Real-time detection of natural objects using AM-coded spectral matching imager

NASA Astrophysics Data System (ADS)

Kimachi, Akira

2004-12-01

This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

Real-time detection of natural objects using AM-coded spectral matching imager

NASA Astrophysics Data System (ADS)

Kimachi, Akira

2005-01-01

This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

Advanced detection, isolation, and accommodation of sensor failures in turbofan engines: Real-time microcomputer implementation

NASA Technical Reports Server (NTRS)

Delaat, John C.; Merrill, Walter C.

1990-01-01

The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming.

Real-time system for imaging and object detection with a multistatic GPR array

DOEpatents

Paglieroni, David W; Beer, N Reginald; Bond, Steven W; Top, Philip L; Chambers, David H; Mast, Jeffrey E; Donetti, John G; Mason, Blake C; Jones, Steven M

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

A Real-Time Method to Estimate Speed of Object Based on Object Detection and Optical Flow Calculation

NASA Astrophysics Data System (ADS)

Liu, Kaizhan; Ye, Yunming; Li, Xutao; Li, Yan

2018-04-01

In recent years Convolutional Neural Network (CNN) has been widely used in computer vision field and makes great progress in lots of contents like object detection and classification. Even so, combining Convolutional Neural Network, which means making multiple CNN frameworks working synchronously and sharing their output information, could figure out useful message that each of them cannot provide singly. Here we introduce a method to real-time estimate speed of object by combining two CNN: YOLOv2 and FlowNet. In every frame, YOLOv2 provides object size; object location and object type while FlowNet providing the optical flow of whole image. On one hand, object size and object location help to select out the object part of optical flow image thus calculating out the average optical flow of every object. On the other hand, object type and object size help to figure out the relationship between optical flow and true speed by means of optics theory and priori knowledge. Therefore, with these two key information, speed of object can be estimated. This method manages to estimate multiple objects at real-time speed by only using a normal camera even in moving status, whose error is acceptable in most application fields like manless driving or robot vision.

Real-time moving objects detection and tracking from airborne infrared camera

NASA Astrophysics Data System (ADS)

Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

2017-10-01

Detecting and tracking moving objects in real-time from an airborne infrared (IR) camera offers interesting possibilities in video surveillance, remote sensing and computer vision applications, such as monitoring large areas simultaneously, quickly changing the point of view on the scene and pursuing objects of interest. To fully exploit such a potential, versatile solutions are needed, but, in the literature, the majority of them works only under specific conditions about the considered scenario, the characteristics of the moving objects or the aircraft movements. In order to overcome these limitations, we propose a novel approach to the problem, based on the use of a cheap inertial navigation system (INS), mounted on the aircraft. To exploit jointly the information contained in the acquired video sequence and the data provided by the INS, a specific detection and tracking algorithm has been developed. It consists of three main stages performed iteratively on each acquired frame. The detection stage, in which a coarse detection map is computed, using a local statistic both fast to calculate and robust to noise and self-deletion of the targeted objects. The registration stage, in which the position of the detected objects is coherently reported on a common reference frame, by exploiting the INS data. The tracking stage, in which the steady objects are rejected, the moving objects are tracked, and an estimation of their future position is computed, to be used in the subsequent iteration. The algorithm has been tested on a large dataset of simulated IR video sequences, recreating different environments and different movements of the aircraft. Promising results have been obtained, both in terms of detection and false alarm rate, and in terms of accuracy in the estimation of position and velocity of the objects. In addition, for each frame, the detection and tracking map has been generated by the algorithm, before the acquisition of the subsequent frame, proving its capability to work in real-time.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Detection of selected intestinal helminths and protozoa at Hospital Universiti Sains Malaysia using multiplex real-time PCR.

PubMed

Basuni, M; Mohamed, Z; Ahmad, M; Zakaria, N Z; Noordin, R

2012-09-01

Intestinal parasites are the causative agents of a number of important human infections in developing countries. The objective of this study was to determine the prevalence of selected helminths and protozoan infections among patients admitted with gastrointestinal disorders at Hospital Universiti Sains Malaysia, Kelantan, Malaysia using multiplex real-time PCR. In addition microscopic examination was also performed following direct smear, zinc sulphate concentration and Kato-Katz thick smear techniques; and the presence of protozoan parasites was confirmed using trichrome and acid-fast stains. Of the 225 faecal samples analysed, 26.2% were positive for intestinal parasites by the multiplex real-time PCR, while 5.3% were positive by microscopy. As compared to microscopy, the multiplex real-time PCR detected 5.8 and 4.5 times more positives for the selected helminth and protozoan infections respectively. Among the selected helminths detected in this study, hookworm was the most prevalent by real-time PCR, while Ascaris lumbricoides was detected the most by microscopy. Meanwhile, among the selected protozoa detected in this study, Entamoeba histolytica was the most prevalent by real-time PCR, however microscopy detected equal number of cases with E. histolytica and Giardia lamblia. This study showed that real-time PCR can be used to obtain a more accurate prevalence data on intestinal helminths and protozoa.

Advanced detection, isolation and accommodation of sensor failures: Real-time evaluation

NASA Technical Reports Server (NTRS)

Merrill, Walter C.; Delaat, John C.; Bruton, William M.

1987-01-01

The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundacy to detect sensor failures. The results of a real time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

Real-time RPA assay for rapid detection and differentiation of wild-type pseudorabies and gE-deleted vaccine viruses.

PubMed

Wang, Jianchang; Liu, Libing; Wang, Jinfeng; Pang, Xiaoyu; Yuan, Wanzhe

2018-02-15

The objective of this study was to develop a dual real-time recombinase polymerase amplification (RPA) assay using exo probes for the detection and differentiation of pseudorabies virus (PRV). Specific RPA primers and probes were designed for gB and gE genes of PRV within the conserved region of viral genome. The reaction process can be completed in 20 min at 39 °C. The dual real-time RPA assay performed in the single tube was capable of specific detecting and differentiating of the wild-type PRV and gE-deleted vaccine strains, without cross-reactions with other non-targeted pig viruses. The analytical sensitivity of the assay was 10 2 copies for gB and gE genes. The dual real-time RPA demonstrated a 100% diagnostic agreement with the real-time PCR on 4 PRV strains and 37 clinical samples. Through the linear regression analysis, the R 2 value of the real-time RPA and the real-time PCR for gB and gE was 0.983 and 0.992, respectively. The dual real-time RPA assay provides an alternative useful tool for rapid, simple, and reliable detection and differentiation of PRV, especially in remote and rural areas. Copyright © 2017 Elsevier Inc. All rights reserved.

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.

PubMed

Christiansen, Peter; Nielsen, Lars N; Steen, Kim A; Jørgensen, Rasmus N; Karstoft, Henrik

2016-11-11

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45-90 m) than RCNN. RCNN has a similar performance at a short range (0-30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

PubMed Central

Christiansen, Peter; Nielsen, Lars N.; Steen, Kim A.; Jørgensen, Rasmus N.; Karstoft, Henrik

2016-01-01

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit). PMID:27845717

A robust approach towards unknown transformation, regional adjacency graphs, multigraph matching, segmentation video frames from unnamed aerial vehicles (UAV)

NASA Astrophysics Data System (ADS)

Gohatre, Umakant Bhaskar; Patil, Venkat P.

2018-04-01

In computer vision application, the multiple object detection and tracking, in real-time operation is one of the important research field, that have gained a lot of attentions, in last few years for finding non stationary entities in the field of image sequence. The detection of object is advance towards following the moving object in video and then representation of object is step to track. The multiple object recognition proof is one of the testing assignment from detection multiple objects from video sequence. The picture enrollment has been for quite some time utilized as a reason for the location the detection of moving multiple objects. The technique of registration to discover correspondence between back to back casing sets in view of picture appearance under inflexible and relative change. The picture enrollment is not appropriate to deal with event occasion that can be result in potential missed objects. In this paper, for address such problems, designs propose novel approach. The divided video outlines utilizing area adjancy diagram of visual appearance and geometric properties. Then it performed between graph sequences by using multi graph matching, then getting matching region labeling by a proposed graph coloring algorithms which assign foreground label to respective region. The plan design is robust to unknown transformation with significant improvement in overall existing work which is related to moving multiple objects detection in real time parameters.

[Analytical performances of real-time PCR by Abbott RealTime CMV with m2000 for the detection of cytomegalovirus in urine].

PubMed

De Monte, Anne; Cannavo, Isabelle; Caramella, Anne; Ollier, Laurence; Giordanengo, Valérie

2016-01-01

Congenital cytomegalovirus (CMV) infection is the leading cause of sensoneurinal disability due to infectious congenital disease. The diagnosis of congenital CMV infection is based on the search of CMV in the urine within the first two weeks of life. Viral culture of urine is the gold standard. However, the PCR is highly sensitive and faster. It is becoming an alternative choice. The objective of this study is the validation of real-time PCR by Abbott RealTime CMV with m2000 for the detection of cytomegalovirus in urine. Repeatability, reproducibility, detection limit and inter-sample contamination were evaluated. Urine samples from patients (n=141) were collected and analyzed simultaneously in culture and PCR in order to assess the correlation of these two methods. The sensitivity and specificity of PCR were also calculated. The Abbott RealTime CMV PCR in urine is an automated and sensitive method (detection limit 200 UI/mL). Fidelity is very good (standard deviation of repeatability: 0.08 to 0.15 LogUI/mL and reproducibility 0.18 LogUI/mL). We can note a good correlation between culture and Abbott RealTime CMV PCR (kappa 96%). When considering rapid culture as reference, real-time PCR was highly sensitive (100%) and specific (98.2%). The real-time PCR by Abbott RealTime CMV with m2000 is optimal for CMV detection in urine.

Real-time door detection for indoor autonomous vehicle

NASA Astrophysics Data System (ADS)

He, Zhihao; Zhu, Ming

2017-07-01

Indoor Autonomous Vehicle(IAV) is used in many indoor scenes. Such as hotels and hospitals. Door detection is a key issue to guide the IAV into rooms. In this paper, we consider door detection in the use of indoor navigation of IAV. Since real-time properties are important for real-world IAV, the detection algorithm must be fast enough. Most monocular-camera based door detection model need a perfect detection of the four line segments of the door or the four corners. But in many situations, line segments could be extended or cut off. And there could be many false detected corners. And few of them can distinguish doors from door-like objects with door-like shape effectively. We proposed a 2-D vision model of the door that is made up of line segments. The number of parts detected is used to determine the possibility of a door. Our algorithm is tested on a database of doors.1 The robustness and real-time are verified. The precision is 89.4%. Average time consumed for processing a 640x320 figure is 44.73ms.

Detection of hidden objects using a real-time 3-D millimeter-wave imaging system

NASA Astrophysics Data System (ADS)

Rozban, Daniel; Aharon, Avihai; Levanon, Assaf; Abramovich, Amir; Yitzhaky, Yitzhak; Kopeika, N. S.

2014-10-01

Millimeter (mm)and sub-mm wavelengths or terahertz (THz) band have several properties that motivate their use in imaging for security applications such as recognition of hidden objects, dangerous materials, aerosols, imaging through walls as in hostage situations, and also in bad weather conditions. There is no known ionization hazard for biological tissue, and atmospheric degradation of THz radiation is relatively low for practical imaging distances. We recently developed a new technology for the detection of THz radiation. This technology is based on very inexpensive plasma neon indicator lamps, also known as Glow Discharge Detector (GDD), that can be used as very sensitive THz radiation detectors. Using them, we designed and constructed a Focal Plane Array (FPA) and obtained recognizable2-dimensional THz images of both dielectric and metallic objects. Using THz wave it is shown here that even concealed weapons made of dielectric material can be detected. An example is an image of a knife concealed inside a leather bag and also under heavy clothing. Three-dimensional imaging using radar methods can enhance those images since it can allow the isolation of the concealed objects from the body and environmental clutter such as nearby furniture or other people. The GDDs enable direct heterodyning between the electric field of the target signal and the reference signal eliminating the requirement for expensive mixers, sources, and Low Noise Amplifiers (LNAs).We expanded the ability of the FPA so that we are able to obtain recognizable 2-dimensional THz images in real time. We show here that the THz detection of objects in three dimensions, using FMCW principles is also applicable in real time. This imaging system is also shown here to be capable of imaging objects from distances allowing standoff detection of suspicious objects and humans from large distances.

Real-time people and vehicle detection from UAV imagery

NASA Astrophysics Data System (ADS)

Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

2011-01-01

A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode.

PubMed

Ye, Tao; Wang, Baocheng; Song, Ping; Li, Juan

2018-06-12

Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN) is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net). It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.

MACS-Mar: a real-time remote sensing system for maritime security applications

NASA Astrophysics Data System (ADS)

Brauchle, Jörg; Bayer, Steven; Hein, Daniel; Berger, Ralf; Pless, Sebastian

2018-04-01

The modular aerial camera system (MACS) is a development platform for optical remote sensing concepts, algorithms and special environments. For real-time services for maritime security (EMSec joint project), a new multi-sensor configuration MACS-Mar was realized. It consists of four co-aligned sensor heads in the visible RGB, near infrared (NIR, 700-950 nm), hyperspectral (HS, 450-900 nm) and thermal infrared (TIR, 7.5-14 µm) spectral range, a mid-cost navigation system, a processing unit and two data links. On-board image projection, cropping of redundant data and compression enable the instant generation of direct-georeferenced high-resolution image mosaics, automatic object detection, vectorization and annotation of floating objects on the water surface. The results were transmitted over a distance up to 50 km in real-time via narrow and broadband data links and were visualized in a maritime situation awareness system. For the automatic onboard detection of floating objects, a segmentation and classification workflow based on RGB, IR and TIR information was developed and tested. The completeness of the object detection in the experiment resulted in 95%, the correctness in 53%. Mostly, bright backwash of ships lead to an overestimation of the number of objects, further refinement using water homogeneity in the TIR, as implemented in the workflow, couldn't be carried out due to problems with the TIR sensor, else distinctly better results could have been expected. The absolute positional accuracy of the projected real-time imagery resulted in 2 m without postprocessing of images or navigation data, the relative measurement accuracy of distances is in the range of the image resolution, which is about 12 cm for RGB imagery in the EMSec experiment.

Machine learning for real time remote detection

NASA Astrophysics Data System (ADS)

Labbé, Benjamin; Fournier, Jérôme; Henaff, Gilles; Bascle, Bénédicte; Canu, Stéphane

2010-10-01

Infrared systems are key to providing enhanced capability to military forces such as automatic control of threats and prevention from air, naval and ground attacks. Key requirements for such a system to produce operational benefits are real-time processing as well as high efficiency in terms of detection and false alarm rate. These are serious issues since the system must deal with a large number of objects and categories to be recognized (small vehicles, armored vehicles, planes, buildings, etc.). Statistical learning based algorithms are promising candidates to meet these requirements when using selected discriminant features and real-time implementation. This paper proposes a new decision architecture benefiting from recent advances in machine learning by using an effective method for level set estimation. While building decision function, the proposed approach performs variable selection based on a discriminative criterion. Moreover, the use of level set makes it possible to manage rejection of unknown or ambiguous objects thus preserving the false alarm rate. Experimental evidences reported on real world infrared images demonstrate the validity of our approach.

Modeling job sites in real time to improve safety during equipment operation

NASA Astrophysics Data System (ADS)

Caldas, Carlos H.; Haas, Carl T.; Liapi, Katherine A.; Teizer, Jochen

2006-03-01

Real-time three-dimensional (3D) modeling of work zones has received an increasing interest to perform equipment operation faster, safer and more precisely. In addition, hazardous job site environment like they exist on construction sites ask for new devices which can rapidly and actively model static and dynamic objects. Flash LADAR (Laser Detection and Ranging) cameras are one of the recent technology developments which allow rapid spatial data acquisition of scenes. Algorithms that can process and interpret the output of such enabling technologies into threedimensional models have the potential to significantly improve work processes. One particular important application is modeling the location and path of objects in the trajectory of heavy construction equipment navigation. Detecting and mapping people, materials and equipment into a three-dimensional computer model allows analyzing the location, path, and can limit or restrict access to hazardous areas. This paper presents experiments and results of a real-time three-dimensional modeling technique to detect static and moving objects within the field of view of a high-frame update rate laser range scanning device. Applications related to heavy equipment operations on transportation and construction job sites are specified.

Real-time classification of vehicles by type within infrared imagery

NASA Astrophysics Data System (ADS)

Kundegorski, Mikolaj E.; Akçay, Samet; Payen de La Garanderie, Grégoire; Breckon, Toby P.

2016-10-01

Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios.

Small real time detection satellites for MDA using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Nakaya, Daiki; Yanagida, Hiroki; Shin, Satori; Ito, Tomonori; Takeuchi, Yusuke

2017-10-01

Hyperspectral Images are now used in the field of agriculture, cosmetics, and space exploring. Behind this fact, there is a result of efforts to contrive miniaturization and decrease in costs. This paper describes low-cost and small Hyperspectral Camera (HSC) under development and a method of utilizing it. Real Time Detection System for MDA is that government agencies put those cameras in small satellites and use them for MDA (Maritime Domain Awareness). We assume early detection of unidentified floating objects to find out disguised fishing ships and submarines.

Near-infrared high-resolution real-time omnidirectional imaging platform for drone detection

NASA Astrophysics Data System (ADS)

Popovic, Vladan; Ott, Beat; Wellig, Peter; Leblebici, Yusuf

2016-10-01

Recent technological advancements in hardware systems have made higher quality cameras. State of the art panoramic systems use them to produce videos with a resolution of 9000 x 2400 pixels at a rate of 30 frames per second (fps).1 Many modern applications use object tracking to determine the speed and the path taken by each object moving through a scene. The detection requires detailed pixel analysis between two frames. In fields like surveillance systems or crowd analysis, this must be achieved in real time.2 In this paper, we focus on the system-level design of multi-camera sensor acquiring near-infrared (NIR) spectrum and its ability to detect mini-UAVs in a representative rural Swiss environment. The presented results show the UAV detection from the trial that we conducted during a field trial in August 2015.

Real-time object detection and semantic segmentation for autonomous driving

NASA Astrophysics Data System (ADS)

Li, Baojun; Liu, Shun; Xu, Weichao; Qiu, Wei

2018-02-01

In this paper, we proposed a Highly Coupled Network (HCNet) for joint objection detection and semantic segmentation. It follows that our method is faster and performs better than the previous approaches whose decoder networks of different tasks are independent. Besides, we present multi-scale loss architecture to learn better representation for different scale objects, but without extra time in the inference phase. Experiment results show that our method achieves state-of-the-art results on the KITTI datasets. Moreover, it can run at 35 FPS on a GPU and thus is a practical solution to object detection and semantic segmentation for autonomous driving.

[Real-time detection and processing of medical signals under windows using Lcard analog interfaces].

PubMed

Kuz'min, A A; Belozerov, A E; Pronin, T V

2008-01-01

Multipurpose modular software for an analog interface based on Lcard 761 is considered. Algorithms for pipeline processing of medical signals under Windows with dynamic control of computational resources are suggested. The software consists of user-friendly completable modifiable modules. The module hierarchy is based on object-oriented heritage principles, which make it possible to construct various real-time systems for long-term detection, processing, and imaging of multichannel medical signals.

A street rubbish detection algorithm based on Sift and RCNN

NASA Astrophysics Data System (ADS)

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

2018-02-01

This paper presents a street rubbish detection algorithm based on image registration with Sift feature and RCNN. Firstly, obtain the rubbish region proposal on the real-time street image and set up the CNN convolution neural network trained by the rubbish samples set consists of rubbish and non-rubbish images; Secondly, for every clean street image, obtain the Sift feature and do image registration with the real-time street image to obtain the differential image, the differential image filters a lot of background information, obtain the rubbish region proposal rect where the rubbish may appear on the differential image by the selective search algorithm. Then, the CNN model is used to detect the image pixel data in each of the region proposal on the real-time street image. According to the output vector of the CNN, it is judged whether the rubbish is in the region proposal or not. If it is rubbish, the region proposal on the real-time street image is marked. This algorithm avoids the large number of false detection caused by the detection on the whole image because the CNN is used to identify the image only in the region proposal on the real-time street image that may appear rubbish. Different from the traditional object detection algorithm based on the region proposal, the region proposal is obtained on the differential image not whole real-time street image, and the number of the invalid region proposal is greatly reduced. The algorithm has the high mean average precision (mAP).

A real-time standard parts inspection based on deep learning

NASA Astrophysics Data System (ADS)

Xu, Kuan; Li, XuDong; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Since standard parts are necessary components in mechanical structure like bogie and connector. These mechanical structures will be shattered or loosen if standard parts are lost. So real-time standard parts inspection systems are essential to guarantee their safety. Researchers would like to take inspection systems based on deep learning because it works well in image with complex backgrounds which is common in standard parts inspection situation. A typical inspection detection system contains two basic components: feature extractors and object classifiers. For the object classifier, Region Proposal Network (RPN) is one of the most essential architectures in most state-of-art object detection systems. However, in the basic RPN architecture, the proposals of Region of Interest (ROI) have fixed sizes (9 anchors for each pixel), they are effective but they waste much computing resources and time. In standard parts detection situations, standard parts have given size, thus we can manually choose sizes of anchors based on the ground-truths through machine learning. The experiments prove that we could use 2 anchors to achieve almost the same accuracy and recall rate. Basically, our standard parts detection system could reach 15fps on NVIDIA GTX1080 (GPU), while achieving detection accuracy 90.01% mAP.

Rapid, cost-effective, sensitive and quantitative detection of Acinetobacter baumannii from pneumonia patients

PubMed Central

Nomanpour, B; Ghodousi, A; Babaei, A; Abtahi, HR; Tabrizi, M; Feizabadi, MM

2011-01-01

Background and Objectives Pneumonia with Acinetobacter baumannii has a major therapeutic problem in health care settings. Decision to initiate correct antibiotic therapy requires rapid identification and quantification of organism. The aim of this study was to develop a rapid and sensitive method for direct detection of A. baumannii from respiratory specimens. Materials and Methods A Taqman real time PCR based on the sequence of bla oxa-51 was designed and used for direct detection of A. baumannii from 361 respiratory specimens of patients with pneumonia. All specimens were checked by conventional bacteriology in parallel. Results The new real time PCR could detect less than 200 cfu per ml of bacteria in specimens. There was agreement between the results of real time PCR and culture (Kappa value 1.0, p value<0.001). The sensitivity, specificity and predictive values of real time PCR were 100%. The prevalence of A. baumannii in pneumonia patients was 10.53 % (n=38). Poly-microbial infections were detected in 65.71% of specimens. Conclusion Acinetobacter baumannii is the third causative agent in nosocomial pneumonia after Pseudomonas aeroginosa (16%) and Staphylococcus aureus (13%) at Tehran hospitals. We recommend that 104 CFU be the threshold for definition of infection with A. baumannii using real time PCR. PMID:22530083

Underwater detection by using ultrasonic sensor

NASA Astrophysics Data System (ADS)

Bakar, S. A. A.; Ong, N. R.; Aziz, M. H. A.; Alcain, J. B.; Haimi, W. M. W. N.; Sauli, Z.

2017-09-01

This paper described the low cost implementation of hardware and software in developing the system of ultrasonic which can visualize the feedback of sound in the form of measured distance through mobile phone and monitoring the frequency of detection by using real time graph of Java application. A single waterproof transducer of JSN-SR04T had been used to determine the distance of an object based on operation of the classic pulse echo detection method underwater. In this experiment, the system was tested by placing the housing which consisted of Arduino UNO, Bluetooth module of HC-06, ultrasonic sensor and LEDs at the top of the box and the transducer was immersed in the water. The system which had been tested for detection in vertical form was found to be capable of reporting through the use of colored LEDs as indicator to the relative proximity of object distance underwater form the sensor. As a conclusion, the system can detect the presence of an object underwater within the range of ultrasonic sensor and display the measured distance onto the mobile phone and the real time graph had been successfully generated.

Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

NASA Astrophysics Data System (ADS)

Abdeljaber, Osama; Avci, Onur; Kiranyaz, Serkan; Gabbouj, Moncef; Inman, Daniel J.

2017-02-01

Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

Coarse-to-fine deep neural network for fast pedestrian detection

NASA Astrophysics Data System (ADS)

Li, Yaobin; Yang, Xinmei; Cao, Lijun

2017-11-01

Pedestrian detection belongs to a category of object detection is a key issue in the field of video surveillance and automatic driving. Although recent object detection methods, such as Fast/Faster RCNN, have achieved excellent performance, it is difficult to meet real-time requirements and limits the application in real scenarios. A coarse-to-fine deep neural network for fast pedestrian detection is proposed in this paper. Two-stage approach is presented to realize fine trade-off between accuracy and speed. In the coarse stage, we train a fast deep convolution neural network to generate most pedestrian candidates at the cost of a number of false positives. The detector can cover the majority of scales, sizes, and occlusions of pedestrians. After that, a classification network is introduced to refine the pedestrian candidates generated from the previous stage. Refining through classification network, most of false detections will be excluded easily and the final pedestrian predictions with bounding box and confidence score are produced. Competitive results have been achieved on INRIA dataset in terms of accuracy, especially the method can achieve real-time detection that is faster than the previous leading methods. The effectiveness of coarse-to-fine approach to detect pedestrians is verified, and the accuracy and stability are also improved.

Real-time inspection by submarine images

NASA Astrophysics Data System (ADS)

Tascini, Guido; Zingaretti, Primo; Conte, Giuseppe

1996-10-01

A real-time application of computer vision concerning tracking and inspection of a submarine pipeline is described. The objective is to develop automatic procedures for supporting human operators in the real-time analysis of images acquired by means of cameras mounted on underwater remotely operated vehicles (ROV) Implementation of such procedures gives rise to a human-machine system for underwater pipeline inspection that can automatically detect and signal the presence of the pipe, of its structural or accessory elements, and of dangerous or alien objects in its neighborhood. The possibility of modifying the image acquisition rate in the simulations performed on video- recorded images is used to prove that the system performs all necessary processing with an acceptable robustness working in real-time up to a speed of about 2.5 kn, widely greater than that the actual ROVs and the security features allow.

Real-Time MENTAT programming language and architecture

NASA Technical Reports Server (NTRS)

Grimshaw, Andrew S.; Silberman, Ami; Liu, Jane W. S.

1989-01-01

Real-time MENTAT, a programming environment designed to simplify the task of programming real-time applications in distributed and parallel environments, is described. It is based on the same data-driven computation model and object-oriented programming paradigm as MENTAT. It provides an easy-to-use mechanism to exploit parallelism, language constructs for the expression and enforcement of timing constraints, and run-time support for scheduling and exciting real-time programs. The real-time MENTAT programming language is an extended C++. The extensions are added to facilitate automatic detection of data flow and generation of data flow graphs, to express the timing constraints of individual granules of computation, and to provide scheduling directives for the runtime system. A high-level view of the real-time MENTAT system architecture and programming language constructs is provided.

Detection of Streptococcus pneumoniae and Haemophilus influenzae Type B by Real-Time PCR from Dried Blood Spot Samples among Children with Pneumonia: A Useful Approach for Developing Countries

PubMed Central

Selva, Laura; Benmessaoud, Rachid; Lanaspa, Miguel; Jroundi, Imane; Moraleda, Cinta; Acacio, Sozinho; Iñigo, Melania; Bastiani, Alien; Monsonis, Manuel; Pallares, Roman; Bassat, Quique; Muñoz-Almagro, Carmen

2013-01-01

Background Dried blood spot (DBS) is a reliable blood collection method for storing samples at room temperature and easily transporting them. We have previously validated a Real-Time PCR for detection of Streptococcus pneumoniae in DBS. The objective of this study was to apply this methodology for the diagnosis of S. pneumoniae and Haemophilus influenzae b (Hib) in DBS samples of children with pneumonia admitted to two hospitals in Mozambique and Morocco. Methods Ply and wzg genes of S. pneumoniae and bexA gene of Hib, were used as targets of Real-Time PCR. 329 DBS samples of children hospitalized with clinical diagnosis of pneumonia were tested. Results Real-Time PCR in DBS allowed for a significant increase in microbiological diagnosis of S. pneumoniae and Hib. When performing blood bacterial culture, only ten isolates of S. pneumoniae and none of Hib were detected (3·0% positivity rate, IC95% 1·4-5·5%). Real-Time PCR from DBS samples increased the detection yield by 4x fold, as 30 S. pneumoniae and 11 Hib cases were detected (12·4% positivity rate, IC95% 9·0-16·5%; P<0·001). Conclusion Real-Time PCR applied in DBS may be a valuable tool for improving diagnosis and surveillance of pneumonia caused by S. pneumoniae or Hib in developing countries. PMID:24116190

A real-time method for autonomous passive acoustic detection-classification of humpback whales.

PubMed

Abbot, Ted A; Premus, Vincent E; Abbot, Philip A

2010-05-01

This paper describes a method for real-time, autonomous, joint detection-classification of humpback whale vocalizations. The approach adapts the spectrogram correlation method used by Mellinger and Clark [J. Acoust. Soc. Am. 107, 3518-3529 (2000)] for bowhead whale endnote detection to the humpback whale problem. The objective is the implementation of a system to determine the presence or absence of humpback whales with passive acoustic methods and to perform this classification with low false alarm rate in real time. Multiple correlation kernels are used due to the diversity of humpback song. The approach also takes advantage of the fact that humpbacks tend to vocalize repeatedly for extended periods of time, and identification is declared only when multiple song units are detected within a fixed time interval. Humpback whale vocalizations from Alaska, Hawaii, and Stellwagen Bank were used to train the algorithm. It was then tested on independent data obtained off Kaena Point, Hawaii in February and March of 2009. Results show that the algorithm successfully classified humpback whales autonomously in real time, with a measured probability of correct classification in excess of 74% and a measured probability of false alarm below 1%.

Real Time Search Algorithm for Observation Outliers During Monitoring Engineering Constructions

NASA Astrophysics Data System (ADS)

Latos, Dorota; Kolanowski, Bogdan; Pachelski, Wojciech; Sołoducha, Ryszard

2017-12-01

Real time monitoring of engineering structures in case of an emergency of disaster requires collection of a large amount of data to be processed by specific analytical techniques. A quick and accurate assessment of the state of the object is crucial for a probable rescue action. One of the more significant evaluation methods of large sets of data, either collected during a specified interval of time or permanently, is the time series analysis. In this paper presented is a search algorithm for those time series elements which deviate from their values expected during monitoring. Quick and proper detection of observations indicating anomalous behavior of the structure allows to take a variety of preventive actions. In the algorithm, the mathematical formulae used provide maximal sensitivity to detect even minimal changes in the object's behavior. The sensitivity analyses were conducted for the algorithm of moving average as well as for the Douglas-Peucker algorithm used in generalization of linear objects in GIS. In addition to determining the size of deviations from the average it was used the so-called Hausdorff distance. The carried out simulation and verification of laboratory survey data showed that the approach provides sufficient sensitivity for automatic real time analysis of large amount of data obtained from different and various sensors (total stations, leveling, camera, radar).

The BEFWM system for detection and phase conjugation of a weak laser beam

NASA Astrophysics Data System (ADS)

Khizhnyak, Anatoliy; Markov, Vladimir

2007-09-01

Real environmental conditions, such as atmospheric turbulence and aero-optics effects, make practical implementation of the object-in-the-loop (TIL) algorithm a very difficult task, especially when the system is set to operate with a signal from the diffuse surface image-resolved object. The problem becomes even more complex since for the remote object the intensity of the returned signal is extremely low. This presentation discusses the results of an analysis and experimental verification of a thresholdless coherent signal receiving system, capable not only in high-sensitivity detection of an ultra weak object-scattered light, but also in its high-gain amplification and phase conjugation. The process of coherent detection by using the Brillouin Enhanced Four Wave Mixing (BEFWM) enables retrieval of complete information on the received signal, including accurate measurement of its wavefront. This information can be used for direct real-time control of the adaptive mirror.

Evaluation of loop-mediated isothermal amplification method (LAMP) for pathogenic Leptospira spp. detection with leptospires isolation and real-time PCR.

PubMed

Suwancharoen, Duangjai; Sittiwicheanwong, Busara; Wiratsudakul, Anuwat

2016-09-01

Leptospirosis has been one of the worldwide zoonotic diseases caused by pathogenic Leptospira spp. Many molecular techniques have consecutively been developed to detect such pathogen including loop-mediated isothermal amplification method (LAMP). The objectives of this study were to evaluate the diagnostic accuracy of LAMP assay and real-time PCR using bacterial culture as the gold standard and to assess the agreement among these three tests using Cohen's kappa statistics. In total, 533 urine samples were collected from 266 beef and 267 dairy cattle reared in central region of Thailand. Sensitivity and specificity of LAMP were 96.8% (95% CI 81.5-99.8) and 97.0% (95% CI 94.9-98.2), respectively. The accuracy of LAMP (97.0%) was significantly higher than that of real-time PCR (91.9%) at 95% CI. With Cohen's kappa statistics, culture method and LAMP were substantially agreed with each other (77.4%), whereas real-time PCR only moderately agreed with culture (47.7%) and LAMP (45.3%), respectively. Consequently, LAMP was more effective than real-time PCR in detecting Leptospira spp. in the urine of cattle. Besides, LAMP had less cost and was simpler than real-time PCR. Thus, LAMP was an excellent alternative for routine surveillance of leptospirosis in cattle.

NATUREYES: Development of surveillance monitoring system for open spaces based on the analysis of different optical sensors data and environmental conditions

NASA Astrophysics Data System (ADS)

Molina-Jimenez, Teresa; Caballero-Aroca, Jose; Simón-Martín, Santiago; Hervás-Juan, Juan; García-Martínez, Jose-David; Pérez-Picazo, Emilio; Dolz-García, Ramón; Pons-Vila, Alejandro; Quintana-Rumbau, Salvador; Valiente Pardo, Jose Antonio; Estrela, Maria José; Pastor-Guzmán, Francisco

2005-09-01

We present results of a R&D project aimed to produce an environmental surveillance system that, working in wild areas, allows for a real-time observation and control of some ambient factors that could produce a natural disaster. The main objective of the project is the development of an open platform capable to work with several kinds of sensors, in order to adapt itself to the needs of each situation. The detection of environmental risks and management of this data to give a real-time response is the overall objective of the project. The main parts of the system are: 1.- Detection system: capable to perform real-time data and image communication, fully autonomous and designed to consider the environmental conditions. 2.- Alarm management headquaters: reception on real-time of data from the detector network. All the data is analysed to enable a decision about whether there is or not an alarm situation. 3.- Mobile alarm-reception system: portable system for reception of the alarm signal from the headquaters. The project was financed by the Science and Technology Ministry, National Research and Development Programme (TIC2000-0366-P4, 2001-2004).

[Contamination of health care institutions environmental objects by Legionella pneumophila].

PubMed

Shkarin, V V; Blagonravova, A S; Chubukova, O A; Korotaeva, S V

2011-01-01

AIM. The extent of environmental objects contamination by Legionella pneumophila in Nizhny Novgorod and Nizhny Novgorod region hospitals evaluation, and detection of potentially hazardous objects. 433 swabs of environmental objects, and 43 hot water supply and pool water samples from various departments of 4 multi-disciplinary hospitals were studies. DNA from environmental samples was detected by using real time PCR. L. pneumophila DNA was detected in 41 (9,47%) samples from environmental objects and in 2 (4,65%) samples from hot water supply. These bacteria were more frequently detected in environmental samples from physiotherapy departments. Repeated detection of legionellae from the same objects was registered. Circulation of legionellae in multidisciplinary hospitals was determined. Circulation high risk departments and risk objects--reservoirs of L. pneumophila in health care institutions were determined.

Autonomous Object Characterization with Large Datasets

DTIC Science & Technology

2015-10-18

desk, where a substantial amount of effort is required to transform raw photometry into a data product, minimizing the amount of time the analyst has...were used to explore concepts in satellite characterization and satellite state change. The first algorithm provides real- time stability estimation... Timely and effective space object (SO) characterization is a challenge, and requires advanced data processing techniques. Detection and identification

Feasibility of real-time location systems in monitoring recovery after major abdominal surgery.

PubMed

Dorrell, Robert D; Vermillion, Sarah A; Clark, Clancy J

2017-12-01

Early mobilization after major abdominal surgery decreases postoperative complications and length of stay, and has become a key component of enhanced recovery pathways. However, objective measures of patient movement after surgery are limited. Real-time location systems (RTLS), typically used for asset tracking, provide a novel approach to monitoring in-hospital patient activity. The current study investigates the feasibility of using RTLS to objectively track postoperative patient mobilization. The real-time location system employs a meshed network of infrared and RFID sensors and detectors that sample device locations every 3 s resulting in over 1 million data points per day. RTLS tracking was evaluated systematically in three phases: (1) sensitivity and specificity of the tracking device using simulated patient scenarios, (2) retrospective passive movement analysis of patient-linked equipment, and (3) prospective observational analysis of a patient-attached tracking device. RTLS tracking detected a simulated movement out of a room with sensitivity of 91% and specificity 100%. Specificity decreased to 75% if time out of room was less than 3 min. All RTLS-tagged patient-linked equipment was identified for 18 patients, but measurable patient movement associated with equipment was detected for only 2 patients (11%) with 1-8 out-of-room walks per day. Ten patients were prospectively monitored using RTLS badges following major abdominal surgery. Patient movement was recorded using patient diaries, direct observation, and an accelerometer. Sensitivity and specificity of RTLS patient tracking were both 100% in detecting out-of-room ambulation and correlated well with direct observation and patient-reported ambulation. Real-time location systems are a novel technology capable of objectively and accurately monitoring patient movement and provide an innovative approach to promoting early mobilization after surgery.

A multi-camera system for real-time pose estimation

NASA Astrophysics Data System (ADS)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

Online decoding of object-based attention using real-time fMRI.

PubMed

Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J

2014-01-01

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Real-time detection and discrimination of visual perception using electrocorticographic signals

NASA Astrophysics Data System (ADS)

Kapeller, C.; Ogawa, H.; Schalk, G.; Kunii, N.; Coon, W. G.; Scharinger, J.; Guger, C.; Kamada, K.

2018-06-01

Objective. Several neuroimaging studies have demonstrated that the ventral temporal cortex contains specialized regions that process visual stimuli. This study investigated the spatial and temporal dynamics of electrocorticographic (ECoG) responses to different types and colors of visual stimulation that were presented to four human participants, and demonstrated a real-time decoder that detects and discriminates responses to untrained natural images. Approach. ECoG signals from the participants were recorded while they were shown colored and greyscale versions of seven types of visual stimuli (images of faces, objects, bodies, line drawings, digits, and kanji and hiragana characters), resulting in 14 classes for discrimination (experiment I). Additionally, a real-time system asynchronously classified ECoG responses to faces, kanji and black screens presented via a monitor (experiment II), or to natural scenes (i.e. the face of an experimenter, natural images of faces and kanji, and a mirror) (experiment III). Outcome measures in all experiments included the discrimination performance across types based on broadband γ activity. Main results. Experiment I demonstrated an offline classification accuracy of 72.9% when discriminating among the seven types (without color separation). Further discrimination of grey versus colored images reached an accuracy of 67.1%. Discriminating all colors and types (14 classes) yielded an accuracy of 52.1%. In experiment II and III, the real-time decoder correctly detected 73.7% responses to face, kanji and black computer stimuli and 74.8% responses to presented natural scenes. Significance. Seven different types and their color information (either grey or color) could be detected and discriminated using broadband γ activity. Discrimination performance maximized for combined spatial-temporal information. The discrimination of stimulus color information provided the first ECoG-based evidence for color-related population-level cortical broadband γ responses in humans. Stimulus categories can be detected by their ECoG responses in real time within 500 ms with respect to stimulus onset.

Foliage penetration by using 4-D point cloud data

NASA Astrophysics Data System (ADS)

Méndez Rodríguez, Javier; Sánchez-Reyes, Pedro J.; Cruz-Rivera, Sol M.

2012-06-01

Real-time awareness and rapid target detection are critical for the success of military missions. New technologies capable of detecting targets concealed in forest areas are needed in order to track and identify possible threats. Currently, LAser Detection And Ranging (LADAR) systems are capable of detecting obscured targets; however, tracking capabilities are severely limited. Now, a new LADAR-derived technology is under development to generate 4-D datasets (3-D video in a point cloud format). As such, there is a new need for algorithms that are able to process data in real time. We propose an algorithm capable of removing vegetation and other objects that may obfuscate concealed targets in a real 3-D environment. The algorithm is based on wavelets and can be used as a pre-processing step in a target recognition algorithm. Applications of the algorithm in a real-time 3-D system could help make pilots aware of high risk hidden targets such as tanks and weapons, among others. We will be using a 4-D simulated point cloud data to demonstrate the capabilities of our algorithm.

Implementing a real time reasoning system for robust diagnosis

NASA Technical Reports Server (NTRS)

Hill, Tim; Morris, William; Robertson, Charlie

1993-01-01

The objective of the Thermal Control System Automation Project (TCSAP) is to develop an advanced fault detection, isolation, and recovery (FDIR) capability for use on the Space Station Freedom (SSF) External Active Thermal Control System (EATCS). Real-time monitoring, control, and diagnosis of the EATCS will be performed with a knowledge based system (KBS). Implementation issues for the current version of the KBS are discussed.

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.

Applicability of Deep-Learning Technology for Relative Object-Based Navigation

DTIC Science & Technology

2017-09-01

burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing...possible selections for navigating an unmanned ground vehicle (UGV) is through real- time visual odometry. To navigate in such an environment, the UGV...UGV) is through real- time visual odometry. To navigate in such an environment, the UGV needs to be able to detect, identify, and relate the static

Real-Time pedestrian detection : layered object recognition system for pedestrian collision sensing.

DOT National Transportation Integrated Search

2010-01-01

In 2005 alone, 64,000 pedestrians were injured and 4,882 were killed in the United States, with pedestrians accounting for 11 percent of all traffic fatalities and 2 percent of injuries. The focus of "Layered Object Recognition System for Pedestrian ...

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.

Real-time 3-dimensional contrast-enhanced ultrasound in detecting hemorrhage of blunt renal trauma.

PubMed

Xu, Rui-Xue; Li, Ye-Kuo; Li, Ting; Wang, Sha-Sha; Yuan, Gui-Zhong; Zhou, Qun-Fang; Zheng, Hai-Rong; Yan, Fei

2013-10-01

The objective of this study is to evaluate the diagnostic value of real-time 3-dimensional contrast-enhanced ultrasound in the hemorrhage of blunt renal trauma. Eighteen healthy New Zealand white rabbits were randomly divided into 3 groups. Blunt renal trauma was performed on each group by using minitype striker. Ultrasonography, color Doppler flow imaging, and contrast-enhanced 2-dimensional and real-time 3-dimensional ultrasound were applied before and after the strike. The time to shock and blood pressure were subjected to statistical analysis. Then, a comparative study of ultrasound and pathology was carried out. All the struck kidneys were traumatic. In the ultrasonography, free fluid was found under the renal capsule. In the color Doppler flow imaging, active hemorrhage was not identified. In 2-dimensional contrast-enhanced ultrasound, active hemorrhage of the damaged kidney was characterized. Real-time 3-dimensional contrast-enhanced ultrasound showed a real-time and stereoscopic ongoing bleeding of the injured kidney. The wider the hemorrhage area in 4-dimensional contrast-enhanced ultrasound was, the faster the blood pressure decreased. Real-time 3-dimensional contrast-enhanced ultrasound is a promising noninvasive tool for stereoscopically and vividly detecting ongoing hemorrhage of blunt renal trauma in real time. © 2013.

Analysis of real-time vibration data

USGS Publications Warehouse

Safak, E.

2005-01-01

In recent years, a few structures have been instrumented to provide continuous vibration data in real time, recording not only large-amplitude motions generated by extreme loads, but also small-amplitude motions generated by ambient loads. The main objective in continuous recording is to track any changes in structural characteristics, and to detect damage after an extreme event, such as an earthquake or explosion. The Fourier-based spectral analysis methods have been the primary tool to analyze vibration data from structures. In general, such methods do not work well for real-time data, because real-time data are mainly composed of ambient vibrations with very low amplitudes and signal-to-noise ratios. The long duration, linearity, and the stationarity of ambient data, however, allow us to utilize statistical signal processing tools, which can compensate for the adverse effects of low amplitudes and high noise. The analysis of real-time data requires tools and techniques that can be applied in real-time; i.e., data are processed and analyzed while being acquired. This paper presents some of the basic tools and techniques for processing and analyzing real-time vibration data. The topics discussed include utilization of running time windows, tracking mean and mean-square values, filtering, system identification, and damage detection.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation.

PubMed

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

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

Kim, Young-Keun, E-mail: ykkim@handong.edu; Kim, Kyung-Soo

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-basedmore » sensor, the system is expected to be highly robust to sea weather conditions.« less

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

NASA Astrophysics Data System (ADS)

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

LivePhantom: Retrieving Virtual World Light Data to Real Environments.

PubMed

Kolivand, Hoshang; Billinghurst, Mark; Sunar, Mohd Shahrizal

2016-01-01

To achieve realistic Augmented Reality (AR), shadows play an important role in creating a 3D impression of a scene. Casting virtual shadows on real and virtual objects is one of the topics of research being conducted in this area. In this paper, we propose a new method for creating complex AR indoor scenes using real time depth detection to exert virtual shadows on virtual and real environments. A Kinect camera was used to produce a depth map for the physical scene mixing into a single real-time transparent tacit surface. Once this is created, the camera's position can be tracked from the reconstructed 3D scene. Real objects are represented by virtual object phantoms in the AR scene enabling users holding a webcam and a standard Kinect camera to capture and reconstruct environments simultaneously. The tracking capability of the algorithm is shown and the findings are assessed drawing upon qualitative and quantitative methods making comparisons with previous AR phantom generation applications. The results demonstrate the robustness of the technique for realistic indoor rendering in AR systems.

LivePhantom: Retrieving Virtual World Light Data to Real Environments

PubMed Central

2016-01-01

To achieve realistic Augmented Reality (AR), shadows play an important role in creating a 3D impression of a scene. Casting virtual shadows on real and virtual objects is one of the topics of research being conducted in this area. In this paper, we propose a new method for creating complex AR indoor scenes using real time depth detection to exert virtual shadows on virtual and real environments. A Kinect camera was used to produce a depth map for the physical scene mixing into a single real-time transparent tacit surface. Once this is created, the camera’s position can be tracked from the reconstructed 3D scene. Real objects are represented by virtual object phantoms in the AR scene enabling users holding a webcam and a standard Kinect camera to capture and reconstruct environments simultaneously. The tracking capability of the algorithm is shown and the findings are assessed drawing upon qualitative and quantitative methods making comparisons with previous AR phantom generation applications. The results demonstrate the robustness of the technique for realistic indoor rendering in AR systems. PMID:27930663

Simulation of a Real-Time Brain Computer Interface for Detecting a Self-Paced Hitting Task.

PubMed

Hammad, Sofyan H; Kamavuako, Ernest N; Farina, Dario; Jensen, Winnie

2016-12-01

An invasive brain-computer interface (BCI) is a promising neurorehabilitation device for severely disabled patients. Although some systems have been shown to work well in restricted laboratory settings, their utility must be tested in less controlled, real-time environments. Our objective was to investigate whether a specific motor task could be reliably detected from multiunit intracortical signals from freely moving animals in a simulated, real-time setting. Intracortical signals were first obtained from electrodes placed in the primary motor cortex of four rats that were trained to hit a retractable paddle (defined as a "Hit"). In the simulated real-time setting, the signal-to-noise-ratio was first increased by wavelet denoising. Action potentials were detected, and features were extracted (spike count, mean absolute values, entropy, and combination of these features) within pre-defined time windows (200 ms, 300 ms, and 400 ms) to classify the occurrence of a "Hit." We found higher detection accuracy of a "Hit" (73.1%, 73.4%, and 67.9% for the three window sizes, respectively) when the decision was made based on a combination of features rather than on a single feature. However, the duration of the window length was not statistically significant (p = 0.5). Our results showed the feasibility of detecting a motor task in real time in a less restricted environment compared to environments commonly applied within invasive BCI research, and they showed the feasibility of using information extracted from multiunit recordings, thereby avoiding the time-consuming and complex task of extracting and sorting single units. © 2016 International Neuromodulation Society.

Real-time detection of optical transients with RAPTOR

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

Borozdin, K. N.; Brumby, Steven P.; Galassi, M. C.

2002-01-01

Fast variability of optical objects is an interesting though poorly explored subject in modern astronomy. Real-time data processing and identification of transient, celestial events in the images is very important, for such study as it allows rapid follow-up with more sensitive instruments, We discuss an approach which we have chosen for the RAPTOR project which is a pioneering close-loop system combining real-time transient detection with rapid follow-up. Our data processing pipeline is able to identify and localize an optical transient within seconds after the observation. We describe the challenges we met, solutions we found and some results obtained in ourmore » search for fast optical transients. The software pipeline we have developed for RAPTOR can easily be applied to the data from other experiments.« less

A novel duplex real time quantitative reverse transcription polymerase chain reaction for rubella virus with armored RNA as a noncompetitive internal positive control.

PubMed

Zhao, Lihong; Li, Ruiying; Liu, Aihua; Zhao, Shuping

2015-07-01

The objective of this study was to build and apply a duplex real time quantitative reverse transcription-polymerase chain reaction (RT-PCR) for rubella virus. Firstly, a 60-bp-long armored RV RNA was constructed in the laboratory. Secondly, a duplex real time RT-PCR assay was established. Thirdly, the 60-bp-long armored RV RNA was used as an internal positive control (IPC) for the duplex real time RT-PCR. And finally the duplex real time RT-PCR assay was applied to detect RV RNA in clinical specimens. The in-house assay has a high amplification efficiency (0.99), a high analytical sensitivity (200 copies/mL), and a good reproducibility. The diagnostic specificity and sensitivity of the in-house assay were both 100%, due to the monitoring of the armored RV RNA IPC. Therefore, the in-house duplex real time quantitative RT-PCR assay is a specific, sensitive, reproducible and accurate assay for quantitation of RV RNA in clinical specimens. And noncompetitive armored RV RNA IPC can monitor RT-PCR inhibition and prevent false-negative and inaccurate results in the real time detection system. Copyright © 2015 Elsevier B.V. All rights reserved.

