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

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

Vector neural network signal integration for radar application

NASA Astrophysics Data System (ADS)

Bierman, Gregory S.

1994-07-01

The Litton Data Systems Vector Neural Network (VNN) is a unique multi-scan integration algorithm currently in development. The target of interest is a low-flying cruise missile. Current tactical radar cannot detect and track the missile in ground clutter at tactically useful ranges. The VNN solves this problem by integrating the energy from multiple frames to effectively increase the target's signal-to-noise ratio. The implementation plan is addressing the APG-63 radar. Real-time results will be available by March 1994.

Multi-Sensor Systems Development for UXO Detection and Discrimination: Man-Portable Dual Magnetic/Electromagnetic Induction Sensor

DTIC Science & Technology

2008-02-01

of the magnetic data to constrain the target depth using joint or cooperative inversions ( Pasion et al. 2002). ERDC/EL TR-08-9 24 Figure 15. EM...baseline ordnance classification test site at Blossom Pt. Naval Research Laboratory. NRL/MR/6110-00-8437, March 20, 1998. Pasion , L., S. Billings, and

RADIAL VELOCITY VARIABILITY OF FIELD BROWN DWARFS

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

Prato, L.; Mace, G. N.; Rice, E. L.

2015-07-20

We present paper six of the NIRSPEC Brown Dwarf Spectroscopic Survey, an analysis of multi-epoch, high-resolution (R ∼ 20,000) spectra of 25 field dwarf systems (3 late-type M dwarfs, 16 L dwarfs, and 6 T dwarfs) taken with the NIRSPEC infrared spectrograph at the W. M. Keck Observatory. With a radial velocity (RV) precision of ∼2 km s{sup −1}, we are sensitive to brown dwarf companions in orbits with periods of a few years or less given a mass ratio of 0.5 or greater. We do not detect any spectroscopic binary brown dwarfs in the sample. Given our target properties,more » and the frequency and cadence of observations, we use a Monte Carlo simulation to determine the detection probability of our sample. Even with a null detection result, our 1σ upper limit for very low mass binary frequency is 18%. Our targets included seven known, wide brown dwarf binary systems. No significant RV variability was measured in our multi-epoch observations of these systems, even for those pairs for which our data spanned a significant fraction of the orbital period. Specialized techniques are required to reach the high precisions sensitive to motion in orbits of very low-mass systems. For eight objects, including six T dwarfs, we present the first published high-resolution spectra, many with high signal to noise, that will provide valuable comparison data for models of brown dwarf atmospheres.« less

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

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

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.

Research on target information optics communications transmission characteristic and performance in multi-screens testing system

NASA Astrophysics Data System (ADS)

Li, Hanshan

2016-04-01

To enhance the stability and reliability of multi-screens testing system, this paper studies multi-screens target optical information transmission link properties and performance in long-distance, sets up the discrete multi-tone modulation transmission model based on geometric model of laser multi-screens testing system and visible light information communication principle; analyzes the electro-optic and photoelectric conversion function of sender and receiver in target optical information communication system; researches target information transmission performance and transfer function of the generalized visible-light communication channel; found optical information communication transmission link light intensity space distribution model and distribution function; derives the SNR model of information transmission communication system. Through the calculation and experiment analysis, the results show that the transmission error rate increases with the increment of transmission rate in a certain channel modulation depth; when selecting the appropriate transmission rate, the bit error rate reach 0.01.

Autonomous collection of dynamically-cued multi-sensor imagery

NASA Astrophysics Data System (ADS)

Daniel, Brian; Wilson, Michael L.; Edelberg, Jason; Jensen, Mark; Johnson, Troy; Anderson, Scott

2011-05-01

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

A method to directly image exoplanets in multi-star systems such as Alpha-Centauri

NASA Astrophysics Data System (ADS)

Thomas, Sandrine J.; Belikov, Ruslan; Bendek, Eduardo

2015-09-01

Direct imaging of extra-solar planets is now a reality, especially with the deployment and commissioning of the first generation of specialized ground-based instruments such as the Gemini Planet Imager and SPHERE. These systems will allow detection of Jupiter-like planets 107 times fainter than their host star. Obtaining this contrast level and beyond requires the combination of a coronagraph to suppress light coming from the host star and a wavefront control system including a deformable mirror (DM) to remove residual starlight (speckles) created by the imperfections of telescope. However, all these current and future systems focus on detecting faint planets around single host stars, while several targets or planet candidates are located around nearby binary stars such as our neighboring star Alpha Centauri. Here, we present a method to simultaneously correct aberrations and diffraction of light coming from the target star as well as its companion star in order to reveal planets orbiting the target star. This method works even if the companion star is outside the control region of the DM (beyond its half-Nyquist frequency), by taking advantage of aliasing effects.

A dual-processor multi-frequency implementation of the FINDS algorithm

NASA Technical Reports Server (NTRS)

Godiwala, Pankaj M.; Caglayan, Alper K.

1987-01-01

This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance.

Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net.

PubMed

Choi, Jin; Jo, Jung Hyun; Yim, Hong-Suh; Choi, Eun-Jung; Cho, Sungki; Park, Jang-Hyun

2018-06-07

An Optical Wide-field patroL-Network (OWL-Net) has been developed for maintaining Korean low Earth orbit (LEO) satellites' orbital ephemeris. The OWL-Net consists of five optical tracking stations. Brightness signals of reflected sunlight of the targets were detected by a charged coupled device (CCD). A chopper system was adopted for fast astrometric data sampling, maximum 50 Hz, within a short observation time. The astrometric accuracy of the optical observation data was validated with precise orbital ephemeris such as Consolidated Prediction File (CPF) data and precise orbit determination result with onboard Global Positioning System (GPS) data from the target satellite. In the optical observation simulation of the OWL-Net for 2017, an average observation span for a single arc of 11 LEO observation targets was about 5 min, while an average optical observation separation time was 5 h. We estimated the position and velocity with an atmospheric drag coefficient of LEO observation targets using a sequential-batch orbit estimation technique after multi-arc batch orbit estimation. Post-fit residuals for the multi-arc batch orbit estimation and sequential-batch orbit estimation were analyzed for the optical measurements and reference orbit (CPF and GPS data). The post-fit residuals with reference show few tens-of-meters errors for in-track direction for multi-arc batch and sequential-batch orbit estimation results.

Observing Active Volcanism on Earth and Beyond With an Autonomous Science Investigation Capability

NASA Astrophysics Data System (ADS)

Davies, A. G.; Mjolsness, E. D.; Fink, W.; Castano, R.; Park, H. G.; Zak, M.; Burl, M. C.

2001-12-01

Operational constraints imposed by restricted downlink and long communication delays make autonomous systems a necessity for exploring dynamic processes in the Solar System and beyond. Our objective is to develop an onboard, modular, automated science analysis tool that will autonomously detect unexpected events, identify rare events at predicted sites, quantify the processes under study, and prioritize the science data and analyses as they are collected. A primary target for this capability is terrestrial active volcanism. Our integrated, science-driven command and control package represents the next stage of the automatic monitoring of volcanic activity pioneered by GOES. The resulting system will maximize science return from day-to-day instrument use and provide immediate reaction to capture the fullest information from infrequent events. For example, a sensor suite consisting of a Galileo-like multi-filter visible wavelength camera and an infrared spectrometer, can acquire high-spatial resolution data of eruptions of lava and volcanic plumes and identify large concentrations of volcanic SO2. After image/spectrum formation, software is applied to the data which is capable of change detection (in the visible and infrared), feature identification (both in imagery and spectra), and novelty detection. In this particular case, the latter module detects change in the parameter space of an advanced multi-component black-body volcanic thermal emission model by means of a novel technique called the "Grey-Box" method which analyzes time series data through a combination of deterministic and stochastic models. This approach can be demonstrated using data obtained by the Galileo spacecraft of ionian volcanism. The system autonomously identifies the most scientifically important targets and prioritizes data and analyses for return. All of these techniques have been successfully demonstrated in laboratory experiments, and are ready to be tested in an operational environment. After identification of a target of interest, an onboard planner prioritizes resources to obtain the best possible dataset of the identified process. We emphasize that the software is modular. The change detection and feature identification modules can be applied to any imaged dataset, and are not confined to volcanic targets. Applications are therefore widespread, across all NASA Enterprises. Examples include detection and quantification of extraterrestrial volcanism (Io, Triton), the monitoring of features in planetary atmospheres (Earth, Gas Giants), the ebb and flow of ices (Earth, Mars), asteriod, comet and supernova detection, change detection in magnetic fields, and identification of structure within radio outbursts.

Multi-laboratory evaluations of the performance of Catellicoccus marimammalium PCR assays developed to target gull fecal sources

EPA Science Inventory

Here we report results from a multi-laboratory (n=11) evaluation of four different PCR methods targeting the 16S rRNA gene of Catellicoccus marimammalium used to detect fecal contamination from birds in coastal environments. The methods included conventional end-point PCR, a SYBR...

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.

Stochastic resonance in attention control

NASA Astrophysics Data System (ADS)

Kitajo, K.; Yamanaka, K.; Ward, L. M.; Yamamoto, Y.

2006-12-01

We investigated the beneficial role of noise in a human higher brain function, namely visual attention control. We asked subjects to detect a weak gray-level target inside a marker box either in the left or the right visual field. Signal detection performance was optimized by presenting a low level of randomly flickering gray-level noise between and outside the two possible target locations. Further, we found that an increase in eye movement (saccade) rate helped to compensate for the usual deterioration in detection performance at higher noise levels. To our knowledge, this is the first experimental evidence that noise can optimize a higher brain function which involves distinct brain regions above the level of primary sensory systems -- switching behavior between multi-stable attention states -- via the mechanism of stochastic resonance.

The effect of depth on the target strength of a humpback whale (Megaptera novaeangliae).

PubMed

Bernasconi, M; Patel, R; Nøttestad, L; Pedersen, G; Brierley, A S

2013-12-01

Marine mammals are very seldom detected and tracked acoustically at different depths. The air contained in body cavities, such as lungs or swimbladders, has a significant effect on the acoustic energy backscattered from whale and fish species. Target strength data were obtained while a humpback whale (Megaptera novaeangliae) swam at the surface and dove underneath a research vessel, providing valuable multi-frequency echosounder recordings of its scattering characteristics from near surface to a depth of about 240 m. Increasing depth dramatically influenced the backscattered energy coming from the large cetacean. This study is tightly linked to the ultimate goal of developing an automated whale detection system for mitigation purposes.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

PubMed

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

2017-03-03

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

PubMed Central

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J.

2017-01-01

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter. PMID:28273796

Multi-phenomenology Observation Network Evaluation Tool'' (MONET)

NASA Astrophysics Data System (ADS)

Oltrogge, D.; North, P.; Vallado, D.

2014-09-01

Evaluating overall performance of an SSA "system-of-systems" observational network collecting against thousands of Resident Space Objects (RSO) is very difficult for typical tasking or scheduling-based analysis tools. This is further complicated by networks that have a wide variety of sensor types and phenomena, to include optical, radar and passive RF types, each having unique resource, ops tempo, competing customer and detectability constraints. We present details of the Multi-phenomenology Observation Network Evaluation Tool (MONET), which circumvents these difficulties by assessing the ideal performance of such a network via a digitized supply-vs-demand approach. Cells of each sensors supply time are distributed among RSO targets of interest to determine the average performance of the network against that set of RSO targets. Orbit Determination heuristics are invoked to represent observation quantity and geometry notionally required to obtain the desired orbit estimation quality. To feed this approach, we derive the detectability and collection rate performance of optical, radar and passive RF sensor physical and performance characteristics. We then prioritize the selected RSO targets according to object size, active/inactive status, orbit regime, and/or other considerations. Finally, the OD-derived tracking demands of each RSO of interest are levied against remaining sensor supply until either (a) all sensor time is exhausted; or (b) the list of RSO targets is exhausted. The outputs from MONET include overall network performance metrics delineated by sensor type, objects and orbits tracked, along with likely orbit accuracies which might result from the conglomerate network tracking.

Multimodal microscopy and the stepwise multi-photon activation fluorescence of melanin

NASA Astrophysics Data System (ADS)

Lai, Zhenhua

The author's work is divided into three aspects: multimodal microscopy, stepwise multi-photon activation fluorescence (SMPAF) of melanin, and customized-profile lenses (CPL) for on-axis laser scanners, which will be introduced respectively. A multimodal microscope provides the ability to image samples with multiple modalities on the same stage, which incorporates the benefits of all modalities. The multimodal microscopes developed in this dissertation are the Keck 3D fusion multimodal microscope 2.0 (3DFM 2.0), upgraded from the old 3DFM with improved performance and flexibility, and the multimodal microscope for targeting small particles (the "Target" system). The control systems developed for both microscopes are low-cost and easy-to-build, with all components off-the-shelf. The control system have not only significantly decreased the complexity and size of the microscope, but also increased the pixel resolution and flexibility. The SMPAF of melanin, activated by a continuous-wave (CW) mode near-infrared (NIR) laser, has potential applications for a low-cost and reliable method of detecting melanin. The photophysics of melanin SMPAF has been studied by theoretical analysis of the excitation process and investigation of the spectra, activation threshold, and photon number absorption of melanin SMPAF. SMPAF images of melanin in mouse hair and skin, mouse melanoma, and human black and white hairs are compared with images taken by conventional multi-photon fluorescence microscopy (MPFM) and confocal reflectance microscopy (CRM). SMPAF images significantly increase specificity and demonstrate the potential to increase sensitivity for melanin detection compared to MPFM images and CRM images. Employing melanin SMPAF imaging to detect melanin inside human skin in vivo has been demonstrated, which proves the effectiveness of melanin detection using SMPAF for medical purposes. Selective melanin ablation with micrometer resolution has been presented using the Target system. Compared to the traditional selective photothermolysis, this method demonstrates higher precision, higher specificity and deeper penetration. Therefore, the SMPAF guided selective ablation of melanin is a promising tool of removing melanin for both medical and cosmetic purposes. Three CPLs have been designed for low-cost linear-motion scanners, low-cost fast spinning scanners and high-precision fast spinning scanners. Each design has been tailored to the industrial manufacturing ability and market demands.

The feature extraction of "cat-eye" targets based on bi-spectrum

NASA Astrophysics Data System (ADS)

Zhang, Tinghua; Fan, Guihua; Sun, Huayan

2016-10-01

In order to resolve the difficult problem of detection and identification of optical targets in complex background or in long-distance transmission, this paper mainly study the range profiles of "cat-eye" targets using bi-spectrum. For the problems of laser echo signal attenuation serious and low Signal-Noise Ratio (SNR), the multi-pulse laser signal echo signal detection algorithm which is based on high-order cumulant, filter processing and the accumulation of multi-pulse is proposed. This could improve the detection range effectively. In order to extract the stable characteristics of the one-dimensional range profile coming from the cat-eye targets, a method is proposed which extracts the bi-spectrum feature, and uses the singular value decomposition to simplify the calculation. Then, by extracting data samples of different distance, type and incidence angle, verify the stability of the eigenvector and effectiveness extracted by bi-spectrum.

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 detection of bound microbubbles for ultrasound molecularly-targeted imaging. PMID:20178897

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system

PubMed Central

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902

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.

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

DTIC Science & Technology

2011-03-01

the actions of malicious and benign users of the Internet, as well as the engi- neering decisions giving rise to observed network topologies. Say and...with resilience, which is particularly important in the domain of quickly-evolving cyber threats. “Self-organization,” says Meadows, “is basically the...system design paradigm is to leverage the advantages of a distributed approach? What is meant by saying the witness conceptually rates the target

Road-Aided Ground Slowly Moving Target 2D Motion Estimation for Single-Channel Synthetic Aperture Radar.

PubMed

Wang, Zhirui; Xu, Jia; Huang, Zuzhen; Zhang, Xudong; Xia, Xiang-Gen; Long, Teng; Bao, Qian

2016-03-16

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target's position on the road as well as its radial velocity can be determined according to the target's offset distance and traffic rules. Furthermore, the target's azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

Colloidal core-seeded semiconductor nanorods as fluorescent labels for in-vitro diagnostics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Chan, YinThai

2016-03-01

Colloidal semiconductor nanocrystals are ideal fluorophores for clinical diagnostics, therapeutics, and highly sensitive biochip applications due to their high photostability, size-tunable color of emission and flexible surface chemistry. The relatively recent development of core-seeded semiconductor nanorods showed that the presence of a rod-like shell can confer even more advantageous physicochemical properties than their spherical counterparts, such as large multi-photon absorption cross-sections and facet-specific chemistry that can be exploited to deposit secondary nanoparticles. It may be envisaged that these highly fluorescent nanorods can be integrated with large scale integrated (LSI) microfluidic systems that allow miniaturization and integration of multiple biochemical processes in a single device at the nanoliter scale, resulting in a highly sensitive and automated detection platform. In this talk, I will describe a LSI microfluidic device that integrates RNA extraction, reverse transcription to cDNA, amplification and target pull-down to detect histidine decarboxylase (HDC) gene directly from human white blood cells samples. When anisotropic colloidal semiconductor nanorods (NRs) were used as the fluorescent readout, the detection limit was found to be 0.4 ng of total RNA, which was much lower than that obtained using spherical quantum dots (QDs) or organic dyes. This was attributed to the large action cross-section of NRs and their high probability of target capture in a pull-down detection scheme. The combination of large scale integrated microfluidics with highly fluorescent semiconductor NRs may find widespread utility in point-of-care devices and multi-target diagnostics.

Background suppression of infrared small target image based on inter-frame registration

NASA Astrophysics Data System (ADS)

Ye, Xiubo; Xue, Bindang

2018-04-01

We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.

Multiplexed colorimetric detection of Kaposi's sarcoma associated herpesvirus and Bartonella DNA using gold and silver nanoparticles

NASA Astrophysics Data System (ADS)

Mancuso, Matthew; Jiang, Li; Cesarman, Ethel; Erickson, David

2013-01-01

Kaposi's sarcoma (KS) is an infectious cancer occurring most commonly in human immunodeficiency virus (HIV) positive patients and in endemic regions, such as Sub-Saharan Africa, where KS is among the top four most prevalent cancers. The cause of KS is the Kaposi's sarcoma-associated herpesvirus (KSHV, also called HHV-8), an oncogenic herpesvirus that while routinely diagnosed in developed nations, provides challenges to developing world medical providers and point-of-care detection. A major challenge in the diagnosis of KS is the existence of a number of other diseases with similar clinical presentation and histopathological features, requiring the detection of KSHV in a biopsy sample. In this work we develop an answer to this challenge by creating a multiplexed one-pot detection system for KSHV DNA and DNA from a frequently confounding disease, bacillary angiomatosis. Gold and silver nanoparticle aggregation reactions are tuned for each target and a multi-color change system is developed capable of detecting both targets down to levels between 1 nM and 2 nM. The system developed here could later be integrated with microfluidic sample processing to create a final device capable of solving the two major challenges in point-of-care KS detection.

Improving Target Detection in Visual Search Through the Augmenting Multi-Sensory Cues

DTIC Science & Technology

2013-01-01

target detection, visual search James Merlo, Joseph E. Mercado , Jan B.F. Van Erp, Peter A. Hancock University of Central Florida 12201 Research Parkway...were controlled by a purpose-created, LabView- based software computer program that synchronised the respective displays and recorded response times and

ALLTEM UXO detection and discrimination

USGS Publications Warehouse

Asch, T.H.; Wright, D.L.; Moulton, C.W.; Irons, T.P.; Nabighian, M.N.

2008-01-01

ALLTEM is a multi-axis electromagnetic induction system designed for unexploded ordnance (UXO) applications. It uses a continuous triangle-wave excitation and provides good late-time signal-to-noise ratio (SNR) especially for ferrous targets. Multi-axis transmitter (Tx) and receiver (Rx) systems such as ALLTEM provide a richer data set from which to invert for the target parameters required to distinguish between clutter and UXO. Inversions of field data over the Army's UXO Calibration Grid and Blind Test Grid at the Yuma Proving Ground (YPG), Arizona in 2006 produced polarizability moment values for many buried UXO items that were reasonable and generally repeatable for targets of the same type buried at different orientations and depths. In 2007 a test stand was constructed that allows for collection of data with varying spatial data density and accurate automated position control. The behavior of inverted ALLTEM test stand data as a function of spatial data density, sensor SNR, and position error has been investigated. The results indicate that the ALLTEM inversion algorithm is more tolerant of sensor noise and position error than has been reported for single-axis systems. A high confidence level in inversion-derived target parameters is required when a target is declared to be harmless scrap metal that may safely be left in the ground. Unless high confidence can be demonstrated, state regulators will likely require that targets be dug regardless of any "no-dig" classifications produced from inversions, in which case remediation costs would not be decreased.

Dynamically re-configurable CMOS imagers for an active vision system

NASA Technical Reports Server (NTRS)

Yang, Guang (Inventor); Pain, Bedabrata (Inventor)

2005-01-01

A vision system is disclosed. The system includes a pixel array, at least one multi-resolution window operation circuit, and a pixel averaging circuit. The pixel array has an array of pixels configured to receive light signals from an image having at least one tracking target. The multi-resolution window operation circuits are configured to process the image. Each of the multi-resolution window operation circuits processes each tracking target within a particular multi-resolution window. The pixel averaging circuit is configured to sample and average pixels within the particular multi-resolution window.

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.

Multi-brain fusion and applications to intelligence analysis

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

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.

Application of infrared uncooled cameras in surveillance systems

NASA Astrophysics Data System (ADS)

Dulski, R.; Bareła, J.; Trzaskawka, P.; PiÄ tkowski, T.

2013-10-01

The recent necessity to protect military bases, convoys and patrols gave serious impact to the development of multisensor security systems for perimeter protection. One of the most important devices used in such systems are IR cameras. The paper discusses technical possibilities and limitations to use uncooled IR camera in a multi-sensor surveillance system for perimeter protection. Effective ranges of detection depend on the class of the sensor used and the observed scene itself. Application of IR camera increases the probability of intruder detection regardless of the time of day or weather conditions. It also simultaneously decreased the false alarm rate produced by the surveillance system. The role of IR cameras in the system was discussed as well as technical possibilities to detect human being. Comparison of commercially available IR cameras, capable to achieve desired ranges was done. The required spatial resolution for detection, recognition and identification was calculated. The simulation of detection ranges was done using a new model for predicting target acquisition performance which uses the Targeting Task Performance (TTP) metric. Like its predecessor, the Johnson criteria, the new model bounds the range performance with image quality. The scope of presented analysis is limited to the estimation of detection, recognition and identification ranges for typical thermal cameras with uncooled microbolometer focal plane arrays. This type of cameras is most widely used in security systems because of competitive price to performance ratio. Detection, recognition and identification range calculations were made, and the appropriate results for the devices with selected technical specifications were compared and discussed.

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 attempt to reconstruct the optical properties of every voxel of the sample volume. The location of a target was estimated to be the weighted center of the optical property of the target. Consequently, the locations of small targets were better specified than those of the extended targets. It was more difficult to retrieve the size and shape of a target. The fluorescent measurements seemed to provide better accuracy than the transillumination measurements. In the case of ex vivo detection of tumors embedded in human breast tissue, measurements using multiple wavelengths provided more robust results, and helped suppress artifacts (false positives) than that from single wavelength measurements. The ability to detect and locate small targets, speedier reconstruction, combined with fluorophore-specific multi-wavelength probing has the potential to make these approaches suitable for breast cancer detection and diagnosis.

Terrain Commander: a next-generation remote surveillance system

NASA Astrophysics Data System (ADS)

Finneral, Henry J.

2003-09-01

Terrain Commander is a fully automated forward observation post that provides the most advanced capability in surveillance and remote situational awareness. The Terrain Commander system was selected by the Australian Government for its NINOX Phase IIB Unattended Ground Sensor Program with the first systems delivered in August of 2002. Terrain Commander offers next generation target detection using multi-spectral peripheral sensors coupled with autonomous day/night image capture and processing. Subsequent intelligence is sent back through satellite communications with unlimited range to a highly sophisticated central monitoring station. The system can "stakeout" remote locations clandestinely for 24 hours a day for months at a time. With its fully integrated SATCOM system, almost any site in the world can be monitored from virtually any other location in the world. Terrain Commander automatically detects and discriminates intruders by precisely cueing its advanced EO subsystem. The system provides target detection capabilities with minimal nuisance alarms combined with the positive visual identification that authorities demand before committing a response. Terrain Commander uses an advanced beamforming acoustic sensor and a distributed array of seismic, magnetic and passive infrared sensors to detect, capture images and accurately track vehicles and personnel. Terrain Commander has a number of emerging military and non-military applications including border control, physical security, homeland defense, force protection and intelligence gathering. This paper reviews the development, capabilities and mission applications of the Terrain Commander system.

Multi-Target Tracking Using an Improved Gaussian Mixture CPHD Filter.

PubMed

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-11-23

The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target number than the PHD filter, the CPHD filter suffers from the spooky effect where there exists arbitrary PHD mass shifting in the presence of missed detections. To address this issue in the Gaussian mixture (GM) implementation of the CPHD filter, this paper presents an improved GM-CPHD filter, which incorporates a weight redistribution scheme into the filtering process to modify the updated weights of the Gaussian components when missed detections occur. In addition, an efficient gating strategy that can adaptively adjust the gate sizes according to the number of missed detections of each Gaussian component is also presented to further improve the computational efficiency of the proposed filter. Simulation results demonstrate that the proposed method offers favorable performance in terms of both estimation accuracy and robustness to clutter and detection uncertainty over the existing methods.

Performance Evaluation Modeling of Network Sensors

NASA Technical Reports Server (NTRS)

Clare, Loren P.; Jennings, Esther H.; Gao, Jay L.

2003-01-01

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

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.

Circular SAR GMTI

NASA Astrophysics Data System (ADS)

Page, Douglas; Owirka, Gregory; Nichols, Howard; Scarborough, Steven

2014-06-01

We describe techniques for improving ground moving target indication (GMTI) performance in multi-channel synthetic aperture radar (SAR) systems. Our approach employs a combination of moving reference processing (MRP) to compensate for defocus of moving target SAR responses and space-time adaptive processing (STAP) to mitigate the effects of strong clutter interference. Using simulated moving target and clutter returns, we demonstrate focusing of the target return using MRP, and discuss the effect of MRP on the clutter response. We also describe formation of adaptive degrees of freedom (DOFs) for STAP filtering of MRP processed data. For the simulated moving target in clutter example, we demonstrate improvement in the signal to interference plus noise (SINR) loss compared to more standard algorithm configurations. In addition to MRP and STAP, the use of tracker feedback, false alarm mitigation, and parameter estimation techniques are also described. A change detection approach for reducing false alarms from clutter discretes is outlined, and processing of a measured data coherent processing interval (CPI) from a continuously orbiting platform is described. The results demonstrate detection and geolocation of a high-value target under track. The endoclutter target is not clearly visible in single-channel SAR chips centered on the GMTI track prediction. Detections are compared to truth data before and after geolocation using measured angle of arrival (AOA).

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

FilmArray, an Automated Nested Multiplex PCR System for Multi-Pathogen Detection: Development and Application to Respiratory Tract Infection

PubMed Central

Poritz, Mark A.; Blaschke, Anne J.; Byington, Carrie L.; Meyers, Lindsay; Nilsson, Kody; Jones, David E.; Thatcher, Stephanie A.; Robbins, Thomas; Lingenfelter, Beth; Amiott, Elizabeth; Herbener, Amy; Daly, Judy; Dobrowolski, Steven F.; Teng, David H. -F.; Ririe, Kirk M.

2011-01-01

The ideal clinical diagnostic system should deliver rapid, sensitive, specific and reproducible results while minimizing the requirements for specialized laboratory facilities and skilled technicians. We describe an integrated diagnostic platform, the “FilmArray”, which fully automates the detection and identification of multiple organisms from a single sample in about one hour. An unprocessed biologic/clinical sample is subjected to nucleic acid purification, reverse transcription, a high-order nested multiplex polymerase chain reaction and amplicon melt curve analysis. Biochemical reactions are enclosed in a disposable pouch, minimizing the PCR contamination risk. FilmArray has the potential to detect greater than 100 different nucleic acid targets at one time. These features make the system well-suited for molecular detection of infectious agents. Validation of the FilmArray technology was achieved through development of a panel of assays capable of identifying 21 common viral and bacterial respiratory pathogens. Initial testing of the system using both cultured organisms and clinical nasal aspirates obtained from children demonstrated an analytical and clinical sensitivity and specificity comparable to existing diagnostic platforms. We demonstrate that automated identification of pathogens from their corresponding target amplicon(s) can be accomplished by analysis of the DNA melting curve of the amplicon. PMID:22039434

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

NASA Astrophysics Data System (ADS)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

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.

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.

Electro-optical system for gunshot detection: analysis, concept, and performance

NASA Astrophysics Data System (ADS)

Kastek, M.; Dulski, R.; Madura, H.; Trzaskawka, P.; Bieszczad, G.; Sosnowski, T.

2011-08-01

The paper discusses technical possibilities to build an effective electro-optical sensor unit for sniper detection using infrared cameras. This unit, comprising of thermal and daylight cameras, can operate as a standalone device but its primary application is a multi-sensor sniper and shot detection system. At first, the analysis was presented of three distinguished phases of sniper activity: before, during and after the shot. On the basis of experimental data the parameters defining the relevant sniper signatures were determined which are essential in assessing the capability of infrared camera to detect sniper activity. A sniper body and muzzle flash were analyzed as targets and the descriptions of phenomena which make it possible to detect sniper activities in infrared spectra as well as analysis of physical limitations were performed. The analyzed infrared systems were simulated using NVTherm software. The calculations for several cameras, equipped with different lenses and detector types were performed. The simulation of detection ranges was performed for the selected scenarios of sniper detection tasks. After the analysis of simulation results, the technical specifications of infrared sniper detection system were discussed, required to provide assumed detection range. Finally the infrared camera setup was proposed which can detected sniper from 1000 meters range.

Detection of small surface vessels in near, medium, and far infrared spectral bands

NASA Astrophysics Data System (ADS)

Dulski, R.; Milewski, S.; Kastek, M.; Trzaskawka, P.; Szustakowski, M.; Ciurapinski, W.; Zyczkowski, M.

2011-11-01

Protection of naval bases and harbors requires close co-operation between security and access control systems covering land areas and those monitoring sea approach routes. The typical location of naval bases and harbors - usually next to a large city - makes it difficult to detect and identify a threat in the dense regular traffic of various sea vessels (i.e. merchant ships, fishing boats, tourist ships). Due to the properties of vessel control systems, such as AIS (Automatic Identification System), and the effectiveness of radar and optoelectronic systems against different targets it seems that fast motor boats called RIB (Rigid Inflatable Boat) could be the most serious threat to ships and harbor infrastructure. In the paper the process and conditions for the detection and identification of high-speed boats in the areas of ports and naval bases in the near, medium and far infrared is presented. Based on the results of measurements and recorded thermal images the actual temperature contrast delta T (RIB / sea) will be determined, which will further allow to specify the theoretical ranges of detection and identification of the RIB-type targets for an operating security system. The data will also help to determine the possible advantages of image fusion where the component images are taken in different spectral ranges. This will increase the probability of identifying the object by the multi-sensor security system equipped additionally with the appropriate algorithms for detecting, tracking and performing the fusion of images from the visible and infrared cameras.

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar

PubMed Central

Liu, Miao; Zhang, Yang; Liang, Fulai; Qi, Fugui; Lv, Hao; Wang, Jianqi; Zhang, Yang

2017-01-01

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar. PMID:28973988

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar.

PubMed

Xue, Huijun; Liu, Miao; Zhang, Yang; Liang, Fulai; Qi, Fugui; Chen, Fuming; Lv, Hao; Wang, Jianqi; Zhang, Yang

2017-09-30

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar.

Multi-laboratory evaluations of the performance of Catellicoccus marimammalium PCR assays developed to target gull fecal sources

USGS Publications Warehouse

Sinigalliano, Christopher D.; Ervin, Jared S.; Van De Werfhorst, Laurie C.; Badgley, Brian D.; Ballestée, Elisenda; Bartkowiaka, Jakob; Boehm, Alexandria B.; Byappanahalli, Muruleedhara N.; Goodwin, Kelly D.; Gourmelon, Michèle; Griffith, John; Holden, Patricia A.; Jay, Jenny; Layton, Blythe; Lee, Cheonghoon; Lee, Jiyoung; Meijer, Wim G.; Noble, Rachel; Raith, Meredith; Ryu, Hodon; Sadowsky, Michael J.; Schriewer, Alexander; Wang, Dan; Wanless, David; Whitman, Richard; Wuertz, Stefan; Santo Domingo, Jorge W.

2013-01-01

Here we report results from a multi-laboratory (n = 11) evaluation of four different PCR methods targeting the 16S rRNA gene of Catellicoccus marimammalium originally developed to detect gull fecal contamination in coastal environments. The methods included a conventional end-point PCR method, a SYBR® Green qPCR method, and two TaqMan® qPCR methods. Different techniques for data normalization and analysis were tested. Data analysis methods had a pronounced impact on assay sensitivity and specificity calculations. Across-laboratory standardization of metrics including the lower limit of quantification (LLOQ), target detected but not quantifiable (DNQ), and target not detected (ND) significantly improved results compared to results submitted by individual laboratories prior to definition standardization. The unit of measure used for data normalization also had a pronounced effect on measured assay performance. Data normalization to DNA mass improved quantitative method performance as compared to enterococcus normalization. The MST methods tested here were originally designed for gulls but were found in this study to also detect feces from other birds, particularly feces composited from pigeons. Sequencing efforts showed that some pigeon feces from California contained sequences similar to C. marimammalium found in gull feces. These data suggest that the prevalence, geographic scope, and ecology of C. marimammalium in host birds other than gulls require further investigation. This study represents an important first step in the multi-laboratory assessment of these methods and highlights the need to broaden and standardize additional evaluations, including environmentally relevant target concentrations in ambient waters from diverse geographic regions.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images.

PubMed

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-05-06

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu's algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape.

Hardware-software face detection system based on multi-block local binary patterns

NASA Astrophysics Data System (ADS)

Acasandrei, Laurentiu; Barriga, Angel

2015-03-01

Face detection is an important aspect for biometrics, video surveillance and human computer interaction. Due to the complexity of the detection algorithms any face detection system requires a huge amount of computational and memory resources. In this communication an accelerated implementation of MB LBP face detection algorithm targeting low frequency, low memory and low power embedded system is presented. The resulted implementation is time deterministic and uses a customizable AMBA IP hardware accelerator. The IP implements the kernel operations of the MB-LBP algorithm and can be used as universal accelerator for MB LBP based applications. The IP employs 8 parallel MB-LBP feature evaluators cores, uses a deterministic bandwidth, has a low area profile and the power consumption is ~95 mW on a Virtex5 XC5VLX50T. The resulted implementation acceleration gain is between 5 to 8 times, while the hardware MB-LBP feature evaluation gain is between 69 and 139 times.

Aerial vehicles collision avoidance using monocular vision

NASA Astrophysics Data System (ADS)

Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

2016-10-01

In this paper image-based collision avoidance algorithm that provides detection of nearby aircraft and distance estimation is presented. The approach requires a vision system with a single moving camera and additional information about carrier's speed and orientation from onboard sensors. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The proposed algorithm is able to detect small targets but unlike many other approaches is designed to work with large-scale objects as well. To localize aerial vehicle position the system of equations relating object coordinates in space and observed image is solved. The system solution gives the current position and speed of the detected object in space. Using this information distance and time to collision can be estimated. Experimental research on real video sequences and modeled data is performed. Video database contained different types of aerial vehicles: aircrafts, helicopters, and UAVs. The presented algorithm is able to detect aerial vehicles from several kilometers under regular daylight conditions.

Coherent Doppler lidar for automated space vehicle rendezvous, stationkeeping and capture

NASA Technical Reports Server (NTRS)

Bilbro, James A.

1991-01-01

The inherent spatial resolution of laser radar makes ladar or lidar an attractive candidate for Automated Rendezvous and Capture application. Previous applications were based on incoherent lidar techniques, requiring retro-reflectors on the target vehicle. Technology improvements (reduced size, no cryogenic cooling requirement) have greatly enhanced the construction of coherent lidar systems. Coherent lidar permits the acquisition of non-cooperative targets at ranges that are limited by the detection capability rather than by the signal-to-noise ratio (SNR) requirements. The sensor can provide translational state information (range, velocity, and angle) by direct measurement and, when used with any array detector, also can provide attitude information by Doppler imaging techniques. Identification of the target is accomplished by scanning with a high pulse repetition frequency (dependent on the SNR). The system performance is independent of range and should not be constrained by sun angle. An initial effort to characterize a multi-element detection system has resulted in a system that is expected to work to a minimum range of 1 meter. The system size, weight and power requirements are dependent on the operating range; 10 km range requires a diameter of 3 centimeters with overall size at 3 x 3 x 15 to 30 cm, while 100 km range requires a 30 cm diameter.

The advanced linked extended reconnaissance and targeting technology demonstration project

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

Hypervelocity Impact (HVI). Volume 2; WLE Small-Scale Fiberglass Panel Flat Multi-Layer Targets A-1, A-2, and B-1

NASA Technical Reports Server (NTRS)

Gorman, Michael R.; Ziola, Steven M.

2007-01-01

During 2003 and 2004, the Johnson Space Center's White Sands Testing Facility in Las Cruces, New Mexico conducted hypervelocity impact tests on the space shuttle wing leading edge. Hypervelocity impact tests were conducted to determine if Micro-Meteoroid/Orbital Debris impacts could be reliably detected and located using simple passive ultrasonic methods. The objective of Targets A-1, A-2, and B-2 was to study hypervelocity impacts through multi-layered panels simulating Whipple shields on spacecraft. Impact damage was detected using lightweight, low power instrumentation capable of being used in flight.

Measurement of positron annihilation lifetimes for positron burst by multi-detector array

NASA Astrophysics Data System (ADS)

Wang, B. Y.; Kuang, P.; Liu, F. Y.; Han, Z. J.; Cao, X. Z.; Zhang, P.

2018-03-01

It is currently impossible to exploit the timing information in a gamma-ray pulse generated within nanoseconds when a high-intensity positron burst annihilation event occurs in a target using conventional single-detector methods. A state-of-the-art solution to the problem is proposed in this paper. In this approach, a multi-detector array composed of many independent detection cells mounted spherically around the target is designed to detect the time distribution of the annihilated gamma rays generated following, in particular, a positron burst emitting huge amounts of positrons in a short pulse duration, even less than a few nano- or picoseconds.

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

Analytical method for fast screening and confirmation of multi-class veterinary drug residues in fish and shrimp by LC-MS/MS.

PubMed

Kim, Junghyun; Suh, Joon Hyuk; Cho, Hyun-Deok; Kang, Wonjae; Choi, Yong Seok; Han, Sang Beom

2016-01-01

A multi-class, multi-residue analytical method based on LC-MS/MS detection was developed for the screening and confirmation of 28 veterinary drug and metabolite residues in flatfish, shrimp and eel. The chosen veterinary drugs are prohibited or unauthorised compounds in Korea, which were categorised into various chemical classes including nitroimidazoles, benzimidazoles, sulfones, quinolones, macrolides, phenothiazines, pyrethroids and others. To achieve fast and simultaneous extraction of various analytes, a simple and generic liquid extraction procedure using EDTA-ammonium acetate buffer and acetonitrile, without further clean-up steps, was applied to sample preparation. The final extracts were analysed by ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). The method was validated for each compound in each matrix at three different concentrations (5, 10 and 20 ng g(-1)) in accordance with Codex guidelines (CAC/GL 71-2009). For most compounds, the recoveries were in the range of 60-110%, and precision, expressed as the relative standard deviation (RSD), was in the range of 5-15%. The detection capabilities (CCβs) were below or equal to 5 ng g(-1), which indicates that the developed method is sufficient to detect illegal fishery products containing the target compounds above the residue limit (10 ng g(-1)) of the new regulatory system (Positive List System - PLS).

a Mini Multi-Gas Detection System Based on Infrared Principle

NASA Astrophysics Data System (ADS)

Zhijian, Xie; Qiulin, Tan

2006-12-01

To counter the problems of gas accidents in coal mines, family safety resulted from using gas, a new infrared detection system with integration and miniaturization has been developed. The infrared detection optics principle used in developing this system is mainly analyzed. The idea that multi gas detection is introduced and guided through analyzing single gas detection is got across. Through researching the design of cell structure, the cell with integration and miniaturization has been devised. The way of data transmission on Controller Area Network (CAN) bus is explained. By taking Single-Chip Microcomputer (SCM) as intelligence handling, the functional block diagram of gas detection system is designed with its hardware and software system analyzed and devised. This system designed has reached the technology requirement of lower power consumption, mini-volume, big measure range, and able to realize multi-gas detection.

Development of "one-pot" method for multi-class compounds in porcine formula feed by multi-function impurity adsorption cleaning followed ultra-performance liquid chromatography-tandem mass spectrometry detection.

PubMed

Wang, Peilong; Wang, Xiao; Zhang, Wei; Su, Xiaoou

2014-02-01

A novel and efficient determination method for multi-class compounds including β-agonists, sedatives, nitro-imidazoles and aflatoxins in porcine formula feed based on a fast "one-pot" extraction/multifunction impurity adsorption (MFIA) clean-up procedure has been developed. 23 target analytes belonging to four different class compounds could be determined simultaneously in a single run. Conditions for "one-pot" extraction were studied in detail. Under the optimized conditions, the multi-class compounds in porcine formula feed samples were extracted and purified with methanol contained ammonia and absorbents by one step. The compounds in extracts were purified by using multi types of absorbent based on MFIA in one pot. The multi-walled carbon nanotubes were employed to improved clean-up efficiency. Shield BEH C18 column was used to separate 23 target analytes, followed by tandem mass spectrometry (MS/MS) detection using an electro-spray ionization source in positive mode. Recovery studies were done at three fortification levels. Overall average recoveries of target compounds in porcine formula feed at each levels were >51.6% based on matrix fortified calibration with coefficients of variation from 2.7% to 13.2% (n=6). The limit of determination (LOD) of these compounds in porcine formula feed sample matrix was <5.0 μg/kg. This method was successfully applied in screening and confirmation of target drugs in >30 porcine formula feed samples. It was demonstrated that the integration of the MFIA protocol with the MS/MS instrument could serve as a valuable strategy for rapid screening and reliable confirmatory analysis of multi-class compounds in real samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Study on multispectral imaging detection and recognition

NASA Astrophysics Data System (ADS)

Jun, Wang; Na, Ding; Gao, Jiaobo; Yu, Hu; Jun, Wu; Li, Junna; Zheng, Yawei; Fei, Gao; Sun, Kefeng

2009-07-01

Multispectral imaging detecting technology use target radiation character in spectral spatial distribution and relation between spectral and image to detect target and remote sensing measure. Its speciality is multi channel, narrow bandwidth, large amount of information, high accuracy. The ability of detecting target in environment of clutter, camouflage, concealment and beguilement is improved. At present, spectral imaging technology in the range of multispectral and hyperspectral develop greatly. The multispectral imaging equipment of unmanned aerial vehicle can be used in mine detection, information, surveillance and reconnaissance. Spectral imaging spectrometer operating in MWIR and LWIR has already been applied in the field of remote sensing and military in the advanced country. The paper presents the technology of multispectral imaging. It can enhance the reflectance, scatter and radiation character of the artificial targets among nature background. The targets among complex background and camouflage/stealth targets can be effectively identified. The experiment results and the data of spectral imaging is obtained.