Real-time, continuous-wave terahertz imaging using a microbolometer focal-plane array

NASA Technical Reports Server (NTRS)

Hu, Qing (Inventor); Min Lee, Alan W. (Inventor)

2010-01-01

The present invention generally provides a terahertz (THz) imaging system that includes a source for generating radiation (e.g., a quantum cascade laser) having one or more frequencies in a range of about 0.1 THz to about 10 THz, and a two-dimensional detector array comprising a plurality of radiation detecting elements that are capable of detecting radiation in that frequency range. An optical system directs radiation from the source to an object to be imaged. The detector array detects at least a portion of the radiation transmitted through the object (or reflected by the object) so as to form a THz image of that object.

Some of the thousand words a picture is worth.

PubMed

Mandler, J M; Johnson, N S

1976-09-01

The effects of real-world schemata on recognition of complex pictures were studied. Two kinds of pictures were used: pictures of objects forming real-world scenes and unorganized collections of the same objects. The recognition test employed distractors that varied four types of information: inventory, spatial location, descriptive and spatial composition. Results emphasized the selective nature of schemata since superior recognition of one kind of information was offset by loss of another. Spatial location information was better recognized in real-world scenes and spatial composition information was better recognized in unorganized scenes. Organized and unorganized pictures did not differ with respect of inventory and descriptive information. The longer the pictures were studied, the longer subjects took to recognize them. Reaction time for hits, misses, and false alarms increased dramatically as presentation time increased from 5 to 60 sec. It was suggested that detection of a difference in a distractor terminated search, but that when no difference was detected, an exhaustive search of the available information took place.

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

TaqMan real-time RT-PCR detection of infectious salmon anaemia virus (ISAV) from formalin-fixed paraffin-embedded Atlantic salmon Salmo salar tissues.

PubMed

Godoy, M G; Kibenge, F S; Kibenge, M J; Olmos, P; Ovalle, L; Yañez, A J; Avendaño-Herrera, R

2010-05-18

The objective of this study was to evaluate the application of a TaqMan real-time reverse transcriptase PCR (RT-PCR) assay for the detection of infectious salmon anaemia virus (ISAV) in formalin-fixed paraffin-embedded (FFPE) fish tissues from Atlantic salmon Salmo salar with and without clinical signs of infection, and to compare it with histological and immunohistochemical (IHC) techniques. Sixteen fish samples obtained in 2007 and 2008 from 4 different farms in Chile were examined. The real-time RT-PCR allowed the detection of ISAV in FFPE samples from 9 of 16 fish, regardless of the organs analyzed, whereas 4 of the real-time RT-PCR negative fish were positive as indicated by histological examination and 3 of the real-time RT-PCR positive fish were negative as indicated by immunohistochemistry evaluation. The presence of ISAV in RT-PCR positive samples was confirmed by amplicon sequencing. This work constitutes the first report on the use of real-time RT-PCR for the detection of ISAV in FFPE sections. The assay is very useful for the examination of archival wax-embedded tissues, and allows for both prospective and retrospective evaluation of tissue samples for the presence of ISAV. However, the method only confirms the presence of the pathogen and should be used in combination with histopathology, which is a more precise tool. The combination of both techniques would be invaluable for confirmatory diagnosis of infectious salmon anaemia (ISA), which is essential for solving salmon farm problems.

Comparison of nested-multiplex, Taqman & SYBR Green real-time PCR in diagnosis of amoebic liver abscess in a tertiary health care institute in India

PubMed Central

Dinoop, K.P.; Parija, Subhash Chandra; Mandal, Jharna; Swaminathan, R.P.; Narayanan, P.

2016-01-01

Background & objectives: Amoebiasis is a common parasitic infection caused by Entamoeba histolytica and amoebic liver abscess (ALA) is the most common extraintestinal manifestation of amoebiasis. The aim of this study was to standardise real-time PCR assays (Taqman and SYBR Green) to detect E. histolytica from liver abscess pus and stool samples and compare its results with nested-multiplex PCR. Methods: Liver abscess pus specimens were subjected to DNA extraction. The extracted DNA samples were subjected to amplification by nested-multiplex PCR, Taqman (18S rRNA) and SYBR Green real-time PCR (16S-like rRNA assays to detect E. histolytica/E. dispar/E. moshkovskii). The amplification products were further confirmed by DNA sequence analysis. Receiver operator characteristic (ROC) curve analysis was done for nested-multiplex and SYBR Green real-time PCR and the area under the curve was calculated for evaluating the accuracy of the tests to dignose ALA. Results: In all, 17, 19 and 25 liver abscess samples were positive for E. histolytica by nested-multiplex PCR, SYBR Green and Taqman real-time PCR assays, respectively. Significant differences in detection of E. histolytica were noted in the real-time PCR assays evaluated (P<0.0001). The nested-multiplex PCR, SYBR Green real-time PCR and Taqman real-time PCR evaluated showed a positivity rate of 34, 38 and 50 per cent, respectively. Based on ROC curve analysis (considering Taqman real-time PCR as the gold standard), it was observed that SYBR Green real-time PCR was better than conventional nested-multiplex PCR for the diagnosis of ALA. Interpretation & conclusions: Taqman real-time PCR targeting the 18S rRNA had the highest positivity rate evaluated in this study. Both nested multiplex and SYBR Green real-time PCR assays utilized were evaluated to give accurate results. Real-time PCR assays can be used as the gold standard in rapid and reliable diagnosis, and appropriate management of amoebiasis, replacing the conventional molecular methods. PMID:26997014

The Accuracy of Eyelid Movement Parameters for Drowsiness Detection

PubMed Central

Wilkinson, Vanessa E.; Jackson, Melinda L.; Westlake, Justine; Stevens, Bronwyn; Barnes, Maree; Swann, Philip; Rajaratnam, Shantha M. W.; Howard, Mark E.

2013-01-01

Study Objectives: Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. Methods: In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). Results: Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. Conclusions: Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness. Citation: Wilkinson VE; Jackson ML; Westlake J; Stevens B; Barnes M; Swann P; Rajaratnam SMW; Howard ME. The accuracy of eyelid movement parameters for drowsiness detection. J Clin Sleep Med 2013;9(12):1315-1324. PMID:24340294

Development of an in-house fast real-time PCR method for detection of fish allergen in foods and comparison with a commercial kit.

PubMed

Herrero, Beatriz; Vieites, Juan M; Espiñeira, Montserrat

2014-05-15

Food allergy is recognised as an important human health problem. Fish represent one of the most important causes of food hypersensitivity reaction. Small amounts of the allergen can cause severe reactions in sensitive individuals, so correct labelling is essential to ensure the protection of consumers. The objective of the present work was to develop a reliable, sensitive and specific real-time PCR method for the detection of fish and traces of fish in all kind of products included those that have undergone aggressive treatments such as high temperature or pressure. This methodology was validated simulating products likely to contain this allergen and spiking them with fish cooking water. In addition, a comparison between the performance of in-house methodology and a commercial kit, both of them based on real-time PCR, was carried out. This work is relevant because it is the first, rapid real-time PCR method developed to date for the detection of fish in processed food products. The results obtained confirm the present assay is a useful tool in detecting fish and, therefore, minimising exposure and reducing incidences of allergic reaction to fish in contaminated products. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparison of real-time PCR with disk diffusion, agar screen and E-test methods for detection of methicillin-resistant Staphylococcus aureus.

PubMed

Shariati, Laleh; Validi, Majid; Tabatabaiefar, Mohammad Amin; Karimi, Ali; Nafisi, Mohammad Reza

2010-12-01

Methicillin-resistant Staphylococcus aureus (MRSA) is a nosocomial pathogen. Our main objective was to compare oxacillin disk test, oxacillin E-test, and oxacillin agar screen for detection of methicillin resistance in S. aureus, using real-time PCR for mecA as the "gold standard" comparison assay. 196 S. aureus isolates were identified out of 284 Staphylococcus isolates. These isolates were screened for MRSA with several methods: disk diffusion, agar screen (6.0 μg/ml), oxacillin E-test, and real-time PCR for detection of mecA gene. Of the 196 S. aureus isolates tested, 96 isolates (49%) were mecA-positive and 100 isolates (51%) mecA-negative. All methods tested had a statistically significant agreement with real-time PCR. E-test was 100% sensitive and specific for mecA presence. The sensitivity and specificity of oxacillin agar screen method were 98 and 99%, respectively and sensitivity and specificity of oxacillin disk diffusion method were 95 and 93%, respectively. In the present study, oxacillin E-test is proposed as the best phenotypic method. For economic reasons, the oxacillin agar screen method (6.0 μg/ml), which is suitable for the detection of MRSA, is recommended due to its accuracy and low cost.

Effective real-time vehicle tracking using discriminative sparse coding on local patches

NASA Astrophysics Data System (ADS)

Chen, XiangJun; Ye, Feiyue; Ruan, Yaduan; Chen, Qimei

2016-01-01

A visual tracking framework that provides an object detector and tracker, which focuses on effective and efficient visual tracking in surveillance of real-world intelligent transport system applications, is proposed. The framework casts the tracking task as problems of object detection, feature representation, and classification, which is different from appearance model-matching approaches. Through a feature representation of discriminative sparse coding on local patches called DSCLP, which trains a dictionary on local clustered patches sampled from both positive and negative datasets, the discriminative power and robustness has been improved remarkably, which makes our method more robust to a complex realistic setting with all kinds of degraded image quality. Moreover, by catching objects through one-time background subtraction, along with offline dictionary training, computation time is dramatically reduced, which enables our framework to achieve real-time tracking performance even in a high-definition sequence with heavy traffic. Experiment results show that our work outperforms some state-of-the-art methods in terms of speed, accuracy, and robustness and exhibits increased robustness in a complex real-world scenario with degraded image quality caused by vehicle occlusion, image blur of rain or fog, and change in viewpoint or scale.

Road detection and buried object detection in elevated EO/IR imagery

NASA Astrophysics Data System (ADS)

Kennedy, Levi; Kolba, Mark P.; Walters, Joshua R.

2012-06-01

To assist the warfighter in visually identifying potentially dangerous roadside objects, the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) has developed an elevated video sensor system testbed for data collection. This system provides color and mid-wave infrared (MWIR) imagery. Signal Innovations Group (SIG) has developed an automated processing capability that detects the road within the sensor field of view and identifies potentially threatening buried objects within the detected road. The road detection algorithm leverages system metadata to project the collected imagery onto a flat ground plane, allowing for more accurate detection of the road as well as the direct specification of realistic physical constraints in the shape of the detected road. Once the road has been detected in an image frame, a buried object detection algorithm is applied to search for threatening objects within the detected road space. The buried object detection algorithm leverages textural and pixel intensity-based features to detect potential anomalies and then classifies them as threatening or non-threatening objects. Both the road detection and the buried object detection algorithms have been developed to facilitate their implementation in real-time in the NVESD system.

Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study.

PubMed

Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A

2018-03-01

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.

Detecting method of subjects' 3D positions and experimental advanced camera control system

NASA Astrophysics Data System (ADS)

Kato, Daiichiro; Abe, Kazuo; Ishikawa, Akio; Yamada, Mitsuho; Suzuki, Takahito; Kuwashima, Shigesumi

1997-04-01

Steady progress is being made in the development of an intelligent robot camera capable of automatically shooting pictures with a powerful sense of reality or tracking objects whose shooting requires advanced techniques. Currently, only experienced broadcasting cameramen can provide these pictures.TO develop an intelligent robot camera with these abilities, we need to clearly understand how a broadcasting cameraman assesses his shooting situation and how his camera is moved during shooting. We use a real- time analyzer to study a cameraman's work and his gaze movements at studios and during sports broadcasts. This time, we have developed a detecting method of subjects' 3D positions and an experimental camera control system to help us further understand the movements required for an intelligent robot camera. The features are as follows: (1) Two sensor cameras shoot a moving subject and detect colors, producing its 3D coordinates. (2) Capable of driving a camera based on camera movement data obtained by a real-time analyzer. 'Moving shoot' is the name we have given to the object position detection technology on which this system is based. We used it in a soccer game, producing computer graphics showing how players moved. These results will also be reported.

Using Real-Time PCR as a tool for monitoring the authenticity of commercial coffees.

PubMed

Ferreira, Thiago; Farah, Adriana; Oliveira, Tatiane C; Lima, Ivanilda S; Vitório, Felipe; Oliveira, Edna M M

2016-05-15

Coffee is one of the main food products commercialized in the world. Its considerable market value among food products makes it susceptible to adulteration, especially with cereals. Therefore, the objective of this study was to develop a method based on Real-Time Polymerase Chain Reaction (PCR) for detection of cereals in commercial ground roast and soluble coffees. After comparison with standard curves obtained by serial dilution of DNA extracted from barley, corn and rice, the method was sensitive and specific to quantify down to 0.6 pg, 14 pg and 16 pg of barley, corn and rice DNA, respectively. To verify the applicability of the method, 30 commercial samples obtained in different countries were evaluated and those classified as gourmets or superior did not present the tested cereals DNA. However, barley was detected in various traditional (cheaper) samples from South America. In addition, corn and rice were also detected in different samples. Real-Time PCR showed to be suitable for detection of food adulterants in commercial ground roast and soluble coffees. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lidar-based door and stair detection from a mobile robot

NASA Astrophysics Data System (ADS)

Bansal, Mayank; Southall, Ben; Matei, Bogdan; Eledath, Jayan; Sawhney, Harpreet

2010-04-01

We present an on-the-move LIDAR-based object detection system for autonomous and semi-autonomous unmanned vehicle systems. In this paper we make several contributions: (i) we describe an algorithm for real-time detection of objects such as doors and stairs in indoor environments; (ii) we describe efficient data structures and algorithms for processing 3D point clouds acquired by laser scanners in a streaming manner, which minimize the memory copying and access. We show qualitative results demonstrating the effectiveness of our approach on runs in an indoor office environment.

Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions

NASA Astrophysics Data System (ADS)

Marchesotti, Luca; Piva, Stefano; Turolla, Andrea; Minetti, Deborah; Regazzoni, Carlo S.

2005-03-01

The presented work describes an innovative architecture for multi-sensor distributed video surveillance applications. The aim of the system is to track moving objects in outdoor environments with a cooperative strategy exploiting two video cameras. The system also exhibits the capacity of focusing its attention on the faces of detected pedestrians collecting snapshot frames of face images, by segmenting and tracking them over time at different resolution. The system is designed to employ two video cameras in a cooperative client/server structure: the first camera monitors the entire area of interest and detects the moving objects using change detection techniques. The detected objects are tracked over time and their position is indicated on a map representing the monitored area. The objects" coordinates are sent to the server sensor in order to point its zooming optics towards the moving object. The second camera tracks the objects at high resolution. As well as the client camera, this sensor is calibrated and the position of the object detected on the image plane reference system is translated in its coordinates referred to the same area map. In the map common reference system, data fusion techniques are applied to achieve a more precise and robust estimation of the objects" track and to perform face detection and tracking. The work novelties and strength reside in the cooperative multi-sensor approach, in the high resolution long distance tracking and in the automatic collection of biometric data such as a person face clip for recognition purposes.

Real-time, T-ray imaging using a sub-terahertz gyrotron

NASA Astrophysics Data System (ADS)

Han, Seong-Tae; Torrezan, Antonio C.; Sirigiri, Jagadishwar R.; Shapiro, Michael A.; Temkin, Richard J.

2012-06-01

We demonstrated real-time, active, T-ray imaging using a 0.46 THz gyrotron capable of producing 16 W in continuous wave operation and a pyroelectric array camera with 124-by-124 pixels. An expanded Gaussian beam from the gyrotron was used to maintain the power density above the detection level of the pyroelectric array over the area of the irradiated object. Real-time imaging at a video rate of 48 Hz was achieved through the use of the built-in chopper of the camera. Potential applications include fast scanning for security purposes and for quality control of dry or frozen foods.

Real-time model-based vision system for object acquisition and tracking

NASA Technical Reports Server (NTRS)

Wilcox, Brian; Gennery, Donald B.; Bon, Bruce; Litwin, Todd

1987-01-01

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

Algorithms and data structures for automated change detection and classification of sidescan sonar imagery

NASA Astrophysics Data System (ADS)

Gendron, Marlin Lee

During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author's Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3--48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author's repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the CAS performs geospatial searching 1.75x faster on large data sets. Finally, the concluding chapter of this dissertation gives important details on how the completed ACDC system will function, and discusses the author's future research to develop additional algorithms and data structures for ACDC.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

[The development and implementation of polymerase chain reaction to detect in real-time operation mode yersinia pestis in field material].

PubMed

Afanas'ev, M V; Chipanin, E V; Shestakov, V E; Denisov, A V; Fomina, L A; Ostiak, A S; Balakhonov, S V

2013-03-01

The article presents the results of development and practical implementation of system of polymerase chain reaction testing in real-time operation mode to detect agent of plague infield material. In laboratory conditions the system demonstrated good results and hence it was applied in conditions of field laboratory of epidemiologic team during planned epizootologic examination of Gorno-Altaisk hot spot of plague. The sampling consisted of more than 1400 objects. It was demonstrated that high sensitivity and specificity is immanent to proposed system. The adaptation of the system to the real time amplifier "Smart Cycler" (Cephid, USA) having some specific technical characteristics makes it possible to consider the proposed test-system as an effective sensitive and precise instrument for screening studies in the process of regular epizootologic examinations of hot spots of plague.

[Clinical utility of real-time fluorescent PCR for combined detection of anaplastic lymphoma kinase and c-ros oncogene 1 receptor tyrosine kinase in non-small cell lung cancer].

PubMed

Bai, D Y; Zhang, H P; Zhong, S; Suo, W H; Gao, D H; Ding, Y; Tu, J H

2016-12-23

Objective: To investigate the clinical application value of combined detection of ALK fusion gene and c-ros oncogene 1 receptor tyrosine kinase (ROS1) fusion gene in non-small cell lung cancer (NSCLC) using real-time fluorescent PCR. Methods: A kit for combined detection of ALK fusion gene and ROS1 fusion gene based on fluorescent PCR was used to simultaneously detect the two fusion genes in 302 cases of NSCLC specimens. The results were validated through Sanger sequencing. The consistency of the two detection methods was analyzed. Results: All 302 cases of NSCLC specimens were successfully analyzed through fluorescent PCR (302/302). 12 cases (4.0%) were found to contain ALK fusion gene, including 3 cases with ALK-M1, 3 with ALK-M2, 3 with ALK-M3, 1 with ALK-M4, and 2 with ALK-M6 fusion gene.12 cases (4.0%) were found to contain ROS1 fusion gene, including 1 case with ROS1-M7, 8 cases with ROS1-M8, 1 case with ROS1-M12, 1 case with ROS1-M14, and 1 case with double-positive ROS1-M3 and ROS1-M8 fusion genes. The total detection rate of ALK fusion gene and ROS1 fusion gene was 7.9% (24/302) and 278 cases showed to be negative for ALK fusion gene and ROS1 fusion gene. The successful detection rates for Sanger DNA sequencing were also 100%. The positive, negative and total coincidence rates obtained by real-time fluorescent PCR and by Sanger DNA sequencing were all 100%. Conclusions: The results of Sanger DNA sequencing demonstrate that the real-time fluorescent PCR assay is equally effective in detecting ALK and ROS1 fusion genes in NSCLC tissues. Furthermore, real-time fluorescent PCR assay can be used to detect trace ALK and ROS1 fusion gene simultaneously in tiny samples, and can save time and avoid repeated sampling. It is worthy of recommendation as a rapid and reliable detection technique.

Space moving target detection using time domain feature

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.

The accuracy of eyelid movement parameters for drowsiness detection.

PubMed

Wilkinson, Vanessa E; Jackson, Melinda L; Westlake, Justine; Stevens, Bronwyn; Barnes, Maree; Swann, Philip; Rajaratnam, Shantha M W; Howard, Mark E

2013-12-15

Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness.

Oxygen flux as an indicator of physiological stress in aquatic organisms: a real-time biomonitoring system of water quality

NASA Astrophysics Data System (ADS)

Sanchez, Brian C.; Yale, Gowri; Chatni, Rameez; Ochoa-Acuña, Hugo G.; Porterfield, D. Marshall; Mclamore, Eric S.; Sepúlveda, María S.

2009-05-01

The detection of harmful chemicals and biological agents in real time is a critical need for protecting water quality. We studied the real-time effects of five environmental contaminants with differing modes of action (atrazine, pentachlorophenol, cadmium chloride, malathion, and potassium cyanide) on respiratory oxygen consumption in 2-day post-fertilization fathead minnow (Pimephales promelas) eggs. Our objective was to assess the sensitivity of fathead minnow eggs using the self-referencing micro-optrode technique to detect instantaneous changes in oxygen consumption after brief exposures to low concentrations of contaminants. Oxygen consumption data indicated that the technique is indeed sensitive enough to reliably detect physiological alterations induced by all contaminants. After 2 h of exposure, we identified significant increases in oxygen consumption upon exposure to pentachlorophenol (100 and 1000 μg/L), cadmium chloride (0.0002 and 0.002 μg/L), and atrazine (150 μg/L). In contrast, we observed a significant decrease in oxygen flux after exposures to potassium cyanide (5.2, 22, and 44 μg/L) and atrazine (1500 μg/L). No effects were detected after exposures to malathion (200 and 340 μg/L). We have also tested the sensitivity of Daphnia magna embryos as another animal model for real-time environmental biomonitoring. Our results are so far encouraging and support further development of this technology as a physiologically coupled biomonitoring tool for the detection of environmental toxicants.

Detecting changes in real-world objects: The relationship between visual long-term memory and change blindness.

PubMed

Brady, Timothy F; Konkle, Talia; Oliva, Aude; Alvarez, George A

2009-01-01

A large body of literature has shown that observers often fail to notice significant changes in visual scenes, even when these changes happen right in front of their eyes. For instance, people often fail to notice if their conversation partner is switched to another person, or if large background objects suddenly disappear.1,2 These 'change blindness' studies have led to the inference that the amount of information we remember about each item in a visual scene may be quite low.1 However, in recent work we have demonstrated that long-term memory is capable of storing a massive number of visual objects with significant detail about each item.3 In the present paper we attempt to reconcile these findings by demonstrating that observers do not experience 'change blindness' with the real world objects used in our previous experiment if they are given sufficient time to encode each item. The results reported here suggest that one of the major causes of change blindness for real-world objects is a lack of encoding time or attention to each object (see also refs. 4 and 5).

[Application of recombinase polymerase amplification in the detection of Pseudomonas aeruginosa].

PubMed

Jin, X J; Gong, Y L; Yang, L; Mo, B H; Peng, Y Z; He, P; Zhao, J N; Li, X L

2018-04-20

Objective: To establish an optimized method of recombinase polymerase amplification (RPA) to rapidly detect Pseudomonas aeruginosa in clinic. Methods: (1) The DNA templates of one standard Pseudomonas aeruginosa strain was extracted and detected by polymerase chain reaction (PCR), real-time fluorescence quantitative PCR and RPA. Time of sample loading, time of amplification, and time of detection of the three methods were recorded. (2) One standard Pseudomonas aeruginosa strain was diluted in 7 concentrations of 1×10(7,) 1×10(6,) 1×10(5,) 1×10(4,) 1×10(3,) 1×10(2,) and 1×10(1) colony forming unit (CFU)/mL after recovery and cultivation. The DNA templates of Pseudomonas aeruginosa and negative control strain Pseudomonas putida were extracted and detected by PCR, real-time fluorescence quantitative PCR, and RPA separately. The sensitivity of the three methods in detecting Pseudomonas aeruginosa was analyzed. (3) The DNA templates of one standard Pseudomonas aeruginosa strain and four negative control strains ( Staphylococcus aureus, Acinetobacter baumanii, Candida albicans, and Pseudomonas putida ) were extracted separately, and then they were detected by PCR, real-time fluorescence quantitative PCR, and RPA. The specificity of the three methods in detecting Pseudomonas aeruginosa was analyzed. (4) The DNA templates of 28 clinical strains of Pseudomonas aeruginosa preserved in glycerin, 1 clinical strain of which was taken by cotton swab, and negative control strain Pseudomonas putida were extracted separately, and then they were detected by RPA. Positive amplification signals of the clinical strains were observed, and the detection rate was calculated. All experiments were repeated for 3 times. Sensitivity results were analyzed by GraphPad Prism 5.01 statistical software. Results: (1) The loading time of RPA, PCR, and real-time fluorescence quantitative PCR for detecting Pseudomonas aeruginosa were all 20 minutes. In PCR, time of amplification was 98 minutes, time of gel detection was 20 minutes, and the total time was 138 minutes. In real-time fluorescence quantitative PCR, amplification and detection could be completed simultaneously, which took 90 minutes, and the total time was 110 minutes. In RPA, amplification and detection could also be completed simultaneously, which took 15 minutes, and the total time was 35 minutes. (2) Pseudomonas putida did not show positive amplification signals or gel positive results in any of the three detection methods. The detection limit of Pseudomonas aeruginosa in real-time fluorescence quantitative PCR and PCR was 1×10(1) CFU/mL, and that of Pseudomonas aeruginosa in RPA was 1×10(2) CFU/mL. In RPA and real-time fluorescence quantitative PCR, the higher the concentration of Pseudomonas aeruginosa, the shorter threshold time and smaller the number of cycles, namely shorter time for detecting the positive amplified signal. In real-time fluorescence quantitative PCR, all positive amplification signal could be detected when the concentration of Pseudomonas aeruginosa was 1×10(1)-1×10(7) CFU/mL. In RPA, the detection rate of positive amplification signal was 0 when the concentration of Pseudomonas aeruginosa was 1×10(1) CFU/mL, while the detection rate of positive amplification signal was 67% when the concentration of Pseudomonas aeruginosa was 1×10(2) CFU/mL, and the detection rate of positive amplification signal was 100% when the concentration of Pseudomonas aeruginosa was 1×10(3)-1×10(7) CFU/mL. (3) In RPA, PCR, and real-time fluorescence quantitative PCR, Pseudomonas aeruginosa showed positive amplification signals and gel positive results, but there were no positive amplification signals or gel positive results in four negative control strains of Acinetobacter baumannii, Staphylococcus aureus, Candida albicans, and Pseudomonas putida . (4) In RPA, 28 clinical strains of Pseudomonas aeruginosa preserved in glycerin and 1 clinical strain of Pseudomonas aeruginosa taken by cotton swab showed positive amplification signals, while Pseudomonas putida did not show positive amplification signal. The detection rate of positive amplification signal of 29 clinical strains of Pseudomonas aeruginosa in RPA was 100%. Conclusions: The established optimized RPA technology for fast detection of Pseudomonas aeruginosa requires shorter time, with high sensitivity and specificity. It was of great value in fast detection of Pseudomonas aeruginosa infection in clinic.

Analysis and segmentation of images in case of solving problems of detecting and tracing objects on real-time video

NASA Astrophysics Data System (ADS)

Ezhova, Kseniia; Fedorenko, Dmitriy; Chuhlamov, Anton

2016-04-01

The article deals with the methods of image segmentation based on color space conversion, and allow the most efficient way to carry out the detection of a single color in a complex background and lighting, as well as detection of objects on a homogeneous background. The results of the analysis of segmentation algorithms of this type, the possibility of their implementation for creating software. The implemented algorithm is very time-consuming counting, making it a limited application for the analysis of the video, however, it allows us to solve the problem of analysis of objects in the image if there is no dictionary of images and knowledge bases, as well as the problem of choosing the optimal parameters of the frame quantization for video analysis.

The Real-Time ObjectAgent Software Architecture for Distributed Satellite Systems

DTIC Science & Technology

2001-01-01

real - time operating system selection are also discussed. The fourth section describes a simple demonstration of real-time ObjectAgent. Finally, the...experience with C++. After selecting the programming language, it was necessary to select a target real - time operating system (RTOS) and embedded...ObjectAgent software to run on the OSE Real Time Operating System . In addition, she is responsible for the integration of ObjectAgent

The Fundamentals of Thermal Imaging Systems.

DTIC Science & Technology

1979-05-10

detection , recognition, or identification, of real ’coene objects aire discussed. It is hoped that the text will be useful to FLIR designers, evaluators...AND ANDERSON EXPERIMENT ........................ 205 Appendix F - BASIC SNR AND DETECTIVITY RELATIONS ................................... 209 Appendix... detection , recognition, or identification, of real scene objects are discussed. I• It is hoped that the material in the text will be useful to

Target tracking and surveillance by fusing stereo and RFID information

NASA Astrophysics Data System (ADS)

Raza, Rana H.; Stockman, George C.

2012-06-01

Ensuring security in high risk areas such as an airport is an important but complex problem. Effectively tracking personnel, containers, and machines is a crucial task. Moreover, security and safety require understanding the interaction of persons and objects. Computer vision (CV) has been a classic tool; however, variable lighting, imaging, and random occlusions present difficulties for real-time surveillance, resulting in erroneous object detection and trajectories. Determining object ID via CV at any instance of time in a crowded area is computationally prohibitive, yet the trajectories of personnel and objects should be known in real time. Radio Frequency Identification (RFID) can be used to reliably identify target objects and can even locate targets at coarse spatial resolution, while CV provides fuzzy features for target ID at finer resolution. Our research demonstrates benefits obtained when most objects are "cooperative" by being RFID tagged. Fusion provides a method to simplify the correspondence problem in 3D space. A surveillance system can query for unique object ID as well as tag ID information, such as target height, texture, shape and color, which can greatly enhance scene analysis. We extend geometry-based tracking so that intermittent information on ID and location can be used in determining a set of trajectories of N targets over T time steps. We show that partial-targetinformation obtained through RFID can reduce computation time (by 99.9% in some cases) and also increase the likelihood of producing correct trajectories. We conclude that real-time decision-making should be possible if the surveillance system can integrate information effectively between the sensor level and activity understanding level.

Event detection for car park entries by video-surveillance

NASA Astrophysics Data System (ADS)

Coquin, Didier; Tailland, Johan; Cintract, Michel

2007-10-01

Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting car park entries, using an adaptive background learning algorithm and two indicators representing activity and identity to overcome the difficulty of tracking objects.

Human detection in sensitive security areas through recognition of omega shapes using MACH filters

NASA Astrophysics Data System (ADS)

Rehman, Saad; Riaz, Farhan; Hassan, Ali; Liaquat, Muwahida; Young, Rupert

2015-03-01

Human detection has gained considerable importance in aggravated security scenarios over recent times. An effective security application relies strongly on detailed information regarding the scene under consideration. A larger accumulation of humans than the number of personal authorized to visit a security controlled area must be effectively detected, amicably alarmed and immediately monitored. A framework involving a novel combination of some existing techniques allows an immediate detection of an undesirable crowd in a region under observation. Frame differencing provides a clear visibility of moving objects while highlighting those objects in each frame acquired by a real time camera. Training of a correlation pattern recognition based filter on desired shapes such as elliptical representations of human faces (variants of an Omega Shape) yields correct detections. The inherent ability of correlation pattern recognition filters caters for angular rotations in the target object and renders decision regarding the existence of the number of persons exceeding an allowed figure in the monitored area.

Object Detection Techniques Applied on Mobile Robot Semantic Navigation

PubMed Central

Astua, Carlos; Barber, Ramon; Crespo, Jonathan; Jardon, Alberto

2014-01-01

The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency. PMID:24732101

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.

PubMed

Huang, Lvwen; Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-08-23

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor

PubMed Central

Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-01-01

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields. PMID:28832520

Evaluation of an image-based tracking workflow using a passive marker and resonant micro-coil fiducials for automatic image plane alignment in interventional MRI.

PubMed

Neumann, M; Breton, E; Cuvillon, L; Pan, L; Lorenz, C H; de Mathelin, M

2012-01-01

In this paper, an original workflow is presented for MR image plane alignment based on tracking in real-time MR images. A test device consisting of two resonant micro-coils and a passive marker is proposed for detection using image-based algorithms. Micro-coils allow for automated initialization of the object detection in dedicated low flip angle projection images; then the passive marker is tracked in clinical real-time MR images, with alternation between two oblique orthogonal image planes along the test device axis; in case the passive marker is lost in real-time images, the workflow is reinitialized. The proposed workflow was designed to minimize dedicated acquisition time to a single dedicated acquisition in the ideal case (no reinitialization required). First experiments have shown promising results for test-device tracking precision, with a mean position error of 0.79 mm and a mean orientation error of 0.24°.

Active Work Zone Safety Using Emerging Technologies : Final Report

DOT National Transportation Integrated Search

2017-07-01

The major objectives of this research were to (1) identify technologies that can be used in real time to detect a hazardous proximity situation between construction equipment and pedestrian workers and provide an appropriate warning; (2) develop a Bl...

An astrometric facility for planetary detection on the space station

NASA Technical Reports Server (NTRS)

Nishioka, Kenji; Scargle, Jeffrey D.; Givens, John J.

1987-01-01

An Astrometric Telescope Facility (ATF) for planetary detection is being studied as a potential space station initial operating capability payload. The primary science objective of this mission is the detection and study of planetary systems around other stars. In addition, the facility will be capable of other astrometric measurements such as stellar motions of other galaxies and highly precise direct measurement of stellar distance within the Milky Way Galaxy. The results of a recently completed ATF preliminary systems definition study are summarized. Results of this study indicate that the preliminary concept for the facility is fully capable of meeting the science objective without the development of any new technologies. A simple straightforward operations approach was developed for the ATF. A real-time facility control is not normally required, but does maintain a near real-time ground monitoring capability for the facility and science data stream on a full-time basis. Facility observational sequences are normally loaded once a week. In addition, the preliminary system is designed to be fail-safe and single-fault tolerant. Routine interactions by the space station crew with the ATF will not be necessary, but onboard controls are provided for crew override as required for emergencies and maintenance.

Flight elements: Fault detection and fault management

NASA Technical Reports Server (NTRS)

Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

1990-01-01

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

In vivo plant flow cytometry: A first proof-of-concept

PubMed Central

Nedosekin, Dmitry A.; Khodakovskaya, Mariya V.; Biris, Alexandru S.; Wang, Daoyuan; Xu, Yang; Villagarcia, Hector; Galanzha, Ekaterina I.; Zharov, Vladimir P.

2011-01-01

In vivo flow cytometry has facilitated advances in the ultrasensitive detection of tumor cells, bacteria, nanoparticles, dyes, and other normal and abnormal objects directly in blood and lymph circulatory systems. Here, we propose in vivo plant flow cytometry for the real-time noninvasive study of nanomaterial transport in xylem and phloem plant vascular systems. As a proof of this concept, we demonstrate in vivo real-time photoacoustic monitoring of quantum dot-carbon nanotube conjugate uptake and uptake by roots and spreading through stem to leaves in a tomato plant. In addition, in vivo scanning cytometry using multimodal photoacoustic, photothermal, and fluorescent detection schematics provided multiplex detection and identification of nanoparticles accumulated in plant leaves in the presence of intensive absorption, scattering, and autofluorescent backgrounds. The use of a portable fiber-based photoacoustic flow cytometer for studies of plant vasculature was demonstrated. These integrated cytometry modalities using both endogenous and exogenous contrast agents have a potential to open new avenues of in vivo study of the nutrients, products of photosynthesis and metabolism, nanoparticles, infectious agents, and other objects transported through plant vasculature. PMID:21905208

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors.

PubMed

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-05-28

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

Rapid toxicity detection in water quality control utilizing automated multispecies biomonitoring for permanent space stations

NASA Technical Reports Server (NTRS)

Morgan, E. L.; Young, R. C.; Smith, M. D.; Eagleson, K. W.

1986-01-01

The objective of this study was to evaluate proposed design characteristics and applications of automated biomonitoring devices for real-time toxicity detection in water quality control on-board permanent space stations. Simulated tests in downlinking transmissions of automated biomonitoring data to Earth-receiving stations were simulated using satellite data transmissions from remote Earth-based stations.

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.

Vision-based object detection and recognition system for intelligent vehicles

NASA Astrophysics Data System (ADS)

Ran, Bin; Liu, Henry X.; Martono, Wilfung

1999-01-01

Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

Demonstration of Uncued Optical Surveillance of LEO

NASA Astrophysics Data System (ADS)

Zimmer, P.; Ackermann, M.; McGraw, J.

2014-09-01

J.T. McGraw and Associates, LLC, in collaboration with the University of New Mexico (UNM), has built and is operating two proof-of-concept wide-field imaging systems to test novel techniques for uncued surveillance of LEO. The imaging systems are built from off-the-shelf optics and detectors resulting in a 350mm aperture and a 6 square degree field of view. For streak detection, field of view is of critical importance because the maximum exposure time on the object is limited by its crossing time and measurements of apparent angular motion are better constrained with longer streaks. The current match of the detector to the optical system is optimized for detection of objects at altitudes above 450km, which for a circular orbit, corresponds to apparent motions of approximately 1 deg./sec. Using our GPU-accelerated detection scheme, the proof-of-concept systems have detected objects fainter than V=12.3, which approximately corresponds to a 24 cm object at 1000 km altitude at better than 6 sigma significance, from sites near and within Albuquerque, NM. This work demonstrates scalable optical systems designed for near real time detection of fast moving objects, which can be then handed off to other instruments capable of tracking and characterizing them. The two proof-of-concept systems, separated by ~30km, work together by taking simultaneous images of the same orbital volume to constrain the orbits of detected objects using parallax measurements. These detections are followed-up by photometric observations taken at UNM to independently assess the objects and the quality of the derived orbits. We believe this demonstrates the potential of small telescope arrays for detecting and cataloguing heretofore unknown LEO objects.

Real time automated inspection

DOEpatents

Fant, Karl M.; Fundakowski, Richard A.; Levitt, Tod S.; Overland, John E.; Suresh, Bindinganavle R.; Ulrich, Franz W.

1985-01-01

A method and apparatus relating to the real time automatic detection and classification of characteristic type surface imperfections occurring on the surfaces of material of interest such as moving hot metal slabs produced by a continuous steel caster. A data camera transversely scans continuous lines of such a surface to sense light intensities of scanned pixels and generates corresponding voltage values. The voltage values are converted to corresponding digital values to form a digital image of the surface which is subsequently processed to form an edge-enhanced image having scan lines characterized by intervals corresponding to the edges of the image. The edge-enhanced image is thresholded to segment out the edges and objects formed by the edges are segmented out by interval matching and bin tracking. Features of the objects are derived and such features are utilized to classify the objects into characteristic type surface imperfections.

Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques.

PubMed

Ferreira, F J O; Crispim, V R; Silva, A X

2010-06-01

In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials. Copyright 2010 Elsevier Ltd. All rights reserved.

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

PubMed

Ren, Shaoqing; He, Kaiming; Girshick, Ross; Sun, Jian

2017-06-01

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, exposing region proposal computation as a bottleneck. In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. An RPN is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection. We further merge RPN and Fast R-CNN into a single network by sharing their convolutional features-using the recently popular terminology of neural networks with 'attention' mechanisms, the RPN component tells the unified network where to look. For the very deep VGG-16 model [3] , our detection system has a frame rate of 5 fps (including all steps) on a GPU, while achieving state-of-the-art object detection accuracy on PASCAL VOC 2007, 2012, and MS COCO datasets with only 300 proposals per image. In ILSVRC and COCO 2015 competitions, Faster R-CNN and RPN are the foundations of the 1st-place winning entries in several tracks. Code has been made publicly available.

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

Preprocessing of A-scan GPR data based on energy features

NASA Astrophysics Data System (ADS)

Dogan, Mesut; Turhan-Sayan, Gonul

2016-05-01

There is an increasing demand for noninvasive real-time detection and classification of buried objects in various civil and military applications. The problem of detection and annihilation of landmines is particularly important due to strong safety concerns. The requirement for a fast real-time decision process is as important as the requirements for high detection rates and low false alarm rates. In this paper, we introduce and demonstrate a computationally simple, timeefficient, energy-based preprocessing approach that can be used in ground penetrating radar (GPR) applications to eliminate reflections from the air-ground boundary and to locate the buried objects, simultaneously, at one easy step. The instantaneous power signals, the total energy values and the cumulative energy curves are extracted from the A-scan GPR data. The cumulative energy curves, in particular, are shown to be useful to detect the presence and location of buried objects in a fast and simple way while preserving the spectral content of the original A-scan data for further steps of physics-based target classification. The proposed method is demonstrated using the GPR data collected at the facilities of IPA Defense, Ankara at outdoor test lanes. Cylindrically shaped plastic containers were buried in fine-medium sand to simulate buried landmines. These plastic containers were half-filled by ammonium nitrate including metal pins. Results of this pilot study are demonstrated to be highly promising to motivate further research for the use of energy-based preprocessing features in landmine detection problem.

Building a robust vehicle detection and classification module

NASA Astrophysics Data System (ADS)

Grigoryev, Anton; Khanipov, Timur; Koptelov, Ivan; Bocharov, Dmitry; Postnikov, Vassily; Nikolaev, Dmitry

2015-12-01

The growing adoption of intelligent transportation systems (ITS) and autonomous driving requires robust real-time solutions for various event and object detection problems. Most of real-world systems still cannot rely on computer vision algorithms and employ a wide range of costly additional hardware like LIDARs. In this paper we explore engineering challenges encountered in building a highly robust visual vehicle detection and classification module that works under broad range of environmental and road conditions. The resulting technology is competitive to traditional non-visual means of traffic monitoring. The main focus of the paper is on software and hardware architecture, algorithm selection and domain-specific heuristics that help the computer vision system avoid implausible answers.

Parallel Flux Tensor Analysis for Efficient Moving Object Detection

DTIC Science & Technology

2011-07-01

computing as well as parallelization to enable real time performance in analyzing complex video [3, 4 ]. There are a number of challenging computer vision... 4 . TITLE AND SUBTITLE Parallel Flux Tensor Analysis for Efficient Moving Object Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...We use the trace of the flux tensor matrix, referred to as Tr JF , that is defined below, Tr JF = ∫ Ω W (x− y)(I2xt(y) + I2yt(y) + I2tt(y))dy ( 4 ) as

X-Ray Backscatter Imaging for Aerospace Applications

NASA Astrophysics Data System (ADS)

Shedlock, Daniel; Edwards, Talion; Toh, Chin

2011-06-01

Scatter x-ray imaging (SXI) is a real time, digital, x-ray backscatter imaging technique that allows radiographs to be taken from one side of an object. This x-ray backscatter imaging technique offers many advantages over conventional transmission radiography that include single-sided access and extremely low radiation fields compared to conventional open source industrial radiography. Examples of some applications include the detection of corrosion, foreign object debris, water intrusion, cracking, impact damage and leak detection in a variety of material such as aluminum, composites, honeycomb structures, and titanium.

Whisker Contact Detection of Rodents Based on Slow and Fast Mechanical Inputs

PubMed Central

Claverie, Laure N.; Boubenec, Yves; Debrégeas, Georges; Prevost, Alexis M.; Wandersman, Elie

2017-01-01

Rodents use their whiskers to locate nearby objects with an extreme precision. To perform such tasks, they need to detect whisker/object contacts with a high temporal accuracy. This contact detection is conveyed by classes of mechanoreceptors whose neural activity is sensitive to either slow or fast time varying mechanical stresses acting at the base of the whiskers. We developed a biomimetic approach to separate and characterize slow quasi-static and fast vibrational stress signals acting on a whisker base in realistic exploratory phases, using experiments on both real and artificial whiskers. Both slow and fast mechanical inputs are successfully captured using a mechanical model of the whisker. We present and discuss consequences of the whisking process in purely mechanical terms and hypothesize that free whisking in air sets a mechanical threshold for contact detection. The time resolution and robustness of the contact detection strategies based on either slow or fast stress signals are determined. Contact detection based on the vibrational signal is faster and more robust to exploratory conditions than the slow quasi-static component, although both slow/fast components allow localizing the object. PMID:28119582

The Real Time Display Builder (RTDB)

NASA Technical Reports Server (NTRS)

Kindred, Erick D.; Bailey, Samuel A., Jr.

1989-01-01

The Real Time Display Builder (RTDB) is a prototype interactive graphics tool that builds logic-driven displays. These displays reflect current system status, implement fault detection algorithms in real time, and incorporate the operational knowledge of experienced flight controllers. RTDB utilizes an object-oriented approach that integrates the display symbols with the underlying operational logic. This approach allows the user to specify the screen layout and the driving logic as the display is being built. RTDB is being developed under UNIX in C utilizing the MASSCOMP graphics environment with appropriate functional separation to ease portability to other graphics environments. RTDB grew from the need to develop customized real-time data-driven Space Shuttle systems displays. One display, using initial functionality of the tool, was operational during the orbit phase of STS-26 Discovery. RTDB is being used to produce subsequent displays for the Real Time Data System project currently under development within the Mission Operations Directorate at NASA/JSC. The features of the tool, its current state of development, and its applications are discussed.

Moving object detection and tracking in videos through turbulent medium

NASA Astrophysics Data System (ADS)

Halder, Kalyan Kumar; Tahtali, Murat; Anavatti, Sreenatha G.

2016-06-01

This paper addresses the problem of identifying and tracking moving objects in a video sequence having a time-varying background. This is a fundamental task in many computer vision applications, though a very challenging one because of turbulence that causes blurring and spatiotemporal movements of the background images. Our proposed approach involves two major steps. First, a moving object detection algorithm that deals with the detection of real motions by separating the turbulence-induced motions using a two-level thresholding technique is used. In the second step, a feature-based generalized regression neural network is applied to track the detected objects throughout the frames in the video sequence. The proposed approach uses the centroid and area features of the moving objects and creates the reference regions instantly by selecting the objects within a circle. Simulation experiments are carried out on several turbulence-degraded video sequences and comparisons with an earlier method confirms that the proposed approach provides a more effective tracking of the targets.

Discriminability and dimensionality effects in visual search for featural conjunctions: a functional pop-out.

PubMed

Dehaene, S

1989-07-01

Treisman and Gelade's (1980) feature-integration theory of attention states that a scene must be serially scanned before the objects in it can be accurately perceived. Is serial scanning compatible with the speed observed in the perception of real-world scenes? Most real scenes consist of many more dimensions (color, size, shape, depth, etc.) than those generally found in search paradigms. Furthermore, real objects differ from each other along many of these dimensions. The present experiment assessed the influence of the total number of dimensions and target/distractor discriminability (the number of dimensions that suffice to separate a target from distractors) on search times for a conjunction of features. Search was always found to be serial. However, for the most discriminable targets, search rate was so fast that search times were in the same range as pop-out detection times. Apparently, greater discriminability enables subjects to direct attention at a faster rate and at only a fraction of the items in a scene.

Hyperspectral discrimination of camouflaged target

NASA Astrophysics Data System (ADS)

Bárta, Vojtěch; Racek, František

2017-10-01

The article deals with detection of camouflaged objects during winter season. Winter camouflage is a marginal affair in most countries due to short time period of the snow cover. In the geographical condition of Central Europe the winter period with snow occurs less than 1/12 of year. The LWIR or SWIR spectral areas are used for detection of camouflaged objects. For those spectral regions the difference in chemical composition and temperature express in spectral features. Exploitation of the LWIR and SWIR devices is demanding due to their large dimension and expensiveness. Therefore, the article deals with estimation of utilization of VIS region for detecting of camouflaged object on snow background. The multispectral image output for the various spectral filters is simulated. Hyperspectral indices are determined to detect the camouflaged objects in the winter. The multispectral image simulation is based on the hyperspectral datacube obtained in real conditions.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Wireless sensor networks for heritage object deformation detection and tracking algorithm.

PubMed

Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

2014-10-31

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

PubMed Central

Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

2014-01-01

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection. PMID:25365458

Development of a fluorescent quantitative real-time polymerase chain reaction assay for the detection of Goose parvovirus in vivo

PubMed Central

Yang, Jin-Long; Cheng, An-Chun; Wang, Ming-Shu; Pan, Kang-Cheng; Li, Min; Guo, Yu-Fei; Li, Chuan-Feng; Zhu, De-Kang; Chen, Xiao-Yue

2009-01-01

Background Goose parvovirus (GPV) is a Dependovirus associated with latent infection and mortality in geese. Currently, it severely affects geese production worldwide. The objective of this study was to develop a fluorescent quantitative real-time polymerase chain reaction (PCR) (FQ-PCR) assay for fast and accurate quantification of GPV DNA in infected goslings, which can aid in the understanding of the regular distribution pattern and the nosogenesis of GPV in vivo. Results The detection limit of the assay was 2.8 × 101 standard DNA copies, with a sensitivity of 3 logs higher than that of the conventional gel-based PCR assay targeting the same gene. The real-time PCR was reproducible, as shown by satisfactory low intraassay and interassay coefficients of variation. Conclusion The high sensitivity, specificity, simplicity, and reproducibility of the GPV fluorogenic PCR assay, combined with a high throughput, make this method suitable for a broad spectrum of GPV etiology-related applications. PMID:19754946

Real-time determination of the efficacy of residual disinfection to limit wastewater contamination in a water distribution system using filtration-based luminescence.

PubMed

Lee, Jiyoung; Deininger, Rolf A

2010-05-01

Water distribution systems can be vulnerable to microbial contamination through cross-connections, wastewater backflow, the intrusion of soiled water after a loss of pressure resulting from an electricity blackout, natural disaster, or intentional contamination of the system in a bioterrrorism event. The most urgent matter a water treatment utility would face in this situation is detecting the presence and extent of a contamination event in real-time, so that immediate action can be taken to mitigate the problem. The current approved microbiological detection methods are culture-based plate count methods, which require incubation time (1 to 7 days). This long period of time would not be useful for the protection of public health. This study was designed to simulate wastewater intrusion in a water distribution system. The objectives were 2-fold: (1) real-time detection of water contamination, and (2) investigation of the sustainability of drinking water systems to suppress the contamination with secondary disinfectant residuals (chlorine and chloramine). The events of drinking water contamination resulting from a wastewater addition were determined by filtration-based luminescence assay. The water contamination was detected by luminescence method within 5 minutes. The signal amplification attributed to wastewater contamination was clear-102-fold signal increase. After 1 hour, chlorinated water could inactivate 98.8% of the bacterial contaminant, while chloraminated water reduced 77.2%.

Evaluation of fatty liver fibrosis in rabbits using real-time shear wave elastography

PubMed Central

LU, YONGPING; WEI, JIA; TANG, YUEYUE; YUAN, YUAN; HUANG, YANLING; ZHANG, YONG; LI, YUNYAN

2014-01-01

The aim of the present study was to detect the elastic modulus (stiffness) of the livers of rabbits with non-alcoholic and alcoholic fatty liver disease using real-time shear wave elastography (SWE), and to investigate the fibrosis development process in the formation of fatty liver. The stiffness of the fatty livers in rabbit models prepared via feeding with alcohol or a high-fat diet were measured using a real-time SWE ultrasound system and a 4–15-MHz linear array probe, and the liver stiffness was compared with the pathological staging of the disease. The stiffness of the liver was positively correlated with the degree of pathological change in fatty liver disease (P<0.01). The stiffness of the liver in the alcoholic fatty liver group was higher compared with that in the non-alcoholic fatty liver and control groups, and the stiffness in the non-alcoholic fatty liver group was higher than that in the control group (P<0.01). Real-time SWE objectively identified the trend in the changing stiffness of the liver and noninvasively detected the development of fibrosis in the progression of non-alcoholic and alcoholic fatty liver disease. PMID:25009583

Infrared dim target detection based on visual attention

NASA Astrophysics Data System (ADS)

Wang, Xin; Lv, Guofang; Xu, Lizhong

2012-11-01

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

Realtime automatic metal extraction of medical x-ray images for contrast improvement

NASA Astrophysics Data System (ADS)

Prangl, Martin; Hellwagner, Hermann; Spielvogel, Christian; Bischof, Horst; Szkaliczki, Tibor

2006-03-01

This paper focuses on an approach for real-time metal extraction of x-ray images taken from modern x-ray machines like C-arms. Such machines are used for vessel diagnostics, surgical interventions, as well as cardiology, neurology and orthopedic examinations. They are very fast in taking images from different angles. For this reason, manual adjustment of contrast is infeasible and automatic adjustment algorithms have been applied to try to select the optimal radiation dose for contrast adjustment. Problems occur when metallic objects, e.g., a prosthesis or a screw, are in the absorption area of interest. In this case, the automatic adjustment mostly fails because the dark, metallic objects lead the algorithm to overdose the x-ray tube. This outshining effect results in overexposed images and bad contrast. To overcome this limitation, metallic objects have to be detected and extracted from images that are taken as input for the adjustment algorithm. In this paper, we present a real-time solution for extracting metallic objects of x-ray images. We will explore the characteristic features of metallic objects in x-ray images and their distinction from bone fragments which form the basis to find a successful way for object segmentation and classification. Subsequently, we will present our edge based real-time approach for successful and fast automatic segmentation and classification of metallic objects. Finally, experimental results on the effectiveness and performance of our approach based on a vast amount of input image data sets will be presented.

Objects Architecture: A Comprehensive Design Approach for Real-Time, Distributed, Fault-Tolerant, Reactive Operating Systems.

DTIC Science & Technology

1987-09-01

real - time operating system should be efficient from the real-time point...5,8]) system naming scheme. 3.2 Protecting Objects Real-time embedded systems usually neglect protection mechanisms. However, a real - time operating system cannot...allocation mechanism should adhere to application constraints. This strong relationship between a real - time operating system and the application

Real-time detecting and tracking ball with OpenCV and Kinect

NASA Astrophysics Data System (ADS)

Osiecki, Tomasz; Jankowski, Stanislaw

2016-09-01

This paper presents a way to detect and track ball with using the OpenCV and Kinect. Object and people recognition, tracking are more and more popular topics nowadays. Described solution makes it possible to detect ball based on the range, which is set by the user and capture information about ball position in three dimensions. It can be store in the computer and use for example to display trajectory of the ball.

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Comparison of Fault Detection Algorithms for Real-time Diagnosis in Large-Scale System. Appendix E

NASA Technical Reports Server (NTRS)

Kirubarajan, Thiagalingam; Malepati, Venkat; Deb, Somnath; Ying, Jie

2001-01-01

In this paper, we present a review of different real-time capable algorithms to detect and isolate component failures in large-scale systems in the presence of inaccurate test results. A sequence of imperfect test results (as a row vector of I's and O's) are available to the algorithms. In this case, the problem is to recover the uncorrupted test result vector and match it to one of the rows in the test dictionary, which in turn will isolate the faults. In order to recover the uncorrupted test result vector, one needs the accuracy of each test. That is, its detection and false alarm probabilities are required. In this problem, their true values are not known and, therefore, have to be estimated online. Other major aspects in this problem are the large-scale nature and the real-time capability requirement. Test dictionaries of sizes up to 1000 x 1000 are to be handled. That is, results from 1000 tests measuring the state of 1000 components are available. However, at any time, only 10-20% of the test results are available. Then, the objective becomes the real-time fault diagnosis using incomplete and inaccurate test results with online estimation of test accuracies. It should also be noted that the test accuracies can vary with time --- one needs a mechanism to update them after processing each test result vector. Using Qualtech's TEAMS-RT (system simulation and real-time diagnosis tool), we test the performances of 1) TEAMSAT's built-in diagnosis algorithm, 2) Hamming distance based diagnosis, 3) Maximum Likelihood based diagnosis, and 4) HidderMarkov Model based diagnosis.

Compact Laser Multi-gas Spectral Sensors for Spacecraft Systems

NASA Technical Reports Server (NTRS)

Tittel, Frank K.

1997-01-01

The objective of this research effort has been the development of a new gas sensor technology to meet NASA requirements for spacecraft and space station human life support systems for sensitive selective and real time detection of trace gas species in the mid-infrared spectral region.

The detection of T-Nos, a genetic element present in GMOs, by cross-priming isothermal amplification with real-time fluorescence.

PubMed

Zhang, Fang; Wang, Liu; Fan, Kai; Wu, Jian; Ying, Yibin

2014-05-01

An isothermal cross-priming amplification (CPA) assay for Agrobacterium tumefaciens nopaline synthase terminator (T-Nos) was established and investigated in this work. A set of six specific primers, recognizing eight distinct regions on the T-Nos sequence, was designed. The CPA assay was performed at a constant temperature, 63 °C, and detected by real-time fluorescence. The results indicated that real-time fluorescent CPA had high specificity, and the limit of detection was 1.06 × 10(3) copies of rice genomic DNA, which could be detected in 40 min. Comparison of real-time fluorescent CPA and conventional polymerase chain reaction (PCR) was also performed. Results revealed that real-time fluorescent CPA had a comparable sensitivity to conventional real-time PCR and had taken a shorter time. In addition, different contents of genetically modified (GM)-contaminated rice seed powder samples were detected for practical application. The result showed real-time fluorescent CPA could detect 0.5 % GM-contaminated samples at least, and the whole reaction could be finished in 35 min. Real-time fluorescent CPA is sensitive enough to monitor labeling systems and provides an attractive method for the detection of GMO.

Real time automated inspection

DOEpatents

Fant, K.M.; Fundakowski, R.A.; Levitt, T.S.; Overland, J.E.; Suresh, B.R.; Ulrich, F.W.

1985-05-21

A method and apparatus are described relating to the real time automatic detection and classification of characteristic type surface imperfections occurring on the surfaces of material of interest such as moving hot metal slabs produced by a continuous steel caster. A data camera transversely scans continuous lines of such a surface to sense light intensities of scanned pixels and generates corresponding voltage values. The voltage values are converted to corresponding digital values to form a digital image of the surface which is subsequently processed to form an edge-enhanced image having scan lines characterized by intervals corresponding to the edges of the image. The edge-enhanced image is thresholded to segment out the edges and objects formed by the edges by interval matching and bin tracking. Features of the objects are derived and such features are utilized to classify the objects into characteristic type surface imperfections. 43 figs.

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

PubMed Central

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

2015-01-01

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

Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels

PubMed Central

Cheng, Karen Elizabeth; Crary, David J; Ray, Jaideep; Safta, Cosmin

2013-01-01

Objective We discuss the use of structural models for the analysis of biosurveillance related data. Methods and results Using a combination of real and simulated data, we have constructed a data set that represents a plausible time series resulting from surveillance of a large scale bioterrorist anthrax attack in Miami. We discuss the performance of anomaly detection with structural models for these data using receiver operating characteristic (ROC) and activity monitoring operating characteristic (AMOC) analysis. In addition, we show that these techniques provide a method for predicting the level of the outbreak valid for approximately 2 weeks, post-alarm. Conclusions Structural models provide an effective tool for the analysis of biosurveillance data, in particular for time series with noisy, non-stationary background and missing data. PMID:23037798

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.

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.

Detection of nicotine as an indicator of tobacco smoke by direct analysis in real time (DART) tandem mass spectrometry

NASA Astrophysics Data System (ADS)

Kuki, Ákos; Nagy, Lajos; Nagy, Tibor; Zsuga, Miklós; Kéki, Sándor

2015-01-01

The residual tobacco smoke contamination (thirdhand smoke, THS) on the clothes of a smoker was examined by direct analysis in real time (DART) mass spectrometry. DART-MS enabled sensitive and selective analysis of nicotine as the indicator of tobacco smoke pollution. Tandem mass spectrometric (MS/MS) experiments were also performed to confirm the identification of nicotine. Transferred thirdhand smoke originated from the fingers of a smoker onto other objects was also detected by DART mass spectrometry. DART-MS/MS was utilized for monitoring the secondhand tobacco smoke (SHS) in the air of the laboratory using nicotine as an indicator. To the best of our knowledge, this is the first report on the application of DART-MS and DART-MS/MS to the detection of thirdhand smoke and to the monitoring of secondhand smoke.

On resilience studies of system detection and recovery techniques against stealthy insider attacks

NASA Astrophysics Data System (ADS)

Wei, Sixiao; Zhang, Hanlin; Chen, Genshe; Shen, Dan; Yu, Wei; Pham, Khanh D.; Blasch, Erik P.; Cruz, Jose B.

2016-05-01

With the explosive growth of network technologies, insider attacks have become a major concern to business operations that largely rely on computer networks. To better detect insider attacks that marginally manipulate network traffic over time, and to recover the system from attacks, in this paper we implement a temporal-based detection scheme using the sequential hypothesis testing technique. Two hypothetical states are considered: the null hypothesis that the collected information is from benign historical traffic and the alternative hypothesis that the network is under attack. The objective of such a detection scheme is to recognize the change within the shortest time by comparing the two defined hypotheses. In addition, once the attack is detected, a server migration-based system recovery scheme can be triggered to recover the system to the state prior to the attack. To understand mitigation of insider attacks, a multi-functional web display of the detection analysis was developed for real-time analytic. Experiments using real-world traffic traces evaluate the effectiveness of Detection System and Recovery (DeSyAR) scheme. The evaluation data validates the detection scheme based on sequential hypothesis testing and the server migration-based system recovery scheme can perform well in effectively detecting insider attacks and recovering the system under attack.

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

NASA Astrophysics Data System (ADS)

Ali, Mohammed Hussain

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

Accelerating object detection via a visual-feature-directed search cascade: algorithm and field programmable gate array implementation

NASA Astrophysics Data System (ADS)

Kyrkou, Christos; Theocharides, Theocharis

2016-07-01

Object detection is a major step in several computer vision applications and a requirement for most smart camera systems. Recent advances in hardware acceleration for real-time object detection feature extensive use of reconfigurable hardware [field programmable gate arrays (FPGAs)], and relevant research has produced quite fascinating results, in both the accuracy of the detection algorithms as well as the performance in terms of frames per second (fps) for use in embedded smart camera systems. Detecting objects in images, however, is a daunting task and often involves hardware-inefficient steps, both in terms of the datapath design and in terms of input/output and memory access patterns. We present how a visual-feature-directed search cascade composed of motion detection, depth computation, and edge detection, can have a significant impact in reducing the data that needs to be examined by the classification engine for the presence of an object of interest. Experimental results on a Spartan 6 FPGA platform for face detection indicate data search reduction of up to 95%, which results in the system being able to process up to 50 1024×768 pixels images per second with a significantly reduced number of false positives.

Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

PubMed Central

Tian, Yuan; Guan, Tao; Wang, Cheng

2010-01-01

To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method. PMID:22319278

Detection of Mycobacterium tuberculosis resistance mutations to rifampin and isoniazid by real-time PCR.

PubMed

Hristea, A; Otelea, D; Paraschiv, S; Macri, A; Baicus, C; Moldovan, O; Tinischi, M; Arama, V; Streinu-Cercel, A

2010-01-01

The objective of our study was to evaluate the use of a real-time polymerase chain reaction (PCR)-based technique for the prediction of phenotypic resistance of Mycobacterium tuberculosis. We tested 67 M tuberculosis strains (26 drug resistant and 41 drug susceptible) using a method recommended for the LightCycler platform. The susceptibility testing was performed by the absolute concentration method. For rifampin resistance, two regions of the rpoB gene were targeted, while for identification of isoniazid resistance, we searched for mutations in katG and inhA genes. The sensitivity and specificity of this method for rapid detection of mutations for isoniazid resistance were 96% (95% CI: 88% to 100%) and 95% (95% CI: 89% to 100%), respectively. For detection of rifampin resistance, the sensitivity and specificity were 92% (95% CI: 81% to 100%) and 74% (95% CI: 61% to 87%), respectively. The main isoniazid resistance mechanism identified in our isolates is related to changes in the katG gene that encodes catalase. We found that for rifampin resistance the concordance between the predicted and observed phenotype was less than satisfactory. Using this method, the best accuracy for genotyping compared with phenotypic resistance testing was obtained for detecting isoniazid resistance mutations. Although real-time PCR assay may be a valuable diagnostic tool, it is not yet completely satisfactory for detection of drug resistance mutations in M tuberculosis.

Oxygen flux as an indicator of physiological stress in fathead minnow (Pimephales promelas) embryos: a real-time biomonitoring system of water quality.

PubMed

Sanchez, Brian C; Ochoa-Acuña, Hugo; Porterfield, D Marshall; Sepúlveda, María S

2008-09-15

The detection of harmful chemicals and biological agents in real time is a critical need for protecting freshwater ecosystems. We studied the real-time effects of five environmental contaminants with differing modes of action (atrazine, cadmium chloride, pentachlorophenol, malathion, and potassium cyanide) on respiratory oxygen consumption in 2-day postfertilization fathead minnow (Pimephales promelas) eggs. Our objective was to assess the sensitivity of fathead minnow eggs using the self-referencing micro-optrode technique to detect instantaneous changes in oxygen consumption after brief exposures to low concentrations of contaminants. Oxygen consumption data indicated that the technique is indeed sensitive enough to reliably detect physiological alterations induced by four of the five contaminants. After 2 h of exposure, we identified significant increases in oxygen consumption upon exposure to pentachlorophenol (100 and 1000 microg/L), cadmium chloride (0.0002 and 0.002 microg/L), and atrazine (150 microg/L). In contrast, we observed a significant decrease in oxygen flux after exposuresto potassium cyanide (44 and 66 microg/L) and atrazine (1500 microg/L). No effects were detected after exposures to malathion (200 and 340 microg/L). Our work is the first step in development of a new technique for physiologically coupled biomonitoring as a sensitive and reliable tool for the detection of environmental toxicants.

Improved segmentation of occluded and adjoining vehicles in traffic surveillance videos

NASA Astrophysics Data System (ADS)

Juneja, Medha; Grover, Priyanka

2013-12-01

Occlusion in image processing refers to concealment of any part of the object or the whole object from view of an observer. Real time videos captured by static cameras on roads often encounter overlapping and hence, occlusion of vehicles. Occlusion in traffic surveillance videos usually occurs when an object which is being tracked is hidden by another object. This makes it difficult for the object detection algorithms to distinguish all the vehicles efficiently. Also morphological operations tend to join the close proximity vehicles resulting in formation of a single bounding box around more than one vehicle. Such problems lead to errors in further video processing, like counting of vehicles in a video. The proposed system brings forward efficient moving object detection and tracking approach to reduce such errors. The paper uses successive frame subtraction technique for detection of moving objects. Further, this paper implements the watershed algorithm to segment the overlapped and adjoining vehicles. The segmentation results have been improved by the use of noise and morphological operations.

Integrated active sensor system for real time vibration monitoring.

PubMed

Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

2015-11-05

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0-60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.

Integrated active sensor system for real time vibration monitoring

PubMed Central

Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

2015-01-01

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0–60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems. PMID:26538293

Track Detection in Railway Sidings Based on MEMS Gyroscope Sensors

PubMed Central

Broquetas, Antoni; Comerón, Adolf; Gelonch, Antoni; Fuertes, Josep M.; Castro, J. Antonio; Felip, Damià; López, Miguel A.; Pulido, José A.

2012-01-01

The paper presents a two-step technique for real-time track detection in single-track railway sidings using low-cost MEMS gyroscopes. The objective is to reliably know the path the train has taken in a switch, diverted or main road, immediately after the train head leaves the switch. The signal delivered by the gyroscope is first processed by an adaptive low-pass filter that rejects noise and converts the temporal turn rate data in degree/second units into spatial turn rate data in degree/meter. The conversion is based on the travelled distance taken from odometer data. The filter is implemented to achieve a speed-dependent cut-off frequency to maximize the signal-to-noise ratio. Although direct comparison of the filtered turn rate signal with a predetermined threshold is possible, the paper shows that better detection performance can be achieved by processing the turn rate signal with a filter matched to the rail switch curvature parameters. Implementation aspects of the track detector have been optimized for real-time operation. The detector has been tested with both simulated data and real data acquired in railway campaigns. PMID:23443376

A Star Image Extractor for the Nano-JASMINE satellite

NASA Astrophysics Data System (ADS)

Yamauchi, M.; Gouda, N.; Kobayashi, Y.; Tsujimoto, T.; Yano, T.; Suganuma, M.; Yamada, Y.; Nakasuka, S.; Sako, N.

2008-07-01

We have developped a software of Star-Image-Extractor (SIE) which works as the on-board real-time image processor. It detects and extracts only the object data from raw image data. SIE has two functions: reducing image data and providing data for the satellite's high accuracy attitude control system.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors

PubMed Central

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-01-01

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms. PMID:27240382

Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

PubMed

Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

2016-09-01

We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

Loop-Mediated Isothermal Amplification for Detection of Endogenous Sad1 Gene in Cotton: An Internal Control for Rapid Onsite GMO Testing.

PubMed

Singh, Monika; Bhoge, Rajesh K; Randhawa, Gurinderjit

2018-04-20

Background : Confirming the integrity of seed samples in powdered form is important priorto conducting a genetically modified organism (GMO) test. Rapid onsite methods may provide a technological solution to check for genetically modified (GM) events at ports of entry. In India, Bt cotton is the commercialized GM crop with four approved GM events; however, 59 GM events have been approved globally. GMO screening is required to test for authorized GM events. The identity and amplifiability of test samples could be ensured first by employing endogenous genes as an internal control. Objective : A rapid onsite detection method was developed for an endogenous reference gene, stearoyl acyl carrier protein desaturase ( Sad1 ) of cotton, employing visual and real-time loop-mediated isothermal amplification (LAMP). Methods : The assays were performed at a constant temperature of 63°C for 30 min for visual LAMP and 62ºC for 40 min for real-time LAMP. Positive amplification was visualized as a change in color from orange to green on addition of SYBR ® Green or detected as real-time amplification curves. Results : Specificity of LAMP assays was confirmed using a set of 10 samples. LOD for visual LAMP was up to 0.1%, detecting 40 target copies, and for real-time LAMP up to 0.05%, detecting 20 target copies. Conclusions : The developed methods could be utilized to confirm the integrity of seed powder prior to conducting a GMO test for specific GM events of cotton. Highlights : LAMP assays for the endogenous Sad1 gene of cotton have been developed to be used as an internal control for onsite GMO testing in cotton.

Detection of distribution of avian influenza H5N1 virus by immunohistochemistry, chromogenic in situ hybridization and real-time PCR techniques in experimentally infected chickens.

PubMed

Chamnanpood, Chanpen; Sanguansermsri, Donruedee; Pongcharoen, Sutatip; Sanguansermsri, Phanchana

2011-03-01

Ten specific pathogen free (SPF) chickens were inoculated intranasally with avian influenza virus subtype H5N1. Evaluation revealed distribution of the virus in twelve organs: liver, intestine, bursa, lung, trachea, thymus, heart, pancreas, brain, spleen, kidney, and esophagus. Immunohistochemistry (IHC), chromogenic in situ hybridization (CISH), and real-time polymerase chain reaction (PCR) were developed and compared for detection of the virus from the organs. The distribution of avian influenza H5N1 in chickens varied by animal and detecting technique. The heart, kidneys, intestines, lungs, and pancreas were positive with all three techniques, while the others varied by techique. The three techniques can be used to detect avian influenza effectively, but the pros and cons of each technique need to be determined. The decision of which technique to use depends on the objective of the examination, budget, type and quality of samples, laboratory facilities and technician skills.

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study.

PubMed

Al-Naji, Ali; Gibson, Kim; Lee, Sang-Heon; Chahl, Javaan

2017-02-03

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications.

Advances in quantum cascade lasers for security and crime-fighting

NASA Astrophysics Data System (ADS)

Normand, Erwan L.; Stokes, Robert J.; Hay, Kenneth; Foulger, Brian; Lewis, Colin

2010-10-01

Advances in the application of Quantum Cascade Lasers (QCL) to trace gas detection will be presented. The solution is real time (~1 μsec per scan), is insensitive to turbulence and vibration, and performs multiple measurements in one sweep. The QCL provides a large dynamic range, which is a linear response from ppt to % level. The concentration can be derived with excellent immunity from cross interference. Point sensing sensors developed by Cascade for home made and commercial explosives operate by monitoring key constituents in real time and matching this to a spatial event (i.e. sniffer device placed close to an object or person walking through portal (overt or covert). Programmable signature detection capability allows for detection of multiple chemical compounds along the most likely array of explosive chemical formulation. The advantages of configuration as "point sensing" or "stand off" will be discussed. In addition to explosives this method is highly applicable to the detection of mobile drugs labs through volatile chemical release.

Real-Time Evaluation of Breast Self-Examination Using Computer Vision

PubMed Central

Mohammadi, Eman; Dadios, Elmer P.; Gan Lim, Laurence A.; Cabatuan, Melvin K.; Naguib, Raouf N. G.; Avila, Jose Maria C.; Oikonomou, Andreas

2014-01-01

Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most cost-effective approach for early breast cancer detection. The general objective of this paper is to design and develop a computer vision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and tracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and blocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region. The palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated, checked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to confirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown that the BSE evaluation algorithm presented in this paper provides robust performance. PMID:25435860

Real-time evaluation of breast self-examination using computer vision.

PubMed

Mohammadi, Eman; Dadios, Elmer P; Gan Lim, Laurence A; Cabatuan, Melvin K; Naguib, Raouf N G; Avila, Jose Maria C; Oikonomou, Andreas

2014-01-01

Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most cost-effective approach for early breast cancer detection. The general objective of this paper is to design and develop a computer vision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and tracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and blocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region. The palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated, checked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to confirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown that the BSE evaluation algorithm presented in this paper provides robust performance.

Development of a highly sensitive one-tube nested real-time PCR for detecting Mycobacterium tuberculosis.

PubMed

Choi, Yeonim; Jeon, Bo-Young; Shim, Tae Sun; Jin, Hyunwoo; Cho, Sang-Nae; Lee, Hyeyoung

2014-12-01

Rapid, accurate detection of Mycobacterium tuberculosis is crucial in the diagnosis of tuberculosis (TB), but conventional diagnostic methods have limited sensitivity and specificity or are time consuming. A new highly sensitive nucleic acid amplification test, combined nested and real-time polymerase chain reaction (PCR) in a single tube (one-tube nested real-time PCR), was developed for detecting M. tuberculosis, which takes advantage of two PCR techniques, i.e., nested PCR and real-time PCR. One-tube nested real-time PCR was designed to have two sequential reactions with two sets of primers and dual probes for the insertion sequence (IS) 6110 sequence of M. tuberculosis in a single closed tube. The minimum limits of detection of IS6110 real-time PCR and IS6110 one-tube nested real-time PCR were 100 fg/μL and 1 fg/μL of M. tuberculosis DNA, respectively. AdvanSure TB/non-tuberculous mycobacteria (NTM) real-time PCR, IS6110 real-time PCR, and two-tube nested real-time PCR showed 100% sensitivity and 100% specificity for clinical M. tuberculosis isolates and NTM isolates. In comparison, the sensitivities of AdvanSure TB/NTM real-time PCR, single IS6110 real-time PCR, and one-tube nested real-time PCR were 91% (152/167), 94.6% (158/167), and 100% (167/167) for sputum specimens, respectively. In conclusion, IS6110 one-tube nested real-time PCR is useful for detecting M. tuberculosis due to its high sensitivity and simple manipulation. Copyright © 2014 Elsevier Inc. All rights reserved.

Instrumental requirements for the detection of electron beam-induced object excitations at the single atom level in high-resolution transmission electron microscopy.

PubMed

Kisielowski, C; Specht, P; Gygax, S M; Barton, B; Calderon, H A; Kang, J H; Cieslinski, R

2015-01-01

This contribution touches on essential requirements for instrument stability and resolution that allows operating advanced electron microscopes at the edge to technological capabilities. They enable the detection of single atoms and their dynamic behavior on a length scale of picometers in real time. It is understood that the observed atom dynamic is intimately linked to the relaxation and thermalization of electron beam-induced sample excitation. Resulting contrast fluctuations are beam current dependent and largely contribute to a contrast mismatch between experiments and theory if not considered. If explored, they open the possibility to study functional behavior of nanocrystals and single molecules at the atomic level in real time. Copyright © 2014 Elsevier Ltd. All rights reserved.

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

Adaptation of red blood cell lysis represents a fundamental breakthrough that improves the sensitivity of Salmonella detection in blood

PubMed Central

Boyd, MA; Tennant, SM; Melendez, JH; Toema, D; Galen, JE; Geddes, CD; Levine, MM

2015-01-01

Aims Isolation of Salmonella Typhi from blood culture is the standard diagnostic for confirming typhoid fever but it is unavailable in many developing countries. We previously described a Microwave Accelerated Metal Enhanced Fluorescence (MAMEF)-based assay to detect Salmonella in medium. Attempts to detect Salmonella in blood were unsuccessful, presumably due to the interference of erythrocytes. The objective of this study was to evaluate various blood treatment methods that could be used prior to PCR, real-time PCR or MAMEF to increase sensitivity of detection of Salmonella. Methods and Results We tested ammonium chloride and erythrocyte lysis buffer, water, Lymphocyte Separation Medium, BD Vacutainer® CPT™ Tubes and dextran. Erythrocyte lysis buffer was the best isolation method as it is fast, inexpensive and works with either fresh or stored blood. The sensitivity of PCR- and real-time PCR detection of Salmonella in spiked blood was improved when whole blood was first lysed using erythrocyte lysis buffer prior to DNA extraction. Removal of erythrocytes and clotting factors also enabled reproducible lysis of Salmonella and fragmentation of DNA, which are necessary for MAMEF sensing. Conclusions Use of the erythrocyte lysis procedure prior to DNA extraction has enabled improved sensitivity of Salmonella detection by PCR and real-time PCR and has allowed lysis and fragmentation of Salmonella using microwave radiation (for future detection by MAMEF). Significance and Impact of the Study Adaptation of the blood lysis method represents a fundamental breakthrough that improves the sensitivity of DNA-based detection of Salmonella in blood. PMID:25630831

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

Comparison of Hybrid Capture 2 Assay with Real-time-PCR for Detection and Quantitation of Hepatitis B Virus DNA.

PubMed

Majid, Farjana; Jahan, Munira; Lutful Moben, Ahmed; Tabassum, Shahina

2014-01-01

Both real-time-polymerase chain reaction (PCR) and hybrid capture 2 (HC2) assay can detect and quantify hepatitis B virus (HBV) DNA. However, real-time-PCR can detect a wide range of HBV DNA, while HC2 assay could not detect lower levels of viremia. The present study was designed to detect and quantify HBV DNA by real-time-PCR and HC2 assay and compare the quantitative data of these two assays. A cross-sectional study was conducted in between July 2010 and June 2011. A total of 66 serologically diagnosed chronic hepatitis B (CHB) patients were selected for the study. Real-time-PCR and HC2 assay was done to detect HBV DNA. Data were analyzed by statistical Package for the social sciences (SPSS). Among 66 serologically diagnosed chronic hepatitis B patients 40 (60.61%) patients had detectable and 26 (39.39%) had undetectable HBV DNA by HC2 assay. Concordant results were obtained for 40 (60.61%) out of these 66 patients by real-time-PCR and HC2 assay with mean viral load of 7.06 ± 1.13 log 10 copies/ml and 6.95 ± 1.08 log 10 copies/ml, respectively. In the remaining 26 patients, HBV DNA was detectable by real-time-PCR in 20 patients (mean HBV DNA level was 3.67 ± 0.72 log 10 copies/ml. However, HBV DNA could not be detectable in six cases by the both assays. The study showed strong correlation (r = 0.915) between real-time-PCR and HC2 assay for the detection and quantification of HBV DNA. HC2 assay may be used as an alternative to real-time-PCR for CHB patients. How to cite this article: Majid F, Jahan M, Moben AL, Tabassum S. Comparison of Hybrid Capture 2 Assay with Real-time-PCR for Detection and Quantitation of Hepatitis B Virus DNA. Euroasian J Hepato-Gastroenterol 2014;4(1):31-35.

Real-time polymerase chain reaction assay for rapid and sensitive detection of anthrax spores in spiked soil and talcum powder.

PubMed

Jain, Neha; Merwyn, S; Rai, G P; Agarwal, G S

2012-05-01

Real-time polymerase chain reaction (real-time PCR) is a laboratory technique based on PCR. This technique is able to detect sequence-specific PCR products as they accumulate in "real time" during the PCR amplification, and also to quantify the number of substrates present in the initial PCR mixture before amplification begins. In the present study, real-time PCR assay was employed for rapid and real-time detection of Bacillus anthracis spores spiked in 0.1 g of soil and talcum powder ranging from 5 to 10(7) spores. DNA was isolated from spiked soil and talcum powder, using PBS containing 1 % Triton-X-100, followed by heat treatment. The isolated DNA was used as template for real-time PCR and PCR. Real-time PCR amplification was obtained in 60 min under the annealing condition at 60°C by employing primers targeting the pag gene of B. anthracis. In the present study, the detection limit of real-time PCR assay in soil was 10(3) spores and 10(2) spores in talcum powder, respectively, whereas PCR could detect 10(4) spores in soil and 10(3) spores in talcum powder, respectively.

Behavioral pattern identification for structural health monitoring in complex systems

NASA Astrophysics Data System (ADS)

Gupta, Shalabh

Estimation of structural damage and quantification of structural integrity are critical for safe and reliable operation of human-engineered complex systems, such as electromechanical, thermofluid, and petrochemical systems. Damage due to fatigue crack is one of the most commonly encountered sources of structural degradation in mechanical systems. Early detection of fatigue damage is essential because the resulting structural degradation could potentially cause catastrophic failures, leading to loss of expensive equipment and human life. Therefore, for reliable operation and enhanced availability, it is necessary to develop capabilities for prognosis and estimation of impending failures, such as the onset of wide-spread fatigue crack damage in mechanical structures. This dissertation presents information-based online sensing of fatigue damage using the analytical tools of symbolic time series analysis ( STSA). Anomaly detection using STSA is a pattern recognition method that has been recently developed based upon a fixed-structure, fixed-order Markov chain. The analysis procedure is built upon the principles of Symbolic Dynamics, Information Theory and Statistical Pattern Recognition. The dissertation demonstrates real-time fatigue damage monitoring based on time series data of ultrasonic signals. Statistical pattern changes are measured using STSA to monitor the evolution of fatigue damage. Real-time anomaly detection is presented as a solution to the forward (analysis) problem and the inverse (synthesis) problem. (1) the forward problem - The primary objective of the forward problem is identification of the statistical changes in the time series data of ultrasonic signals due to gradual evolution of fatigue damage. (2) the inverse problem - The objective of the inverse problem is to infer the anomalies from the observed time series data in real time based on the statistical information generated during the forward problem. A computer-controlled special-purpose fatigue test apparatus, equipped with multiple sensing devices (e.g., ultrasonics and optical microscope) for damage analysis, has been used to experimentally validate the STSA method for early detection of anomalous behavior. The sensor information is integrated with a software module consisting of the STSA algorithm for real-time monitoring of fatigue damage. Experiments have been conducted under different loading conditions on specimens constructed from the ductile aluminium alloy 7075 - T6. The dissertation has also investigated the application of the STSA method for early detection of anomalies in other engineering disciplines. Two primary applications include combustion instability in a generic thermal pulse combustor model and whirling phenomenon in a typical misaligned shaft.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

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

1999-08-01

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

Rapid detection of highly pathogenic porcine reproductive and respiratory syndrome virus by a fluorescent probe-based isothermal recombinase polymerase amplification assay.

PubMed

Yang, Yang; Qin, Xiaodong; Sun, Yingjun; Chen, Ting; Zhang, Zhidong

2016-12-01

A novel fluorescent probe-based real-time reverse transcription recombinase polymerase amplification (real-time RT-RPA) assay was developed for rapid detection of highly pathogenic type 2 porcine reproductive and respiratory syndrome virus (HP-PRRSV). The sensitivity analysis showed that the detection limit of RPA was 70 copies of HP-PRRSV RNA/reaction. The real-time RT-RPA highly specific amplified HP-PRRSV with no cross-reaction with classic PRRSV, classic swine fever virus, pseudorabies virus, and foot-and-mouth disease virus. Assessment with 125 clinical samples showed that the developed real-time RT-RPA assay was well correlated with real-time RT-qPCR assays for detection of HP-PRRSV. These results suggest that the developed real-time RT-RPA assay is suitable for rapid detection of HP-PRRSV.

Development of a surface plasmon resonance and nanomechanical biosensing hybrid platform for multiparametric reading

NASA Astrophysics Data System (ADS)

Alvarez, Mar; Fariña, David; Escuela, Alfonso M.; Sendra, Jose Ramón; Lechuga, Laura M.

2013-01-01

We have developed a hybrid platform that combines two well-known biosensing technologies based on quite different transducer principles: surface plasmon resonance and nanomechanical sensing. The new system allows the simultaneous and real-time detection of two independent parameters, refractive index change (Δn), and surface stress change (Δσ) when a biomolecular interaction takes place. Both parameters have a direct relation with the mass coverage of the sensor surface. The core of the platform is a common fluid cell, where the solution arrives to both sensor areas at the same time and under the same conditions (temperature, velocity, diffusion, etc.).The main objective of this integration is to achieve a better understanding of the physical behaviour of the transducers during sensing, increasing the information obtained in real time in one single experiment. The potential of the hybrid platform is demonstrated by the detection of DNA hybridization.

Development of a surface plasmon resonance and nanomechanical biosensing hybrid platform for multiparametric reading.

PubMed

Alvarez, Mar; Fariña, David; Escuela, Alfonso M; Sendra, Jose Ramón; Lechuga, Laura M

2013-01-01

We have developed a hybrid platform that combines two well-known biosensing technologies based on quite different transducer principles: surface plasmon resonance and nanomechanical sensing. The new system allows the simultaneous and real-time detection of two independent parameters, refractive index change (Δn), and surface stress change (Δσ) when a biomolecular interaction takes place. Both parameters have a direct relation with the mass coverage of the sensor surface. The core of the platform is a common fluid cell, where the solution arrives to both sensor areas at the same time and under the same conditions (temperature, velocity, diffusion, etc.).The main objective of this integration is to achieve a better understanding of the physical behaviour of the transducers during sensing, increasing the information obtained in real time in one single experiment. The potential of the hybrid platform is demonstrated by the detection of DNA hybridization.

A novel real-time health monitoring system for unmanned vehicles

NASA Astrophysics Data System (ADS)

Zhang, David C.; Ouyang, Lien; Qing, Peter; Li, Irene

2008-04-01

Real-time monitoring the status of in-service structures such as unmanned vehicles can provide invaluable information to detect the damages to the structures on time. The unmanned vehicles can be maintained and repaired in time if such damages are found. One typical cause of damages of unmanned vehicles is from impacts caused by bumping into some obstacles or being hit by some objects such as hostile fire. This paper introduces a novel impact event sensing system that can detect the location of the impact events and the force-time history of the impact events. The system consists of the Piezo-electric sensor network, the hardware platform and the analysis software. The new customized battery-powered impact event sensing system supports up to 64-channel parallel data acquisition. It features an innovative low-power hardware trigger circuit that monitors 64 channels simultaneously. The system is in the sleep mode most of the time. When an impact event happens, the system will wake up in micro-seconds and detect the impact location and corresponding force-time history. The system can be combined with the SMART sensing system to further evaluate the impact damage severity.

Detection and tracking of drones using advanced acoustic cameras

NASA Astrophysics Data System (ADS)

Busset, Joël.; Perrodin, Florian; Wellig, Peter; Ott, Beat; Heutschi, Kurt; Rühl, Torben; Nussbaumer, Thomas

2015-10-01

Recent events of drones flying over city centers, official buildings and nuclear installations stressed the growing threat of uncontrolled drone proliferation and the lack of real countermeasure. Indeed, detecting and tracking them can be difficult with traditional techniques. A system to acoustically detect and track small moving objects, such as drones or ground robots, using acoustic cameras is presented. The described sensor, is completely passive, and composed of a 120-element microphone array and a video camera. The acoustic imaging algorithm determines in real-time the sound power level coming from all directions, using the phase of the sound signals. A tracking algorithm is then able to follow the sound sources. Additionally, a beamforming algorithm selectively extracts the sound coming from each tracked sound source. This extracted sound signal can be used to identify sound signatures and determine the type of object. The described techniques can detect and track any object that produces noise (engines, propellers, tires, etc). It is a good complementary approach to more traditional techniques such as (i) optical and infrared cameras, for which the object may only represent few pixels and may be hidden by the blooming of a bright background, and (ii) radar or other echo-localization techniques, suffering from the weakness of the echo signal coming back to the sensor. The distance of detection depends on the type (frequency range) and volume of the noise emitted by the object, and on the background noise of the environment. Detection range and resilience to background noise were tested in both, laboratory environments and outdoor conditions. It was determined that drones can be tracked up to 160 to 250 meters, depending on their type. Speech extraction was also experimentally investigated: the speech signal of a person being 80 to 100 meters away can be captured with acceptable speech intelligibility.

Optical sectioning in wide-field microscopy obtained by dynamic structured light illumination and detection based on a smart pixel detector array.

PubMed

Mitić, Jelena; Anhut, Tiemo; Meier, Matthias; Ducros, Mathieu; Serov, Alexander; Lasser, Theo

2003-05-01

Optical sectioning in wide-field microscopy is achieved by illumination of the object with a continuously moving single-spatial-frequency pattern and detecting the image with a smart pixel detector array. This detector performs an on-chip electronic signal processing that extracts the optically sectioned image. The optically sectioned image is directly observed in real time without any additional postprocessing.

Shell-vial culture, coupled with real-time PCR, applied to Rickettsia conorii and Rickettsia massiliae-Bar29 detection, improving the diagnosis of the Mediterranean spotted fever.

PubMed

Segura, Ferran; Pons, Immaculada; Sanfeliu, Isabel; Nogueras, María-Mercedes

2016-04-01

Rickettsia conorii and Rickettsia massiliae-Bar29 are related to Mediterranean spotted fever (MSF). They are intracellular microorganisms. The Shell-vial culture assay (SV) improved Rickettsia culture but it still has some limitations: blood usually contains low amount of microorganisms and the samples that contain the highest amount of them are non-sterile. The objectives of this study were to optimize SV culture conditions and monitoring methods and to establish antibiotic concentrations useful for non-sterile samples. 12 SVs were inoculated with each microorganism, incubated at different temperatures and monitored by classical methods and real-time PCR. R. conorii was detected by all methods at all temperatures since 7th day of incubation. R. massiliae-Bar29 was firstly observed at 28°C. Real-time PCR allowed to detected it 2-7 days earlier (depend on temperature) than classical methods. Antibiotics concentration needed for the isolation of these Rickettsia species from non-sterile samples was determined inoculating SV with R. conorii, R. massiliae-Bar29, biopsy or tick, incubating them with different dilutions of antibiotics and monitoring them weekly. To sum up, if a MSF diagnosis is suspected, SV should be incubated at both 28°C and 32°C for 1-3 weeks and monitored by a sensitive real-time PCR. If the sample is non-sterile the panel of antibiotics tested can be added. Copyright © 2016 Elsevier GmbH. All rights reserved.

Real-time PCR-based method for the rapid detection of extended RAS mutations using bridged nucleic acids in colorectal cancer.

PubMed

Iida, Takao; Mizuno, Yukie; Kaizaki, Yasuharu

2017-10-27

Mutations in RAS and BRAF are predictors of the efficacy of anti-epidermal growth factor receptor (EGFR) therapy in patients with metastatic colorectal cancer (mCRC). Therefore, simple, rapid, cost-effective methods to detect these mutations in the clinical setting are greatly needed. In the present study, we evaluated BNA Real-time PCR Mutation Detection Kit Extended RAS (BNA Real-time PCR), a real-time PCR method that uses bridged nucleic acid clamping technology to rapidly detect mutations in RAS exons 2-4 and BRAF exon 15. Genomic DNA was extracted from 54 formalin-fixed paraffin-embedded (FFPE) tissue samples obtained from mCRC patients. Among the 54 FFPE samples, BNA Real-time PCR detected 21 RAS mutations (38.9%) and 5 BRAF mutations (9.3%), and the reference assay (KRAS Mutation Detection Kit and MEBGEN™ RASKET KIT) detected 22 RAS mutations (40.7%). The concordance rate of detected RAS mutations between the BNA Real-time PCR assay and the reference assays was 98.2% (53/54). The BNA Real-time PCR assay proved to be a more simple, rapid, and cost-effective method for detecting KRAS and RAS mutations compared with existing assays. These findings suggest that BNA Real-time PCR is a valuable tool for predicting the efficacy of early anti-EGFR therapy in mCRC patients. Copyright © 2017 Elsevier B.V. All rights reserved.

SNP-based real-time pyrosequencing as a sensitive and specific tool for identification and differentiation of Rickettsia species in Ixodes ricinus ticks.

PubMed

Janecek, Elisabeth; Streichan, Sabine; Strube, Christina

2012-10-18

Rickettsioses are caused by pathogenic species of the genus Rickettsia and play an important role as emerging diseases. The bacteria are transmitted to mammal hosts including humans by arthropod vectors. Since detection, especially in tick vectors, is usually based on PCR with genus-specific primers to include different occurring Rickettsia species, subsequent species identification is mainly achieved by Sanger sequencing. In the present study a real-time pyrosequencing approach was established with the objective to differentiate between species occurring in German Ixodes ticks, which are R. helvetica, R. monacensis, R. massiliae, and R. felis. Tick material from a quantitative real-time PCR (qPCR) based study on Rickettsia-infections in I. ricinus allowed direct comparison of both sequencing techniques, Sanger and real-time pyrosequencing. A sequence stretch of rickettsial citrate synthase (gltA) gene was identified to contain divergent single nucleotide polymorphism (SNP) sites suitable for Rickettsia species differentiation. Positive control plasmids inserting the respective target sequence of each Rickettsia species of interest were constructed for initial establishment of the real-time pyrosequencing approach using Qiagen's PSQ 96MA Pyrosequencing System operating in a 96-well format. The approach included an initial amplification reaction followed by the actual pyrosequencing, which is traceable by pyrograms in real-time. Afterwards, real-time pyrosequencing was applied to 263 Ixodes tick samples already detected Rickettsia-positive in previous qPCR experiments. Establishment of real-time pyrosequencing using positive control plasmids resulted in accurate detection of all SNPs in all included Rickettsia species. The method was then applied to 263 Rickettsia-positive Ixodes ricinus samples, of which 153 (58.2%) could be identified for their species (151 R. helvetica and 2 R. monacensis) by previous custom Sanger sequencing. Real-time pyrosequencing identified all Sanger-determined ticks as well as 35 previously undifferentiated ticks resulting in a total number of 188 (71.5%) identified samples. Pyrosequencing sensitivity was found to be strongly dependent on gltA copy numbers in the reaction setup. Whereas less than 101 copies in the initial amplification reaction resulted in identification of 15.1% of the samples only, the percentage increased to 54.2% at 101-102 copies, to 95.6% at >102-103 copies and reached 100% samples identified for their Rickettsia species if more than 103 copies were present in the template. The established real-time pyrosequencing approach represents a reliable method for detection and differentiation of Rickettsia spp. present in I. ricinus diagnostic material and prevalence studies. Furthermore, the method proved to be faster, more cost-effective as well as more sensitive than custom Sanger sequencing with simultaneous high specificity.

In-vitro and in-vivo imaging of MMP activity in cartilage and joint injury

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

Fukui, Tomoaki; Tenborg, Elizabeth; Yik, Jasper H.N.

Non-destructive detection of cartilage-degrading activities represents an advance in osteoarthritis (OA) research, with implications in studies of OA pathogenesis, progression, and intervention strategies. Matrix metalloproteinases (MMPs) are principal cartilage degrading enzymes that contribute to OA pathogenesis. MMPSense750 is an in-vivo fluorimetric imaging probe with the potential to continuously and non-invasively trace real-time MMP activities, but its use in OA-related research has not been reported. Our objective is to detect and characterize the early degradation activities shortly after cartilage or joint injury with MMPSense750. We determined the appropriate concentration, assay time, and linear range using various concentrations of recombinant MMPs asmore » standards. We then quantified MMP activity from cartilage explants subjected to either mechanical injury or inflammatory cytokine treatment in-vitro. Finally, we performed in-vivo MMP imaging of a mouse model of post-traumatic OA. Our in-vitro results showed that the optimal assay time was highly dependent on the MMP enzyme. In cartilage explant culture media, mechanical impact or cytokine treatment increased MMP activity. Injured knees of mice showed significantly higher fluorescent signal than uninjured knees. We conclude that MMPSense750 detects human MMP activities and can be used for in-vitro study with cartilage, as well as in-vivo studies of knee injury, and can offering real-time insight into the degradative processes that occurring within the joint before structural changes become evident radiographically. - Highlights: • MMPSense750 is near-infrared fluorescent probe which can detect MMP activity. • MMPSense750 can detect human MMP-3, -9, and -13. • The reaction kinetics with MMPSense750 were different for the three MMPs. • MMPSense750 can visualized real time MMP activity in mouse injured knees. • MMPSense750 is convenient tool to evaluate real-time MMP activity non-invasively.« less

The Gaia On-Board Scientific Data Handling

NASA Astrophysics Data System (ADS)

Arenou, F.; Babusiaux, C.; Chéreau, F.; Mignot, S.

2005-01-01

Because Gaia will perform a continuous all-sky survey at a medium (Spectro) or very high (Astro) angular resolution, the on-board processing needs to cope with a high variety of objects and densities which calls for generic and adaptive algorithms at the detection level, but not only. Consequently, the Pyxis scientific algorithms developed for the on-board data handling cover a large range of application: detection and confirmation of astronomical objects, background sky estimation, classification of detected objects, Near-Earth Objects onboard detection, and window selection and positioning. Very dense fields, where the real-time computing requirements should remain within fixed bounds, are particularly challenging. Another constraint stems from the limited telemetry bandwidth and an additional compromise has to be found between scientific requirements and constraints in terms of the mass, volume and power budgets of the satellite. The rationale for the on-board data handling procedure is described here, together with the developed algorithms, the main issues and the expected scientific performances in the Astro and Spectro instruments.

Detection of Treponema Denticola in Symptomatic Apical Periodontitis and in Symptomatic Apical Abscesses by Real-Time PCR

PubMed Central

Ozbek, Selcuk M.; Ozbek, Ahmet; Erdogan, Aziz S.

2009-01-01

Objectives: The aim of this study was to investigate the presence of Treponema denticola in symptomatic apical periodontitis and in symptomatic apical abscesses by real-time polymerase chain reaction (PCR) method. Methods: Microbial samples were collected from 60 single-rooted teeth having carious lesions and necrotic pulps. For each tooth, clinical data including patient symptoms were recorded. Teeth were categorized by diagnosis as having symptomatic apical periodontitis or symptomatic apical abscess. Aseptic microbial samples were collected using paper points from 30 infected root canals and from aspirates of 30 abscesses. DNA was extracted from the samples by using a QIAamp® DNA mini-kit and analyzed with real-time PCR. Results: T. denticola was detected in 24 of 30 cases diagnosed as symptomatic apical abscesses (80%), and 19 of 30 cases diagnosed as symptomatic apical periodontitis (63.3%). In general T. denticola was found in 43 of 60 cases (71.6%). Conclusions: Our findings suggest that T. denticola can participate in the pathogenesis of symptomatic apical abscesses. PMID:19421390

Towards an active real-time THz camera: first realization of a hybrid system

NASA Astrophysics Data System (ADS)

May, T.; am Weg, C.; Alcin, A.; Hils, B.; Löffler, T.; Roskos, H. G.

2007-04-01

We report the realization of a hybrid system for stand-off THz reflectrometry measurements. The design combines the best of two worlds: the high radiation power of sub-THz micro-electronic emitters and the high sensitivity of coherent opto-electronic detection. Our system is based on a commercially available multiplied Gunn source with a cw output power of 0.6 mW at 0.65 THz. We combine it with electro-optic mixing with femtosecond light pulses in a ZnTe crystal. This scheme can be described as heterodyne detection with a Ti:sapphire fs-laser acting as local oscillator and therefore allows for phase-sensitive measurements. Example images of test objects are obtained with mechanical scanning optics and with measurement times per pixel as short as 10 ms. The test objects are placed at a distance of 1 m from the detector and also from the source. The results indicate diffraction-limited resolution. Different contrast mechanisms, based on absorption, scattering, and difference in optical thickness are employed. Our evaluation shows that it should be possible to realize a real-time multi-pixel detector with several hundreds of pixels and a dynamic range of at least two orders of magnitude in power.

Response of the REWARD detection system to the presence of a Radiological Dispersal Device

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

Luis, R.; Baptista, M.; Barros, S.

2015-07-01

In recent years an increased international concern has emerged about the radiological and nuclear (RN) threats associated with the illicit trafficking of nuclear and radioactive materials that could be potentially used for terrorist attacks. The objective of the REWARD (Real Time Wide Area Radiation Surveillance System) project, co-funded by the European Union 7. Framework Programme Security, consisted in building a mobile system for real time, wide area radiation surveillance, using a CdZnTe detector for gamma radiation and a neutron detector based on novel silicon technologies. The sensing unit includes a GPS system and a wireless communication interface to send themore » data remotely to a monitoring base station, where it will be analyzed in real time and correlated with historical data from the tag location, in order to generate an alarm when an abnormal situation is detected. Due to its portability and accuracy, the system will be extremely useful in many different scenarios such as nuclear terrorism, lost radioactive sources, radioactive contamination or nuclear accidents. This paper shortly introduces the REWARD detection system, depicts some terrorist threat scenarios involving radioactive sources and special nuclear materials and summarizes the simulation work undertaken during the past three years in the framework of the REWARD project. The main objective consisted in making predictions regarding the behavior of the REWARD system in the presence of a Radiological Dispersion Device (RDD), one of the reference scenarios foreseen for REWARD, using the Monte Carlo simulation program MCNP6. The reference scenario is characterized in detail, from the i) radiological protection, ii) radiation detection requirements and iii) communications points of view. Experimental tests were performed at the Fire Brigades Facilities in Rome and at the Naples Fire Brigades, and the results, which validate the simulation work, are presented and analyzed. The response of the REWARD detection system to the presence of an RDD is predicted and discussed. (authors)« less

ARK: Autonomous mobile robot in an industrial environment

NASA Technical Reports Server (NTRS)

Nickerson, S. B.; Jasiobedzki, P.; Jenkin, M.; Jepson, A.; Milios, E.; Down, B.; Service, J. R. R.; Terzopoulos, D.; Tsotsos, J.; Wilkes, D.