Tunnel Detection Using Seismic Methods

NASA Astrophysics Data System (ADS)

Miller, R.; Park, C. B.; Xia, J.; Ivanov, J.; Steeples, D. W.; Ryden, N.; Ballard, R. F.; Llopis, J. L.; Anderson, T. S.; Moran, M. L.; Ketcham, S. A.

2006-05-01

Surface seismic methods have shown great promise for use in detecting clandestine tunnels in areas where unauthorized movement beneath secure boundaries have been or are a matter of concern for authorities. Unauthorized infiltration beneath national borders and into or out of secure facilities is possible at many sites by tunneling. Developments in acquisition, processing, and analysis techniques using multi-channel seismic imaging have opened the door to a vast number of near-surface applications including anomaly detection and delineation, specifically tunnels. Body waves have great potential based on modeling and very preliminary empirical studies trying to capitalize on diffracted energy. A primary limitation of all seismic energy is the natural attenuation of high-frequency energy by earth materials and the difficulty in transmitting a high- amplitude source pulse with a broad spectrum above 500 Hz into the earth. Surface waves have shown great potential since the development of multi-channel analysis methods (e.g., MASW). Both shear-wave velocity and backscatter energy from surface waves have been shown through modeling and empirical studies to have great promise in detecting the presence of anomalies, such as tunnels. Success in developing and evaluating various seismic approaches for detecting tunnels relies on investigations at known tunnel locations, in a variety of geologic settings, employing a wide range of seismic methods, and targeting a range of uniquely different tunnel geometries, characteristics, and host lithologies. Body-wave research at the Moffat tunnels in Winter Park, Colorado, provided well-defined diffraction-looking events that correlated with the subsurface location of the tunnel complex. Natural voids related to karst have been studied in Kansas, Oklahoma, Alabama, and Florida using shear-wave velocity imaging techniques based on the MASW approach. Manmade tunnels, culverts, and crawl spaces have been the target of multi-modal analysis in Kansas and California. Clandestine tunnels used for illegal entry into the U.S. from Mexico were studied at two different sites along the southern border of California. All these studies represent the empirical basis for suggesting surface seismic has a significant role to play in tunnel detection and that methods are under development and very nearly at hand that will provide an effective tool in appraising and maintaining parameter security. As broadband sources, gravity-coupled towed spreads, and automated analysis software continues to make advancements, so does the applicability of routine deployment of seismic imaging systems that can be operated by technicians with interpretation aids for nearly real-time target selection. Key to making these systems commercial is the development of enhanced imaging techniques in geologically noisy areas and highly variable surface terrain.

An ultra-small, multi-point, and multi-color photo-detection system with high sensitivity and high dynamic range.

PubMed

Anazawa, Takashi; Yamazaki, Motohiro

2017-12-05

Although multi-point, multi-color fluorescence-detection systems are widely used in various sciences, they would find wider applications if they are miniaturized. Accordingly, an ultra-small, four-emission-point and four-color fluorescence-detection system was developed. Its size (space between emission points and a detection plane) is 15 × 10 × 12 mm, which is three-orders-of-magnitude smaller than that of a conventional system. Fluorescence from four emission points with an interval of 1 mm on the same plane was respectively collimated by four lenses and split into four color fluxes by four dichroic mirrors. Then, a total of sixteen parallel color fluxes were directly input into an image sensor and simultaneously detected. The emission-point plane and the detection plane (the image-sensor surface) were parallel and separated by a distance of only 12 mm. The developed system was applied to four-capillary array electrophoresis and successfully achieved Sanger DNA sequencing. Moreover, compared with a conventional system, the developed system had equivalent high fluorescence-detection sensitivity (lower detection limit of 17 pM dROX) and 1.6-orders-of-magnitude higher dynamic range (4.3 orders of magnitude).

Near-infrared fluorescence image quality test methods for standardized performance evaluation

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Wang, Bohan; Yang, Charles; Ghassemi, Pejhman; Wang, Quanzeng; Chen, Yu; Pfefer, Joshua

2017-03-01

Near-infrared fluorescence (NIRF) imaging has gained much attention as a clinical method for enhancing visualization of cancers, perfusion and biological structures in surgical applications where a fluorescent dye is monitored by an imaging system. In order to address the emerging need for standardization of this innovative technology, it is necessary to develop and validate test methods suitable for objective, quantitative assessment of device performance. Towards this goal, we develop target-based test methods and investigate best practices for key NIRF imaging system performance characteristics including spatial resolution, depth of field and sensitivity. Characterization of fluorescence properties was performed by generating excitation-emission matrix properties of indocyanine green and quantum dots in biological solutions and matrix materials. A turbid, fluorophore-doped target was used, along with a resolution target for assessing image sharpness. Multi-well plates filled with either liquid or solid targets were generated to explore best practices for evaluating detection sensitivity. Overall, our results demonstrate the utility of objective, quantitative, target-based testing approaches as well as the need to consider a wide range of factors in establishing standardized approaches for NIRF imaging system performance.

Discovery and characterization of 3000+ main-sequence binaries from APOGEE spectra

NASA Astrophysics Data System (ADS)

El-Badry, Kareem; Ting, Yuan-Sen; Rix, Hans-Walter; Quataert, Eliot; Weisz, Daniel R.; Cargile, Phillip; Conroy, Charlie; Hogg, David W.; Bergemann, Maria; Liu, Chao

2018-05-01

We develop a data-driven spectral model for identifying and characterizing spatially unresolved multiple-star systems and apply it to APOGEE DR13 spectra of main-sequence stars. Binaries and triples are identified as targets whose spectra can be significantly better fit by a superposition of two or three model spectra, drawn from the same isochrone, than any single-star model. From an initial sample of ˜20 000 main-sequence targets, we identify ˜2500 binaries in which both the primary and secondary stars contribute detectably to the spectrum, simultaneously fitting for the velocities and stellar parameters of both components. We additionally identify and fit ˜200 triple systems, as well as ˜700 velocity-variable systems in which the secondary does not contribute detectably to the spectrum. Our model simplifies the process of simultaneously fitting single- or multi-epoch spectra with composite models and does not depend on a velocity offset between the two components of a binary, making it sensitive to traditionally undetectable systems with periods of hundreds or thousands of years. In agreement with conventional expectations, almost all the spectrally identified binaries with measured parallaxes fall above the main sequence in the colour-magnitude diagram. We find excellent agreement between spectrally and dynamically inferred mass ratios for the ˜600 binaries in which a dynamical mass ratio can be measured from multi-epoch radial velocities. We obtain full orbital solutions for 64 systems, including 14 close binaries within hierarchical triples. We make available catalogues of stellar parameters, abundances, mass ratios, and orbital parameters.

Two novel motion-based algorithms for surveillance video analysis on embedded platforms

NASA Astrophysics Data System (ADS)

Vijverberg, Julien A.; Loomans, Marijn J. H.; Koeleman, Cornelis J.; de With, Peter H. N.

2010-05-01

This paper proposes two novel motion-vector based techniques for target detection and target tracking in surveillance videos. The algorithms are designed to operate on a resource-constrained device, such as a surveillance camera, and to reuse the motion vectors generated by the video encoder. The first novel algorithm for target detection uses motion vectors to construct a consistent motion mask, which is combined with a simple background segmentation technique to obtain a segmentation mask. The second proposed algorithm aims at multi-target tracking and uses motion vectors to assign blocks to targets employing five features. The weights of these features are adapted based on the interaction between targets. These algorithms are combined in one complete analysis application. The performance of this application for target detection has been evaluated for the i-LIDS sterile zone dataset and achieves an F1-score of 0.40-0.69. The performance of the analysis algorithm for multi-target tracking has been evaluated using the CAVIAR dataset and achieves an MOTP of around 9.7 and MOTA of 0.17-0.25. On a selection of targets in videos from other datasets, the achieved MOTP and MOTA are 8.8-10.5 and 0.32-0.49 respectively. The execution time on a PC-based platform is 36 ms. This includes the 20 ms for generating motion vectors, which are also required by the video encoder.

Multi-channeled single chain variable fragment (scFv) based microfluidic device for explosives detection.

PubMed

Charles, Paul T; Davis, Jasmine; Adams, André A; Anderson, George P; Liu, Jinny L; Deschamps, Jeffrey R; Kusterbeck, Anne W

2015-11-01

The development of explosives detection technologies has increased significantly over the years as environmental and national security agencies implement tighter pollution control measures and methods for improving homeland security. 2, 4, 6-Trinitrotoluene (TNT), known primarily as a component in munitions, has been targeted for both its toxicity and carcinogenic properties that if present at high concentrations can be a detriment to both humans, marine and plant ecosystems. Enabling end users with environmental detection and monitoring systems capable of providing real-time, qualitative and quantitative chemical analysis of these toxic compounds would be extremely beneficial. Reported herein is the development of a multi-channeled microfluidic device immobilized with single chain fragment variable (scFv) recombinant proteins specific for the explosive, TNT. Fluorescence displacement immunoassays performed under constant flow demonstrated trace level sensitivity and specificity for TNT. The utility of three multi-channeled devices immobilized with either (1) scFv recombinant protein, (2) biotinylated-scFv (bt-scFv) and (3) monoclonal anti-TNT (whole IgG molecule) were investigated and compared. Fluorescence dose response curves, crossreactivity measurements and limits of detection (LOD) for TNT were determined. Fluorescence displacement immunoassays for TNT in natural seawater demonstrated detection limits at sub-parts-per-billion levels (0.5 ppb) utilizing the microfluidic device with immobilized bt-scFv. Published by Elsevier B.V.

Pilot Integration of HIV Screening and Healthcare Settings with Multi- Component Social Network and Partner Testing for HIV Detection.

PubMed

Rentz, Michael F; Ruffner, Andrew H; Ancona, Rachel M; Hart, Kimberly W; Kues, John R; Barczak, Christopher M; Lindsell, Christopher J; Fichtenbaum, Carl J; Lyons, Michael S

2017-11-23

Healthcare settings screen broadly for HIV. Public health settings use social network and partner testing ("Transmission Network Targeting (TNT)") to select high-risk individuals based on their contacts. HIV screening and TNT systems are not integrated, and healthcare settings have not implemented TNT. The study aimed to evaluate pilot implementation of multi-component, multi-venue TNT in conjunction with HIV screening by a healthcare setting. Our urban, academic health center implemented a TNT program in collaboration with the local health department for five months during 2011. High-risk or HIV positive patients of the infectious diseases clinic and emergency department HIV screening program were recruited to access social and partner networks via compensated peer-referral, testing of companions present with them, and partner notification services. Contacts became the next-generation index cases in a snowball recruitment strategy. The pilot TNT program yielded 485 HIV tests for 482 individuals through eight generations of recruitment with five (1.0%; 95% CI = 0.4%, 2.3%) new diagnoses. Of these, 246 (51.0%; 95% CI = 46.6%, 55.5%) reported that they had not been tested for HIV within the last 12 months and 383 (79.5%; 95% CI = 75.7%, 82.9%) had not been tested by the existing ED screening program within the last five years. TNT complements population screening by more directly targeting high-risk individuals and by expanding the population receiving testing. Information from existing healthcare services could be used to seed TNT programs, or TNT could be implemented within healthcare settings. Research evaluating multi-component, multi-venue HIV detection is necessary to maximize complementary approaches while minimizing redundancy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

An AdaBoost Based Approach to Automatic Classification and Detection of Buildings Footprints, Vegetation Areas and Roads from Satellite Images

NASA Astrophysics Data System (ADS)

Gonulalan, Cansu

In recent years, there has been an increasing demand for applications to monitor the targets related to land-use, using remote sensing images. Advances in remote sensing satellites give rise to the research in this area. Many applications ranging from urban growth planning to homeland security have already used the algorithms for automated object recognition from remote sensing imagery. However, they have still problems such as low accuracy on detection of targets, specific algorithms for a specific area etc. In this thesis, we focus on an automatic approach to classify and detect building foot-prints, road networks and vegetation areas. The automatic interpretation of visual data is a comprehensive task in computer vision field. The machine learning approaches improve the capability of classification in an intelligent way. We propose a method, which has high accuracy on detection and classification. The multi class classification is developed for detecting multiple objects. We present an AdaBoost-based approach along with the supervised learning algorithm. The combi- nation of AdaBoost with "Attentional Cascade" is adopted from Viola and Jones [1]. This combination decreases the computation time and gives opportunity to real time applications. For the feature extraction step, our contribution is to combine Haar-like features that include corner, rectangle and Gabor. Among all features, AdaBoost selects only critical features and generates in extremely efficient cascade structured classifier. Finally, we present and evaluate our experimental results. The overall system is tested and high performance of detection is achieved. The precision rate of the final multi-class classifier is over 98%.

Structural Information Detection Based Filter for GF-3 SAR Images

NASA Astrophysics Data System (ADS)

Sun, Z.; Song, Y.

2018-04-01

GF-3 satellite with high resolution, large swath, multi-imaging mode, long service life and other characteristics, can achieve allweather and all day monitoring for global land and ocean. It has become the highest resolution satellite system in the world with the C-band multi-polarized synthetic aperture radar (SAR) satellite. However, due to the coherent imaging system, speckle appears in GF-3 SAR images, and it hinders the understanding and interpretation of images seriously. Therefore, the processing of SAR images has big challenges owing to the appearance of speckle. The high-resolution SAR images produced by the GF-3 satellite are rich in information and have obvious feature structures such as points, edges, lines and so on. The traditional filters such as Lee filter and Gamma MAP filter are not appropriate for the GF-3 SAR images since they ignore the structural information of images. In this paper, the structural information detection based filter is constructed, successively including the point target detection in the smallest window, the adaptive windowing method based on regional characteristics, and the most homogeneous sub-window selection. The despeckling experiments on GF-3 SAR images demonstrate that compared with the traditional filters, the proposed structural information detection based filter can well preserve the points, edges and lines as well as smooth the speckle more sufficiently.

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.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images

PubMed Central

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-01-01

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu’s algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape. PMID:28481260

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

NASA Astrophysics Data System (ADS)

Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

2014-11-01

In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

Multiplexed detection of anthrax-related toxin genes.

PubMed

Moser, Michael J; Christensen, Deanna R; Norwood, David; Prudent, James R

2006-02-01

Simultaneous analysis of three targets in three colors on any real-time polymerase chain reaction (PCR) instrument would increase the flexibility of real-time PCR. For the detection of Bacillus strains that can cause inhalation anthrax-related illness, this ability would be valuable because two plasmids confer virulence, and internal positive controls are needed to monitor the testing in cases lacking target-specific signals. Using a real-time PCR platform called MultiCode-RTx, multiple assays were developed that specifically monitor the presence of Bacillus anthracis-specific virulence plasmid-associated genes. In particular for use on LightCycler-1, two triplex RTx systems demonstrated high sensitivity with limits of detection nearing single-copy levels for both plasmids. Specificity was established using a combination of Ct values and correct amplicon melting temperatures. All reactions were further verified by detection of an internal positive control. For these two triplex RTx assays, the analytical detection limit was one to nine plasmid copy equivalents, 100% analytical specificity with a 95% confidence interval (CI) of 9%, and 100% analytical sensitivity with a CI of 2%. Although further testing using clinical or environmental samples will be required to assess diagnostic sensitivity and specificity, the RTx platform achieves similar results to those of probe-based real-time systems.

A miniaturized optoelectronic system for rapid quantitative label-free detection of harmful species in food

NASA Astrophysics Data System (ADS)

Raptis, Ioannis; Misiakos, Konstantinos; Makarona, Eleni; Salapatas, Alexandros; Petrou, Panagiota; Kakabakos, Sotirios; Botsialas, Athanasios; Jobst, Gerhard; Haasnoot, Willem; Fernandez-Alba, Amadeo; Lees, Michelle; Valamontes, Evangelos

2016-03-01

Optical biosensors have emerged in the past decade as the most promising candidates for portable, highly-sensitive bioanalytical systems that can be employed for in-situ measurements. In this work, a miniaturized optoelectronic system for rapid, quantitative, label-free detection of harmful species in food is presented. The proposed system has four distinctive features that can render to a powerful tool for the next generation of Point-of-Need applications, namely it accommodates the light sources and ten interferometric biosensors on a single silicon chip of a less-than-40mm2 footprint, each sensor can be individually functionalized for a specific target analyte, the encapsulation can be performed at the wafer-scale, and finally it exploits a new operation principle, Broad-band Mach-Zehnder Interferometry to ameliorate its analytical capabilities. Multi-analyte evaluation schemes for the simultaneous detection of harmful contaminants, such as mycotoxins, allergens and pesticides, proved that the proposed system is capable of detecting within short time these substances at concentrations below the limits imposed by regulatory authorities, rendering it to a novel tool for the near-future food safety applications.

Multi-Source Fusion for Explosive Hazard Detection in Forward Looking Sensors

DTIC Science & Technology

2016-12-01

include; (1) Investigating (a) thermal, (b) synthetic aperture acoustics ( SAA ) and (c) voxel space Radar for buried and side threat attacks. (2...detection. (3) With respect to SAA , we developed new approaches in the time and frequency domains for analyzing signature of concealed targets (called...Fraz). We also developed a method to extract a multi-spectral signature from SAA and deep learning was used on limited training and class imbalance

Regional fringe analysis for improving depth measurement in phase-shifting fringe projection profilometry

NASA Astrophysics Data System (ADS)

Chien, Kuang-Che Chang; Tu, Han-Yen; Hsieh, Ching-Huang; Cheng, Chau-Jern; Chang, Chun-Yen

2018-01-01

This study proposes a regional fringe analysis (RFA) method to detect the regions of a target object in captured shifted images to improve depth measurement in phase-shifting fringe projection profilometry (PS-FPP). In the RFA method, region-based segmentation is exploited to segment the de-fringed image of a target object, and a multi-level fuzzy-based classification with five presented features is used to analyze and discriminate the regions of an object from the segmented regions, which were associated with explicit fringe information. Then, in the experiment, the performance of the proposed method is tested and evaluated on 26 test cases made of five types of materials. The qualitative and quantitative results demonstrate that the proposed RFA method can effectively detect the desired regions of an object to improve depth measurement in the PS-FPP system.

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.

Loop-mediated isothermal amplification (LAMP) assay for speedy diagnosis of tubercular lymphadenitis: The multi-targeted 60-minute approach.

PubMed

Sharma, Megha; Sharma, Kusum; Sharma, Aman; Gupta, Nalini; Rajwanshi, Arvind

2016-09-01

Tuberculous lymphadenitis (TBLA), the most common presentation of tuberculosis, poses a significant diagnostic challenge in the developing countries. Timely, accurate and cost-effective diagnosis can decrease the high morbidity associated with TBLA especially in resource-poor high-endemic regions. The loop-mediated isothermal amplification assay (LAMP), using two targets, was evaluated for the diagnosis of TBLA. LAMP assay using 3 sets of primers (each for IS6110 and MPB64) was performed on 170 fine needle aspiration samples (85 confirmed, 35 suspected, 50 control cases of TBLA). Results were compared against IS6110 PCR, cytology, culture and smear. The overall sensitivity and specificity of LAMP assay, using multi-targeted approach, was 90% and 100% respectively in diagnosing TBLA. The sensitivity of multi-targeted LAMP, only MPB64 LAMP, only IS6110 LAMP and IS6110 PCR was 91.7%, 89.4%, 84.7% and 75.2%, respectively among confirmed cases and 85.7%, 77.1%, 68.5% and 60%, respectively among suspected cases of TBLA. Additional 12/120 (10%) cases were detected using multi-targeted method. The multi-targeted LAMP, with its speedy and reliable results, is a potential diagnostic test for TBLA in low-resource countries. Copyright © 2016 Elsevier Ltd. All rights reserved.

ARCHITECTURE AND DYNAMICS OF KEPLER'S CANDIDATE MULTIPLE TRANSITING PLANET SYSTEMS

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

Lissauer, Jack J.; Jenkins, Jon M.; Borucki, William J.

About one-third of the {approx}1200 transiting planet candidates detected in the first four months of Kepler data are members of multiple candidate systems. There are 115 target stars with two candidate transiting planets, 45 with three, 8 with four, and 1 each with five and six. We characterize the dynamical properties of these candidate multi-planet systems. The distribution of observed period ratios shows that the vast majority of candidate pairs are neither in nor near low-order mean-motion resonances. Nonetheless, there are small but statistically significant excesses of candidate pairs both in resonance and spaced slightly too far apart to bemore » in resonance, particularly near the 2:1 resonance. We find that virtually all candidate systems are stable, as tested by numerical integrations that assume a nominal mass-radius relationship. Several considerations strongly suggest that the vast majority of these multi-candidate systems are true planetary systems. Using the observed multiplicity frequencies, we find that a single population of planetary systems that matches the higher multiplicities underpredicts the number of singly transiting systems. We provide constraints on the true multiplicity and mutual inclination distribution of the multi-candidate systems, revealing a population of systems with multiple super-Earth-size and Neptune-size planets with low to moderate mutual inclinations.« less

Fly Eye radar: detection through high scattered media

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo; Gorwara, Ashok

2017-05-01

Longer radio frequency waves better penetrating through high scattered media than millimeter waves, but imaging resolution limited by diffraction at longer wavelength. Same time frequency and amplitudes of diffracted waves (frequency domain measurement) provides information of object. Phase shift of diffracted waves (phase front in time domain) consists information about shape of object and can be applied for reconstruction of object shape or even image by recording of multi-frequency digital hologram. Spectrum signature or refracted waves allows identify the object content. Application of monopulse method with overlap closely spaced antenna patterns provides high accuracy measurement of amplitude, phase, and direction to signal source. Digitizing of received signals separately in each antenna relative to processor time provides phase/frequency independence. Fly eye non-scanning multi-frequency radar system provides simultaneous continuous observation of multiple targets and wide possibilities for stepped frequency, simultaneous frequency, chaotic frequency sweeping waveform (CFS), polarization modulation for reliable object detection. Proposed c-band fly eye radar demonstrated human detection through 40 cm concrete brick wall with human and wall material spectrum signatures and can be applied for through wall human detection, landmines, improvised explosive devices detection, underground or camouflaged object imaging.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Fast photoacoustic imaging system based on 320-element linear transducer array.

PubMed

Yin, Bangzheng; Xing, Da; Wang, Yi; Zeng, Yaguang; Tan, Yi; Chen, Qun

2004-04-07

A fast photoacoustic (PA) imaging system, based on a 320-transducer linear array, was developed and tested on a tissue phantom. To reconstruct a test tomographic image, 64 time-domain PA signals were acquired from a tissue phantom with embedded light-absorption targets. A signal acquisition was accomplished by utilizing 11 phase-controlled sub-arrays, each consisting of four transducers. The results show that the system can rapidly map the optical absorption of a tissue phantom and effectively detect the embedded light-absorbing target. By utilizing the multi-element linear transducer array and phase-controlled imaging algorithm, we thus can acquire PA tomography more efficiently, compared to other existing technology and algorithms. The methodology and equipment thus provide a rapid and reliable approach to PA imaging that may have potential applications in noninvasive imaging and clinic diagnosis.

Experimental Study of Magnetic Multi-Walled Carbon Nanotube-Doxorubicin Conjugate in a Lymph Node Metastatic Model of Breast Cancer.

PubMed

Ji, Jian; Liu, Minfeng; Meng, Yue; Liu, Runqi; Yan, Yan; Dong, Jianyu; Guo, Zhaoze; Ye, Changsheng

2016-07-07

BACKGROUND The lymphatic system plays a significant role in the defense of a subject against breast cancer and is one of the major pathways for the metastasis of breast cancer. To improve the prognosis, many means, including surgery, radiotherapy, and chemotherapy, have been used. However, the combination of all these modalities has limited efficacy. Lymph nodes, therefore, have become an exceptionally potential target organ in cancer chemotherapy. MATERIAL AND METHODS A lymph node metastatic model of breast cancer was established in BALB/c mice. Magnetic multi-walled carbon nanotube carrier with good adsorption and lymph node-targeting capacity was prepared and conjugated with doxorubicin to make the magnetic multi-walled carbon nanotube-doxorubicin suspension. Dispersions of doxorubicin, magnetic multi-walled carbon nanotube-doxorubicin, and magnetic multi-walled carbon nanotube were injected into lymph node metastatic mice to compare their inhibitory effects on tumor cells in vivo. Inhibition of these dispersions on EMT-6 breast cancer cells was detected via MTT assay in vitro. RESULTS Although no significant difference was found between the effects of doxorubicin and magnetic multi-walled carbon nanotube-doxorubicin with the same concentration of doxorubicin on EMT-6 breast cancer cells in vitro, in terms of sizes of metastatic lymph nodes and xenograft tumors, apoptosis in metastatic lymph nodes, and adverse reactions, the magnetic multi-walled carbon nanotube-doxorubicin group differed significantly from the other groups. CONCLUSIONS The magnetic multi-walled carbon nanotube-doxorubicin clearly played an inhibitory role in lymph node metastases to EMT-6 breast cancer cells.

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.

Discriminative correlation filter tracking with occlusion detection

NASA Astrophysics Data System (ADS)

Zhang, Shuo; Chen, Zhong; Yu, XiPeng; Zhang, Ting; He, Jing

2018-03-01

Aiming at the problem that the correlation filter-based tracking algorithm can not track the target of severe occlusion, a target re-detection mechanism is proposed. First of all, based on the ECO, we propose the multi-peak detection model and the response value to distinguish the occlusion and deformation in the target tracking, which improve the success rate of tracking. And then we add the confidence model to update the mechanism to effectively prevent the model offset problem which due to similar targets or background during the tracking process. Finally, the redetection mechanism of the target is added, and the relocation is performed after the target is lost, which increases the accuracy of the target positioning. The experimental results demonstrate that the proposed tracker performs favorably against state-of-the-art methods in terms of robustness and accuracy.

Multicolor Super-Resolution Fluorescence Imaging via Multi-Parameter Fluorophore Detection

PubMed Central

Bates, Mark; Dempsey, Graham T; Chen, Kok Hao; Zhuang, Xiaowei

2012-01-01

Understanding the complexity of the cellular environment will benefit from the ability to unambiguously resolve multiple cellular components, simultaneously and with nanometer-scale spatial resolution. Multicolor super-resolution fluorescence microscopy techniques have been developed to achieve this goal, yet challenges remain in terms of the number of targets that can be simultaneously imaged and the crosstalk between color channels. Herein, we demonstrate multicolor stochastic optical reconstruction microscopy (STORM) based on a multi-parameter detection strategy, which uses both the fluorescence activation wavelength and the emission color to discriminate between photo-activatable fluorescent probes. First, we obtained two-color super-resolution images using the near-infrared cyanine dye Alexa 750 in conjunction with a red cyanine dye Alexa 647, and quantified color crosstalk levels and image registration accuracy. Combinatorial pairing of these two switchable dyes with fluorophores which enhance photo-activation enabled multi-parameter detection of six different probes. Using this approach, we obtained six-color super-resolution fluorescence images of a model sample. The combination of multiple fluorescence detection parameters for improved fluorophore discrimination promises to substantially enhance our ability to visualize multiple cellular targets with sub-diffraction-limit resolution. PMID:22213647

Track-before-detect labeled multi-bernoulli particle filter with label switching

NASA Astrophysics Data System (ADS)

Garcia-Fernandez, Angel F.

2016-10-01

This paper presents a multitarget tracking particle filter (PF) for general track-before-detect measurement models. The PF is presented in the random finite set framework and uses a labelled multi-Bernoulli approximation. We also present a label switching improvement algorithm based on Markov chain Monte Carlo that is expected to increase filter performance if targets get in close proximity for a sufficiently long time. The PF is tested in two challenging numerical examples.

Semiconductor Laser Multi-Spectral Sensing and Imaging

PubMed Central

Le, Han Q.; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers. PMID:22315555

Semiconductor laser multi-spectral sensing and imaging.

PubMed

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Multi-target detection and positioning in crowds using multiple camera surveillance

NASA Astrophysics Data System (ADS)

Huang, Jiahu; Zhu, Qiuyu; Xing, Yufeng

2018-04-01

In this study, we propose a pixel correspondence algorithm for positioning in crowds based on constraints on the distance between lines of sight, grayscale differences, and height in a world coordinates system. First, a Gaussian mixture model is used to obtain the background and foreground from multi-camera videos. Second, the hair and skin regions are extracted as regions of interest. Finally, the correspondences between each pixel in the region of interest are found under multiple constraints and the targets are positioned by pixel clustering. The algorithm can provide appropriate redundancy information for each target, which decreases the risk of losing targets due to a large viewing angle and wide baseline. To address the correspondence problem for multiple pixels, we construct a pixel-based correspondence model based on a similar permutation matrix, which converts the correspondence problem into a linear programming problem where a similar permutation matrix is found by minimizing an objective function. The correct pixel correspondences can be obtained by determining the optimal solution of this linear programming problem and the three-dimensional position of the targets can also be obtained by pixel clustering. Finally, we verified the algorithm with multiple cameras in experiments, which showed that the algorithm has high accuracy and robustness.

Smart nanomaterials for biomedics.

PubMed

Choi, Soonmo; Tripathi, Anuj; Singh, Deepti

2014-10-01

Nanotechnology has become important in various disciplines of technology and science. It has proven to be a potential candidate for various applications ranging from biosensors to the delivery of genes and therapeutic agents to tissue engineering. Scaffolds for every application can be tailor made to have the appropriate physicochemical properties that will influence the in vivo system in the desired way. For highly sensitive and precise detection of specific signals or pathogenic markers, or for sensing the levels of particular analytes, fabricating target-specific nanomaterials can be very useful. Multi-functional nano-devices can be fabricated using different approaches to achieve multi-directional patterning in a scaffold with the ability to alter topographical cues at scale of less than or equal to 100 nm. Smart nanomaterials are made to understand the surrounding environment and act accordingly by either protecting the drug in hostile conditions or releasing the "payload" at the intended intracellular target site. All of this is achieved by exploiting polymers for their functional groups or incorporating conducting materials into a natural biopolymer to obtain a "smart material" that can be used for detection of circulating tumor cells, detection of differences in the body analytes, or repair of damaged tissue by acting as a cell culture scaffold. Nanotechnology has changed the nature of diagnosis and treatment in the biomedical field, and this review aims to bring together the most recent advances in smart nanomaterials.

A Multi-resolution, Multi-epoch Low Radio Frequency Survey of the Kepler K2 Mission Campaign 1 Field

NASA Astrophysics Data System (ADS)

Tingay, S. J.; Hancock, P. J.; Wayth, R. B.; Intema, H.; Jagannathan, P.; Mooley, K.

2016-10-01

We present the first dedicated radio continuum survey of a Kepler K2 mission field, Field 1, covering the North Galactic Cap. The survey is wide field, contemporaneous, multi-epoch, and multi-resolution in nature and was conducted at low radio frequencies between 140 and 200 MHz. The multi-epoch and ultra wide field (but relatively low resolution) part of the survey was provided by 15 nights of observation using the Murchison Widefield Array (MWA) over a period of approximately a month, contemporaneous with K2 observations of the field. The multi-resolution aspect of the survey was provided by the low resolution (4‧) MWA imaging, complemented by non-contemporaneous but much higher resolution (20″) observations using the Giant Metrewave Radio Telescope (GMRT). The survey is, therefore, sensitive to the details of radio structures across a wide range of angular scales. Consistent with other recent low radio frequency surveys, no significant radio transients or variables were detected in the survey. The resulting source catalogs consist of 1085 and 1468 detections in the two MWA observation bands (centered at 154 and 185 MHz, respectively) and 7445 detections in the GMRT observation band (centered at 148 MHz), over 314 square degrees. The survey is presented as a significant resource for multi-wavelength investigations of the more than 21,000 target objects in the K2 field. We briefly examine our survey data against K2 target lists for dwarf star types (stellar types M and L) that have been known to produce radio flares.

Carbon Nanotube Nanoelectrode Array for Ultrasensitive DNA Detection

NASA Technical Reports Server (NTRS)

Li, Jun; Koehne, Jessica; Chen, Hua; Cassell, Alan; Ng, Hou Tee; Fan, Wendy; Ye, Qi; Han, Jie; Meyyappan, M.

2003-01-01

A reliable nanoelectrode array based on vertically aligned multi-walled carbon nanotubes (MWNTs) embedded in SiO2 is used for ultrasensitive DNA detection. Characteristic nanoelectrode behavior is observed using low-density MWNT arrays for measuring both bulk and surface immobilized redox species such as K4Fe(CN)6. The open-end of MWNTs present similar properties as graphite edge-plane electrodes with wide potential window, flexible chemical functionalities, and good biocompatibility. Oligonucleotide probes are selectively functionalized at the open ends cf the nanotube array and specifically hybridized with oligonucleotide targets. The guanine groups are employed as the signal moieties in the electrochemical measurements. Ru(bpy)3(2+) mediator is used to further amplify the guanine oxidation signal. The hybridization of subattomoles of PCR amplified DNA targets is detected electrochemically by combining the MWNT nanoelectrode array with the Ru(bpy)32' amplification mechanism. This system provides a general platform of molecular diagnostics for applications requiring ultrahigh sensitivity, high-degree of miniaturization, and simple sample preparations.

Clinically compatible flexible wide-field multi-color fluorescence endoscopy with a porcine colon model

PubMed Central

Oh, Gyugnseok; Park, Youngrong; Yoo, Su Woong; Hwang, Soonjoo; Chin-Yu, Alexey V. Dan; Ryu, Yeon-Mi; Kim, Sang-Yeob; Do, Eun-Ju; Kim, Ki Hean; Kim, Sungjee; Myung, Seung-Jae; Chung, Euiheon

2017-01-01

Early detection of structural or molecular changes in dysplastic epithelial tissues is crucial for cancer screening and surveillance. Multi-targeting molecular endoscopic fluorescence imaging may improve noninvasive detection of precancerous lesions in the colon. Here, we report the first clinically compatible, wide-field-of-view, multi-color fluorescence endoscopy with a leached fiber bundle scope using a porcine model. A porcine colon model that resembles the human colon is used for the detection of surrogate tumors composed of multiple biocompatible fluorophores (FITC, ICG, and heavy metal-free quantum dots (hfQDs)). With an ex vivo porcine colon tumor model, molecular imaging with hfQDs conjugated with MMP14 antibody was achieved by spraying molecular probes on a mucosa layer that contains xenograft tumors. With an in vivo porcine colon embedded with surrogate tumors, target-to-background ratios of 3.36 ± 0.43, 2.70 ± 0.72, and 2.10 ± 0.13 were achieved for FITC, ICG, and hfQD probes, respectively. This promising endoscopic technology with molecular contrast shows the capacity to reveal hidden tumors and guide treatment strategy decisions. PMID:28270983

A multi-electrode biomimetic electrolocation sensor

NASA Astrophysics Data System (ADS)

Mayekar, K.; Damalla, D.; Gottwald, M.; Bousack, H.; von der Emde, G.

2012-04-01

We present the concept of an active multi-electrode catheter inspired by the electroreceptive system of the weakly electric fish, Gnathonemus petersii. The skin of this fish exhibits numerous electroreceptor organs which are capable of sensing a self induced electrical field. Our sensor is composed of a sending electrode and sixteen receiving electrodes. The electrical field produced by the sending electrode was measured by the receiving electrodes and objects were detected by the perturbation of the electrical field they induce. The intended application of such a sensor is in coronary diagnostics, in particular in distinguishing various types of plaques, which are major causes of heart attack. For calibration of the sensor system, finite element modeling (FEM) was performed. To validate the model, experimental measurements were carried out with two different systems. The physical system was glass tubing with metal and plastic wall insertions as targets. For the control of the experiment and for data acquisition, the software LabView designed for 17 electrodes was used. Different parameters of the electric images were analyzed for the prediction of the electrical properties and size of the inserted targets in the tube. Comparisons of the voltage modulations predicted from the FEM model and the experiments showed a good correspondence. It can be concluded that this novel biomimetic method can be further developed for detailed investigations of atherosclerotic lesions. Finally, we discuss various design strategies to optimize the output of the sensor using different simulated models to enhance target recognition.

Multiple-camera tracking: UK government requirements

NASA Astrophysics Data System (ADS)

Hosmer, Paul

2007-10-01

The Imagery Library for Intelligent Detection Systems (i-LIDS) is the UK government's new standard for Video Based Detection Systems (VBDS). The standard was launched in November 2006 and evaluations against it began in July 2007. With the first four i-LIDS scenarios completed, the Home Office Scientific development Branch (HOSDB) are looking toward the future of intelligent vision in the security surveillance market by adding a fifth scenario to the standard. The fifth i-LIDS scenario will concentrate on the development, testing and evaluation of systems for the tracking of people across multiple cameras. HOSDB and the Centre for the Protection of National Infrastructure (CPNI) identified a requirement to track targets across a network of CCTV cameras using both live and post event imagery. The Detection and Vision Systems group at HOSDB were asked to determine the current state of the market and develop an in-depth Operational Requirement (OR) based on government end user requirements. Using this OR the i-LIDS team will develop a full i-LIDS scenario to aid the machine vision community in its development of multi-camera tracking systems. By defining a requirement for multi-camera tracking and building this into the i-LIDS standard the UK government will provide a widely available tool that developers can use to help them turn theory and conceptual demonstrators into front line application. This paper will briefly describe the i-LIDS project and then detail the work conducted in building the new tracking aspect of the standard.

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

Multi-agent autonomous system

NASA Technical Reports Server (NTRS)

Fink, Wolfgang (Inventor); Dohm, James (Inventor); Tarbell, Mark A. (Inventor)

2010-01-01

A multi-agent autonomous system for exploration of hazardous or inaccessible locations. The multi-agent autonomous system includes simple surface-based agents or craft controlled by an airborne tracking and command system. The airborne tracking and command system includes an instrument suite used to image an operational area and any craft deployed within the operational area. The image data is used to identify the craft, targets for exploration, and obstacles in the operational area. The tracking and command system determines paths for the surface-based craft using the identified targets and obstacles and commands the craft using simple movement commands to move through the operational area to the targets while avoiding the obstacles. Each craft includes its own instrument suite to collect information about the operational area that is transmitted back to the tracking and command system. The tracking and command system may be further coupled to a satellite system to provide additional image information about the operational area and provide operational and location commands to the tracking and command system.

An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

PubMed

Wang, Ophelia; Zachmann, Luke J; Sesnie, Steven E; Olsson, Aaryn D; Dickson, Brett G

2014-01-01

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives.

An Iterative and Targeted Sampling Design Informed by Habitat Suitability Models for Detecting Focal Plant Species over Extensive Areas

PubMed Central

Wang, Ophelia; Zachmann, Luke J.; Sesnie, Steven E.; Olsson, Aaryn D.; Dickson, Brett G.

2014-01-01

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives. PMID:25019621

Three dimensional time reversal optical tomography

NASA Astrophysics Data System (ADS)

Wu, Binlin; Cai, W.; Alrubaiee, M.; Xu, M.; Gayen, S. K.

2011-03-01

Time reversal optical tomography (TROT) approach is used to detect and locate absorptive targets embedded in a highly scattering turbid medium to assess its potential in breast cancer detection. TROT experimental arrangement uses multi-source probing and multi-detector signal acquisition and Multiple-Signal-Classification (MUSIC) algorithm for target location retrieval. Light transport from multiple sources through the intervening medium with embedded targets to the detectors is represented by a response matrix constructed using experimental data. A TR matrix is formed by multiplying the response matrix by its transpose. The eigenvectors with leading non-zero eigenvalues of the TR matrix correspond to embedded objects. The approach was used to: (a) obtain the location and spatial resolution of an absorptive target as a function of its axial position between the source and detector planes; and (b) study variation in spatial resolution of two targets at the same axial position but different lateral positions. The target(s) were glass sphere(s) of diameter ~9 mm filled with ink (absorber) embedded in a 60 mm-thick slab of Intralipid-20% suspension in water with an absorption coefficient μa ~ 0.003 mm-1 and a transport mean free path lt ~ 1 mm at 790 nm, which emulate the average values of those parameters for human breast tissue. The spatial resolution and accuracy of target location depended on axial position, and target contrast relative to the background. Both the targets could be resolved and located even when they were only 4-mm apart. The TROT approach is fast, accurate, and has the potential to be useful in breast cancer detection and localization.

Modeling Multi-wavelength Stellar Astrometry. III. Determination of the Absolute Masses of Exoplanets and Their Host Stars

NASA Astrophysics Data System (ADS)

Coughlin, J. L.; López-Morales, Mercedes

2012-05-01

Astrometric measurements of stellar systems are becoming significantly more precise and common, with many ground- and space-based instruments and missions approaching 1 μas precision. We examine the multi-wavelength astrometric orbits of exoplanetary systems via both analytical formulae and numerical modeling. Exoplanets have a combination of reflected and thermally emitted light that causes the photocenter of the system to shift increasingly farther away from the host star with increasing wavelength. We find that, if observed at long enough wavelengths, the planet can dominate the astrometric motion of the system, and thus it is possible to directly measure the orbits of both the planet and star, and thus directly determine the physical masses of the star and planet, using multi-wavelength astrometry. In general, this technique works best for, though is certainly not limited to, systems that have large, high-mass stars and large, low-mass planets, which is a unique parameter space not covered by other exoplanet characterization techniques. Exoplanets that happen to transit their host star present unique cases where the physical radii of the planet and star can be directly determined via astrometry alone. Planetary albedos and day-night contrast ratios may also be probed via this technique due to the unique signature they impart on the observed astrometric orbits. We develop a tool to examine the prospects for near-term detection of this effect, and give examples of some exoplanets that appear to be good targets for detection in the K to N infrared observing bands, if the required precision can be achieved.

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.

Design of magnetic and fluorescent nanoparticles for in vivo MR and NIRF cancer imaging

NASA Astrophysics Data System (ADS)

Key, Jaehong

One big challenge for cancer treatment is that it has many errors in detection of cancers in the early stages before metastasis occurs. Using a current imaging modality, the detection of small tumors having potential metastasis is still very difficult. Thus, the development of multi-component nanoparticles (NPs) for dual modality cancer imaging is invaluable. The multi-component NPs can be an alternative to overcome the limitations from an imaging modality. For example, the multi-component NPs can visualize small tumors in both magnetic resonance imaging (MRI) and near infrared fluorescence (NIRF) imaging, which can help find the location of the tumors deep inside the body using MRI and subsequently guide surgeons to delineate the margin of tumors using highly sensitive NIRF imaging during a surgical operation. In this dissertation, we demonstrated the potential of the MRI and NIRF dual-modality NPs for skin and bladder cancer imaging. The multi-component NPs consisted of glycol chitosan, superparamagnetic iron oxide, NIRF dye, and cancer targeting peptides. We characterized the NPs and evaluated them with tumor bearing mice as well as various cancer cells. The findings of this research will contribute to the development of cancer diagnostic imaging and it can also be extensively applied to drug delivery system and fluorescence-guided surgical removal of cancer.

Integrated signal probe based aptasensor for dual-analyte detection.