1994-01-01

This paper describes research on the ARK (Autonomous Mobile Robot in a Known Environment) project. The technical objective of the project is to build a robot that can navigate in a complex industrial environment using maps with permanent structures. The environment is not altered in any way by adding easily identifiable beacons and the robot relies on naturally occurring objects to use as visual landmarks for navigation. The robot is equipped with various sensors that can detect unmapped obstacles, landmarks and objects. In this paper we describe the robot's industrial environment, it's architecture, a novel combined range and vision sensor and our recent results in controlling the robot in the real-time detection of objects using their color and in the processing of the robot's range and vision sensor data for navigation.

Analytical Performances of Human Immunodeficiency Virus Type 1 RNA-Based Amplix® Real-Time PCR Platform for HIV-1 RNA Quantification

PubMed Central

Mboumba Bouassa, Ralph-Sydney; Jenabian, Mohammad-Ali; Wolyec, Serge Tonen; Robin, Leman; Matta, Mathieu; Longo, Jean de Dieu; Grésenguet, Gérard; Andreoletti, Laurent; Bélec, Laurent

2016-01-01

Objectives. We evaluated the performances of Amplix real-time PCR platform developed by Biosynex (Strasbourg, France), combining automated station extraction (Amplix station 16 Dx) and real-time PCR (Amplix NG), for quantifying plasma HIV-1 RNA by lyophilized HIV-1 RNA-based Amplix reagents targeting gag and LTR, using samples from HIV-1-infected adults from Central African Republic. Results. Amplix real-time PCR assay showed low limit of detection (28 copies/mL), across wide dynamic range (1.4–10 log copies/mL), 100% sensitivity and 99% specificity, high reproducibility, and accuracy with mean bias < 5%. The assay showed excellent correlations and concordance of 95.3% with the reference HIV-1 RNA load assay (Roche), with mean absolute bias of +0.097 log copies/mL by Bland-Altman analysis. The assay was able to detect and quantify the most prevalent HIV-1 subtype strains and the majority of non-B subtypes, CRFs of HIV-1 group M, and HIV-1 groups N and O circulating in Central Africa. The Amplix assay showed 100% sensitivity and 99.6% specificity to diagnose virological failure in clinical samples from antiretroviral drug-experienced patients. Conclusions. The HIV-1 RNA-based Amplix real-time PCR platform constitutes sensitive and reliable system for clinical monitoring of HIV-1 RNA load in HIV-1-infected children and adults, particularly adapted to intermediate laboratory facilities in sub-Saharan Africa. PMID:28050283

Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes.

PubMed

Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

2016-02-23

Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb(2+), and connecting our platform with pipelines of tap water and wastewater for real-time online Pb(2+) detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques.

A man-made object detection for underwater TV

NASA Astrophysics Data System (ADS)

Cheng, Binbin; Wang, Wenwu; Chen, Yao

2018-03-01

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

Ultrafast dark-field surface inspection with hybrid-dispersion laser scanning

NASA Astrophysics Data System (ADS)

Yazaki, Akio; Kim, Chanju; Chan, Jacky; Mahjoubfar, Ata; Goda, Keisuke; Watanabe, Masahiro; Jalali, Bahram

2014-06-01

High-speed surface inspection plays an important role in industrial manufacturing, safety monitoring, and quality control. It is desirable to go beyond the speed limitation of current technologies for reducing manufacturing costs and opening a new window onto a class of applications that require high-throughput sensing. Here, we report a high-speed dark-field surface inspector for detection of micrometer-sized surface defects that can travel at a record high speed as high as a few kilometers per second. This method is based on a modified time-stretch microscope that illuminates temporally and spatially dispersed laser pulses on the surface of a fast-moving object and detects scattered light from defects on the surface with a sensitive photodetector in a dark-field configuration. The inspector's ability to perform ultrafast dark-field surface inspection enables real-time identification of difficult-to-detect features on weakly reflecting surfaces and hence renders the method much more practical than in the previously demonstrated bright-field configuration. Consequently, our inspector provides nearly 1000 times higher scanning speed than conventional inspectors. To show our method's broad utility, we demonstrate real-time inspection of the surface of various objects (a non-reflective black film, transparent flexible film, and reflective hard disk) for detection of 10 μm or smaller defects on a moving target at 20 m/s within a scan width of 25 mm at a scan rate of 90.9 MHz. Our method holds promise for improving the cost and performance of organic light-emitting diode displays for next-generation smart phones, lithium-ion batteries for green electronics, and high-efficiency solar cells.

A novel method of multiple nucleic acid detection: Real-time RT-PCR coupled with probe-melting curve analysis.

PubMed

Han, Yang; Hou, Shao-Yang; Ji, Shang-Zhi; Cheng, Juan; Zhang, Meng-Yue; He, Li-Juan; Ye, Xiang-Zhong; Li, Yi-Min; Zhang, Yi-Xuan

2017-11-15

A novel method, real-time reverse transcription PCR (real-time RT-PCR) coupled with probe-melting curve analysis, has been established to detect two kinds of samples within one fluorescence channel. Besides a conventional TaqMan probe, this method employs another specially designed melting-probe with a 5' terminus modification which meets the same label with the same fluorescent group. By using an asymmetric PCR method, the melting-probe is able to detect an extra sample in the melting stage effectively while it almost has little influence on the amplification detection. Thus, this method allows the availability of united employment of both amplification stage and melting stage for detecting samples in one reaction. The further demonstration by simultaneous detection of human immunodeficiency virus (HIV) and hepatitis C virus (HCV) in one channel as a model system is presented in this essay. The sensitivity of detection by real-time RT-PCR coupled with probe-melting analysis was proved to be equal to that detected by conventional real-time RT-PCR. Because real-time RT-PCR coupled with probe-melting analysis can double the detection throughputs within one fluorescence channel, it is expected to be a good solution for the problem of low-throughput in current real-time PCR. Copyright © 2017 Elsevier Inc. All rights reserved.

Protective materials with real-time puncture detection capability

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

Hermes, R.E.; Stampfer, J.F.; Valdez-Boyle, L.S.

1996-08-01

The protection of workers from chemical, biological, or radiological hazards requires the use of protective materials that can maintain their integrity during use. An accidental puncture in the protective material can result in a significant exposure to the worker. A five ply material has been developed that incorporates two layers of an electrically conductive polymer sandwiched between three layers of a nonconductive polymer. A normally open circuit that is connected between the conductive layers will be closed by puncturing the material with either a conductive or nonconductive object. This can be used to activate an audible alarm or visual beaconmore » to warn the worker of a breach in the integrity of the material. The worker is not connected to the circuit, and the puncture can be detected in real-time, even when caused by a nonconductor.« less

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.

Droplet digital polymerase chain reaction (PCR) outperforms real-time PCR in the detection of environmental DNA from an invasive fish species.

PubMed

Doi, Hideyuki; Takahara, Teruhiko; Minamoto, Toshifumi; Matsuhashi, Saeko; Uchii, Kimiko; Yamanaka, Hiroki

2015-05-05

Environmental DNA (eDNA) has been used to investigate species distributions in aquatic ecosystems. Most of these studies use real-time polymerase chain reaction (PCR) to detect eDNA in water; however, PCR amplification is often inhibited by the presence of organic and inorganic matter. In droplet digital PCR (ddPCR), the sample is partitioned into thousands of nanoliter droplets, and PCR inhibition may be reduced by the detection of the end-point of PCR amplification in each droplet, independent of the amplification efficiency. In addition, real-time PCR reagents can affect PCR amplification and consequently alter detection rates. We compared the effectiveness of ddPCR and real-time PCR using two different PCR reagents for the detection of the eDNA from invasive bluegill sunfish, Lepomis macrochirus, in ponds. We found that ddPCR had higher detection rates of bluegill eDNA in pond water than real-time PCR with either of the PCR reagents, especially at low DNA concentrations. Limits of DNA detection, which were tested by spiking the bluegill DNA to DNA extracts from the ponds containing natural inhibitors, found that ddPCR had higher detection rate than real-time PCR. Our results suggest that ddPCR is more resistant to the presence of PCR inhibitors in field samples than real-time PCR. Thus, ddPCR outperforms real-time PCR methods for detecting eDNA to document species distributions in natural habitats, especially in habitats with high concentrations of PCR inhibitors.

A multispectral automatic target recognition application for maritime surveillance, search, and rescue

NASA Astrophysics Data System (ADS)

Schoonmaker, Jon; Reed, Scott; Podobna, Yuliya; Vazquez, Jose; Boucher, Cynthia

2010-04-01

Due to increased security concerns, the commitment to monitor and maintain security in the maritime environment is increasingly a priority. A country's coast is the most vulnerable area for the incursion of illegal immigrants, terrorists and contraband. This work illustrates the ability of a low-cost, light-weight, multi-spectral, multi-channel imaging system to handle the environment and see under difficult marine conditions. The system and its implemented detecting and tracking technologies should be organic to the maritime homeland security community for search and rescue, fisheries, defense, and law enforcement. It is tailored for airborne and ship based platforms to detect, track and monitor suspected objects (such as semi-submerged targets like marine mammals, vessels in distress, and drug smugglers). In this system, automated detection and tracking technology is used to detect, classify and localize potential threats or objects of interest within the imagery provided by the multi-spectral system. These algorithms process the sensor data in real time, thereby providing immediate feedback when features of interest have been detected. A supervised detection system based on Haar features and Cascade Classifiers is presented and results are provided on real data. The system is shown to be extendable and reusable for a variety of different applications.

The development of a real-time reverse transcription-polymerase chain reaction (rRT-PCR) assay using TaqMan technology for the pan detection of bluetongue virus (BTV).

PubMed

Mulholland, Catherine; McMenamy, Michael J; Hoffmann, Bernd; Earley, Bernadette; Markey, Bryan; Cassidy, Joseph; Allan, Gordon; Welsh, Michael D; McKillen, John

2017-07-01

Bluetongue virus (BTV) is an infectious, non-contagious viral disease of domestic and wild ruminants that is transmitted by adult females of certain Culicoides species. Since 2006, several serotypes including BTV-1, 2, 4, 6, 8, 9 and 16, have spread from the Mediterranean basin into Northern Europe for the first time. BTV-8 in particular, caused a major epidemic in northern Europe. As a result, it is evident that most European countries are at risk of BTV infection. The objective of this study was to develop and validate a real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) assay based on TaqMan technology for the detection of representative strains of all BTV serotypes. Primers and probes were based on genome segment 10 of the virus, the NS3 gene. The assay was tested for sensitivity, and specificity. The analytical sensitivity of the rRT-PCR assay was 200 copies of RNA per reaction. The assay did not amplify the closely related orbivirus epizootic hemorrhagic disease virus (EHDV) but successfully detected all BTV reference strains including clinical samples from animals experimentally infected with BTV-8. This real time RT-PCR assay offers a sensitive, specific and rapid alternative assay for the pan detection of BTV that could be used as part of a panel of diagnostic assays for the detection of all serotypes of BTV. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Comparison of Hybrid Capture 2 Assay with Real-time-PCR for Detection and Quantitation of Hepatitis B Virus DNA

PubMed Central

Jahan, Munira; Lutful Moben, Ahmed; Tabassum, Shahina

2014-01-01

ABSTRACT Background Both real-time-polymerase chain reaction (PCR) and hybrid capture 2 (HC2) assay can detect and quantify hepatitis B virus (HBV) DNA. However, real-time-PCR can detect a wide range of HBV DNA, while HC2 assay could not detect lower levels of viremia. The present study was designed to detect and quantify HBV DNA by real-time-PCR and HC2 assay and compare the quantitative data of these two assays. Materials and methods A cross-sectional study was conducted in between July 2010 and June 2011. A total of 66 serologically diagnosed chronic hepatitis B (CHB) patients were selected for the study. Real-time-PCR and HC2 assay was done to detect HBV DNA. Data were analyzed by statistical Package for the social sciences (SPSS). Results Among 66 serologically diagnosed chronic hepatitis B patients 40 (60.61%) patients had detectable and 26 (39.39%) had undetectable HBV DNA by HC2 assay. Concordant results were obtained for 40 (60.61%) out of these 66 patients by real-time-PCR and HC2 assay with mean viral load of 7.06 ± 1.13 log10 copies/ml and 6.95 ± 1.08 log10 copies/ml, respectively. In the remaining 26 patients, HBV DNA was detectable by real-time-PCR in 20 patients (mean HBV DNA level was 3.67 ± 0.72 log10 copies/ml. However, HBV DNA could not be detectable in six cases by the both assays. The study showed strong correlation (r = 0.915) between real-time-PCR and HC2 assay for the detection and quantification of HBV DNA. Conclusion HC2 assay may be used as an alternative to real-time-PCR for CHB patients. How to cite this article: Majid F, Jahan M, Moben AL, Tabassum S. Comparison of Hybrid Capture 2 Assay with Real-time-PCR for Detection and Quantitation of Hepatitis B Virus DNA. Euroasian J Hepato-Gastroenterol 2014;4(1):31-35. PMID:29264316

Comparison of culture, single and multiplex real-time PCR for detection of Sabin poliovirus shedding in recently vaccinated Indian children.

PubMed

Giri, Sidhartha; Rajan, Anand K; Kumar, Nirmal; Dhanapal, Pavithra; Venkatesan, Jayalakshmi; Iturriza-Gomara, Miren; Taniuchi, Mami; John, Jacob; Abraham, Asha Mary; Kang, Gagandeep

2017-08-01

Although, culture is considered the gold standard for poliovirus detection from stool samples, real-time PCR has emerged as a faster and more sensitive alternative. Detection of poliovirus from the stool of recently vaccinated children by culture, single and multiplex real-time PCR was compared. Of the 80 samples tested, 55 (68.75%) were positive by culture compared to 61 (76.25%) and 60 (75%) samples by the single and one step multiplex real-time PCR assays respectively. Real-time PCR (singleplex and multiplex) is more sensitive than culture for poliovirus detection in stool, although the difference was not statistically significant. © 2017 Wiley Periodicals, Inc.

Powered Descent Trajectory Guidance and Some Considerations for Human Lunar Landing

NASA Technical Reports Server (NTRS)

Sostaric, Ronald R.

2007-01-01

The Autonomous Precision Landing and Hazard Detection and Avoidance Technology development (ALHAT) will enable an accurate (better than 100m) landing on the lunar surface. This technology will also permit autonomous (independent from ground) avoidance of hazards detected in real time. A preliminary trajectory guidance algorithm capable of supporting these tasks has been developed and demonstrated in simulations. Early results suggest that with expected improvements in sensor technology and lunar mapping, mission objectives are achievable.

Detecting abandoned objects using interacting multiple models

NASA Astrophysics Data System (ADS)

Becker, Stefan; Münch, David; Kieritz, Hilke; Hübner, Wolfgang; Arens, Michael

2015-10-01

In recent years, the wide use of video surveillance systems has caused an enormous increase in the amount of data that has to be stored, monitored, and processed. As a consequence, it is crucial to support human operators with automated surveillance applications. Towards this end an intelligent video analysis module for real-time alerting in case of abandoned objects in public spaces is proposed. The overall processing pipeline consists of two major parts. First, person motion is modeled using an Interacting Multiple Model (IMM) filter. The IMM filter estimates the state of a person according to a finite-state, discrete-time Markov chain. Second, the location of persons that stay at a fixed position defines a region of interest, in which a nonparametric background model with dynamic per-pixel state variables identifies abandoned objects. In case of a detected abandoned object, an alarm event is triggered. The effectiveness of the proposed system is evaluated on the PETS 2006 dataset and the i-Lids dataset, both reflecting prototypical surveillance scenarios.

Detection and forecasting of oyster norovirus outbreaks: recent advances and future perspectives.

PubMed

Wang, Jiao; Deng, Zhiqiang

2012-09-01

Norovirus is a highly infectious pathogen that is commonly found in oysters growing in fecally contaminated waters. Norovirus outbreaks can cause the closure of oyster harvesting waters and acute gastroenteritis in humans associated with consumption of contaminated raw oysters. Extensive efforts and progresses have been made in detection and forecasting of oyster norovirus outbreaks over the past decades. The main objective of this paper is to provide a literature review of methods and techniques for detecting and forecasting oyster norovirus outbreaks and thereby to identify the future directions for improving the detection and forecasting of norovirus outbreaks. It is found that (1) norovirus outbreaks display strong seasonality with the outbreak peak occurring commonly in December-March in the U.S. and April-May in the Europe; (2) norovirus outbreaks are affected by multiple environmental factors, including but not limited to precipitation, temperature, solar radiation, wind, and salinity; (3) various modeling approaches may be employed to forecast norovirus outbreaks, including Bayesian models, regression models, Artificial Neural Networks, and process-based models; and (4) diverse techniques are available for near real-time detection of norovirus outbreaks, including multiplex PCR, seminested PCR, real-time PCR, quantitative PCR, and satellite remote sensing. The findings are important to the management of oyster growing waters and to future investigations into norovirus outbreaks. It is recommended that a combined approach of sensor-assisted real time monitoring and modeling-based forecasting should be utilized for an efficient and effective detection and forecasting of norovirus outbreaks caused by consumption of contaminated oysters. Copyright © 2012 Elsevier Ltd. All rights reserved.

Development and evaluation of real-time loop-mediated isothermal amplification assay for rapid detection of cystic echinococcosis.

PubMed

Ahmed, Mohamed E; Eldigail, Mawahib H; Elamin, Fatima M; Ali, Ibtisam A; Grobusch, Martin P; Aradaib, Imadeldin E

2016-09-13

Cystic echinococcosis (CE) or hydatidosis, caused by the larval stage of Echinococcus granulosus (EG)-complex, is a neglected parasitic disease of public health importance. The disease is endemic in many African and Mediterranean countries including the Sudan. The objective of the present study was to develop and evaluate a real-time loop-mediated isothermal amplification (LAMP) assay for simple and rapid detection of CE in humans and domestic live stock in Sudan. A set of six LAMP primers, designed from the mitochondrial NADH-1 gene of EG cattle strain of genotype 5 (G5), was used as a target for LAMP assay. The assay was performed at a constant temperature (63 °C), with a real-time follow-up using a LightCycler and fluorochrome dye. Following amplification cycles in a simple water bath, LAMP products were observed for color change by naked eye and were visualized under UV light source using agarose gel electrophoresis. The real-time LAMP assay identified a variety of hydatid cysts strains recovered in the Sudan, including Echinococcus canadenses (G6) and Echinococcus ortleppi (G5). Real-time LAMP positive results were detected by the presence of an amplification curve, whereas negative results were indicated by absence of fluorescence detection. Positive LAMP results appeared as a bluish-colored reaction as observed by naked eye, whereas negative LAMP results were observed as purple-colored reaction. The sensitivity studies indicated that the LAMP assay detected as little as a 10 fg of parasite DNA. There was 100 % agreement between results of the LAMP assay and our previously described nested PCR when testing 10-fold serial dilution of DNA extracted from EG-complex hydatid cyst. However, there was no cross-reactivity with other parasites including cysticercus bovis, Fasciola gigantica, and Schistosoma bovis and nucleic acid free samples. The developed LAMP assay would be expected to prove highly significant in epidemiological surveys of CE in developing countries or areas of resource-poor settings for both ease of use and cost.

Molecular detection and species identification of Alexandrium (Dinophyceae) causing harmful algal blooms along the Chilean coastline

PubMed Central

Jedlicki, Ana; Fernández, Gonzalo; Astorga, Marcela; Oyarzún, Pablo; Toro, Jorge E.; Navarro, Jorge M.; Martínez, Víctor

2012-01-01

Background and aims On the basis of morphological evidence, the species involved in South American Pacific coast harmful algal blooms (HABs) has been traditionally recognized as Alexandrium catenella (Dinophyceae). However, these observations have not been confirmed using evidence based on genomic sequence variability. Our principal objective was to accurately determine the species of Alexandrium involved in local HABs in order to implement a real-time polymerase chain reaction (PCR) assay for its rapid and easy detection on filter-feeding shellfish, such as mussels. Methodology For species-specific determination, the intergenic spacer 1 (ITS1), 5.8S subunit, ITS2 and the hypervariable genomic regions D1–D5 of the large ribosomal subunit of local strains were sequenced and compared with two data sets of other Alexandrium sequences. Species-specific primers were used to amplify signature sequences within the genomic DNA of the studied species by conventional and real-time PCR. Principal results Phylogenetic analysis determined that the Chilean strain falls into Group I of the tamarensis complex. Our results support the allocation of the Chilean Alexandrium species as a toxic Alexandrium tamarense rather than A. catenella, as currently defined. Once local species were determined to belong to Group I of the tamarensis complex, a highly sensitive and accurate real-time PCR procedure was developed to detect dinoflagellate presence in Mytilus spp. (Bivalvia) samples after being fed (challenged) in vitro with the Chilean Alexandrium strain. The results show that real-time PCR is useful to detect Alexandrium intake in filter-feeding molluscs. Conclusions It has been shown that the classification of local Alexandrium using morphological evidence is not very accurate. Molecular methods enabled the HAB dinoflagellate species of the Chilean coast to be assigned as A. tamarense rather than A. catenella. Real-time PCR analysis based on A. tamarense primers allowed the detection of dinoflagellate DNA in Mytilus spp. samples exposed to this alga. Through the specific assignment of dinoflagellate species involved in HABs, more reliable preventive policies can be implemented. PMID:23259043

Online anomaly detection in wireless body area networks for reliable healthcare monitoring.

PubMed

Salem, Osman; Liu, Yaning; Mehaoua, Ahmed; Boutaba, Raouf

2014-09-01

In this paper, we propose a lightweight approach for online detection of faulty measurements by analyzing the data collected from medical wireless body area networks. The proposed framework performs sequential data analysis using a smart phone as a base station, and takes into account the constrained resources of the smart phone, such as processing power and storage capacity. The main objective is to raise alarms only when patients enter in an emergency situation, and to discard false alarms triggered by faulty measurements or ill-behaved sensors. The proposed approach is based on the Haar wavelet decomposition, nonseasonal Holt-Winters forecasting, and the Hampel filter for spatial analysis, and on for temporal analysis. Our objective is to reduce false alarms resulting from unreliable measurements and to reduce unnecessary healthcare intervention. We apply our proposed approach on real physiological dataset. Our experimental results prove the effectiveness of our approach in achieving good detection accuracy with a low false alarm rate. The simplicity and the processing speed of our proposed framework make it useful and efficient for real time diagnosis.

Real-time Transients from Palomar-QUEST Synoptic Sky Survey

NASA Astrophysics Data System (ADS)

Mahabal, Ashish A.; Drake, A.; Djorgovski, S. G.; Donalek, C.; Glikman, E.; Graham, M. J.; Williams, R.; Baltay, C.; Rabinowitz, D.; Bauer, A.; Ellman, N.; Lauer, R.; PQ Team Indiana

2006-12-01

The data from the driftscans of the Palomar-QUEST synoptic sky survey is now routinely processed in real-time. We describe here the various components of the pipeline. We search for both variable and transient objects, including supernovae, variable AGN, GRB orphan afterglows, cataclysmic variables, interesting stellar flares, novae, other types of variable stars, and do not exclude the possibility of even entirely new types of objects or phenomena. In order to flag as many asteroids as possible we have been doing two 4-hour scans of the same area covering 250 sq. deg and detect over a million sources. Flagging a source as a candidate transient requires detection in at least two filters besides its absence in fiducial sky constructed from past images. We use various software filters to eliminate instrument artifacts, and false alarms due to the proximity of bright, saturated stars which dominate the initial detection rate. This leaves up to a couple of hundred asteroids and genuine transients. Previously known asteroids are flagged through an automated comparison with a databases of known asteroids, and new ones through apparent motion. In the end, we have typically 10 20 astrophysical transients remaining per night, and we are currently working on their automated classification, and spectroscopic follow-up. We present preliminary results from real-time follow-up of a few candidates carried out with the Palomar 200-inch telescope as part of a pilot project. Finally we outline the plans for the much harder problem of classifying the transients more accurately for distribution through VOEventNet to astronomers interested only in specific types of transients, more details and overall setting of which is covered in our VOEventNet poster (Drake et al.)

Development of real-time recombinase polymerase amplification assay for rapid and sensitive detection of canine parvovirus 2.

PubMed

Geng, Yunyun; Wang, Jianchang; Liu, Libing; Lu, Yan; Tan, Ke; Chang, Yan-Zhong

2017-11-06

Canine parvovirus 2, a linear single-stranded DNA virus belonging to the genus Parvovirus within the family Parvoviridae, is a highly contagious pathogen of domestic dogs and several wild canidae species. Early detection of canine parvovirus (CPV-2) is crucial to initiating appropriate outbreak control strategies. Recombinase polymerase amplification (RPA), a novel isothermal gene amplification technique, has been developed for the molecular detection of diverse pathogens. In this study, a real-time RPA assay was developed for the detection of CPV-2 using primers and an exo probe targeting the CPV-2 nucleocapsid protein gene. The real-time RPA assay was performed successfully at 38 °C, and the results were obtained within 4-12 min for 10 5 -10 1 molecules of template DNA. The assay only detected CPV-2, and did not show cross-detection of other viral pathogens, demonstrating a high level of specificity. The analytical sensitivity of the real-time RPA was 10 1 copies/reaction of a standard DNA template, which was 10 times more sensitive than the common RPA method. The clinical sensitivity of the real-time RPA assay matched 100% (n = 91) to the real-time PCR results. The real-time RPA assay is a simple, rapid, reliable and affordable method that can potentially be applied for the detection of CPV-2 in the research laboratory and point-of-care diagnosis.

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

PubMed Central

Al-Naji, Ali; Gibson, Kim; Lee, Sang-Heon; Chahl, Javaan

2017-01-01

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications. PMID:28165382

Optimizing the real-time automatic location of the events produced in Romania using an advanced processing system

NASA Astrophysics Data System (ADS)

Neagoe, Cristian; Grecu, Bogdan; Manea, Liviu

2016-04-01

National Institute for Earth Physics (NIEP) operates a real time seismic network which is designed to monitor the seismic activity on the Romanian territory, which is dominated by the intermediate earthquakes (60-200 km) from Vrancea area. The ability to reduce the impact of earthquakes on society depends on the existence of a large number of high-quality observational data. The development of the network in recent years and an advanced seismic acquisition are crucial to achieving this objective. The software package used to perform the automatic real-time locations is Seiscomp3. An accurate choice of the Seiscomp3 setting parameters is necessary to ensure the best performance of the real-time system i.e., the most accurate location for the earthquakes and avoiding any false events. The aim of this study is to optimize the algorithms of the real-time system that detect and locate the earthquakes in the monitored area. This goal is pursued by testing different parameters (e.g., STA/LTA, filters applied to the waveforms) on a data set of representative earthquakes of the local seismicity. The results are compared with the locations from the Romanian Catalogue ROMPLUS.

Sequence Optimized Real-Time RT-PCR Assay for Detection of Crimean-Congo Hemorrhagic Fever Virus

DTIC Science & Technology

2017-03-21

19-23]. Real-56 time reverse-transcription PCR remains the gold standard for quantitative , sensitive, and specific 57 detection of CCHFV; however...five-fold in two different series , and samples were run by real- time RT-PCR 116 in triplicate. The preliminary LOD was the lowest RNA dilution where...1 Sequence optimized real- time RT-PCR assay for detection of Crimean-Congo hemorrhagic fever 1 virus 2 3 JW Koehler1, KL Delp1, AT Hall1, SP

Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

The Application of Sensors on Guardrails for the Purpose of Real Time Impact Detection

DTIC Science & Technology

2012-03-01

collection methods ; however, there are major differences in the measures of performance for policy goals and objectives (U.S. DOT, 2002). The goal here is...seriousness of this issue has motivated the US Department of Transportation and Transportation Research Board to develop and deploy new methods and... methods to integrate new sensing capabilities into existing Intelligent Transportation Systems in a time efficient and cost effective manner. In

Low-level processing for real-time image analysis

NASA Technical Reports Server (NTRS)

Eskenazi, R.; Wilf, J. M.

1979-01-01

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

GPU-based real-time trinocular stereo vision

NASA Astrophysics Data System (ADS)

Yao, Yuanbin; Linton, R. J.; Padir, Taskin

2013-01-01

Most stereovision applications are binocular which uses information from a 2-camera array to perform stereo matching and compute the depth image. Trinocular stereovision with a 3-camera array has been proved to provide higher accuracy in stereo matching which could benefit applications like distance finding, object recognition, and detection. This paper presents a real-time stereovision algorithm implemented on a GPGPU (General-purpose graphics processing unit) using a trinocular stereovision camera array. Algorithm employs a winner-take-all method applied to perform fusion of disparities in different directions following various image processing techniques to obtain the depth information. The goal of the algorithm is to achieve real-time processing speed with the help of a GPGPU involving the use of Open Source Computer Vision Library (OpenCV) in C++ and NVidia CUDA GPGPU Solution. The results are compared in accuracy and speed to verify the improvement.

Multithreaded hybrid feature tracking for markerless augmented reality.

PubMed

Lee, Taehee; Höllerer, Tobias

2009-01-01

We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-05-01

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

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-09-01

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

Detectability of Chelyabinsk-like impactors with Pan-STARRS

NASA Astrophysics Data System (ADS)

Micheli, Marco; Wainscoat, Richard J.; Denneau, Larry

2018-03-01

In this work we present the results of our analysis of the detectability of an object in the size range of the recent Chelyabinsk impactor under the current discovery and follow-up capabilities, using the specific observational strategy of the Pan-STARRS survey as a reference point. We first discuss the observability of real-life cases inspired by the impact trajectories of 2008 TC3, 2014 AA, the past Earth encounters with 2014 RC and 2015 TB145, the upcoming fly-by of 2012 TC4 and the Chelyabinsk event. We then expand our analysis with the investigation of synthetic impactors with realistic orbital distributions. Among the various conclusions of our analysis, we discuss how the time of first detectability of an object does not necessarily correspond to the moment when that same object can be recognized as an impactor. We also point out how objects discovered only a few days before impact can be immediately identified as impactors, partly thanks to the good astrometric quality that telescopes like Pan-STARRS currently achieve.

Resonator memories and optical novelty filters

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.; Erle, Marie C.

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

Resonator Memories And Optical Novelty Filters

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.; Erie, Marie C.

1987-05-01

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content-addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive ma-terials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydream-ing" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Simultaneous detection of transgenic DNA by surface plasmon resonance imaging with potential application to gene doping detection.

PubMed

Scarano, Simona; Ermini, Maria Laura; Spiriti, Maria Michela; Mascini, Marco; Bogani, Patrizia; Minunni, Maria

2011-08-15

Surface plasmon resonance imaging (SPRi) was used as the transduction principle for the development of optical-based sensing for transgenes detection in human cell lines. The objective was to develop a multianalyte, label-free, and real-time approach for DNA sequences that are identified as markers of transgenosis events. The strategy exploits SPRi sensing to detect the transgenic event by targeting selected marker sequences, which are present on shuttle vector backbone used to carry out the transfection of human embryonic kidney (HEK) cell lines. Here, we identified DNA sequences belonging to the Cytomegalovirus promoter and the Enhanced Green Fluorescent Protein gene. System development is discussed in terms of probe efficiency and influence of secondary structures on biorecognition reaction on sensor; moreover, optimization of PCR samples pretreatment was carried out to allow hybridization on biosensor, together with an approach to increase SPRi signals by in situ mass enhancement. Real-time PCR was also employed as reference technique for marker sequences detection on human HEK cells. We can foresee that the developed system may have potential applications in the field of antidoping research focused on the so-called gene doping.

Amaro-autonomous real-time detection of moving maritime objects: introducing a flight experiment for an on-board ship detection system

NASA Astrophysics Data System (ADS)

Schwenk, Kurt; Willburger, Katharina; Pless, Sebastian

2017-10-01

Motivated by politics and economy, the monitoring of the world wide ship traffic is a field of high topicality. To detect illegal activities like piracy, illegal fishery, ocean dumping and refugee transportation is of great value. The analysis of satellite images on the ground delivers a great contribution to situation awareness. However, for many applications the up-to-dateness of the data is crucial. With ground based processing, the time between image acquisition and delivery of the data to the end user is in the range of several hours. The highest influence to the duration of ground based processing is the delay caused by the transmission of the large amount of image data from the satellite to the processing centre on the ground. One expensive solution to this issue is the usage of data relay satellites systems like EDRS. Another approach is to analyse the image data directly on-board of the satellite. Since the product data (e.g. ship position, heading, velocity, characteristics) is very small compared to the input image data, real-time connections provided by satellite telecommunication services like Iridium or Orbcomm can be used to send small packets of information directly to the end user without significant delay. The AMARO (Autonomous real-time detection of moving maritime objects) project at DLR is a feasibility study of an on-board ship detection system involving a real-time low bandwidth communication. The operation of a prototype on-board ship detection system will be demonstrated on an airborne platform. In this article, the scope, aim and design of a flight experiment for an on-board ship detection system scheduled for mid of 2018 is presented. First, the scope and the constraints of the experiment are explained in detail. The main goal is to demonstrate the operability of an automatic ship detection system on board of an airplane. For data acquisition the optical high resolution DLR MACS-MARE camera (VIS/NIR) is used. The system will be able to send product data, like position, size and a small image of the ship directly to the user's smart-phone by email. The time between the acquisition of the image data and the delivery of the product data to the end-user is aimed to be less than three minutes. For communication, the SMS-like Iridium Short Burst Data (SBD) Service was chosen, providing a message size of around 300 Bytes. Under optimal sending/receiving conditions, messages can be transmitted bidirectional every 20 seconds. Due to the very small data bandwidth, not all product data may be transmittable at once, for instance, when flying over busy ships traffic zones. Therefore the system offers two services: a query and a push service. With the query service the end user can explicitly request data of a defined location and fixed time period by posting queries in an SQL-like language. With the push service, events can be predefined and messages are received automatically, if and when the event occurs. Finally, the hardware set-up, details of the ship detection algorithms and the current status of the experiment is presented.

Detection of Leptospira interrogans DNA and antigen in fixed equine eyes affected with end-stage equine recurrent uveitis.

PubMed

Pearce, Jacqueline W; Galle, Laurence E; Kleiboeker, Steve B; Turk, James R; Schommer, Susan K; Dubielizig, Richard R; Mitchell, William J; Moore, Cecil P; Giuliano, Elizabeth A

2007-11-01

Equine recurrent uveitis (ERU) is the most frequent cause of blindness in horses worldwide. Leptospira has been implicated as an etiologic agent in some cases of ERU and has been detected in fresh ocular tissues of affected horses. The objective of this study was to determine the presence of Leptospira antigen and DNA in fixed equine ocular tissues affected with end-stage ERU. Sections of eyes from 30 horses were obtained. Controls included 1) 10 normal equine eyes and 2) 10 equine eyes with a nonrecurrent form of uveitis. The experimental group consisted of 10 eyes diagnosed with ERU based on clinical signs and histologic lesions. Sections were subjected to immunohistochemical staining with an array of rabbit anti-Leptospira polyclonal antibodies. DNA extractions were performed by using a commercial kit designed for fixed tissue. Real-time PCR analysis was completed on extracted DNA. The target sequence for PCR was designed from alignments of available Leptospira 16S rDNA partial sequences obtained from GenBank. Two of 10 test samples were positive for Leptospira antigen by immunohistochemical assay. Zero of 20 controls were positive for Leptospira antigen. All test samples and controls were negative for Leptospira DNA by real-time PCR analysis. Leptospira was detected at a lower frequency than that previously reported for fresh ERU-affected aqueous humor and vitreous samples. Leptospira is not frequently detectable in fixed ocular tissues of horses affected with ERU when using traditional immunohistochemical and real-time PCR techniques.

Data Analytics for Smart Parking Applications.

PubMed

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-09-23

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset.

Data Analytics for Smart Parking Applications

PubMed Central

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-01-01

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset. PMID:27669259

Online Conditional Outlier Detection in Nonstationary Time Series

PubMed Central

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-01-01

The objective of this work is to develop methods for detecting outliers in time series data. Such methods can become the key component of various monitoring and alerting systems, where an outlier may be equal to some adverse condition that needs human attention. However, real-world time series are often affected by various sources of variability present in the environment that may influence the quality of detection; they may (1) explain some of the changes in the signal that would otherwise lead to false positive detections, as well as, (2) reduce the sensitivity of the detection algorithm leading to increase in false negatives. To alleviate these problems, we propose a new two-layer outlier detection approach that first tries to model and account for the nonstationarity and periodic variation in the time series, and then tries to use other observable variables in the environment to explain any additional signal variation. Our experiments on several data sets in different domains show that our method provides more accurate modeling of the time series, and that it is able to significantly improve outlier detection performance. PMID:29644345

Online Conditional Outlier Detection in Nonstationary Time Series.

PubMed

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-05-01

The objective of this work is to develop methods for detecting outliers in time series data. Such methods can become the key component of various monitoring and alerting systems, where an outlier may be equal to some adverse condition that needs human attention. However, real-world time series are often affected by various sources of variability present in the environment that may influence the quality of detection; they may (1) explain some of the changes in the signal that would otherwise lead to false positive detections, as well as, (2) reduce the sensitivity of the detection algorithm leading to increase in false negatives. To alleviate these problems, we propose a new two-layer outlier detection approach that first tries to model and account for the nonstationarity and periodic variation in the time series, and then tries to use other observable variables in the environment to explain any additional signal variation. Our experiments on several data sets in different domains show that our method provides more accurate modeling of the time series, and that it is able to significantly improve outlier detection performance.

Rectal swab sampling followed by an enrichment culture-based real-time PCR assay to detect Salmonella enterocolitis in children.

PubMed

Lin, L-H; Tsai, C-Y; Hung, M-H; Fang, Y-T; Ling, Q-D

2011-09-01

Although routine bacterial culture is the traditional reference standard method for the detection of Salmonella infection in children with diarrhoea, it is a time-consuming procedure that usually only gives results after 3-4 days. Some molecular detection methods can improve the turn-around time to within 24 h, but these methods are not applied directly from stool or rectal swab specimens as routine diagnostic methods for the detection of gastrointestinal pathogens. In this study, we tested the feasibility of a bacterial enrichment culture-based real-time PCR assay method for detecting and screening for diarrhoea in children caused by Salmonella. Our results showed that the minimum real-time PCR assay time required to detect enriched bacterial culture from a swab was 3 h. In all children with suspected Salmonella diarrhoea, the enrichment culture-based real-time PCR achieved 85.4% sensitivity and 98.1% specificity, as compared with the 53.7% sensitivity and 100% specificity of detection with the routine bacterial culture method. We suggest that rectal swab sampling followed by enrichment culture-based real-time PCR is suitable as a rapid method for detecting and screening for Salmonella in paediatric patients. © 2011 The Authors. Clinical Microbiology and Infection © 2011 European Society of Clinical Microbiology and Infectious Diseases.

Real-time multiple human perception with color-depth cameras on a mobile robot.

PubMed

Zhang, Hao; Reardon, Christopher; Parker, Lynne E

2013-10-01

The ability to perceive humans is an essential requirement for safe and efficient human-robot interaction. In real-world applications, the need for a robot to interact in real time with multiple humans in a dynamic, 3-D environment presents a significant challenge. The recent availability of commercial color-depth cameras allow for the creation of a system that makes use of the depth dimension, thus enabling a robot to observe its environment and perceive in the 3-D space. Here we present a system for 3-D multiple human perception in real time from a moving robot equipped with a color-depth camera and a consumer-grade computer. Our approach reduces computation time to achieve real-time performance through a unique combination of new ideas and established techniques. We remove the ground and ceiling planes from the 3-D point cloud input to separate candidate point clusters. We introduce the novel information concept, depth of interest, which we use to identify candidates for detection, and that avoids the computationally expensive scanning-window methods of other approaches. We utilize a cascade of detectors to distinguish humans from objects, in which we make intelligent reuse of intermediary features in successive detectors to improve computation. Because of the high computational cost of some methods, we represent our candidate tracking algorithm with a decision directed acyclic graph, which allows us to use the most computationally intense techniques only where necessary. We detail the successful implementation of our novel approach on a mobile robot and examine its performance in scenarios with real-world challenges, including occlusion, robot motion, nonupright humans, humans leaving and reentering the field of view (i.e., the reidentification challenge), human-object and human-human interaction. We conclude with the observation that the incorporation of the depth information, together with the use of modern techniques in new ways, we are able to create an accurate system for real-time 3-D perception of humans by a mobile robot.

A portable fetal heart monitor and its adaption to the detection of certain prenatal abnormalities

NASA Technical Reports Server (NTRS)

Zahorian, Stephen A.

1994-01-01

There were three primary objectives for this task: (1) The investigation of the feasibility of making the fetal heart rate monitor portable, using a laptop computer; (2) Improvements in the signal processing for the monitor; and (3) Implementation of a real-time hardware software system. These tasks have been completed as discussed in the following section.

DEVELOPMENT OF DATA QUALITY OBJECTIVES AND USE OF TWO VARIATIONS OF GENETICALLY-MODIFIED STREPTOCOCCUS GORDONIL AS LYSIS CONTROLS IN A QPCR ASSAY FOR ASSESSING SANITARY QUALITY OF WATER

EPA Science Inventory

Joseph B. James and Fred J. Genthner

United States Environmental Protection Agency, Gulf Breeze, FL

Background: Methods using rapid cycle, real-time, quantitative (QPCR) are being developed for detecting and quantifying Enterococcus spp. as well as other aquatic b...

A real time sorbent based air monitoring system for determining low level airborne exposure levels to Lewisite

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

Lattin, F.G.; Paul, D.G.; Jakubowski, E.M.

1994-12-31

The Real Time Analytical Platform (RTAP) is designed to provide mobile, real-time monitoring support to ensure protection of worker safety in areas where military unique compounds are used and stored, and at disposal sites. Quantitative analysis of low-level vapor concentrations in air is accomplished through sorbent-based collection with subsequent thermal desorption into a gas chromatograph (GC) equipped with a variety of detectors. The monitoring system is characterized by its sensitivity (ability to measure at low concentrations), selectivity (ability to filter out interferences), dynamic range and linearity, real time mode (versus methods requiring extensive sample preparation procedures), and ability to interfacemore » with complimentary GC detectors. This presentation describes an RTAP analytical method for analyzing lewisite, an arsenical compound, that consists of a GC screening technique with an Electron Capture Detector (ECD), and a confirmation technique using an Atomic Emission Detector (AED). Included in the presentation is a description of quality assurance objectives in the monitoring system, and an assessment of method accuracy, precision and detection levels.« less

Correlation of immune activation with HIV-1 RNA levels assayed by real-time RT-PCR in HIV-1 Subtype C infected patients in Northern India

PubMed Central

Agarwal, Atima; Sankaran, Sumathi; Vajpayee, Madhu; Sreenivas, V; Seth, Pradeep; Dandekar, Satya

2014-01-01

Background Assays with specificity and cost effectiveness are needed for the measurement of HIV-1 burden to monitor disease progression or response to anti-retroviral therapy (ART) in HIV-1 subtype C infected patients. Objectives The objective of this study was to develop and validate an affordable; one step Real-Time RT-PCR assay with high specificity and sensitivity to measure plasma HIV-1 loads in HIV-1 subtype C infected patients. Results We developed an RT-PCR assay to detect and quantitate plasma HIV-1 levels in HIV-1 subtype C infected patients. An inverse correlation between plasma viral loads (PVL) and CD4+ T-cell numbers was detected at all CDC stages. Significant correlations were found between CD8+ T-cell activation and PVL, as well as with the clinical and immunological status of the patients. Conclusions The RT-PCR assay provides a sensitive method to measure PVL in HIV-1 subtype C infected patients. Viral loads correlated with immune activation and can be used to monitor HIV care in India. PMID:17962068

Detection of viable Salmonella in ice cream by TaqMan real-time polymerase chain reaction assay combining propidium monoazide.

PubMed

Wang, Yuexia; Yang, Ming; Liu, Shuchun; Chen, Wanyi; Suo, Biao

2015-09-01

Real-time polymerase chain reaction (PCR) allows rapid detection of Salmonella in frozen dairy products, but it might cause a false positive detection result because it might amplify DNA from dead target cells as well. In this study, Salmonella-free frozen ice cream was initially inoculated with heat-killed Salmonella Typhimurium cells and stored at -18°C. Bacterial DNA extracted from the sample was amplified using TaqMan probe-based real-time PCR targeting the invA gene. Our results indicated that DNA from the dead cells remained stable in frozen ice cream for at least 20 days, and could produce fluorescence signal for real-time PCR as well. To overcome this limitation, propidium monoazide (PMA) was combined with real-time PCR. PMA treatment can effectively prevent PCR amplification from heat-killed Salmonella cells in frozen ice cream. The PMA real-time PCR assay can selectively detect viable Salmonella at as low as 10 3  CFU/mL. Combining 18 hours of pre-enrichment with the assay allows for the detection of viable Salmonella at 10 0  CFU/mL and avoiding the false-positive result of dead cells. The PMA real-time PCR assay provides an alternative specifically for detection of viable Salmonella in ice cream. However, when the PMA real-time PCR assay was evaluated in ice cream subjected to frozen storage, it obviously underestimated the contamination situation of viable Salmonella, which might lead to a false negative result. According to this result, the use of enrichment prior to PMA real-time PCR analysis remains as the more appropriate approach. Copyright © 2015. Published by Elsevier B.V.

Detection of Histoplasma capsulatum from clinical specimens by cycling probe-based real-time PCR and nested real-time PCR.

PubMed

Muraosa, Yasunori; Toyotome, Takahito; Yahiro, Maki; Watanabe, Akira; Shikanai-Yasuda, Maria Aparecida; Kamei, Katsuhiko

2016-05-01

We developed new cycling probe-based real-time PCR and nested real-time PCR assays for the detection of Histoplasma capsulatum that were designed to detect the gene encoding N-acetylated α-linked acidic dipeptidase (NAALADase), which we previously identified as an H. capsulatum antigen reacting with sera from patients with histoplasmosis. Both assays specifically detected the DNAs of all H. capsulatum strains but not those of other fungi or human DNA. The limited of detection (LOD) of the real-time PCR assay was 10 DNA copies when using 10-fold serial dilutions of the standard plasmid DNA and 50 DNA copies when using human serum spiked with standard plasmid DNA. The nested real-time PCR improved the LOD to 5 DNA copies when using human serum spiked with standard plasmid DNA, which represents a 10-fold higher than that observed with the real-time PCR assay. To assess the ability of the two assays to diagnose histoplasmosis, we analyzed a small number of clinical specimens collected from five patients with histoplasmosis, such as sera (n = 4), formalin-fixed paraffin-embedded (FFPE) tissue (n = 4), and bronchoalveolar lavage fluid (BALF) (n = 1). Although clinical sensitivity of the real-time PCR assay was insufficiently sensitive (33%), the nested real-time PCR assay increased the clinical sensitivity (77%), suggesting it has a potential to be a useful method for detecting H. capsulatum DNA in clinical specimens. © The Author 2015. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dosimetry of heavy ions by use of CCD detectors

NASA Technical Reports Server (NTRS)

Schott, J. U.

1994-01-01

The design and the atomic composition of Charge Coupled Devices (CCD's) make them unique for investigations of single energetic particle events. As detector system for ionizing particles they detect single particles with local resolution and near real time particle tracking. In combination with its properties as optical sensor, particle transversals of single particles are to be correlated to any objects attached to the light sensitive surface of the sensor by simple imaging of their shadow and subsequent image analysis of both, optical image and particle effects, observed in affected pixels. With biological objects it is possible for the first time to investigate effects of single heavy ions in tissue or extinguished organs of metabolizing (i.e. moving) systems with a local resolution better than 15 microns. Calibration data for particle detection in CCD's are presented for low energetic protons and heavy ions.

Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

PubMed Central

Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

2012-01-01

Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

PubMed

Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

2012-12-12

Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

Multiplex Real-Time PCR Assay for Rapid Detection of Methicillin-Resistant Staphylococci Directly from Positive Blood Cultures

PubMed Central

Wang, Hye-young; Kim, Sunghyun; Kim, Jungho; Park, Soon-Deok

2014-01-01

Methicillin-resistant Staphylococcus aureus (MRSA) is the most prevalent cause of bloodstream infections (BSIs) and is recognized as a major nosocomial pathogen. This study aimed to evaluate a newly designed multiplex real-time PCR assay capable of the simultaneous detection of mecA, S. aureus, and coagulase-negative staphylococci (CoNS) in blood culture specimens. The Real-MRSA and Real-MRCoNS multiplex real-time PCR assays (M&D, Republic of Korea) use the TaqMan probes 16S rRNA for Staphylococcus spp., the nuc gene for S. aureus, and the mecA gene for methicillin resistance. The detection limit of the multiplex real-time PCR assay was 103 CFU/ml per PCR for each gene target. The multiplex real-time PCR assay was evaluated using 118 clinical isolates from various specimen types and a total of 350 positive blood cultures from a continuous monitoring blood culture system. The results obtained with the multiplex real-time PCR assay for the three targets were in agreement with those of conventional identification and susceptibility testing methods except for one organism. Of 350 positive bottle cultures, the sensitivities of the multiplex real-time PCR kit were 100% (166/166 cultures), 97.2% (35/36 cultures), and 99.2% (117/118 cultures) for the 16S rRNA, nuc, and mecA genes, respectively, and the specificities for all three targets were 100%. The Real-MRSA and Real-MRCoNS multiplex real-time PCR assays are very useful for the rapid accurate diagnosis of staphylococcal BSIs. In addition, the Real-MRSA and Real-MRCoNS multiplex real-time PCR assays could have an important impact on the choice of appropriate antimicrobial therapy, based on detection of the mecA gene. PMID:24648566

Detection of Toxoplasma gondii and Epstein-Barr virus in HIV patients with clinical symptoms of suspected central nervous system infection using duplex real-time polymerase chain reaction

NASA Astrophysics Data System (ADS)

Rahmawati, E.; Ibrahim, F.; Imran, D.; Sudarmono, P.

2017-08-01

Focal brain lesion is a neurological complication in HIV, which is marked as a space occupying lesion (SOL) and needs rapid and effective treatment. This lesion is mainly caused by encephalitis toxoplasma and primary central nervous system lymphoma related to the Epstein-Barr virus (EBV) infection, which is difficult to distinguish using CT scan or magnetic resonance imaging (MRI). The gold standard of diagnosing focal brain lesion has been brain biopsy, but this examination is an invasive procedure that causes complications. The objective of this study is to obtain the rapid laboratory diagnosis of Toxoplasma gondii (T. gondii) and EBV infection. In this experimental study, blood and cerebrospinal fluid were obtained from HIV patients who were admitted to the Neurology Department of Cipto Mangunkusumo Hospital. The samples were examined using duplex real-time polymerase chain reaction (PCR) to detect T. gondii and EBV. The first step was the optimization of duplex real-time PCR, including the annealing temperature, primer and probe concentration, elution volume, and template volume. Minimal DNA detection was used to measure minimal T. gondii and EBV. Cross reactions were determined for technical specificity using the bacteria and viruses Staphylococcus aureus, Klebsiella pneumonia, Pseudomonas aeruginosa, Mycobacterium tuberculosis H37Rv, Candida spp, cytomegalovirus, herpes zoster virus, and varicella zoster virus. Duplex real-time PCR was applied optimally to patients. In the optimization of duplex real-time PCR, the annealing temperature of T. gondii and EBV were 58 °C, the concentration of primer forward and reverse for T. gondii and EBV were 0.2 μM, the concentration of probe for T. gondii and EBV were 0.4μM and 0.2 μM, respectively. Minimal DNA detection of T. gondii and EBV were 5.68 copy/ml and 1.31 copy/ml, respectively. There was no cross reaction between another bacteria and virus that were used as the primer and probe for T. gondii and EBV. The blood duplex real-time PCR was positive for T. gondii (16%), EBV (40%), and both (16%). The cerebrospinal fluid samples were positive for T. gondii (20%), EBV (28%), and both (4%).

Faint Object Detection in Multi-Epoch Observations via Catalog Data Fusion

NASA Astrophysics Data System (ADS)

Budavári, Tamás; Szalay, Alexander S.; Loredo, Thomas J.

2017-03-01

Astronomy in the time-domain era faces several new challenges. One of them is the efficient use of observations obtained at multiple epochs. The work presented here addresses faint object detection and describes an incremental strategy for separating real objects from artifacts in ongoing surveys. The idea is to produce low-threshold single-epoch catalogs and to accumulate information across epochs. This is in contrast to more conventional strategies based on co-added or stacked images. We adopt a Bayesian approach, addressing object detection by calculating the marginal likelihoods for hypotheses asserting that there is no object or one object in a small image patch containing at most one cataloged source at each epoch. The object-present hypothesis interprets the sources in a patch at different epochs as arising from a genuine object; the no-object hypothesis interprets candidate sources as spurious, arising from noise peaks. We study the detection probability for constant-flux objects in a Gaussian noise setting, comparing results based on single and stacked exposures to results based on a series of single-epoch catalog summaries. Our procedure amounts to generalized cross-matching: it is the product of a factor accounting for the matching of the estimated fluxes of the candidate sources and a factor accounting for the matching of their estimated directions. We find that probabilistic fusion of multi-epoch catalogs can detect sources with similar sensitivity and selectivity compared to stacking. The probabilistic cross-matching framework underlying our approach plays an important role in maintaining detection sensitivity and points toward generalizations that could accommodate variability and complex object structure.

Multi-Level Pre-Correlation RFI Flagging for Real-Time Implementation on UniBoard

NASA Astrophysics Data System (ADS)

Dumez-Viou, Cédric; Weber, Rodolphe; Ravier, Philippe

2016-03-01

Because of the denser active use of the spectrum, and because of radio telescopes higher sensitivity, radio frequency interference (RFI) mitigation has become a sensitive topic for current and future radio telescope designs. Even if quite sophisticated approaches have been proposed in the recent years, the majority of RFI mitigation operational procedures are based on post-correlation corrupted data flagging. Moreover, given the huge amount of data delivered by current and next generation radio telescopes, all these RFI detection procedures have to be at least automatic and, if possible, real-time. In this paper, the implementation of a real-time pre-correlation RFI detection and flagging procedure into generic high-performance computing platforms based on field programmable gate arrays (FPGA) is described, simulated and tested. One of these boards, UniBoard, developed under a Joint Research Activity in the RadioNet FP7 European programme is based on eight FPGAs interconnected by a high speed transceiver mesh. It provides up to 4 TMACs with ®Altera Stratix IV FPGA and 160 Gbps data rate for the input data stream. The proposed concept is to continuously monitor the data quality at different stages in the digital preprocessing pipeline between the antennas and the correlator, at the station level and the core level. In this way, the detectors are applied at stages where different time-frequency resolutions can be achieved and where the interference-to-noise ratio (INR) is maximum right before any dilution of RFI characteristics by subsequent channelizations or signal recombinations. The detection decisions could be linked to a RFI statistics database or could be attached to the data for later stage flagging. Considering the high in-out data rate in the pre-correlation stages, only real-time and go-through detectors (i.e. no iterative processing) can be implemented. In this paper, a real-time and adaptive detection scheme is described. An ongoing case study has been set up with the Electronic Multi-Beam Radio Astronomy Concept (EMBRACE) radio telescope facility at Nançay Observatory. The objective is to evaluate the performances of this concept in term of hardware complexity, detection efficiency and additional RFI metadata rate cost. The UniBoard implementation scheme is described.

Interlaboratory study of DNA extraction from multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for individual kernel detection system of genetically modified maize.

PubMed

Akiyama, Hiroshi; Sakata, Kozue; Makiyma, Daiki; Nakamura, Kosuke; Teshima, Reiko; Nakashima, Akie; Ogawa, Asako; Yamagishi, Toru; Futo, Satoshi; Oguchi, Taichi; Mano, Junichi; Kitta, Kazumi

2011-01-01

In many countries, the labeling of grains, feed, and foodstuff is mandatory if the genetically modified (GM) organism content exceeds a certain level of approved GM varieties. We previously developed an individual kernel detection system consisting of grinding individual kernels, DNA extraction from the individually ground kernels, GM detection using multiplex real-time PCR, and GM event detection using multiplex qualitative PCR to analyze the precise commingling level and varieties of GM maize in real sample grains. We performed the interlaboratory study of the DNA extraction with multiple ground samples, multiplex real-time PCR detection, and multiplex qualitative PCR detection to evaluate its applicability, practicality, and ruggedness for the individual kernel detection system of GM maize. DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR were evaluated by five laboratories in Japan, and all results from these laboratories were consistent with the expected results in terms of the commingling level and event analysis. Thus, the DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for the individual kernel detection system is applicable and practicable in a laboratory to regulate the commingling level of GM maize grain for GM samples, including stacked GM maize.

Learned filters for object detection in multi-object visual tracking

NASA Astrophysics Data System (ADS)

Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

2016-05-01

We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

Measurement of Irradiated Pyroprocessing Samples via Laser Induced Breakdown Spectroscopy

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

Phongikaroon, Supathorn

The primary objective of this research is to develop an applied technology and provide an assessment to remotely measure and analyze the real time or near real time concentrations of used nuclear fuel (UNF) dissolute in electrorefiners. Here, Laser-Induced Breakdown Spectroscopy (LIBS), in UNF pyroprocessing facilities will be investigated. LIBS is an elemental analysis method, which is based on the emission from plasma generated by focusing a laser beam into the medium. This technology has been reported to be applicable in the media of solids, liquids (includes molten metals), and gases for detecting elements of special nuclear materials. The advantagesmore » of applying the technology for pyroprocessing facilities are: (i) Rapid real-time elemental analysis|one measurement/laser pulse, or average spectra from multiple laser pulses for greater accuracy in < 2 minutes; (ii) Direct detection of elements and impurities in the system with low detection limits|element specific, ranging from 2-1000 ppm for most elements; and (iii) Near non-destructive elemental analysis method (about 1 g material). One important challenge to overcome is achieving high-resolution spectral analysis to quantitatively analyze all important fission products and actinides. Another important challenge is related to accessibility of molten salt, which is heated in a heavily insulated, remotely operated furnace in a high radiation environment with an argon atmosphere.« less

Real-time portable system for fabric defect detection using an ARM processor

NASA Astrophysics Data System (ADS)

Fernandez-Gallego, J. A.; Yañez-Puentes, J. P.; Ortiz-Jaramillo, B.; Alvarez, J.; Orjuela-Vargas, S. A.; Philips, W.

2012-06-01

Modern textile industry seeks to produce textiles as little defective as possible since the presence of defects can decrease the final price of products from 45% to 65%. Automated visual inspection (AVI) systems, based on image analysis, have become an important alternative for replacing traditional inspections methods that involve human tasks. An AVI system gives the advantage of repeatability when implemented within defined constrains, offering more objective and reliable results for particular tasks than human inspection. Costs of automated inspection systems development can be reduced using modular solutions with embedded systems, in which an important advantage is the low energy consumption. Among the possibilities for developing embedded systems, the ARM processor has been explored for acquisition, monitoring and simple signal processing tasks. In a recent approach we have explored the use of the ARM processor for defects detection by implementing the wavelet transform. However, the computation speed of the preprocessing was not yet sufficient for real time applications. In this approach we significantly improve the preprocessing speed of the algorithm, by optimizing matrix operations, such that it is adequate for a real time application. The system was tested for defect detection using different defect types. The paper is focused in giving a detailed description of the basis of the algorithm implementation, such that other algorithms may use of the ARM operations for fast implementations.

An automatic detection method for the boiler pipe header based on real-time image acquisition

NASA Astrophysics Data System (ADS)

Long, Yi; Liu, YunLong; Qin, Yongliang; Yang, XiangWei; Li, DengKe; Shen, DingJie

2017-06-01

Generally, an endoscope is used to test the inner part of the thermal power plants boiler pipe header. However, since the endoscope hose manual operation, the length and angle of the inserted probe cannot be controlled. Additionally, it has a big blind spot observation subject to the length of the endoscope wire. To solve these problems, an automatic detection method for the boiler pipe header based on real-time image acquisition and simulation comparison techniques was proposed. The magnetic crawler with permanent magnet wheel could carry the real-time image acquisition device to complete the crawling work and collect the real-time scene image. According to the obtained location by using the positioning auxiliary device, the position of the real-time detection image in a virtual 3-D model was calibrated. Through comparing of the real-time detection images and the computer simulation images, the defects or foreign matter fall into could be accurately positioning, so as to repair and clean up conveniently.

Bayes filter modification for drivability map estimation with observations from stereo vision

NASA Astrophysics Data System (ADS)

Panchenko, Aleksei; Prun, Viktor; Turchenkov, Dmitri

2017-02-01

Reconstruction of a drivability map for a moving vehicle is a well-known research topic in applied robotics. Here creating such a map for an autonomous truck on a generally planar surface containing separate obstacles is considered. The source of measurements for the truck is a calibrated pair of cameras. The stereo system detects and reconstructs several types of objects, such as road borders, other vehicles, pedestrians and general tall objects or highly saturated objects (e.g. road cone). For creating a robust mapping module we use a modification of Bayes filtering, which introduces some novel techniques for occupancy map update step. Specifically, our modified version becomes applicable to the presence of false positive measurement errors, stereo shading and obstacle occlusion. We implemented the technique and achieved real-time 15 FPS computations on an industrial shake proof PC. Our real world experiments show the positive effect of the filtering step.

Understanding of Object Detection Based on CNN Family and YOLO

NASA Astrophysics Data System (ADS)

Du, Juan

2018-04-01

As a key use of image processing, object detection has boomed along with the unprecedented advancement of Convolutional Neural Network (CNN) and its variants since 2012. When CNN series develops to Faster Region with CNN (R-CNN), the Mean Average Precision (mAP) has reached 76.4, whereas, the Frame Per Second (FPS) of Faster R-CNN remains 5 to 18 which is far slower than the real-time effect. Thus, the most urgent requirement of object detection improvement is to accelerate the speed. Based on the general introduction to the background and the core solution CNN, this paper exhibits one of the best CNN representatives You Only Look Once (YOLO), which breaks through the CNN family’s tradition and innovates a complete new way of solving the object detection with most simple and high efficient way. Its fastest speed has achieved the exciting unparalleled result with FPS 155, and its mAP can also reach up to 78.6, both of which have surpassed the performance of Faster R-CNN greatly. Additionally, compared with the latest most advanced solution, YOLOv2 achieves an excellent tradeoff between speed and accuracy as well as an object detector with strong generalization ability to represent the whole image.

Shape-based human detection for threat assessment

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Zhan, Pengcheng; Thomas, Aaron; Schoenberger, Robert B.

2004-07-01

Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments. Any moving objects including animals can falsely trigger the security system. Other security systems that utilize video equipment require human interpretation of the scene in order to make real-time threat assessment. Shape-based human detection technique has been developed for accurate early threat assessments for open and remote environment. Potential threats are isolated from the static background scene using differential motion analysis and contours of the intruding objects are extracted for shape analysis. Contour points are simplified by removing redundant points connecting short and straight line segments and preserving only those with shape significance. Contours are represented in tangent space for comparison with shapes stored in database. Power cepstrum technique has been developed to search for the best matched contour in database and to distinguish a human from other objects from different viewing angles and distances.

A COMPARATIVE STUDY OF REAL-TIME AND STATIC ULTRASONOGRAPHY DIAGNOSES FOR THE INCIDENTAL DETECTION OF DIFFUSE THYROID DISEASE.

PubMed

Kim, Dong Wook

2015-08-01

The aim of this study was to compare the diagnostic accuracy of real-time and static ultrasonography (US) for the incidental detection of diffuse thyroid disease (DTD). In 118 consecutive patients, a single radiologist performed real-time US before thyroidectomy. For static US, the same radiologist retrospectively investigated the sonographic findings on a picture-archiving and communication system after 3 months. The diagnostic categories of both real-time and static US diagnoses were determined based on the number of abnormal findings, and the diagnostic indices were calculated by a receiver operating characteristic (ROC) curve analysis using the histopathologic results as the reference standard. Histopathologic results included normal thyroid (n = 77), Hashimoto thyroiditis (n = 11), non-Hashimoto lymphocytic thyroiditis (n = 29), and diffuse hyperplasia (n = 1). Normal thyroid and DTD showed significant differences in echogenicity, echotexture, glandular margin, and vascularity on both real-time and static US. There was a positive correlation between US categories and histopathologic results in both real-time and static US. The highest diagnostic indices were obtained when the cutoff criteria of real-time and static US diagnoses were chosen as indeterminate and suspicious for DTD, respectively. The ROC curve analysis showed that real-time US was superior to static US in diagnostic accuracy. Both real-time and static US may be helpful for the detection of incidental DTD, but real-time US is superior to static US for detecting incidental DTD.

Optimization of the elution buffer and concentration method for detecting hepatitis E virus in swine liver using a nested reverse transcription-polymerase chain reaction and real-time reverse transcription-polymerase chain reaction.

PubMed

Son, Na Ry; Seo, Dong Joo; Lee, Min Hwa; Seo, Sheungwoo; Wang, Xiaoyu; Lee, Bog-Hieu; Lee, Jeong-Su; Joo, In-Sun; Hwang, In-Gyun; Choi, Changsun

2014-09-01

The aim of this study was to develop an optimal technique for detecting hepatitis E virus (HEV) in swine livers. Here, three elution buffers and two concentration methods were compared with respect to enhancing recovery of HEV from swine liver samples. Real-time reverse transcription-polymerase chain reaction (RT-PCR) and nested RT-PCR were performed to detect HEV RNA. When phosphate-buffered saline (PBS, pH 7.4) was used to concentrate HEV in swine liver samples using ultrafiltration, real-time RT-PCR detected HEV in 6 of the 26 samples. When threonine buffer was used to concentrate HEV using polyethylene glycol (PEG) precipitation and ultrafiltration, real-time RT-PCR detected HEV in 1 and 3 of the 26 samples, respectively. When glycine buffer was used to concentrate HEV using ultrafiltration and PEG precipitation, real-time RT-PCR detected HEV in 1 and 3 samples of the 26 samples, respectively. When nested RT-PCR was used to detect HEV, all samples tested negative regardless of the type of elution buffer or concentration method used. Therefore, the combination of real-time RT-PCR and ultrafiltration with PBS buffer was the most sensitive and reliable method for detecting HEV in swine livers. Copyright © 2014 Elsevier B.V. All rights reserved.

A Metrics-Based Approach to Intrusion Detection System Evaluation for Distributed Real-Time Systems

DTIC Science & Technology

2002-04-01

Based Approach to Intrusion Detection System Evaluation for Distributed Real - Time Systems Authors: G. A. Fink, B. L. Chappell, T. G. Turner, and...Distributed, Security. 1 Introduction Processing and cost requirements are driving future naval combat platforms to use distributed, real - time systems of...distributed, real - time systems . As these systems grow more complex, the timing requirements do not diminish; indeed, they may become more constrained

Real-time monitoring of acoustic linear and nonlinear behavior of titanium alloys during low-cycle fatigue and high-cycle fatigue

NASA Astrophysics Data System (ADS)

Frouin, Jerome; Sathish, Shamachary; Na, Jeong K.

2000-05-01

An in-situ technique to measure sound velocity, ultrasonic attenuation and acoustic nonlinear property has been developed for characterization and early detection of fatigue damage in aerospace materials. For this purpose we have developed a computer software and measurement technique including hardware for the automation of the measurement. New transducer holder and special grips are designed. The automation has allowed us to test the long-term stability of the electronics over a period of time and so proof of the linearity of the system. Real-time monitoring of the material nonlinearity has been performed on dog-bone specimens from zero fatigue all the way to the final fracture under low-cycle fatigue test condition (LCF) and high-cycle test condition (HCF). Real-time health monitoring of the material can greatly contribute to the understanding of material behavior under cyclic loading. Interpretation of the results show that correlation exist between the slope of the curve described by the material nonlinearity and the life of the component. This new methodology was developed with an objective to predict the initiation of fatigue microcracks, and to detect, in-situ fatigue crack initiation as well as to quantify early stages of fatigue damage.

Foliage discrimination using a rotating ladar

NASA Technical Reports Server (NTRS)

Castano, A.; Matthies, L.

2003-01-01

We present a real time algorithm that detects foliage using range from a rotating laser. Objects not classified as foliage are conservatively labeled as non-driving obstacles. In contrast to related work that uses range statistics to classify objects, we exploit the expected localities and continuities of an obstacle, in both space and time. Also, instead of attempting to find a single accurate discriminating factor for every ladar return, we hypothesize the class of some few returns and then spread the confidence (and classification) to other returns using the locality constraints. The Urbie robot is presently using this algorithm to descriminate drivable grass from obstacles during outdoor autonomous navigation tasks.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Brown, A.; Brown, J.

2010-09-01

We develop and evaluate the performance of advanced algorithms which provide significantly improved capabilities for automated detection and tracking of ballistic and flying dim objects in the presence of highly structured intense clutter. Applications include ballistic missile early warning, midcourse tracking, trajectory prediction, and resident space object detection and tracking. The set of algorithms include, in particular, adaptive spatiotemporal clutter estimation-suppression and nonlinear filtering-based multiple-object track-before-detect. These algorithms are suitable for integration into geostationary, highly elliptical, or low earth orbit scanning or staring sensor suites, and are based on data-driven processing that adapts to real-world clutter backgrounds, including celestial, earth limb, or terrestrial clutter. In many scenarios of interest, e.g., for highly elliptic and, especially, low earth orbits, the resulting clutter is highly nonstationary, providing a significant challenge for clutter suppression to or below sensor noise levels, which is essential for dim object detection and tracking. We demonstrate the success of the developed algorithms using semi-synthetic and real data. In particular, our algorithms are shown to be capable of detecting and tracking point objects with signal-to-clutter levels down to 1/1000 and signal-to-noise levels down to 1/4.

Real-time estimation of ionospheric delay using GPS measurements

NASA Astrophysics Data System (ADS)

Lin, Lao-Sheng

1997-12-01

When radio waves such as the GPS signals propagate through the ionosphere, they experience an extra time delay. The ionospheric delay can be eliminated (to the first order) through a linear combination of L1 and L2 observations from dual-frequency GPS receivers. Taking advantage of this dispersive principle, one or more dual- frequency GPS receivers can be used to determine a model of the ionospheric delay across a region of interest and, if implemented in real-time, can support single-frequency GPS positioning and navigation applications. The research objectives of this thesis were: (1) to develop algorithms to obtain accurate absolute Total Electron Content (TEC) estimates from dual-frequency GPS observables, and (2) to develop an algorithm to improve the accuracy of real-time ionosphere modelling. In order to fulfil these objectives, four algorithms have been proposed in this thesis. A 'multi-day multipath template technique' is proposed to mitigate the pseudo-range multipath effects at static GPS reference stations. This technique is based on the assumption that the multipath disturbance at a static station will be constant if the physical environment remains unchanged from day to day. The multipath template, either single-day or multi-day, can be generated from the previous days' GPS data. A 'real-time failure detection and repair algorithm' is proposed to detect and repair the GPS carrier phase 'failures', such as the occurrence of cycle slips. The proposed algorithm uses two procedures: (1) application of a statistical test on the state difference estimated from robust and conventional Kalman filters in order to detect and identify the carrier phase failure, and (2) application of a Kalman filter algorithm to repair the 'identified carrier phase failure'. A 'L1/L2 differential delay estimation algorithm' is proposed to estimate GPS satellite transmitter and receiver L1/L2 differential delays. This algorithm, based on the single-site modelling technique, is able to estimate the sum of the satellite and receiver L1/L2 differential delay for each tracked GPS satellite. A 'UNSW grid-based algorithm' is proposed to improve the accuracy of real-time ionosphere modelling. The proposed algorithm is similar to the conventional grid-based algorithm. However, two modifications were made to the algorithm: (1) an 'exponential function' is adopted as the weighting function, and (2) the 'grid-based ionosphere model' estimated from the previous day is used to predict the ionospheric delay ratios between the grid point and reference points. (Abstract shortened by UMI.)

RAPTOR-scan: Identifying and Tracking Objects Through Thousands of Sky Images

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

Davidoff, Sherri; Wozniak, Przemyslaw

2004-09-28

The RAPTOR-scan system mines data for optical transients associated with gamma-ray bursts and is used to create a catalog for the RAPTOR telescope system. RAPTOR-scan can detect and track individual astronomical objects across data sets containing millions of observed points.Accurately identifying a real object over many optical images (clustering the individual appearances) is necessary in order to analyze object light curves. To achieve this, RAPTOR telescope observations are sent in real time to a database. Each morning, a program based on the DBSCAN algorithm clusters the observations and labels each one with an object identifier. Once clustering is complete, themore » analysis program may be used to query the database and produce light curves, maps of the sky field, or other informative displays.Although RAPTOR-scan was designed for the RAPTOR optical telescope system, it is a general tool designed to identify objects in a collection of astronomical data and facilitate quick data analysis. RAPTOR-scan will be released as free software under the GNU General Public License.« less

A New Moving Object Detection Method Based on Frame-difference and Background Subtraction

NASA Astrophysics Data System (ADS)

Guo, Jiajia; Wang, Junping; Bai, Ruixue; Zhang, Yao; Li, Yong

2017-09-01

Although many methods of moving object detection have been proposed, moving object extraction is still the core in video surveillance. However, with the complex scene in real world, false detection, missed detection and deficiencies resulting from cavities inside the body still exist. In order to solve the problem of incomplete detection for moving objects, a new moving object detection method combined an improved frame-difference and Gaussian mixture background subtraction is proposed in this paper. To make the moving object detection more complete and accurate, the image repair and morphological processing techniques which are spatial compensations are applied in the proposed method. Experimental results show that our method can effectively eliminate ghosts and noise and fill the cavities of the moving object. Compared to other four moving object detection methods which are GMM, VIBE, frame-difference and a literature's method, the proposed method improve the efficiency and accuracy of the detection.

Performances of the New Real Time Tsunami Detection Algorithm applied to tide gauges data

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Morucci, S.

2017-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection (TDA) based on the real-time tide removal and real-time band-pass filtering of seabed pressure time series acquired by Bottom Pressure Recorders. The TDA algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability with respect to the most widely used tsunami detection algorithm, while containing the computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. In this work we present the performance of the TDA algorithm applied to tide gauge data. We have adapted the new tsunami detection algorithm and the Monte Carlo test methodology to tide gauges. Sea level data acquired by coastal tide gauges in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event generated by Tohoku earthquake on March 11th 2011, using data recorded by several tide gauges scattered all over the Pacific area.

Multi-resolution model-based traffic sign detection and tracking

NASA Astrophysics Data System (ADS)

Marinas, Javier; Salgado, Luis; Camplani, Massimo

2012-06-01

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.

Detection of Food Allergens by Taqman Real-Time PCR Methodology.

PubMed

García, Aina; Madrid, Raquel; García, Teresa; Martín, Rosario; González, Isabel

2017-01-01

Real-time PCR (polymerase chain reaction) has shown to be a very effective technology for the detection of food allergens. The protocol described herein consists on a real-time PCR assay targeting the plant ITS (Internal Transcribed Spacer) region, using species-specific primers and hydrolysis probes (Taqman) dual labeled with a reporter fluorophore at the 5' end (6-carboxyfluorescein, FAM) and a quencher fluorophore at the 3' end (Blackberry, BBQ). The species-specific real-time PCR systems (primers/probe) described in this work allowed the detection of different nuts (peanut, hazelnut, pistachio, almond, cashew, macadamia, walnut and pecan), common allergens present in commercial food products, with a detection limit of 0.1 mg/kg.

Using Machine Learning for Advanced Anomaly Detection and Classification

NASA Astrophysics Data System (ADS)

Lane, B.; Poole, M.; Camp, M.; Murray-Krezan, J.

2016-09-01

Machine Learning (ML) techniques have successfully been used in a wide variety of applications to automatically detect and potentially classify changes in activity, or a series of activities by utilizing large amounts data, sometimes even seemingly-unrelated data. The amount of data being collected, processed, and stored in the Space Situational Awareness (SSA) domain has grown at an exponential rate and is now better suited for ML. This paper describes development of advanced algorithms to deliver significant improvements in characterization of deep space objects and indication and warning (I&W) using a global network of telescopes that are collecting photometric data on a multitude of space-based objects. The Phase II Air Force Research Laboratory (AFRL) Small Business Innovative Research (SBIR) project Autonomous Characterization Algorithms for Change Detection and Characterization (ACDC), contracted to ExoAnalytic Solutions Inc. is providing the ability to detect and identify photometric signature changes due to potential space object changes (e.g. stability, tumble rate, aspect ratio), and correlate observed changes to potential behavioral changes using a variety of techniques, including supervised learning. Furthermore, these algorithms run in real-time on data being collected and processed by the ExoAnalytic Space Operations Center (EspOC), providing timely alerts and warnings while dynamically creating collection requirements to the EspOC for the algorithms that generate higher fidelity I&W. This paper will discuss the recently implemented ACDC algorithms, including the general design approach and results to date. The usage of supervised algorithms, such as Support Vector Machines, Neural Networks, k-Nearest Neighbors, etc., and unsupervised algorithms, for example k-means, Principle Component Analysis, Hierarchical Clustering, etc., and the implementations of these algorithms is explored. Results of applying these algorithms to EspOC data both in an off-line "pattern of life" analysis as well as using the algorithms on-line in real-time, meaning as data is collected, will be presented. Finally, future work in applying ML for SSA will be discussed.

Visible spectrum-based non-contact HRV and dPTT for stress detection

NASA Astrophysics Data System (ADS)

Kaur, Balvinder; Hutchinson, J. Andrew; Ikonomidou, Vasiliki N.

2017-05-01

Stress is a major health concern that not only compromises our quality of life, but also affects our physical health and well-being. Despite its importance, our ability to objectively detect and quantify it in a real-time, non-invasive manner is very limited. This capability would have a wide variety of medical, military, and security applications. We have developed a pipeline of image and signal processing algorithms to make such a system practical, which includes remote cardiac pulse detection based on visible spectrum videos and physiological stress detection based on the variability in the remotely detected cardiac signals. First, to determine a reliable cardiac pulse, principal component analysis (PCA) was applied for noise reduction and independent component analysis (ICA) was applied for source selection. To determine accurate cardiac timing for heart rate variability (HRV) analysis, a blind source separation method based least squares (LS) estimate was used to determine signal peaks that were closely related to R-peaks of the electrocardiogram (ECG) signal. A new metric, differential pulse transit time (dPTT), defined as the difference in arrival time of the remotely acquired cardiac signal at two separate distal locations, was derived. It was demonstrated that the remotely acquired metrics, HRV and dPTT, have potential for remote stress detection. The developed algorithms were tested against human subject data collected under two physiological conditions using the modified Trier Social Stress Test (TSST) and the Affective Stress Response Test (ASRT). This research provides evidence that the variability in remotely-acquired blood wave (BW) signals can be used for stress (high and mild) detection, and as a guide for further development of a real-time remote stress detection system based on remote HRV and dPTT.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands.

PubMed

Mateo, Carlos M; Gil, Pablo; Torres, Fernando

2016-05-05

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object's surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand's fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

NASA Astrophysics Data System (ADS)

Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas

2016-04-01

The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten, Austria) and an agricultural maize crop stand (Heidelberg, Germany). This research demonstrates the potential and also limitations of fully automated, near real-time 4D LiDAR monitoring in geosciences.

Compressed multi-block local binary pattern for object tracking

NASA Astrophysics Data System (ADS)

Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

2018-04-01

Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

Effect of Sequence Polymorphisms on Performance of Two Real-Time PCR Assays for Detection of Herpes Simplex Virus

PubMed Central

Stevenson, Jeffery; Hymas, Weston; Hillyard, David

2005-01-01

Herpes simplex virus (HSV) is the most common cause of acquired, sporadic encephalitis in the United States. PCR identification of HSV in spinal fluid has become the diagnostic gold standard due to its sensitivity and potential for speed, replacing other methods such as culture. We developed a real-time PCR assay to detect HSV, using a new type of hybridization probe, the Eclipse probe. In this study, we ran 323 samples (171 positives and 152 negatives) with the Eclipse real-time PCR assay and compared these results with another PCR assay using gel detection. The real-time assay agreed with our reference method for 319 out of the 323 samples tested (99%). Using two different real-time PCR platforms, we discovered that SNPs within the amplicon's probe binding region that are used to distinguish HSV-1 from HSV-2 can decrease assay sensitivity. This problem is potentially a general one for assays using fluorescent probes to detect target amplification in a real-time format. While real-time PCR can be a powerful tool in the field of infectious disease, careful sequence evaluation and clinical validation are essential in creating an effective assay. PMID:15872272

Real-time implementation of logo detection on open source BeagleBoard

NASA Astrophysics Data System (ADS)

George, M.; Kehtarnavaz, N.; Estevez, L.

2011-03-01

This paper presents the real-time implementation of our previously developed logo detection and tracking algorithm on the open source BeagleBoard mobile platform. This platform has an OMAP processor that incorporates an ARM Cortex processor. The algorithm combines Scale Invariant Feature Transform (SIFT) with k-means clustering, online color calibration and moment invariants to robustly detect and track logos in video. Various optimization steps that are carried out to allow the real-time execution of the algorithm on BeagleBoard are discussed. The results obtained are compared to the PC real-time implementation results.

A Novel High Throughput Assay for Anthelmintic Drug Screening and Resistance Diagnosis by Real-Time Monitoring of Parasite Motility

PubMed Central

Smout, Michael J.; Kotze, Andrew C.; McCarthy, James S.; Loukas, Alex

2010-01-01

Background Helminth parasites cause untold morbidity and mortality to billions of people and livestock. Anthelmintic drugs are available but resistance is a problem in livestock parasites, and is a looming threat for human helminths. Testing the efficacy of available anthelmintic drugs and development of new drugs is hindered by the lack of objective high-throughput screening methods. Currently, drug effect is assessed by observing motility or development of parasites using laborious, subjective, low-throughput methods. Methodology/Principal Findings Here we describe a novel application for a real-time cell monitoring device (xCELLigence) that can simply and objectively assess anthelmintic effects by measuring parasite motility in real time in a fully automated high-throughput fashion. We quantitatively assessed motility and determined real time IC50 values of different anthelmintic drugs against several developmental stages of major helminth pathogens of humans and livestock, including larval Haemonchus contortus and Strongyloides ratti, and adult hookworms and blood flukes. The assay enabled quantification of the onset of egg hatching in real time, and the impact of drugs on hatch rate, as well as discriminating between the effects of drugs on motility of drug-susceptible and –resistant isolates of H. contortus. Conclusions/Significance Our findings indicate that this technique will be suitable for discovery and development of new anthelmintic drugs as well as for detection of phenotypic resistance to existing drugs for the majority of helminths and other pathogens where motility is a measure of pathogen viability. The method is also amenable to use for other purposes where motility is assessed, such as gene silencing or antibody-mediated killing. PMID:21103363

Congestion detection of pedestrians using the velocity entropy: A case study of Love Parade 2010 disaster

NASA Astrophysics Data System (ADS)

Huang, Lida; Chen, Tao; Wang, Yan; Yuan, Hongyong

2015-12-01

Gatherings of large human crowds often result in crowd disasters such as the Love Parade Disaster in Duisburg, Germany on July 24, 2010. To avoid these tragedies, video surveillance and early warning are becoming more and more significant. In this paper, the velocity entropy is first defined as the criterion for congestion detection, which represents the motion magnitude distribution and the motion direction distribution simultaneously. Then the detection method is verified by the simulation data based on AnyLogic software. To test the generalization performance of this method, video recordings of a real-world case, the Love Parade disaster, are also used in the experiments. The velocity histograms of the foreground object in the videos are extracted by the Gaussian Mixture Model (GMM) and optical flow computation. With a sequential change-point detection algorithm, the velocity entropy can be applied to detect congestions of the Love Parade festival. It turned out that without recognizing and tracking individual pedestrian, our method can detect abnormal crowd behaviors in real-time.

[Multiplex real-time PCR method for rapid detection of Marburg virus and Ebola virus].

PubMed

Yang, Yu; Bai, Lin; Hu, Kong-Xin; Yang, Zhi-Hong; Hu, Jian-Ping; Wang, Jing

2012-08-01

Marburg virus and Ebola virus are acute infections with high case fatality rates. A rapid, sensitive detection method was established to detect Marburg virus and Ebola virus by multiplex real-time fluorescence quantitative PCR. Designing primers and Taqman probes from highly conserved sequences of Marburg virus and Ebola virus through whole genome sequences alignment, Taqman probes labeled by FAM and Texas Red, the sensitivity of the multiplex real-time quantitative PCR assay was optimized by evaluating the different concentrations of primers and Probes. We have developed a real-time PCR method with the sensitivity of 30.5 copies/microl for Marburg virus positive plasmid and 28.6 copies/microl for Ebola virus positive plasmids, Japanese encephalitis virus, Yellow fever virus, Dengue virus were using to examine the specificity. The Multiplex real-time PCR assays provide a sensitive, reliable and efficient method to detect Marburg virus and Ebola virus simultaneously.

Real-Time PCR in Clinical Microbiology: Applications for Routine Laboratory Testing

PubMed Central

Espy, M. J.; Uhl, J. R.; Sloan, L. M.; Buckwalter, S. P.; Jones, M. F.; Vetter, E. A.; Yao, J. D. C.; Wengenack, N. L.; Rosenblatt, J. E.; Cockerill, F. R.; Smith, T. F.

2006-01-01

Real-time PCR has revolutionized the way clinical microbiology laboratories diagnose many human microbial infections. This testing method combines PCR chemistry with fluorescent probe detection of amplified product in the same reaction vessel. In general, both PCR and amplified product detection are completed in an hour or less, which is considerably faster than conventional PCR detection methods. Real-time PCR assays provide sensitivity and specificity equivalent to that of conventional PCR combined with Southern blot analysis, and since amplification and detection steps are performed in the same closed vessel, the risk of releasing amplified nucleic acids into the environment is negligible. The combination of excellent sensitivity and specificity, low contamination risk, and speed has made real-time PCR technology an appealing alternative to culture- or immunoassay-based testing methods for diagnosing many infectious diseases. This review focuses on the application of real-time PCR in the clinical microbiology laboratory. PMID:16418529

Application test of a Detection Method for the Enclosed Turbine Runner Chamber

NASA Astrophysics Data System (ADS)

Liu, Yunlong; Shen, Dingjie; Xie, Yi; Yang, Xiangwei; Long, Yi; Li, Wenbo

2017-06-01

At present, for the existing problems of the testing methods for the key hidden metal components of the turbine runner chamber, such as the poor reliability, the inaccurate locating and the larger detection blind spots of the detection device, under the downtime without opening the cover of the hydropower turbine runner chamber, an automatic detection method based on real-time image acquisition and simulation comparison techniques was proposed. By using the permanent magnet wheel, the magnetic crawler which carry the real-time image acquisition device, could complete the crawling work on the inner surface of the enclosed chamber. Then the image acquisition device completed the real-time collection of the scene image of the enclosed chamber. According to the obtained location by using the positioning auxiliary device, the position of the real-time detection image in a virtual 3D model was calibrated. Through comparing of the real-time detection images and the computer simulation images, the defects or foreign matter fall into could be accurately positioning, so as to repair and clean up conveniently.

Detection of Alicyclobacillus spp. in Fruit Juice by Combination of Immunomagnetic Separation and a SYBR Green I Real-Time PCR Assay

PubMed Central

Yuan, Yahong; Liu, Bin; Wang, Ling; Yue, Tianli

2015-01-01

An approach based on immunomagnetic separation (IMS) and SYBR Green I real-time PCR (real-time PCR) with species-specific primers and melting curve analysis was proposed as a rapid and effective method for detecting Alicyclobacillus spp. in fruit juices. Specific primers targeting the 16S rDNA sequences of Alicyclobacillus spp. were designed and then confirmed by the amplification of DNA extracted from standard strains and isolates. Spiked samples containing known amounts of target bacteria were used to obtain standard curves; the correlation coefficient was greater than 0.986 and the real-time PCR amplification efficiencies were 98.9%- 101.8%. The detection limit of the testing system was 2.8×101 CFU/mL. The coefficient of variation for intra-assay and inter-assay variability were all within the acceptable limit of 5%. Besides, the performance of the IMS-real-time PCR assay was further investigated by detecting naturally contaminated kiwi fruit juice; the sensitivity, specificity and accuracy were 91.7%, 95.9% and 95.3%, respectively. The established IMS-real-time PCR procedure provides a new method for identification and quantitative detection of Alicyclobacillus spp. in fruit juice. PMID:26488469

Automatic guidance of attention during real-world visual search.

PubMed

Seidl-Rathkopf, Katharina N; Turk-Browne, Nicholas B; Kastner, Sabine

2015-08-01

Looking for objects in cluttered natural environments is a frequent task in everyday life. This process can be difficult, because the features, locations, and times of appearance of relevant objects often are not known in advance. Thus, a mechanism by which attention is automatically biased toward information that is potentially relevant may be helpful. We tested for such a mechanism across five experiments by engaging participants in real-world visual search and then assessing attentional capture for information that was related to the search set but was otherwise irrelevant. Isolated objects captured attention while preparing to search for objects from the same category embedded in a scene, as revealed by lower detection performance (Experiment 1A). This capture effect was driven by a central processing bottleneck rather than the withdrawal of spatial attention (Experiment 1B), occurred automatically even in a secondary task (Experiment 2A), and reflected enhancement of matching information rather than suppression of nonmatching information (Experiment 2B). Finally, attentional capture extended to objects that were semantically associated with the target category (Experiment 3). We conclude that attention is efficiently drawn towards a wide range of information that may be relevant for an upcoming real-world visual search. This mechanism may be adaptive, allowing us to find information useful for our behavioral goals in the face of uncertainty.

A video-based real-time adaptive vehicle-counting system for urban roads.

PubMed

Liu, Fei; Zeng, Zhiyuan; Jiang, Rong

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

A video-based real-time adaptive vehicle-counting system for urban roads

PubMed Central

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984

Real-Time Detection of Sporadic Meteors in the Intensified TV Imaging Systems.

PubMed

Vítek, Stanislav; Nasyrova, Maria

2017-12-29

The automatic observation of the night sky through wide-angle video systems with the aim of detecting meteor and fireballs is currently among routine astronomical observations. The observation is usually done in multi-station or network mode, so it is possible to estimate the direction and the speed of the body flight. The high velocity of the meteorite flying through the atmosphere determines the important features of the camera systems, namely the high frame rate. Thanks to high frame rates, such imaging systems produce a large amount of data, of which only a small fragment has scientific potential. This paper focuses on methods for the real-time detection of fast moving objects in the video sequences recorded by intensified TV systems with frame rates of about 60 frames per second. The goal of our effort is to remove all unnecessary data during the daytime and make free hard-drive capacity for the next observation. The processing of data from the MAIA (Meteor Automatic Imager and Analyzer) system is demonstrated in the paper.

Automated segmentation and feature extraction of product inspection items

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1997-03-01

X-ray film and linescan images of pistachio nuts on conveyor trays for product inspection are considered. The final objective is the categorization of pistachios into good, blemished and infested nuts. A crucial step before classification is the separation of touching products and the extraction of features essential for classification. This paper addresses new detection and segmentation algorithms to isolate touching or overlapping items. These algorithms employ a new filter, a new watershed algorithm, and morphological processing to produce nutmeat-only images. Tests on a large database of x-ray film and real-time x-ray linescan images of around 2900 small, medium and large nuts showed excellent segmentation results. A new technique to detect and segment dark regions in nutmeat images is also presented and tested on approximately 300 x-ray film and approximately 300 real-time linescan x-ray images with 95-97 percent detection and correct segmentation. New algorithms are described that determine nutmeat fill ratio and locate splits in nutmeat. The techniques formulated in this paper are of general use in many different product inspection and computer vision problems.

Real-Time Detection of Sporadic Meteors in the Intensified TV Imaging Systems

PubMed Central

2017-01-01

The automatic observation of the night sky through wide-angle video systems with the aim of detecting meteor and fireballs is currently among routine astronomical observations. The observation is usually done in multi-station or network mode, so it is possible to estimate the direction and the speed of the body flight. The high velocity of the meteorite flying through the atmosphere determines the important features of the camera systems, namely the high frame rate. Thanks to high frame rates, such imaging systems produce a large amount of data, of which only a small fragment has scientific potential. This paper focuses on methods for the real-time detection of fast moving objects in the video sequences recorded by intensified TV systems with frame rates of about 60 frames per second. The goal of our effort is to remove all unnecessary data during the daytime and make free hard-drive capacity for the next observation. The processing of data from the MAIA (Meteor Automatic Imager and Analyzer) system is demonstrated in the paper. PMID:29286294

ANALYSIS OF ENTEROCOCCUS FAECALIS IN SAMPLES FROM TURKISH PATIENTS WITH PRIMARY ENDODONTIC INFECTIONS AND FAILED ENDODONTIC TREATMENT BY REAL-TIME PCR SYBR GREEN METHOD

PubMed Central

Ozbek, Selcuk M.; Ozbek, Ahmet; Erdogan, Aziz S.

2009-01-01

Objective: The aims of this study were to investigate the presence of Enterococcus faecalis in primary endodontic infections and failed endodontic treatments using real-time PCR and to determine the statistical importance of the presence of E. faecalis in a Turkish population with endodontic infections. Material and Methods: E. faecalis was investigated from 79 microbial samples collected from patients who were treated at the Endodontic Clinic of the Dental School of Atatürk University (Erzurum, Turkey). Microbial samples were taken from 43 patients (Group 1) with failed endodontic treatments and 36 patients (Group 2) with chronic apical periodontitis (primary endodontic infections). DNA was extracted from the samples by using a QIAamp® DNA mini-kit and analyzed with real-time PCR SYBR Green. Results: E. faecalis was detected in 41 out of 79 patients, suggesting that it exists in not less than 61% of all endodontic infections when the proportion test (z= -1.645,

A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers

PubMed Central

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Fan, Lihong; Wang, Xiaolei

2017-01-01

The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services. PMID:29186058

A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers.

PubMed

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Fan, Lihong; Wang, Xiaolei

2017-11-29

The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services.

Near real-time, on-the-move software PED using VPEF

NASA Astrophysics Data System (ADS)

Green, Kevin; Geyer, Chris; Burnette, Chris; Agarwal, Sanjeev; Swett, Bruce; Phan, Chung; Deterline, Diane

2015-05-01

The scope of the Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System (MOVERS) development effort, managed by the Night Vision and Electronic Sensors Directorate (NVESD), is to develop, integrate, and demonstrate new sensor technologies and algorithms that improve improvised device/mine detection using efficient and effective exploitation and fusion of sensor data and target cues from existing and future Route Clearance Package (RCP) sensor systems. Unfortunately, the majority of forward looking Full Motion Video (FMV) and computer vision processing, exploitation, and dissemination (PED) algorithms are often developed using proprietary, incompatible software. This makes the insertion of new algorithms difficult due to the lack of standardized processing chains. In order to overcome these limitations, EOIR developed the Government off-the-shelf (GOTS) Video Processing and Exploitation Framework (VPEF) to be able to provide standardized interfaces (e.g., input/output video formats, sensor metadata, and detected objects) for exploitation software and to rapidly integrate and test computer vision algorithms. EOIR developed a vehicle-based computing framework within the MOVERS and integrated it with VPEF. VPEF was further enhanced for automated processing, detection, and publishing of detections in near real-time, thus improving the efficiency and effectiveness of RCP sensor systems.

Development of a smartphone application to measure physical activity using sensor-assisted self-report.

PubMed

Dunton, Genevieve Fridlund; Dzubur, Eldin; Kawabata, Keito; Yanez, Brenda; Bo, Bin; Intille, Stephen

2014-01-01

Despite the known advantages of objective physical activity monitors (e.g., accelerometers), these devices have high rates of non-wear, which leads to missing data. Objective activity monitors are also unable to capture valuable contextual information about behavior. Adolescents recruited into physical activity surveillance and intervention studies will increasingly have smartphones, which are miniature computers with built-in motion sensors. This paper describes the design and development of a smartphone application ("app") called Mobile Teen that combines objective and self-report assessment strategies through (1) sensor-informed context-sensitive ecological momentary assessment (CS-EMA) and (2) sensor-assisted end-of-day recall. The Mobile Teen app uses the mobile phone's built-in motion sensor to automatically detect likely bouts of phone non-wear, sedentary behavior, and physical activity. The app then uses transitions between these inferred states to trigger CS-EMA self-report surveys measuring the type, purpose, and context of activity in real-time. The end of the day recall component of the Mobile Teen app allows users to interactively review and label their own physical activity data each evening using visual cues from automatically detected major activity transitions from the phone's built-in motion sensors. Major activity transitions are identified by the app, which cues the user to label that "chunk," or period, of time using activity categories. Sensor-driven CS-EMA and end-of-day recall smartphone apps can be used to augment physical activity data collected by objective activity monitors, filling in gaps during non-wear bouts and providing additional real-time data on environmental, social, and emotional correlates of behavior. Smartphone apps such as these have potential for affordable deployment in large-scale epidemiological and intervention studies.

Development of a Smartphone Application to Measure Physical Activity Using Sensor-Assisted Self-Report

PubMed Central

Dunton, Genevieve Fridlund; Dzubur, Eldin; Kawabata, Keito; Yanez, Brenda; Bo, Bin; Intille, Stephen

2013-01-01

Introduction: Despite the known advantages of objective physical activity monitors (e.g., accelerometers), these devices have high rates of non-wear, which leads to missing data. Objective activity monitors are also unable to capture valuable contextual information about behavior. Adolescents recruited into physical activity surveillance and intervention studies will increasingly have smartphones, which are miniature computers with built-in motion sensors. Methods: This paper describes the design and development of a smartphone application (“app”) called Mobile Teen that combines objective and self-report assessment strategies through (1) sensor-informed context-sensitive ecological momentary assessment (CS-EMA) and (2) sensor-assisted end-of-day recall. Results: The Mobile Teen app uses the mobile phone’s built-in motion sensor to automatically detect likely bouts of phone non-wear, sedentary behavior, and physical activity. The app then uses transitions between these inferred states to trigger CS-EMA self-report surveys measuring the type, purpose, and context of activity in real-time. The end of the day recall component of the Mobile Teen app allows users to interactively review and label their own physical activity data each evening using visual cues from automatically detected major activity transitions from the phone’s built-in motion sensors. Major activity transitions are identified by the app, which cues the user to label that “chunk,” or period, of time using activity categories. Conclusion: Sensor-driven CS-EMA and end-of-day recall smartphone apps can be used to augment physical activity data collected by objective activity monitors, filling in gaps during non-wear bouts and providing additional real-time data on environmental, social, and emotional correlates of behavior. Smartphone apps such as these have potential for affordable deployment in large-scale epidemiological and intervention studies. PMID:24616888

Real-time computer treatment of THz passive device images with the high image quality

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2012-06-01

We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.

Automatic Reacquisition of Satellite Positions by Detecting Their Expected Streaks in Astronomical Images

NASA Astrophysics Data System (ADS)

Levesque, M.

Artificial satellites, and particularly space junk, drift continuously from their known orbits. In the surveillance-of-space context, they must be observed frequently to ensure that the corresponding orbital parameter database entries are up-to-date. Autonomous ground-based optical systems are periodically tasked to observe these objects, calculate the difference between their predicted and real positions and update object orbital parameters. The real satellite positions are provided by the detection of the satellite streaks in the astronomical images specifically acquired for this purpose. This paper presents the image processing techniques used to detect and extract the satellite positions. The methodology includes several processing steps including: image background estimation and removal, star detection and removal, an iterative matched filter for streak detection, and finally false alarm rejection algorithms. This detection methodology is able to detect very faint objects. Simulated data were used to evaluate the methodology's performance and determine the sensitivity limits where the algorithm can perform detection without false alarm, which is essential to avoid corruption of the orbital parameter database.

[The establishment of a novel method of nano-immunomagnetic separation and Real-time PCR for detecting Vibrio cholerae from seafood].