PubMed

Xiang, Juan; Pi, Xiaomei; Chen, Xiaoqing; Xiang, Lei; Yang, Minghui; Ren, Hao; Shen, Xiaojuan; Qi, Ning; Deng, Chunyan

2017-10-15

For the multi-analyte detection, although the sensitivity has commonly met the practical requirements, the reliability, reproducibility and stability need to be further improved. In this work, two different aptamer probes labeled with redox tags were used as signal probe1 (sP1) and signal probe2 (sP2), which were integrated into one unity DNA architecture to develop the integrated signal probe (ISP). Comparing with the conventional independent signal probes for the simultaneous multi-analyte detection, the proposed ISP was more reproducible and accurate. This can be due to that ISP in one DNA structure can ensure the completely same modification condition and an equal stoichiometric ratio between sP1 and sP2, and furthermore the cross interference between sP1 and sP2 can be successfully prevented by regulating the complementary position of sP1 and sP2. The ISP-based assay system would be a great progress for the dual-analyte detection. Combining with gold nanoparticles (AuNPs) signal amplification, the ISP/AuNPs-based aptasensor for the sensitive dual-analyte detection was explored. Based on DNA structural switching induced by targets binding to aptamer, the simultaneous dual-analyte detection was simply achieved by monitoring the electrochemical responses of methylene blue (MB) and ferrocene (Fc) This proposed detection system possesses such advantages as simplicity in design, easy operation, good reproducibility and accuracy, high sensitivity and selectivity, which indicates the excellent application of this aptasensor in the field of clinical diagnosis or other molecular sensors. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiband tissue classification for ultrasonic transmission tomography using spectral profile detection

NASA Astrophysics Data System (ADS)

Jeong, Jeong-Won; Kim, Tae-Seong; Shin, Dae-Chul; Do, Synho; Marmarelis, Vasilis Z.

2004-04-01

Recently it was shown that soft tissue can be differentiated with spectral unmixing and detection methods that utilize multi-band information obtained from a High-Resolution Ultrasonic Transmission Tomography (HUTT) system. In this study, we focus on tissue differentiation using the spectral target detection method based on Constrained Energy Minimization (CEM). We have developed a new tissue differentiation method called "CEM filter bank". Statistical inference on the output of each CEM filter of a filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We validate this method through 3-D inter/intra-phantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation in multiple tomographic slices. Also spectral coherence between target and object profiles of an identical tissue at different slices and phantoms is evaluated by conventional cross-correlation analysis. The performance of the proposed classifier is assessed using Receiver Operating Characteristic (ROC) analysis. Finally we apply our method to classify tiny structures inside a beef kidney such as Styrofoam balls (~1mm), chicken tissue (~5mm), and vessel-duct structures.

TECHNIQUES FOR HIGH-CONTRAST IMAGING IN MULTI-STAR SYSTEMS. I. SUPER-NYQUIST WAVEFRONT CONTROL

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

Thomas, S.; Belikov, R.; Bendek, E.

2015-09-01

Direct imaging of extra-solar planets is now a reality with the deployment and commissioning of the first generation of specialized ground-based instruments (GPI, SPHERE, P1640, and SCExAO). These systems allow of planets 10{sup 7} times fainter than their host star. For space-based missions (EXCEDE, EXO-C, EXO-S, WFIRST), various teams have demonstrated laboratory contrasts reaching 10{sup −10} within a few diffraction limits from the star. However, all of these current and future systems are designed to detect faint planets around a single host star, while most non-M-dwarf stars such as Alpha Centauri belong to multi-star systems. Direct imaging around binaries/multiple systemsmore » at a level of contrast allowing detection of Earth-like planets is challenging because the region of interest is contaminated by the host star's companion in addition to the host itself. Generally, the light leakage is caused by both diffraction and aberrations in the system. Moreover, the region of interest usually falls outside the correcting zone of the deformable mirror (DM) with respect to the companion. Until now, it has been thought that removing the light of a companion star is too challenging, leading to the exclusion of many binary systems from target lists of direct imaging coronographic missions. In this paper, we will show new techniques for high-contrast imaging of planets around multi-star systems and detail the Super-Nyquist Wavefront Control (SNWC) method, which allows wavefront errors to be controlled beyond the nominal control region of the DM. Our simulations have demonstrated that, with SNWC, raw contrasts of at least 5 × 10{sup −9} in a 10% bandwidth are possible.« less

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-11-01

also produced a real-time implementation of the tracking and anomalous behavior detection system that runs on real- world data – either using real-time...surveillance and airborne IED detection . 15. SUBJECT TERMS Multi-hypothesis tracking , particle filters, anomalous behavior detection , Bayesian...analyst to support decision making with large data sets. A key feature of the real-time tracking and behavior detection system developed is that the

Design of mini-multi-gas monitoring system based on IR absorption

NASA Astrophysics Data System (ADS)

Tan, Qiu-lin; Zhang, Wen-dong; Xue, Chen-yang; Xiong, Ji-jun; Ma, You-chun; Wen, Fen

2008-07-01

In this paper, a novel non-dispersive infrared ray (IR) gas detection system is described. Conventional devices typically include several primary components: a broadband source (usually an incandescent filament), a rotating chopper shutter, a narrow-band filter, a sample tube and a detector. But we mainly use the mini-multi-channel detector, electrical modulation means and mini-gas-cell structure. To solve the problems of gas accidents in coal mines, and for family safety that results from using gas, this new IR detection system with integration, miniaturization and non-moving parts has been developed. It is based on the principle that certain gases absorb infrared radiation at specific (and often unique) wavelengths. The infrared detection optics principle used in developing this system is mainly analyzed. The idea of multi-gas detection is introduced and guided through the analysis of the single-gas detection. Through researching the design of cell structure, a cell with integration and miniaturization has been devised. By taking a single-chip microcomputer (SCM) as intelligence handling, the functional block diagram of a gas detection system is designed with the analyzing and devising of its hardware and software system. The way of data transmission on a controller area network (CAN) bus and wireless data transmission mode is explained. This system has reached the technology requirement of lower power consumption, mini-volume, wide measure range, and is able to realize multi-gas detection.

Simultaneous atmospheric nitrous oxide, methane and water vapor detection with a single continuous wave quantum cascade laser.

PubMed

Cao, Yingchun; Sanchez, Nancy P; Jiang, Wenzhe; Griffin, Robert J; Xie, Feng; Hughes, Lawrence C; Zah, Chung-en; Tittel, Frank K

2015-02-09

A continuous wave (CW) quantum cascade laser (QCL) based absorption sensor system was demonstrated and developed for simultaneous detection of atmospheric nitrous oxide (N(2)O), methane (CH(4)), and water vapor (H(2)O). A 7.73-µm CW QCL with its wavelength scanned over a spectral range of 1296.9-1297.6 cm(-1) was used to simultaneously target three neighboring strong absorption lines, N(2)O at 1297.05 cm(-1), CH(4) at 1297.486 cm(-1), and H(2)O at 1297.184 cm(-1). An astigmatic multipass Herriott cell with a 76-m path length was utilized for laser based gas absorption spectroscopy at an optimum pressure of 100 Torr. Wavelength modulation and second harmonic detection was employed for data processing. Minimum detection limits (MDLs) of 1.7 ppb for N(2)O, 8.5 ppb for CH(4), and 11 ppm for H(2)O were achieved with a 2-s integration time for individual gas detection. This single QCL based multi-gas detection system possesses applications in environmental monitoring and breath analysis.

TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

NASA Astrophysics Data System (ADS)

Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

2014-06-01

The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

Development and applicability of a ready-to-use PCR system for GMO screening.

PubMed

Rosa, Sabrina F; Gatto, Francesco; Angers-Loustau, Alexandre; Petrillo, Mauro; Kreysa, Joachim; Querci, Maddalena

2016-06-15

With the growing number of GMOs introduced to the market, testing laboratories have seen their workload increase significantly. Ready-to-use multi-target PCR-based detection systems, such as pre-spotted plates (PSP), reduce analysis time while increasing capacity. This paper describes the development and applicability to GMO testing of a screening strategy involving a PSP and its associated web-based Decision Support System. The screening PSP was developed to detect all GMOs authorized in the EU in one single PCR experiment, through the combination of 16 validated assays. The screening strategy was successfully challenged in a wide inter-laboratory study on real-life food/feed samples. The positive outcome of this study could result in the adoption of a PSP screening strategy across the EU; a step that would increase harmonization and quality of GMO testing in the EU. Furthermore, this system could represent a model for other official control areas where high-throughput DNA-based detection systems are needed. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Study on high accuracy detection of multi-component gas in oil-immerse power transformer].

PubMed

Fan, Jie; Chen, Xiao; Huang, Qi-Feng; Zhou, Yu; Chen, Gang

2013-12-01

In order to solve the problem of low accuracy and mutual interference in multi-component gas detection, a kind of multi-component gas detection network with high accuracy was designed. A semiconductor laser with narrow bandwidth was utilized as light source and a novel long-path gas cell was also used in this system. By taking the single sine signal to modulate the spectrum of laser and using space division multiplexing (SDM) and time division multiplexing (TDM) technique, the detection of multi-component gas was achieved. The experiments indicate that the linearity relevance coefficient is 0. 99 and the measurement relative error is less than 4%. The system dynamic response time is less than 15 s, by filling a volume of multi-component gas into the gas cell gradually. The system has advantages of high accuracy and quick response, which can be used in the fault gas on-line monitoring for power transformers in real time.

Multi-target-qubit unconventional geometric phase gate in a multi-cavity system

NASA Astrophysics Data System (ADS)

Liu, Tong; Cao, Xiao-Zhi; Su, Qi-Ping; Xiong, Shao-Jie; Yang, Chui-Ping

2016-02-01

Cavity-based large scale quantum information processing (QIP) may involve multiple cavities and require performing various quantum logic operations on qubits distributed in different cavities. Geometric-phase-based quantum computing has drawn much attention recently, which offers advantages against inaccuracies and local fluctuations. In addition, multiqubit gates are particularly appealing and play important roles in QIP. We here present a simple and efficient scheme for realizing a multi-target-qubit unconventional geometric phase gate in a multi-cavity system. This multiqubit phase gate has a common control qubit but different target qubits distributed in different cavities, which can be achieved using a single-step operation. The gate operation time is independent of the number of qubits and only two levels for each qubit are needed. This multiqubit gate is generic, e.g., by performing single-qubit operations, it can be converted into two types of significant multi-target-qubit phase gates useful in QIP. The proposal is quite general, which can be used to accomplish the same task for a general type of qubits such as atoms, NV centers, quantum dots, and superconducting qubits.

Multi-target-qubit unconventional geometric phase gate in a multi-cavity system.

PubMed

Liu, Tong; Cao, Xiao-Zhi; Su, Qi-Ping; Xiong, Shao-Jie; Yang, Chui-Ping

2016-02-22

Cavity-based large scale quantum information processing (QIP) may involve multiple cavities and require performing various quantum logic operations on qubits distributed in different cavities. Geometric-phase-based quantum computing has drawn much attention recently, which offers advantages against inaccuracies and local fluctuations. In addition, multiqubit gates are particularly appealing and play important roles in QIP. We here present a simple and efficient scheme for realizing a multi-target-qubit unconventional geometric phase gate in a multi-cavity system. This multiqubit phase gate has a common control qubit but different target qubits distributed in different cavities, which can be achieved using a single-step operation. The gate operation time is independent of the number of qubits and only two levels for each qubit are needed. This multiqubit gate is generic, e.g., by performing single-qubit operations, it can be converted into two types of significant multi-target-qubit phase gates useful in QIP. The proposal is quite general, which can be used to accomplish the same task for a general type of qubits such as atoms, NV centers, quantum dots, and superconducting qubits.

Ships and Maritime Targets Observation Campaigns Using Available C- and X-Band SAR Satellite

NASA Astrophysics Data System (ADS)

Velotto, Domenico; Bentes, Carlos; Lehner, Susanne

2015-04-01

Obviously, radar resolution and swath width are two very important factors when it comes to synthetic aperture radar (SAR) maritime targets detections. The dilemma of using single polarization SAR imagery with higher resolution and coverage or quad- (or dual- polarimetric) imagery with its richness of information, is still unsolved when it comes to this application.In the framework of ESA project MARISS and EU project DOLPHIN, in situ campaigns aimed at solving this dilemma have been carried out. Single and multi- polarimetric SAR data acquired by TerraSAR-X, RADARSAT-2 and COSMO-SkyMed have been acquired with close time gaps and partial coverage overlap. In this way several moving and non-moving maritime targets have been imaged with different polarization, geometry and working frequency. Available ground truth reports provided by Automatic Identification System (AIS) data, nautical chart and wind farm location are used to validate the different types of maritime targets.

Unlabeled multi tumor marker detection system based on bioinitiated light addressable potentiometric sensor.

PubMed

Jia, Yun-Fang; Gao, Chun-Ying; He, Jia; Feng, Dao-Fu; Xing, Ke-Li; Wu, Ming; Liu, Yang; Cai, Wen-Sheng; Feng, Xi-Zeng

2012-08-21

Multi biomarkers' assays are of great significance in clinical diagnosis. A label-free multi tumor markers' parallel detection system was proposed based on a light addressable potentiometric sensor (LAPS). Arrayed LAPS chips with basic structure of Si(3)N(4)-SiO(2)-Si were prepared on silicon wafers, and the label-free parallel detection system for this component was developed with user friendly controlling interfaces. Then the l-3,4-dihydroxyphenyl-alanine (L-Dopa) hydrochloric solution was used to initiate the surface of LAPS. The L-Dopa immobilization state was investigated by the theoretical calculation. L-Dopa initiated LAPS' chip was biofunctionalized respectively by the antigens and antibodies of four tumor markers, α-fetoprotein (AFP), carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9) and Ferritin. Then unlabeled antibodies and antigens of these four biomarkers were detected by the proposed detection systems. Furthermore physical and measuring principles in this system were described, and qualitative understanding for experimental data were given. The measured response ranges were compared with their clinical cutoff values, and sensitivities were calculated by OriginLab. The results indicate that this bioinitiated LAPS based label-free detection system may offer a new choice for the realization of unlabeled multi tumor markers' clinical assay.

Flat Surface Damage Detection System (FSDDS)

NASA Technical Reports Server (NTRS)

Williams, Martha; Lewis, Mark; Gibson, Tracy; Lane, John; Medelius, Pedro; Snyder, Sarah; Ciarlariello, Dan; Parks, Steve; Carrejo, Danny; Rojdev, Kristina

2013-01-01

The Flat Surface Damage Detection system (FSDDS} is a sensory system that is capable of detecting impact damages to surfaces utilizing a novel sensor system. This system will provide the ability to monitor the integrity of an inflatable habitat during in situ system health monitoring. The system consists of three main custom designed subsystems: the multi-layer sensing panel, the embedded monitoring system, and the graphical user interface (GUI). The GUI LABVIEW software uses a custom developed damage detection algorithm to determine the damage location based on the sequence of broken sensing lines. It estimates the damage size, the maximum depth, and plots the damage location on a graph. Successfully demonstrated as a stand alone technology during 2011 D-RATS. Software modification also allowed for communication with HDU avionics crew display which was demonstrated remotely (KSC to JSC} during 2012 integration testing. Integrated FSDDS system and stand alone multi-panel systems were demonstrated remotely and at JSC, Mission Operations Test using Space Network Research Federation (SNRF} network in 2012. FY13, FSDDS multi-panel integration with JSC and SNRF network Technology can allow for integration with other complementary damage detection systems.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

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.

Correcting Estimates of the Occurrence Rate of Earth-like Exoplanets for Stellar Multiplicity

NASA Astrophysics Data System (ADS)

Cantor, Elliot; Dressing, Courtney D.; Ciardi, David R.; Christiansen, Jessie

2018-06-01

One of the most prominent questions in the exoplanet field has been determining the true occurrence rate of potentially habitable Earth-like planets. NASA’s Kepler mission has been instrumental in answering this question by searching for transiting exoplanets, but follow-up observations of Kepler target stars are needed to determine whether or not the surveyed Kepler targets are in multi-star systems. While many researchers have searched for companions to Kepler planet host stars, few studies have investigated the larger target sample. Regardless of physical association, the presence of nearby stellar companions biases our measurements of a system’s planetary parameters and reduces our sensitivity to small planets. Assuming that all Kepler target stars are single (as is done in many occurrence rate calculations) would overestimate our search completeness and result in an underestimate of the frequency of potentially habitable Earth-like planets. We aim to correct for this bias by characterizing the set of targets for which Kepler could have detected Earth-like planets. We are using adaptive optics (AO) imaging to reveal potential stellar companions and near-infrared spectroscopy to refine stellar parameters for a subset of the Kepler targets that are most amenable to the detection of Earth-like planets. We will then derive correction factors to correct for the biases in the larger set of target stars and determine the true frequency of systems with Earth-like planets. Due to the prevalence of stellar multiples, we expect to calculate an occurrence rate for Earth-like exoplanets that is higher than current figures.

Global calibration of multi-cameras with non-overlapping fields of view based on photogrammetry and reconfigurable target

NASA Astrophysics Data System (ADS)

Xia, Renbo; Hu, Maobang; Zhao, Jibin; Chen, Songlin; Chen, Yueling

2018-06-01

Multi-camera vision systems are often needed to achieve large-scale and high-precision measurement because these systems have larger fields of view (FOV) than a single camera. Multiple cameras may have no or narrow overlapping FOVs in many applications, which pose a huge challenge to global calibration. This paper presents a global calibration method for multi-cameras without overlapping FOVs based on photogrammetry technology and a reconfigurable target. Firstly, two planar targets are fixed together and made into a long target according to the distance between the two cameras to be calibrated. The relative positions of the two planar targets can be obtained by photogrammetric methods and used as invariant constraints in global calibration. Then, the reprojection errors of target feature points in the two cameras’ coordinate systems are calculated at the same time and optimized by the Levenberg–Marquardt algorithm to find the optimal solution of the transformation matrix between the two cameras. Finally, all the camera coordinate systems are converted to the reference coordinate system in order to achieve global calibration. Experiments show that the proposed method has the advantages of high accuracy (the RMS error is 0.04 mm) and low cost and is especially suitable for on-site calibration.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Multi-targeted priming for genome-wide gene expression assays.

PubMed

Adomas, Aleksandra B; Lopez-Giraldez, Francesc; Clark, Travis A; Wang, Zheng; Townsend, Jeffrey P

2010-08-17

Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of Saccharomyces cerevisiae and of Neurospora crassa, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays. We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of Saccharomyces cerevisiae and Neurospora crassa while avoiding priming ribosomal RNA or transfer RNA. Examining the response of Saccharomyces cerevisiae to nitrogen deficiency and profiling Neurospora crassa early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression. Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and N. crassa early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and precise assay of the transcribed sequences within the genome.

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

NASA Astrophysics Data System (ADS)

Gómez A, Héctor F.; Martínez-Tomás, Rafael; Arias Tapia, Susana A.; Rincón Zamorano, Mariano

2014-04-01

Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

Multi-layer cube sampling for liver boundary detection in PET-CT images.

PubMed

Liu, Xinxin; Yang, Jian; Song, Shuang; Song, Hong; Ai, Danni; Zhu, Jianjun; Jiang, Yurong; Wang, Yongtian

2018-06-01

Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.

Detecting Water Bodies in LANDSAT8 Oli Image Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, W.; He, G.; Long, T.; Ni, Y.

2018-04-01

Water body identifying is critical to climate change, water resources, ecosystem service and hydrological cycle. Multi-layer perceptron(MLP) is the popular and classic method under deep learning framework to detect target and classify image. Therefore, this study adopts this method to identify the water body of Landsat8. To compare the performance of classification, the maximum likelihood and water index are employed for each study area. The classification results are evaluated from accuracy indices and local comparison. Evaluation result shows that multi-layer perceptron(MLP) can achieve better performance than the other two methods. Moreover, the thin water also can be clearly identified by the multi-layer perceptron. The proposed method has the application potential in mapping global scale surface water with multi-source medium-high resolution satellite data.

Cumulative detection probabilities and range accuracy of a pulsed Geiger-mode avalanche photodiode laser ranging system

NASA Astrophysics Data System (ADS)

Luo, Hanjun; Ouyang, Zhengbiao; Liu, Qiang; Chen, Zhiliang; Lu, Hualan

2017-10-01

Cumulative pulses detection with appropriate cumulative pulses number and threshold has the ability to improve the detection performance of the pulsed laser ranging system with GM-APD. In this paper, based on Poisson statistics and multi-pulses cumulative process, the cumulative detection probabilities and their influence factors are investigated. With the normalized probability distribution of each time bin, the theoretical model of the range accuracy and precision is established, and the factors limiting the range accuracy and precision are discussed. The results show that the cumulative pulses detection can produce higher target detection probability and lower false alarm probability. However, for a heavy noise level and extremely weak echo intensity, the false alarm suppression performance of the cumulative pulses detection deteriorates quickly. The range accuracy and precision is another important parameter evaluating the detection performance, the echo intensity and pulse width are main influence factors on the range accuracy and precision, and higher range accuracy and precision is acquired with stronger echo intensity and narrower echo pulse width, for 5-ns echo pulse width, when the echo intensity is larger than 10, the range accuracy and precision lower than 7.5 cm can be achieved.

Systematic understanding the mechanisms of vitiligo pathogenesis and its treatment by Qubaibabuqi formula.

PubMed

Pei, Tianli; Zheng, Chunli; Huang, Chao; Chen, Xuetong; Guo, Zihu; Fu, Yingxue; Liu, Jianling; Wang, Yonghua

2016-08-22

Vitiligo is a depigmentation disorder, which results in substantial cosmetic disfigurement and poses a detriment to patients' physical as well as mental. Now the molecular pathogenesis of vitiligo still remains unclear, which leads to a daunting challenge for vitiligo therapy in modern medicine. Herbal medicines, characterized by multi-compound and multi-target, have long been shown effective in treating vitiligo, but their molecular mechanisms of action also remain ambiguous. Here we proposed a systems pharmacology approach using a clinically effective herb formula as a tool to detect the molecular pathogenesis of vitiligo. This study provided an integrative analysis of active chemicals, drug targets and interacting pathways of the Uygur medicine Qubaibabuqi formula for curing Vitiligo. The results show that 56 active ingredients of Qubaibabuqi interacting with 83 therapeutic proteins were identified. And Qubaibabuqi probably participate in immunomodulation, neuromodulation and keratinocytes apoptosis inhibition in treatment of vitiligo by a synergistic/cooperative way. The drug-target network-based analysis and pathway-based analysis can provide a new approach for understanding the pathogenesis of vitiligo and uncovering the molecular mechanisms of Qubaibabuqi, which will also facilitate the application of traditional Chinese herbs in modern medicine. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease.

PubMed

Cheng, Bo; Liu, Mingxia; Shen, Dinggang; Li, Zuoyong; Zhang, Daoqiang

2017-04-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multi-domain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods.

The Effect of Sub-Aperture in DRIA Framework Applied on Multi-Aspect PolSAR Data

NASA Astrophysics Data System (ADS)

Xue, Feiteng; Yin, Qiang; Lin, Yun; Hong, Wen

2016-08-01

Multi-aspect SAR is a new remote sensing technology, achieves consecutive data in large look angle as platform moves. Multi- aspect observation brings higher resolution and SNR to SAR picture. Multi-aspect PolSAR data can increase the accuracy of target identify and classification because it contains the 3-D polarimetric scattering properties.DRIA(detecting-removing-incoherent-adding)framework is a multi-aspect PolSAR data processing method. In this method, the anisotropic and isotropic scattering is separated by maximum- likelihood ratio test. The anisotropic scattering is removed to gain a removal series. The isotropic scattering is incoherent added to gain a high resolution picture. The removal series describes the anisotropic scattering property and is used in features extraction and classification.This article focuses on the effect brought by difference of sub-aperture numbers in anisotropic scattering detection and removal. The more sub-apertures are, the less look angle is. Artificial target has anisotropic scattering because of Bragg resonances. The increase of sub-aperture number brings more accurate observation in azimuth though the quality of each single image may loss. The accuracy of classification in agricultural fields is affected by the anisotropic scattering brought by Bragg resonances. The size of the sub-aperture has a significant effect in the removal result of Bragg resonances.

A novel visual saliency detection method for infrared video sequences

NASA Astrophysics Data System (ADS)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

Infrared video applications such as target detection and recognition, moving target tracking, and so forth can benefit a lot from visual saliency detection, which is essentially a method to automatically localize the ;important; content in videos. In this paper, a novel visual saliency detection method for infrared video sequences is proposed. Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered. For spatial saliency, we adopt a mutual consistency-guided spatial cues combination-based method to capture the regions with obvious luminance contrast and contour features. For temporal saliency, a multi-frame symmetric difference approach is proposed to discriminate salient moving regions of interest from background motions. Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy. Besides, to highlight the spatiotemporal salient regions uniformly, a multi-scale fusion approach is embedded into the spatiotemporal saliency model. Finally, a Gestalt theory-inspired optimization algorithm is designed to further improve the reliability of the final saliency map. Experimental results demonstrate that our method outperforms many state-of-the-art saliency detection approaches for infrared videos under various backgrounds.

Comparative performance between compressed and uncompressed airborne imagery

NASA Astrophysics Data System (ADS)

Phan, Chung; Rupp, Ronald; Agarwal, Sanjeev; Trang, Anh; Nair, Sumesh

2008-04-01

The US Army's RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division is evaluating the compressibility of airborne multi-spectral imagery for mine and minefield detection application. Of particular interest is to assess the highest image data compression rate that can be afforded without the loss of image quality for war fighters in the loop and performance of near real time mine detection algorithm. The JPEG-2000 compression standard is used to perform data compression. Both lossless and lossy compressions are considered. A multi-spectral anomaly detector such as RX (Reed & Xiaoli), which is widely used as a core algorithm baseline in airborne mine and minefield detection on different mine types, minefields, and terrains to identify potential individual targets, is used to compare the mine detection performance. This paper presents the compression scheme and compares detection performance results between compressed and uncompressed imagery for various level of compressions. The compression efficiency is evaluated and its dependence upon different backgrounds and other factors are documented and presented using multi-spectral data.

Multi Ray Model for Near-Ground Millimeter Wave Radar

PubMed Central

Litvak, Boris; Pinhasi, Yosef

2017-01-01

A quasi-optical multi-ray model for a short-range millimeter wave radar is presented. The model considers multi-path effects emerging while multiple rays are scattered from the target and reflected to the radar receiver. Among the examined scenarios, the special case of grazing ground reflections is analyzed. Such a case becomes relevant when short range anti-collision radars are employed in vehicles. Such radars operate at millimeter wavelengths, and are aimed at the detection of targets located several tens of meters from the transmitter. Reflections from the road are expected to play a role in the received signal strength, together with the direct line-of-sight beams illuminated and scattered from the target. The model is demonstrated experimentally using radar operating in the W-band. Controlled measurements were done to distinguish between several scattering target features. The experimental setup was designed to imitate vehicle near-ground millimeter wave radars operating in vehicles. A comparison between analytical calculations and experimental results is made and discussed. PMID:28867776

Virtual target tracking (VTT) as applied to mobile satellite communication networks

NASA Astrophysics Data System (ADS)

Amoozegar, Farid

1999-08-01

Traditionally, target tracking has been used for aerospace applications, such as, tracking highly maneuvering targets in a cluttered environment for missile-to-target intercept scenarios. Although the speed and maneuvering capability of current aerospace targets demand more efficient algorithms, many complex techniques have already been proposed in the literature, which primarily cover the defense applications of tracking methods. On the other hand, the rapid growth of Global Communication Systems, Global Information Systems (GIS), and Global Positioning Systems (GPS) is creating new and more diverse challenges for multi-target tracking applications. Mobile communication and computing can very well appreciate a huge market for Cellular Communication and Tracking Devices (CCTD), which will be tracking networked devices at the cellular level. The objective of this paper is to introduce a new concept, i.e., Virtual Target Tracking (VTT) for commercial applications of multi-target tracking algorithms and techniques as applied to mobile satellite communication networks. It would be discussed how Virtual Target Tracking would bring more diversity to target tracking research.

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.

Fault recovery for real-time, multi-tasking computer system

NASA Technical Reports Server (NTRS)

Hess, Richard (Inventor); Kelly, Gerald B. (Inventor); Rogers, Randy (Inventor); Stange, Kent A. (Inventor)

2011-01-01

System and methods for providing a recoverable real time multi-tasking computer system are disclosed. In one embodiment, a system comprises a real time computing environment, wherein the real time computing environment is adapted to execute one or more applications and wherein each application is time and space partitioned. The system further comprises a fault detection system adapted to detect one or more faults affecting the real time computing environment and a fault recovery system, wherein upon the detection of a fault the fault recovery system is adapted to restore a backup set of state variables.

Multi-wavelength Spatial LED illumination based detector for in vitro detection of Botulinum Neurotoxin A Activity

PubMed Central

Sun, Steven; Francis, Jesse; Sapsford, Kim E.; Kostov, Yordan; Rasooly, Avraham

2010-01-01

A portable and rapid detection system for the activity analysis of Botulinum Neurotoxins (BoNT) is needed for food safety and bio-security applications. To improve BoNT activity detection, a previously designed portable charge-coupled device (CCD) based detector was modified and equipped with a higher intensity more versatile multi-wavelength spatial light-emitting diode (LED) illumination, a faster CCD detector and the capability to simultaneously detect 30 samples. A FITC/DABCYL Förster Resonance Energy Transfer (FRET)-labeled peptide substrate (SNAP-25), with BoNT-A target cleavage site sequence was used to measure BoNT-A light chain (LcA) activity through the FITC fluorescence increase that occurs upon peptide substrate cleavage. For fluorescence excitation, a multi-wavelength spatial LED illuminator was used and compared to our previous electroluminescent (EL) strips. The LED illuminator was equipped with blue, green, red and white LEDs, covering a spectrum of 450-680 nm (red 610-650 nm, green 492-550 nm, blue 450-495 nm, and white LED 440-680 nm). In terms of light intensity, the blue LED was found to be ~80 fold higher than the previously used blue EL strips. When measuring the activity of LcA the CCD detector limit of detection (LOD) was found to be 0.08 nM LcA for both the blue LED (2 s exposure) and the blue EL (which require ≥60 s exposure) while the limits of quantitation (LOQ) is about 1 nM. The LOD for white LED was higher at 1.4 nM while the white EL was not used for the assay due to a high variable background. Unlike the weaker intensity EL illumination the high intensity LED illumination enabled shorter exposure times and allowed multi-wavelength illumination without the need to physically change the excitation strip, thus making spectrum excitation of multiple fluorophores possible increasing the versatility of the detector platform for a variety of optical detection assays. PMID:20498728

Saliva surface-enhanced Raman spectroscopy for noninvasive optical detection of nasopharyngeal cancer

NASA Astrophysics Data System (ADS)

Lin, Xueliang; Ge, Xiaosong; Xu, Zhihong; Zheng, Zuci; Huang, Wei; Hong, Quanxing; Lin, Duo

2016-10-01

The early cancer detection is of great significance to increase the patient's survival rate and reduce the risk of cancer development. Surface enhanced Raman spectroscopy (SERS) technique, a rapid, convenient, nondestructive optical detection method, can provide a characteristic "fingerprint" information of target substances, even achieving single molecule detection. Its ultra-high detection sensitivity has made it become one of the most potential biochemical detection methods. Saliva, a multi-constituent oral fluid, contains the bio-markers which is capable of reflecting the systemic health condition of human, showing promising potential as an effect medium for disease monitoring. Compared with the serum samples, the collection and processing of saliva is safer, more convenient and noninvasive. Thus, saliva test is becoming the hotspot issues of the noninvasive cancer research field. This review highlights and analyzes current application progress within the field of SERS saliva test in cancer detection. Meanwhile, the primary research results of SERS saliva for the noninvasive differentiation of nasopharyngeal cancer, normal and rhinitis obtained by our group are shown.

Numerical analysis of wavefront measurement characteristics by using plenoptic camera

NASA Astrophysics Data System (ADS)

Lv, Yang; Ma, Haotong; Zhang, Xuanzhe; Ning, Yu; Xu, Xiaojun

2016-01-01

To take advantage of the large-diameter telescope for high-resolution imaging of extended targets, it is necessary to detect and compensate the wave-front aberrations induced by atmospheric turbulence. Data recorded by Plenoptic cameras can be used to extract the wave-front phases associated to the atmospheric turbulence in an astronomical observation. In order to recover the wave-front phase tomographically, a method of completing the large Field Of View (FOV), multi-perspective wave-front detection simultaneously is urgently demanded, and it is plenoptic camera that possesses this unique advantage. Our paper focuses more on the capability of plenoptic camera to extract the wave-front from different perspectives simultaneously. In this paper, we built up the corresponding theoretical model and simulation system to discuss wave-front measurement characteristics utilizing plenoptic camera as wave-front sensor. And we evaluated the performance of plenoptic camera with different types of wave-front aberration corresponding to the occasions of applications. In the last, we performed the multi-perspective wave-front sensing employing plenoptic camera as wave-front sensor in the simulation. Our research of wave-front measurement characteristics employing plenoptic camera is helpful to select and design the parameters of a plenoptic camera, when utilizing which as multi-perspective and large FOV wave-front sensor, which is expected to solve the problem of large FOV wave-front detection, and can be used for AO in giant telescopes.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks.

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed. PMID:29186756

Radar-based collision avoidance for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Zhuang, Jia-yuan; Zhang, Lei; Zhao, Shi-qi; Cao, Jian; Wang, Bo; Sun, Han-bing

2016-12-01

Unmanned surface vehicles (USVs) have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into realtime marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle (V-obstacle) which adjusts the USV's heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.

Intravital imaging of mouse colonic adenoma using MMP-based molecular probes with multi-channel fluorescence endoscopy.

PubMed

Oh, Gyungseok; Yoo, Su Woong; Jung, Yebin; Ryu, Yeon-Mi; Park, Youngrong; Kim, Sang-Yeob; Kim, Ki Hean; Kim, Sungjee; Myung, Seung-Jae; Chung, Euiheon

2014-05-01

Intravital imaging has provided molecular, cellular and anatomical insight into the study of tumor. Early detection and treatment of gastrointestinal (GI) diseases can be enhanced with specific molecular markers and endoscopic imaging modalities. We present a wide-field multi-channel fluorescence endoscope to screen GI tract for colon cancer using multiple molecular probes targeting matrix metalloproteinases (MMP) conjugated with quantum dots (QD) in AOM/DSS mouse model. MMP9 and MMP14 antibody (Ab)-QD conjugates demonstrate specific binding to colonic adenoma. The average target-to-background (T/B) ratios are 2.10 ± 0.28 and 1.78 ± 0.18 for MMP14 Ab-QD and MMP9 Ab-QD, respectively. The overlap between the two molecular probes is 67.7 ± 8.4%. The presence of false negative indicates that even more number of targeting could increase the sensitivity of overall detection given heterogeneous molecular expression in tumors. Our approach indicates potential for the screening of small or flat lesions that are precancerous.

An overload behavior detection system for engineering transport vehicles based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Libo; Wu, Gang

2018-04-01

This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

Multi-voxel pattern analysis reveals increased memory targeting and reduced use of retrieved details during single-agenda source monitoring

PubMed Central

McDuff, Susan G. R.; Frankel, Hillary C.; Norman, Kenneth A.

2009-01-01

We used multi-voxel pattern analysis (MVPA) of fMRI data to gain insight into how subjects’ retrieval agendas influence source memory judgments (was item X studied using source Y?). In Experiment 1, we used a single-agenda test where subjects judged whether items were studied with the targeted source or not. In Experiment 2, we used a multi-agenda test where subjects judged whether items were studied using the targeted source, studied using a different source, or nonstudied. To evaluate the differences between single- and multi-agenda source monitoring, we trained a classifier to detect source-specific fMRI activity at study, and then we applied the classifier to data from the test phase. We focused on trials where the targeted source and the actual source differed, so we could use MVPA to track neural activity associated with both the targeted source and the actual source. Our results indicate that single-agenda monitoring was associated with increased focus on the targeted source (as evidenced by increased targeted-source activity, relative to baseline) and reduced use of information relating to the actual, non-target source. In the multi-agenda experiment, high-levels of actual-source activity were associated with increased correct rejections, suggesting that subjects were using recollection of actual-source information to avoid source memory errors. In the single-agenda experiment, there were comparable levels of actual-source activity (suggesting that recollection was taking place), but the relationship between actual-source activity and behavior was absent (suggesting that subjects were failing to make proper use of this information). PMID:19144851

High-resolution 3D laser imaging based on tunable fiber array link

NASA Astrophysics Data System (ADS)

Zhao, Sisi; Ruan, Ningjuan; Yang, Song

2017-10-01

Airborne photoelectric reconnaissance system with the bore sight down to the ground is an important battlefield situational awareness system, which can be used for reconnaissance and surveillance of complex ground scene. Airborne 3D imaging Lidar system is recognized as the most potential candidates for target detection under the complex background, and is progressing in the directions of high resolution, long distance detection, high sensitivity, low power consumption, high reliability, eye safe and multi-functional. However, the traditional 3D laser imaging system has the disadvantages of lower imaging resolutions because of the small size of the existing detector, and large volume. This paper proposes a high resolution laser 3D imaging technology based on the tunable optical fiber array link. The echo signal is modulated by a tunable optical fiber array link and then transmitted to the focal plane detector. The detector converts the optical signal into electrical signals which is given to the computer. Then, the computer accomplishes the signal calculation and image restoration based on modulation information, and then reconstructs the target image. This paper establishes the mathematical model of tunable optical fiber array signal receiving link, and proposes the simulation and analysis of the affect factors on high density multidimensional point cloud reconstruction.

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.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer’s Disease

PubMed Central

Cheng, Bo; Liu, Mingxia; Li, Zuoyong

2017-01-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer’s Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multidomain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods. PMID:27928657

Generic Sensor Modeling Using Pulse Method

NASA Technical Reports Server (NTRS)

Helder, Dennis L.; Choi, Taeyoung

2005-01-01

Recent development of high spatial resolution satellites such as IKONOS, Quickbird and Orbview enable observation of the Earth's surface with sub-meter resolution. Compared to the 30 meter resolution of Landsat 5 TM, the amount of information in the output image was dramatically increased. In this era of high spatial resolution, the estimation of spatial quality of images is gaining attention. Historically, the Modulation Transfer Function (MTF) concept has been used to estimate an imaging system's spatial quality. Sometimes classified by target shapes, various methods were developed in laboratory environment utilizing sinusoidal inputs, periodic bar patterns and narrow slits. On-orbit sensor MTF estimation was performed on 30-meter GSD Landsat4 Thematic Mapper (TM) data from the bridge pulse target as a pulse input . Because of a high resolution sensor s small Ground Sampling Distance (GSD), reasonably sized man-made edge, pulse, and impulse targets can be deployed on a uniform grassy area with accurate control of ground targets using tarps and convex mirrors. All the previous work cited calculated MTF without testing the MTF estimator's performance. In previous report, a numerical generic sensor model had been developed to simulate and improve the performance of on-orbit MTF estimating techniques. Results from the previous sensor modeling report that have been incorporated into standard MTF estimation work include Fermi edge detection and the newly developed 4th order modified Savitzky-Golay (MSG) interpolation technique. Noise sensitivity had been studied by performing simulations on known noise sources and a sensor model. Extensive investigation was done to characterize multi-resolution ground noise. Finally, angle simulation was tested by using synthetic pulse targets with angles from 2 to 15 degrees, several brightness levels, and different noise levels from both ground targets and imaging system. As a continuing research activity using the developed sensor model, this report was dedicated to MTF estimation via pulse input method characterization using the Fermi edge detection and 4th order MSG interpolation method. The relationship between pulse width and MTF value at Nyquist was studied including error detection and correction schemes. Pulse target angle sensitivity was studied by using synthetic targets angled from 2 to 12 degrees. In this report, from the ground and system noise simulation, a minimum SNR value was suggested for a stable MTF value at Nyquist for the pulse method. Target width error detection and adjustment technique based on a smooth transition of MTF profile is presented, which is specifically applicable only to the pulse method with 3 pixel wide targets.

Research on infrared ship detection method in sea-sky background

NASA Astrophysics Data System (ADS)

Tang, Da; Sun, Gang; Wang, Ding-he; Niu, Zhao-dong; Chen, Zeng-ping

2013-09-01

An approach to infrared ship detection based on sea-sky-line(SSL) detection, ROI extraction and feature recognition is proposed in this paper. Firstly, considering that far ships are expected to be adjacent to the SSL, SSL is detected to find potential target areas. Radon transform is performed on gradient image to choose candidate SSLs, and detection result is given by fuzzy synthetic evaluation values. Secondly, in view of recognizable condition that there should be enough differences between target and background in infrared image, two gradient masks have been created and improved as practical guidelines in eliminating false alarm. Thirdly, extract ROI near the SSL by using multi-grade segmentation and fusion method after image sharpening, and unsuitable candidates are screened out according to the gradient masks and ROI shape. Finally, we segment the rest of ROIs by two-stage modified OTSU, and calculate target confidence as a standard measuring the facticity of target. Compared with other ship detection methods, proposed method is suitable for bipolar targets, which offers a good practicability and accuracy, and achieves a satisfying detection speed. Detection experiments with 200 thousand frames show that the proposed method is widely applicable, powerful in resistance to interferences and noises with a detection rate of above 95%, which satisfies the engineering needs commendably.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

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.

Fusion-based multi-target tracking and localization for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2008-04-01

In this paper, we have presented two approaches addressing visual target tracking and localization in complex urban environment. The two techniques presented in this paper are: fusion-based multi-target visual tracking, and multi-target localization via camera calibration. For multi-target tracking, the data fusion concepts of hypothesis generation/evaluation/selection, target-to-target registration, and association are employed. An association matrix is implemented using RGB histograms for associated tracking of multi-targets of interests. Motion segmentation of targets of interest (TOI) from the background was achieved by a Gaussian Mixture Model. Foreground segmentation, on other hand, was achieved by the Connected Components Analysis (CCA) technique. The tracking of individual targets was estimated by fusing two sources of information, the centroid with the spatial gating, and the RGB histogram association matrix. The localization problem is addressed through an effective camera calibration technique using edge modeling for grid mapping (EMGM). A two-stage image pixel to world coordinates mapping technique is introduced that performs coarse and fine location estimation of moving TOIs. In coarse estimation, an approximate neighborhood of the target position is estimated based on nearest 4-neighbor method, and in fine estimation, we use Euclidean interpolation to localize the position within the estimated four neighbors. Both techniques were tested and shown reliable results for tracking and localization of Targets of interests in complex urban environment.

Detection and quantification of explosives and CWAs using a handheld widely tunable quantum cascade laser

NASA Astrophysics Data System (ADS)

Deutsch, Erik R.; Haibach, Frederick G.; Mazurenko, Alexander

2012-06-01

The requirements for standoff detection of Explosives and CWA/TICs on surfaces in the battlefield are challenging because of the low detection limits. The variety of targets, backgrounds and interferences increase the challenges. Infrared absorption spectroscopy with traditional infrared detection technologies, incandescent sources that offer broad wavelength range but poor spectral intensity, are particularly challenged in standoff applications because most photons are lost to the target, background and the environment. Using a brighter source for active infrared detection e.g. a widely-tunable quantum cascade laser (QCL) source, provides sufficient spectral intensity to achieve the needed sensitivity and selectivity for explosives, CWAs, and TICs on surfaces. Specific detection of 1-10 μg/cm2 is achieved within seconds. CWAs, and TICs in vapor and aerosol form present a different challenge. Vapors and aerosols are present at low concentrations, so long pathlengths are required to achieve the desired sensitivity. The collimated output beam from the QCL simplifies multi-reflection cells for vapor detection while also enabling large standoff distances. Results obtained by the QCL system indicate that <1 ppm for vapors can be achieved with specificity in a measurement time of seconds, and the QCL system was successfully able to detect agents in the presence of interferents. QCLs provide additional capabilities for the dismounted warfighter. Given the relatively low power consumption, small package, and instant-on capability of the QCL, a handheld device can provide field teams with early detection of toxic agents and energetic materials in standoff, vapor, or aerosol form using a single technology and device which makes it attractive compared other technologies.