PubMed

Cheng, Jinxia; Zeng, Jing; Liu, Li; Wei, Haiyan; Zhao, Xiaojuan; Zhang, Ximeng; Zhang, Lei; Zhang, Haiyu

2014-02-01

A novel method of Nano-Immunomagnetic Separation (Nano-IMS) plus Real-time PCR was established for detecting Vibrio cholerae. The Nano-Immunomagnetic Beads were created by using the monoclonal antibody of Vibrio cholerae, which was named Nano-IMB-Vc. Nano-IMB-Vc has specific adsorption of Vibrio cholerae, combined with Real-time PCR technology, a method for rapid detection of Vibrio cholerae was established. The capture specificity of Nano-IMB-Vc was tested by using 15 bacteria strains. The specificity of Real-time PCR method was tested by using 102 targets and 101 non-targets bacteria strains. The sensitivity of Nano-IMS plus Real-time PCR were tested in pure culture and in artificial samples and compared with NMKL No.156. The capture ratio of Nano-IMB-Vc was reached 70.2% at the level of 10(3) CFU/ml. In pure culture, the sensitivity of Nano-IMS plus Real-time PCR was reached at 5.4×10(2) CFU/ml. The specific of Real-time PCR method was tested by using 102 targets and 101 non-targets bacteria. The results showed that 102 strains of Vibrio cholerae test results were all positive, and the rest of the 101 strains of non-target bacteria test results were negative. No cross-reaction was founded. Add 1 CFU vibrio cholerae per 25 g sample, it could be detect with Nano-IMS plus Real-time PCR method after 8 hours enrichment. The Nano-IMS plus Real-time PCR method of Vibrio cholerae established in this study has good specificity and sensitivity, which could be applied to the rapid detection of Vibrio cholerae.

Deep Learning for real-time gravitational wave detection and parameter estimation: Results with Advanced LIGO data

NASA Astrophysics Data System (ADS)

George, Daniel; Huerta, E. A.

2018-03-01

The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of multimessenger astrophysics. To enhance the scope of this emergent field of science, we pioneered the use of deep learning with convolutional neural networks, that take time-series inputs, for rapid detection and characterization of gravitational wave signals. This approach, Deep Filtering, was initially demonstrated using simulated LIGO noise. In this article, we present the extension of Deep Filtering using real data from LIGO, for both detection and parameter estimation of gravitational waves from binary black hole mergers using continuous data streams from multiple LIGO detectors. We demonstrate for the first time that machine learning can detect and estimate the true parameters of real events observed by LIGO. Our results show that Deep Filtering achieves similar sensitivities and lower errors compared to matched-filtering while being far more computationally efficient and more resilient to glitches, allowing real-time processing of weak time-series signals in non-stationary non-Gaussian noise with minimal resources, and also enables the detection of new classes of gravitational wave sources that may go unnoticed with existing detection algorithms. This unified framework for data analysis is ideally suited to enable coincident detection campaigns of gravitational waves and their multimessenger counterparts in real-time.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

PubMed Central

Mateo, Carlos M.; Gil, Pablo; Torres, Fernando

2016-01-01

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID:27164102

A novel quantitative real-time polymerase chain reaction method for detecting toxigenic Pasteurella multocida in nasal swabs from swine.

PubMed

Scherrer, Simone; Frei, Daniel; Wittenbrink, Max Michael

2016-12-01

Progressive atrophic rhinitis (PAR) in pigs is caused by toxigenic Pasteurella multocida. In Switzerland, PAR is monitored by selective culture of nasal swabs and subsequent polymerase chain reaction (PCR) screening of bacterial colonies for the P. multocida toxA gene. A panel of 203 nasal swabs from a recent PAR outbreak were used to evaluate a novel quantitative real-time PCR for toxigenic P. multocida in porcine nasal swabs. In comparison to the conventional PCR with a limit of detection of 100 genome equivalents per PCR reaction, the real-time PCR had a limit of detection of 10 genome equivalents. The real-time PCR detected toxA-positive P. multocida in 101 samples (49.8%), whereas the conventional PCR was less sensitive with 90 toxA-positive samples (44.3%). In comparison to the real-time PCR, 5.4% of the toxA-positive samples revealed unevaluable results by conventional PCR. The approach of culture-coupled toxA PCR for the monitoring of PAR in pigs is substantially improved by a novel quantitative real-time PCR.

Development of internally controlled duplex real-time NASBA diagnostics assays for the detection of microorganisms associated with bacterial meningitis.

PubMed

Clancy, Eoin; Coughlan, Helena; Higgins, Owen; Boo, Teck Wee; Cormican, Martin; Barrett, Louise; Smith, Terry J; Reddington, Kate; Barry, Thomas

2016-08-01

Three duplex molecular beacon based real-time Nucleic Acid Sequence Based Amplification (NASBA) assays have been designed and experimentally validated targeting RNA transcripts for the detection and identification of Haemophilus influenzae, Neisseria meningitidis and Streptococcus pneumoniae respectively. Each real-time NASBA diagnostics assay includes an endogenous non-competitive Internal Amplification Control (IAC) to amplify the splice variant 1 mRNA of the Homo sapiens TBP gene from human total RNA. All three duplex real-time NASBA diagnostics assays were determined to be 100% specific for the target species tested for. Also the Limits of Detection (LODs) for the H. influenzae, N. meningitidis and S. pneumoniae duplex real-time NASBA assays were 55.36, 0.99, and 57.24 Cell Equivalents (CE) respectively. These robust duplex real-time NASBA diagnostics assays have the potential to be used in a clinical setting for the rapid (<60min) specific detection and identification of the most prominent microorganisms associated with bacterial meningitis in humans. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time color measurement using active illuminant

NASA Astrophysics Data System (ADS)

Tominaga, Shoji; Horiuchi, Takahiko; Yoshimura, Akihiko

2010-01-01

This paper proposes a method for real-time color measurement using active illuminant. A synchronous measurement system is constructed by combining a high-speed active spectral light source and a high-speed monochrome camera. The light source is a programmable spectral source which is capable of emitting arbitrary spectrum in high speed. This system is the essential advantage of capturing spectral images without using filters in high frame rates. The new method of real-time colorimetry is different from the traditional method based on the colorimeter or the spectrometers. We project the color-matching functions onto an object surface as spectral illuminants. Then we can obtain the CIE-XYZ tristimulus values directly from the camera outputs at every point on the surface. We describe the principle of our colorimetric technique based on projection of the color-matching functions and the procedure for realizing a real-time measurement system of a moving object. In an experiment, we examine the performance of real-time color measurement for a static object and a moving object.

Machine-learning-based real-bogus system for the HSC-SSP moving object detection pipeline

NASA Astrophysics Data System (ADS)

Lin, Hsing-Wen; Chen, Ying-Tung; Wang, Jen-Hung; Wang, Shiang-Yu; Yoshida, Fumi; Ip, Wing-Huen; Miyazaki, Satoshi; Terai, Tsuyoshi

2018-01-01

Machine-learning techniques are widely applied in many modern optical sky surveys, e.g., Pan-STARRS1, PTF/iPTF, and the Subaru/Hyper Suprime-Cam survey, to reduce human intervention in data verification. In this study, we have established a machine-learning-based real-bogus system to reject false detections in the Subaru/Hyper-Suprime-Cam Strategic Survey Program (HSC-SSP) source catalog. Therefore, the HSC-SSP moving object detection pipeline can operate more effectively due to the reduction of false positives. To train the real-bogus system, we use stationary sources as the real training set and "flagged" data as the bogus set. The training set contains 47 features, most of which are photometric measurements and shape moments generated from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ˜96% with a false positive rate (fpr) ˜1% or tpr ˜99% at fpr ˜5%. Therefore, we conclude that stationary sources are decent real training samples, and using photometry measurements and shape moments can reject false positives effectively.

Detection of Listeria monocytogenes in ready-to-eat food by Step One real-time polymerase chain reaction.

PubMed

Pochop, Jaroslav; Kačániová, Miroslava; Hleba, Lukáš; Lopasovský, L'ubomír; Bobková, Alica; Zeleňáková, Lucia; Stričík, Michal

2012-01-01

The aim of this study was to follow contamination of ready-to-eat food with Listeria monocytogenes by using the Step One real time polymerase chain reaction (PCR). We used the PrepSEQ Rapid Spin Sample Preparation Kit for isolation of DNA and MicroSEQ® Listeria monocytogenes Detection Kit for the real-time PCR performance. In 30 samples of ready-to-eat milk and meat products without incubation we detected strains of Listeria monocytogenes in five samples (swabs). Internal positive control (IPC) was positive in all samples. Our results indicated that the real-time PCR assay developed in this study could sensitively detect Listeria monocytogenes in ready-to-eat food without incubation.

A new real-time tsunami detection algorithm

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Pignagnoli, L.

2016-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection based on the real-time tide removal and real-time band-pass filtering of sea-bed pressure recordings. The algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability, at low computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. Pressure data sets acquired by Bottom Pressure Recorders in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event which occurred at Haida Gwaii on October 28th, 2012 using data recorded by the Bullseye underwater node of Ocean Networks Canada. The algorithm successfully ran for test purpose in year-long missions onboard the GEOSTAR stand-alone multidisciplinary abyssal observatory, deployed in the Gulf of Cadiz during the EC project NEAREST and on NEMO-SN1 cabled observatory deployed in the Western Ionian Sea, operational node of the European research infrastructure EMSO.

Automatic target recognition and detection in infrared imagery under cluttered background

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Koç, Aykut; Alatan, A. Aydın.

2017-10-01

Visual object classification has long been studied in visible spectrum by utilizing conventional cameras. Since the labeled images has recently increased in number, it is possible to train deep Convolutional Neural Networks (CNN) with significant amount of parameters. As the infrared (IR) sensor technology has been improved during the last two decades, labeled images extracted from IR sensors have been started to be used for object detection and recognition tasks. We address the problem of infrared object recognition and detection by exploiting 15K images from the real-field with long-wave and mid-wave IR sensors. For feature learning, a stacked denoising autoencoder is trained in this IR dataset. To recognize the objects, the trained stacked denoising autoencoder is fine-tuned according to the binary classification loss of the target object. Once the training is completed, the test samples are propagated over the network, and the probability of the test sample belonging to a class is computed. Moreover, the trained classifier is utilized in a detect-by-classification method, where the classification is performed in a set of candidate object boxes and the maximum confidence score in a particular location is accepted as the score of the detected object. To decrease the computational complexity, the detection step at every frame is avoided by running an efficient correlation filter based tracker. The detection part is performed when the tracker confidence is below a pre-defined threshold. The experiments conducted on the real field images demonstrate that the proposed detection and tracking framework presents satisfactory results for detecting tanks under cluttered background.

Faint Object Detection in Multi-Epoch Observations via Catalog Data Fusion

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

Budavári, Tamás; Szalay, Alexander S.; Loredo, Thomas J.

Astronomy in the time-domain era faces several new challenges. One of them is the efficient use of observations obtained at multiple epochs. The work presented here addresses faint object detection and describes an incremental strategy for separating real objects from artifacts in ongoing surveys. The idea is to produce low-threshold single-epoch catalogs and to accumulate information across epochs. This is in contrast to more conventional strategies based on co-added or stacked images. We adopt a Bayesian approach, addressing object detection by calculating the marginal likelihoods for hypotheses asserting that there is no object or one object in a small imagemore » patch containing at most one cataloged source at each epoch. The object-present hypothesis interprets the sources in a patch at different epochs as arising from a genuine object; the no-object hypothesis interprets candidate sources as spurious, arising from noise peaks. We study the detection probability for constant-flux objects in a Gaussian noise setting, comparing results based on single and stacked exposures to results based on a series of single-epoch catalog summaries. Our procedure amounts to generalized cross-matching: it is the product of a factor accounting for the matching of the estimated fluxes of the candidate sources and a factor accounting for the matching of their estimated directions. We find that probabilistic fusion of multi-epoch catalogs can detect sources with similar sensitivity and selectivity compared to stacking. The probabilistic cross-matching framework underlying our approach plays an important role in maintaining detection sensitivity and points toward generalizations that could accommodate variability and complex object structure.« less

Change Detection Algorithms for Surveillance in Visual IoT: A Comparative Study

NASA Astrophysics Data System (ADS)

Akram, Beenish Ayesha; Zafar, Amna; Akbar, Ali Hammad; Wajid, Bilal; Chaudhry, Shafique Ahmad

2018-01-01

The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule's Coefficient) and JC (Jaccard's Coefficient), execution time and memory consumption. Experimental results showed that Kapur's algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes.

Real-Time Polymerase Chain Reaction Detection of Angiostrongylus cantonensis DNA in Cerebrospinal Fluid from Patients with Eosinophilic Meningitis

PubMed Central

Qvarnstrom, Yvonne; Xayavong, Maniphet; da Silva, Ana Cristina Aramburu; Park, Sarah Y.; Whelen, A. Christian; Calimlim, Precilia S.; Sciulli, Rebecca H.; Honda, Stacey A. A.; Higa, Karen; Kitsutani, Paul; Chea, Nora; Heng, Seng; Johnson, Stuart; Graeff-Teixeira, Carlos; Fox, LeAnne M.; da Silva, Alexandre J.

2016-01-01

Angiostrongylus cantonensis is the most common infectious cause of eosinophilic meningitis. Timely diagnosis of these infections is difficult, partly because reliable laboratory diagnostic methods are unavailable. The aim of this study was to evaluate the usefulness of a real-time polymerase chain reaction (PCR) assay for the detection of A. cantonensis DNA in human cerebrospinal fluid (CSF) specimens. A total of 49 CSF specimens from 33 patients with eosinophilic meningitis were included: A. cantonensis DNA was detected in 32 CSF specimens, from 22 patients. Four patients had intermittently positive and negative real-time PCR results on subsequent samples, indicating that the level of A. cantonensis DNA present in CSF may fluctuate during the course of the illness. Immunodiagnosis and/or supplemental PCR testing supported the real-time PCR findings for 30 patients. On the basis of these observations, this real-time PCR assay can be useful to detect A. cantonensis in the CSF from patients with eosinophilic meningitis. PMID:26526920

On-Site Molecular Detection of Soil-Borne Phytopathogens Using a Portable Real-Time PCR System

PubMed Central

DeShields, Joseph B.; Bomberger, Rachel A.; Woodhall, James W.; Wheeler, David L.; Moroz, Natalia; Johnson, Dennis A.; Tanaka, Kiwamu

2018-01-01

On-site diagnosis of plant diseases can be a useful tool for growers for timely decisions enabling the earlier implementation of disease management strategies that reduce the impact of the disease. Presently in many diagnostic laboratories, the polymerase chain reaction (PCR), particularly real-time PCR, is considered the most sensitive and accurate method for plant pathogen detection. However, laboratory-based PCRs typically require expensive laboratory equipment and skilled personnel. In this study, soil-borne pathogens of potato are used to demonstrate the potential for on-site molecular detection. This was achieved using a rapid and simple protocol comprising of magnetic bead-based nucleic acid extraction, portable real-time PCR (fluorogenic probe-based assay). The portable real-time PCR approach compared favorably with a laboratory-based system, detecting as few as 100 copies of DNA from Spongospora subterranea. The portable real-time PCR method developed here can serve as an alternative to laboratory-based approaches and a useful on-site tool for pathogen diagnosis. PMID:29553557

Handheld hyperspectral imager for standoff detection of chemical and biological aerosols

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele; Jensen, James O.; McAnally, Gerard

2004-02-01

Pacific Advanced Technology has developed a small hand held imaging spectrometer, Sherlock, for gas leak and aerosol detection and imaging. The system is based on a patent technique that uses diffractive optics and image processing algorithms to detect spectral information about objects in the scene of the camera (IMSS Image Multi-spectral Sensing). This camera has been tested at Dugway Proving Ground and Dstl Porton Down facility looking at Chemical and Biological agent simulants. The camera has been used to investigate surfaces contaminated with chemical agent simulants. In addition to Chemical and Biological detection the camera has been used for environmental monitoring of green house gases and is currently undergoing extensive laboratory and field testing by the Gas Technology Institute, British Petroleum and Shell Oil for applications for gas leak detection and repair. The camera contains an embedded Power PC and a real time image processor for performing image processing algorithms to assist in the detection and identification of gas phase species in real time. In this paper we will present an over view of the technology and show how it has performed for different applications, such as gas leak detection, surface contamination, remote sensing and surveillance applications. In addition a sampling of the results form TRE field testing at Dugway in July of 2002 and Dstl at Porton Down in September of 2002 will be given.

Development of a real-time PCR assay with an internal amplification control for detection of Gram-negative histamine-producing bacteria in fish.

PubMed

Bjornsdottir-Butler, Kristin; Jones, Jessica L; Benner, Ronald; Burkhardt, William

2011-05-01

Prompt detection of bacteria that contribute to scombrotoxin (histamine) fish poisoning can aid in the detection of potentially toxic fish products and prevent the occurrence of illness. We report development of the first real-time PCR method for rapid detection of Gram-negative histamine-producing bacteria (HPB) in fish. The real-time PCR assay was 100% inclusive for detecting high-histamine producing isolates and did not detect any of the low- or non-histamine producing isolates. The efficiency of the assay with/without internal amplification control ranged from 96-104% and in the presence of background flora and inhibitory matrices was 92/100% and 73-96%, respectively. This assay was used to detect HPB from naturally contaminated yellowfin tuna, bluefish, and false albacore samples. Photobacterium damselae (8), Plesiomonas shigelloides (2), Shewanella sp. (1), and Morganella morganii (1) were subsequently isolated from the real-time PCR positive fish samples. These results indicate that the real-time PCR assay developed in this study is a rapid and sensitive method for detecting high-HPB. The assay may be adapted for quantification of HPB, either directly or with an MPN-PCR method. Copyright © 2010. Published by Elsevier Ltd.

Quantitative detection of the potato cyst nematode, Globodera pallida, and the beet cyst nematode, Heterodera schachtii, using Real-Time PCR with SYBR green I dye.

PubMed

Madani, Mehrdad; Subbotin, Sergei A; Moens, Maurice

2005-04-01

The potato cyst nematode Globodera pallida and the beet cyst nematode Heterodera schachtii are major nematode pests in world agriculture. Precise identification and knowledge about the number of nematodes in field soil are necessary to develop effective integrated pest control. Here we report the results of the Real-Time PCR assay for the rapid detection and quantification of G. pallida and H. schachtii. Using species specific primers and SYBR green I dye, we were able to detect a single second stage juvenile of cyst forming nematodes in samples. The specificity of the reaction was confirmed by the lack of amplification of DNAs from other Heterodera or Globodera species. Validation tests showed a rather high correlation between real numbers of second stage juveniles in a sample and expected numbers detected by Real-Time PCR. Reasons for observed differences in sensitivity and reliability of quantification detection for two species as well as other problems of Real-Time PCR are discussed. The Real-Time PCR assay with SYBR green I dye targeting fragments of the ITS-rDNA provided a sensitive means for the rapid and simultaneous detection and quantification of juveniles of these pests.

A novel spatter detection algorithm based on typical cellular neural network operations for laser beam welding processes

NASA Astrophysics Data System (ADS)

Nicolosi, L.; Abt, F.; Blug, A.; Heider, A.; Tetzlaff, R.; Höfler, H.

2012-01-01

Real-time monitoring of laser beam welding (LBW) has increasingly gained importance in several manufacturing processes ranging from automobile production to precision mechanics. In the latter, a novel algorithm for the real-time detection of spatters was implemented in a camera based on cellular neural networks. The latter can be connected to the optics of commercially available laser machines leading to real-time monitoring of LBW processes at rates up to 15 kHz. Such high monitoring rates allow the integration of other image evaluation tasks such as the detection of the full penetration hole for real-time control of process parameters.

Development of recombinase polymerase amplification assays for the rapid detection of peste des petits ruminants virus.

PubMed

Zhang, Yongning; Wang, Jianchang; Zhang, Zhou; Mei, Lin; Wang, Jinfeng; Wu, Shaoqiang; Lin, Xiangmei

2018-04-01

Peste des petits ruminants (PPR) is a severe infectious disease of small ruminants caused by PPR virus (PPRV). Rapid and sensitive detection of PPRV is critical for controlling PPR. This report describes the development and evaluation of a conventional reverse transcription recombinase polymerase amplification (RT-RPA) assay and a real-time RT-RPA assay, targeting the PPRV N gene. Sensitivity analysis revealed that the conventional RT-RPA assay could detect 852 copies of standard PPRV RNA per reaction at 95% probability within 20 min at 41 °C, and the real-time RT-RPA assay could detect 103 copies of RNA molecules per reaction at 95% probability. Specificity analysis showed that both assays have no cross-reactivity with nucleic acid templates prepared from other selected viruses or common pathogens. Clinical evaluation using 162 ovine and hircine serum and nasal swab samples showed that the performance of both the real-time RT-RPA assay and the conventional RT-RPA assay were comparable to that of real-time RT-PCR. The overall agreements between real-time RT-PCR and real-time RT-RPA, and conventional RT-RPA were 99.4% (161/162) and 98.8% (160/162), respectively. The R 2 value of real-time RT-RPA and real-time RT-PCR was 0.900 by linear regression analysis. Our results suggest that both RT-RPA assays have a potential application in the rapid, sensitive and specific detection of PPRV. Copyright © 2018 Elsevier B.V. All rights reserved.

Commanding and Controlling Satellite Clusters (IEEE Intelligent Systems, November/December 2000)

DTIC Science & Technology

2000-01-01

real - time operating system , a message-passing OS well suited for distributed...ground Flight processors ObjectAgent RTOS SCL RTOS RDMS Space command language Real - time operating system Rational database management system TS-21 RDMS...engineer with Princeton Satellite Systems. She is working with others to develop ObjectAgent software to run on the OSE Real Time Operating System .

Low-complexity object detection with deep convolutional neural network for embedded systems

NASA Astrophysics Data System (ADS)

Tripathi, Subarna; Kang, Byeongkeun; Dane, Gokce; Nguyen, Truong

2017-09-01

We investigate low-complexity convolutional neural networks (CNNs) for object detection for embedded vision applications. It is well-known that consolidation of an embedded system for CNN-based object detection is more challenging due to computation and memory requirement comparing with problems like image classification. To achieve these requirements, we design and develop an end-to-end TensorFlow (TF)-based fully-convolutional deep neural network for generic object detection task inspired by one of the fastest framework, YOLO.1 The proposed network predicts the localization of every object by regressing the coordinates of the corresponding bounding box as in YOLO. Hence, the network is able to detect any objects without any limitations in the size of the objects. However, unlike YOLO, all the layers in the proposed network is fully-convolutional. Thus, it is able to take input images of any size. We pick face detection as an use case. We evaluate the proposed model for face detection on FDDB dataset and Widerface dataset. As another use case of generic object detection, we evaluate its performance on PASCAL VOC dataset. The experimental results demonstrate that the proposed network can predict object instances of different sizes and poses in a single frame. Moreover, the results show that the proposed method achieves comparative accuracy comparing with the state-of-the-art CNN-based object detection methods while reducing the model size by 3× and memory-BW by 3 - 4× comparing with one of the best real-time CNN-based object detectors, YOLO. Our 8-bit fixed-point TF-model provides additional 4× memory reduction while keeping the accuracy nearly as good as the floating-point model. Moreover, the fixed- point model is capable of achieving 20× faster inference speed comparing with the floating-point model. Thus, the proposed method is promising for embedded implementations.

Extraction of DNA from orange juice, and detection of bacterium Candidatus Liberibacter asiaticus by real-time PCR.

PubMed

Bai, Jinhe; Baldwin, Elizabeth; Liao, Hui-Ling; Zhao, Wei; Kostenyuk, Igor; Burns, Jacqueline; Irey, Mike

2013-10-02

Orange juice processed from Huanglongbing (HLB) affected fruit is often associated with bitter taste and/or off-flavor. HLB disease in Florida is associated with Candidatus Liberibacter asiaticus (CLas), a phloem-limited bacterium. The current standard to confirm CLas for citrus trees is to take samples from midribs of leaves, which are rich in phloem tissues, and use a quantitative real-time polymerase chain reaction (qPCR) test to detect the 16S rDNA gene of CLas. It is extremely difficult to detect CLas in orange juice because of the low CLas population, high sugar and pectin concentration, low pH, and possible existence of an inhibitor to DNA amplification. The objective of this research was to improve extraction of DNA from orange juice and detection of CLas by qPCR. Homogenization using a sonicator increased DNA yield by 86% in comparison to mortar and pestle extraction. It is difficult to separate DNA from pectin; however, DNA was successfully extracted by treating the juice with pectinase. Application of an elution column successfully removed the unidentified inhibitor to DNA amplification. This work provided a protocol to extract DNA from whole orange juice and detect CLas in HLB-affected fruit.

Discrimination of complex synthetic echoes by an echolocating bottlenose dolphin

NASA Astrophysics Data System (ADS)

Helweg, David A.; Moore, Patrick W.; Dankiewicz, Lois A.; Zafran, Justine M.; Brill, Randall L.

2003-02-01

Bottlenose dolphins (Tursiops truncatus) detect and discriminate underwater objects by interrogating the environment with their native echolocation capabilities. Study of dolphins' ability to detect complex (multihighlight) signals in noise suggest echolocation object detection using an approximate 265-μs energy integration time window sensitive to the echo region of highest energy or containing the highlight with highest energy. Backscatter from many real objects contains multiple highlights, distributed over multiple integration windows and with varying amplitude relationships. This study used synthetic echoes with complex highlight structures to test whether high-amplitude initial highlights would interfere with discrimination of low-amplitude trailing highlights. A dolphin was trained to discriminate two-highlight synthetic echoes using differences in the center frequencies of the second highlights. The energy ratio (ΔdB) and the timing relationship (ΔT) between the first and second highlights were manipulated. An iso-sensitivity function was derived using a factorial design testing ΔdB at -10, -15, -20, and -25 dB and ΔT at 10, 20, 40, and 80 μs. The results suggest that the animal processed multiple echo highlights as separable analyzable features in the discrimination task, perhaps perceived through differences in spectral rippling across the duration of the echoes.

A Star Image Extractor for Small Satellites

NASA Astrophysics Data System (ADS)

Yamada, Yoshiyuki; Yamauchi, Masahiro; Gouda, Naoteru; Kobayashi, Yukiyasu; Tsujimoto, Takuji; Yano, Taihei; Suganuma, Masahiro; Nakasuka, Shinichi; Sako, Nobutada; Inamori, Takaya

We have developed a Star Image Extractor (SIE) which works as an on-board real-time image processor. It is a logic circuit written on an FPGA(Field Programmable Gate Array) device. It detects and extracts only an object data from raw image data. SIE will be required with the Nano-JASMINE 1) satellite. Nano-JASMINE is the small astrometry satellite that observes objects in our galaxy. It will be launched in 2010 and needs two years mission period. Nano-JASMINE observes an object with the TDI (Time Delayed Integration) observation mode. TDI is one of operation modes of CCD detector. Data is obtained, by rotating the imaging system including CCD at a rated synchronized with a vertical charge transfer of CCD. Obtained image data is sent through SIE to the Mission-controller.

Methodology for object-oriented real-time systems analysis and design: Software engineering

NASA Technical Reports Server (NTRS)

Schoeffler, James D.

1991-01-01

Successful application of software engineering methodologies requires an integrated analysis and design life-cycle in which the various phases flow smoothly 'seamlessly' from analysis through design to implementation. Furthermore, different analysis methodologies often lead to different structuring of the system so that the transition from analysis to design may be awkward depending on the design methodology to be used. This is especially important when object-oriented programming is to be used for implementation when the original specification and perhaps high-level design is non-object oriented. Two approaches to real-time systems analysis which can lead to an object-oriented design are contrasted: (1) modeling the system using structured analysis with real-time extensions which emphasizes data and control flows followed by the abstraction of objects where the operations or methods of the objects correspond to processes in the data flow diagrams and then design in terms of these objects; and (2) modeling the system from the beginning as a set of naturally occurring concurrent entities (objects) each having its own time-behavior defined by a set of states and state-transition rules and seamlessly transforming the analysis models into high-level design models. A new concept of a 'real-time systems-analysis object' is introduced and becomes the basic building block of a series of seamlessly-connected models which progress from the object-oriented real-time systems analysis and design system analysis logical models through the physical architectural models and the high-level design stages. The methodology is appropriate to the overall specification including hardware and software modules. In software modules, the systems analysis objects are transformed into software objects.

Investigation of Legionella Contamination in Bath Water Samples by Culture, Amoebic Co-Culture, and Real-Time Quantitative PCR Methods.

PubMed

Edagawa, Akiko; Kimura, Akio; Kawabuchi-Kurata, Takako; Adachi, Shinichi; Furuhata, Katsunori; Miyamoto, Hiroshi

2015-10-19

We investigated Legionella contamination in bath water samples, collected from 68 bathing facilities in Japan, by culture, culture with amoebic co-culture, real-time quantitative PCR (qPCR), and real-time qPCR with amoebic co-culture. Using the conventional culture method, Legionella pneumophila was detected in 11 samples (11/68, 16.2%). Contrary to our expectation, the culture method with the amoebic co-culture technique did not increase the detection rate of Legionella (4/68, 5.9%). In contrast, a combination of the amoebic co-culture technique followed by qPCR successfully increased the detection rate (57/68, 83.8%) compared with real-time qPCR alone (46/68, 67.6%). Using real-time qPCR after culture with amoebic co-culture, more than 10-fold higher bacterial numbers were observed in 30 samples (30/68, 44.1%) compared with the same samples without co-culture. On the other hand, higher bacterial numbers were not observed after propagation by amoebae in 32 samples (32/68, 47.1%). Legionella was not detected in the remaining six samples (6/68, 8.8%), irrespective of the method. These results suggest that application of the amoebic co-culture technique prior to real-time qPCR may be useful for the sensitive detection of Legionella from bath water samples. Furthermore, a combination of amoebic co-culture and real-time qPCR might be useful to detect viable and virulent Legionella because their ability to invade and multiply within free-living amoebae is considered to correlate with their pathogenicity for humans. This is the first report evaluating the efficacy of the amoebic co-culture technique for detecting Legionella in bath water samples.

Detection and enumeration of Salmonella enteritidis in homemade ice cream associated with an outbreak: comparison of conventional and real-time PCR methods.

PubMed

Seo, K H; Valentin-Bon, I E; Brackett, R E

2006-03-01

Salmonellosis caused by Salmonella Enteritidis (SE) is a significant cause of foodborne illnesses in the United States. Consumption of undercooked eggs and egg-containing products has been the primary risk factor for the disease. The importance of the bacterial enumeration technique has been enormously stressed because of the quantitative risk analysis of SE in shell eggs. Traditional enumeration methods mainly depend on slow and tedious most-probable-number (MPN) methods. Therefore, specific, sensitive, and rapid methods for SE quantitation are needed to collect sufficient data for risk assessment and food safety policy development. We previously developed a real-time quantitative PCR assay for the direct detection and enumeration of SE and, in this study, applied it to naturally contaminated ice cream samples with and without enrichment. The detection limit of the real-time PCR assay was determined with artificially inoculated ice cream. When applied to the direct detection and quantification of SE in ice cream, the real-time PCR assay was as sensitive as the conventional plate count method in frequency of detection. However, populations of SE derived from real-time quantitative PCR were approximately 1 log higher than provided by MPN and CFU values obtained by conventional culture methods. The detection and enumeration of SE in naturally contaminated ice cream can be completed in 3 h by this real-time PCR method, whereas the cultural enrichment method requires 5 to 7 days. A commercial immunoassay for the specific detection of SE was also included in the study. The real-time PCR assay proved to be a valuable tool that may be useful to the food industry in monitoring its processes to improve product quality and safety.

Investigation of Legionella Contamination in Bath Water Samples by Culture, Amoebic Co-Culture, and Real-Time Quantitative PCR Methods

PubMed Central

Edagawa, Akiko; Kimura, Akio; Kawabuchi-Kurata, Takako; Adachi, Shinichi; Furuhata, Katsunori; Miyamoto, Hiroshi

2015-01-01

We investigated Legionella contamination in bath water samples, collected from 68 bathing facilities in Japan, by culture, culture with amoebic co-culture, real-time quantitative PCR (qPCR), and real-time qPCR with amoebic co-culture. Using the conventional culture method, Legionella pneumophila was detected in 11 samples (11/68, 16.2%). Contrary to our expectation, the culture method with the amoebic co-culture technique did not increase the detection rate of Legionella (4/68, 5.9%). In contrast, a combination of the amoebic co-culture technique followed by qPCR successfully increased the detection rate (57/68, 83.8%) compared with real-time qPCR alone (46/68, 67.6%). Using real-time qPCR after culture with amoebic co-culture, more than 10-fold higher bacterial numbers were observed in 30 samples (30/68, 44.1%) compared with the same samples without co-culture. On the other hand, higher bacterial numbers were not observed after propagation by amoebae in 32 samples (32/68, 47.1%). Legionella was not detected in the remaining six samples (6/68, 8.8%), irrespective of the method. These results suggest that application of the amoebic co-culture technique prior to real-time qPCR may be useful for the sensitive detection of Legionella from bath water samples. Furthermore, a combination of amoebic co-culture and real-time qPCR might be useful to detect viable and virulent Legionella because their ability to invade and multiply within free-living amoebae is considered to correlate with their pathogenicity for humans. This is the first report evaluating the efficacy of the amoebic co-culture technique for detecting Legionella in bath water samples. PMID:26492259

[Real-time PCR kits for the detection of the African Swine Fever virus].

PubMed

Latyshev, O E; Eliseeva, O V; Grebennikova, T V; Verkhovskiĭ, O A; Tsibezov, V V; Chernykh, O Iu; Dzhailidi, G A; Aliper, T I

2014-01-01

The results obtained using the diagnostic kit based on real-time polymerase chain reaction to detect the DNA of the African Swine Fever in the pathological material, as well as in the culture fluid, are presented. A high sensitivity and specificity for detection of the DNA in the organs and tissues of animals was shown to be useful for detection in the European Union referentiality reagent kits for DNA detection by real time PCR of ASFV. More rapid and effective method of DNA extraction using columns mini spin Quick gDNA(TM) MiniPrep was suggested and compared to the method of DNA isolation on the inorganic sorbent. High correlation of the results of the DNA detection of ASFV by real-time PCR and antigen detection results ASFV by competitive ELISA obtained with the ELISA SEROTEST/INGEZIM COMRAC PPA was demonstrated. The kit can be used in the veterinary services for effective monitoring of ASFV to contain, eliminate and prevent further spread of the disease.

Real-time distortion correction for visual inspection systems based on FPGA

NASA Astrophysics Data System (ADS)

Liang, Danhua; Zhang, Zhaoxia; Chen, Xiaodong; Yu, Daoyin

2008-03-01

Visual inspection is a kind of new technology based on the research of computer vision, which focuses on the measurement of the object's geometry and location. It can be widely used in online measurement, and other real-time measurement process. Because of the defects of the traditional visual inspection, a new visual detection mode -all-digital intelligent acquisition and transmission is presented. The image processing, including filtering, image compression, binarization, edge detection and distortion correction, can be completed in the programmable devices -FPGA. As the wide-field angle lens is adopted in the system, the output images have serious distortion. Limited by the calculating speed of computer, software can only correct the distortion of static images but not the distortion of dynamic images. To reach the real-time need, we design a distortion correction system based on FPGA. The method of hardware distortion correction is that the spatial correction data are calculated first under software circumstance, then converted into the address of hardware storage and stored in the hardware look-up table, through which data can be read out to correct gray level. The major benefit using FPGA is that the same circuit can be used for other circularly symmetric wide-angle lenses without being modified.

Real-time fluorescence ligase chain reaction for sensitive detection of single nucleotide polymorphism based on fluorescence resonance energy transfer.

PubMed

Sun, Yueying; Lu, Xiaohui; Su, Fengxia; Wang, Limei; Liu, Chenghui; Duan, Xinrui; Li, Zhengping

2015-12-15

Most of practical methods for detection of single nucleotide polymorphism (SNP) need at least two steps: amplification (usually by PCR) and detection of SNP by using the amplification products. Ligase chain reaction (LCR) can integrate the amplification and allele discrimination in one step. However, the detection of LCR products still remains a great challenge for highly sensitive and quantitative SNP detection. Herein, a simple but robust strategy for real-time fluorescence LCR has been developed for highly sensitive and quantitative SNP detection. A pair of LCR probes are firstly labeled with a fluorophore and a quencher, respectively. When the pair of LCR probes are ligated in LCR, the fluorophore will be brought close to the quencher, and thus, the fluorescence will be specifically quenched by fluorescence resonance energy transfer (FRET). The decrease of fluorescence intensity resulted from FRET can be real-time monitored in the LCR process. With the proposed real-time fluorescence LCR assay, 10 aM DNA targets or 100 pg genomic DNA can be accurately determined and as low as 0.1% mutant DNA can be detected in the presence of a large excess of wild-type DNA, indicating the high sensitivity and specificity. The real-time measuring does not require the detection step after LCR and gives a wide dynamic range for detection of DNA targets (from 10 aM to 1 pM). As LCR has been widely used for detection of SNP, DNA methylation, mRNA and microRNA, the real-time fluorescence LCR assay shows great potential for various genetic analysis. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison of Remote Sensing Image Processing Techniques to Identify Tornado Damage Areas from Landsat TM Data

PubMed Central

Myint, Soe W.; Yuan, May; Cerveny, Randall S.; Giri, Chandra P.

2008-01-01

Remote sensing techniques have been shown effective for large-scale damage surveys after a hazardous event in both near real-time or post-event analyses. The paper aims to compare accuracy of common imaging processing techniques to detect tornado damage tracks from Landsat TM data. We employed the direct change detection approach using two sets of images acquired before and after the tornado event to produce a principal component composite images and a set of image difference bands. Techniques in the comparison include supervised classification, unsupervised classification, and object-oriented classification approach with a nearest neighbor classifier. Accuracy assessment is based on Kappa coefficient calculated from error matrices which cross tabulate correctly identified cells on the TM image and commission and omission errors in the result. Overall, the Object-oriented Approach exhibits the highest degree of accuracy in tornado damage detection. PCA and Image Differencing methods show comparable outcomes. While selected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approach performs significantly better with 15-20% higher accuracy than the other two techniques. PMID:27879757

Detection of mRNA by reverse transcription PCR as an indicator of viability in Phytophthora ramorum

Treesearch

Antonio Chimento; Santa Olga Cacciola; Matteo Garbelotto

2008-01-01

Real-Time PCR technologies offer increasing opportunities to detect and study phytopathogenic fungi. They combine the sensitivity of conventional PCR with the generation of a specific fluorescent signal providing both real-time analysis of the reaction kinetics and quantification of specific DNA targets. Before the development of Real-Time PCR and...

Robust multiperson detection and tracking for mobile service and social robots.

PubMed

Li, Liyuan; Yan, Shuicheng; Yu, Xinguo; Tan, Yeow Kee; Li, Haizhou

2012-10-01

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

Real-time video analysis for retail stores

NASA Astrophysics Data System (ADS)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Improved dual-loop detection system for collecting real-time truck data

DOT National Transportation Integrated Search

2005-02-01

The WSDOTs dual-loop detectors capability of measuring vehicle lengths makes the dual-loop detection system a potential real-time truck data source for freight movement study. However, a previous study found the WSDOT dual-loop detection system...

Implementation of a real-time intersection accident detection system (Phase 1).

DOT National Transportation Integrated Search

2004-10-01

The focus of this research is the feasibility study for the implementation of a real-time accident : detection system at intersections. After reviewing accident detection algorithms investigated in the prior : phase of the research, we explored schem...

Automated Cloud Observation for Ground Telescope Optimization

NASA Astrophysics Data System (ADS)

Lane, B.; Jeffries, M. W., Jr.; Therien, W.; Nguyen, H.

As the number of man-made objects placed in space each year increases with advancements in commercial, academic and industry, the number of objects required to be detected, tracked, and characterized continues to grow at an exponential rate. Commercial companies, such as ExoAnalytic Solutions, have deployed ground based sensors to maintain track custody of these objects. For the ExoAnalytic Global Telescope Network (EGTN), observation of such objects are collected at the rate of over 10 million unique observations per month (as of September 2017). Currently, the EGTN does not optimally collect data on nights with significant cloud levels. However, a majority of these nights prove to be partially cloudy providing clear portions in the sky for EGTN sensors to observe. It proves useful for a telescope to utilize these clear areas to continue resident space object (RSO) observation. By dynamically updating the tasking with the varying cloud positions, the number of observations could potentially increase dramatically due to increased persistence, cadence, and revisit. This paper will discuss the recent algorithms being implemented within the EGTN, including the motivation, need, and general design. The use of automated image processing as well as various edge detection methods, including Canny, Sobel, and Marching Squares, on real-time large FOV images of the sky enhance the tasking and scheduling of a ground based telescope is discussed in Section 2. Implementations of these algorithms on single and expanding to multiple telescopes, will be explored. Results of applying these algorithms to the EGTN in real-time and comparison to non-optimized EGTN tasking is presented in Section 3. Finally, in Section 4 we explore future work in applying these throughout the EGTN as well as other optical telescopes.

Dynamic engagement of cognitive control modulates recovery from misinterpretation during real-time language processing

PubMed Central

Hsu, Nina S.; Novick, Jared M.

2016-01-01

Speech unfolds swiftly, yet listeners keep pace by rapidly assigning meaning to what they hear. Sometimes though, initial interpretations turn out wrong. How do listeners revise misinterpretations of language input moment-by-moment, to avoid comprehension errors? Cognitive control may play a role by detecting when processing has gone awry, and then initiating behavioral adjustments accordingly. However, no research has investigated a cause-and-effect interplay between cognitive control engagement and overriding erroneous interpretations in real-time. Using a novel cross-task paradigm, we show that Stroop-conflict detection, which mobilizes cognitive control procedures, subsequently facilitates listeners’ incremental processing of temporarily ambiguous spoken instructions that induce brief misinterpretation. When instructions followed Stroop-incongruent versus-congruent items, listeners’ eye-movements to objects in a scene reflected more transient consideration of the false interpretation and earlier recovery of the correct one. Comprehension errors also decreased. Cognitive control engagement therefore accelerates sentence re-interpretation processes, even as linguistic input is still unfolding. PMID:26957521

Absence of Measles Virus Detection from Stapes of Patients with Otosclerosis.

PubMed

Flores-García, María de Lourdes; Colín-Castro, Claudia Adriana; Hernández-Palestina, Mario Sabas; Sánchez-Larios, Roberto; Franco-Cendejas, Rafael

2018-01-01

Objective To determine molecularly the presence of measles virus genetic material in the stapes of patients with otosclerosis. Study Design A cross-sectional study. Setting A tertiary referral hospital. Subjects and Methods Genetic material was extracted from the stapes of patients with otosclerosis (n = 93) during the period from March 2011 to April 2012. The presence of viral measles sequences was evaluated by the real-time reverse transcriptase polymerase chain reaction (RT-PCR). The expression of the CD46 gene was determined. Results Ninety-three patients were included in the study. No sample was positive for any of 3 measles virus genes (H, N, and F). Measles virus RNA was not detected in any sample by real-time RT-PCR. CD46 levels were positive in 3.3% (n = 3) and negative in 96.7% (n = 90). Conclusion This study does not support the theory of measles virus as the cause of otosclerosis. It is necessary to do more research about other causal theories to clarify its etiology and prevention.

Detection of bacteria and fungi in blood of patients with febrile neutropenia by real-time PCR with universal primers and probes.

PubMed

Teranishi, Hideto; Ohzono, Nanae; Inamura, Norikazu; Kato, Atsushi; Wakabayashi, Tokio; Akaike, Hiroto; Terada, Kihei; Ouchi, Kazunobu

2015-03-01

Febrile neutropenia is the main treatment-related cause of mortality in cancer patients. During June 2012 to April 2014, 97 blood culture samples were collected from patients receiving chemotherapy for hematological malignancy and cancer with febrile neutropenia episodes (FNEs). The samples were examined for the presence of bacteria and fungi using real-time PCR amplification and sequencing of 16S and 18S rRNA genes. Bacteria were identified in 20 of 97 samples (20.6%) by the real-time PCR assay and in 10 of 97 (10.3%) samples by blood culture. In 6 blood culture-positive samples, the real-time PCR assay detected the same type of bacteria. No fungi were detected by the real-time PCR assay or blood culture. During antibiotic therapy, all samples were negative by blood culture, but the real-time PCR assay yielded a positive result in 2 cases of 2 (100%). The bacterial DNA copy number was not well correlated with the serum C-reactive protein titer of patients with FNEs. We conclude that a real-time PCR assay could provide better detection of causative microbes' in a shorter time, and with a smaller blood sample than blood culture. Using a real-time PCR assay in combination with blood culture could improve microbiological documentation of FNEs. Copyright © 2014 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Enhancements to the EPANET-RTX (Real-Time Analytics) ...

EPA Pesticide Factsheets

Technical brief and software The U.S. Environmental Protection Agency (EPA) developed EPANET-RTX as a collection of object-oriented software libraries comprising the core data access, data transformation, and data synthesis (real-time analytics) components of a real-time hydraulic and water quality modeling system. While EPANET-RTX uses the hydraulic and water quality solvers of EPANET, the object libraries are a self-contained set of building blocks for software developers. “Real-time EPANET” promises to change the way water utilities, commercial vendors, engineers, and the water community think about modeling.

Real-time 3D change detection of IEDs

NASA Astrophysics Data System (ADS)

Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

2012-06-01

Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

A cost effective real-time PCR for the detection of adenovirus from viral swabs

PubMed Central

2013-01-01

Compared to traditional testing strategies, nucleic acid amplification tests such as real-time PCR offer many advantages for the detection of human adenoviruses. However, commercial assays are expensive and cost prohibitive for many clinical laboratories. To overcome fiscal challenges, a cost effective strategy was developed using a combination of homogenization and heat treatment with an “in-house” real-time PCR. In 196 swabs submitted for adenovirus detection, this crude extraction method showed performance characteristics equivalent to viral DNA obtained from a commercial nucleic acid extraction. In addition, the in-house real-time PCR outperformed traditional testing strategies using virus culture, with sensitivities of 100% and 69.2%, respectively. Overall, the combination of homogenization and heat treatment with a sensitive in-house real-time PCR provides accurate results at a cost comparable to viral culture. PMID:23758993

Simultaneous detection of papaya ringspot virus, papaya leaf distortion mosaic virus, and papaya mosaic virus by multiplex real-time reverse transcription PCR.

PubMed

Huo, P; Shen, W T; Yan, P; Tuo, D C; Li, X Y; Zhou, P

2015-12-01

Both the single infection of papaya ringspot virus (PRSV), papaya leaf distortion mosaic virus (PLDMV) or papaya mosaic virus (PapMV) and double infection of PRSV and PLDMV or PapMV which cause indistinguishable symptoms, threaten the papaya industry in Hainan Island, China. In this study, a multiplex real-time reverse transcription PCR (RT-PCR) was developed to detect simultaneously the three viruses based on their distinctive melting temperatures (Tms): 81.0±0.8°C for PRSV, 84.7±0.6°C for PLDMV, and 88.7±0.4°C for PapMV. The multiplex real-time RT-PCR method was specific and sensitive in detecting the three viruses, with a detection limit of 1.0×10(1), 1.0×10(2), and 1.0×10(2) copies for PRSV, PLDMV, and PapMV, respectively. Indeed, the reaction was 100 times more sensitive than the multiplex RT-PCR for PRSV, and 10 times more sensitive than multiplex RT-PCR for PLDMV. Field application of the multiplex real-time RT-PCR demonstrated that some non-symptomatic samples were positive for PLDMV by multiplex real-time RT-PCR but negative by multiplex RT-PCR, whereas some samples were positive for both PRSV and PLDMV by multiplex real-time RT-PCR assay but only positive for PLDMV by multiplex RT-PCR. Therefore, this multiplex real-time RT-PCR assay provides a more rapid, sensitive and reliable method for simultaneous detection of PRSV, PLDMV, PapMV and their mixed infections in papaya.

Real-time PCR for the early detection and quantification of Coxiella burnetii as an alternative to the murine bioassay.

PubMed

Howe, Gerald B; Loveless, Bonnie M; Norwood, David; Craw, Philip; Waag, David; England, Marilyn; Lowe, John R; Courtney, Bernard C; Pitt, M Louise; Kulesh, David A

2009-01-01

Real-time PCR was used to analyze archived blood from non-human primates (NHP) and fluid samples originating from a well-controlled Q fever vaccine efficacy trial. The PCR targets were the IS1111 element and the com1 gene of Coxiella burnetii. Data from that previous study were used to evaluate real-time PCR as an alternative to the use of sero-conversion by mouse bioassay for both quantification and early detection of C. burnetii bacteria. Real-time PCR and the mouse bioassay exhibited no statistical difference in quantifying the number of microorganisms delivered in the aerosol challenge dose. The presence of C. burnetii in peripheral blood of non-human primates was detected by real-time PCR as early after exposure as the mouse bioassay with results available within hours instead of weeks. This study demonstrates that real-time PCR has the ability to replace the mouse bioassay to measure dosage and monitor infection of C. burnetii in a non-human primate model.

Rapid and sensitive detection of Yersinia pestis using amplification of plague diagnostic bacteriophages monitored by real-time PCR.

PubMed

Sergueev, Kirill V; He, Yunxiu; Borschel, Richard H; Nikolich, Mikeljon P; Filippov, Andrey A

2010-06-28

Yersinia pestis, the agent of plague, has caused many millions of human deaths and still poses a serious threat to global public health. Timely and reliable detection of such a dangerous pathogen is of critical importance. Lysis by specific bacteriophages remains an essential method of Y. pestis detection and plague diagnostics. The objective of this work was to develop an alternative to conventional phage lysis tests--a rapid and highly sensitive method of indirect detection of live Y. pestis cells based on quantitative real-time PCR (qPCR) monitoring of amplification of reporter Y. pestis-specific bacteriophages. Plague diagnostic phages phiA1122 and L-413C were shown to be highly effective diagnostic tools for the detection and identification of Y. pestis by using qPCR with primers specific for phage DNA. The template DNA extraction step that usually precedes qPCR was omitted. phiA1122-specific qPCR enabled the detection of an initial bacterial concentration of 10(3) CFU/ml (equivalent to as few as one Y. pestis cell per 1-microl sample) in four hours. L-413C-mediated detection of Y. pestis was less sensitive (up to 100 bacteria per sample) but more specific, and thus we propose parallel qPCR for the two phages as a rapid and reliable method of Y. pestis identification. Importantly, phiA1122 propagated in simulated clinical blood specimens containing EDTA and its titer rise was detected by both a standard plating test and qPCR. Thus, we developed a novel assay for detection and identification of Y. pestis using amplification of specific phages monitored by qPCR. The method is simple, rapid, highly sensitive, and specific and allows the detection of only live bacteria.