Using the Detectability Index to Predict P300 Speller Performance

PubMed Central

Mainsah, B.O.; Collins, L.M.; Throckmorton, C.S.

2017-01-01

Objective The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping algorithms and other stimulus paradigms is desirable. Approach We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian dynamic stopping (DS) algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance The proposed method could serve as a useful tool to initially asses BCI performance without extensive online testing, in order to estimate the amount of data required to achieve a desired accuracy level. PMID:27705956

Using the detectability index to predict P300 speller performance

NASA Astrophysics Data System (ADS)

Mainsah, B. O.; Collins, L. M.; Throckmorton, C. S.

2016-12-01

Objective. The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping (DS) algorithms and other stimulus paradigms is desirable. Approach. We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian DS algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results. Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance. The proposed method could serve as a useful tool to initially assess BCI performance without extensive online testing, in order to estimate the amount of data required to achieve a desired accuracy level.

Autonomous UAV-Based Mapping of Large-Scale Urban Firefights

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

Snarski, S; Scheibner, K F; Shaw, S

2006-03-09

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urbanmore » firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with no false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type.« less

Priming nanoparticle-guided diagnostics and therapeutics towards human organs-on-chips microphysiological system

NASA Astrophysics Data System (ADS)

Choi, Jin-Ha; Lee, Jaewon; Shin, Woojung; Choi, Jeong-Woo; Kim, Hyun Jung

2016-10-01

Nanotechnology and bioengineering have converged over the past decades, by which the application of multi-functional nanoparticles (NPs) has been emerged in clinical and biomedical fields. The NPs primed to detect disease-specific biomarkers or to deliver biopharmaceutical compounds have beena validated in conventional in vitro culture models including two dimensional (2D) cell cultures or 3D organoid models. However, a lack of experimental models that have strong human physiological relevance has hampered accurate validation of the safety and functionality of NPs. Alternatively, biomimetic human "Organs-on-Chips" microphysiological systems have recapitulated the mechanically dynamic 3D tissue interface of human organ microenvironment, in which the transport, cytotoxicity, biocompatibility, and therapeutic efficacy of NPs and their conjugates may be more accurately validated. Finally, integration of NP-guided diagnostic detection and targeted nanotherapeutics in conjunction with human organs-on-chips can provide a novel avenue to accelerate the NP-based drug development process as well as the rapid detection of cellular secretomes associated with pathophysiological processes.

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

Design and analysis of a multi-passband complex filter for the multiband cognitive radar system

NASA Astrophysics Data System (ADS)

Lee, Hua-Chin; Ting, Der-Hong; Tsao, Ya-Lan

2017-05-01

Multiband cognitive radar systems, operating in a variety of frequency bands and combining the different channels into a joint system, can provide significant flexibility and capability to detect and track hostile targets. This paper proposes a multi-passband complex filter (MPCF) architecture and the related circuit design for a multiband cognitive radar system. By operating under the 5.8GHz UNII band, the sensing part detects the current usage of frequency bands from 5.15GHz to 5.825GHz and provides the information of unused channels. The multiband cognitive radar system uses the whole unused channels and eliminates the used channels by using an on-chip MPCF in order to be coexistent with the Wi-Fi standard. The MPCF filters out the unwanted channels and leave the wanted channels. It dynamically changes the bandwidth of frequency from 20MHz to 80MHz using the 0.18μm CMOS technology. The MPCF is composed of the combination of 5th-order Chebyshev low-pass filters and high-pass filters, and the overall inband ripple of the MPCF is 1.2dB. The consuming current is 21.7mA at 1.8V power supply and the 20MHz bandwidth noise is 55.5nV. The total harmonic distortion (THD) is 45dB at 25MHz and the adjacent channel rejection is 24dB. The result of the MPCF guarantees the performance requirements of the multiband cognitive radar system.

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Multi-modal distraction: insights from children's limited attention.

PubMed

Matusz, Pawel J; Broadbent, Hannah; Ferrari, Jessica; Forrest, Benjamin; Merkley, Rebecca; Scerif, Gaia

2015-03-01

How does the multi-sensory nature of stimuli influence information processing? Cognitive systems with limited selective attention can elucidate these processes. Six-year-olds, 11-year-olds and 20-year-olds engaged in a visual search task that required them to detect a pre-defined coloured shape under conditions of low or high visual perceptual load. On each trial, a peripheral distractor that could be either compatible or incompatible with the current target colour was presented either visually, auditorily or audiovisually. Unlike unimodal distractors, audiovisual distractors elicited reliable compatibility effects across the two levels of load in adults and in the older children, but high visual load significantly reduced distraction for all children, especially the youngest participants. This study provides the first demonstration that multi-sensory distraction has powerful effects on selective attention: Adults and older children alike allocate attention to potentially relevant information across multiple senses. However, poorer attentional resources can, paradoxically, shield the youngest children from the deleterious effects of multi-sensory distraction. Furthermore, we highlight how developmental research can enrich the understanding of distinct mechanisms controlling adult selective attention in multi-sensory environments. Copyright © 2014 Elsevier B.V. All rights reserved.

Metrology Camera System Using Two-Color Interferometry

NASA Technical Reports Server (NTRS)

Dubovitsky, Serge; Liebe, Carl Christian; Peters, Robert; Lay, Oliver

2007-01-01

A metrology system that contains no moving parts simultaneously measures the bearings and ranges of multiple reflective targets in its vicinity, enabling determination of the three-dimensional (3D) positions of the targets with submillimeter accuracy. The system combines a direction-measuring metrology camera and an interferometric range-finding subsystem. Because the system is based partly on a prior instrument denoted the Modulation Sideband Technology for Absolute Ranging (MSTAR) sensor and because of its 3D capability, the system is denoted the MSTAR3D. Developed for use in measuring the shape (for the purpose of compensating for distortion) of large structures like radar antennas, it can also be used to measure positions of multiple targets in the course of conventional terrestrial surveying. A diagram of the system is shown in the figure. One of the targets is a reference target having a known, constant distance with respect to the system. The system comprises a laser for generating local and target beams at a carrier frequency; a frequency shifting unit to introduce a frequency shift offset between the target and local beams; a pair of high-speed modulators that apply modulation to the carrier frequency in the local and target beams to produce a series of modulation sidebands, the highspeed modulators having modulation frequencies of FL and FM; a target beam launcher that illuminates the targets with the target beam; optics and a multipixel photodetector; a local beam launcher that launches the local beam towards the multi-pixel photodetector; a mirror for projecting to the optics a portion of the target beam reflected from the targets, the optics being configured to focus the portion of the target beam at the multi-pixel photodetector; and a signal-processing unit connected to the photodetector. The portion of the target beam reflected from the targets produces spots on the multi-pixel photodetector corresponding to the targets, respectively, and the signal-processing unit centroids the spots to determine bearings of the targets, respectively. As the spots oscillate in intensity because they are mixed with the local laser beam that is flood illuminating the focal plane, the phase of oscillation of each spot is measured, the phase of sidebands in the oscillation of each spot being proportional to a distance to the corresponding target relative to the reference target A.

Design of optical axis jitter control system for multi beam lasers based on FPGA

NASA Astrophysics Data System (ADS)

Ou, Long; Li, Guohui; Xie, Chuanlin; Zhou, Zhiqiang

2018-02-01

A design of optical axis closed-loop control system for multi beam lasers coherent combining based on FPGA was introduced. The system uses piezoelectric ceramics Fast Steering Mirrors (FSM) as actuator, the Fairfield spot detection of multi beam lasers by the high speed CMOS camera for optical detecting, a control system based on FPGA for real-time optical axis jitter suppression. The algorithm for optical axis centroid detecting and PID of anti-Integral saturation were realized by FPGA. Optimize the structure of logic circuit by reuse resource and pipeline, as a result of reducing logic resource but reduced the delay time, and the closed-loop bandwidth increases to 100Hz. The jitter of laser less than 40Hz was reduced 40dB. The cost of the system is low but it works stably.

Under-sampling in a Multiple-Channel Laser Vibrometry System

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

Corey, Jordan

2007-03-01

Laser vibrometry is a technique used to detect vibrations on objects using the interference of coherent light with itself. Most vibrometry systems process only one target location at a time, but processing multiple locations simultaneously provides improved detection capabilities. Traditional laser vibrometry systems employ oversampling to sample the incoming modulated-light signal, however as the number of channels increases in these systems, certain issues arise such a higher computational cost, excessive heat, increased power requirements, and increased component cost. This thesis describes a novel approach to laser vibrometry that utilizes undersampling to control the undesirable issues associated with over-sampled systems. Undersamplingmore » allows for significantly less samples to represent the modulated-light signals, which offers several advantages in the overall system design. These advantages include an improvement in thermal efficiency, lower processing requirements, and a higher immunity to the relative intensity noise inherent in laser vibrometry applications. A unique feature of this implementation is the use of a parallel architecture to increase the overall system throughput. This parallelism is realized using a hierarchical multi-channel architecture based on off-the-shelf programmable logic devices (PLDs).« less

35-GHz radar sensor for automotive collision avoidance

NASA Astrophysics Data System (ADS)

Zhang, Jun

1999-07-01

This paper describes the development of a radar sensor system used for automotive collision avoidance. Because the heavy truck may have great larger radar cross section than a motorcyclist has, the radar receiver may have a large dynamic range. And multi-targets at different speed may confuse the echo spectrum causing the ambiguity between range and speed of target. To get more information about target and background and to adapt to the large dynamic range and multi-targets, a frequency modulated and pseudo- random binary sequences phase modulated continuous wave radar system is described. The analysis of this double- modulation system is given. A high-speed signal processing and data processing component are used to process and combine the data and information from echo at different direction and at every moment.

A non-targeted UHPLC-UV methid with classical and multi-variate data analysis to detect adulteration of skim milk powder with foreign proteins

USDA-ARS?s Scientific Manuscript database

Ultra-High performance liquid chromatography (UHPLC) with single wavelength (215 nm) detection was used to obtain chromatographic profiles of authentic skim milk powder (SMP) and synthetic mixtures of SMP with variable amounts of soy (SPI), pea (PPI), brown rice (BRP), and hydrolyzed wheat protein (...

A Method of Character Detection and Segmentation for Highway Guide Signs

NASA Astrophysics Data System (ADS)

Xu, Jiawei; Zhang, Chongyang

2018-01-01

In this paper, a method of character detection and segmentation for highway signs in China is proposed. It consists of four steps. Firstly, the highway sign area is detectedby colour and geometric features, andthe possible character region is obtained by multi-level projection strategy. Secondly, pseudo target character region is removed by local binary patterns (LBP) feature. Thirdly, convolutional neural network (CNN)is used to classify target regions. Finally, adaptive projection strategies are used to segment characters strings. Experimental results indicate that the proposed method achieves new state-of-the-art results.

Fly eye radar or micro-radar sensor technology

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo; Asmolova, Olga

2014-05-01

To compensate for its eye's inability to point its eye at a target, the fly's eye consists of multiple angularly spaced sensors giving the fly the wide-area visual coverage it needs to detect and avoid the threats around him. Based on a similar concept a revolutionary new micro-radar sensor technology is proposed for detecting and tracking ground and/or airborne low profile low altitude targets in harsh urban environments. Distributed along a border or around a protected object (military facility and buildings, camp, stadium) small size, low power unattended radar sensors can be used for target detection and tracking, threat warning, pre-shot sniper protection and provides effective support for homeland security. In addition it can provide 3D recognition and targets classification due to its use of five orders more pulses than any scanning radar to each space point, by using few points of view, diversity signals and intelligent processing. The application of an array of directional antennas eliminates the need for a mechanical scanning antenna or phase processor. It radically decreases radar size and increases bearing accuracy several folds. The proposed micro-radar sensors can be easy connected to one or several operators by point-to-point invisible protected communication. The directional antennas have higher gain, can be multi-frequency and connected to a multi-functional network. Fly eye micro-radars are inexpensive, can be expendable and will reduce cost of defense.

Modified SPC for short run test and measurement process in multi-stations

NASA Astrophysics Data System (ADS)

Koh, C. K.; Chin, J. F.; Kamaruddin, S.

2018-03-01

Due to short production runs and measurement error inherent in electronic test and measurement (T&M) processes, continuous quality monitoring through real-time statistical process control (SPC) is challenging. Industry practice allows the installation of guard band using measurement uncertainty to reduce the width of acceptance limit, as an indirect way to compensate the measurement errors. This paper presents a new SPC model combining modified guard band and control charts (\\bar{\\text{Z}} chart and W chart) for short runs in T&M process in multi-stations. The proposed model standardizes the observed value with measurement target (T) and rationed measurement uncertainty (U). S-factor (S f) is introduced to the control limits to improve the sensitivity in detecting small shifts. The model was embedded in automated quality control system and verified with a case study in real industry.

Multi-color IR sensors based on QWIP technology for security and surveillance applications

NASA Astrophysics Data System (ADS)

Sundaram, Mani; Reisinger, Axel; Dennis, Richard; Patnaude, Kelly; Burrows, Douglas; Cook, Robert; Bundas, Jason

2006-05-01

Room-temperature targets are detected at the furthest distance by imaging them in the long wavelength (LW: 8-12 μm) infrared spectral band where they glow brightest. Focal plane arrays (FPAs) based on quantum well infrared photodetectors (QWIPs) have sensitivity, noise, and cost metrics that have enabled them to become the best commercial solution for certain security and surveillance applications. Recently, QWIP technology has advanced to provide pixelregistered dual-band imaging in both the midwave (MW: 3-5 μm) and longwave infrared spectral bands in a single chip. This elegant technology affords a degree of target discrimination as well as the ability to maximize detection range for hot targets (e.g. missile plumes) by imaging in the midwave and for room-temperature targets (e.g. humans, trucks) by imaging in the longwave with one simple camera. Detection-range calculations are illustrated and FPA performance is presented.

Countering MANPADS: study of new concepts and applications: part two

NASA Astrophysics Data System (ADS)

Maltese, Dominique; Vergnolle, Jean-François; Aragones, Julien; Renaudat, Mathieu

2007-04-01

The latest events of ground-to-air Man Portable Air Defense (MANPAD) attacks against aircraft have revealed a new threat both for military and civilian aircraft. Consequently, the implementation of protecting systems (i.e. Directed Infra Red Counter Measure - DIRCM) in order to face IR guided missiles turns out to be now inevitable. In a near future, aircraft will have to possess detection, tracking, identification, targeting and jamming capabilities to face MANPAD threats. Besides, Multiple Missiles attacks become more and more current scenarios to deal with. In this paper, a practical example of DIRCM systems under study at SAGEM DEFENSE & SECURITY Company is presented. The article is the continuation of a previous SPIE one. Self-protection solutions include built-in and automatic locking-on, tracking, identification and laser jamming capabilities, including defeat assessment. Target Designations are provided by a Missile Warning System. Targets scenarios including multiple threats are considered to design systems architectures. In a first step, the article reminds the context, current and future threats (IR seekers of different generations...), and scenarios for system definition. Then, it focuses on potential self-protection systems under study at SAGEM DEFENSE & SECURITY Company. Different strategies including target identification, multi band laser and active imagery have been previously studied in order to design DIRCM System solutions. Thus, results of self-protection scenarios are provided for different MANPAD scenarios to highlight key problems to solve. Data have been obtained from simulation software modeling full DIRCM systems architectures on technical and operational scenarios (parametric studies).

Detection and Identification of Mars Analogue Volcano — Ice Interaction Environments

NASA Astrophysics Data System (ADS)

Cousins, C. R.; Crawford, I.; Gunn, M.; Harris, J. K.; Steele, A.

2012-03-01

Volcano-ice interaction produces many environments available to microbial colonisation. Similar processes are likely to have occurred on Mars, and are prime exobiology targets. Multi-instrument analyses of volcano-ice deposits are presented.

Establishment of a universal and rational gene detection strategy through three-way junction-based remote transduction.

PubMed

Tang, Yidan; Lu, Baiyang; Zhu, Zhentong; Li, Bingling

2018-01-21

The polymerase chain reaction and many isothermal amplifications are able to achieve super gene amplification. Unfortunately, most commonly-used transduction methods, such as dye staining and Taqman-like probing, still suffer from shortcomings including false signals or difficult probe design, or are incompatible with multi-analysis. Here a universal and rational gene detection strategy has been established by translating isothermal amplicons to enzyme-free strand displacement circuits via three-way junction-based remote transduction. An assistant transduction probe was imported to form a partial hybrid with the target single-stranded nucleic acid. After systematic optimization the hybrid could serve as an associative trigger to activate a downstream circuit detector via a strand displacement reaction across the three-way junction. By doing so, the detection selectivity can be double-guaranteed through both amplicon-transducer recognition and the amplicon-circuit reaction. A well-optimized circuit can be immediately applied to a new target detection through simply displacing only 10-12 nt on only one component, according to the target. More importantly, this property for the first time enables multi-analysis and logic-analysis in a single reaction, sharing a single fluorescence reporter. In an applicable model, trace amounts of Cronobacter and Enterobacteria genes have been clearly distinguished from samples with no bacteria or one bacterium, with ultra-high sensitivity and selectivity.

Neuropharmacology beyond reductionism - A likely prospect.

PubMed

Margineanu, Doru Georg

2016-03-01

Neuropharmacology had several major past successes, but the last few decades did not witness any leap forward in the drug treatment of brain disorders. Moreover, current drugs used in neurology and psychiatry alleviate the symptoms, while hardly curing any cause of disease, basically because the etiology of most neuro-psychic syndromes is but poorly known. This review argues that this largely derives from the unbalanced prevalence in neuroscience of the analytic reductionist approach, focused on the cellular and molecular level, while the understanding of integrated brain activities remains flimsier. The decline of drug discovery output in the last decades, quite obvious in neuropharmacology, coincided with the advent of the single target-focused search of potent ligands selective for a well-defined protein, deemed critical in a given pathology. However, all the widespread neuro-psychic troubles are multi-mechanistic and polygenic, their complex etiology making unsuited the single-target drug discovery. An evolving approach, based on systems biology considers that a disease expresses a disturbance of the network of interactions underlying organismic functions, rather than alteration of single molecular components. Accordingly, systems pharmacology seeks to restore a disturbed network via multi-targeted drugs. This review notices that neuropharmacology in fact relies on drugs which are multi-target, this feature having occurred just because those drugs were selected by phenotypic screening in vivo, or emerged from serendipitous clinical observations. The novel systems pharmacology aims, however, to devise ab initio multi-target drugs that will appropriately act on multiple molecular entities. Though this is a task much more complex than the single-target strategy, major informatics resources and computational tools for the systemic approach of drug discovery are already set forth and their rapid progress forecasts promising outcomes for neuropharmacology. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Multi-Agent Cooperative Target Search

PubMed Central

Hu, Jinwen; Xie, Lihua; Xu, Jun; Xu, Zhao

2014-01-01

This paper addresses a vision-based cooperative search for multiple mobile ground targets by a group of unmanned aerial vehicles (UAVs) with limited sensing and communication capabilities. The airborne camera on each UAV has a limited field of view and its target discriminability varies as a function of altitude. First, by dividing the whole surveillance region into cells, a probability map can be formed for each UAV indicating the probability of target existence within each cell. Then, we propose a distributed probability map updating model which includes the fusion of measurement information, information sharing among neighboring agents, information decay and transmission due to environmental changes such as the target movement. Furthermore, we formulate the target search problem as a multi-agent cooperative coverage control problem by optimizing the collective coverage area and the detection performance. The proposed map updating model and the cooperative control scheme are distributed, i.e., assuming that each agent only communicates with its neighbors within its communication range. Finally, the effectiveness of the proposed algorithms is illustrated by simulation. PMID:24865884

Estimate of the influence of muzzle smoke on function range of infrared system

NASA Astrophysics Data System (ADS)

Luo, Yan-ling; Wang, Jun; Wu, Jiang-hui; Wu, Jun; Gao, Meng; Gao, Fei; Zhao, Yu-jie; Zhang, Lei

2013-09-01

Muzzle smoke produced by weapons shooting has important influence on infrared (IR) system while detecting targets. Based on the theoretical model of detecting spot targets and surface targets of IR system while there is muzzle smoke, the function range for detecting spot targets and surface targets are deduced separately according to the definition of noise equivalent temperature difference(NETD) and minimum resolution temperature difference(MRTD). Also parameters of muzzle smoke affecting function range of IR system are analyzed. Base on measured data of muzzle smoke for single shot, the function range of an IR system for detecting typical targets are calculated separately while there is muzzle smoke and there is no muzzle smoke at 8-12 micron waveband. For our IR system function range has reduced by over 10% for detecting tank if muzzle smoke exists. The results will provide evidence for evaluating the influence of muzzle smoke on IR system and will help researchers to improve ammo craftwork.

An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

PubMed Central

Butun, Ismail; Ra, In-Ho; Sankar, Ravi

2015-01-01

In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

Method and apparatus for operating a powertrain system upon detecting a stuck-closed clutch

DOEpatents

Hansen, R. Anthony

2014-02-18

A powertrain system includes a multi-mode transmission having a plurality of torque machines. A method for controlling the powertrain system includes identifying all presently applied clutches including commanded applied clutches and the stuck-closed clutch upon detecting one of the torque-transfer clutches is in a stuck-closed condition. A closed-loop control system is employed to control operation of the multi-mode transmission accounting for all the presently applied clutches.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, G.P.; Skeate, M.F.

1996-10-15

An apparatus for multi-dimensional computation is disclosed which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination. 10 figs.

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.

Countering MANPADS: study of new concepts and applications

NASA Astrophysics Data System (ADS)

Maltese, Dominique; Robineau, Jacques; Audren, Jean-Thierry; Aragones, Julien; Sailliot, Christophe

2006-05-01

The latest events of ground-to-air Man Portable Air Defense (MANPAD) attacks against aircraft have revealed a new threat both for military and civilian aircraft. Consequently, the implementation of Protecting systems (i.e. Directed InfraRed Counter Measure - DIRCM) in order to face IR guided missiles turns out to be now inevitable. In a near future, aircraft will have to possess detection, tracking, targeting and jamming capabilities to face single and multiple MANPAD threats fired in short-range scenarios from various environments (urban sites, landscape...). In this paper, a practical example of a DIRCM system under study at SAGEM DEFENSE & SECURITY company is presented. The self-protection solution includes built-in and automatic locking-on, tracking, identification and laser jamming capabilities, including defeat assessment. Target Designations are provided by a Missile Warning System. Multiple Target scenarios have been considered to design the system architecture. The article deals with current and future threats (IR seekers of different generations...), scenarios and platforms for system definition. Plus, it stresses on self-protection solutions based on laser jamming capability. Different strategies including target identification, multi band laser, active imagery are described. The self-protection system under study at SAGEM DEFENSE & SECURITY company is also a part of this chapter. Eventually, results of self-protection scenarios are provided for different MANPAD scenarios. Data have been obtained from a simulation software. The results highlight how the system reacts to incoming IR-guided missiles in short time scenarios.

A Systems Biology-Based Investigation into the Pharmacological Mechanisms of Sheng-ma-bie-jia-tang Acting on Systemic Lupus Erythematosus by Multi-Level Data Integration.

PubMed

Huang, Lin; Lv, Qi; Liu, Fenfen; Shi, Tieliu; Wen, Chengping

2015-11-12

Sheng-ma-bie-jia-tang (SMBJT) is a Traditional Chinese Medicine (TCM) formula that is widely used for the treatment of Systemic Lupus Erythematosus (SLE) in China. However, molecular mechanism behind this formula remains unknown. Here, we systematically analyzed targets of the ingredients in SMBJT to evaluate its potential molecular mechanism. First, we collected 1,267 targets from our previously published database, the Traditional Chinese Medicine Integrated Database (TCMID). Next, we conducted gene ontology and pathway enrichment analyses for these targets and determined that they were enriched in metabolism (amino acids, fatty acids, etc.) and signaling pathways (chemokines, Toll-like receptors, adipocytokines, etc.). 96 targets, which are known SLE disease proteins, were identified as essential targets and the rest 1,171 targets were defined as common targets of this formula. The essential targets directly interacted with SLE disease proteins. Besides, some common targets also had essential connections to both key targets and SLE disease proteins in enriched signaling pathway, e.g. toll-like receptor signaling pathway. We also found distinct function of essential and common targets in immune system processes. This multi-level approach to deciphering the underlying mechanism of SMBJT treatment of SLE details a new perspective that will further our understanding of TCM formulas.

The evaluation of multi-structure, multi-atlas pelvic anatomy features in a prostate MR lymphography CAD system

NASA Astrophysics Data System (ADS)

Meijs, M.; Debats, O.; Huisman, H.

2015-03-01

In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.

ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

NASA Astrophysics Data System (ADS)

Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

2018-02-01

Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

Board of Regents of the Nevada System of Higher Education, on behalf of the University of Nevada, Reno

DOEpatents

Adams, Jesse D.; Sulchek, Todd A.; Feigin, Stuart C.

2017-07-11

A disclosed chemical detection system for detecting a target material, such as an explosive material, can include a cantilevered probe, a probe heater coupled to the cantilevered probe, and a piezoelectric element disposed on the cantilevered probe. The piezoelectric element can be configured as a detector and/or an actuator. Detection can include, for example, detecting a movement of the cantilevered probe or a property of the cantilevered probe. The movement or a change in the property of the cantilevered probe can occur, for example, by adsorption of the target material, desorption of the target material, reaction of the target material and/or phase change of the target material. Examples of detectable movements and properties include temperature shifts, impedance shifts, and resonant frequency shifts of the cantilevered probe. The overall chemical detection system can be incorporated, for example, into a handheld explosive material detection system.

SAR and LIDAR fusion: experiments and applications

NASA Astrophysics Data System (ADS)

Edwards, Matthew C.; Zaugg, Evan C.; Bradley, Joshua P.; Bowden, Ryan D.

2013-05-01

In recent years ARTEMIS, Inc. has developed a series of compact, versatile Synthetic Aperture Radar (SAR) systems which have been operated on a variety of small manned and unmanned aircraft. The multi-frequency-band SlimSAR has demonstrated a variety of capabilities including maritime and littoral target detection, ground moving target indication, polarimetry, interferometry, change detection, and foliage penetration. ARTEMIS also continues to build upon the radar's capabilities through fusion with other sensors, such as electro-optical and infrared camera gimbals and light detection and ranging (LIDAR) devices. In this paper we focus on experiments and applications employing SAR and LIDAR fusion. LIDAR is similar to radar in that it transmits a signal which, after being reflected or scattered by a target area, is recorded by the sensor. The differences are that a LIDAR uses a laser as a transmitter and optical sensors as a receiver, and the wavelengths used exhibit a very different scattering phenomenology than the microwaves used in radar, making SAR and LIDAR good complementary technologies. LIDAR is used in many applications including agriculture, archeology, geo-science, and surveying. Some typical data products include digital elevation maps of a target area and features and shapes extracted from the data. A set of experiments conducted to demonstrate the fusion of SAR and LIDAR data include a LIDAR DEM used in accurately processing the SAR data of a high relief area (mountainous, urban). Also, feature extraction is used in improving geolocation accuracy of the SAR and LIDAR data.

Multi-reverse flow injection analysis integrated with multi-optical sensor for simultaneous determination of Mn(II), Fe(II), Cu(II) and Fe(III) in natural waters.

PubMed

Youngvises, Napaporn; Suwannasaroj, Kittigan; Jakmunee, Jaroon; AlSuhaimi, Awadh

2017-05-01

Multi-reverse flow injection analysis (Mr-FIA) integrated with multi-optical sensor was developed and optimized for the simultaneous determination of multi ions; Mn(II), Fe(II), Cu(II) and Fe(III) in water samples. The sample/standard solutions were propelled making use of a four channels peristaltic pump whereas 4 colorimetric reagents specific for the metal ions were separately injected in sample streams using multi-syringe pump. The color zones that formed in the individual mixing coils were then streamed into multi-channels spectrometer, which comprised of four flows through cell and four pairs of light emitting diode and photodiode, whereby signals were measured concurrently. The linearity range (along with detection limit, µgL -1 ) was 0.050-3.0(16), 0.30-2.0 (11), 0.050-1.0(12) and 0.10-1.0(50)mgL -1 , for Mn(II), Fe(II), Cu(II) and Fe(III), respectively. In the interim, the correlation coefficients were 0.9924-0.9942. The percentages relative standard deviation was less than 3. The proposed system was applied successfully to determine targeted metal ions simultaneously in natural water with high sample throughput and low reagent consumption, thus it satisfies the criteria of Green Analytical Chemistry (GAC) and its goals. Copyright © 2016 Elsevier B.V. All rights reserved.

[A review of mixed gas detection system based on infrared spectroscopic technique].

PubMed

Dang, Jing-Min; Fu, Li; Yan, Zi-Hui; Zheng, Chuan-Tao; Chang, Yu-Chun; Chen, Chen; Wang, Yi-Din

2014-10-01

In order to provide the experiences and references to the researchers who are working on infrared (IR) mixed gas detection field. The proposed manuscript reviews two sections of the aforementioned field, including optical multiplexing structure and detection method. At present, the coherent light sources whose representative are quantum cascade laser (QCL) and inter-band cascade laser(ICL) become the mainstream light source in IR mixed gas detection, which replace the traditional non-coherent light source, such as IR radiation source and IR light emitting diode. In addition, the photon detector which has a super high detectivity and very short response time is gradually beyond thermal infrared detector, dominant in the field of infrared detector. The optical multiplexing structure is the key factor of IR mixed gas detection system, which consists of single light source multi-plexing detection structure and multi light source multiplexing detection structure. Particularly, single light source multiplexing detection structure is advantages of small volume and high integration, which make it a plausible candidate for the portable mixed gas detection system; Meanwhile, multi light source multiplexing detection structure is embodiment of time division multiplex, frequency division multiplexing and wavelength division multiplexing, and become the leading structure of the mixed gas detection system because of its wider spectral range, higher spectral resolution, etc. The detection method applied to IR mixed gas detection includes non-dispersive infrared (NDIR) spectroscopy, wavelength and frequency-modulation spectroscopy, cavity-enhanced spectroscopy and photoacoustic spectroscopy, etc. The IR mixed gas detection system designed by researchers after recognizing the whole sections of the proposed system, which play a significant role in industrial and agricultural production, environmental monitoring, and life science, etc.

Design Multi-Sides System Unmanned Surface Vehicle (USV) Rocket

NASA Astrophysics Data System (ADS)

Syam, Rafiudin; Sutresman, Onny; Mappaita, Abdullah; Amiruddin; Wiranata, Ardi

2018-02-01

This study aims to design and test USV multislide forms. This system is excellent for maneuvering on the x-y-z coordinates. The disadvantage of a single side USV is that it is very difficult to maneuver to achieve very dynamic targets. While for multi sides system easily maneuvered though x-y-z coordinates. In addition to security defense purposes, multi-side system is also good for maritime intelligence, surveillance. In this case, electric deducted fan with Multi-Side system so that the vehicle can still operate even in reverse condition. Multipleside USV experiments have done with good results. In a USV study designed to use two propulsions.

Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

NASA Astrophysics Data System (ADS)

Schultz, Gregory M.; Keranen, Joe; Miller, Jonathan S.; Shubitidze, Fridon

2014-06-01

The remediation of explosive remnants of war (ERW) and associated unexploded ordnance (UXO) has seen improvements through the injection of modern technological advances and streamlined standard operating procedures. However, reliable and cost-effective detection and geophysical mapping of sites contaminated with UXO such as cluster munitions, abandoned ordnance, and improvised explosive devices rely on the ability to discriminate hazardous items from metallic clutter. In addition to anthropogenic clutter, handheld and vehicle-based metal detector systems are plagued by natural geologic and environmental noise in many post conflict areas. We present new and advanced electromagnetic induction (EMI) technologies including man-portable and towed EMI arrays and associated data processing software. While these systems feature vastly different form factors and transmit-receive configurations, they all exhibit several fundamental traits that enable successful classification of EMI anomalies. Specifically, multidirectional sampling of scattered magnetic fields from targets and corresponding high volume of unique data provide rich information for extracting useful classification features for clutter rejection analysis. The quality of classification features depends largely on the extent to which the data resolve unique physics-based parameters. To date, most of the advanced sensors enable high quality inversion by producing data that are extremely rich in spatial content through multi-angle illumination and multi-point reception.

A Multi-Peer Assessment Platform for Programming Language Learning: Considering Group Non-Consensus and Personal Radicalness

ERIC Educational Resources Information Center

Wang, Yanqing; Liang, Yaowen; Liu, Luning; Liu, Ying

2016-01-01

Multi-peer assessment has often been used by teachers to reduce personal bias and make the assessment more reliable. This study reviews the design and development of multi-peer assessment systems that detect and solve two common issues in such systems: non-consensus among group members and personal radicalness in some assessments. A multi-peer…

Demonstration Report: Handheld UXO Discriminator, SERDP No. MR-1667

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

Gasperikova, E.

2010-09-01

In 2003, the Defense Science Board observed: 'The problem is that instruments that can detect the buried UXOs also detect numerous scrap metal objects and other artifacts, which leads to an enormous amount of expensive digging. Typically 100 holes may be dug before a real UXO is unearthed! The Task Force assessment is that much of this wasteful digging can be eliminated by the use of more advanced technology instruments that exploit modern digital processing and advanced multi-mode sensors to achieve an improved level of discrimination of scrap from UXOs.' In keeping with these remarks and with prior funding (UX-1225,more » MM-0437, and MM-0838), the LBNL group has successfully designed and built the cart-mounted Berkeley UXO Discriminator (BUD) and demonstrated its performance at various test sites (cf. Gasperikova et al., 2007, 2008, and 2009). Because hand-held systems have the advantage of being lightweight, compact, portable, and deployable under most site conditions, they are particularly useful in areas of dense vegetation or challenging terrain. In heavily wooded areas or areas with steep or uneven terrain, hand-held sensors may be the only suitable device for UXO detection and discrimination because it can be carried through spaces that the operator could walk through or at least approach. Furthermore, it is desirable to find and characterize a metallic object without the need to accurately locate the sensors at multiple positions around the target. The ideal system would thus locate and characterize the target from a single position of the sensor and indicate to the operator where to flag the target for subsequent study. Based on these considerations, we designed and built a sensor package in a shape of a 14-in (0.35 m) cube. This hand-held prototype incorporates the key features of the cart-mounted system - (a) three orthogonal transmitters and ten pairs of receivers, and (b) difference or gradient measurements that significantly reduce the ambient and motion noise, and greatly enhance the sensitivity to the gradients of the target. The system characterizes the target from a single position. Results from a local test site were in a good agreement with theoretical performance calculations of such a device. This survey was designed to demonstrate performance of the system under realistic survey conditions at the Aberdeen Proving Ground (APG) in Aberdeen, MD. The survey was preformed in an area with known items ('Calibration Grid'), and in a seeded blind test area (the 'Blind Test Grid'). The ground truth for the surveys conducted on the Blind Test Grid was withheld from the testers. Only the graded test scores based on target detection and target classification were provided. For more information, see http://aec.army.mil/usaec/technology/uxo01c03.html.« less

Dual quantum cascade laser-based sensor for simultaneous NO and NO2 detection using a wavelength modulation-division multiplexing technique

NASA Astrophysics Data System (ADS)

Yu, Yajun; Sanchez, Nancy P.; Yi, Fan; Zheng, Chuantao; Ye, Weilin; Wu, Hongpeng; Griffin, Robert J.; Tittel, Frank K.

2017-05-01

A sensor system capable of simultaneous measurements of NO and NO2 was developed using a wavelength modulation-division multiplexing (WMDM) scheme and multi-pass absorption spectroscopy. A continuous wave (CW), distributed-feedback (DFB) quantum cascade laser (QCL) and a CW external-cavity (EC) QCL were employed for targeting a NO absorption doublet at 1900.075 cm-1 and a NO2 absorption line at 1630.33 cm-1, respectively. Simultaneous detection was realized by modulating both QCLs independently at different frequencies and demodulating the detector signals with LabView-programmed lock-in amplifiers. The sensor operated at a reduced pressure of 40 Torr and a data sampling rate of 1 Hz. An Allan-Werle deviation analysis indicated that the minimum detection limits of NO and NO2 can reach sub-ppbv concentration levels with averaging times of 100 and 200 s, respectively.

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.

Development and Measurements of a Mid-Infrared Multi-Gas Sensor System for CO, CO₂ and CH₄ Detection.

PubMed

Dong, Ming; Zheng, Chuantao; Miao, Shuzhuo; Zhang, Yu; Du, Qiaoling; Wang, Yiding; Tittel, Frank K

2017-09-27

A multi-gas sensor system was developed that uses a single broadband light source and multiple carbon monoxide (CO), carbon dioxide (CO₂) and methane (CH₄) pyroelectric detectors by use of the time division multiplexing (TDM) technique. A stepper motor-based rotating system and a single-reflection spherical optical mirror were designed and adopted to realize and enhance multi-gas detection. Detailed measurements under static detection mode (without rotation) and dynamic mode (with rotation) were performed to study the performance of the sensor system for the three gas species. Effects of the motor rotating period on sensor performances were also investigated and a rotation speed of 0.4π rad/s was required to obtain a stable sensing performance, corresponding to a detection period of ~10 s to realize one round of detection. Based on an Allan deviation analysis, the 1 σ detection limits under static operation are 2.96, 4.54 and 2.84 parts per million in volume (ppmv) for CO, CO₂ and CH₄, respectively and the 1 σ detection limits under dynamic operations are 8.83, 8.69 and 10.29 ppmv for the three gas species, respectively. The reported sensor has potential applications in various fields requiring CO, CO₂ and CH₄ detection such as in coal mines.

Extending multi-tenant architectures: a database model for a multi-target support in SaaS applications

NASA Astrophysics Data System (ADS)

Rico, Antonio; Noguera, Manuel; Garrido, José Luis; Benghazi, Kawtar; Barjis, Joseph

2016-05-01

Multi-tenant architectures (MTAs) are considered a cornerstone in the success of Software as a Service as a new application distribution formula. Multi-tenancy allows multiple customers (i.e. tenants) to be consolidated into the same operational system. This way, tenants run and share the same application instance as well as costs, which are significantly reduced. Functional needs vary from one tenant to another; either companies from different sectors run different types of applications or, although deploying the same functionality, they do differ in the extent of their complexity. In any case, MTA leaves one major concern regarding the companies' data, their privacy and security, which requires special attention to the data layer. In this article, we propose an extended data model that enhances traditional MTAs in respect of this concern. This extension - called multi-target - allows MT applications to host, manage and serve multiple functionalities within the same multi-tenant (MT) environment. The practical deployment of this approach will allow SaaS vendors to target multiple markets or address different levels of functional complexity and yet commercialise just one single MT application. The applicability of the approach is demonstrated via a case study of a real multi-tenancy multi-target (MT2) implementation, called Globalgest.

Gold-manganese nanoparticles for targeted diagnostic and imaging

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

Murph, Simona Hunyadi

Imagine the possibility of non-invasive, non-radiation based Magnetic resonance imaging (MRI) in combating cardiac disease. Researchers at the Savannah River National Laboratory (SRNL) are developing a process that would use nanotechnology in a novel, targeted approach that would allow MRIs to be more descriptive and brighter, and to target specific organs. Researchers at SRNL have discovered a way to use multifunctional metallic gold-manganese nanoparticles to create a unique, targeted positive contrast agent. SRNL Senior Scientist Dr. Simona Hunyadi Murph says she first thought of using the nanoparticles for cardiac disease applications after learning that people who survive an infarct exhibitmore » up to 15 times higher rate of developing chronic heart failure, arrhythmias and/or sudden death compared to the general population. Without question, nanotechnology will revolutionize the future of technology. The development of functional nanomaterials with multi-detection modalities opens up new avenues for creating multi-purpose technologies for biomedical applications.« less

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

PubMed Central

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-01-01

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

PubMed

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-10-27

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

On deception detection in multi-agent systems and deception intent

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Li, Deqing; Yuan, Xiuqing

2008-04-01

Deception detection plays an important role in the military decision-making process, but detecting deception is a challenging task. The deception planning process involves a number of human factors. It is intent-driven where intentions are usually hidden or not easily observable. As a result, in order to detect deception, any adversary model must have the capability to capture the adversary's intent. This paper discusses deception detection in multi-agent systems and in adversary modeling. We examined psychological and cognitive science research on deception and implemented various theories of deception within our approach. First, in multi-agent expert systems, one detection method uses correlations between agents to predict reasonable opinions/responses of other agents (Santos & Johnson, 2004). We further explore this idea and present studies that show the impact of different factors on detection success rate. Second, from adversary modeling, our detection method focuses on inferring adversary intent. By combining deception "branches" with intent inference models, we can estimate an adversary's deceptive activities and at the same time enhance intent inference. Two major kinds of deceptions are developed in this approach in different fashions. Simulative deception attempts to find inconsistency in observables, while dissimulative deception emphasizes the inference of enemy intentions.

Nanoscaled aptasensors for multi-analyte sensing

PubMed Central

Saberian-Borujeni, Mehdi; Johari-Ahar, Mohammad; Hamzeiy, Hossein; Barar, Jaleh; Omidi, Yadollah

2014-01-01

Introduction: Nanoscaled aptamers (Aps), as short single-stranded DNA or RNA oligonucleotides, are able to bind to their specific targets with high affinity, upon which they are considered as powerful diagnostic and analytical sensing tools (the so-called "aptasensors"). Aptamers are selected from a random pool of oligonucleotides through a procedure known as "systematic evolution of ligands by exponential enrichment". Methods: In this work, the most recent studies in the field of aptasensors are reviewed and discussed with a main focus on the potential of aptasensors for the multianalyte detection(s). Results: Due to the specific folding capability of aptamers in the presence of analyte, aptasensors have substantially successfully been exploited for the detection of a wide range of small and large molecules (e.g., drugs and their metabolites, toxins, and associated biomarkers in various diseases) at very low concentrations in the biological fluids/samples even in presence of interfering species. Conclusion: Biological samples are generally considered as complexes in the real biological media. Hence, the development of aptasensors with capability to determine various targets simultaneously within a biological matrix seems to be our main challenge. To this end, integration of various key scientific dominions such as bioengineering and systems biology with biomedical researches are inevitable. PMID:25671177

FRIENDS OF HOT JUPITERS. II. NO CORRESPONDENCE BETWEEN HOT-JUPITER SPIN-ORBIT MISALIGNMENT AND THE INCIDENCE OF DIRECTLY IMAGED STELLAR COMPANIONS

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

Ngo, Henry; Knutson, Heather A.; Hinkley, Sasha

Multi-star systems are common, yet little is known about a stellar companion's influence on the formation and evolution of planetary systems. For instance, stellar companions may have facilitated the inward migration of hot Jupiters toward to their present day positions. Many observed short-period gas giant planets also have orbits that are misaligned with respect to their star's spin axis, which has also been attributed to the presence of a massive outer companion on a non-coplanar orbit. We present the results of a multi-band direct imaging survey using Keck NIRC2 to measure the fraction of short-period gas giant planets found inmore » multi-star systems. Over three years, we completed a survey of 50 targets ('Friends of Hot Jupiters') with 27 targets showing some signature of multi-body interaction (misaligned or eccentric orbits) and 23 targets in a control sample (well-aligned and circular orbits). We report the masses, projected separations, and confirmed common proper motion for the 19 stellar companions found around 17 stars. Correcting for survey incompleteness, we report companion fractions of 48% ± 9%, 47% ± 12%, and 51% ± 13% in our total, misaligned/eccentric, and control samples, respectively. This total stellar companion fraction is 2.8σ larger than the fraction of field stars with companions approximately 50-2000 AU. We observe no correlation between misaligned/eccentric hot Jupiter systems and the incidence of stellar companions. Combining this result with our previous radial velocity survey, we determine that 72% ± 16% of hot Jupiters are part of multi-planet and/or multi-star systems.« less

Multifunctional millimeter-wave radar system for helicopter safety

NASA Astrophysics Data System (ADS)

Goshi, Darren S.; Case, Timothy J.; McKitterick, John B.; Bui, Long Q.