Deep Space Wide Area Search Strategies

NASA Astrophysics Data System (ADS)

Capps, M.; McCafferty, J.

There is an urgent need to expand the space situational awareness (SSA) mission beyond catalog maintenance to providing near real-time indications and warnings of emerging events. While building and maintaining a catalog of space objects is essential to SSA, this does not address the threat of uncatalogued and uncorrelated deep space objects. The Air Force therefore has an interest in transformative technologies to scan the geostationary (GEO) belt for uncorrelated space objects. Traditional ground based electro-optical sensors are challenged in simultaneously detecting dim objects while covering large areas of the sky using current CCD technology. Time delayed integration (TDI) scanning has the potential to enable significantly larger coverage rates while maintaining sensitivity for detecting near-GEO objects. This paper investigates strategies of employing TDI sensing technology from a ground based electro-optical telescope, toward providing tactical indications and warnings of deep space threats. We present results of a notional wide area search TDI sensor that scans the GEO belt from three locations: Maui, New Mexico, and Diego Garcia. Deep space objects in the NASA 2030 debris catalog are propagated over multiple nights as an indicative data set to emulate notional uncatalogued near-GEO orbits which may be encountered by the TDI sensor. Multiple scan patterns are designed and simulated, to compare and contrast performance based on 1) efficiency in coverage, 2) number of objects detected, and 3) rate at which detections occur, to enable follow-up observations by other space surveillance network (SSN) sensors. A step-stare approach is also modeled using a dedicated, co-located sensor notionally similar to the Ground-Based Electro-Optical Deep Space Surveillance (GEODSS) tower. Equivalent sensitivities are assumed. This analysis quantifies the relative benefit of TDI scanning for the wide area search mission.

Real-time PCR in virology.

PubMed

Mackay, Ian M; Arden, Katherine E; Nitsche, Andreas

2002-03-15

The use of the polymerase chain reaction (PCR) in molecular diagnostics has increased to the point where it is now accepted as the gold standard for detecting nucleic acids from a number of origins and it has become an essential tool in the research laboratory. Real-time PCR has engendered wider acceptance of the PCR due to its improved rapidity, sensitivity, reproducibility and the reduced risk of carry-over contamination. There are currently five main chemistries used for the detection of PCR product during real-time PCR. These are the DNA binding fluorophores, the 5' endonuclease, adjacent linear and hairpin oligoprobes and the self-fluorescing amplicons, which are described in detail. We also discuss factors that have restricted the development of multiplex real-time PCR as well as the role of real-time PCR in quantitating nucleic acids. Both amplification hardware and the fluorogenic detection chemistries have evolved rapidly as the understanding of real-time PCR has developed and this review aims to update the scientist on the current state of the art. We describe the background, advantages and limitations of real-time PCR and we review the literature as it applies to virus detection in the routine and research laboratory in order to focus on one of the many areas in which the application of real-time PCR has provided significant methodological benefits and improved patient outcomes. However, the technology discussed has been applied to other areas of microbiology as well as studies of gene expression and genetic disease.

Flightspeed Integral Image Analysis Toolkit

NASA Technical Reports Server (NTRS)

Thompson, David R.

2009-01-01

The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

Collision detection in complex dynamic scenes using an LGMD-based visual neural network with feature enhancement.

PubMed

Yue, Shigang; Rind, F Claire

2006-05-01

The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.

The applicability of TaqMan-based quantitative real-time PCR assays for detecting and enumeratIng Cryptosporidium spp. oocysts in the environment

EPA Science Inventory

Molecular detection methods such as PCR have been extensively used to type Cryptosporidium oocysts detected in the environment. More recently, studies have developed quantitative real-time PCR assays for detection and quantification of microbial contaminants in water as well as ...

Tracking-Learning-Detection.

PubMed

Kalal, Zdenek; Mikolajczyk, Krystian; Matas, Jiri

2012-07-01

This paper investigates long-term tracking of unknown objects in a video stream. The object is defined by its location and extent in a single frame. In every frame that follows, the task is to determine the object's location and extent or indicate that the object is not present. We propose a novel tracking framework (TLD) that explicitly decomposes the long-term tracking task into tracking, learning, and detection. The tracker follows the object from frame to frame. The detector localizes all appearances that have been observed so far and corrects the tracker if necessary. The learning estimates the detector's errors and updates it to avoid these errors in the future. We study how to identify the detector's errors and learn from them. We develop a novel learning method (P-N learning) which estimates the errors by a pair of "experts": (1) P-expert estimates missed detections, and (2) N-expert estimates false alarms. The learning process is modeled as a discrete dynamical system and the conditions under which the learning guarantees improvement are found. We describe our real-time implementation of the TLD framework and the P-N learning. We carry out an extensive quantitative evaluation which shows a significant improvement over state-of-the-art approaches.

Detection of Brucella spp. in milk from seronegative cows by real-time polymerase chain reaction in the region of Batna, Algeria

PubMed Central

Sabrina, Rabehi; Mossadak, Hamdi Taha; Bakir, Mamache; Asma, Meghezzi; Khaoula, Boushaba

2018-01-01

Aim: The aim of this study was to detect Brucella spp. DNA in milk samples collected from seronegative cows using the real-time polymerase chain reaction (PCR) assay for diagnosis of brucellosis in seronegative dairy cows to prevent transmission of disease to humans and to reduce economic losses in animal production. Materials and Methods: In this study, 65 milk samples were investigated for the detection of Brucella spp. The detection of the IS711 gene in all samples was done by real-time PCR assay by comparative cycle threshold method. Results: The results show that of the 65 DNA samples tested, 2 (3.08%) were positive for Brucella infection. The mean cyclic threshold values of IS711 real-time PCR test were 37.97 and 40.48, indicating a positive reaction. Conclusion: The results of the present study indicated that the real-time PCR appears to offer several advantages over serological tests. For this reason, the real-time PCR should be validated on representative numbers of Brucella-infected and free samples before being implemented in routine diagnosis in human and animal brucellosis for controlling this disease. PMID:29657430

Implementation of a General Real-Time Visual Anomaly Detection System Via Soft Computing

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steve; Ferrell, Bob; Steinrock, Todd (Technical Monitor)

2001-01-01

The intelligent visual system detects anomalies or defects in real time under normal lighting operating conditions. The application is basically a learning machine that integrates fuzzy logic (FL), artificial neural network (ANN), and generic algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs segmentation to separate the object being tested from the background, preprocesses the image using fuzzy reasoning, performs the final segmentation using fuzzy reasoning techniques to retrieve regions with potential anomalies or defects, and finally retrieves them using a learning model built via ANN and GA techniques. FL provides a powerful framework for knowledge representation and overcomes uncertainty and vagueness typically found in image analysis. ANN provides learning capabilities, and GA leads to robust learning results. An application prototype currently runs on a regular PC under Windows NT, and preliminary work has been performed to build an embedded version with multiple image processors. The application prototype is being tested at the Kennedy Space Center (KSC), Florida, to visually detect anomalies along slide basket cables utilized by the astronauts to evacuate the NASA Shuttle launch pad in an emergency. The potential applications of this anomaly detection system in an open environment are quite wide. Another current, potentially viable application at NASA is in detecting anomalies of the NASA Space Shuttle Orbiter's radiator panels.

Multiplex Real-Time PCR for Detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL) Genes from Selective Enrichments from Animals and Retail Meat

PubMed Central

Velasco, Valeria; Sherwood, Julie S.; Rojas-García, Pedro P.; Logue, Catherine M.

2014-01-01

The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL) genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat). The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus), mecA (associated with methicillin resistance) and PVL (virulence factor), and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68–0.88 (from substantial to almost perfect agreement) and 0.29–0.77 (from fair to substantial agreement) for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0–0.49 (from no agreement beyond that expected by chance to moderate agreement) for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA) using the standard culture method. PMID:24849624

Multiplex real-time PCR for detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL) genes from selective enrichments from animals and retail meat.

PubMed

Velasco, Valeria; Sherwood, Julie S; Rojas-García, Pedro P; Logue, Catherine M

2014-01-01

The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL) genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat). The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus), mecA (associated with methicillin resistance) and PVL (virulence factor), and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68-0.88 (from substantial to almost perfect agreement) and 0.29-0.77 (from fair to substantial agreement) for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0-0.49 (from no agreement beyond that expected by chance to moderate agreement) for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA) using the standard culture method.

New multiplex real-time PCR approach to detect gene mutations for spinal muscular atrophy.

PubMed

Liu, Zhidai; Zhang, Penghui; He, Xiaoyan; Liu, Shan; Tang, Shi; Zhang, Rong; Wang, Xinbin; Tan, Junjie; Peng, Bin; Jiang, Li; Hong, Siqi; Zou, Lin

2016-08-17

Spinal muscular atrophy (SMA) is the most common autosomal recessive disease in children, and the diagnosis is complicated and difficult, especially at early stage. Early diagnosis of SMA is able to improve the outcome of SMA patients. In our study, Real-time PCR was developed to measure the gene mutation or deletion of key genes for SMA and to further analyse genotype-phenotype correlation. The multiple real-time PCR for detecting the mutations of survival of motor neuron (SMN), apoptosis inhibitory protein (NAIP) and general transcription factor IIH, polypeptide 2 gene (GTF2H2) was established and confirmed by DNA sequencing and multiplex ligation-dependent probe amplification (MLPA). The diagnosis and prognosis of 141 hospitalized children, 100 normal children and further 2000 cases of dry blood spot (DBS) samples were analysed by this multiple real-time PCR. The multiple real-time PCR was established and the accuracy of it to detect the mutations of SMN, NAIP and GTF2H2 was at least 98.8 % comparing with DNA sequencing and MLPA. Among 141 limb movement disorders children, 75 cases were SMA. 71 cases of SMA (94.67 %) were with SMN c.840 mutation, 9 cases (12 %) with NAIP deletion and 3 cases (4 %) with GTF2H2 deletion. The multiple real-time PCR was able to diagnose and predict the prognosis of SMA patients. Simultaneously, the real-time PCR was applied to detect trace DNA from DBS and able to make an early diagnosis of SMA. The clinical and molecular characteristics of SMA in Southwest of China were presented. Our work provides a novel way for detecting SMA in children by using real-time PCR and the potential usage in newborn screening for early diagnosis of SMA.

The relative importance of real-time in-cab and external feedback in managing fatigue in real-world commercial transport operations.

PubMed

Fitzharris, Michael; Liu, Sara; Stephens, Amanda N; Lenné, Michael G

2017-05-29

Real-time driver monitoring systems represent a solution to address key behavioral risks as they occur, particularly distraction and fatigue. The efficacy of these systems in real-world settings is largely unknown. This article has three objectives: (1) to document the incidence and duration of fatigue in real-world commercial truck-driving operations, (2) to determine the reduction, if any, in the incidence of fatigue episodes associated with providing feedback, and (3) to tease apart the relative contribution of in-cab warnings from 24/7 monitoring and feedback to employers. Data collected from a commercially available in-vehicle camera-based driver monitoring system installed in a commercial truck fleet operating in Australia were analyzed. The real-time driver monitoring system makes continuous assessments of driver drowsiness based on eyelid position and other factors. Data were collected in a baseline period where no feedback was provided to drivers. Real-time feedback to drivers then occurred via in-cab auditory and haptic warnings, which were further enhanced by direct feedback by company management when fatigue events were detected by external 24/7 monitors. Fatigue incidence rates and their timing of occurrence across the three time periods were compared. Relative to no feedback being provided to drivers when fatigue events were detected, in-cab warnings resulted in a 66% reduction in fatigue events, with a 95% reduction achieved by the real-time provision of direct feedback in addition to in-cab warnings (p < 0.01). With feedback, fatigue events were shorter in duration a d occurred later in the trip, and fewer drivers had more than one verified fatigue event per trip. That the provision of feedback to the company on driver fatigue events in real time provides greater benefit than feedback to the driver alone has implications for companies seeking to mitigate risks associated with fatigue. Having fewer fatigue events is likely a reflection of the device itself and the accompanying safety culture of the company in terms of how the information is used. Data were analysed on a per-truck trip basis, and the findings are indicative of fatigue events in a large-scale commercial transport fleet. Future research ought to account for individual driver performance, which was not possible with the available data in this retrospective analysis. Evidence that real-time driver monitoring feedback is effective in reducing fatigue events is invaluable in the development of fleet safety policies, and of future national policy and vehicle safety regulations. Implications for automotive driver monitoring are discussed.

Real-Time Laser Ultrasound Tomography for Profilometry of Solids

NASA Astrophysics Data System (ADS)

Zarubin, V. P.; Bychkov, A. S.; Karabutov, A. A.; Simonova, V. A.; Kudinov, I. A.; Cherepetskaya, E. B.

2018-01-01

We studied the possibility of applying laser ultrasound tomography for profilometry of solids. The proposed approach provides high spatial resolution and efficiency, as well as profilometry of contaminated objects or objects submerged in liquids. The algorithms for the construction of tomograms and recognition of the profiles of studied objects using the parallel programming technology NDIVIA CUDA are proposed. A prototype of the real-time laser ultrasound profilometer was used to obtain the profiles of solid surfaces of revolution. The proposed method allows the real-time determination of the surface position for cylindrical objects with an approximation accuracy of up to 16 μm.

Collision detection and modeling of rigid and deformable objects in laparoscopic simulator

NASA Astrophysics Data System (ADS)

Dy, Mary-Clare; Tagawa, Kazuyoshi; Tanaka, Hiromi T.; Komori, Masaru

2015-03-01

Laparoscopic simulators are viable alternatives for surgical training and rehearsal. Haptic devices can also be incorporated with virtual reality simulators to provide additional cues to the users. However, to provide realistic feedback, the haptic device must be updated by 1kHz. On the other hand, realistic visual cues, that is, the collision detection and deformation between interacting objects must be rendered at least 30 fps. Our current laparoscopic simulator detects the collision between a point on the tool tip, and on the organ surfaces, in which haptic devices are attached on actual tool tips for realistic tool manipulation. The triangular-mesh organ model is rendered using a mass spring deformation model, or finite element method-based models. In this paper, we investigated multi-point-based collision detection on the rigid tool rods. Based on the preliminary results, we propose a method to improve the collision detection scheme, and speed up the organ deformation reaction. We discuss our proposal for an efficient method to compute simultaneous multiple collision between rigid (laparoscopic tools) and deformable (organs) objects, and perform the subsequent collision response, with haptic feedback, in real-time.

A Novel Tactile Sensor with Electromagnetic Induction and Its Application on Stick-Slip Interaction Detection

PubMed Central

Liu, Yanjie; Han, Haijun; Liu, Tao; Yi, Jingang; Li, Qingguo; Inoue, Yoshio

2016-01-01

Real-time detection of contact states, such as stick-slip interaction between a robot and an object on its end effector, is crucial for the robot to grasp and manipulate the object steadily. This paper presents a novel tactile sensor based on electromagnetic induction and its application on stick-slip interaction. An equivalent cantilever-beam model of the tactile sensor was built and capable of constructing the relationship between the sensor output and the friction applied on the sensor. With the tactile sensor, a new method to detect stick-slip interaction on the contact surface between the object and the sensor is proposed based on the characteristics of friction change. Furthermore, a prototype was developed for a typical application, stable wafer transferring on a wafer transfer robot, by considering the spatial magnetic field distribution and the sensor size according to the requirements of wafer transfer. The experimental results validate the sensing mechanism of the tactile sensor and verify its feasibility of detecting stick-slip on the contact surface between the wafer and the sensor. The sensing mechanism also provides a new approach to detect the contact state on the soft-rigid surface in other robot-environment interaction systems. PMID:27023545

Millimeter-wave imaging sensor data evaluation

NASA Technical Reports Server (NTRS)

Wilson, William J.; Ibbott, Anthony C.

1987-01-01

A passive 3-mm radiometer system with a mechanically scanned antenna was built for use on a small aircraft or an Unmanned Aerial Vehicle to produce real near-real-time, moderate-resolution (0.5) images of the ground. One of the main advantages of this passive imaging sensor is that it is able to provide surveillance information through dust, smoke, fog and clouds when visual and IR systems are unusable. It can also be used for a variety of remote sensing applications, such as measurements of surface moisture, surface temperature, vegetation extent and snow cover. It is also possible to detect reflective objects under vegetation cover.

The Neural Dynamics of Attentional Selection in Natural Scenes.

PubMed

Kaiser, Daniel; Oosterhof, Nikolaas N; Peelen, Marius V

2016-10-12

The human visual system can only represent a small subset of the many objects present in cluttered scenes at any given time, such that objects compete for representation. Despite these processing limitations, the detection of object categories in cluttered natural scenes is remarkably rapid. How does the brain efficiently select goal-relevant objects from cluttered scenes? In the present study, we used multivariate decoding of magneto-encephalography (MEG) data to track the neural representation of within-scene objects as a function of top-down attentional set. Participants detected categorical targets (cars or people) in natural scenes. The presence of these categories within a scene was decoded from MEG sensor patterns by training linear classifiers on differentiating cars and people in isolation and testing these classifiers on scenes containing one of the two categories. The presence of a specific category in a scene could be reliably decoded from MEG response patterns as early as 160 ms, despite substantial scene clutter and variation in the visual appearance of each category. Strikingly, we find that these early categorical representations fully depend on the match between visual input and top-down attentional set: only objects that matched the current attentional set were processed to the category level within the first 200 ms after scene onset. A sensor-space searchlight analysis revealed that this early attention bias was localized to lateral occipitotemporal cortex, reflecting top-down modulation of visual processing. These results show that attention quickly resolves competition between objects in cluttered natural scenes, allowing for the rapid neural representation of goal-relevant objects. Efficient attentional selection is crucial in many everyday situations. For example, when driving a car, we need to quickly detect obstacles, such as pedestrians crossing the street, while ignoring irrelevant objects. How can humans efficiently perform such tasks, given the multitude of objects contained in real-world scenes? Here we used multivariate decoding of magnetoencephalogaphy data to characterize the neural underpinnings of attentional selection in natural scenes with high temporal precision. We show that brain activity quickly tracks the presence of objects in scenes, but crucially only for those objects that were immediately relevant for the participant. These results provide evidence for fast and efficient attentional selection that mediates the rapid detection of goal-relevant objects in real-world environments. Copyright © 2016 the authors 0270-6474/16/3610522-07$15.00/0.

Optical Observations of GEO Debris with Two Telescopes

NASA Technical Reports Server (NTRS)

Seitzer, P.; Abercromby, K.; Rodriguez, H.; Barker, E.

2007-01-01

For several years, the Michigan Orbital DEbris Survey Telescope (MODEST), the University of Michigan s 0.6/0.9-m Schmidt telescope on Cerro Tololo Inter-American Observatory in Chile has been used to survey the debris population at GEO in the visible regime. Magnitudes, positions, and angular rates are determined for GEO objects as they move across the telescope s field-of-view (FOV) during a 5-minute window. This short window of time is not long enough to determine a full six parameter orbit so usually a circular orbit is assumed. A longer arc of time is necessary to determine eccentricity and to look for changes in the orbit with time. MODEST can follow objects in real-time, but only at the price of stopping survey operations. A second telescope would allow for longer arcs of orbit to obtain the full six orbital parameters, as well as assess the changes over time. An additional benefit of having a second telescope is the capability of obtaining BVRI colors of the faint targets, aiding efforts to determine the material type of faint debris. For 14 nights in March 2007, two telescopes were used simultaneously to observe the GEO debris field. MODEST was used exclusively in survey mode. As objects were detected, they were handed off in near real-time to the Cerro Tololo 0.9-m telescope for follow-up observations. The goal was to determine orbits and colors for all objects fainter than R = 15th magnitude (corresponds to 1 meter in size assuming a 0.2 albedo) detected by MODEST. The hand-off process was completely functional during the final eight nights and follow-ups for objects from night-to-night were possible. The cutoff magnitude level of 15th was selected on the basis of an abrupt change in the observed angular rate distribution in the MODEST surveys. Objects brighter than 15th magnitude tend to lie on a well defined locus in the angular rate plane (and have orbits in the catalog), while fainter objects fill the plane almost uniformly. We need to determine full six-parameter orbits to investigate what causes this change in observed angular rates. Are these faint objects either the same population of high area-to-mass (A/M) objects on eccentric orbits as discovered by the ESA Space Debris Telescope (Schildknecht, et al. 2004), or are they just normal debris from breakups in GEO?

Real-time visual tracking of less textured three-dimensional objects on mobile platforms

NASA Astrophysics Data System (ADS)

Seo, Byung-Kuk; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

2012-12-01

Natural feature-based approaches are still challenging for mobile applications (e.g., mobile augmented reality), because they are feasible only in limited environments such as highly textured and planar scenes/objects, and they need powerful mobile hardware for fast and reliable tracking. In many cases where conventional approaches are not effective, three-dimensional (3-D) knowledge of target scenes would be beneficial. We present a well-established framework for real-time visual tracking of less textured 3-D objects on mobile platforms. Our framework is based on model-based tracking that efficiently exploits partially known 3-D scene knowledge such as object models and a background's distinctive geometric or photometric knowledge. Moreover, we elaborate on implementation in order to make it suitable for real-time vision processing on mobile hardware. The performance of the framework is tested and evaluated on recent commercially available smartphones, and its feasibility is shown by real-time demonstrations.

Video enhancement workbench: an operational real-time video image processing system

NASA Astrophysics Data System (ADS)

Yool, Stephen R.; Van Vactor, David L.; Smedley, Kirk G.

1993-01-01

Video image sequences can be exploited in real-time, giving analysts rapid access to information for military or criminal investigations. Video-rate dynamic range adjustment subdues fluctuations in image intensity, thereby assisting discrimination of small or low- contrast objects. Contrast-regulated unsharp masking enhances differentially shadowed or otherwise low-contrast image regions. Real-time removal of localized hotspots, when combined with automatic histogram equalization, may enhance resolution of objects directly adjacent. In video imagery corrupted by zero-mean noise, real-time frame averaging can assist resolution and location of small or low-contrast objects. To maximize analyst efficiency, lengthy video sequences can be screened automatically for low-frequency, high-magnitude events. Combined zoom, roam, and automatic dynamic range adjustment permit rapid analysis of facial features captured by video cameras recording crimes in progress. When trying to resolve small objects in murky seawater, stereo video places the moving imagery in an optimal setting for human interpretation.

Objective speech quality evaluation of real-time speech coders

NASA Astrophysics Data System (ADS)

Viswanathan, V. R.; Russell, W. H.; Huggins, A. W. F.

1984-02-01

This report describes the work performed in two areas: subjective testing of a real-time 16 kbit/s adaptive predictive coder (APC) and objective speech quality evaluation of real-time coders. The speech intelligibility of the APC coder was tested using the Diagnostic Rhyme Test (DRT), and the speech quality was tested using the Diagnostic Acceptability Measure (DAM) test, under eight operating conditions involving channel error, acoustic background noise, and tandem link with two other coders. The test results showed that the DRT and DAM scores of the APC coder equalled or exceeded the corresponding test scores fo the 32 kbit/s CVSD coder. In the area of objective speech quality evaluation, the report describes the development, testing, and validation of a procedure for automatically computing several objective speech quality measures, given only the tape-recordings of the input speech and the corresponding output speech of a real-time speech coder.

Real-Time Polymerase Chain Reaction Detection of Angiostrongylus cantonensis DNA in Cerebrospinal Fluid from Patients with Eosinophilic Meningitis.

PubMed

Qvarnstrom, Yvonne; Xayavong, Maniphet; da Silva, Ana Cristina Aramburu; Park, Sarah Y; Whelen, A Christian; Calimlim, Precilia S; Sciulli, Rebecca H; Honda, Stacey A A; Higa, Karen; Kitsutani, Paul; Chea, Nora; Heng, Seng; Johnson, Stuart; Graeff-Teixeira, Carlos; Fox, LeAnne M; da Silva, Alexandre J

2016-01-01

Angiostrongylus cantonensis is the most common infectious cause of eosinophilic meningitis. Timely diagnosis of these infections is difficult, partly because reliable laboratory diagnostic methods are unavailable. The aim of this study was to evaluate the usefulness of a real-time polymerase chain reaction (PCR) assay for the detection of A. cantonensis DNA in human cerebrospinal fluid (CSF) specimens. A total of 49 CSF specimens from 33 patients with eosinophilic meningitis were included: A. cantonensis DNA was detected in 32 CSF specimens, from 22 patients. Four patients had intermittently positive and negative real-time PCR results on subsequent samples, indicating that the level of A. cantonensis DNA present in CSF may fluctuate during the course of the illness. Immunodiagnosis and/or supplemental PCR testing supported the real-time PCR findings for 30 patients. On the basis of these observations, this real-time PCR assay can be useful to detect A. cantonensis in the CSF from patients with eosinophilic meningitis. © The American Society of Tropical Medicine and Hygiene.

Real-time EEG-based detection of fatigue driving danger for accident prediction.

PubMed

Wang, Hong; Zhang, Chi; Shi, Tianwei; Wang, Fuwang; Ma, Shujun

2015-03-01

This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

Five-dimensional ultrasound system for soft tissue visualization.

PubMed

Deshmukh, Nishikant P; Caban, Jesus J; Taylor, Russell H; Hager, Gregory D; Boctor, Emad M

2015-12-01

A five-dimensional ultrasound (US) system is proposed as a real-time pipeline involving fusion of 3D B-mode data with the 3D ultrasound elastography (USE) data as well as visualization of these fused data and a real-time update capability over time for each consecutive scan. 3D B-mode data assist in visualizing the anatomy of the target organ, and 3D elastography data adds strain information. We investigate the feasibility of such a system and show that an end-to-end real-time system, from acquisition to visualization, can be developed. We present a system that consists of (a) a real-time 3D elastography algorithm based on a normalized cross-correlation (NCC) computation on a GPU; (b) real-time 3D B-mode acquisition and network transfer; (c) scan conversion of 3D elastography and B-mode volumes (if acquired by 4D wobbler probe); and (d) visualization software that fuses, visualizes, and updates 3D B-mode and 3D elastography data in real time. We achieved a speed improvement of 4.45-fold for the threaded version of the NCC-based 3D USE versus the non-threaded version. The maximum speed was 79 volumes/s for 3D scan conversion. In a phantom, we validated the dimensions of a 2.2-cm-diameter sphere scan-converted to B-mode volume. Also, we validated the 5D US system visualization transfer function and detected 1- and 2-cm spherical objects (phantom lesion). Finally, we applied the system to a phantom consisting of three lesions to delineate the lesions from the surrounding background regions of the phantom. A 5D US system is achievable with real-time performance. We can distinguish between hard and soft areas in a phantom using the transfer functions.

Development of real-time PCR and loop-mediated isothermal amplification (LAMP) assays for the differential detection of digital dermatitis associated treponemes.

PubMed

Anklam, Kelly; Kulow, Megan; Yamazaki, Wataru; Döpfer, Dörte

2017-01-01

Bovine digital dermatitis (DD) is a severe infectious cause of lameness in cattle worldwide, with important economic and welfare consequences. There are three treponeme phylogroups (T. pedis, T. phagedenis, and T. medium) that are implicated in playing an important causative role in DD. This study was conducted to develop real-time PCR and loop-mediated isothermal amplification (LAMP) assays for the detection and differentiation of the three treponeme phylogroups associated with DD. The real-time PCR treponeme phylogroup assays targeted the 16S-23S rDNA intergenic space (ITS) for T. pedis and T. phagedenis, and the flagellin gene (flaB2) for T. medium. The 3 treponeme phylogroup LAMP assays targeted the flagellin gene (flaB2) and the 16S rRNA was targeted for the Treponeme ssp. LAMP assay. The real-time PCR and LAMP assays correctly detected the target sequence of all control strains examined, and no cross-reactions were observed, representing 100% specificity. The limit of detection for each of the three treponeme phylogroup real-time PCR and LAMP assays was ≤ 70 fg/μl. The detection limit for the Treponema spp. LAMP assay ranged from 7-690 fg/μl depending on phylogroup. Treponemes were isolated from 40 DD lesion biopsies using an immunomagnetic separation culture method. The treponeme isolation samples were then subjected to the real-time PCR and LAMP assays for analysis. The treponeme phylogroup real-time PCR and LAMP assay results had 100% agreement, matching on all isolation samples. These results indicate that the developed assays are a sensitive and specific test for the detection and differentiation of the three main treponeme phylogroups implicated in DD.

Development of real-time PCR and loop-mediated isothermal amplification (LAMP) assays for the differential detection of digital dermatitis associated treponemes

PubMed Central

Kulow, Megan; Yamazaki, Wataru; Döpfer, Dörte

2017-01-01

Bovine digital dermatitis (DD) is a severe infectious cause of lameness in cattle worldwide, with important economic and welfare consequences. There are three treponeme phylogroups (T. pedis, T. phagedenis, and T. medium) that are implicated in playing an important causative role in DD. This study was conducted to develop real-time PCR and loop-mediated isothermal amplification (LAMP) assays for the detection and differentiation of the three treponeme phylogroups associated with DD. The real-time PCR treponeme phylogroup assays targeted the 16S-23S rDNA intergenic space (ITS) for T. pedis and T. phagedenis, and the flagellin gene (flaB2) for T. medium. The 3 treponeme phylogroup LAMP assays targeted the flagellin gene (flaB2) and the 16S rRNA was targeted for the Treponeme ssp. LAMP assay. The real-time PCR and LAMP assays correctly detected the target sequence of all control strains examined, and no cross-reactions were observed, representing 100% specificity. The limit of detection for each of the three treponeme phylogroup real-time PCR and LAMP assays was ≤ 70 fg/μl. The detection limit for the Treponema spp. LAMP assay ranged from 7–690 fg/μl depending on phylogroup. Treponemes were isolated from 40 DD lesion biopsies using an immunomagnetic separation culture method. The treponeme isolation samples were then subjected to the real-time PCR and LAMP assays for analysis. The treponeme phylogroup real-time PCR and LAMP assay results had 100% agreement, matching on all isolation samples. These results indicate that the developed assays are a sensitive and specific test for the detection and differentiation of the three main treponeme phylogroups implicated in DD. PMID:28542573

Advanced miniature processing handware for ATR applications

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Buried object detection in GPR images

DOEpatents

Paglieroni, David W; Chambers, David H; Bond, Steven W; Beer, W. Reginald

2014-04-29

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning.

PubMed

Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

Real-Time Joint Streaming Data Processing from Social and Physical Sensors

NASA Astrophysics Data System (ADS)

Kropivnitskaya, Y. Y.; Qin, J.; Tiampo, K. F.; Bauer, M.

2014-12-01

The results of the technological breakthroughs in computing that have taken place over the last few decades makes it possible to achieve emergency management objectives that focus on saving human lives and decreasing economic effects. In particular, the integration of a wide variety of information sources, including observations from spatially-referenced physical sensors and new social media sources, enables better real-time seismic hazard analysis through distributed computing networks. The main goal of this work is to utilize innovative computational algorithms for better real-time seismic risk analysis by integrating different data sources and processing tools into streaming and cloud computing applications. The Geological Survey of Canada operates the Canadian National Seismograph Network (CNSN) with over 100 high-gain instruments and 60 low-gain or strong motion seismographs. The processing of the continuous data streams from each station of the CNSN provides the opportunity to detect possible earthquakes in near real-time. The information from physical sources is combined to calculate a location and magnitude for an earthquake. The automatically calculated results are not always sufficiently precise and prompt that can significantly reduce the response time to a felt or damaging earthquake. Social sensors, here represented as Twitter users, can provide information earlier to the general public and more rapidly to the emergency planning and disaster relief agencies. We introduce joint streaming data processing from social and physical sensors in real-time based on the idea that social media observations serve as proxies for physical sensors. By using the streams of data in the form of Twitter messages, each of which has an associated time and location, we can extract information related to a target event and perform enhanced analysis by combining it with physical sensor data. Results of this work suggest that the use of data from social media, in conjunction with the development of innovative computing algorithms, when combined with sensor data can provide a new paradigm for real-time earthquake detection in order to facilitate rapid and inexpensive natural risk reduction.

Method for Real-Time Model Based Structural Anomaly Detection

NASA Technical Reports Server (NTRS)

Urnes, James M., Sr. (Inventor); Smith, Timothy A. (Inventor); Reichenbach, Eric Y. (Inventor)

2015-01-01

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Development of novel algorithm and real-time monitoring ambulatory system using Bluetooth module for fall detection in the elderly.

PubMed

Hwang, J Y; Kang, J M; Jang, Y W; Kim, H

2004-01-01

Novel algorithm and real-time ambulatory monitoring system for fall detection in elderly people is described. Our system is comprised of accelerometer, tilt sensor and gyroscope. For real-time monitoring, we used Bluetooth. Accelerometer measures kinetic force, tilt sensor and gyroscope estimates body posture. Also, we suggested algorithm using signals which obtained from the system attached to the chest for fall detection. To evaluate our system and algorithm, we experimented on three people aged over 26 years. The experiment of four cases such as forward fall, backward fall, side fall and sit-stand was repeated ten times and the experiment in daily life activity was performed one time to each subject. These experiments showed that our system and algorithm could distinguish between falling and daily life activity. Moreover, the accuracy of fall detection is 96.7%. Our system is especially adapted for long-time and real-time ambulatory monitoring of elderly people in emergency situation.

Automatic guidance of attention during real-world visual search

PubMed Central

Seidl-Rathkopf, Katharina N.; Turk-Browne, Nicholas B.; Kastner, Sabine

2015-01-01

Looking for objects in cluttered natural environments is a frequent task in everyday life. This process can be difficult, as the features, locations, and times of appearance of relevant objects are often not known in advance. A mechanism by which attention is automatically biased toward information that is potentially relevant may thus be helpful. Here we tested for such a mechanism across five experiments by engaging participants in real-world visual search and then assessing attentional capture for information that was related to the search set but was otherwise irrelevant. Isolated objects captured attention while preparing to search for objects from the same category embedded in a scene, as revealed by lower detection performance (Experiment 1A). This capture effect was driven by a central processing bottleneck rather than the withdrawal of spatial attention (Experiment 1B), occurred automatically even in a secondary task (Experiment 2A), and reflected enhancement of matching information rather than suppression of non-matching information (Experiment 2B). Finally, attentional capture extended to objects that were semantically associated with the target category (Experiment 3). We conclude that attention is efficiently drawn towards a wide range of information that may be relevant for an upcoming real-world visual search. This mechanism may be adaptive, allowing us to find information useful for our behavioral goals in the face of uncertainty. PMID:25898897

Use of real-time quantitative PCR to detect Chlamydophila felis infection.

PubMed

Helps, C; Reeves, N; Tasker, S; Harbour, D

2001-07-01

A real-time PCR assay was developed to detect and quantify Chlamydophila felis infection of cats. The assay uses a molecular beacon to specifically identify the major outer membrane protein gene, is highly reproducible, and is able to detect fewer than 10 genomic copies.

Real-time biscuit tile image segmentation method based on edge detection.

PubMed

Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

2018-05-01

In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Security Event Recognition for Visual Surveillance

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Pregnancy rates of beef cattle are not affected by Campylobacter fetus subsp. venerealis real-time PCR-positive breeding sires in New Zealand.

PubMed

Sanhueza, J M; Heuer, C; Jackson, R; Hughes, P; Anderson, P; Kelly, K; Walker, G

2014-09-01

Campylobacter fetus subspecies venerealis (C. fetus venerealis) is the causal agent of bovine genital campylobacteriosis, a venereal disease that is asymptomatic in bulls but responsible for reproductive wastage in female cattle. In New Zealand, a commercial real-time PCR assay was introduced in 2007 to identify the DNA of this pathogen in preputial scrapings; however, concerns were raised about the specificity of the test following anecdotal reports of a high number of test-positive bulls with no apparent relationship to reproductive performance. The objective of this study, therefore, was to examine the association between real-time PCR assay results from beef breeding bulls and pregnancy rates in beef herds using these bulls. Veterinarians from four veterinary practices selected beef cattle herds with relatively high and low pregnancy rates between December 2008 and February 2009. Preputial scrapings were collected from bulls used for mating in those herds. Samples were tested using the real-time PCR assay under consideration. Bivariable and multivariable analyses were used to assess the relationship between pregnancy rates in each mob (15-month-old heifers, 27-month-old heifers and mixed-age cows) and the percentage of real-time PCR-positive bulls in each mob. Sixty-four (28.8%) of 222 bulls tested positive, 130 (58.6%) tested negative, and 28 (12.6%) returned an inconclusive result to the real-time PCR assay. The percentage of bulls testing real-time PCR-positive in these mobs was not associated with pregnancy rates (p=0.757) after controlling for mob, average body condition score of cows, cow to bull ratio, length of the mating period, and farm. Real-time PCR assay results were not associated with pregnancy rates, suggesting that the specificity of the real-time PCR assay was too low to be used to reliably detect C. fetus venerealis. This study adds to a growing body of evidence indicating that C. fetus venerealis strains are either absent from, or present at clinically insignificant levels of endemicity among, beef breeding herds in New Zealand. The real-time PCR assay that was assessed in this study should not be used for the detection of C. fetus venerealis in bulls or for investigations of low conception rates in cattle in New Zealand. During the course of this survey, sequencing analysis of an apparent C. fetus venerealis isolate from the intestines of a Friesian bull turned out to be Campylobacter hyointestinalis. As a consequence, this real-time PCR assay for C. fetus venerealis is no longer being offered by diagnostic laboratories in New Zealand.

Overseas testing of a multisensor landmine detection system: results and lessons learned

NASA Astrophysics Data System (ADS)

Keranen, Joe G.; Topolosky, Zeke

2009-05-01

The Nemesis detection system has been developed to provide an efficient and reliable unmanned, multi-sensor, groundbased platform to detect and mark landmines. The detection system consists of two detection sensor arrays: a Ground Penetrating Synthetic Aperture Radar (GPSAR) developed by Planning Systems, Inc. (PSI) and an electromagnetic induction (EMI) sensor array developed by Minelab Electronics, PTY. Limited. Under direction of the Night Vision and Electronic Sensors Directorate (NVESD), overseas testing was performed at Kampong Chhnang Test Center (KCTC), Cambodia, from May 12-30, 2008. Test objectives included: evaluation of detection performance, demonstration of real-time visualization and alarm generation, and evaluation of system operational efficiency. Testing was performed on five sensor test lanes, each consisting of a unique soil mixture and three off-road lanes which include curves, overgrowth, potholes, and non-uniform lane geometry. In this paper, we outline the test objectives, procedures, results, and lessons learned from overseas testing. We also describe the current state of the system, and plans for future enhancements and modifications including clutter rejection and feature-level fusion.

A Study on the Model of Detecting the Variation of Geomagnetic Intensity Based on an Adapted Motion Strategy.

PubMed

Li, Hong; Liu, Mingyong; Liu, Kun; Zhang, Feihu

2017-12-25

By simulating the geomagnetic fields and analyzing thevariation of intensities, this paper presents a model for calculating the objective function ofan Autonomous Underwater Vehicle (AUV)geomagnetic navigation task. By investigating the biologically inspired strategies, the AUV successfullyreachesthe destination duringgeomagnetic navigation without using the priori geomagnetic map. Similar to the pattern of a flatworm, the proposed algorithm relies on a motion pattern to trigger a local searching strategy by detecting the real-time geomagnetic intensity. An adapted strategy is then implemented, which is biased on the specific target. The results show thereliabilityandeffectivenessofthe proposed algorithm.

Real-time automatic fiducial marker tracking in low contrast cine-MV images

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

Lin, Wei-Yang; Lin, Shu-Fang; Yang, Sheng-Chang

2013-01-15

Purpose: To develop a real-time automatic method for tracking implanted radiographic markers in low-contrast cine-MV patient images used in image-guided radiation therapy (IGRT). Methods: Intrafraction motion tracking using radiotherapy beam-line MV images have gained some attention recently in IGRT because no additional imaging dose is introduced. However, MV images have much lower contrast than kV images, therefore a robust and automatic algorithm for marker detection in MV images is a prerequisite. Previous marker detection methods are all based on template matching or its derivatives. Template matching needs to match object shape that changes significantly for different implantation and projection angle.more » While these methods require a large number of templates to cover various situations, they are often forced to use a smaller number of templates to reduce the computation load because their methods all require exhaustive search in the region of interest. The authors solve this problem by synergetic use of modern but well-tested computer vision and artificial intelligence techniques; specifically the authors detect implanted markers utilizing discriminant analysis for initialization and use mean-shift feature space analysis for sequential tracking. This novel approach avoids exhaustive search by exploiting the temporal correlation between consecutive frames and makes it possible to perform more sophisticated detection at the beginning to improve the accuracy, followed by ultrafast sequential tracking after the initialization. The method was evaluated and validated using 1149 cine-MV images from two prostate IGRT patients and compared with manual marker detection results from six researchers. The average of the manual detection results is considered as the ground truth for comparisons. Results: The average root-mean-square errors of our real-time automatic tracking method from the ground truth are 1.9 and 2.1 pixels for the two patients (0.26 mm/pixel). The standard deviations of the results from the 6 researchers are 2.3 and 2.6 pixels. The proposed framework takes about 128 ms to detect four markers in the first MV images and about 23 ms to track these markers in each of the subsequent images. Conclusions: The unified framework for tracking of multiple markers presented here can achieve marker detection accuracy similar to manual detection even in low-contrast cine-MV images. It can cope with shape deformations of fiducial markers at different gantry angles. The fast processing speed reduces the image processing portion of the system latency, therefore can improve the performance of real-time motion compensation.« less

Real-time, in-situ detection of volatile profiles for the prevention of aflatoxin fungal contamination in pistachios

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

Bond, Tiziana C.; Chang, Allan; Zhou, Jenny

The objective in this project is to provide a proof of concept will demonstrate the feasibility of a Raman, in-situ warning system for detecting and removing developing fungal hot spots from pistachio stockpiles and transit containers, thus decreasing human health risks and product loss as a result of contamination. The proposed project has the following goals: to calibrate the Raman fingerprinting of biomarkers, standalone and in premixed samples, to build a database with the vibrational profiles distinctive to the signatures of the bouquet emitted by the contaminated pistachios; to test the improvement in the detection of the detectable markers withmore » enhanced Raman on a small probe.« less

Improvement in QEPAS system utilizing a second harmonic based wavelength calibration technique

NASA Astrophysics Data System (ADS)

Zhang, Qinduan; Chang, Jun; Wang, Fupeng; Wang, Zongliang; Xie, Yulei; Gong, Weihua

2018-05-01

A simple laser wavelength calibration technique, based on second harmonic signal, is demonstrated in this paper to improve the performance of quartz enhanced photoacoustic spectroscopy (QEPAS) gas sensing system, e.g. improving the signal to noise ratio (SNR), detection limit and long-term stability. Constant current, corresponding to the gas absorption line, combining f/2 frequency sinusoidal signal are used to drive the laser (constant driving mode), a software based real-time wavelength calibration technique is developed to eliminate the wavelength drift due to ambient fluctuations. Compared to conventional wavelength modulation spectroscopy (WMS), this method allows lower filtering bandwidth and averaging algorithm applied to QEPAS system, improving SNR and detection limit. In addition, the real-time wavelength calibration technique guarantees the laser output is modulated steadily at gas absorption line. Water vapor is chosen as an objective gas to evaluate its performance compared to constant driving mode and conventional WMS system. The water vapor sensor was designed insensitive to the incoherent external acoustic noise by the numerical averaging technique. As a result, the SNR increases 12.87 times in wavelength calibration technique based system compared to conventional WMS system. The new system achieved a better linear response (R2 = 0 . 9995) in concentration range from 300 to 2000 ppmv, and achieved a minimum detection limit (MDL) of 630 ppbv.

A real-time robot arm collision detection system

NASA Technical Reports Server (NTRS)

Shaffer, Clifford A.; Herb, Gregory M.

1990-01-01

A data structure and update algorithm are presented for a prototype real time collision detection safety system for a multi-robot environment. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3-D space into eight equal cubic octants until each octant meets some decomposition criteria. The octree stores cylspheres (cylinders with spheres on each end) and rectangular solids as primitives (other primitives can easily be added as required). These primitives make up the two seven degrees-of-freedom robot arms and environment modeled by the system. Octree nodes containing more than a predetermined number N of primitives are decomposed. This rule keeps the octree small, as the entire environment for the application can be modeled using a few dozen primitives. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Incidents in which one robot arm comes too close to another arm or an object are reported. Cycle time for interpreting current joint angles, updating the octree, and detecting/reporting imminent collisions averages 30 milliseconds on an Intel 80386 processor running at 20 MHz.

Real-time edge tracking using a tactile sensor

NASA Technical Reports Server (NTRS)

Berger, Alan D.; Volpe, Richard; Khosla, Pradeep K.

1989-01-01

Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented.

Networked localization of sniper shots using acoustics

NASA Astrophysics Data System (ADS)

Hengy, S.; Hamery, P.; De Mezzo, S.; Duffner, P.

2011-06-01

The presence of snipers in modern conflicts leads to high insecurity for the soldiers. In order to improve the soldier's protection against this threat, the French German Research Institute of Saint-Louis (ISL) initiated studies in the domain of acoustic localization of shots. Mobile antennas mounted on the soldier's helmet were initially used for real-time detection, classification and localization of sniper shots. It showed good performances in land scenarios, but also in urban scenarios if the array was in the shot corridor, meaning that the microphones first detect the direct wave and then the reflections of the Mach and muzzle waves. As soon as the acoustic arrays were not near to the shot corridor (only reflections are detected) this solution lost its efficiency and erroneous estimated position were given. In order to estimate the position of the shooter in every kind of urban scenario, ISL started studying time reversal techniques. Knowing the position of every reflective object in the environment (buildings, walls, ...) it should be possible to estimate the position of the shooter. First, a synthetic propagation algorithm has been developed and validated for real scale applications. It has then been validated for small scale models, allowing us to test our time reversal based algorithms in our laboratory. In this paper we discuss all the challenges that are induced by the application of sniper detection using time reversal techniques. We will discuss all the hard points that can be encountered and try to find some solutions in order to optimize the use of this technique.

Independent motion detection with a rival penalized adaptive particle filter

NASA Astrophysics Data System (ADS)

Becker, Stefan; Hübner, Wolfgang; Arens, Michael

2014-10-01

Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic filter for real-time detection and tracking of independently moving objects. The proposed approach introduces a competition scheme between particles in order to ensure an improved multi-modality. Further, the filter design helps to generate a particle distribution which is homogenous even in the presence of multiple targets showing non-rigid motion patterns. The effectiveness of the method is shown on exemplary outdoor sequences.

Development of duplex real-time RT-PCR based on Taqman technology for detecting simultaneously the genome of pan-enterovirus and enterovirus 71.

PubMed

Hwang, Seoyeon; Kang, Byunghak; Hong, Jiyoung; Kim, Ahyoun; Kim, Hyejin; Kim, Kisang; Cheon, Doo-Sung

2013-07-01

Human enterovirus (EV) 71 is the main etiological agent of hand, foot, and mouth disease (HFMD). It is associated with neurological complications, and caused fatalities during recent outbreaks in the Asia-Pacific region. Infections caused by EV71 could lead to many complications, ranging from brainstem encephalitis to pulmonary oedema, resulting in high mortality. In this study, a duplex real-time RT-PCR assay was developed in order to simultaneously detect pan-EV and EV71. EV71-specific primers and probes were designed based on the highly conserved VP1 region of EV71. Five EV71 strains were detected as positive, and no positive fluorescence signal was observed in the duplex real-time RT-PCR for other viral RNA, which showed 100% specificity for the selected panel, and no cross-reactions were observed in this duplex real-time RT-PCR. The EV71-specific duplex real-time RT-PCR was more sensitive than conventional RT-PCR, and detected viral titers that were 10-fold lower than those measured by the latter. Of the 381 HFMD clinical specimens, 196 (51.4%) cases were pan-EV-positive, of which 170 (86.7%) were EV71-positive when tested by pan-EV and EV71-specific duplex real-time RT-PCR. EV71-specific duplex real-time RT-PCR offers a rapid and sensitive method to detect EV71 from clinical specimens, and will allow quarantine measures to be taken more effectively during outbreaks. Copyright © 2013 Wiley Periodicals, Inc.

Rapid detection method for Bacillus anthracis using a combination of multiplexed real-time PCR and pyrosequencing and its application for food biodefense.

PubMed

Janzen, Timothy W; Thomas, Matthew C; Goji, Noriko; Shields, Michael J; Hahn, Kristen R; Amoako, Kingsley K

2015-02-01

Bacillus anthracis, the causative agent of anthrax, has the capacity to form highly resilient spores as part of its life cycle. The potential for the dissemination of these spores using food as a vehicle is a huge public health concern and, hence, requires the development of a foodborne bioterrorism response approach. In this work, we address a critical gap in food biodefense by presenting a novel, combined, sequential method involving the use of real-time PCR and pyrosequencing for the rapid, specific detection of B. anthracis spores in three food matrices: milk, apple juice, and bottled water. The food samples were experimentally inoculated with 40 CFU ml(-1), and DNA was extracted from the spores and analyzed after immunomagnetic separation. Applying the combination of multiplex real-time PCR and pyrosequencing, we successfully detected the presence of targets on both of the virulence plasmids and the chromosome. The results showed that DNA amplicons generated from a five-target multiplexed real-time PCR detection using biotin-labeled primers can be used for single-plex pyrosequencing detection. The combined use of multiplexed real-time PCR and pyrosequencing is a novel, rapid detection method for B. anthracis from food and provides a tool for accurate, quantitative identification with potential biodefense applications.

A method for real-time visual stimulus selection in the study of cortical object perception.

PubMed

Leeds, Daniel D; Tarr, Michael J

2016-06-01

The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit's image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across pre-determined 1cm(3) rain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds et al., 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) real-time estimation of cortical responses to stimuli is reasonably consistent; 3) search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond. Copyright © 2016 Elsevier Inc. All rights reserved.

A method for real-time visual stimulus selection in the study of cortical object perception

PubMed Central

Leeds, Daniel D.; Tarr, Michael J.

2016-01-01

The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit’s image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across predetermined 1 cm3 brain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) Real-time estimation of cortical responses to stimuli are reasonably consistent; 3) Search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond. PMID:26973168

Rapid Diagnosis of Tuberculosis by Real-Time High-Resolution Imaging of Mycobacterium tuberculosis Colonies.