2012-06-01

A multi-featured sensor solution has been developed that enhances the operational safety and functionality of small airborne platforms, representing an invaluable stride toward enabling higher-risk, tactical missions. This paper demonstrates results from a recently developed multi-functional sensor system that integrates a high performance millimeter-wave radar front end, an evidence grid-based integration processing scheme, and the incorporation into a 3D Synthetic Vision System (SVS) display. The front end architecture consists of a w-band real-beam scanning radar that generates a high resolution real-time radar map and operates with an adaptable antenna architecture currently configured with an interferometric capability for target height estimation. The raw sensor data is further processed within an evidence grid-based integration functionality that results in high-resolution maps in the region surrounding the platform. Lastly, the accumulated radar results are displayed in a fully rendered 3D SVS environment integrated with local database information to provide the best representation of the surrounding environment. The integrated system concept will be discussed and initial results from an experimental flight test of this developmental system will be presented. Specifically, the forward-looking operation of the system demonstrates the system's ability to produce high precision terrain mapping with obstacle detection and avoidance capability, showcasing the system's versatility in a true operational environment.

Development and test of photon counting lidar

NASA Astrophysics Data System (ADS)

Wang, Chun-hui; Wang, Ao-you; Tao, Yu-liang; Li, Xu; Peng, Huan; Meng, Pei-bei

2018-02-01

In order to satisfy the application requirements of spaceborne three dimensional imaging lidar , a prototype of nonscanning multi-channel lidar based on receiver field of view segmentation was designed and developed. High repetition frequency micro-pulse lasers, optics fiber array and Geiger-mode APD, combination with time-correlated single photon counting technology, were adopted to achieve multi-channel detection. Ranging experiments were carried out outdoors. In low echo photon condition, target photon counting showed time correlated and noise photon counting were random. Detection probability and range precision versus threshold were described and range precision increased from 0.44 to 0.11 when threshold increased from 4 to 8.

Active animal health surveillance in European Union Member States: gaps and opportunities.

PubMed

Bisdorff, B; Schauer, B; Taylor, N; Rodríguez-Prieto, V; Comin, A; Brouwer, A; Dórea, F; Drewe, J; Hoinville, L; Lindberg, A; Martinez Avilés, M; Martínez-López, B; Peyre, M; Pinto Ferreira, J; Rushton, J; VAN Schaik, G; Stärk, K D C; Staubach, C; Vicente-Rubiano, M; Witteveen, G; Pfeiffer, D; Häsler, B

2017-03-01

Animal health surveillance enables the detection and control of animal diseases including zoonoses. Under the EU-FP7 project RISKSUR, a survey was conducted in 11 EU Member States and Switzerland to describe active surveillance components in 2011 managed by the public or private sector and identify gaps and opportunities. Information was collected about hazard, target population, geographical focus, legal obligation, management, surveillance design, risk-based sampling, and multi-hazard surveillance. Two countries were excluded due to incompleteness of data. Most of the 664 components targeted cattle (26·7%), pigs (17·5%) or poultry (16·0%). The most common surveillance objectives were demonstrating freedom from disease (43·8%) and case detection (26·8%). Over half of components applied risk-based sampling (57·1%), but mainly focused on a single population stratum (targeted risk-based) rather than differentiating between risk levels of different strata (stratified risk-based). About a third of components were multi-hazard (37·3%). Both risk-based sampling and multi-hazard surveillance were used more frequently in privately funded components. The study identified several gaps (e.g. lack of systematic documentation, inconsistent application of terminology) and opportunities (e.g. stratified risk-based sampling). The greater flexibility provided by the new EU Animal Health Law means that systematic evaluation of surveillance alternatives will be required to optimize cost-effectiveness.

Multi-residue analysis of legacy POPs and emerging organic contaminants in Singapore's coastal waters using gas chromatography-triple quadrupole tandem mass spectrometry.

PubMed

Zhang, Hui; Bayen, Stéphane; Kelly, Barry C

2015-08-01

A gas chromatography-triple quadrupole mass spectrometry (GC-MS/MS) based method was developed for determination of 86 hydrophobic organic compounds in seawater. Solid-phase extraction (SPE) was employed for sequestration of target analytes in the dissolved phase. Ultrasound assisted extraction (UAE) and florisil chromatography were utilized for determination of concentrations in suspended sediments (particulate phase). The target compounds included multi-class hydrophobic contaminants with a wide range of physical-chemical properties. This list includes several polycyclic and nitro-aromatic musks, brominated and chlorinated flame retardants, methyl triclosan, chlorobenzenes, organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs). Spiked MilliQ water and seawater samples were used to evaluate the method performance. Analyte recoveries were generally good, with the exception of some of the more volatile target analytes (chlorobenzenes and bromobenzenes). The method is very sensitive, with method detection limits typically in the low parts per quadrillion (ppq) range. Analysis of 51 field-collected seawater samples (dissolved and particulate-bound phases) from four distinct coastal sites around Singapore showed trace detection of several polychlorinated biphenyl congeners and other legacy POPs, as well as several current-use emerging organic contaminants (EOCs). Polycyclic and nitro-aromatic musks, bromobenzenes, dechlorane plus isomers (syn-DP, anti-DP) and methyl triclosan were frequently detected at appreciable levels (2-20,000pgL(-1)). The observed concentrations of the monitored contaminants in Singapore's marine environment were generally comparable to previously reported levels in other coastal marine systems. To our knowledge, these are the first measurements of these emerging contaminants of concern in Singapore or Southeast Asia. The developed method may prove beneficial for future environmental monitoring of hydrophobic organic contaminants in marine environments. Further, the study provides novel information regarding several potentially hazardous contaminants of concern in Singapore's marine environment, which will aid future risk assessment initiatives. Copyright © 2015 Elsevier B.V. All rights reserved.

An immuno-biosensor system based on quartz crystal microbalance for avian influenza virus detection

NASA Astrophysics Data System (ADS)

Liu, Shengping; Chen, Guoming; Zhou, Qi; Wei, Yunlong

2007-12-01

For the quick detection of Avian Influenza Virus (AIV), a biosensor based on Quartz Crystal Microbalance (QCM) was fabricated according to the specific bonding principle between antibody and antigen. Staphylococcal Protein A (SPA) was extracted from Staphylococcus and purified. Then SPA was coated on the surface of QCM for immobilizing AIV monoclonal antibodies. The use of AIV monoclonal antibody could enhance the specificity of the immuno-biosensor. A multi-channel piezoelectricity detection system for the immuno-biosensor was developed. The system can work for the quick detection of AIV antigen in the case of the entirely aqueous status owe to one special oscillating circuit designed in this work. The optimum conditions of SPA coating and AIV monoclonal antibody immobilization were investigated utilizing the multi-channel detection system. The preliminary application of the immuno-biosensor system for detection of AIV was evaluated. Results indicate that the immuno-biosensor system can detect the AIV antigens with a linear range of 3-200ng/ml. The system can accomplish the detection of AIV antigens around 40 minutes.

SU-E-T-480: Radiobiological Dose Comparison of Single Fraction SRS, Multi-Fraction SRT and Multi-Stage SRS of Large Target Volumes Using the Linear-Quadratic Formula

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

Ding, C; Hrycushko, B; Jiang, S

2014-06-01

Purpose: To compare the radiobiological effect on large tumors and surrounding normal tissues from single fraction SRS, multi-fractionated SRT, and multi-staged SRS treatment. Methods: An anthropomorphic head phantom with a centrally located large volume target (18.2 cm{sup 3}) was scanned using a 16 slice large bore CT simulator. Scans were imported to the Multiplan treatment planning system where a total prescription dose of 20Gy was used for a single, three staged and three fractionated treatment. Cyber Knife treatment plans were inversely optimized for the target volume to achieve at least 95% coverage of the prescription dose. For the multistage plan,more » the target was segmented into three subtargets having similar volume and shape. Staged plans for individual subtargets were generated based on a planning technique where the beam MUs of the original plan on the total target volume are changed by weighting the MUs based on projected beam lengths within each subtarget. Dose matrices for each plan were export in DICOM format and used to calculate equivalent dose distributions in 2Gy fractions using an alpha beta ratio of 10 for the target and 3 for normal tissue. Results: Singe fraction SRS, multi-stage plan and multi-fractionated SRT plans had an average 2Gy dose equivalent to the target of 62.89Gy, 37.91Gy and 33.68Gy, respectively. The normal tissue within 12Gy physical dose region had an average 2Gy dose equivalent of 29.55Gy, 16.08Gy and 13.93Gy, respectively. Conclusion: The single fraction SRS plan had the largest predicted biological effect for the target and the surrounding normal tissue. The multi-stage treatment provided for a more potent biologically effect on target compared to the multi-fraction SRT treatments with less biological normal tissue than single-fraction SRS treatment.« less

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Multi-functional liposomes showing radiofrequency-triggered release and magnetic resonance imaging for tumor multi-mechanism therapy.

PubMed

Du, Bin; Han, Shuping; Li, Hongyan; Zhao, Feifei; Su, Xiangjie; Cao, Xiaohui; Zhang, Zhenzhong

2015-03-12

Recently, nanoplatforms with multiple functions, such as tumor-targeting drug carriers, MRI, optical imaging, thermal therapy etc., have become popular in the field of cancer research. The present study reports a novel multi-functional liposome for cancer theranostics. A dual targeted drug delivery with radiofrequency-triggered drug release and imaging based on the magnetic field influence was used advantageously for tumor multi-mechanism therapy. In this system, the surface of fullerene (C60) was decorated with iron oxide nanoparticles, and PEGylation formed a hybrid nanosystem (C60-Fe3O4-PEG2000). Thermosensitive liposomes (dipalmitoylphosphatidylcholine, DPPC) with DSPE-PEG2000-folate wrapped up the hybrid nanosystem and docetaxel (DTX), which were designed to combine features of biological and physical (magnetic) drug targeting for fullerene radiofrequency-triggered drug release. The magnetic liposomes not only served as powerful tumor diagnostic magnetic resonance imaging (MRI) contrast agents, but also as powerful agents for photothermal ablation of tumors. Furthermore, a remarkable thermal therapy combined chemotherapy multi-functional liposome nanoplatform converted radiofrequency energy into thermal energy to release drugs from thermosensitive liposomes, which was also observed during both in vitro and in vivo treatment. The multi-functional liposomes also could selectively kill cancer cells in highly localized regions via their excellent active tumor targeting and magnetic targeted abilities.

Symbolic Analysis of Concurrent Programs with Polymorphism

NASA Technical Reports Server (NTRS)

Rungta, Neha Shyam

2010-01-01

The current trend of multi-core and multi-processor computing is causing a paradigm shift from inherently sequential to highly concurrent and parallel applications. Certain thread interleavings, data input values, or combinations of both often cause errors in the system. Systematic verification techniques such as explicit state model checking and symbolic execution are extensively used to detect errors in such systems [7, 9]. Explicit state model checking enumerates possible thread schedules and input data values of a program in order to check for errors [3, 9]. To partially mitigate the state space explosion from data input values, symbolic execution techniques substitute data input values with symbolic values [5, 7, 6]. Explicit state model checking and symbolic execution techniques used in conjunction with exhaustive search techniques such as depth-first search are unable to detect errors in medium to large-sized concurrent programs because the number of behaviors caused by data and thread non-determinism is extremely large. We present an overview of abstraction-guided symbolic execution for concurrent programs that detects errors manifested by a combination of thread schedules and data values [8]. The technique generates a set of key program locations relevant in testing the reachability of the target locations. The symbolic execution is then guided along these locations in an attempt to generate a feasible execution path to the error state. This allows the execution to focus in parts of the behavior space more likely to contain an error.

Interference Information Based Power Control for Cognitive Radio with Multi-Hop Cooperative Sensing

NASA Astrophysics Data System (ADS)

Yu, Youngjin; Murata, Hidekazu; Yamamoto, Koji; Yoshida, Susumu

Reliable detection of other radio systems is crucial for systems that share the same frequency band. In wireless communication channels, there is uncertainty in the received signal level due to multipath fading and shadowing. Cooperative sensing techniques in which radio stations share their sensing information can improve the detection probability of other systems. In this paper, a new cooperative sensing scheme that reduces the false detection probability while maintaining the outage probability of other systems is investigated. In the proposed system, sensing information is collected using multi-hop transmission from all sensing stations that detect other systems, and transmission decisions are based on the received sensing information. The proposed system also controls the transmit power based on the received CINRs from the sensing stations. Simulation results reveal that the proposed system can reduce the outage probability of other systems, or improve its link success probability.

Autonomous UAV-based mapping of large-scale urban firefights

NASA Astrophysics Data System (ADS)

Snarski, Stephen; Scheibner, Karl; Shaw, Scott; Roberts, Randy; LaRow, Andy; Breitfeller, Eric; Lupo, Jasper; Nielson, Darron; Judge, Bill; Forren, Jim

2006-05-01

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urban firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with very low false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type. The combined results of the high-intensity firefight data collect and a detailed systems study demonstrate the readiness of the FightSight concept for full system development and integration.

The design of the JUNO veto system

NASA Astrophysics Data System (ADS)

Lu, H.; Baussan, E.; experiment, JUNO

2017-09-01

The Jiangmen Underground Neutrino Observatory (JUNO) is a multipurpose 20 kton liquid scintillator detector. The detector will be built in a 700 m deep underground laboratory, and its primary physics goal will be to determine the neutrino mass hierarchy. Due to the low background requirement of the experiment, a multi-veto system for cosmic muon detection and background reduction is designed. The volume outside the central detector is filled with pure water and equipped with 2000 MCP-PMTs (20 inches) to form a water Cherenkov detector for muon tagging. A Top Tracker system will be built by re-using the Target Tracker plastic scintillator modules of the OPERA experiment and will cover half of the top area. This will provide valuable information for cosmic muon induced 9Li/8He study.

Cantilevered probe detector with piezoelectric element

DOEpatents

Adams, Jesse D; Sulchek, Todd A; Feigin, Stuart C

2014-04-29

A disclosed chemical detection system for detecting a target material, such as an explosive material, can include a cantilevered probe, a probe heater coupled to the cantilevered probe, and a piezoelectric element disposed on the cantilevered probe. The piezoelectric element can be configured as a detector and/or an actuator. Detection can include, for example, detecting a movement of the cantilevered probe or a property of the cantilevered probe. The movement or a change in the property of the cantilevered probe can occur, for example, by adsorption of the target material, desorption of the target material, reaction of the target material and/or phase change of the target material. Examples of detectable movements and properties include temperature shifts, impedance shifts, and resonant frequency shifts of the cantilevered probe. The overall chemical detection system can be incorporated, for example, into a handheld explosive material detection system.

Cantilevered probe detector with piezoelectric element

DOEpatents

Adams, Jesse D; Sulchek, Todd A; Feigin, Stuart C

2013-04-30

A disclosed chemical detection system for detecting a target material, such as an explosive material, can include a cantilevered probe, a probe heater coupled to the cantilevered probe, and a piezoelectric element disposed on the cantilevered probe. The piezoelectric element can be configured as a detector and/or an actuator. Detection can include, for example, detecting a movement of the cantilevered probe or a property of the cantilevered probe. The movement or a change in the property of the cantilevered probe can occur, for example, by adsorption of the target material, desorption of the target material, reaction of the target material and/or phase change of the target material. Examples of detectable movements and properties include temperature shifts, impedance shifts, and resonant frequency shifts of the cantilevered probe. The overall chemical detection system can be incorporated, for example, into a handheld explosive material detection system.

Cantilevered probe detector with piezoelectric element

DOEpatents

Adams, Jesse D [Reno, NV; Sulchek, Todd A [Oakland, CA; Feigin, Stuart C [Reno, NV

2012-07-10

A disclosed chemical detection system for detecting a target material, such as an explosive material, can include a cantilevered probe, a probe heater coupled to the cantilevered probe, and a piezoelectric element disposed on the cantilevered probe. The piezoelectric element can be configured as a detector and/or an actuator. Detection can include, for example, detecting a movement of the cantilevered probe or a property of the cantilevered probe. The movement or a change in the property of the cantilevered probe can occur, for example, by adsorption of the target material, desorption of the target material, reaction of the target material and/or phase change of the target material. Examples of detectable movements and properties include temperature shifts, impedance shifts, and resonant frequency shifts of the cantilevered probe. The overall chemical detection system can be incorporated, for example, into a handheld explosive material detection system.

Cantilevered probe detector with piezoelectric element

DOEpatents

Adams, Jesse D.; Sulchek, Todd A.; Feigin, Stuart C.

2010-04-06

A disclosed chemical detection system for detecting a target material, such as an explosive material, can include a cantilevered probe, a probe heater coupled to the cantilevered probe, and a piezoelectric element disposed on the cantilevered probe. The piezoelectric element can be configured as a detector and/or an actuator. Detection can include, for example, detecting a movement of the cantilevered probe or a property of the cantilevered probe. The movement or a change in the property of the cantilevered probe can occur, for example, by adsorption of the target material, desorption of the target material, reaction of the target material and/or phase change of the target material. Examples of detectable movements and properties include temperature shifts, impedance shifts, and resonant frequency shifts of the cantilevered probe. The overall chemical detection system can be incorporated, for example, into a handheld explosive material detection system.

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.

Chaos in Kepler's Multiple Planet Systems and K2s Observations of the Atmospheres of Uranus Neptune

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.

2016-01-01

More than one-third of the 4700 planet candidates found by NASA's Kepler spacecraft during its prime mission are associated with target stars that have more than one planet candidate, and such "multis" account for the vast majority of candidates that have been verified as true planets. The large number of multis tells us that flat multiplanet systems like our Solar System are common. Virtually all of the candidate planetary systems are stable, as tested by numerical integrations that assume a physically motivated mass-radius relationship, but some of the systems lie in chaotic regions close to instability. The characteristics of some of the most interesting confirmed Kepler multi-planet systems will be discussed. The Kepler spacecraft's 'second life' in theK2 mission has allowed it to obtain long time-series observations of Solar System targets, including the giant planets Uranus & Neptune. These observations show variability caused by the chaotic weather patterns on Uranus & Neptune.

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.

Davisson-Germer Prize in Atomic or Surface Physics: The COLTRIMS multi-particle imaging technique-new Insight into the World of Correlation

NASA Astrophysics Data System (ADS)

Schmidt-Bocking, Horst

2008-05-01

The correlated many-particle dynamics in Coulombic systems, which is one of the unsolved fundamental problems in AMO-physics, can now be experimentally approached with so far unprecedented completeness and precision. The recent development of the COLTRIMS technique (COLd Target Recoil Ion Momentum Spectroscopy) provides a coincident multi-fragment imaging technique for eV and sub-eV fragment detection. In its completeness it is as powerful as the bubble chamber in high energy physics. In recent benchmark experiments quasi snapshots (duration as short as an atto-sec) of the correlated dynamics between electrons and nuclei has been made for atomic and molecular objects. This new imaging technique has opened a powerful observation window into the hidden world of many-particle dynamics. Recent multiple-ionization studies will be presented and the observation of correlated electron pairs will be discussed.

Accurate multi-robot targeting for keyhole neurosurgery based on external sensor monitoring.

PubMed

Comparetti, Mirko Daniele; Vaccarella, Alberto; Dyagilev, Ilya; Shoham, Moshe; Ferrigno, Giancarlo; De Momi, Elena

2012-05-01

Robotics has recently been introduced in surgery to improve intervention accuracy, to reduce invasiveness and to allow new surgical procedures. In this framework, the ROBOCAST system is an optically surveyed multi-robot chain aimed at enhancing the accuracy of surgical probe insertion during keyhole neurosurgery procedures. The system encompasses three robots, connected as a multiple kinematic chain (serial and parallel), totalling 13 degrees of freedom, and it is used to automatically align the probe onto a desired planned trajectory. The probe is then inserted in the brain, towards the planned target, by means of a haptic interface. This paper presents a new iterative targeting approach to be used in surgical robotic navigation, where the multi-robot chain is used to align the surgical probe to the planned pose, and an external sensor is used to decrease the alignment errors. The iterative targeting was tested in an operating room environment using a skull phantom, and the targets were selected on magnetic resonance images. The proposed targeting procedure allows about 0.3 mm to be obtained as the residual median Euclidean distance between the planned and the desired targets, thus satisfying the surgical accuracy requirements (1 mm), due to the resolution of the diffused medical images. The performances proved to be independent of the robot optical sensor calibration accuracy.

Simulation Research Framework with Embedded Intelligent Algorithms for Analysis of Multi-Target, Multi-Sensor, High-Cluttered Environments

NASA Astrophysics Data System (ADS)

Hanlon, Nicholas P.

The National Air Space (NAS) can be easily described as a complex aviation system-of-systems that seamlessly works in harmony to provide safe transit for all aircraft within its domain. The number of aircraft within the NAS is growing and according the FAA, "[o]n any given day, more than 85,000 flights are in the skies in the United States...This translates into roughly 5,000 planes in the skies above the United States at any given moment. More than 15,000 federal air traffic controllers in airport traffic control towers, terminal radar approach control facilities and air route traffic control centers guide pilots through the system". The FAA is currently rolling out the Next Generation Air Transportation System (NextGen) to handle projected growth while leveraging satellite-based navigation for improved tracking. A key component to instantiating NextGen lies in the equipage of Automatic Dependent Surveillance-Broadcast (ADS-B), a performance based surveillance technology that uses GPS navigation for more precise positioning than radars providing increased situational awareness to air traffic controllers. Furthermore, the FAA is integrating UAS into the NAS, further congesting the airways and information load on air traffic controllers. The expected increase in aircraft density due to NextGen implementation and UAS integration will require innovative algorithms to cope with the increase data flow and to support air traffic controllers in their decision-making. This research presents a few innovative algorithms to support increased aircraft density and UAS integration into the NAS. First, it is imperative that individual tracks are correlated prior to fusing to ensure a proper picture of the environment is correct. However, current approaches do not scale well as the number of targets and sensors are increased. This work presents a fuzzy clustering design to hierarchically break the problem down into smaller subspaces prior to correlation. This approach provides nearly identical performance metrics at orders of magnitude faster in execution. Second, a fuzzy inference system is presented that alleviates air traffic controllers from information overload by utilizing flight plan data and radar/GPS correlation values to highlight aircraft that deviate from their intended routes. Third, a genetic algorithm optimizes sensor placement that is robust and capable of handling unexpected routes in the environment. Fourth, a fuzzy CUSUM algorithm more accurately detects and corrects aircraft mode changes. Finally, all the work is packaged in a holistic simulation research framework that provides evaluation and analysis of various multi-sensor, multi-target scenarios.

Multi-Tasking and Choice of Training Data Influencing Parietal ERP Expression and Single-Trial Detection-Relevance for Neuroscience and Clinical Applications.

PubMed

Kirchner, Elsa A; Kim, Su Kyoung

2018-01-01

Event-related potentials (ERPs) are often used in brain-computer interfaces (BCIs) for communication or system control for enhancing or regaining control for motor-disabled persons. Especially results from single-trial EEG classification approaches for BCIs support correlations between single-trial ERP detection performance and ERP expression. Hence, BCIs can be considered as a paradigm shift contributing to new methods with strong influence on both neuroscience and clinical applications. Here, we investigate the relevance of the choice of training data and classifier transfer for the interpretability of results from single-trial ERP detection. In our experiments, subjects performed a visual-motor oddball task with motor-task relevant infrequent ( targets ), motor-task irrelevant infrequent ( deviants ), and motor-task irrelevant frequent ( standards ) stimuli. Under dual-task condition, a secondary senso-motor task was performed, compared to the simple-task condition. For evaluation, average ERP analysis and single-trial detection analysis with different numbers of electrodes were performed. Further, classifier transfer was investigated between simple and dual task. Parietal positive ERPs evoked by target stimuli (but not by deviants) were expressed stronger under dual-task condition, which is discussed as an increase of task emphasis and brain processes involved in task coordination and change of task set. Highest classification performance was found for targets irrespective whether all 62, 6 or 2 parietal electrodes were used. Further, higher detection performance of targets compared to standards was achieved under dual-task compared to simple-task condition in case of training on data from 2 parietal electrodes corresponding to results of ERP average analysis. Classifier transfer between tasks improves classification performance in case that training took place on more varying examples (from dual task). In summary, we showed that P300 and overlaying parietal positive ERPs can successfully be detected while subjects are performing additional ongoing motor activity. This supports single-trial detection of ERPs evoked by target events to, e.g., infer a patient's attentional state during therapeutic intervention.

The NASA Meter Class Autonomous Telescope: Ascension Island

DTIC Science & Technology

2013-09-01

understand the debris environment by providing high fidelity data in a timely manner to protect satellites and spacecraft in orbit around the Earth...gigabytes of image data nightly. With fainter detection limits, precision detection, acquisition and tracking of targets, multi-color photometry ...ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for

Detection of Chemical Precursors of Explosives

NASA Technical Reports Server (NTRS)

Li, Jing

2012-01-01

Certain selected chemicals associated with terrorist activities are too unstable to be prepared in final form. These chemicals are often prepared as precursor components, to be combined at a time immediately preceding the detonation. One example is a liquid explosive, which usually requires an oxidizer, an energy source, and a chemical or physical mechanism to combine the other components. Detection of the oxidizer (e.g. H2O2) or the energy source (e.g., nitromethane) is often possible, but must be performed in a short time interval (e.g., 5 15 seconds) and in an environment with a very small concentration (e.g.,1 100 ppm), because the target chemical(s) is carried in a sealed container. These needs are met by this invention, which provides a system and associated method for detecting one or more chemical precursors (components) of a multi-component explosive compound. Different carbon nanotubes (CNTs) are loaded (by doping, impregnation, coating, or other functionalization process) for detecting of different chemical substances that are the chemical precursors, respectively, if these precursors are present in a gas to which the CNTs are exposed. After exposure to the gas, a measured electrical parameter (e.g. voltage or current that correlate to impedance, conductivity, capacitance, inductance, etc.) changes with time and concentration in a predictable manner if a selected chemical precursor is present, and will approach an asymptotic value promptly after exposure to the precursor. The measured voltage or current are compared with one or more sequences of their reference values for one or more known target precursor molecules, and a most probable concentration value is estimated for each one, two, or more target molecules. An error value is computed, based on differences of voltage or current for the measured and reference values, using the most probable concentration values. Where the error value is less than a threshold, the system concludes that the target molecule is likely. Presence of one, two, or more target molecules in the gas can be sensed from a single set of measurements.

Direct Detection and Differentiation of Pathogenic Leptospira Species Using a Multi-Gene Targeted Real Time PCR Approach

PubMed Central

Ferreira, Ana Sofia; Costa, Pedro; Rocha, Teresa; Amaro, Ana; Vieira, Maria Luísa; Ahmed, Ahmed; Thompson, Gertrude; Hartskeerl, Rudy A.; Inácio, João

2014-01-01

Leptospirosis is a growing public and veterinary health concern caused by pathogenic species of Leptospira. Rapid and reliable laboratory tests for the direct detection of leptospiral infections in animals are in high demand not only to improve diagnosis but also for understanding the epidemiology of the disease. In this work we describe a novel and simple TaqMan-based multi-gene targeted real-time PCR approach able to detect and differentiate Leptospira interrogans, L. kirschneri, L. borgpeteresenii and L. noguchii, which constitute the veterinary most relevant pathogenic species of Leptospira. The method uses sets of species-specific probes, and respective flanking primers, designed from ompL1 and secY gene sequences. To monitor the presence of inhibitors, a duplex amplification assay targeting both the mammal β-actin and the leptospiral lipL32 genes was implemented. The analytical sensitivity of all primer and probe sets was estimated to be <10 genome equivalents (GE) in the reaction mixture. Application of the amplification reactions on genomic DNA from a variety of pathogenic and non-pathogenic Leptospira strains and other non-related bacteria revealed a 100% analytical specificity. Additionally, pathogenic leptospires were successfully detected in five out of 29 tissue samples from animals (Mus spp., Rattus spp., Dolichotis patagonum and Sus domesticus). Two samples were infected with L. borgpetersenii, two with L. interrogans and one with L. kirschneri. The possibility to detect and identify these pathogenic agents to the species level in domestic and wildlife animals reinforces the diagnostic information and will enhance our understanding of the epidemiology of leptopirosis. PMID:25398140

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.

Point Cloud Refinement with a Target-Free Intrinsic Calibration of a Mobile Multi-Beam LIDAR System

NASA Astrophysics Data System (ADS)

Nouiraa, H.; Deschaud, J. E.; Goulettea, F.

2016-06-01

LIDAR sensors are widely used in mobile mapping systems. The mobile mapping platforms allow to have fast acquisition in cities for example, which would take much longer with static mapping systems. The LIDAR sensors provide reliable and precise 3D information, which can be used in various applications: mapping of the environment; localization of objects; detection of changes. Also, with the recent developments, multi-beam LIDAR sensors have appeared, and are able to provide a high amount of data with a high level of detail. A mono-beam LIDAR sensor mounted on a mobile platform will have an extrinsic calibration to be done, so the data acquired and registered in the sensor reference frame can be represented in the body reference frame, modeling the mobile system. For a multibeam LIDAR sensor, we can separate its calibration into two distinct parts: on one hand, we have an extrinsic calibration, in common with mono-beam LIDAR sensors, which gives the transformation between the sensor cartesian reference frame and the body reference frame. On the other hand, there is an intrinsic calibration, which gives the relations between the beams of the multi-beam sensor. This calibration depends on a model given by the constructor, but the model can be non optimal, which would bring errors and noise into the acquired point clouds. In the litterature, some optimizations of the calibration parameters are proposed, but need a specific routine or environment, which can be constraining and time-consuming. In this article, we present an automatic method for improving the intrinsic calibration of a multi-beam LIDAR sensor, the Velodyne HDL-32E. The proposed approach does not need any calibration target, and only uses information from the acquired point clouds, which makes it simple and fast to use. Also, a corrected model for the Velodyne sensor is proposed. An energy function which penalizes points far from local planar surfaces is used to optimize the different proposed parameters for the corrected model, and we are able to give a confidence value for the calibration parameters found. Optimization results on both synthetic and real data are presented.

LSNR Airborne LIDAR Mapping System Design and Early Results (Invited)

NASA Astrophysics Data System (ADS)

Shrestha, K.; Carter, W. E.; Slatton, K. C.

2009-12-01

Low signal-to-noise ratio (LSNR) detection techniques allow for implementation of airborne light detection and range (LIDAR) instrumentation aboard platforms with prohibitive power, size, and weight restrictions. The University of Florida has developed the Coastal Area Tactical-mapping System (CATS), a prototype LSNR LIDAR system capable of single photon laser ranging. CATS is designed to operate in a fixed-wing aircraft flying 600 m above ground level, producing 532 nm, 480 ps, 3 μJ output pulses at 8 kHz. To achieve continuous coverage of the terrain with 20 cm spatial resolution in a single pass, a 10x10 array of laser beamlets is scanned. A Risley prism scanner (two rotating V-coated optical wedges) allows the array of laser beamlets to be deflected in a variety of patterns, including conical, spiral, and lines at selected angles to the direction of flight. Backscattered laser photons are imaged onto a 100 channel (10x10 segmented-anode) photomultiplier tube (PMT) with a micro-channel plate (MCP) amplifier. Each channel of the PMT is connected to a multi-stop 2 GHz event timer. Here we report on tests in which ranges for known targets were accumulated for repeated laser shots and statistical analyses were applied to evaluate range accuracy, minimum separation distance, bathymetric mapping depth, and atmospheric scattering. Ground-based field test results have yielded 10 cm range accuracy and sub-meter feature identification at variable scan settings. These experiments also show that a secondary surface can be detected at a distance of 15 cm from the first. Range errors in secondary surface identification for six separate trials were within 7.5 cm, or within the timing resolution limit of the system. Operating at multi-photon sensitivity may have value for situations in which high ambient noise precludes single-photon sensitivity. Low reflectivity targets submerged in highly turbid waters can cause detection issues. CATS offers the capability to adjust the sensitivity of the sensor by changing the PMT supply voltage. For heavily turbid water, the multi-photon state (2300 V, 2.5*10^5 gain) was not sufficient for feature identification. Extraction of the bottom signal in a heavily turbid suspension necessitated maximum MCP-PMT gain (2500 V, 8*10^5 gain). Extrapolation of bathymetric test results suggest that the density of data points from the sea bottom should be sufficient to establish near-shore depths (up to 5 m) at a spatial resolution of 1 meter, in moderately turbid water. Initial airborne tests over fresh water lakes in central Florida indicate that scan patterns containing near nadir laser points produce strong returns from the surface of the water that cause oscillations in the PMT—preventing the detection of the lake bottom in shallow clear water. These results suggest that it may be necessary to tilt the sensor head in its mount, or use a scan pattern that does not include nadir points, such as a circular scan, for bathymetric mapping. Additional tests are ongoing to optimize the performance of the CATS LSNR airborne LIDAR system for both high spatial resolution terrain mapping and shallow water bathymetric mapping.

Automated high-throughput flow-through real-time diagnostic system

DOEpatents

Regan, John Frederick

2012-10-30

An automated real-time flow-through system capable of processing multiple samples in an asynchronous, simultaneous, and parallel fashion for nucleic acid extraction and purification, followed by assay assembly, genetic amplification, multiplex detection, analysis, and decontamination. The system is able to hold and access an unlimited number of fluorescent reagents that may be used to screen samples for the presence of specific sequences. The apparatus works by associating extracted and purified sample with a series of reagent plugs that have been formed in a flow channel and delivered to a flow-through real-time amplification detector that has a multiplicity of optical windows, to which the sample-reagent plugs are placed in an operative position. The diagnostic apparatus includes sample multi-position valves, a master sample multi-position valve, a master reagent multi-position valve, reagent multi-position valves, and an optical amplification/detection system.

Detection and Monitoring of Small-Scale Mining Operations in the Eastern Democratic Republic of the Congo (DRC) Using Multi-Temporal, Multi-Sensor Remote Sensing Data

NASA Astrophysics Data System (ADS)

Walther, Christian; Frei, Michaela

2017-04-01

Mining of so-called "conflict minerals" is often related with small-scale mining activities. The here discussed activities are located in forested areas in the eastern DRC, which are often remote, difficult to access and insecure for traditional geological field inspection. In order to accelerate their CTC (Certified Trading Chain)-certification process, remote sensing data are used for detection and monitoring of these small-scale mining operations. This requires a high image acquisition frequency due to mining site relocations and for compensation of year-round high cloud coverage, especially for optical data evaluation. Freely available medium resolution optical data of Sentinel-2 and Landsat-8 as well as SAR data of Sentinel-1 are used for detecting small mining targets with a minimum size of approximately 0.5 km2. The developed method enables a robust multi-temporal detection of mining sites, monitoring of mining site spatio-temporal relocations and environmental changes. Since qualitative and quantitative comparable results are generated, the followed change detection approach is objective and transparent and may push the certification process forward.

Optical smoothing of laser imprinting in planar-target experiments on OMEGA EP using multi-FM 1-D smoothing by spectral dispersion

DOE PAGES

Hohenberger, M.; Shvydky, A.; Marozas, J. A.; ...

2016-09-07

Direct-drive ignition on the National Ignition Facility (NIF) requires single-beam smoothing to minimize imprinting of laser nonuniformities that can negatively affect implosion performance. One-dimensional, multi-FM smoothing by spectral dispersion (SSD) has been proposed to provide the required smoothing [J. A. Marozas, J. D. Zuegel, and T. J. B. Collins, Bull. Am. Phys. Soc. 55, 294 (2010)]. A prototype multi-FM SSD system has been integrated into the NIF-like beamline of the OMEGA EP Laser System. Experiments have been performed to verify the smoothing performance by measuring Rayleigh–Taylor growth rates in planar targets of laser-imprinted and preimposed surface modulations. Multi-FM 1-D SSDmore » has been observed to reduce imprint levels by ~50% compared to the nominal OMEGA EP SSD system. In conclusion, the experimental results are in agreement with 2-D DRACO simulations using realistic, time-dependent far-field spot-intensity calculations that emulate the effect of SSD.« less

Optical smoothing of laser imprinting in planar-target experiments on OMEGA EP using multi-FM 1-D smoothing by spectral dispersion

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

Hohenberger, M., E-mail: mhoh@lle.rochester.edu; Shvydky, A.; Marozas, J. A.

Direct-drive ignition on the National Ignition Facility (NIF) requires single-beam smoothing to minimize imprinting of laser nonuniformities that can negatively affect implosion performance. One-dimensional, multi-FM smoothing by spectral dispersion (SSD) has been proposed to provide the required smoothing [Marozas et al., Bull. Am. Phys. Soc. 55, 294 (2010)]. A prototype multi-FM SSD system has been integrated into the NIF-like beamline of the OMEGA EP Laser System. Experiments have been performed to verify the smoothing performance by measuring Rayleigh–Taylor growth rates in planar targets of laser-imprinted and preimposed surface modulations. Multi-FM 1-D SSD has been observed to reduce imprint levels bymore » ∼50% compared to the nominal OMEGA EP SSD system. The experimental results are in agreement with 2-D DRACO simulations using realistic, time-dependent far-field spot-intensity calculations that emulate the effect of SSD.« less

Optical smoothing of laser imprinting in planar-target experiments on OMEGA EP using multi-FM 1-D smoothing by spectral dispersion

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

Hohenberger, M.; Shvydky, A.; Marozas, J. A.

Direct-drive ignition on the National Ignition Facility (NIF) requires single-beam smoothing to minimize imprinting of laser nonuniformities that can negatively affect implosion performance. One-dimensional, multi-FM smoothing by spectral dispersion (SSD) has been proposed to provide the required smoothing [J. A. Marozas, J. D. Zuegel, and T. J. B. Collins, Bull. Am. Phys. Soc. 55, 294 (2010)]. A prototype multi-FM SSD system has been integrated into the NIF-like beamline of the OMEGA EP Laser System. Experiments have been performed to verify the smoothing performance by measuring Rayleigh–Taylor growth rates in planar targets of laser-imprinted and preimposed surface modulations. Multi-FM 1-D SSDmore » has been observed to reduce imprint levels by ~50% compared to the nominal OMEGA EP SSD system. In conclusion, the experimental results are in agreement with 2-D DRACO simulations using realistic, time-dependent far-field spot-intensity calculations that emulate the effect of SSD.« less

Detecting Shielded Special Nuclear Materials Using Multi-Dimensional Neutron Source and Detector Geometries

NASA Astrophysics Data System (ADS)

Santarius, John; Navarro, Marcos; Michalak, Matthew; Fancher, Aaron; Kulcinski, Gerald; Bonomo, Richard

2016-10-01

A newly initiated research project will be described that investigates methods for detecting shielded special nuclear materials by combining multi-dimensional neutron sources, forward/adjoint calculations modeling neutron and gamma transport, and sparse data analysis of detector signals. The key tasks for this project are: (1) developing a radiation transport capability for use in optimizing adaptive-geometry, inertial-electrostatic confinement (IEC) neutron source/detector configurations for neutron pulses distributed in space and/or phased in time; (2) creating distributed-geometry, gas-target, IEC fusion neutron sources; (3) applying sparse data and noise reduction algorithms, such as principal component analysis (PCA) and wavelet transform analysis, to enhance detection fidelity; and (4) educating graduate and undergraduate students. Funded by DHS DNDO Project 2015-DN-077-ARI095.

Standardized UXO Technology Demonstration Site Blind Grid Scoring Record No. 764

DTIC Science & Technology

2006-04-01

Attainable accuracy of depth (z) ± 0.3 meter Detection performance for ferrous and nonferrous metals : will detect ammunition components 20-mm...ASSOCIATES, INC. 6832 OLD DOMINION DRIVE MCLEAN, VA 22101 TECHNOLOGY TYPE/PLATFORM: MULTI CHANNEL DETECTOR SYSTEM (AMOS)/TOWED PREPARED BY: U.S...Multi Channel Detector System (AMOS)/Towed, MEC 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON a. REPORT Unclassified b. ABSTRACT

Optical Remote Sensing for Fence-Line Monitoring using Open-Path Quantum Cascade Laser (QCL) mono-static system for multiple target compounds in the Mid IR 7-13um (Fingerprint) region.

NASA Astrophysics Data System (ADS)

Zemek, P. G.

2017-12-01

Quantum Cascade Lasers (QCLs) are quickly replacing Tunable Diode Lasers (TDL) for multi-target species identification and quantification in both extractive and open-path (OP) Optical Remote Sensing (ORS) fence-line instrumentation. As was seen with TDL incorporation and pricing drops as the adoption by the telecommunications industry and its current scaling has improved robustness and pricing, the QCL is also, albiet more slowly, becoming a mature market. There are several advantages of QCLs over conventional TDLs such as improved brightness and beam density, high resolution, as well as the incorporation of external etalons or internal gratings to scan over wide spectral areas. QCLs typically operate in the Mid infra-red (MIR) as opposed to the Near-Infrared (NIR) region used with TDL. The MidIR is a target rich absorption band area where compounds have high absorbtivity coefficients resulting in better detection limits as compared to TDL instruments. The use of novel chemometrics and more sensitive non-cryo-cooled detectors has allowed some of the first QCL open-path instruments in both active and passive operation. Data and field studies of one of the newest QCL OP systems is presented that allows one system to measure multiple target compounds. Multiple QCL spectral regions may be stitched together to increase the capability of QCLs over TDL OP systems. A comparison of several ORS type systems will be presented.

Characterization of polymeric substance classes in cereal-based beverages using asymmetrical flow field-flow fractionation with a multi-detection system.

PubMed

Krebs, Georg; Becker, Thomas; Gastl, Martina

2017-09-01

Cereal-based beverages contain a complex mixture of various polymeric macromolecules including polysaccharides, peptides, and polyphenols. The molar mass of polymers and their degradation products affect different technological and especially sensory parameters of beverages. Asymmetrical flow field-flow fractionation (AF4) coupled with multi-angle light scattering (MALS) and refractive index detection (dRI) or UV detection (UV) is a technique for structure and molar mass distribution analysis of macromolecules commonly used for pure compound solutions. The objective of this study was to develop a systematic approach for identifying the polymer classes in an AF4//MALS/dRI/UV fractogram of the complex matrix in beer, a yeast-fermented cereal-based beverage. Assignment of fractogram fractions to polymer substance classes was achieved by targeted precipitations, enzymatic hydrolysis, and alignments with purified polymer standards. Corresponding effects on dRI and UV signals were evaluated according to the detector's sensitivities. Using these techniques, the AF4 fractogram of beer was classified into different fractions: (1) the low molar mass fraction was assigned to proteinaceous molecules with different degrees of glycosylation, (2) the middle molar mass fraction was attributed to protein-polyphenol complexes with a coelution of non-starch polysaccharides, and (3) the high molar mass fraction was identified as a mixture of the cell wall polysaccharides (i.e., β-glucan and arabinoxylan) with a low content of polysaccharide-protein association. In addition, dextrins derived from incomplete starch hydrolysis were identified in all fractions and over the complete molar mass range. The ability to assess the components of an AF4 fractogram is beneficial for the targeted design and evaluation of polymers in fermented cereal-based beverages and for controlling and monitoring quality parameters.

Miniaturized, multibeam, solid state scanning laser radar in automobile collision avoidance sensor systems

NASA Astrophysics Data System (ADS)

Sargent, Ronald A.

1995-06-01

Recent intelligent transportation systems (ITS) initiatives sponsored by commercial transportation companies and the U.S. Department of Transportation include an area dedicated to Automated Vehicle Control Systems (AVCS). AVCS systems are dedicated to improving passenger automobile safety, efficiency, and impact on the environment. Minimizing the number of automobile collisions through automated obstacle detection and vehicle response is vital to this effort. Simple, reliable, low cost sensors installed in automobiles to provide driver warning and/or input to vehicle systems such as braking or cruise control are the key piece to making this technology as common as air bags and seat belts. EPA emission regulations now require specific areas to periodically report the mix of vehicle types. These reports must include in the mix the 13 possible categories for vehicles. Simple low cost senors installed as part of the traffic management system will facilitate the determination of vehicle category. Laser Atlanta has recently developed two distinct types of sensors that utilize a unique multi- beam approach to detect `targets' that are potential hazards. They also provide range and range rate data to automobile control and traffic management systems.

Multi-analyte validation in heterogeneous solution by ELISA.

PubMed

Lakshmipriya, Thangavel; Gopinath, Subash C B; Hashim, Uda; Murugaiyah, Vikneswaran

2017-12-01

Enzyme Linked Immunosorbent Assay (ELISA) is a standard assay that has been used widely to validate the presence of analyte in the solution. With the advancement of ELISA, different strategies have shown and became a suitable immunoassay for a wide range of analytes. Herein, we attempted to provide additional evidence with ELISA, to show its suitability for multi-analyte detection. To demonstrate, three clinically relevant targets have been chosen, which include 16kDa protein from Mycobacterium tuberculosis, human blood clotting Factor IXa and a tumour marker Squamous Cell Carcinoma antigen. Indeed, we adapted the routine steps from the conventional ELISA to validate the occurrence of analytes both in homogeneous and heterogeneous solutions. With the homogeneous and heterogeneous solutions, we could attain the sensitivity of 2, 8 and 1nM for the targets 16kDa protein, FIXa and SSC antigen, respectively. Further, the specific multi-analyte validations were evidenced with the similar sensitivities in the presence of human serum. ELISA assay in this study has proven its applicability for the genuine multiple target validation in the heterogeneous solution, can be followed for other target validations. Copyright © 2017 Elsevier B.V. All rights reserved.

Elastic all-optical multi-hop interconnection in data centers with adaptive spectrum allocation

NASA Astrophysics Data System (ADS)

Hong, Yuanyuan; Hong, Xuezhi; Chen, Jiajia; He, Sailing

2017-01-01

In this paper, a novel flex-grid all-optical interconnect scheme that supports transparent multi-hop connections in data centers is proposed. An inter-rack all-optical multi-hop connection is realized with an optical loop employed at flex-grid wavelength selective switches (WSSs) in an intermediate rack rather than by relaying through optical-electric-optical (O-E-O) conversions. Compared with the conventional O-E-O based approach, the proposed all-optical scheme is able to off-load the traffic at intermediate racks, leading to a reduction of the power consumption and cost. The transmission performance of the proposed flex-grid multi-hop all-optical interconnect scheme with various modulation formats, including both coherently detected and directly detected approaches, are investigated by Monte-Carlo simulations. To enhance the spectrum efficiency (SE), number-of-hop adaptive bandwidth allocation is introduced. Numerical results show that the SE can be improved by up to 33.3% at 40 Gbps, and by up to 25% at 100 Gbps. The impact of parameters, such as targeted bit error rate (BER) level and insertion loss of components, on the transmission performance of the proposed approach are also explored. The results show that the maximum SE improvement of the adaptive approach over the non-adaptive one is enhanced with the decrease of the targeted BER levels and the component insertion loss.

Magnetic resonance/transrectal ultrasound fusion biopsy of the prostate compared to systematic 12-core biopsy for the diagnosis and characterization of prostate cancer: multi-institutional retrospective analysis of 389 patients.

PubMed

Mariotti, Guilherme C; Costa, Daniel N; Pedrosa, Ivan; Falsarella, Priscila M; Martins, Tatiana; Roehrborn, Claus G; Rofsky, Neil M; Xi, Yin; M Andrade, Thais C; Queiroz, Marcos R; Lotan, Yair; Garcia, Rodrigo G; Lemos, Gustavo C; Baroni, Ronaldo H

2016-09-01

To determine the incremental diagnostic value of targeted biopsies added to an extended sextant biopsy scheme on a per-patient, risk-stratified basis in 2 academic centers using different multiparametric magnetic resonance imaging (MRI) protocols, a large group of radiologists, multiple biopsy systems, and different biopsy operators. All patients with suspected prostate cancer (PCa) who underwent multiparametric MRI of the prostate in 2 academic centers between February 2013 and January 2015 followed by systematic and targeted MRI-transrectal ultrasound fusion biopsy were reviewed. Risk-stratified detection rate using systematic biopsies was compared with targeted biopsies on a per-patient basis. The McNemar test was used to compare diagnostic performance of the 2 approaches. A total of 389 men met eligibility criteria. PCa was diagnosed in 47% (182/389), 52%(202/389), and 60%(235/389) of patients using the targeted, systematic, and combined (targeted plus systematic) approach, respectively. Compared with systematic biopsy, targeted biopsy diagnosed 11% (37 vs. 26) more intermediate-to-high risk (P<0.0001) and 16% (10 vs. 16) fewer low-risk tumors (P<0.0001). These results were replicated when data from each center, biopsy-naïve patients, and men with previous negative biopsies were analyzed separately. Targeted MRI-transrectal ultrasound fusion biopsy consistently improved the detection of clinically significant PCa in a large patient cohort with diverse equipment, protocols, radiologists, and biopsy operators as can be encountered in clinical practice. Copyright © 2016 Elsevier Inc. All rights reserved.

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

Development and Measurements of a Mid-Infrared Multi-Gas Sensor System for CO, CO2 and CH4 Detection

PubMed Central

Dong, Ming; Zheng, Chuantao; Miao, Shuzhuo; Zhang, Yu; Du, Qiaoling; Wang, Yiding

2017-01-01

A multi-gas sensor system was developed that uses a single broadband light source and multiple carbon monoxide (CO), carbon dioxide (CO2) and methane (CH4) pyroelectric detectors by use of the time division multiplexing (TDM) technique. A stepper motor-based rotating system and a single-reflection spherical optical mirror were designed and adopted to realize and enhance multi-gas detection. Detailed measurements under static detection mode (without rotation) and dynamic mode (with rotation) were performed to study the performance of the sensor system for the three gas species. Effects of the motor rotating period on sensor performances were also investigated and a rotation speed of 0.4π rad/s was required to obtain a stable sensing performance, corresponding to a detection period of ~10 s to realize one round of detection. Based on an Allan deviation analysis, the 1σ detection limits under static operation are 2.96, 4.54 and 2.84 parts per million in volume (ppmv) for CO, CO2 and CH4, respectively and the 1σ detection limits under dynamic operations are 8.83, 8.69 and 10.29 ppmv for the three gas species, respectively. The reported sensor has potential applications in various fields requiring CO, CO2 and CH4 detection such as in coal mines. PMID:28953260

Target-type probability combining algorithms for multisensor tracking

NASA Astrophysics Data System (ADS)

Wigren, Torbjorn

2001-08-01

Algorithms for the handing of target type information in an operational multi-sensor tracking system are presented. The paper discusses recursive target type estimation, computation of crosses from passive data (strobe track triangulation), as well as the computation of the quality of the crosses for deghosting purposes. The focus is on Bayesian algorithms that operate in the discrete target type probability space, and on the approximations introduced for computational complexity reduction. The centralized algorithms are able to fuse discrete data from a variety of sensors and information sources, including IFF equipment, ESM's, IRST's as well as flight envelopes estimated from track data. All algorithms are asynchronous and can be tuned to handle clutter, erroneous associations as well as missed and erroneous detections. A key to obtain this ability is the inclusion of data forgetting by a procedure for propagation of target type probability states between measurement time instances. Other important properties of the algorithms are their abilities to handle ambiguous data and scenarios. The above aspects are illustrated in a simulations study. The simulation setup includes 46 air targets of 6 different types that are tracked by 5 airborne sensor platforms using ESM's and IRST's as data sources.

Photon-number-resolving SSPDs with system detection efficiency over 50% at telecom range

NASA Astrophysics Data System (ADS)

Zolotov, P.; Divochiy, A.; Vakhtomin, Yu.; Moshkova, M.; Morozov, P.; Seleznev, V.; Smirnov, K.

2018-02-01

We used technology of making high-efficiency superconducting single-photon detectors as a basis for improvement of photon-number-resolving devices. By adding optical cavity and using an improved NbN superconducting film, we enhanced previously reported system detection efficiency at telecom range for such detectors. Our results show that implementation of optical cavity helps to develop four-section device with quantum efficiency over 50% at 1.55 µm. Performed experimental studies of detecting multi-photon optical pulses showed irregularities over defining multi-photon through single-photon quantum efficiency.

A Multi-Channel Method for Detecting Periodic Forced Oscillations in Power Systems

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

Follum, James D.; Tuffner, Francis K.

2016-11-14

Forced oscillations in electric power systems are often symptomatic of equipment malfunction or improper operation. Detecting and addressing the cause of the oscillations can improve overall system operation. In this paper, a multi-channel method of detecting forced oscillations and estimating their frequencies is proposed. The method operates by comparing the sum of scaled periodograms from various channels to a threshold. A method of setting the threshold to specify the detector's probability of false alarm while accounting for the correlation between channels is also presented. Results from simulated and measured power system data indicate that the method outperforms its single-channel counterpartmore » and is suitable for real-world applications.« less

Multi-Harmony: detecting functional specificity from sequence alignment

PubMed Central

Brandt, Bernd W.; Feenstra, K. Anton; Heringa, Jaap

2010-01-01

Many protein families contain sub-families with functional specialization, such as binding different ligands or being involved in different protein–protein interactions. A small number of amino acids generally determine functional specificity. The identification of these residues can aid the understanding of protein function and help finding targets for experimental analysis. Here, we present multi-Harmony, an interactive web sever for detecting sub-type-specific sites in proteins starting from a multiple sequence alignment. Combining our Sequence Harmony (SH) and multi-Relief (mR) methods in one web server allows simultaneous analysis and comparison of specificity residues; furthermore, both methods have been significantly improved and extended. SH has been extended to cope with more than two sub-groups. mR has been changed from a sampling implementation to a deterministic one, making it more consistent and user friendly. For both methods Z-scores are reported. The multi-Harmony web server produces a dynamic output page, which includes interactive connections to the Jalview and Jmol applets, thereby allowing interactive analysis of the results. Multi-Harmony is available at http://www.ibi.vu.nl/ programs/shmrwww. PMID:20525785

Analysis of detection performance of multi band laser beam analyzer

NASA Astrophysics Data System (ADS)

Du, Baolin; Chen, Xiaomei; Hu, Leili

2017-10-01

Compared with microwave radar, Laser radar has high resolution, strong anti-interference ability and good hiding ability, so it becomes the focus of laser technology engineering application. A large scale Laser radar cross section (LRCS) measurement system is designed and experimentally tested. First, the boundary conditions are measured and the long range laser echo power is estimated according to the actual requirements. The estimation results show that the echo power is greater than the detector's response power. Secondly, a large scale LRCS measurement system is designed according to the demonstration and estimation. The system mainly consists of laser shaping, beam emitting device, laser echo receiving device and integrated control device. Finally, according to the designed lidar cross section measurement system, the scattering cross section of target is simulated and tested. The simulation results are basically the same as the test results, and the correctness of the system is proved.

Multitarget detection algorithm for automotive FMCW radar

NASA Astrophysics Data System (ADS)

Hyun, Eugin; Oh, Woo-Jin; Lee, Jong-Hun

2012-06-01

Today, 77 GHz FMCW (Frequency Modulation Continuous Wave) radar has strong advantages of range and velocity detection for automotive applications. However, FMCW radar brings out ghost targets and missed targets in multi-target situations. In this paper, in order to resolve these limitations, we propose an effective pairing algorithm, which consists of two steps. In the proposed method, a waveform with different slopes in two periods is used. In the 1st pairing processing, all combinations of range and velocity are obtained in each of two wave periods. In the 2nd pairing step, using the results of the 1st pairing processing, fine range and velocity are detected. In that case, we propose the range-velocity windowing technique in order to compensate for the non-ideal beat-frequency characteristic that arises due to the non-linearity of the RF module. Based on experimental results, the performance of the proposed algorithm is improved compared with that of the typical method.

An Autonomous Sensor System Architecture for Active Flow and Noise Control Feedback

NASA Technical Reports Server (NTRS)

Humphreys, William M, Jr.; Culliton, William G.

2008-01-01

Multi-channel sensor fusion represents a powerful technique to simply and efficiently extract information from complex phenomena. While the technique has traditionally been used for military target tracking and situational awareness, a study has been successfully completed that demonstrates that sensor fusion can be applied equally well to aerodynamic applications. A prototype autonomous hardware processor was successfully designed and used to detect in real-time the two-dimensional flow reattachment location generated by a simple separated-flow wind tunnel model. The success of this demonstration illustrates the feasibility of using autonomous sensor processing architectures to enhance flow control feedback signal generation.

Multispectral image fusion based on fractal features

NASA Astrophysics Data System (ADS)

Tian, Jie; Chen, Jie; Zhang, Chunhua

2004-01-01

Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the composition of source pyramid images. So this fusion scheme is a multi-resolution analysis. The wavelet decomposition of image can be actually considered as special pyramid decomposition. According to wavelet decomposition theories, the approximation of image (formula available in paper) at resolution 2j+1 equal to its orthogonal projection in space , that is, where Ajf is the low-frequency approximation of image f(x, y) at resolution 2j and , , represent the vertical, horizontal and diagonal wavelet coefficients respectively at resolution 2j. These coefficients describe the high-frequency information of image at direction of vertical, horizontal and diagonal respectively. Ajf, , and are independent and can be considered as images. In this paper J is set to be 1, so the source image is decomposed to produce the son-images Af, D1f, D2f and D3f. To solve the problem of detecting artifacts, the concepts of vertical fractal dimension FD1, horizontal fractal dimension FD2 and diagonal fractal dimension FD3 are proposed in this paper. The vertical fractal dimension FD1 corresponds to the vertical wavelet coefficients image after the wavelet decomposition of source image, the horizontal fractal dimension FD2 corresponds to the horizontal wavelet coefficients and the diagonal fractal dimension FD3 the diagonal one. These definitions enrich the illustration of source images. Therefore they are helpful to classify the targets. Then the detection of artifacts in the decomposed images is a problem of pattern recognition in 4-D space. The combination of FD0, FD1, FD2 and FD3 make a vector of (FD0, FD1, FD2, FD3), which can be considered as a united feature vector of the studied image. All the parts of the images are classified in the 4-D pattern space created by the vector of (FD0, FD1, FD2, FD3) so that the area that contains man-made objects could be detected. This detection can be considered as a coarse recognition, and then the significant areas in each son-images are signed so that they can be dealt with special rules. There has been various fusion rules developed with each one aiming at a special problem. These rules have different performance, so it is very important to select an appropriate rule during the design of an image fusion system. Recent research denotes that the rule should be adjustable so that it is always suitable to extrude the features of targets and to preserve the pixels of useful information. In this paper, owing to the consideration that fractal dimension is one of the main features to distinguish man-made targets from natural objects, the fusion rule was defined that if the studied region of image contains man-made target, the pixels of the source image whose fractal dimension is minimal are saved to be the pixels of the fused image, otherwise, a weighted average operator is adopted to avoid loss of information. The main idea of this rule is to store the pixels with low fractal dimensions, so it can be named Minimal Fractal dimensions (MFD) fusion rule. This fractal-based algorithm is compared with a common weighted average fusion algorithm. An objective assessment is taken to the two fusion results. The criteria of Entropy, Cross-Entropy, Peak Signal-to-Noise Ratio (PSNR) and Standard Gray Scale Difference are defined in this paper. Reversely to the idea of constructing an ideal image as the assessing reference, the source images are selected to be the reference in this paper. It can be deemed that this assessment is to calculate how much the image quality has been enhanced and the quantity of information has been increased when the fused image is compared with the source images. The experimental results imply that the fractal-based multi-spectral fusion algorithm can effectively preserve the information of man-made objects with a high contrast. It is proved that this algorithm could well preserve features of military targets because that battlefield targets are most man-made objects and in common their images differ from fractal models obviously. Furthermore, the fractal features are not sensitive to the imaging conditions and the movement of targets, so this fractal-based algorithm may be very practical.

Research on effect of rough surface on FMCW laser radar range accuracy

NASA Astrophysics Data System (ADS)

Tao, Huirong

2018-03-01

The non-cooperative targets large scale measurement system based on frequency-modulated continuous-wave (FMCW) laser detection and ranging technology has broad application prospects. It is easy to automate measurement without cooperative targets. However, the complexity and diversity of the surface characteristics of the measured surface directly affects the measurement accuracy. First, the theoretical analysis of range accuracy for a FMCW laser radar was studied, the relationship between surface reflectivity and accuracy was obtained. Then, to verify the effect of surface reflectance for ranging accuracy, a standard tool ball and three standard roughness samples were measured within 7 m to 24 m. The uncertainty of each target was obtained. The results show that the measurement accuracy is found to increase as the surface reflectivity gets larger. Good agreements were obtained between theoretical analysis and measurements from rough surfaces. Otherwise, when the laser spot diameter is smaller than the surface correlation length, a multi-point averaged measurement can reduce the measurement uncertainty. The experimental results show that this method is feasible.

Time Domain Astronomy with Fermi GBM in the Multi-messenger Era

NASA Astrophysics Data System (ADS)

Wilson-Hodge, Colleen A.; Fermi GBM team, GBM-LIGO team

2018-01-01

As the Multi-Messenger era begins with detections of gravitational waves with LIGO/Virgo and neutrinos with IceCube, the Fermi Gamma-ray Burst Monitor (GBM) provides context observations of gamma-ray transients between 8 keV and 40 MeV. Fermi GBM has a wide field of view, high uptime, and both in-orbit triggering and high time resolution continuous data enabling offline searches for weaker transients. GBM detects numerous gamma-ray bursts (GRBs), soft gamma-ray repeaters, X-ray bursters, solar flares and terrestrial gamma-ray flashes. Longer timescale transients, predominantly in our galaxy so far, are detected using the Earth occultation technique and epoch-folding for periodic sources. The GBM team has developed two ground-based searches to enhance detections of faint transients, especially short GRBs. The targeted search uses the time and location of an event detected with another instrument to coherently search the GBM data, increasing the sensitivity to a transient. The untargeted search agnostically searches the GBM data for all directions and times to find weaker transients. This search finds about 80 short GRBs per year, adding to the 40 per year triggered on-orbit. With its large field of view, high duty cycle and increasingly sophisticated detection methods, Fermi GBM is expected to have a major role in the Multi-Messenger era.

Inelastic Boosted Dark Matter at direct detection experiments

NASA Astrophysics Data System (ADS)

Giudice, Gian F.; Kim, Doojin; Park, Jong-Chul; Shin, Seodong

2018-05-01

We explore a novel class of multi-particle dark sectors, called Inelastic Boosted Dark Matter (iBDM). These models are constructed by combining properties of particles that scatter off matter by making transitions to heavier states (Inelastic Dark Matter) with properties of particles that are produced with a large Lorentz boost in annihilation processes in the galactic halo (Boosted Dark Matter). This combination leads to new signals that can be observed at ordinary direct detection experiments, but require unconventional searches for energetic recoil electrons in coincidence with displaced multi-track events. Related experimental strategies can also be used to probe MeV-range boosted dark matter via their interactions with electrons inside the target material.

Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments

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

Wang, Anbo

This report summarizes technical progress on the program “Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments” funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Center for Photonics Technology at Virginia Tech. The objective of this project is to develop a first-of-a-kind technology for remote fiber optic generation and detection of acoustic waves for structural health monitoring in harsh environments. During the project period, which is from April 1, 2013 to Septemeber 30, 2016, three different acoustic generation mechanisms were studied in detail for their applications inmore » building a fiber optic acoustic generation unit (AGU), including laser induced plasma breakdown (LIP), Erbium-doped fiber laser absorption, and metal laser absorption. By comparing the performance of the AGUs designed based on these three mechanisms and analyzing the experimental results with simulations, the metal laser absorption method was selected to build a complete fiber optic structure health monitoring (FO-SHM) system for the proposed high temperature multi-parameter structure health monitoring application. Based on the simulation of elastic wave propagation and fiber Bragg grating acoustic pulse detection, an FO-SHM element together with a completed interrogation system were designed and built. This system was first tested on an aluminum piece in the low-temperature range and successfully demonstrated its capability of multi-parameter monitoring and multi-point sensing. In the later stages of the project, the research was focused on improving the surface attachment design and preparing the FO-SHM element for high temperature environment tests. After several upgrades to the surface attachment methods, the FO-SHM element was able to work reliably up to 600oC when attached to P91 pipes, which are the target material of this project. In the final stage of this project, this FO-SHM sensing system was tested in the simulated harsh environment for its multi-parameter monitoring performance and high-temperature survivability.« less

Rationale and design of the ADDITION-Leicester study, a systematic screening programme and Randomised Controlled Trial of multi-factorial cardiovascular risk intervention in people with Type 2 Diabetes Mellitus detected by screening

PubMed Central

2010-01-01

Background Earlier diagnosis followed by multi-factorial cardiovascular risk intervention may improve outcomes in Type 2 Diabetes Mellitus (T2DM). Latent phase identification through screening requires structured, appropriately targeted population-based approaches. Providers responsible for implementing screening policy await evidence of clinical and cost effectiveness from randomised intervention trials in screen-detected T2DM cases. UK South Asians are at particularly high risk of abnormal glucose tolerance and T2DM. To be effective national screening programmes must achieve good coverage across the population by identifying barriers to the detection of disease and adapting to the delivery of earlier care. Here we describe the rationale and methods of a systematic community screening programme and randomised controlled trial of cardiovascular risk management within a UK multiethnic setting (ADDITION-Leicester). Design A single-blind cluster randomised, parallel group trial among people with screen-detected T2DM comparing a protocol driven intensive multi-factorial treatment with conventional care. Methods ADDITION-Leicester consists of community-based screening and intervention phases within 20 general practices coordinated from a single academic research centre. Screening adopts a universal diagnostic approach via repeated 75g-Oral Glucose Tolerance Tests within an eligible non-diabetic population of 66,320 individuals aged 40-75 years (25-75 years South Asian). Volunteers also provide detailed medical and family histories; complete health questionnaires, undergo anthropometric measures, lipid profiling and a proteinuria assessment. Primary outcome is reduction in modelled Coronary Heart Disease (UKPDS CHD) risk at five years. Seven thousand (30% of South Asian ethnic origin) volunteers over three years will be recruited to identify a screen-detected T2DM cohort (n = 285) powered to detected a 6% relative difference (80% power, alpha 0.05) between treatment groups at one year. Randomisation will occur at practice-level with newly diagnosed T2DM cases receiving either conventional (according to current national guidelines) or intensive (algorithmic target-driven multi-factorial cardiovascular risk intervention) treatments. Discussion ADDITION-Leicester is the largest multiethnic (targeting >30% South Asian recruitment) community T2DM and vascular risk screening programme in the UK. By assessing feasibility and efficacy of T2DM screening, it will inform national disease prevention policy and contribute significantly to our understanding of the health care needs of UK South Asians. Trial registration Clinicaltrial.gov (NCT00318032). PMID:20170482

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Studies on Radar Sensor Networks

DTIC Science & Technology

2007-08-08

scheme in which 2-D image was created via adding voltages with the appropriate time offset. Simulation results show that our DCT-based scheme works...using RSNs in terms of the probability of miss detection PMD and the root mean square error (RMSE). Simulation results showed that multi-target detection... Simulation results are presented to evaluate the feasibility and effectiveness of the proposed JMIC algorithm in a query surveillance region. 5 SVD-QR and

Study of multi-functional precision optical measuring system for large scale equipment

NASA Astrophysics Data System (ADS)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

Hybrid PET/MR imaging: physics and technical considerations.

PubMed

Shah, Shetal N; Huang, Steve S

2015-08-01

In just over a decade, hybrid imaging with FDG PET/CT has become a standard bearer in the management of cancer patients. An exquisitely sensitive whole-body imaging modality, it combines the ability to detect subtle biologic changes with FDG PET and the anatomic information offered by CT scans. With advances in MR technology and advent of novel targeted PET radiotracers, hybrid PET/MRI is an evolutionary technique that is poised to revolutionize hybrid imaging. It offers unparalleled spatial resolution and functional multi-parametric data combined with biologic information in the non-invasive detection and characterization of diseases, without the deleterious effects of ionizing radiation. This article reviews the basic principles of FDG PET and MR imaging, discusses the salient technical developments of hybrid PET/MR systems, and provides an introduction to FDG PET/MR image acquisition.

MW 08-multi-beam air and surface surveillance radar

NASA Astrophysics Data System (ADS)

1989-09-01

Signal of the Netherlands has developed and is marketing the MW 08, a 3-D radar to be used for short to medium range surveillance, target acquisition, and tracking. MW 08 is a fully automated detecting and tracking radar. It is designed to counter threats from aircraft and low flying antiship missiles. It can also deal with the high level missile threat. MW 08 operates in the 5 cm band using one antenna for both transmitting and receiving. The antenna is an array, consisting of 8 stripline antennas. The received radar energy is processed by 8 receiver channels. These channels come together in the beam forming network, in which 8 virtual beams are formed. From this beam pattern, 6 beams are used for the elevation coverage of 0-70 degrees. MW 08's output signals of the beam former are further handled by FFT and plot processors for target speed information, clutter rejection, and jamming suppression. A general purpose computer handles target track initiation, and tracking. Tracking data are transferred to the command and control systems with 3-D target information for fastest possible lockon.

Designing manufacturable filters for a 16-band plenoptic camera using differential evolution

NASA Astrophysics Data System (ADS)

Doster, Timothy; Olson, Colin C.; Fleet, Erin; Yetzbacher, Michael; Kanaev, Andrey; Lebow, Paul; Leathers, Robert

2017-05-01

A 16-band plenoptic camera allows for the rapid exchange of filter sets via a 4x4 filter array on the lens's front aperture. This ability to change out filters allows for an operator to quickly adapt to different locales or threat intelligence. Typically, such a system incorporates a default set of 16 equally spaced at-topped filters. Knowing the operating theater or the likely targets of interest it becomes advantageous to tune the filters. We propose using a modified beta distribution to parameterize the different possible filters and differential evolution (DE) to search over the space of possible filter designs. The modified beta distribution allows us to jointly optimize the width, taper and wavelength center of each single- or multi-pass filter in the set over a number of evolutionary steps. Further, by constraining the function parameters we can develop solutions which are not just theoretical but manufacturable. We examine two independent tasks: general spectral sensing and target detection. In the general spectral sensing task we utilize the theory of compressive sensing (CS) and find filters that generate codings which minimize the CS reconstruction error based on a fixed spectral dictionary of endmembers. For the target detection task and a set of known targets, we train the filters to optimize the separation of the background and target signature. We compare our results to the default 16 at-topped non-overlapping filter set which comes with the plenoptic camera and full hyperspectral resolution data which was previously acquired.

RadMAP: The Radiological Multi-sensor Analysis Platform

NASA Astrophysics Data System (ADS)

Bandstra, Mark S.; Aucott, Timothy J.; Brubaker, Erik; Chivers, Daniel H.; Cooper, Reynold J.; Curtis, Joseph C.; Davis, John R.; Joshi, Tenzing H.; Kua, John; Meyer, Ross; Negut, Victor; Quinlan, Michael; Quiter, Brian J.; Srinivasan, Shreyas; Zakhor, Avideh; Zhang, Richard; Vetter, Kai

2016-12-01

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. In this paper we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

Multianalyte detection using a capillary-based flow immunosensor.

PubMed

Narang, U; Gauger, P R; Kusterbeck, A W; Ligler, F S

1998-01-01

A highly sensitive, dual-analyte detection system using capillary-based immunosensors has been designed for explosive detection. This model system consists of two capillaries, one coated with antibodies specific for 2,4,6-trinitrotoluene (TNT) and the other specific for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) combined into a single device. The fused silica capillaries are prepared by coating anti-TNT and anti-RDX antibodies onto the silanized inner walls using a hetero-bifunctional crosslinker. After immobilization, the antibodies are saturated with a suitable fluorophorelabeled antigen. A "T" connector is used to continuously flow the buffer solution through the individual capillaries. To perform the assay, an aliquot of TNT or RDX or a mixture of the two analytes is injected into the continuous flow stream. In each capillary, the target analyte displaces the fluorophore-labeled antigen from the binding pocket of the antibody. The labeled antigen displaced from either capillary is detected downstream using two portable spectrofluorometers. The limits of detection for TNT and RDX in the multi-analyte formate are 44 fmol (100 microliters of 0.1 ng/ml TNT solution) and 224 fmol (100 microliters of 0.5 ng/ml RDX solution), respectively. The entire assay for both analytes can be performed in less than 3 min.

Multi-Tasking and Choice of Training Data Influencing Parietal ERP Expression and Single-Trial Detection—Relevance for Neuroscience and Clinical Applications

PubMed Central

Kirchner, Elsa A.; Kim, Su Kyoung

2018-01-01

Event-related potentials (ERPs) are often used in brain-computer interfaces (BCIs) for communication or system control for enhancing or regaining control for motor-disabled persons. Especially results from single-trial EEG classification approaches for BCIs support correlations between single-trial ERP detection performance and ERP expression. Hence, BCIs can be considered as a paradigm shift contributing to new methods with strong influence on both neuroscience and clinical applications. Here, we investigate the relevance of the choice of training data and classifier transfer for the interpretability of results from single-trial ERP detection. In our experiments, subjects performed a visual-motor oddball task with motor-task relevant infrequent (targets), motor-task irrelevant infrequent (deviants), and motor-task irrelevant frequent (standards) stimuli. Under dual-task condition, a secondary senso-motor task was performed, compared to the simple-task condition. For evaluation, average ERP analysis and single-trial detection analysis with different numbers of electrodes were performed. Further, classifier transfer was investigated between simple and dual task. Parietal positive ERPs evoked by target stimuli (but not by deviants) were expressed stronger under dual-task condition, which is discussed as an increase of task emphasis and brain processes involved in task coordination and change of task set. Highest classification performance was found for targets irrespective whether all 62, 6 or 2 parietal electrodes were used. Further, higher detection performance of targets compared to standards was achieved under dual-task compared to simple-task condition in case of training on data from 2 parietal electrodes corresponding to results of ERP average analysis. Classifier transfer between tasks improves classification performance in case that training took place on more varying examples (from dual task). In summary, we showed that P300 and overlaying parietal positive ERPs can successfully be detected while subjects are performing additional ongoing motor activity. This supports single-trial detection of ERPs evoked by target events to, e.g., infer a patient's attentional state during therapeutic intervention. PMID:29636660

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

Real-time micro-vibration multi-spot synchronous measurement within a region based on heterodyne interference

NASA Astrophysics Data System (ADS)

Lan, Ma; Xiao, Wen; Chen, Zonghui; Hao, Hongliang; Pan, Feng

2018-01-01

Real-time micro-vibration measurement is widely used in engineering applications. It is very difficult for traditional optical detection methods to achieve real-time need in a relatively high frequency and multi-spot synchronous measurement of a region at the same time,especially at the nanoscale. Based on the method of heterodyne interference, an experimental system of real-time measurement of micro - vibration is constructed to satisfy the demand in engineering applications. The vibration response signal is measured by combing optical heterodyne interferometry and a high-speed CMOS-DVR image acquisition system. Then, by extracting and processing multiple pixels at the same time, four digital demodulation technique are implemented to simultaneously acquire the vibrating velocity of the target from the recorded sequences of images. Different kinds of demodulation algorithms are analyzed and the results show that these four demodulation algorithms are suitable for different interference signals. Both autocorrelation algorithm and cross-correlation algorithm meet the needs of real-time measurements. The autocorrelation algorithm demodulates the frequency more accurately, while the cross-correlation algorithm is more accurate in solving the amplitude.

A complete system for 3D reconstruction of roots for phenotypic analysis.

PubMed

Kumar, Pankaj; Cai, Jinhai; Miklavcic, Stanley J

2015-01-01

Here we present a complete system for 3D reconstruction of roots grown in a transparent gel medium or washed and suspended in water. The system is capable of being fully automated as it is self calibrating. The system starts with detection of root tips in root images from an image sequence generated by a turntable motion. Root tips are detected using the statistics of Zernike moments on image patches centred on high curvature points on root boundary and Bayes classification rule. The detected root tips are tracked in the image sequence using a multi-target tracking algorithm. Conics are fitted to the root tip trajectories using a novel ellipse fitting algorithm which weighs the data points by its eccentricity. The conics projected from the circular trajectory have a complex conjugate intersection which are image of the circular points. Circular points constraint the image of the absolute conics which are directly related to the internal parameters of the camera. The pose of the camera is computed from the image of the rotation axis and the horizon. The silhouettes of the roots and camera parameters are used to reconstruction the 3D voxel model of the roots. We show the results of real 3D reconstruction of roots which are detailed and realistic for phenotypic analysis.

Development and application of a multi-targeting reference plasmid as calibrator for analysis of five genetically modified soybean events.

PubMed

Pi, Liqun; Li, Xiang; Cao, Yiwei; Wang, Canhua; Pan, Liangwen; Yang, Litao

2015-04-01

Reference materials are important in accurate analysis of genetically modified organism (GMO) contents in food/feeds, and development of novel reference plasmid is a new trend in the research of GMO reference materials. Herein, we constructed a novel multi-targeting plasmid, pSOY, which contained seven event-specific sequences of five GM soybeans (MON89788-5', A2704-12-3', A5547-127-3', DP356043-5', DP305423-3', A2704-12-5', and A5547-127-5') and sequence of soybean endogenous reference gene Lectin. We evaluated the specificity, limit of detection and quantification, and applicability of pSOY in both qualitative and quantitative PCR analyses. The limit of detection (LOD) was as low as 20 copies in qualitative PCR, and the limit of quantification (LOQ) in quantitative PCR was 10 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and Lectin assays were higher than 90%, and the squared regression coefficients (R(2)) were more than 0.999. The quantification bias varied from 0.21% to 19.29%, and the relative standard deviations were from 1.08% to 9.84% in simulated samples analysis. All the results demonstrated that the developed multi-targeting plasmid, pSOY, was a credible substitute of matrix reference materials, and could be used as a reliable reference calibrator in the identification and quantification of multiple GM soybean events.

Multi-static networked 3D ladar for surveillance and access control

NASA Astrophysics Data System (ADS)

Wang, Y.; Ogirala, S. S. R.; Hu, B.; Le, Han Q.

2007-04-01

A theoretical design and simulation of a 3D ladar system concept for surveillance, intrusion detection, and access control is described. It is a non-conventional system architecture that consists of: i) multi-static configuration with an arbitrarily scalable number of transmitters (Tx's) and receivers (Rx's) that form an optical wireless code-division-multiple-access (CDMA) network, and ii) flexible system architecture with modular plug-and-play components that can be deployed for any facility with arbitrary topology. Affordability is a driving consideration; and a key feature for low cost is an asymmetric use of many inexpensive Rx's in conjunction with fewer Tx's, which are generally more expensive. The Rx's are spatially distributed close to the surveyed area for large coverage, and capable of receiving signals from multiple Tx's with moderate laser power. The system produces sensing information that scales as NxM, where N, M are the number of Tx's and Rx's, as opposed to linear scaling ~N in non-network system. Also, for target positioning, besides laser pointing direction and time-of-flight, the algorithm includes multiple point-of-view image fusion and triangulation for enhanced accuracy, which is not applicable to non-networked monostatic ladars. Simulation and scaled model experiments on some aspects of this concept are discussed.

A multi-view face recognition system based on cascade face detector and improved Dlib

NASA Astrophysics Data System (ADS)

Zhou, Hongjun; Chen, Pei; Shen, Wei

2018-03-01

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

[Application of network biology on study of traditional Chinese medicine].

PubMed

Tian, Sai-Sai; Yang, Jian; Zhao, Jing; Zhang, Wei-Dong

2018-01-01

With the completion of the human genome project, people have gradually recognized that the functions of the biological system are fulfilled through network-type interaction between genes, proteins and small molecules, while complex diseases are caused by the imbalance of biological processes due to a number of gene expression disorders. These have contributed to the rise of the concept of the "multi-target" drug discovery. Treatment and diagnosis of traditional Chinese medicine are based on holism and syndrome differentiation. At the molecular level, traditional Chinese medicine is characterized by multi-component and multi-target prescriptions, which is expected to provide a reference for the development of multi-target drugs. This paper reviews the application of network biology in traditional Chinese medicine in six aspects, in expectation to provide a reference to the modernized study of traditional Chinese medicine. Copyright© by the Chinese Pharmaceutical Association.

Magnetic STAR technology for real-time localization and classification of unexploded ordnance and buried mines

NASA Astrophysics Data System (ADS)

Wiegert, R. F.

2009-05-01

A man-portable Magnetic Scalar Triangulation and Ranging ("MagSTAR") technology for Detection, Localization and Classification (DLC) of unexploded ordnance (UXO) has been developed by Naval Surface Warfare Center Panama City Division (NSWC PCD) with support from the Strategic Environmental Research and Development Program (SERDP). Proof of principle of the MagSTAR concept and its unique advantages for real-time, high-mobility magnetic sensing applications have been demonstrated by field tests of a prototype man-portable MagSTAR sensor. The prototype comprises: a) An array of fluxgate magnetometers configured as a multi-tensor gradiometer, b) A GPS-synchronized signal processing system. c) Unique STAR algorithms for point-by-point, standoff DLC of magnetic targets. This paper outlines details of: i) MagSTAR theory, ii) Design and construction of the prototype sensor, iii) Signal processing algorithms recently developed to improve the technology's target-discrimination accuracy, iv) Results of field tests of the portable gradiometer system against magnetic dipole targets. The results demonstrate that the MagSTAR technology is capable of very accurate, high-speed localization of magnetic targets at standoff distances of several meters. These advantages could readily be transitioned to a wide range of defense, security and sensing applications to provide faster and more effective DLC of UXO and buried mines.

Automated Image Intelligence Adaptive Sensor Management System for High Altitude Long Endurance UAVs in a Dynamic and Anti-Access Area Denial Environment

NASA Astrophysics Data System (ADS)

Kim, Gi Young

The problem we investigate deals with an Image Intelligence (IMINT) sensor allocation schedule for High Altitude Long Endurance UAVs in a dynamic and Anti-Access Area Denial (A2AD) environment. The objective is to maximize the Situational Awareness (SA) of decision makers. The value of SA can be improved in two different ways. First, if a sensor allocated to an Areas of Interest (AOI) detects target activity, then the SA value will be increased. Second, the SA value increases if an AOI is monitored for a certain period of time, regardless of target detections. These values are functions of the sensor allocation time, sensor type and mode. Relatively few studies in the archival literature have been devoted to an analytic, detailed explanation of the target detection process, and AOI monitoring value dynamics. These two values are the fundamental criteria used to choose the most judicious sensor allocation schedule. This research presents mathematical expressions for target detection processes, and shows the monitoring value dynamics. Furthermore, the dynamics of target detection is the result of combined processes between belligerent behavior (target activity) and friendly behavior (sensor allocation). We investigate these combined processes and derive mathematical expressions for simplified cases. These closed form mathematical models can be used for Measures of Effectiveness (MOEs), i.e., target activity detection to evaluate sensor allocation schedules. We also verify these models with discrete event simulations which can also be used to describe more complex systems. We introduce several methodologies to achieve a judicious sensor allocation schedule focusing on the AOI monitoring value. The first methodology is a discrete time integer programming model which provides an optimal solution but is impractical for real world scenarios due to its computation time. Thus, it is necessary to trade off the quality of solution with computation time. The Myopic Greedy Procedure (MGP) is a heuristic which chooses the largest immediate unit time return at each decision epoch. This reduces computation time significantly, but the quality of the solution may be only 95% of optimal (for small size problems). Another alternative is a multi-start random constructive Hybrid Myopic Greedy Procedure (H-MGP), which incorporates stochastic variation in choosing an action at each stage, and repeats it a predetermined number of times (roughly 99.3% of optimal with 1000 repetitions). Finally, the One Stage Look Ahead (OSLA) procedure considers all the 'top choices' at each stage for a temporary time horizon and chooses the best action (roughly 98.8% of optimal with no repetition). Using OSLA procedure, we can have ameliorated solutions within a reasonable computation time. Other important issues discussed in this research are methodologies for the development of input parameters for real world applications.

Signal processing in SETI.

PubMed

Cullers, D K; Linscott, I R; Oliver, B M

1985-11-01

The development of a multi-channel spectrum analyzer (MCSA) for the SETI program is described. The spectrum analyzer is designed for both all-sky surveys and targeted searches. The mechanisms of the MCSA are explained and a diagram is provided. Detection of continuous wave signals, pulses, and patterns is examined.

Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

NASA Astrophysics Data System (ADS)

Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

2013-05-01

Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment.

Analytical performance of the various acquisition modes in Orbitrap MS and MS/MS.

PubMed

Kaufmann, Anton

2018-04-30

Quadrupole Orbitrap instruments (Q Orbitrap) permit high-resolution mass spectrometry (HRMS)-based full scan acquisitions and have a number of acquisition modes where the quadrupole isolates a particular mass range prior to a possible fragmentation and HRMS-based acquisition. Selecting the proper acquisition mode(s) is essential if trace analytes are to be quantified in complex matrix extracts. Depending on the particular requirements, such as sensitivity, selectivity of detection, linear dynamic range, and speed of analysis, different acquisition modes may have to be chosen. This is particularly important in the field of multi-residue analysis (e.g., pesticides or veterinary drugs in food samples) where a large number of analytes within a complex matrix have to be detected and reliably quantified. Meeting the specific detection and quantification performance criteria for every targeted compound may be challenging. It is the aim of this paper to describe the strengths and the limitations of the currently available Q Orbitrap acquisition modes. In addition, the incorporation of targeted acquisitions between full scan experiments is discussed. This approach is intended to integrate compounds that require an additional degree of sensitivity or selectivity into multi-residue methods. This article is protected by copyright. All rights reserved.

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.

A Bevel Gear Quality Inspection System Based on Multi-Camera Vision Technology.

PubMed

Liu, Ruiling; Zhong, Dexing; Lyu, Hongqiang; Han, Jiuqiang

2016-08-25

Surface defect detection and dimension measurement of automotive bevel gears by manual inspection are costly, inefficient, low speed and low accuracy. In order to solve these problems, a synthetic bevel gear quality inspection system based on multi-camera vision technology is developed. The system can detect surface defects and measure gear dimensions simultaneously. Three efficient algorithms named Neighborhood Average Difference (NAD), Circle Approximation Method (CAM) and Fast Rotation-Position (FRP) are proposed. The system can detect knock damage, cracks, scratches, dents, gibbosity or repeated cutting of the spline, etc. The smallest detectable defect is 0.4 mm × 0.4 mm and the precision of dimension measurement is about 40-50 μm. One inspection process takes no more than 1.3 s. Both precision and speed meet the requirements of real-time online inspection in bevel gear production.

Trans-rectal ultrasound visibility of prostate lesions identified by magnetic resonance imaging increases accuracy of image-fusion targeted biopsies.

PubMed

Ukimura, Osamu; Marien, Arnaud; Palmer, Suzanne; Villers, Arnauld; Aron, Manju; de Castro Abreu, Andre Luis; Leslie, Scott; Shoji, Sunao; Matsugasumi, Toru; Gross, Mitchell; Dasgupta, Prokar; Gill, Inderbir S

2015-11-01

To compare the diagnostic yield of targeted prostate biopsy using image-fusion of multi-parametric magnetic resonance (mp-MR) with real-time trans-rectal ultrasound (TRUS) for clinically significant lesions that are suspicious only on mp-MR versus lesions that are suspicious on both mp-MR and TRUS. Pre-biopsy MRI and TRUS were each scaled on a 3-point score: highly suspicious, likely, and unlikely for clinically significant cancer (sPCa). Using an MR-TRUS elastic image-fusion system (Koelis), a 127 consecutive patients with a suspicious clinically significant index lesion on pre-biopsy mp-MR underwent systematic biopsies and MR/US-fusion targeted biopsies (01/2010-09/2013). Biopsy histological outcomes were retrospectively compared with MR suspicion level and TRUS-visibility of the MR-suspicious lesion. sPCa was defined as biopsy Gleason score ≥7 and/or maximum cancer core length ≥5 mm. Targeted biopsies outperformed systematic biopsies in overall cancer detection rate (61 vs. 41 %; p = 0.007), sPCa detection rate (43 vs. 23 %; p = 0.0013), cancer core length (7.5 vs. 3.9 mm; p = 0.0002), and cancer rate per core (56 vs. 12 %; p < 0.0001), respectively. Highly suspicious lesions on mp-MR correlated with higher positive biopsy rate (p < 0.0001), higher Gleason score (p = 0.018), and greater cancer core length (p < 0.0001). Highly suspicious lesions on TRUS in corresponding to MR-suspicious lesion had a higher biopsy yield (p < 0.0001) and higher sPCa detection rate (p < 0.0001). Since majority of MR-suspicious lesions were also suspicious on TRUS, TRUS-visibility allowed selection of the specific MR-visible lesion which should be targeted from among the multiple TRUS suspicious lesions in each prostate. MR-TRUS fusion-image-guided biopsies outperformed systematic biopsies. TRUS-visibility of a MR-suspicious lesion facilitates image-guided biopsies, resulting in higher detection of significant cancer.

Minimizing the Disruptive Effects of Prospective Memory in Simulated Air Traffic Control

PubMed Central

Loft, Shayne; Smith, Rebekah E.; Remington, Roger

2015-01-01

Prospective memory refers to remembering to perform an intended action in the future. Failures of prospective memory can occur in air traffic control. In two experiments, we examined the utility of external aids for facilitating air traffic management in a simulated air traffic control task with prospective memory requirements. Participants accepted and handed-off aircraft and detected aircraft conflicts. The prospective memory task involved remembering to deviate from a routine operating procedure when accepting target aircraft. External aids that contained details of the prospective memory task appeared and flashed when target aircraft needed acceptance. In Experiment 1, external aids presented either adjacent or non-adjacent to each of the 20 target aircraft presented over the 40min test phase reduced prospective memory error by 11% compared to a condition without external aids. In Experiment 2, only a single target aircraft was presented a significant time (39min–42min) after presentation of the prospective memory instruction, and the external aids reduced prospective memory error by 34%. In both experiments, costs to the efficiency of non-prospective memory air traffic management (non-target aircraft acceptance response time, conflict detection response time) were reduced by non-adjacent aids compared to no aids or adjacent aids. In contrast, in both experiments, the efficiency of the prospective memory air traffic management (target aircraft acceptance response time) was facilitated by adjacent aids compared to non-adjacent aids. Together, these findings have potential implications for the design of automated alerting systems to maximize multi-task performance in work settings where operators monitor and control demanding perceptual displays. PMID:24059825

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing

NASA Astrophysics Data System (ADS)

Kerekes, John P.; Presnar, Michael D.; Fourspring, Kenneth D.; Ninkov, Zoran; Pogorzala, David R.; Raisanen, Alan D.; Rice, Andrew C.; Vasquez, Juan R.; Patel, Jeffrey P.; MacIntyre, Robert T.; Brown, Scott D.

2009-05-01

A novel multi-object spectrometer (MOS) is being explored for use as an adaptive performance-driven sensor that tracks moving targets. Developed originally for astronomical applications, the instrument utilizes an array of micromirrors to reflect light to a panchromatic imaging array. When an object of interest is detected the individual micromirrors imaging the object are tilted to reflect the light to a spectrometer to collect a full spectrum. This paper will present example sensor performance from empirical data collected in laboratory experiments, as well as our approach in designing optical and radiometric models of the MOS channels and the micromirror array. Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor. Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

Multi-capillary based optical sensors for highly sensitive protein detection

NASA Astrophysics Data System (ADS)

Okuyama, Yasuhira; Katagiri, Takashi; Matsuura, Yuji

2017-04-01

A fluorescence measuring method based on glass multi-capillary for detecting trace amounts of proteins is proposed. It promises enhancement of sensitivity due to effects of the adsorption area expansion and the longitudinal excitation. The sensitivity behavior of this method was investigated by using biotin-streptavidin binding. According to experimental examinations, it was found that the sensitivity was improved by a factor of 70 from common glass wells. We also confirmed our measuring system could detect 1 pg/mL of streptavidin. These results suggest that multi-capillary has a potential as a high-sensitive biosensor.

A Practical Millimeter-Wave Holographic Imaging System with Tunable IF Attenuator

NASA Astrophysics Data System (ADS)

Zhu, Yu-Kun; Yang, Ming-Hui; Wu, Liang; Sun, Yun; Sun, Xiao-Wei

2017-10-01

A practical millimeter-wave (mmw) holographic imaging system with tunable intermediate frequency (IF) attenuator has been developed. It can be used for the detection of concealed weapons at security checkpoints, especially the airport. The system is utilized to scan the passenger and detect the weapons hidden in the clothes. To reconstruct the three dimensions (3-D) image, a holographic mmw imaging algorithm based on aperture synthesis and back scattering is presented. The system is active and works at 28-33 GHz. Tunable IF attenuator is applied to compensate the intensity and phase differences between multi-channels and multi-frequencies.

Chandra Interactive Analysis of Observations (CIAO)

NASA Technical Reports Server (NTRS)

Dobrzycki, Adam

2000-01-01

The Chandra (formerly AXAF) telescope, launched on July 23, 1999, provides X-rays data with unprecedented spatial and spectral resolution. As part of the Chandra scientific support, the Chandra X-ray Observatory Center provides a new data analysis system, CIAO ("Chandra Interactive Analysis of Observations"). We will present the main components of the system: "First Look" analysis; SHERPA: a multi-dimensional, multi-mission modeling and fitting application; Chandra Imaging and Plotting System; Detect package-source detection algorithms; and DM package generic data manipulation tools, We will set up a demonstration of the portable version of the system and show examples of Chandra Data Analysis.

Disposable Multi-Sensor Unattended Ground Sensor Systems for Detecting Personnel (Systemes de detection multi-capteurs terrestres autonome destines a detecter du personnel)

DTIC Science & Technology

2015-02-01

du personnel » (SET-158 RTG) identifient et accèdent aux technologies potentielles de détection des personnes, qui améliorent la sécurité par...croissante de systèmes de détection à distance, qui soient robustes et de haute performance afin d’assurer la surveillance et l’acquisition des ...les caméras basse et haute résolution. Dans la seconde phase, des approches de phénoménologie des capteurs et de traitement du

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning.

PubMed

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multi-atlas-based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

Parallel detection experiment of fluorescence confocal microscopy using DMD.

PubMed

Wang, Qingqing; Zheng, Jihong; Wang, Kangni; Gui, Kun; Guo, Hanming; Zhuang, Songlin

2016-05-01

Parallel detection of fluorescence confocal microscopy (PDFCM) system based on Digital Micromirror Device (DMD) is reported in this paper in order to realize simultaneous multi-channel imaging and improve detection speed. DMD is added into PDFCM system, working to take replace of the single traditional pinhole in the confocal system, which divides the laser source into multiple excitation beams. The PDFCM imaging system based on DMD is experimentally set up. The multi-channel image of fluorescence signal of potato cells sample is detected by parallel lateral scanning in order to verify the feasibility of introducing the DMD into fluorescence confocal microscope. In addition, for the purpose of characterizing the microscope, the depth response curve is also acquired. The experimental result shows that in contrast to conventional microscopy, the DMD-based PDFCM system has higher axial resolution and faster detection speed, which may bring some potential benefits in the biology and medicine analysis. SCANNING 38:234-239, 2016. © 2015 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

PubMed

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

PubMed Central

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Present situation and trend of precision guidance technology and its intelligence

NASA Astrophysics Data System (ADS)

Shang, Zhengguo; Liu, Tiandong

2017-11-01

This paper first introduces the basic concepts of precision guidance technology and artificial intelligence technology. Then gives a brief introduction of intelligent precision guidance technology, and with the help of development of intelligent weapon based on deep learning project in foreign: LRASM missile project, TRACE project, and BLADE project, this paper gives an overview of the current foreign precision guidance technology. Finally, the future development trend of intelligent precision guidance technology is summarized, mainly concentrated in the multi objectives, intelligent classification, weak target detection and recognition, intelligent between complex environment intelligent jamming and multi-source, multi missile cooperative fighting and other aspects.

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

NASA Tech Briefs, January 2013

NASA Technical Reports Server (NTRS)

2013-01-01

Topics include: Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector; Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators; 3D Hail Size Distribution Interpolation/Extrapolation Algorithm; Color-Changing Sensors for Detecting the Presence of Hypergolic Fuels; Artificial Intelligence Software for Assessing Postural Stability; Transformers: Shape-Changing Space Systems Built with Robotic Textiles; Fibrillar Adhesive for Climbing Robots; Using Pre-Melted Phase Change Material to Keep Payloads in Space Warm for Hours without Power; Development of a Centrifugal Technique for the Microbial Bioburden Analysis of Freon (CFC-11); Microwave Sinterator Freeform Additive Construction System (MS-FACS); DSP/FPGA Design for a High-Speed Programmable S-Band Space Transceiver; On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers; FPGA Vision Data Architecture; Memory Circuit Fault Simulator; Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination; Regolith Advanced Surface Systems Operations Robot Excavator; Magnetically Actuated Seal; Hybrid Electrostatic/Flextensional Mirror for Lightweight, Large-Aperture, and Cryogenic Space Telescopes; System for Contributing and Discovering Derived Mission and Science Data; Remote Viewer for Maritime Robotics Software; Stackfile Database; Reachability Maps for In Situ Operations; JPL Space Telecommunications Radio System Operating Environment; RFI-SIM: RFI Simulation Package; ION Configuration Editor; Dtest Testing Software; IMPaCT - Integration of Missions, Programs, and Core Technologies; Integrated Systems Health Management (ISHM) Toolkit; Wind-Driven Wireless Networked System of Mobile Sensors for Mars Exploration; In Situ Solid Particle Generator; Analysis of the Effects of Streamwise Lift Distribution on Sonic Boom Signature; Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments; Towed Subsurface Optical Communications Buoy; High-Collection-Efficiency Fluorescence Detection Cell; Ultra-Compact, Superconducting Spectrometer-on-a-Chip at Submillimeter Wavelengths; UV Resonant Raman Spectrometer with Multi-Line Laser Excitation; Medicine Delivery Device with Integrated Sterilization and Detection; Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME; Airborne Tomographic Swath Ice Sounding Processing System; flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter; Estimating Torque Imparted on Spacecraft Using Telemetry; PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils; Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences; Metric Learning to Enhance Hyperspectral Image Segmentation; Basic Operational Robotics Instructional System; Sheet Membrane Spacesuit Water Membrane Evaporator; Advanced Materials and Manufacturing for Low-Cost, High-Performance Liquid Rocket Combustion Chambers; Motor Qualification for Long-Duration Mars Missions.

Navy Acquisition: Development of the AN/BSY-1 Combat System

DTIC Science & Technology

1992-01-01

AN/BSY-1, a computer-based combat system, is designed to detect, classify, track, and launch weapons at enemy surface, subsurface, and land targets. The Navy expects the AN/BSY-1 system to locate targets sooner than previous systems, allow operators to perform multiple tasks and address multiple targets concurrently, and reduce the time between detecting a target and launching weapons. The Navy has contracted with the International Business Machines (IBM) Corporation for 23 AN/BSY-1 systems, maintenance and operational trainers, and a software

High-power VCSELs for smart munitions

NASA Astrophysics Data System (ADS)

Geske, Jon; MacDougal, Michael; Cole, Garrett; Snyder, Donald

2006-08-01

The next generation of low-cost smart munitions will be capable of autonomously detecting and identifying targets aided partly by the ability to image targets with compact and robust scanning rangefinder and LADAR capabilities. These imaging systems will utilize arrays of high performance, low-cost semiconductor diode lasers capable of achieving high peak powers in pulses ranging from 5 to 25 nanoseconds in duration. Aerius Photonics is developing high-power Vertical-Cavity Surface-Emitting Lasers (VCSELs) to meet the needs of these smart munitions applications. The authors will report the results of Aerius' development program in which peak pulsed powers exceeding 60 Watts were demonstrated from single VCSEL emitters. These compact packaged emitters achieved pulse energies in excess of 1.5 micro-joules with multi kilo-hertz pulse repetition frequencies. The progress of the ongoing effort toward extending this performance to arrays of VCSEL emitters and toward further improving laser slope efficiency will be reported.

Nanoparticle imaging probes for molecular imaging with computed tomography and application to cancer imaging

NASA Astrophysics Data System (ADS)

Roeder, Ryan K.; Curtis, Tyler E.; Nallathamby, Prakash D.; Irimata, Lisa E.; McGinnity, Tracie L.; Cole, Lisa E.; Vargo-Gogola, Tracy; Cowden Dahl, Karen D.

2017-03-01

Precision imaging is needed to realize precision medicine in cancer detection and treatment. Molecular imaging offers the ability to target and identify tumors, associated abnormalities, and specific cell populations with overexpressed receptors. Nuclear imaging and radionuclide probes provide high sensitivity but subject the patient to a high radiation dose and provide limited spatiotemporal information, requiring combined computed tomography (CT) for anatomic imaging. Therefore, nanoparticle contrast agents have been designed to enable molecular imaging and improve detection in CT alone. Core-shell nanoparticles provide a powerful platform for designing tailored imaging probes. The composition of the core is chosen for enabling strong X-ray contrast, multi-agent imaging with photon-counting spectral CT, and multimodal imaging. A silica shell is used for protective, biocompatible encapsulation of the core composition, volume-loading fluorophores or radionuclides for multimodal imaging, and facile surface functionalization with antibodies or small molecules for targeted delivery. Multi-agent (k-edge) imaging and quantitative molecular imaging with spectral CT was demonstrated using current clinical agents (iodine and BaSO4) and a proposed spectral library of contrast agents (Gd2O3, HfO2, and Au). Bisphosphonate-functionalized Au nanoparticles were demonstrated to enhance sensitivity and specificity for the detection of breast microcalcifications by conventional radiography and CT in both normal and dense mammary tissue using murine models. Moreover, photon-counting spectral CT enabled quantitative material decomposition of the Au and calcium signals. Immunoconjugated Au@SiO2 nanoparticles enabled highly-specific targeting of CD133+ ovarian cancer stem cells for contrast-enhanced detection in model tumors.

Cell-Specific Multifunctional Processing of Heterogeneous Cell Systems in a Single Laser Pulse Treatment

PubMed Central

Lukianova-Hleb, Ekaterina Y.; Mutonga, Martin B. G.; Lapotko, Dmitri O.

2012-01-01

Current methods of cell processing for gene and cell therapies use several separate procedures for gene transfer and cell separation or elimination, because no current technology can offer simultaneous multi-functional processing of specific cell sub-sets in highly heterogeneous cell systems. Using the cell-specific generation of plasmonic nanobubbles of different sizes around cell-targeted gold nanoshells and nanospheres, we achieved simultaneous multifunctional cell-specific processing in a rapid single 70 ps laser pulse bulk treatment of heterogeneous cell suspension. This method supported the detection of cells, delivery of external molecular cargo to one type of cells and the concomitant destruction of another type of cells without damaging other cells in suspension, and real-time guidance of the two above cellular effects. PMID:23167546

A real-time tracking system of infrared dim and small target based on FPGA and DSP

NASA Astrophysics Data System (ADS)

Rong, Sheng-hui; Zhou, Hui-xin; Qin, Han-lin; Wang, Bing-jian; Qian, Kun

2014-11-01

A core technology in the infrared warning system is the detection tracking of dim and small targets with complicated background. Consequently, running the detection algorithm on the hardware platform has highly practical value in the military field. In this paper, a real-time detection tracking system of infrared dim and small target which is used FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) as the core was designed and the corresponding detection tracking algorithm and the signal flow is elaborated. At the first stage, the FPGA obtain the infrared image sequence from the sensor, then it suppresses background clutter by mathematical morphology method and enhances the target intensity by Laplacian of Gaussian operator. At the second stage, the DSP obtain both the original image and the filtered image form the FPGA via the video port. Then it segments the target from the filtered image by an adaptive threshold segmentation method and gets rid of false target by pipeline filter. Experimental results show that our system can achieve higher detection rate and lower false alarm rate.

Sequential Adaptive Multi-Modality Target Detection and Classification Using Physics Based Models

DTIC Science & Technology

2006-09-01

estimation," R. Raghuram, R. Raich and A.O. Hero, IEEE Intl. Conf. on Acoustics, Speech , and Signal Processing, Toulouse France, June 2006, <http...can then be solved using off-the-shelf classifiers such as radial basis functions, SVM, or kNN classifier structures. When applied to mine detection we...stage waveform selection for adaptive resource constrained state estimation," 2006 IEEE Intl. Conf. on Acoustics, Speech , and Signal Processing

Distinguishing Different Strategies of Across-Dimension Attentional Selection

ERIC Educational Resources Information Center

Huang, Liqiang; Pashler, Harold

2012-01-01

Selective attention in multidimensional displays has usually been examined using search tasks requiring the detection of a single target. We examined the ability to perceive a spatial structure in multi-item subsets of a display that were defined either conjunctively or disjunctively. Observers saw two adjacent displays and indicated whether the…

Identification of New Drug Targets in Multi-Drug Resistant Bacterial Infections

DTIC Science & Technology

2012-10-01

readout from malachite green, which detects the presence of inorganic phosphate with a simple color change. We have performed preliminary tests, however...SK requires ATP as a co-factor, which substantially increases the background by reacting with the malachite green. For the coupled reaction of SK

Carbon Nanotube Nanoelectrode Array as an Electronic Chip for Ultrasensitive Label-free DNA Detection

NASA Technical Reports Server (NTRS)

Li, Jun; Koehne, Jessica; Chen, Hua; Cassell, Alan; Ng, Hou Tee; Fan, Wendy; Ye, Qi; Han, Jie; Meyyappan, M.

2003-01-01

A reliable nanoelectrode array based on vertically aligned multi-walled carbon nanotubes (MWNTs) embedded in SiO2 is used for ultrasensitive DNA detection. Characteristic nanoelectrode behavior is observed using low-density MWNT arrays for measuring both bulk and surface immobilized redox species such as K4Fe(CN)6 and ferrocene derivatives. The open-end of MWNTs are found to present similar properties as graphite edge-plane electrodes with wide potential window, flexible chemical functionalities, and good biocompatibility. BRCA1 related oligonucleotide probes with 18 bp are selectively functionalized at the open ends of the nanotube array and specifically hybridized with oligonucleotide targets incorporated with a polyG tag. The guanine groups are employed as the signal moieties in the electrochemical measurements. R(bpy)(sup 2+, sub 3) mediator is used to further amplify the guanine oxidation signal. The hybridization of sub-attomoles of DNA targets is detected electrochemically by combining the MWNT nanoelectrode array with the R(bpy)(sup 2+, sub 3) amplification mechanism. This technique was employed for direct electrochemical detection of label-free PCR amplicon from a healthy donor through specific hybridization with the BRCA1 probe. The detection limit is estimated to be less than 1000 DNA molecules since abundant guanine bases in the PCR amplicon provides a large signal. This system provides a general platform for rapid molecular diagnostics in applications requiring ultrahigh sensitivity, high-degree of miniaturization, and simple sample preparation, and low-cost operation.

A Multi-Level Decision Fusion Strategy for Condition Based Maintenance of Composite Structures

PubMed Central

Sharif Khodaei, Zahra; Aliabadi, M.H.

2016-01-01

In this work, a multi-level decision fusion strategy is proposed which weighs the Value of Information (VoI) against the intended functions of a Structural Health Monitoring (SHM) system. This paper presents a multi-level approach for three different maintenance strategies in which the performance of the SHM systems is evaluated against its intended functions. Level 1 diagnosis results in damage existence with minimum sensors covering a large area by finding the maximum energy difference for the guided waves propagating in pristine structure and the post-impact state; Level 2 diagnosis provides damage detection and approximate localization using an approach based on Electro-Mechanical Impedance (EMI) measures, while Level 3 characterizes damage (exact location and size) in addition to its detection by utilising a Weighted Energy Arrival Method (WEAM). The proposed multi-level strategy is verified and validated experimentally by detection of Barely Visible Impact Damage (BVID) on a curved composite fuselage panel. PMID:28773910

Focused ultrasound: concept for automated transcutaneous control of hemorrhage in austere settings.

PubMed

Kucewicz, John C; Bailey, Michael R; Kaczkowski, Peter J; Carter, Stephen J

2009-04-01

High intensity focused ultrasound (HIFU) is being developed for a range of clinical applications. Of particular interest to NASA and the military is the use of HIFU for traumatic injuries because HIFU has the unique ability to transcutaneously stop bleeding. Automation of this technology would make possible its use in remote, austere settings by personnel not specialized in medical ultrasound. Here a system to automatically detect and target bleeding is tested and reported. The system uses Doppler ultrasound images from a clinical ultrasound scanner for bleeding detection and hardware for HIFU therapy. The system was tested using a moving string to simulate blood flow and targeting was visualized by Schlieren imaging to show the focusing of the HIFU acoustic waves. When instructed by the operator, a Doppler ultrasound image is acquired and processed to detect and localize the moving string, and the focus of the HIFU array is electronically adjusted to target the string. Precise and accurate targeting was verified in the Schlieren images. An automated system to detect and target simulated bleeding has been built and tested. The system could be combined with existing algorithms to detect, target, and treat clinical bleeding.

Towards large scale multi-target tracking

NASA Astrophysics Data System (ADS)

Vo, Ba-Ngu; Vo, Ba-Tuong; Reuter, Stephan; Lam, Quang; Dietmayer, Klaus

2014-06-01

Multi-target tracking is intrinsically an NP-hard problem and the complexity of multi-target tracking solutions usually do not scale gracefully with problem size. Multi-target tracking for on-line applications involving a large number of targets is extremely challenging. This article demonstrates the capability of the random finite set approach to provide large scale multi-target tracking algorithms. In particular it is shown that an approximate filter known as the labeled multi-Bernoulli filter can simultaneously track one thousand five hundred targets in clutter on a standard laptop computer.

Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.

Evaluation of two-stage system for neutron measurement aiming at increase in count rate at Japan Atomic Energy Agency-Fusion Neutronics Source

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

Shinohara, K., E-mail: shinohara.koji@jaea.go.jp; Ochiai, K.; Sukegawa, A.

In order to increase the count rate capability of a neutron detection system as a whole, we propose a multi-stage neutron detection system. Experiments to test the effectiveness of this concept were carried out on Fusion Neutronics Source. Comparing four configurations of alignment, it was found that the influence of an anterior stage on a posterior stage was negligible for the pulse height distribution. The two-stage system using 25 mm thickness scintillator was about 1.65 times the count rate capability of a single detector system for d-D neutrons and was about 1.8 times the count rate capability for d-T neutrons.more » The results suggested that the concept of a multi-stage detection system will work in practice.« less

MultiMiTar: a novel multi objective optimization based miRNA-target prediction method.

PubMed

Mitra, Ramkrishna; Bandyopadhyay, Sanghamitra

2011-01-01

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm.

Multi-stage separations based on dielectrophoresis

DOEpatents

Mariella, Jr., Raymond P.

2004-07-13

A system utilizing multi-stage traps based on dielectrophoresis. Traps with electrodes arranged transverse to the flow and traps with electrodes arranged parallel to the flow with combinations of direct current and alternating voltage are used to trap, concentrate, separate, and/or purify target particles.

Minor Body Surveyor: A Multi-Object, High Speed, Spectro-Photometer Space Mission System Employing Wide-Area Intelligent Change Detection

NASA Astrophysics Data System (ADS)

Kaplan, M. L.; van Cleve, J. E.; Alcock, C.

2003-12-01

Detection and characterization of the small bodies of the outer solar system presents unique challenges to terrestrial based sensing systems, principally the inverse 4th power decrease of reflected and thermal signals with target distance from the Sun. These limits are surpassed by new techniques [1,2,3] employing star-object occultation event sensing, which are capable of detecting sub-kilometer objects in the Kuiper Belt and Oort cloud. This poster will present an instrument and space mission concept based on adaptations of the NASA Discovery Kepler program currently in development at Ball Aerospace and Technologies Corp. Instrument technologies to enable this space science mission are being pursued and will be described. In particular, key attributes of an optimized payload include the ability to provide: 1) Coarse spectral resolution (using an objective spectrometer approach) 2) Wide FOV, simultaneous object monitoring (up to 150,000 stars employing select data regions within a large focal plane mosaic) 3) Fast temporal frame integration and readout architectures (10 to 50 msec for each monitored object) 4) Real-time, intelligent change detection processing (to limit raw data volumes) The Minor Body Surveyor combines the focal plane and processing technology elements into a densely packaged format to support general space mission issues of mass and power consumption, as well as telemetry resources. Mode flexibility is incorporated into the real-time processing elements to allow for either temporal (Occultations) or spatial (Moving targets) change detection. In addition, a basic image capture mode is provided for general pointing and field reference measurements. The overall space mission architecture is described as well. [1] M. E. Bailey. Can 'Invisible' Bodies be Observed in the Solar System. Nature, 259:290-+, January 1976. [2] T. S. Axelrod, C. Alcock, K. H. Cook, and H.-S. Park. A Direct Census of the Oort Cloud with a Robotic Telescope. In ASP Conf. Ser. 34: Robotic Telescopes in the 1990s, pages 171-181, 1992. [3] F. Roques and M. Moncuquet. A Detection Method for Small Kuiper Belt Objects: The Search for Stellar Occultations. Icarus, 147:530-544, October 2000.

Identifying EGFR-Expressed Cells and Detecting EGFR Multi-Mutations at Single-Cell Level by Microfluidic Chip

NASA Astrophysics Data System (ADS)

Li, Ren; Zhou, Mingxing; Li, Jine; Wang, Zihua; Zhang, Weikai; Yue, Chunyan; Ma, Yan; Peng, Hailin; Wei, Zewen; Hu, Zhiyuan

2018-03-01

EGFR mutations companion diagnostics have been proved to be crucial for the efficacy of tyrosine kinase inhibitor targeted cancer therapies. To uncover multiple mutations occurred in minority of EGFR-mutated cells, which may be covered by the noises from majority of un-mutated cells, is currently becoming an urgent clinical requirement. Here we present the validation of a microfluidic-chip-based method for detecting EGFR multi-mutations at single-cell level. By trapping and immunofluorescently imaging single cells in specifically designed silicon microwells, the EGFR-expressed cells were easily identified. By in situ lysing single cells, the cell lysates of EGFR-expressed cells were retrieved without cross-contamination. Benefited from excluding the noise from cells without EGFR expression, the simple and cost-effective Sanger's sequencing, but not the expensive deep sequencing of the whole cell population, was used to discover multi-mutations. We verified the new method with precisely discovering three most important EGFR drug-related mutations from a sample in which EGFR-mutated cells only account for a small percentage of whole cell population. The microfluidic chip is capable of discovering not only the existence of specific EGFR multi-mutations, but also other valuable single-cell-level information: on which specific cells the mutations occurred, or whether different mutations coexist on the same cells. This microfluidic chip constitutes a promising method to promote simple and cost-effective Sanger's sequencing to be a routine test before performing targeted cancer therapy.[Figure not available: see fulltext.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

PubMed

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

PubMed Central

Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-01-01

Background Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. Methodology We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. Conclusions This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. PMID:21445339

Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

PubMed

Zhang, Zhen; Ma, Cheng; Zhu, Rong

2016-10-14

High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

Fault detection of helicopter gearboxes using the multi-valued influence matrix method

NASA Technical Reports Server (NTRS)

Chin, Hsinyung; Danai, Kourosh; Lewicki, David G.

1993-01-01

In this paper we investigate the effectiveness of a pattern classifying fault detection system that is designed to cope with the variability of fault signatures inherent in helicopter gearboxes. For detection, the measurements are monitored on-line and flagged upon the detection of abnormalities, so that they can be attributed to a faulty or normal case. As such, the detection system is composed of two components, a quantization matrix to flag the measurements, and a multi-valued influence matrix (MVIM) that represents the behavior of measurements during normal operation and at fault instances. Both the quantization matrix and influence matrix are tuned during a training session so as to minimize the error in detection. To demonstrate the effectiveness of this detection system, it was applied to vibration measurements collected from a helicopter gearbox during normal operation and at various fault instances. The results indicate that the MVIM method provides excellent results when the full range of faults effects on the measurements are included in the training set.

EDITORIAL: Imaging systems and techniques Imaging systems and techniques

NASA Astrophysics Data System (ADS)

Yang, Wuqiang; Giakos, George; Nikita, Konstantina; Pastorino, Matteo; Karras, Dimitrios

2009-10-01

The papers in this special issue focus on providing the state-of-the-art approaches and solutions to some of the most challenging imaging areas, such as the design, development, evaluation and applications of imaging systems, measuring techniques, image processing algorithms and instrumentation, with an ultimate aim of enhancing the measurement accuracy and image quality. This special issue explores the principles, engineering developments and applications of new imaging systems and techniques, and encourages broad discussion of imaging methodologies, shaping the future and identifying emerging trends. The multi-faceted field of imaging requires drastic adaptation to the rapid changes in our society, economy, environment and technological evolution. There is an urgent need to address new problems, which tend to be either static but complex, or dynamic, e.g. rapidly evolving with time, with many unknowns, and to propose innovative solutions. For instance, the battles against cancer and terror, monitoring of space resources and enhanced awareness, management of natural resources and environmental monitoring are some of the areas that need to be addressed. The complexity of the involved imaging scenarios and demanding design parameters, e.g. speed, signal-to-noise ratio (SNR), specificity, contrast, spatial resolution, scatter rejection, complex background and harsh environments, necessitate the development of a multi-functional, scalable and efficient imaging suite of sensors, solutions driven by innovation, and operation on diverse detection and imaging principles. Efficient medical imaging techniques capable of providing physiological information at the molecular level present another important research area. Advanced metabolic and functional imaging techniques, operating on multiple physical principles, and using high-resolution, high-selectivity nano-imaging methods, quantum dots, nanoparticles, biomarkers, nanostructures, nanosensors, micro-array imaging chips and nano-clinics for optical diagnostics and targeted therapy, can play an important role in the diagnosis and treatment of cancer. These techniques can also be used to provide efficient drug delivery for treatment of other diseases, with increased sensitivity and specificity. Similarly, enhanced stand-off detection, classification, identification and surveillance techniques, for comprehensive civilian and military target protection and enhanced space situational awareness can open new frontiers of research and applications in the defence arena and homeland security. For instance, the development of potential imaging sensor architectures, enhanced remote sensing systems, ladars, lidars and radars can provide data capable of ensuring continuous monitoring of various imaging/physical/chemical parameters under different operating conditions, using both active and passive detection principles, reconfigurable and scalable focal plane array architectures, reliable systems for stand-off detection of explosives, and enhanced airport security. The above areas pose challenging problems to the technical community and indicate an ever-growing need for innovative and auspicious solutions. We would like to thank all authors for their valuable contributions, without which this special issue would not have become reality.

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.

Methods, compounds and systems for detecting a microorganism in a sample

DOEpatents

Colston, Jr, Bill W.; Fitch, J. Patrick; Gardner, Shea N.; Williams, Peter L.; Wagner, Mark C.

2016-09-06

Methods to identify a set of probe polynucleotides suitable for detecting a set of targets and in particular methods for identification of primers suitable for detection of target microorganisms related polynucleotides, set of polynucleotides and compositions, and related methods and systems for detection and/or identification of microorganisms in a sample.

The Human Kinome Targeted by FDA Approved Multi-Target Drugs and Combination Products: A Comparative Study from the Drug-Target Interaction Network Perspective.

PubMed

Li, Ying Hong; Wang, Pan Pan; Li, Xiao Xu; Yu, Chun Yan; Yang, Hong; Zhou, Jin; Xue, Wei Wei; Tan, Jun; Zhu, Feng

2016-01-01

The human kinome is one of the most productive classes of drug target, and there is emerging necessity for treating complex diseases by means of polypharmacology (multi-target drugs and combination products). However, the advantages of the multi-target drugs and the combination products are still under debate. A comparative analysis between FDA approved multi-target drugs and combination products, targeting the human kinome, was conducted by mapping targets onto the phylogenetic tree of the human kinome. The approach of network medicine illustrating the drug-target interactions was applied to identify popular targets of multi-target drugs and combination products. As identified, the multi-target drugs tended to inhibit target pairs in the human kinome, especially the receptor tyrosine kinase family, while the combination products were able to against targets of distant homology relationship. This finding asked for choosing the combination products as a better solution for designing drugs aiming at targets of distant homology relationship. Moreover, sub-networks of drug-target interactions in specific disease were generated, and mechanisms shared by multi-target drugs and combination products were identified. In conclusion, this study performed an analysis between approved multi-target drugs and combination products against the human kinome, which could assist the discovery of next generation polypharmacology.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information.

PubMed

Wang, Chundong; Zhu, Likun; Gong, Liangyi; Zhao, Zhentang; Yang, Lei; Liu, Zheli; Cheng, Xiaochun

2018-03-15

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information

PubMed Central

Wang, Chundong; Zhao, Zhentang; Yang, Lei; Liu, Zheli; Cheng, Xiaochun

2018-01-01

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks. PMID:29543773

Graphene Oxide/Silver Nanohybrid as Multi-functional Material for Highly Efficient Bacterial Disinfection and Detection of Organic Dye

NASA Astrophysics Data System (ADS)

Tam, Le Thi; Dinh, Ngo Xuan; Van Cuong, Nguyen; Van Quy, Nguyen; Huy, Tran Quang; Ngo, Duc-The; Mølhave, Kristian; Le, Anh-Tuan

2016-10-01

In this work, a multi-functional hybrid system consisting of graphene oxide and silver nanoparticles (GO-Ag NPs) was successfully synthesized by using a two-step chemical process. We firstly demonstrated noticeable bactericidal ability of the GO-Ag hybrid system. We provide more chemo-physical evidence explaining the antibacterial behavior of GO-Ag nanohybrid against Gram-negative Escherichia Coli and Gram-positive Staphylococcus aureus in light of ultrastructural damage analyses and Ag1+ ions release rate onto the cells/medium. A further understanding of the mode of antimicrobial action is very important for designing and developing advanced antimicrobial systems. Secondly, we have also demonstrated that the GO-Ag nanohybrid material could be used as a potential surface enhanced Raman scattering (SERS) substrate to detect and quantify organic dyes, e.g., methylene blue (MB), in aqueous media. Our findings revealed that the GO-Ag hybrid system showed better SERS performance of MB detection than that of pure Ag-NPs. MB could be detected at a concentration as low as 1 ppm. The GO-Ag-based SERS platform can be effectively used to detect trace concentrations of various types of organic dyes in aqueous media. With the aforementioned properties, the GO-Ag hybrid system is found to be very promising as a multi-functional material for advanced biomedicine and environmental monitoring applications.

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

PubMed

Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

2009-01-01

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

Integrated multisensor perimeter detection systems

NASA Astrophysics Data System (ADS)

Kent, P. J.; Fretwell, P.; Barrett, D. J.; Faulkner, D. A.

2007-10-01

The report describes the results of a multi-year programme of research aimed at the development of an integrated multi-sensor perimeter detection system capable of being deployed at an operational site. The research was driven by end user requirements in protective security, particularly in threat detection and assessment, where effective capability was either not available or prohibitively expensive. Novel video analytics have been designed to provide robust detection of pedestrians in clutter while new radar detection and tracking algorithms provide wide area day/night surveillance. A modular integrated architecture based on commercially available components has been developed. A graphical user interface allows intuitive interaction and visualisation with the sensors. The fusion of video, radar and other sensor data provides the basis of a threat detection capability for real life conditions. The system was designed to be modular and extendable in order to accommodate future and legacy surveillance sensors. The current sensor mix includes stereoscopic video cameras, mmWave ground movement radar, CCTV and a commercially available perimeter detection cable. The paper outlines the development of the system and describes the lessons learnt after deployment in a pilot trial.

Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data.

PubMed

Chung, Dongjun; Kuan, Pei Fen; Li, Bo; Sanalkumar, Rajendran; Liang, Kun; Bresnick, Emery H; Dewey, Colin; Keleş, Sündüz

2011-07-01

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip) as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads). This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads). Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.

Development of a 3D ultrasound-guided prostate biopsy system

NASA Astrophysics Data System (ADS)

Cool, Derek; Sherebrin, Shi; Izawa, Jonathan; Fenster, Aaron

2007-03-01

Biopsy of the prostate using ultrasound guidance is the clinical gold standard for diagnosis of prostate adenocarinoma. However, because early stage tumors are rarely visible under US, the procedure carries high false-negative rates and often patients require multiple biopsies before cancer is detected. To improve cancer detection, it is imperative that throughout the biopsy procedure, physicians know where they are within the prostate and where they have sampled during prior biopsies. The current biopsy procedure is limited to using only 2D ultrasound images to find and record target biopsy core sample sites. This information leaves ambiguity as the physician tries to interpret the 2D information and apply it to their 3D workspace. We have developed a 3D ultrasound-guided prostate biopsy system that provides 3D intra-biopsy information to physicians for needle guidance and biopsy location recording. The system is designed to conform to the workflow of the current prostate biopsy procedure, making it easier for clinical integration. In this paper, we describe the system design and validate its accuracy by performing an in vitro biopsy procedure on US/CT multi-modal patient-specific prostate phantoms. A clinical sextant biopsy was performed by a urologist on the phantoms and the 3D models of the prostates were generated with volume errors less than 4% and mean boundary errors of less than 1 mm. Using the 3D biopsy system, needles were guided to within 1.36 +/- 0.83 mm of 3D targets and the position of the biopsy sites were accurately localized to 1.06 +/- 0.89 mm for the two prostates.

Multi-kilobase homozygous targeted gene replacement in human induced pluripotent stem cells.

PubMed

Byrne, Susan M; Ortiz, Luis; Mali, Prashant; Aach, John; Church, George M

2015-02-18

Sequence-specific nucleases such as TALEN and the CRISPR/Cas9 system have so far been used to disrupt, correct or insert transgenes at precise locations in mammalian genomes. We demonstrate efficient 'knock-in' targeted replacement of multi-kilobase genes in human induced pluripotent stem cells (iPSC). Using a model system replacing endogenous human genes with their mouse counterpart, we performed a comprehensive study of targeting vector design parameters for homologous recombination. A 2.7 kilobase (kb) homozygous gene replacement was achieved in up to 11% of iPSC without selection. The optimal homology arm length was around 2 kb, with homology length being especially critical on the arm not adjacent to the cut site. Homologous sequence inside the cut sites was detrimental to targeting efficiency, consistent with a synthesis-dependent strand annealing (SDSA) mechanism. Using two nuclease sites, we observed a high degree of gene excisions and inversions, which sometimes occurred more frequently than indel mutations. While homozygous deletions of 86 kb were achieved with up to 8% frequency, deletion frequencies were not solely a function of nuclease activity and deletion size. Our results analyzing the optimal parameters for targeting vector design will inform future gene targeting efforts involving multi-kilobase gene segments, particularly in human iPSC. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Bevel Gear Quality Inspection System Based on Multi-Camera Vision Technology

PubMed Central

Liu, Ruiling; Zhong, Dexing; Lyu, Hongqiang; Han, Jiuqiang

2016-01-01

Surface defect detection and dimension measurement of automotive bevel gears by manual inspection are costly, inefficient, low speed and low accuracy. In order to solve these problems, a synthetic bevel gear quality inspection system based on multi-camera vision technology is developed. The system can detect surface defects and measure gear dimensions simultaneously. Three efficient algorithms named Neighborhood Average Difference (NAD), Circle Approximation Method (CAM) and Fast Rotation-Position (FRP) are proposed. The system can detect knock damage, cracks, scratches, dents, gibbosity or repeated cutting of the spline, etc. The smallest detectable defect is 0.4 mm × 0.4 mm and the precision of dimension measurement is about 40–50 μm. One inspection process takes no more than 1.3 s. Both precision and speed meet the requirements of real-time online inspection in bevel gear production. PMID:27571078

Biomolecule detection based on Si single-electron transistors for practical use

NASA Astrophysics Data System (ADS)

Nakajima, Anri; Kudo, Takashi; Furuse, Sadaharu

2013-07-01

Experimental and theoretical analyses demonstrated that ultra-sensitive biomolecule detection can be achieved using a Si single-electron transistor (SET). A multi-island channel structure was used to enable room-temperature operation. Coulomb oscillation increases transconductance without increasing channel width, which increases detection sensitivity to a charged target. A biotin-modified SET biosensor was used to detect streptavidin at a dilute concentration. In addition, an antibody-functionalized SET biosensor was used for immunodetection of prostate-specific antigen, demonstrating its suitability for practical use. The feasibility of ultra-sensitive detection of biomolecules for practical use by using a SET biosensor was clearly proven through this systematic study.

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.

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.

Improved thermal neutron activation sensor for detection of bulk explosives

NASA Astrophysics Data System (ADS)

McFee, John E.; Faust, Anthony A.; Andrews, H. Robert; Clifford, Edward T. H.; Mosquera, Cristian M.

2012-06-01

Defence R&D Canada - Suffield and Bubble Technology Industries have been developing thermal neutron activation (TNA) sensors for detection of buried bulk explosives since 1994. First generation sensors, employing an isotopic source and NaI(Tl) gamma ray detectors, were deployed by Canadian Forces in 2002 as confirmation sensors on the ILDS teleoperated, vehicle-mounted, multi-sensor anti-tank landmine detection systems. The first generation TNA could detect anti-tank mines buried 10 cm or less in no more than a minute, but deeper mines and those significantly displaced horizontally required considerably longer times. Mines as deep as 30 cm could be detected with long counting times (1000 s). The second generation TNA detector is being developed with a number of improvements aimed at increasing sensitivity and facilitating ease of operation. Among these are an electronic neutron generator to increase sensitivity for deeper and horizontally displaced explosives; LaBr3(Ce) scintillators, to improve time response and energy resolution; improved thermal and electronic stability; improved sensor head geometry to minimize spatial response nonuniformity; and more robust data processing. This improved sensitivity can translate to either decreased counting times, decreased minimum detectable explosive quantities, increased maximum sensor-to-target displacement, or a trade off among all three. Experiments to characterize the performance of the latest generation TNA in detecting buried landmines and IEDs hidden in culverts were conducted during 2011. This paper describes the second generation system. The experimental setup and methodology are detailed and preliminary comparisons between the performance of first and second generation systems are presented.

Flow injection analysis of organic peroxide explosives using acid degradation and chemiluminescent detection of released hydrogen peroxide.

PubMed

Mahbub, Parvez; Zakaria, Philip; Guijt, Rosanne; Macka, Mirek; Dicinoski, Greg; Breadmore, Michael; Nesterenko, Pavel N

2015-10-01

The applicability of acid degradation of organic peroxides into hydrogen peroxide in a pneumatically driven flow injection system with chemiluminescence reaction with luminol and Cu(2+) as a catalyst (FIA-CL) was investigated for the fast and sensitive detection of organic peroxide explosives (OPEs). The target OPEs included hexamethylene triperoxide diamine (HMTD), triacetone triperoxide (TATP) and methylethyl ketone peroxide (MEKP). Under optimised conditions maximum degradations of 70% and 54% for TATP and HMTD, respectively were achieved at 162 µL min(-1), and 9% degradation for MEKP at 180 µL min(-1). Flow rates were precisely controlled in this single source pneumatic pressure driven multi-channel FIA system by model experiments on mixing of easily detectable component solutions. The linear range for detection of TATP, HMTD and H2O2 was 1-200 µM (r(2)=0.98-0.99) at both flow rates, while that for MEKP was 20-200 µM (r(2)=0.97) at 180 µL min(-1). The detection limits (LODs) obtained were 0.5 µM for TATP, HMTD and H2O2 and 10 µM for MEKP. The detection times varied from 1.5 to 3 min in this FIA-CL system. Whilst the LOD for H2O2 was comparable with those reported by other investigators, the LODs and analysis times for TATP and HMTD were superior, and significantly, this is the first time the detection of MEKP has been reported by FIA-CL. Copyright © 2015 Elsevier B.V. All rights reserved.

Multi-static Serial LiDAR for Surveillance and Identification of Marine Life at MHK Installations

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

Alsenas, Gabriel; Dalgleish, Fraser; Ouyang, Bing

Final Report for project DE-EE0006787: Multi-static Serial LiDAR for Surveillance and Identification of Marine Life at MHK Installations. This project developed and tested an optical monitoring system prototype that will be suitable for marine and hydrokinetic (MHK) full project lifecycle observation (baseline, commissioning, and decommissioning), with automated real-time classification of marine animals. This system can be deployed to collect pre-installation baseline species observations at a proposed deployment site with minimal post-processing overhead. To satisfy deployed MHK project species of concern (e.g. Endangered Species Act-listed) monitoring requirements, the system provides automated tracking and notification of the presence of managed animals withinmore » established perimeters of MHK equipment and provides high resolution imagery of their behavior through a wide range of conditions. During a project’s decommissioning stage, the system can remain installed to provide resource managers with post-installation data. Our technology, known as an Unobtrusive Multi-static Serial LiDAR Imager (UMSLI), is a technology transfer of underwater distributed LiDAR imaging technology that preserves the advantages of traditional optical and acoustic solutions while overcoming associated disadvantages for MHK environmental monitoring applications. This new approach is a purposefully-designed, reconfigurable adaptation of an existing technology that can be easily mounted on or around different classes of MHK equipment. The system uses low average power red (638nm) laser illumination to be invisible and eye-safe to marine animals and is compact and cost effective. The equipment is designed for long term, maintenance-free operations, to inherently generate a sparse primary dataset that only includes detected anomalies (animal presence information), and to allow robust real-time automated animal classification/identification with a low data bandwidth requirement. Advantages of the technology over others currently being used or being considered for MHK monitoring include: Unlike a conventional camera, the depth of field is near-infinite and limited by attenuation (approximately 5-8 m) rather than focal properties of a lens; Operation in an adaptive mode which can project a sparse grid of pulses with higher peak power for longer range detection (>10 meters) and track animals within a zone of interest with high resolution imagery for identification of marine life at closer range (<5m); System detection limit and Signal-to-Noise-Ratio is superior to a camera, due to rejection of both backscattering component and ambient solar background; Multiple wide-angle pulsed laser illuminators and bucket detectors can be flexibly configured to cover a 4pi steradian (i.e. omnidirectional) scene volume, while also retrieving 3D features of animal targets from timing information; Process and classification framework centered around a novel active learning and incremental classification classifier that enables accurate identification of a variety of marine animals automatically; A two-tiered monitoring architecture and invisible watermarking-based data archiving and retrieving approach ensures significant data reduction while preserving high fidelity monitoring. A methodology to train and optimize the classifier for target species of concern to optimize site monitoring effectiveness. This technological innovation addresses a high priority regulatory requirement to observe marine life interaction near MHK projects. Our solution improves resource manager confidence that any interactions between marine animals and equipment are observed in a cost-effective and automated manner. Without EERE funding, this novel application of multi-static LiDAR would not have been available to the MHK community for environmental monitoring.« less

Combination Approaches to Combat Multi-Drug Resistant Bacteria

PubMed Central

Worthington, Roberta J.; Melander, Christian

2013-01-01

The increasing prevalence of infections caused by multi-drug resistant bacteria is a global health problem that is exacerbated by the dearth of novel classes of antibiotics entering the clinic over the past 40 years. Herein we describe recent developments toward combination therapies for the treatment of multi-drug resistant bacterial infections. These efforts include antibiotic-antibiotic combinations, and the development of adjuvants that either directly target resistance mechanisms such as the inhibition of β-lactamase enzymes, or indirectly target resistance by interfering with bacterial signaling pathways such as two-component systems. We also discuss screening of libraries of previously approved drugs to identify non-obvious antimicrobial adjuvants. PMID:23333434

New Method for Accurate Calibration of Micro-Channel Plate based Detection Systems and its use in the Fast Plasma Investigation of NASA's Magnetospheric MultiScale Mission

NASA Astrophysics Data System (ADS)

Gliese, U.; Avanov, L. A.; Barrie, A.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M.; Pollock, C. J.; Jacques, A. D.

2013-12-01

The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental concepts of this method, named threshold scan, will be presented. It will be shown how to derive all the individual detection system parameters. This new method has been successfully applied to achieve a highly accurate calibration of the 16 Dual Electron Spectrometers and 16 Dual Ion Spectrometers of the MMS mission. The practical application of the method will be presented together with the achieved calibration results and their significance. Finally, it will be shown how this method will be applied to ensure the best possible in flight calibration during the mission.

Real Time Corner Detection for Miniaturized Electro-Optical Sensors Onboard Small Unmanned Aerial Systems

PubMed Central

Forlenza, Lidia; Carton, Patrick; Accardo, Domenico; Fasano, Giancarmine; Moccia, Antonio

2012-01-01

This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d’Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed. PMID:22368499

Data fusion algorithm for rapid multi-mode dust concentration measurement system based on MEMS

NASA Astrophysics Data System (ADS)

Liao, Maohao; Lou, Wenzhong; Wang, Jinkui; Zhang, Yan

2018-03-01

As single measurement method cannot fully meet the technical requirements of dust concentration measurement, the multi-mode detection method is put forward, as well as the new requirements for data processing. This paper presents a new dust concentration measurement system which contains MEMS ultrasonic sensor and MEMS capacitance sensor, and presents a new data fusion algorithm for this multi-mode dust concentration measurement system. After analyzing the relation between the data of the composite measurement method, the data fusion algorithm based on Kalman filtering is established, which effectively improve the measurement accuracy, and ultimately forms a rapid data fusion model of dust concentration measurement. Test results show that the data fusion algorithm is able to realize the rapid and exact concentration detection.

Harmonic regression based multi-temporal cloud filtering algorithm for Landsat 8

NASA Astrophysics Data System (ADS)

Joshi, P.

2015-12-01

Landsat data archive though rich is seen to have missing dates and periods owing to the weather irregularities and inconsistent coverage. The satellite images are further subject to cloud cover effects resulting in erroneous analysis and observations of ground features. In earlier studies the change detection algorithm using statistical control charts on harmonic residuals of multi-temporal Landsat 5 data have been shown to detect few prominent remnant clouds [Brooks, Evan B., et al, 2014]. So, in this work we build on this harmonic regression approach to detect and filter clouds using a multi-temporal series of Landsat 8 images. Firstly, we compute the harmonic coefficients using the fitting models on annual training data. This time series of residuals is further subjected to Shewhart X-bar control charts which signal the deviations of cloud points from the fitted multi-temporal fourier curve. For the process with standard deviation σ we found the second and third order harmonic regression with a x-bar chart control limit [Lσ] ranging between [0.5σ < Lσ < σ] as most efficient in detecting clouds. By implementing second order harmonic regression with successive x-bar chart control limits of L and 0.5 L on the NDVI, NDSI and haze optimized transformation (HOT), and utilizing the seasonal physical properties of these parameters, we have designed a novel multi-temporal algorithm for filtering clouds from Landsat 8 images. The method is applied to Virginia and Alabama in Landsat8 UTM zones 17 and 16 respectively. Our algorithm efficiently filters all types of cloud cover with an overall accuracy greater than 90%. As a result of the multi-temporal operation and the ability to recreate the multi-temporal database of images using only the coefficients of the fourier regression, our algorithm is largely storage and time efficient. The results show a good potential for this multi-temporal approach for cloud detection as a timely and targeted solution for the Landsat 8 research community, catering to the need for innovative processing solutions in the infant stage of the satellite.

Aerobot Autonomy Architecture

NASA Technical Reports Server (NTRS)

Elfes, Alberto; Hall, Jeffery L.; Kulczycki, Eric A.; Cameron, Jonathan M.; Morfopoulos, Arin C.; Clouse, Daniel S.; Montgomery, James F.; Ansar, Adnan I.; Machuzak, Richard J.

2009-01-01

An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.

Laser ultrasonic multi-component imaging

DOEpatents

Williams, Thomas K [Federal Way, WA; Telschow, Kenneth [Des Moines, WA

2011-01-25

Techniques for ultrasonic determination of the interfacial relationship of multi-component systems are discussed. In implementations, a laser energy source may be used to excite a multi-component system including a first component and a second component at least in partial contact with the first component. Vibrations resulting from the excitation may be detected for correlation with a resonance pattern indicating if discontinuity exists at the interface of the first and second components.

[Remote system of natural gas leakage based on multi-wavelength characteristics spectrum analysis].

PubMed

Li, Jing; Lu, Xu-Tao; Yang, Ze-Hui

2014-05-01

In order to be able to quickly, to a wide range of natural gas pipeline leakage monitoring, the remote detection system for concentration of methane gas was designed based on static Fourier transform interferometer. The system used infrared light, which the center wavelength was calibrated to absorption peaks of methane molecules, to irradiated tested area, and then got the interference fringes by converging collimation system and interference module. Finally, the system calculated the concentration-path-length product in tested area by multi-wavelength characteristics spectrum analysis algorithm, furthermore the inversion of the corresponding concentration of methane. By HITRAN spectrum database, Selected wavelength position of 1. 65 microm as the main characteristic absorption peaks, thereby using 1. 65 pm DFB laser as the light source. In order to improve the detection accuracy and stability without increasing the hardware configuration of the system, solved absorbance ratio by the auxiliary wave-length, and then get concentration-path-length product of measured gas by the method of the calculation proportion of multi-wavelength characteristics. The measurement error from external disturbance is caused by this innovative approach, and it is more similar to a differential measurement. It will eliminate errors in the process of solving the ratio of multi-wavelength characteristics, and can improve accuracy and stability of the system. The infrared absorption spectrum of methane is constant, the ratio of absorbance of any two wavelengths by methane is also constant. The error coefficients produced by the system is the same when it received the same external interference, so the measured noise of the system can be effectively reduced by the ratio method. Experimental tested standards methane gas tank with leaking rate constant. Using the tested data of PN1000 type portable methane detector as the standard data, and were compared to the tested data of the system, while tested distance of the system were 100, 200 and 500 m. Experimental results show that the methane concentration detected value was stable after a certain time leakage, the concentration-path-length product value of the system was stable. For detection distance of 100 m, the detection error of the concentration-path-length product was less than 1. 0%. With increasing distance from tested area, the detection error is increased correspondingly. When the distance was 500 m, the detection error was less than 4. 5%. In short, the detected error of the system is less than 5. 0% after the gas leakage stable, to meet the requirements of the field of natural gas leakage remote sensing.

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.

CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery

PubMed Central

Kwon, Min-Seok; Nam, Seungyoon; Lee, Sungyoung; Ahn, Young Zoo; Chang, Hae Ryung; Kim, Yon Hui; Park, Taesung

2017-01-01

The recent creation of enormous, cancer-related “Big Data” public depositories represents a powerful means for understanding tumorigenesis. However, a consistently accurate system for clinically evaluating single/multi-biomarkers remains lacking, and it has been asserted that oft-failed clinical advancement of biomarkers occurs within the very early stages of biomarker assessment. To address these challenges, we developed a clinically testable, web-based tool, CANcer-specific single/multi-biomarker Evaluation System (CANES), to evaluate biomarker effectiveness, across 2,134 whole transcriptome datasets, from 94,147 biological samples (from 18 tumor types). For user-provided single/multi-biomarkers, CANES evaluates the performance of single/multi-biomarker candidates, based on four classification methods, support vector machine, random forest, neural networks, and classification and regression trees. In addition, CANES offers several advantages over earlier analysis tools, including: 1) survival analysis; 2) evaluation of mature miRNAs as markers for user-defined diagnostic or prognostic purposes; and 3) provision of a “pan-cancer” summary view, based on each single marker. We believe that such “landscape” evaluation of single/multi-biomarkers, for diagnostic therapeutic/prognostic decision-making, will be highly valuable for the discovery and “repurposing” of existing biomarkers (and their specific targeted therapies), leading to improved patient therapeutic stratification, a key component of targeted therapy success for the avoidance of therapy resistance. PMID:29050243

High-contrast imaging in multi-star systems: progress in technology development and lab results

NASA Astrophysics Data System (ADS)

Belikov, Ruslan; Pluzhnik, Eugene; Bendek, Eduardo; Sirbu, Dan

2017-09-01

We present the continued progress and laboratory results advancing the technology readiness of Multi-Star Wavefront Control (MSWC), a method to directly image planets and disks in multi-star systems such as Alpha Centauri. This method works with almost any coronagraph (or external occulter with a DM) and requires little or no change to existing and mature hardware. In particular, it works with single-star coronagraphs and does not require the off-axis star(s) to be coronagraphically suppressed. Because of the ubiquity of multistar systems, this method increases the science yield of many missions and concepts such as WFIRST, Exo-C/S, HabEx, LUVOIR, and potentially enables the detection of Earthlike planets (if they exist) around our nearest neighbor star, Alpha Centauri, with a small and low-cost space telescope such as ACESat. Our lab demonstrations were conducted at the Ames Coronagraph Experiment (ACE) laboratory and show both the feasibility as well as the trade-offs involved in using MSWC. We show several simulations and laboratory tests at roughly TRL-3 corresponding to representative targets and missions, including Alpha Centauri with WFIRST. In particular, we demonstrate MSWC in Super-Nyquist mode, where the distance between the desired dark zone and the off-axis star is larger than the conventional (sub-Nyquist) control range of the DM. Our laboratory tests did not yet include a coronagraph, but did demonstrate significant speckle suppression from two independent light sources at sub- as well as super-Nyquist separations.

A multi-wavelength (u.v. to visible) laser system for early detection of oral cancer

NASA Astrophysics Data System (ADS)

Najda, S. P.; Perlin, P.; Leszczyński, M.; Slight, T. J.; Meredith, W.; Schemmann, M.; Moseley, H.; Woods, J. A.; Valentine, R.; Kalra, S.; Mossey, P.; Theaker, E.; Macluskey, M.; Mimnagh, G.; Mimnagh, W.

2015-03-01

A multi-wavelength (360nm - 440nm), real-time Photonic Cancer Detector (PCD) optical system based on GaN semiconductor laser technology is outlined. A proof of concept using blue laser technology for early detection of cancer has already been tested and proven for esophageal cancer. This concept is expanded to consider a wider range of wavelengths and the PCD will initially be used for early diagnosis of oral cancers. The PCD creates an image of the oral cavity (broad field white light detection) and maps within the oral cavity any suspicious lesions with high sensitivity using a narrow field tunable detector.

Two-Photon Flow Cytometry

NASA Technical Reports Server (NTRS)

Zhog, Cheng Frank; Ye, Jing Yong; Norris, Theodore B.; Myc, Andrzej; Cao, Zhengyl; Bielinska, Anna; Thomas, Thommey; Baker, James R., Jr.

2004-01-01

Flow cytometry is a powerful technique for obtaining quantitative information from fluorescence in cells. Quantitation is achieved by assuring a high degree of uniformity in the optical excitation and detection, generally by using a highly controlled flow such as is obtained via hydrodynamic focusing. In this work, we demonstrate a two-beam, two- channel detection and two-photon excitation flow cytometry (T(sup 3)FC) system that enables multi-dye analysis to be performed very simply, with greatly relaxed requirements on the fluid flow. Two-photon excitation using a femtosecond near-infrared (NIR) laser has the advantages that it enables simultaneous excitation of multiple dyes and achieves very high signal-to-noise ratio through simplified filtering and fluorescence background reduction. By matching the excitation volume to the size of a cell, single-cell detection is ensured. Labeling of cells by targeted nanoparticles with multiple fluorophores enables normalization of the fluorescence signal and thus ratiometric measurements under nonuniform excitation. Quantitative size measurements can also be done even under conditions of nonuniform flow via a two-beam layout. This innovative detection scheme not only considerably simplifies the fluid flow system and the excitation and collection optics, it opens the way to quantitative cytometry in simple and compact microfluidics systems, or in vivo. Real-time detection of fluorescent microbeads in the vasculature of mouse ear demonstrates the ability to do flow cytometry in vivo. The conditions required to perform quantitative in vivo cytometry on labeled cells will be presented.

Development of Convergence Nanoparticles (Phase II): Detection and Therapeutics of Pathogen Targets by Using Multi-Mode Hybrid Nanoparticle Probe

DTIC Science & Technology

2010-04-05

Chloride (Aldrich 45011, 5g) 1 -Ethyl- 3 -[ 3 - dimethylaminopropyl ]carbodiimide hydrochloride (Pierce 25952-53-8, 25g) Oleylamine (Aldrich O7805, 500g...email: jcheon@yonsei.ac.kr Table of Content 1 . Abstract 2. Introduction 3 . Approach 4. Results and discussions 5. Pay-off 6. Summary 7...highly accurate detection and therapeutics of biological pathogens. 3 . Approaches 1 ) Approach Our research was focused on the development of

Performance of the improved larger acceptance spectrometer: VAMOS++

NASA Astrophysics Data System (ADS)

Rejmund, M.; Lecornu, B.; Navin, A.; Schmitt, C.; Damoy, S.; Delaune, O.; Enguerrand, J. M.; Fremont, G.; Gangnant, P.; Gaudefroy, L.; Jacquot, B.; Pancin, J.; Pullanhiotan, S.; Spitaels, C.

2011-08-01

Measurements and ion optic calculations showed that the large momentum acceptance of the VAMOS spectrometer at GANIL could be further increased from ˜11% to ˜30% by suitably enlarging the dimensions of the detectors used at the focal plane. Such a new detection system built for the focal plane of VAMOS is described. It consists of larger area detectors (1000 mm×150 mm) namely, a Multi-Wire Parallel Plate Avalanche Counter (MWPPAC), two drift chambers, a segmented ionization chamber and an array of Si detectors. Compared to the earlier existing system (VAMOS), we show that the new system (VAMOS++) has a dispersion-independent momentum acceptance. Additionally, a start detector (MWPPAC) has been introduced near the target to further improve the mass resolution to ˜1/220. The performance of the VAMOS++ spectrometer is demonstrated using measurements of residues formed in the collisions of 129Xe at 967 MeV on 197Au.

Electro-Optic Computing Architectures: Volume II. Components and System Design and Analysis

DTIC Science & Technology

1998-02-01

The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit

Cryogenic readout for multiple VUV4 Multi-Pixel Photon Counters in liquid xenon

NASA Astrophysics Data System (ADS)

Di Giovanni, A.

2018-03-01

This work concerned the preliminary tests and characterization of a cryogenic preamplifier board for an array made of 16 S13370-3050CN (VUV4 family) Multi-Pixel Photon Counters manufactured by Hamamatsu and operated at liquid xenon temperature. The proposed prototype is based on the use of the Analog Devices AD8011 current feedback operational amplifier. The detector allows for single photon detection, making this device a promising choice for the future generation of neutrino and dark matter detectors based on liquid xenon targets.

Large scale tracking algorithms

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

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

Automatic Target Cueing (ATC) Task 1 Report - Literature Survey on ATC

DTIC Science & Technology

2013-10-30

xa s In st ru m en t D aV in ci c hi p C ++ O ut da te d in fo rm at io n as w eb pa ge w as la st u pd at ed in...techniques such as contrast/ edge enhancement to increase the detectability of targets in the urban terrain. [P-4] restores long-distance thermal...Range? Sensor Experimental Setup Results [P-3] Contrast enhancement Edge enhancement Multi-scale edge domain Still images Yes IR

High-Performance Multi-Fuel AMTEC Power System

DTIC Science & Technology

2000-12-01

AMTEC technology has demonstrated thermal to electric conversion efficiencies and power densities which make it an attractive option for meso-scaic...power generation. This report details development of an integrated, logistics-fueled, 500 W AMTEC power supply. The development targeted 2O% AMTEC ...cylindrical multi-tube/single cell AMTEC configuration with effective management of alkali metal flow; scaling down and integrating a multi-fuel micro-combustor

Common aperture multispectral optics for military applications

NASA Astrophysics Data System (ADS)

Thompson, N. A.

2012-06-01

With the recent developments in multi-spectral detector technology the interest in common aperture, common focal plane multi-spectral imaging systems is increasing. Such systems are particularly desirable for military applications where increased levels of target discrimination and identification are required in cost-effective, rugged, lightweight systems. During the optical design of dual waveband or multi-spectral systems, the options for material selection are limited. This selection becomes even more restrictive for military applications as material resilience and thermal properties must be considered in addition to colour correction. In this paper we discuss the design challenges that lightweight multi-spectral common aperture systems present along with some potential design solutions. Consideration will be given to material selection for optimum colour correction as well as material resilience and thermal correction. This discussion is supported using design examples that are currently in development at Qioptiq.

Integrated Multi-process Microfluidic Systems for Automating Analysis

PubMed Central

Yang, Weichun; Woolley, Adam T.

2010-01-01

Microfluidic technologies have been applied extensively in rapid sample analysis. Some current challenges for standard microfluidic systems are relatively high detection limits, and reduced resolving power and peak capacity compared to conventional approaches. The integration of multiple functions and components onto a single platform can overcome these separation and detection limitations of microfluidics. Multiplexed systems can greatly increase peak capacity in multidimensional separations and can increase sample throughput by analyzing many samples simultaneously. On-chip sample preparation, including labeling, preconcentration, cleanup and amplification, can all serve to speed up and automate processes in integrated microfluidic systems. This paper summarizes advances in integrated multi-process microfluidic systems for automated analysis, their benefits and areas for needed improvement. PMID:20514343

AIE-doped poly(ionic liquid) photonic spheres: a single sphere-based customizable sensing platform for the discrimination of multi-analytes† †Electronic supplementary information (ESI) available: Synthesis and characterization of the AIE luminogen, experimental details, response profiles and results of the multivariate analysis. See DOI: 10.1039/c7sc02409f Click here for additional data file.

PubMed Central

Zhang, Wanlin; Gao, Ning; Cui, Jiecheng; Wang, Chen; Wang, Shiqiang; Zhang, Guanxin; Dong, Xiaobiao

2017-01-01

By simultaneously exploiting the unique properties of ionic liquids and aggregation-induced emission (AIE) luminogens, as well as photonic structures, a novel customizable sensing system for multi-analytes was developed based on a single AIE-doped poly(ionic liquid) photonic sphere. It was found that due to the extraordinary multiple intermolecular interactions involved in the ionic liquid units, one single sphere could differentially interact with broader classes of analytes, thus generating response patterns with remarkable diversity. Moreover, the optical properties of both the AIE luminogen and photonic structure integrated in the poly(ionic liquid) sphere provide multidimensional signal channels for transducing the involved recognition process in a complementary manner and the acquisition of abundant and sufficient sensing information could be easily achieved on only one sphere sensor element. More importantly, the sensing performance of our poly(ionic liquid) photonic sphere is designable and customizable through a simple ion-exchange reaction and target-oriented multi-analyte sensing can be conveniently realized using a selective receptor species, such as counterions, showing great flexibility and extendibility. The power of our single sphere-based customizable sensing system was exemplified by the successful on-demand detection and discrimination of four multi-analyte challenge systems: all 20 natural amino acids, nine important phosphate derivatives, ten metal ions and three pairs of enantiomers. To further demonstrate the potential of our spheres for real-life application, 20 amino acids in human urine and their 26 unprecedented complex mixtures were also discriminated between by the single sphere-based array. PMID:28989662

Polarimetric analysis of a CdZnTe spectro-imager under multi-pixel irradiation conditions

NASA Astrophysics Data System (ADS)

Pinto, M.; da Silva, R. M. Curado; Maia, J. M.; Simões, N.; Marques, J.; Pereira, L.; Trindade, A. M. F.; Caroli, E.; Auricchio, N.; Stephen, J. B.; Gonçalves, P.

2016-12-01

So far, polarimetry in high-energy astrophysics has been insufficiently explored due to the complexity of the required detection, electronic and signal processing systems. However, its importance is today largely recognized by the astrophysical community, therefore the next generation of high-energy space instruments will certainly provide polarimetric observations, contemporaneously with spectroscopy and imaging. We have been participating in high-energy observatory proposals submitted to ESA Cosmic Vision calls, such as GRI (Gamma-Ray Imager), DUAL and ASTROGAM, where the main instrument was a spectro-imager with polarimetric capabilities. More recently, the H2020 AHEAD project was launched with the objective to promote more coherent and mature future high-energy space mission proposals. In this context of high-energy proposal development, we have tested a CdZnTe detection plane prototype polarimeter under a partially polarized gamma-ray beam generated from an aluminum target irradiated by a 22Na (511 keV) radioactive source. The polarized beam cross section was 1 cm2, allowing the irradiation of a wide multi-pixelated area where all the pixels operate simultaneously as a scatterer and as an absorber. The methods implemented to analyze such multi-pixel irradiation are similar to those required to analyze a spectro-imager polarimeter operating in space, since celestial source photons should irradiate its full pixilated area. Correction methods to mitigate systematic errors inherent to CdZnTe and to the experimental conditions were also implemented. The polarization level ( 40%) and the polarization angle (precision of ±5° up to ±9°) obtained under multi-pixel irradiation conditions are presented and compared with simulated data.

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.

Ultra-Sensitive Detection of Plasmodium falciparum by Amplification of Multi-Copy Subtelomeric Targets

PubMed Central

Hofmann, Natalie; Mwingira, Felista; Shekalaghe, Seif; Robinson, Leanne J.; Mueller, Ivo; Felger, Ingrid

2015-01-01

Background Planning and evaluating malaria control strategies relies on accurate definition of parasite prevalence in the population. A large proportion of asymptomatic parasite infections can only be identified by surveillance with molecular methods, yet these infections also contribute to onward transmission to mosquitoes. The sensitivity of molecular detection by PCR is limited by the abundance of the target sequence in a DNA sample; thus, detection becomes imperfect at low densities. We aimed to increase PCR diagnostic sensitivity by targeting multi-copy genomic sequences for reliable detection of low-density infections, and investigated the impact of these PCR assays on community prevalence data. Methods and Findings Two quantitative PCR (qPCR) assays were developed for ultra-sensitive detection of Plasmodium falciparum, targeting the high-copy telomere-associated repetitive element 2 (TARE-2, ∼250 copies/genome) and the var gene acidic terminal sequence (varATS, 59 copies/genome). Our assays reached a limit of detection of 0.03 to 0.15 parasites/μl blood and were 10× more sensitive than standard 18S rRNA qPCR. In a population cross-sectional study in Tanzania, 295/498 samples tested positive using ultra-sensitive assays. Light microscopy missed 169 infections (57%). 18S rRNA qPCR failed to identify 48 infections (16%), of which 40% carried gametocytes detected by pfs25 quantitative reverse-transcription PCR. To judge the suitability of the TARE-2 and varATS assays for high-throughput screens, their performance was tested on sample pools. Both ultra-sensitive assays correctly detected all pools containing one low-density P. falciparum–positive sample, which went undetected by 18S rRNA qPCR, among nine negatives. TARE-2 and varATS qPCRs improve estimates of prevalence rates, yet other infections might still remain undetected when absent in the limited blood volume sampled. Conclusions Measured malaria prevalence in communities is largely determined by the sensitivity of the diagnostic tool used. Even when applying standard molecular diagnostics, prevalence in our study population was underestimated by 8% compared to the new assays. Our findings highlight the need for highly sensitive tools such as TARE-2 and varATS qPCR in community surveillance and for monitoring interventions to better describe malaria epidemiology and inform malaria elimination efforts. PMID:25734259

Study on pixel matching method of the multi-angle observation from airborne AMPR measurements

NASA Astrophysics Data System (ADS)

Hou, Weizhen; Qie, Lili; Li, Zhengqiang; Sun, Xiaobing; Hong, Jin; Chen, Xingfeng; Xu, Hua; Sun, Bin; Wang, Han

2015-10-01

For the along-track scanning mode, the same place along the ground track could be detected by the Advanced Multi-angular Polarized Radiometer (AMPR) with several different scanning angles from -55 to 55 degree, which provides a possible means to get the multi-angular detection for some nearby pixels. However, due to the ground sample spacing and spatial footprint of the detection, the different sizes of footprints cannot guarantee the spatial matching of some partly overlap pixels, which turn into a bottleneck for the effective use of the multi-angular detected information of AMPR to study the aerosol and surface polarized properties. Based on our definition and calculation of t he pixel coincidence rate for the multi-angular detection, an effective multi-angle observation's pixel matching method is presented to solve the spatial matching problem for airborne AMPR. Assuming the shape of AMPR's each pixel is an ellipse, and the major axis and minor axis depends on the flying attitude and each scanning angle. By the definition of coordinate system and origin of coordinate, the latitude and longitude could be transformed into the Euclidian distance, and the pixel coincidence rate of two nearby ellipses could be calculated. Via the traversal of each ground pixel, those pixels with high coincidence rate could be selected and merged, and with the further quality control of observation data, thus the ground pixels dataset with multi-angular detection could be obtained and analyzed, providing the support for the multi-angular and polarized retrieval algorithm research in t he next study.

Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

NASA Technical Reports Server (NTRS)

Gliese, U.; Avanov, L. A.; Barrie, A. C.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Gershman, D. J.; Dorelli, J. C.;

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

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.

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.

Development of an FBG Sensor Array for Multi-Impact Source Localization on CFRP Structures.

PubMed

Jiang, Mingshun; Sai, Yaozhang; Geng, Xiangyi; Sui, Qingmei; Liu, Xiaohui; Jia, Lei

2016-10-24

We proposed and studied an impact detection system based on a fiber Bragg grating (FBG) sensor array and multiple signal classification (MUSIC) algorithm to determine the location and the number of low velocity impacts on a carbon fiber-reinforced polymer (CFRP) plate. A FBG linear array, consisting of seven FBG sensors, was used for detecting the ultrasonic signals from impacts. The edge-filter method was employed for signal demodulation. Shannon wavelet transform was used to extract narrow band signals from the impacts. The Gerschgorin disc theorem was used for estimating the number of impacts. We used the MUSIC algorithm to obtain the coordinates of multi-impacts. The impact detection system was tested on a 500 mm × 500 mm × 1.5 mm CFRP plate. The results show that the maximum error and average error of the multi-impacts' localization are 9.2 mm and 7.4 mm, respectively.

Optimized swimmer tracking system based on a novel multi-related-targets approach

NASA Astrophysics Data System (ADS)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2017-02-01

Robust tracking is a crucial step in automatic swimmer evaluation from video sequences. We designed a robust swimmer tracking system using a new multi-related-targets approach. The main idea is to consider the swimmer as a bloc of connected subtargets that advance at the same speed. If one of the subtargets is partially or totally occluded, it can be localized by knowing the position of the others. In this paper, we first introduce the two-dimensional direct linear transformation technique that we used to calibrate the videos. Then, we present the classical tracking approach based on dynamic fusion. Next, we highlight the main contribution of our work, which is the multi-related-targets tracking approach. This approach, the classical head-only approach and the ground truth are then compared, through testing on a database of high-level swimmers in training, national and international competitions (French National Championships, Limoges 2015, and World Championships, Kazan 2015). Tracking percentage and the accuracy of the instantaneous speed are evaluated and the findings show that our new appraoach is significantly more accurate than the classical approach.

Transiting exoplanet candidates from K2 Campaigns 5 and 6

NASA Astrophysics Data System (ADS)

Pope, Benjamin J. S.; Parviainen, Hannu; Aigrain, Suzanne

2016-10-01

We introduce a new transit search and vetting pipeline for observations from the K2 mission, and present the candidate transiting planets identified by this pipeline out of the targets in Campaigns 5 and 6. Our pipeline uses the Gaussian process-based K2SC code to correct for the K2 pointing systematics and simultaneously model stellar variability. The systematics-corrected, variability-detrended light curves are searched for transits with the box-least-squares method, and a period-dependent detection threshold is used to generate a preliminary candidate list. Two or three individuals vet each candidate manually to produce the final candidate list, using a set of automatically generated transit fits and assorted diagnostic tests to inform the vetting. We detect 145 single-planet system candidates and 5 multi-planet systems, independently recovering the previously published hot Jupiters EPIC 212110888b, WASP-55b (EPIC 212300977b) and Qatar-2b (EPIC 212756297b). We also report the outcome of reconnaissance spectroscopy carried out for all candidates with Kepler magnitude Kp ≤ 13, identifying 12 targets as likely false positives. We compare our results to those of other K2 transit search pipelines, noting that ours performs particularly well for variable and/or active stars, but that the results are very similar overall. All the light curves and code used in the transit search and vetting process are publicly available, as are the follow-up spectra.

A high frequency electromagnetic impedance imaging system

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

Tseng, Hung-Wen; Lee, Ki Ha; Becker, Alex

2003-01-15

Non-invasive, high resolution geophysical mapping of the shallow subsurface is necessary for delineation of buried hazardous wastes, detecting unexploded ordinance, verifying and monitoring of containment or moisture contents, and other environmental applications. Electromagnetic (EM) techniques can be used for this purpose since electrical conductivity and dielectric permittivity are representative of the subsurface media. Measurements in the EM frequency band between 1 and 100 MHz are very important for such applications, because the induction number of many targets is small and the ability to determine the subsurface distribution of both electrical properties is required. Earlier workers were successful in developing systemsmore » for detecting anomalous areas, but quantitative interpretation of the data was difficult. Accurate measurements are necessary, but difficult to achieve for high-resolution imaging of the subsurface. We are developing a broadband non-invasive method for accurately mapping the electrical conductivity and dielectric permittivity of the shallow subsurface using an EM impedance approach similar to the MT exploration technique. Electric and magnetic sensors were tested to ensure that stray EM scattering is minimized and the quality of the data collected with the high-frequency impedance (HFI) system is good enough to allow high-resolution, multi-dimensional imaging of hidden targets. Additional efforts are being made to modify and further develop existing sensors and transmitters to improve the imaging capability and data acquisition efficiency.« less

An efficient enzyme-powered micromotor device fabricated by cyclic alternate hybridization assembly for DNA detection.

PubMed

Fu, Shizhe; Zhang, Xueqing; Xie, Yuzhe; Wu, Jie; Ju, Huangxian

2017-07-06

An efficient enzyme-powered micromotor device was fabricated by assembling multiple layers of catalase on the inner surface of a poly(3,4-ethylenedioxythiophene and sodium 4-styrenesulfonate)/Au microtube (PEDOT-PSS/Au). The catalase assembly was achieved by programmed DNA hybridization, which was performed by immobilizing a designed sandwich DNA structure as the sensing unit on the PEDOT-PSS/Au, and then alternately hybridizing with two assisting DNA to bind the enzyme for efficient motor motion. The micromotor device showed unique features of good reproducibility, stability and motion performance. Under optimal conditions, it showed a speed of 420 μm s -1 in 2% H 2 O 2 and even 51 μm s -1 in 0.25% H 2 O 2 . In the presence of target DNA, the sensing unit hybridized with target DNA to release the multi-layer DNA as well as the multi-catalase, resulting in a decrease of the motion speed. By using the speed as a signal, the micromotor device could detect DNA from 10 nM to 1 μM. The proposed micromotor device along with the cyclic alternate DNA hybridization assembly technique provided a new path to fabricate efficient and versatile micromotors, which would be an exceptional tool for rapid and simple detection of biomolecules.

Multi-target determination of organic ultraviolet absorbents in organism tissues by ultrasonic assisted extraction and ultra-high performance liquid chromatography-tandem mass spectrometry.

PubMed

Peng, Xianzhi; Jin, Jiabin; Wang, Chunwei; Ou, Weihui; Tang, Caiming

2015-03-06

A sensitive and reliable method was developed for multi-target determination of 13 most widely used organic ultraviolet (UV) absorbents (including UV filters and UV stabilizers) in aquatic organism tissues. The organic UV absorbents were extracted using ultrasonic-assisted extraction, purified via gel permeation chromatography coupled with silica gel column chromatography, and determined by ultra-high performance liquid chromatography-tandem mass spectrometry. Recoveries of the UV absorbents from organism tissues mostly ranged from 70% to 120% from fish filet with satisfactory reproducibility. Method quantification limits were 0.003-1.0ngg(-1) dry weight (dw) except for 2-ethylhexyl 4-methoxycinnamate. This method has been applied to analysis of the UV absorbents in wild and farmed aquatic organisms collected from the Pearl River Estuary, South China. 2-Hydroxy-4-methoxybenzophenone and UV-P were frequently detected in both wild and farmed marine organisms at low ngg(-1)dw. 3-(4-Methylbenzylidene)camphor and most of the benzotriazole UV stabilizers were also frequently detected in maricultured fish. Octocrylene and 2-ethylhexyl 4-methoxycinnamate were not detected in any sample. This work lays basis for in-depth study about bioaccumulation and biomagnification of the UV absorbents in marine environment. Copyright © 2015 Elsevier B.V. All rights reserved.

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter.

PubMed

Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei

2016-11-02

Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system's error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts.

Multi-Channel RF System for MRI-Guided Transurethral Ultrasound Thermal Therapy

NASA Astrophysics Data System (ADS)

Yak, Nicolas; Asselin, Matthew; Chopra, Rajiv; Bronskill, Michael

2009-04-01

MRI-guided transurethral ultrasound thermal therapy is an approach to treating localized prostate cancer which targets precise deposition of thermal energy within a confined region of the gland. This treatment requires a system incorporating a heating applicator with multiple planar ultrasound transducers and associated RF electronics to control individual elements independently in order to achieve accurate 3D treatment. We report the design, construction, and characterization of a prototype multi-channel system capable of controlling 16 independent RF signals for a 16-element heating applicator. The main components are a control computer, microcontroller, and a 16-channel signal generator with 16 amplifiers, each incorporating a low-pass filter and transmitted/reflected power detection circuit. Each channel can deliver from 0.5 to 10 W of electrical power and good linearity from 3 to 12 MHz. Harmonic RF signals near the Larmor frequency of a 1.5 T MRI were measured to be below -30 dBm and heating experiments within the 1.5 T MR system showed no significant decrease in SNR of the temperature images. The frequency and power for all 16 channels could be changed in less than 250 ms, which was sufficiently rapid for proper performance of the control algorithms. A common backplane design was chosen which enabled an inexpensive, modular approach for each channel resulting in an overall system with minimal footprint.

The role of multi-target policy instruments in agri-environmental policy mixes.

PubMed

Schader, Christian; Lampkin, Nicholas; Muller, Adrian; Stolze, Matthias

2014-12-01

The Tinbergen Rule has been used to criticise multi-target policy instruments for being inefficient. The aim of this paper is to clarify the role of multi-target policy instruments using the case of agri-environmental policy. Employing an analytical linear optimisation model, this paper demonstrates that there is no general contradiction between multi-target policy instruments and the Tinbergen Rule, if multi-target policy instruments are embedded in a policy-mix with a sufficient number of targeted instruments. We show that the relation between cost-effectiveness of the instruments, related to all policy targets, is the key determinant for an economically sound choice of policy instruments. If economies of scope with respect to achieving policy targets are realised, a higher cost-effectiveness of multi-target policy instruments can be achieved. Using the example of organic farming support policy, we discuss several reasons why economies of scope could be realised by multi-target agri-environmental policy instruments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Uncued Low SNR Detection with Likelihood from Image Multi Bernoulli Filter

NASA Astrophysics Data System (ADS)

Murphy, T.; Holzinger, M.

2016-09-01

Both SSA and SDA necessitate uncued, partially informed detection and orbit determination efforts for small space objects which often produce only low strength electro-optical signatures. General frame to frame detection and tracking of objects includes methods such as moving target indicator, multiple hypothesis testing, direct track-before-detect methods, and random finite set based multiobject tracking. This paper will apply the multi-Bernoilli filter to low signal-to-noise ratio (SNR), uncued detection of space objects for space domain awareness applications. The primary novel innovation in this paper is a detailed analysis of the existing state-of-the-art likelihood functions and a likelihood function, based on a binary hypothesis, previously proposed by the authors. The algorithm is tested on electro-optical imagery obtained from a variety of sensors at Georgia Tech, including the GT-SORT 0.5m Raven-class telescope, and a twenty degree field of view high frame rate CMOS sensor. In particular, a data set of an extended pass of the Hitomi Astro-H satellite approximately 3 days after loss of communication and potential break up is examined.

Detection and Learning of Unexpected Behaviors of Systems of Dynamical Systems by Using the Q2 Abstractions

DTIC Science & Technology

2017-11-01

Finite State Machine ............................................... 21 9 Main Ontological Concepts for Representing Structure of a Multi -Agent...19 NetLogo Simulation of persistent surveillance of circular plume by 4 UAVs ........................36 20 Flocking Emergent Behaviors in Multi -UAV...Region) - Undesirable Group Formation ................................................................................... 40 24 Two UAVs Moving in

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 classification of UXO. For maximum generality, our algorithm is robust and can handle sparse training examples of multi-class data. This procedure uses an unsupervised starter, semi-supervised techniques to gather training data, and concludes with supervised learning until all TOI are found. Additionally, an inference method for estimating the number of remaining true positives from a partial Receiver Operating Characteristic (ROC) curve is presented and applied to live-site dig histories.