PubMed

Ghodbane, Ramzi; Asmar, Shady; Betzner, Marlena; Linet, Marie; Pierquin, Joseph; Raoult, Didier; Drancourt, Michel

2015-08-01

Culture remains the cornerstone of diagnosis for pulmonary tuberculosis, but the fastidiousness of Mycobacterium tuberculosis may delay culture-based diagnosis for weeks. We evaluated the performance of real-time high-resolution imaging for the rapid detection of M. tuberculosis colonies growing on a solid medium. A total of 50 clinical specimens, including 42 sputum specimens, 4 stool specimens, 2 bronchoalveolar lavage fluid specimens, and 2 bronchial aspirate fluid specimens were prospectively inoculated into (i) a commercially available Middlebrook broth and evaluated for mycobacterial growth indirectly detected by measuring oxygen consumption (standard protocol) and (ii) a home-made solid medium incubated in an incubator featuring real-time high-resolution imaging of colonies (real-time protocol). Isolates were identified by Ziehl-Neelsen staining and matrix-assisted laser desorption ionization-time of flight mass spectrometry. Use of the standard protocol yielded 14/50 (28%) M. tuberculosis isolates, which is not significantly different from the 13/50 (26%) M. tuberculosis isolates found using the real-time protocol (P = 1.00 by Fisher's exact test), and the contamination rate of 1/50 (2%) was not significantly different from the contamination rate of 2/50 (4%) using the real-time protocol (P = 1.00). The real-time imaging protocol showed a 4.4-fold reduction in time to detection, 82 ± 54 h versus 360 ± 142 h (P < 0.05). These preliminary data give the proof of concept that real-time high-resolution imaging of M. tuberculosis colonies is a new technology that shortens the time to growth detection and the laboratory diagnosis of pulmonary tuberculosis. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

SSME propellant path leak detection real-time

NASA Technical Reports Server (NTRS)

Crawford, R. A.; Smith, L. M.

1994-01-01

Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

Demonstrating the Value of Near Real-time Satellite-based Earth Observations in a Research and Education Framework

NASA Astrophysics Data System (ADS)

Chiu, L.; Hao, X.; Kinter, J. L.; Stearn, G.; Aliani, M.

2017-12-01

The launch of GOES-16 series provides an opportunity to advance near real-time applications in natural hazard detection, monitoring and warning. This study demonstrates the capability and values of receiving real-time satellite-based Earth observations over a fast terrestrial networks and processing high-resolution remote sensing data in a university environment. The demonstration system includes 4 components: 1) Near real-time data receiving and processing; 2) data analysis and visualization; 3) event detection and monitoring; and 4) information dissemination. Various tools are developed and integrated to receive and process GRB data in near real-time, produce images and value-added data products, and detect and monitor extreme weather events such as hurricane, fire, flooding, fog, lightning, etc. A web-based application system is developed to disseminate near-real satellite images and data products. The images are generated with GIS-compatible format (GeoTIFF) to enable convenient use and integration in various GIS platforms. This study enhances the capacities for undergraduate and graduate education in Earth system and climate sciences, and related applications to understand the basic principles and technology in real-time applications with remote sensing measurements. It also provides an integrated platform for near real-time monitoring of extreme weather events, which are helpful for various user communities.

SYBR Green Real-Time PCR Method To Detect Clostridium botulinum Type A▿

PubMed Central

Fenicia, Lucia; Anniballi, Fabrizio; De Medici, Dario; Delibato, Elisabetta; Aureli, Paolo

2007-01-01

Botulinum toxins (BoNTs) are classically produced by Clostridium botulinum but rarely also from neurotoxigenic strains of Clostridium baratii and Clostridium butyricum. BoNT type A (BoNT/A), BoNT/B, BoNT/E, and very rarely BoNT/F are mainly responsible for human botulism. Standard microbiological methods take into consideration only the detection of C. botulinum. The presumptive identification of the toxigenic strains together with the typing of BoNT has to be performed by mouse bioassay. The development of PCR-based methods for the detection and typing of BoNT-producing clostridia would be an ideal alternative to the mouse bioassay. The objective of this study was to develop a rapid and robust real-time PCR method for detecting C. botulinum type A. Four different techniques for the extraction and purification of DNA from cultured samples were initially compared. Of the techniques used, Chelex 100, DNeasy tissue kit, InstaGene matrix DNA, and boiling, the boiling technique was significantly less efficient than the other three. These did not give statistically different results, and Chelex 100 was chosen because it was less expensive than the others. In order to eliminate any false-negative results, an internal amplification control was synthesized and included in the amplification mixture according to ISO 22174. The specificity of the method was tested against 75 strains of C. botulinum type A, 4 strains of C. botulinum type Ab, and 101 nontarget strains. The detection limit of the reaction was less than 6 × 101 copies of C. botulinum type A DNA. The robustness of the method was confirmed using naturally contaminated stool specimens to evaluate the tolerance of inhibitor substances. SYBR green real-time PCR showed very high specificity for the detection of C. botulinum types A and Ab (inclusivity and exclusivity, 100%). PMID:17369349

ALLFlight: detection of moving objects in IR and ladar images

NASA Astrophysics Data System (ADS)

Doehler, H.-U.; Peinecke, Niklas; Lueken, Thomas; Schmerwitz, Sven

2013-05-01

Supporting a helicopter pilot during landing and takeoff in degraded visual environment (DVE) is one of the challenges within DLR's project ALLFlight (Assisted Low Level Flight and Landing on Unprepared Landing Sites). Different types of sensors (TV, Infrared, mmW radar and laser radar) are mounted onto DLR's research helicopter FHS (flying helicopter simulator) for gathering different sensor data of the surrounding world. A high performance computer cluster architecture acquires and fuses all the information to get one single comprehensive description of the outside situation. While both TV and IR cameras deliver images with frame rates of 25 Hz or 30 Hz, Ladar and mmW radar provide georeferenced sensor data with only 2 Hz or even less. Therefore, it takes several seconds to detect or even track potential moving obstacle candidates in mmW or Ladar sequences. Especially if the helicopter is flying with higher speed, it is very important to minimize the detection time of obstacles in order to initiate a re-planning of the helicopter's mission timely. Applying feature extraction algorithms on IR images in combination with data fusion algorithms of extracted features and Ladar data can decrease the detection time appreciably. Based on real data from flight tests, the paper describes applied feature extraction methods for moving object detection, as well as data fusion techniques for combining features from TV/IR and Ladar data.

Real-time optical multiple object recognition and tracking system and method

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Liu, Hua Kuang (Inventor)

1987-01-01

The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.

Evaluation of Earthquake Detection Performance in Terms of Quality and Speed in SEISCOMP3 Using New Modules Qceval, Npeval and Sceval

NASA Astrophysics Data System (ADS)

Roessler, D.; Weber, B.; Ellguth, E.; Spazier, J.

2017-12-01

The geometry of seismic monitoring networks, site conditions and data availability as well as monitoring targets and strategies typically impose trade-offs between data quality, earthquake detection sensitivity, false detections and alert times. Network detection capabilities typically change with alteration of the seismic noise level by human activity or by varying weather and sea conditions. To give helpful information to operators and maintenance coordinators, gempa developed a range of tools to evaluate earthquake detection and network performance including qceval, npeval and sceval. qceval is a module which analyzes waveform quality parameters in real-time and deactivates and reactivates data streams based on waveform quality thresholds for automatic processing. For example, thresholds can be defined for latency, delay, timing quality, spikes and gaps count and rms. As changes in the automatic processing have a direct influence on detection quality and speed, another tool called "npeval" was designed to calculate in real-time the expected time needed to detect and locate earthquakes by evaluating the effective network geometry. The effective network geometry is derived from the configuration of stations participating in the detection. The detection times are shown as an additional layer on the map and updated in real-time as soon as the effective network geometry changes. Yet another new tool, "sceval", is an automatic module which classifies located seismic events (Origins) in real-time. sceval evaluates the spatial distribution of the stations contributing to an Origin. It confirms or rejects the status of Origins, adds comments or leaves the Origin unclassified. The comments are passed to an additional sceval plug-in where the end user can customize event types. This unique identification of real and fake events in earthquake catalogues allows to lower network detection thresholds. In real-time monitoring situations operators can limit the processing to events with unclassified Origins, reducing their workload. Classified Origins can be treated specifically by other procedures. These modules have been calibrated and fully tested by several complex seismic monitoring networks in the region of Indonesia and Northern Chile.

Multimarker Quantitative Real-Time PCR Detection of Circulating Melanoma Cells in Peripheral Blood: Relation to Disease Stage in Melanoma Patients

PubMed Central

Koyanagi, Kazuo; Kuo, Christine; Nakagawa, Taku; Mori, Takuji; Ueno, Hideaki; Lorico, Arnulfo R.; Wang, He-Jing; Hseuh, Eddie; O’Day, Steven J.; Hoon, Dave S.B.

2010-01-01

Background Detection of melanoma cells in circulation may be important in assessing tumor progression. The objective of this study was to develop a specific, reliable, multimarker quantitative real-time reverse transcription-PCR (qRT) assay for detecting melanoma cells in patients’ blood. Methods We developed qRT assays for the mRNA of four melanoma-associated markers: MART-1, GalNAc-T, PAX-3, and MAGE-A3. In optimization studies, we tested 17 melanoma cell lines and 49 peripheral blood leukocyte (PBL) samples from volunteers. We performed RNA and melanoma cell dilution studies to assess the detection limits and imprecision of the assays. We measured the mRNAs in blood specimens from 94 melanoma patients [American Joint Committee on Cancer (AJCC) stage I, n = 20; II, n = 20; III, n = 32; IV, n = 22]. Results All markers were frequently detected in melanoma cell lines, whereas none of the markers was detected in PBLs from volunteers. The qRT assay could detect 1 melanoma cell in 107 PBLs in the melanoma cell-dilution studies. Markers were detected in 15%, 30%, 75%, and 86% of melanoma patients with AJCC stage I, II, III, and IV disease, respectively. The number of positive markers and AJCC stage were significantly correlated (Spearman correlation coefficient = 0.58; P <0.0001). Conclusions Multimarker qRT can detect circulating melanoma cells in blood. Measurement of the studied molecular markers in blood may be useful in detection of metastasis and monitoring treatment response of melanoma patients. PMID:15817820

Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection.

PubMed

Sarikaya, Duygu; Corso, Jason J; Guru, Khurshid A

2017-07-01

Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos. To the best of our knowledge, this approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos. Our architecture applies a region proposal network (RPN) and a multimodal two stream convolutional network for object detection to jointly predict objectness and localization on a fusion of image and temporal motion cues. Our results with an average precision of 91% and a mean computation time of 0.1 s per test frame detection indicate that our study is superior to conventionally used methods for medical imaging while also emphasizing the benefits of using RPN for precision and efficiency. We also introduce a new data set, ATLAS Dione, for RAS video understanding. Our data set provides video data of ten surgeons from Roswell Park Cancer Institute, Buffalo, NY, USA, performing six different surgical tasks on the daVinci Surgical System (dVSS) with annotations of robotic tools per frame.

Real-time supernova neutrino burst monitor at Super-Kamiokande

NASA Astrophysics Data System (ADS)

Abe, K.; Haga, Y.; Hayato, Y.; Ikeda, M.; Iyogi, K.; Kameda, J.; Kishimoto, Y.; Miura, M.; Moriyama, S.; Nakahata, M.; Nakano, Y.; Nakayama, S.; Sekiya, H.; Shiozawa, M.; Suzuki, Y.; Takeda, A.; Tanaka, H.; Tomura, T.; Ueno, K.; Wendell, R. A.; Yokozawa, T.; Irvine, T.; Kajita, T.; Kametani, I.; Kaneyuki, K.; Lee, K. P.; McLachlan, T.; Nishimura, Y.; Richard, E.; Okumura, K.; Labarga, L.; Fernandez, P.; Berkman, S.; Tanaka, H. A.; Tobayama, S.; Gustafson, J.; Kearns, E.; Raaf, J. L.; Stone, J. L.; Sulak, L. R.; Goldhaber, M.; Carminati, G.; Kropp, W. R.; Mine, S.; Weatherly, P.; Renshaw, A.; Smy, M. B.; Sobel, H. W.; Takhistov, V.; Ganezer, K. S.; Hartfiel, B. L.; Hill, J.; Keig, W. E.; Hong, N.; Kim, J. Y.; Lim, I. T.; Akiri, T.; Himmel, A.; Scholberg, K.; Walter, C. W.; Wongjirad, T.; Ishizuka, T.; Tasaka, S.; Jang, J. S.; Learned, J. G.; Matsuno, S.; Smith, S. N.; Hasegawa, T.; Ishida, T.; Ishii, T.; Kobayashi, T.; Nakadaira, T.; Nakamura, K.; Oyama, Y.; Sakashita, K.; Sekiguchi, T.; Tsukamoto, T.; Suzuki, A. T.; Takeuchi, Y.; Bronner, C.; Hirota, S.; Huang, K.; Ieki, K.; Kikawa, T.; Minamino, A.; Murakami, A.; Nakaya, T.; Suzuki, K.; Takahashi, S.; Tateishi, K.; Fukuda, Y.; Choi, K.; Itow, Y.; Mitsuka, G.; Mijakowski, P.; Hignight, J.; Imber, J.; Jung, C. K.; Yanagisawa, C.; Wilking, M. J.; Ishino, H.; Kibayashi, A.; Koshio, Y.; Mori, T.; Sakuda, M.; Yamaguchi, R.; Yano, T.; Kuno, Y.; Tacik, R.; Kim, S. B.; Okazawa, H.; Choi, Y.; Nishijima, K.; Koshiba, M.; Suda, Y.; Totsuka, Y.; Yokoyama, M.; Martens, K.; Marti, Ll.; Vagins, M. R.; Martin, J. F.; de Perio, P.; Konaka, A.; Chen, S.; Zhang, Y.; Connolly, K.; Wilkes, R. J.

2016-08-01

We present a real-time supernova neutrino burst monitor at Super-Kamiokande (SK). Detecting supernova explosions by neutrinos in real time is crucial for giving a clear picture of the explosion mechanism. Since the neutrinos are expected to come earlier than light, a fast broadcasting of the detection may give astronomers a chance to make electromagnetic radiation observations of the explosions right at the onset. The role of the monitor includes a fast announcement of the neutrino burst detection to the world and a determination of the supernova direction. We present the online neutrino burst detection system and studies of the direction determination accuracy based on simulations at SK.

Development and validation of a duplex real-time PCR assay for the simultaneous detection of three mustard species (Sinapis alba, Brassica nigra and Brassica juncea) in food.

PubMed

Palle-Reisch, Monika; Cichna-Markl, Margit; Hochegger, Rupert

2014-06-15

The paper presents a duplex real-time PCR assay for the simultaneous detection of three potentially allergenic mustard species commonly used in food: white mustard (Sinapis alba), black mustard (Brassica nigra) and brown mustard (Brassica juncea). White mustard is detected in the "green" and black/brown mustard in the "yellow" channel. The duplex real-time PCR assay does not show cross-reactivity with other Brassicaceae species including broccoli, cauliflower, radish and rapeseed. Low cross-reactivities (difference in the Ct value ⩾ 11.91 compared with the positive control) were obtained with cumin, fenugreek, ginger, rye and turmeric. When applying 500 ng DNA per PCR tube, the duplex real-time PCR assay allowed the detection of white, black and brown mustard in brewed model sausages down to a concentration of 5mg/kg in 10 out of 10 replicates. The duplex real-time PCR assay was applied to verify correct labelling of commercial foodstuffs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integrated micro-optofluidic platform for real-time detection of airborne microorganisms

NASA Astrophysics Data System (ADS)

Choi, Jeongan; Kang, Miran; Jung, Jae Hee

2015-11-01

We demonstrate an integrated micro-optofluidic platform for real-time, continuous detection and quantification of airborne microorganisms. Measurements of the fluorescence and light scattering from single particles in a microfluidic channel are used to determine the total particle number concentration and the microorganism number concentration in real-time. The system performance is examined by evaluating standard particle measurements with various sample flow rates and the ratios of fluorescent to non-fluorescent particles. To apply this method to real-time detection of airborne microorganisms, airborne Escherichia coli, Bacillus subtilis, and Staphylococcus epidermidis cells were introduced into the micro-optofluidic platform via bioaerosol generation, and a liquid-type particle collection setup was used. We demonstrate successful discrimination of SYTO82-dyed fluorescent bacterial cells from other residue particles in a continuous and real-time manner. In comparison with traditional microscopy cell counting and colony culture methods, this micro-optofluidic platform is not only more accurate in terms of the detection efficiency for airborne microorganisms but it also provides additional information on the total particle number concentration.

Integrated micro-optofluidic platform for real-time detection of airborne microorganisms

PubMed Central

Choi, Jeongan; Kang, Miran; Jung, Jae Hee

2015-01-01

We demonstrate an integrated micro-optofluidic platform for real-time, continuous detection and quantification of airborne microorganisms. Measurements of the fluorescence and light scattering from single particles in a microfluidic channel are used to determine the total particle number concentration and the microorganism number concentration in real-time. The system performance is examined by evaluating standard particle measurements with various sample flow rates and the ratios of fluorescent to non-fluorescent particles. To apply this method to real-time detection of airborne microorganisms, airborne Escherichia coli, Bacillus subtilis, and Staphylococcus epidermidis cells were introduced into the micro-optofluidic platform via bioaerosol generation, and a liquid-type particle collection setup was used. We demonstrate successful discrimination of SYTO82-dyed fluorescent bacterial cells from other residue particles in a continuous and real-time manner. In comparison with traditional microscopy cell counting and colony culture methods, this micro-optofluidic platform is not only more accurate in terms of the detection efficiency for airborne microorganisms but it also provides additional information on the total particle number concentration. PMID:26522006

Rapid and reliable diagnostic method to detect Zika virus by real-time fluorescence reverse transcription loop-mediated isothermal amplification.

PubMed

Guo, Xu-Guang; Zhou, Yong-Zhuo; Li, Qin; Wang, Wei; Wen, Jin-Zhou; Zheng, Lei; Wang, Qian

2018-04-18

To detect Zika virus more rapidly and accurately, we developed a novel method that utilized a real-time fluorescence reverse transcription loop-mediated isothermal amplification (LAMP) technique. The NS5 gene was amplified by a set of six specific primers that recognized six distinct sequences. The amplification process, including 60 min of thermostatic reaction with Bst DNA polymerase following real-time fluorescence reverse transcriptase using genomic Zika virus standard strain (MR766), was conducted through fluorescent signaling. Among the six pairs of primers that we designate here, NS5 was the most efficient with a high sensitivity of up to 3.3 ng/μl and reproducible specificity on eight pathogen samples that were used as negative controls. The real-time fluorescence reverse transcription LAMP detection process can be completed within 35 min. Our study demonstrated that real-time fluorescence reverse transcription LAMP could be highly beneficial and convenient clinical application to detect Zika virus due to its high specificity and stability.

Gold nanoparticle-based RT-PCR and real-time quantitative RT-PCR assays for detection of Japanese encephalitis virus

NASA Astrophysics Data System (ADS)

Huang, Su-Hua; Yang, Tsuey-Ching; Tsai, Ming-Hong; Tsai, I.-Shou; Lu, Huang-Chih; Chuang, Pei-Hsin; Wan, Lei; Lin, Ying-Ju; Lai, Chih-Ho; Lin, Cheng-Wen

2008-10-01

Virus isolation and antibody detection are routinely used for diagnosis of Japanese encephalitis virus (JEV) infection, but the low level of transient viremia in some JE patients makes JEV isolation from clinical and surveillance samples very difficult. We describe the use of gold nanoparticle-based RT-PCR and real-time quantitative RT-PCR assays for detection of JEV from its RNA genome. We tested the effect of gold nanoparticles on four different PCR systems, including conventional PCR, reverse-transcription PCR (RT-PCR), and SYBR green real-time PCR and RT-PCR assays for diagnosis in the acute phase of JEV infection. Gold nanoparticles increased the amplification yield of the PCR product and shortened the PCR time compared to the conventional reaction. In addition, nanogold-based real-time RT-PCR showed a linear relationship between Ct and template amount using ten-fold dilutions of JEV. The nanogold-based RT-PCR and real-time quantitative RT-PCR assays were able to detect low levels (1-10 000 copies) of the JEV RNA genomes extracted from culture medium or whole blood, providing early diagnostic tools for the detection of low-level viremia in the acute-phase infection. The assays described here were simple, sensitive, and rapid approaches for detection and quantitation of JEV in tissue cultured samples as well as clinical samples.

Detection of Yersinia Enterocolitica Species in Pig Tonsils and Raw Pork Meat by the Real-Time Pcr and Culture Methods.

PubMed

Stachelska, M A

2017-09-26

The aim of the present study was to establish a rapid and accurate real-time PCR method to detect pathogenic Yersinia enterocolitica in pork. Yersinia enterocolitica is considered to be a crucial zoonosis, which can provoke diseases both in humans and animals. The classical culture methods designated to detect Y. enterocolitica species in food matrices are often very time-consuming. The chromosomal locus _tag CH49_3099 gene, that appears in pathogenic Y. enterocolitica strains, was applied as DNA target for the 5' nuclease PCR protocol. The probe was labelled at the 5' end with the fluorescent reporter dye (FAM) and at the 3' end with the quencher dye (TAMRA). The real-time PCR cycling parameters included 41 cycles. A Ct value which reached a value higher than 40 constituted a negative result. The developed for the needs of this study qualitative real-time PCR method appeared to give very specific and reliable results. The detection rate of locus _tag CH49_3099 - positive Y. enterocolitica in 150 pig tonsils was 85 % and 32 % with PCR and culture methods, respectively. Both the Real-time PCR results and culture method results were obtained from material that was enriched during overnight incubation. The subject of the study were also raw pork meat samples. Among 80 samples examined, 7 ones were positive when real-time PCR was applied, and 6 ones were positive when classical culture method was applied. The application of molecular techniques based on the analysis of DNA sequences such as the Real-time PCR enables to detect this pathogenic bacteria very rapidly and with higher specificity, sensitivity and reliability in comparison to classical culture methods.

People Detection by a Mobile Robot Using Stereo Vision in Dynamic Indoor Environments

NASA Astrophysics Data System (ADS)

Méndez-Polanco, José Alberto; Muñoz-Meléndez, Angélica; Morales, Eduardo F.

People detection and tracking is a key issue for social robot design and effective human robot interaction. This paper addresses the problem of detecting people with a mobile robot using a stereo camera. People detection using mobile robots is a difficult task because in real world scenarios it is common to find: unpredictable motion of people, dynamic environments, and different degrees of human body occlusion. Additionally, we cannot expect people to cooperate with the robot to perform its task. In our people detection method, first, an object segmentation method that uses the distance information provided by a stereo camera is used to separate people from the background. The segmentation method proposed in this work takes into account human body proportions to segment people and provides a first estimation of people location. After segmentation, an adaptive contour people model based on people distance to the robot is used to calculate a probability of detecting people. Finally, people are detected merging the probabilities of the contour people model and by evaluating evidence over time by applying a Bayesian scheme. We present experiments on detection of standing and sitting people, as well as people in frontal and side view with a mobile robot in real world scenarios.

Development and validation of a real-time PCR assay for the detection of anguillid herpesvirus 1.

PubMed

van Beurden, S J; Voorbergen-Laarman, M A; Roozenburg, I; van Tellingen, J; Haenen, O L M; Engelsma, M Y

2016-01-01

Anguillid herpesvirus 1 (AngHV1) causes a haemorrhagic disease with increased mortality in wild and farmed European eel, Anguilla anguilla (L.) and Japanese eel Anguilla japonica, Temminck & Schlegel). Detection of AngHV1 is currently based on virus isolation in cell culture, antibody-based typing assays or conventional PCR. We developed, optimized and concisely validated a diagnostic TaqMan probe based real-time PCR assay for the detection of AngHV1. The primers and probe target AngHV1 open reading frame 57, encoding the capsid protease and scaffold protein. Compared to conventional PCR, the developed real-time PCR is faster, less labour-intensive and has a reduced risk of cross-contamination. The real-time PCR assay was shown to be analytically sensitive and specific and has a high repeatability, efficiency and r(2) -value. The diagnostic performance of the assay was determined by testing 10% w/v organ suspensions and virus cultures from wild and farmed European eels from the Netherlands by conventional and real-time PCR. The developed real-time PCR assay is a useful tool for the rapid and sensitive detection of AngHV1 in 10% w/v organ suspensions from wild and farmed European eels. © 2015 John Wiley & Sons Ltd.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning

PubMed Central

Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea). PMID:28264011

[Real-time PCR in rapid diagnosis of Aeromonas hydrophila necrotizing soft tissue infections].

PubMed

Kohayagawa, Yoshitaka; Izumi, Yoko; Ushita, Misuzu; Niinou, Norio; Koshizaki, Masayuki; Yamamori, Yuji; Kaneko, Sakae; Fukushima, Hiroshi

2009-11-01

We report a case of rapidly progressive necrotizing soft tissue infection and sepsis followed by a patient's death. We suspected Vibrio vulnificus infection because the patient's underlying disease was cirrhosis and the course extremely rapid. No microbe had been detected at death. We extracted DNA from a blood culture bottle. SYBR green I real-time PCR was conducted but could not detect V. vulnificus vvh in the DNA sample. Aeromonas hydrophila was cultured and identified in blood and necrotized tissue samples. Real-time PCR was conducted to detect A. hydrophila ahh1, AHCYTOEN and aerA in the DNA sample extracted from the blood culture bottle and an isolated necrotized tissue strain, but only ahh1 was positive. High-mortality in necrotizing soft tissue infections makes it is crucial to quickly detect V. vulnificus and A. hydrophila. We found real-time PCR for vvh, ahh1, AHCYTOEN, and aerA useful in detecting V. vulnificus and A. hydrophila in necrotizing soft tissue infections.

Collaborative real-time scheduling of multiple PTZ cameras for multiple object tracking in video surveillance

NASA Astrophysics Data System (ADS)

Liu, Yu-Che; Huang, Chung-Lin

2013-03-01

This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object's face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.

An anti-disturbing real time pose estimation method and system

NASA Astrophysics Data System (ADS)

Zhou, Jian; Zhang, Xiao-hu

2011-08-01

Pose estimation relating two-dimensional (2D) images to three-dimensional (3D) rigid object need some known features to track. In practice, there are many algorithms which perform this task in high accuracy, but all of these algorithms suffer from features lost. This paper investigated the pose estimation when numbers of known features or even all of them were invisible. Firstly, known features were tracked to calculate pose in the current and the next image. Secondly, some unknown but good features to track were automatically detected in the current and the next image. Thirdly, those unknown features which were on the rigid and could match each other in the two images were retained. Because of the motion characteristic of the rigid object, the 3D information of those unknown features on the rigid could be solved by the rigid object's pose at the two moment and their 2D information in the two images except only two case: the first one was that both camera and object have no relative motion and camera parameter such as focus length, principle point, and etc. have no change at the two moment; the second one was that there was no shared scene or no matched feature in the two image. Finally, because those unknown features at the first time were known now, pose estimation could go on in the followed images in spite of the missing of known features in the beginning by repeating the process mentioned above. The robustness of pose estimation by different features detection algorithms such as Kanade-Lucas-Tomasi (KLT) feature, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) were compared and the compact of the different relative motion between camera and the rigid object were discussed in this paper. Graphic Processing Unit (GPU) parallel computing was also used to extract and to match hundreds of features for real time pose estimation which was hard to work on Central Processing Unit (CPU). Compared with other pose estimation methods, this new method can estimate pose between camera and object when part even all known features are lost, and has a quick response time benefit from GPU parallel computing. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in autonomous navigation and positioning, robots fields at unknown environment. The results of simulation and experiments demonstrate that proposed method could suppress noise effectively, extracted features robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

Comparison of nested-multiplex, Taqman & SYBR Green real-time PCR in diagnosis of amoebic liver abscess in a tertiary health care institute in India.

PubMed

Dinoop, K P; Parija, Subhash Chandra; Mandal, Jharna; Swaminathan, R P; Narayanan, P

2016-01-01

Amoebiasis is a common parasitic infection caused by Entamoeba histolytica and amoebic liver abscess (ALA) is the most common extraintestinal manifestation of amoebiasis. The aim of this study was to standardise real-time PCR assays (Taqman and SYBR Green) to detect E. histolytica from liver abscess pus and stool samples and compare its results with nested-multiplex PCR. Liver abscess pus specimens were subjected to DNA extraction. The extracted DNA samples were subjected to amplification by nested-multiplex PCR, Taqman (18S rRNA) and SYBR Green real-time PCR (16S-like rRNA assays to detect E. histolytica/E. dispar/E. moshkovskii). The amplification products were further confirmed by DNA sequence analysis. Receiver operator characteristic (ROC) curve analysis was done for nested-multiplex and SYBR Green real-time PCR and the area under the curve was calculated for evaluating the accuracy of the tests to dignose ALA. In all, 17, 19 and 25 liver abscess samples were positive for E. histolytica by nested-multiplex PCR, SYBR Green and Taqman real-time PCR assays, respectively. Significant differences in detection of E. histolytica were noted in the real-time PCR assays evaluated ( P<0.0001). The nested-multiplex PCR, SYBR Green real-time PCR and Taqman real-time PCR evaluated showed a positivity rate of 34, 38 and 50 per cent, respectively. Based on ROC curve analysis (considering Taqman real-time PCR as the gold standard), it was observed that SYBR Green real-time PCR was better than conventional nested-multiplex PCR for the diagnosis of ALA. Taqman real-time PCR targeting the 18S rRNA had the highest positivity rate evaluated in this study. Both nested multiplex and SYBR Green real-time PCR assays utilized were evaluated to give accurate results. Real-time PCR assays can be used as the gold standard in rapid and reliable diagnosis, and appropriate management of amoebiasis, replacing the conventional molecular methods.

Laser-induced fluorescence imaging of bacteria

NASA Astrophysics Data System (ADS)

Hilton, Peter J.

1998-12-01

This paper outlines a method for optically detecting bacteria on various backgrounds, such as meat, by imaging their laser induced auto-fluorescence response. This method can potentially operate in real-time, which is many times faster than current bacterial detection methods, which require culturing of bacterial samples. This paper describes the imaging technique employed whereby a laser spot is scanned across an object while capturing, filtering, and digitizing the returned light. Preliminary results of the bacterial auto-fluorescence are reported and plans for future research are discussed. The results to date are encouraging with six of the eight bacterial strains investigated exhibiting auto-fluorescence when excited at 488 nm. Discrimination of these bacterial strains against red meat is shown and techniques for reducing background fluorescence discussed.

Two Multiplex Real-Time PCR Assays to Detect and Differentiate Acinetobacter baumannii and Non- baumannii Acinetobacter spp. Carrying blaNDM, blaOXA-23-Like, blaOXA-40-Like, blaOXA-51-Like, and blaOXA-58-Like Genes

PubMed Central

Yang, Qiu; Rui, Yongyu

2016-01-01

Nosocomial infections caused by Acinetobacter spp. resistant to carbapenems are increasingly reported worldwide. Carbapenem-resistant Acinetobacter (CRA) is becoming a serious concern with increasing patient morbidity, mortality, and lengths of hospital stay. Therefore, the rapid detection of CRA is essential for epidemiological surveillance. Polymerase chain reaction (PCR) has been extensively used for the rapid identification of most pathogens. In this study, we have developed two multiplex real-time PCR assays to detect and differentiate A. baumannii and non-A. baumannii Acinetobacter spp, and common carbapenemase genes, including blaNDM, blaOXA-23-like, blaOXA-40-like, blaOXA-51-like, and blaOXA-58-like. We demonstrate the potential utility of these assays for the direct detection of blaNDM-, blaOXA-23-like-, blaOXA-40-like-, blaOXA-51-like-, and blaOXA-58-like-positive CRA in clinical specimens. Primers were specifically designed, and two multiplex real-time PCR assays were developed: multiplex real-time PCR assay1 for the detection of Acinetobacter baumannii 16S–23S rRNA internal transcribed spacer sequence, the Acinetobacter recA gene, and class-B-metalloenzyme-encoding gene blaNDM; and multiplex real-time PCR assay2 to detect class-D-oxacillinase-encoding genes (blaOXA-23-like, blaOXA-40-like, blaOXA-51-like,and blaOXA-58-like). The assays were performed on an ABI Prism 7500 FAST Real-Time PCR System. CRA isolates were used to compare the assays with conventional PCR and sequencing. Known amounts of CRA cells were added to sputum and fecal specimens and used to test the multiplex real-time PCR assays. The results for target and nontarget amplification showed that the multiplex real-time PCR assays were specific, the limit of detection for each target was 10 copies per 20 μL reaction volume, the assays were linear over six log dilutions of the target genes (r2 > 0.99), and the Ct values of the coefficients of variation for intra- and interassay reproducibility were less than 5%. The multiplex real-time PCR assays showed 100% concordance with conventional PCR when tested against 400 CRA isolates and their sensitivity for the target DNA in sputum and fecal specimens was 102 CFU/mL. Therefore, these novel multiplex real-time PCR assays allow the sensitive and specific characterization and differentiation of blaNDM-, blaOXA-23-like-, blaOXA-40-like-, blaOXA-51-like-, and blaOXA-58-like-positive CRA, making them potential tools for the direct detection of CRA in clinical specimens and the surveillance of nosocomial infections. PMID:27391234

Real-time monitoring of CO2 storage sites: Application to Illinois Basin-Decatur Project

USGS Publications Warehouse

Picard, G.; Berard, T.; Chabora, E.; Marsteller, S.; Greenberg, S.; Finley, R.J.; Rinck, U.; Greenaway, R.; Champagnon, C.; Davard, J.

2011-01-01

Optimization of carbon dioxide (CO2) storage operations for efficiency and safety requires use of monitoring techniques and implementation of control protocols. The monitoring techniques consist of permanent sensors and tools deployed for measurement campaigns. Large amounts of data are thus generated. These data must be managed and integrated for interpretation at different time scales. A fast interpretation loop involves combining continuous measurements from permanent sensors as they are collected to enable a rapid response to detected events; a slower loop requires combining large datasets gathered over longer operational periods from all techniques. The purpose of this paper is twofold. First, it presents an analysis of the monitoring objectives to be performed in the slow and fast interpretation loops. Second, it describes the implementation of the fast interpretation loop with a real-time monitoring system at the Illinois Basin-Decatur Project (IBDP) in Illinois, USA. ?? 2011 Published by Elsevier Ltd.

A real-time robot arm collision avoidance system

NASA Technical Reports Server (NTRS)

Shaffer, Clifford A.; Herb, Gregory M.

1992-01-01

A data structure and update algorithm are presented for a prototype real-time collision avoidance safety system simulating a multirobot workspace. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3D space into eight equal cubic octants until each octant meets some decomposition criteria. The N-objects octree, which indexes a collection of 3D primitive solids is used. These primitives make up the two (seven-degrees-of-freedom) robot arms and workspace modeled by the system. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Cycle time for interpreting current arm joint angles, updating the octree to reflect new positions, and detecting/reporting imminent collisions averages 30 ms on an Intel 80386 processor running at 20 MHz.

Detection of Mental State and Reduction of Artifacts Using Functional Near Infrared Spectroscopy (FNIRS)

NASA Technical Reports Server (NTRS)

Harrivel, Angela (Inventor); Hearn, Tristan (Inventor)

2017-01-01

fNIRS may be used in real time or near-real time to detect the mental state of individuals. Phase measurement can be applied to drive an adaptive filter for the removal of motion artifacts in real time or near-real time. In this manner, the application of fNIRS may be extended to practical non-laboratory environments. For example, the mental state of an operator of a vehicle may be monitored, and alerts may be issued and/or an autopilot may be engaged when the mental state of the operator indicates that the operator is inattentive.

Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices.

PubMed

Gradl, Stefan; Kugler, Patrick; Lohmuller, Clemens; Eskofier, Bjoern

2012-01-01

We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the Pan-Tompkins algorithm for QRS-detection and contains further algorithm blocks to detect abnormal heartbeats. The algorithm was validated using the MIT-BIH Arrhythmia and MIT-BIH Supraventricular Arrhythmia databases. More than 99% of all QRS complexes were detected correctly by the algorithm. Overall sensitivity for abnormal beat detection was 89.5% with a specificity of 80.6%. The application is available for download and may be used for real-time ECG-monitoring on mobile devices.

ControlShell - A real-time software framework

NASA Technical Reports Server (NTRS)

Schneider, Stanley A.; Ullman, Marc A.; Chen, Vincent W.

1991-01-01

ControlShell is designed to enable modular design and impplementation of real-time software. It is an object-oriented tool-set for real-time software system programming. It provides a series of execution and data interchange mechansims that form a framework for building real-time applications. These mechanisms allow a component-based approach to real-time software generation and mangement. By defining a set of interface specifications for intermodule interaction, ControlShell provides a common platform that is the basis for real-time code development and exchange.

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

Real-time detection of laser-GaAs interaction process

NASA Astrophysics Data System (ADS)

Jia, Zhichao; Li, Zewen; Lv, Xueming; Ni, Xiaowu

2017-05-01

A real-time method based on laser scattering technology was used to detect the interaction process of GaAs with a 1080 nm laser. The detector collected the scattered laser beam from the GaAs wafer. The main scattering sources were back surface at first, later turn into front surface and vapor, so scattering signal contained much information of the interaction process. The surface morphologies of GaAs with different irradiation times were observed using an optical microscope to confirm occurrence of various phenomena. The proposed method is shown to be effective for the real-time detection of GaAs. By choosing a proper wavelength, the scattering technology can be promoted in detection of thicker GaAs wafer or other materials.

Real time freeway incident detection.

DOT National Transportation Integrated Search

2014-04-01

The US Department of Transportation (US-DOT) estimates that over half of all congestion : events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time : incident detection on freeways is an important part of any mo...

Real-time PCR detection of Plasmodium directly from whole blood and filter paper samples

PubMed Central

2011-01-01

Background Real-time PCR is a sensitive and specific method for the analysis of Plasmodium DNA. However, prior purification of genomic DNA from blood is necessary since PCR inhibitors and quenching of fluorophores from blood prevent efficient amplification and detection of PCR products. Methods Reagents designed to specifically overcome PCR inhibition and quenching of fluorescence were evaluated for real-time PCR amplification of Plasmodium DNA directly from blood. Whole blood from clinical samples and dried blood spots collected in the field in Colombia were tested. Results Amplification and fluorescence detection by real-time PCR were optimal with 40× SYBR® Green dye and 5% blood volume in the PCR reaction. Plasmodium DNA was detected directly from both whole blood and dried blood spots from clinical samples. The sensitivity and specificity ranged from 93-100% compared with PCR performed on purified Plasmodium DNA. Conclusions The methodology described facilitates high-throughput testing of blood samples collected in the field by fluorescence-based real-time PCR. This method can be applied to a broad range of clinical studies with the advantages of immediate sample testing, lower experimental costs and time-savings. PMID:21851640

Development of a pan-Simbu real-time reverse transcriptase PCR for the detection of Simbu serogroup viruses and comparison with SBV diagnostic PCR systems.

PubMed

Fischer, Melina; Schirrmeier, Horst; Wernike, Kerstin; Wegelt, Anne; Beer, Martin; Hoffmann, Bernd

2013-11-05

Schmallenberg virus (SBV), a novel orthobunyavirus of the Simbu serogroup, was first identified in October 2011 in dairy cattle in Germany, where it caused fever, diarrhea and a drop in milk yield. Since then, SBV additionally has been detected in adult sheep and goats. Although symptoms of acute infection were not observed, infection during a vulnerable phase of pregnancy caused congenital malformations and stillbirths. In view of the current situation and the possible emergence of further Simbu serogroup members, a pan-Simbu real-time reverse transcriptase (RT) PCR system for the reliable detection of Simbu serogroup viruses should be developed. In this study a pan-Simbu real-time RT-PCR system was established and compared to several SBV real-time RT-PCR assays. All PCR-systems were tested using a panel of different Simbu serogroup viruses as well as several field samples from diseased cattle, sheep and goats originating from all over Germany. Several pan-Simbu real-time RT-PCR products were sequenced via Sanger sequencing. Furthermore, in silico analyses were performed to investigate suitability for the detection of further orthobunyaviruses. All tested members of the Simbu serogroup (n = 14) as well as most of the field samples were successfully detected by the pan-Simbu real-time RT-PCR system. The comparison of this intercalating dye assay with different TaqMan probe-based assays developed for SBV diagnostics confirmed the functionality of the pan-Simbu assay for screening purposes. However, the SBV-TaqMan-assay SBV-S3 delivered the highest analytical sensitivity of less than ten copies per reaction for duplex systems including an internal control. In addition, for confirmation of SBV-genome detection the highly specific SBV-M1 assay was established. The pan-Simbu real-time RT-PCR system was able to detect all tested members of the Simbu serogroup, most of the SBV field samples as well as three tested Bunyamwera serogroup viruses with a suitable sensitivity. According to in silico analyses, this system seems to be able to detect a broad orthobunyavirus spectrum. As an additional feature of the pan-Simbu real-time RT-PCR system, subsequent species classification via sequencing is feasible. Regarding SBV diagnostics, the performance of the S-segment targeting SBV-S3 assay was superior with respect to the analytical sensitivity.

Detection of Echinoderm Microtubule Associated Protein Like 4-Anaplastic Lymphoma Kinase Fusion Genes in Non-small Cell Lung Cancer Clinical Samples by a Real-time Quantitative Reverse Transcription Polymerase Chain Reaction Method.

PubMed

Zhao, Jing; Zhao, Jin-Yin; Chen, Zhi-Xia; Zhong, Wei; Li, Long-Yun; Liu, Li-Cheng; Hu, Xiao-Xu; Chen, Wei-Jun; Wang, Meng-Zhao

2016-12-20

Objective To establish a real-time quantitative reverse transcription polymerase chain reaction assay (qRT-PCR) for the rapid, sensitive, and specific detection of echinoderm microtubule associated protein like 4-anaplastic lymphoma kinase (EML4-ALK) fusion genes in non-small cell lung cancer. Methods The specific primers for the four variants of EML4-ALK fusion genes (V1, V2, V3a, and V3b) and Taqman fluorescence probes for the detection of the target sequences were carefully designed by the Primer Premier 5.0 software. Then, using pseudovirus containing EML4-ALK fusion genes variants (V1, V2, V3a, and V3b) as the study objects, we further analyzed the lower limit, sensitivity, and specificity of this method. Finally, 50 clinical samples, including 3 ALK-fluorescence in situ hybridization (FISH) positive specimens, were collected and used to detect EML4-ALK fusion genes using this method. Results The lower limit of this method for the detection of EML4-ALK fusion genes was 10 copies/μl if no interference of background RNA existed. Regarding the method's sensitivity, the detection resolution was as high as 1% and 0.5% in the background of 500 and 5000 copies/μl wild-type ALK gene, respectively. Regarding the method's specificity, no non-specific amplification was found when it was used to detect EML4-ALK fusion genes in leukocyte and plasma RNA samples from healthy volunteers. Among the 50 clinical samples, 47 ALK-FISH negative samples were also negative. Among 3 ALK-FISH positive samples, 2 cases were detected positive using this method, but another was not detected because of the failure of RNA extraction. Conclusion The proposed qRT-PCR assay for the detection of EML4-ALK fusion genes is rapid, simple, sensitive, and specific, which is deserved to be validated and widely used in clinical settings.

On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels.

PubMed

Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho; Kim, Hee-Kang

2018-03-11

Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services.

On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels

PubMed Central

Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho

2018-01-01

Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services. PMID:29534483

Evaluation of two commercial real-time PCR assays for detecting Campylobacter in broiler carcass rinses.

USDA-ARS?s Scientific Manuscript database

Traditional plating methods are reliable means for Campylobacter identification from poultry samples but automated gene-based detection systems now available can reduce assay time, data collection and analysis. Bio-Rad and DuPont Qualicon recently introduced Campylobacter assays for their real-time ...

DETECTION OF FECAL ENTEROCOCCI USING A REAL TIME PCR METHOD

EPA Science Inventory

In spite of their importance in public health, the detection of fecal enterococci is performed via culturing methods that are time consuming and that are subject to inaccuracies that relate to their culturable status. In order to address these problems, a real time PCR (TaqMan) ...

Real-time detection with AdaBoost-svm combination in various face orientation

NASA Astrophysics Data System (ADS)

Fhonna, R. P.; Nasution, M. K. M.; Tulus

2018-03-01

Most of the research has used algorithm AdaBoost-SVM for face detection. However, to our knowledge so far there is no research has been facing detection on real-time data with various orientations using the combination of AdaBoost and Support Vector Machine (SVM). Characteristics of complex and diverse face variations and real-time data in various orientations, and with a very complex application will slow down the performance of the face detection system this becomes a challenge in this research. Face orientation performed on the detection system, that is 900, 450, 00, -450, and -900. This combination method is expected to be an effective and efficient solution in various face orientations. The results showed that the highest average detection rate is on the face detection oriented 00 and the lowest detection rate is in the face orientation 900.

Ubiquitous health monitoring and real-time cardiac arrhythmias detection: a case study.

PubMed

Li, Jian; Zhou, Haiying; Zuo, Decheng; Hou, Kun-Mean; De Vaulx, Christophe

2014-01-01

As the symptoms and signs of heart diseases that cause sudden cardiac death, cardiac arrhythmia has attracted great attention. Due to limitations in time and space, traditional approaches to cardiac arrhythmias detection fail to provide a real-time continuous monitoring and testing service applicable in different environmental conditions. Integrated with the latest technologies in ECG (electrocardiograph) analysis and medical care, the pervasive computing technology makes possible the ubiquitous cardiac care services, and thus brings about new technical challenges, especially in the formation of cardiac care architecture and realization of the real-time automatic ECG detection algorithm dedicated to care devices. In this paper, a ubiquitous cardiac care prototype system is presented with its architecture framework well elaborated. This prototype system has been tested and evaluated in all the clinical-/home-/outdoor-care modes with a satisfactory performance in providing real-time continuous cardiac arrhythmias monitoring service unlimitedly adaptable in time and space.

Continuous, Real-Time Monitoring of Cocaine in Undiluted Blood Serum via a Microfluidic, Electrochemical Aptamer-Based Sensor

PubMed Central

Swensen, James S.; Xiao, Yi; Ferguson, Brian S.; Lubin, Arica A.; Lai, Rebecca Y.; Heeger, Alan J.; Plaxco, Kevin W.; Soh, H. Tom.

2009-01-01

The development of a biosensor system capable of continuous, real-time measurement of small-molecule analytes directly in complex, unprocessed aqueous samples has been a significant challenge, and successful implementation has been achieved for only a limited number of targets. Towards a general solution to this problem, we report here the Microfluidic Electrochemical Aptamer-based Sensor (MECAS) chip wherein we integrate target-specific DNA aptamers that fold, and thus generate an electrochemical signal, in response to the analyte with a microfluidic detection system. As a model, we demonstrate the continuous, real-time (~1 minute time resolution) detection of the small molecule drug cocaine at near physiological, low micromolar concentrations directly in undiluted, otherwise unmodified blood serum. We believe our approach of integrating folding-based electrochemical sensors with miniaturized detection systems may lay the ground work for the real-time, point-of-care detection of a wide variety of molecular targets. PMID:19271708

Railway clearance intrusion detection method with binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

Analytical and clinical performance characteristics of the Abbott RealTime MTB RIF/INH Resistance, an assay for the detection of rifampicin and isoniazid resistant Mycobacterium tuberculosis in pulmonary specimens.

PubMed

Kostera, Joshua; Leckie, Gregor; Tang, Ning; Lampinen, John; Szostak, Magdalena; Abravaya, Klara; Wang, Hong

2016-12-01

Clinical management of drug-resistant tuberculosis patients continues to present significant challenges to global health. To tackle these challenges, the Abbott RealTime MTB RIF/INH Resistance assay was developed to accelerate the diagnosis of rifampicin and/or isoniazid resistant tuberculosis to within a day. This article summarizes the performance of the Abbott RealTime MTB RIF/INH Resistance assay; including reliability, analytical sensitivity, and clinical sensitivity/specificity as compared to Cepheid GeneXpert MTB/RIF version 1.0 and Hain MTBDRplus version 2.0. The limit of detection (LOD) of the Abbott RealTime MTB RIF/INH Resistance assay was determined to be 32 colony forming units/milliliter (cfu/mL) using the Mycobacterium tuberculosis (MTB) strain H37Rv cell line. For rifampicin resistance detection, the Abbott RealTime MTB RIF/INH Resistance assay demonstrated statistically equivalent clinical sensitivity and specificity as compared to Cepheid GeneXpert MTB/RIF. For isoniazid resistance detection, the assay demonstrated statistically equivalent clinical sensitivity and specificity as compared to Hain MTBDRplus. The performance data presented herein demonstrate that the Abbott RealTime MTB RIF/INH Resistance assay is a sensitive, robust, and reliable test for realtime simultaneous detection of first line anti-tuberculosis antibiotics rifampicin and isoniazid in patient specimens. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Real-time color image processing for forensic fiber investigations

NASA Astrophysics Data System (ADS)

Paulsson, Nils

1995-09-01

This paper describes a system for automatic fiber debris detection based on color identification. The properties of the system are fast analysis and high selectivity, a necessity when analyzing forensic fiber samples. An ordinary investigation separates the material into well above 100,000 video images to analyze. The system is based on standard techniques such as CCD-camera, motorized sample table, and IBM-compatible PC/AT with add-on-boards for video frame digitalization and stepping motor control as the main parts. It is possible to operate the instrument at full video rate (25 image/s) with aid of the HSI-color system (hue- saturation-intensity) and software optimization. High selectivity is achieved by separating the analysis into several steps. The first step is fast direct color identification of objects in the analyzed video images and the second step analyzes detected objects with a more complex and time consuming stage of the investigation to identify single fiber fragments for subsequent analysis with more selective techniques.

Rapid and sensitive detection of canine distemper virus by real-time reverse transcription recombinase polymerase amplification.

PubMed

Wang, Jianchang; Wang, Jinfeng; Li, Ruiwen; Liu, Libing; Yuan, Wanzhe

2017-08-15

Canine distemper, caused by Canine distemper virus (CDV), is a highly contagious and fatal systemic disease in free-living and captive carnivores worldwide. Recombinase polymerase amplification (RPA), as an isothermal gene amplification technique, has been explored for the molecular detection of diverse pathogens. A real-time reverse transcription RPA (RT-RPA) assay for the detection of canine distemper virus (CDV) using primers and exo probe targeting the CDV nucleocapsid protein gene was developed. A series of other viruses were tested by the RT-RPA.Thirty-two field samples were further tested by RT-RPA, and the resuts were compared with those obtained by the real-time RT-PCR. The RT-RPA assay was performed successfully at 40 °C, and the results were obtained within 3 min-12 min. The assay could detect CDV, but did not show cross-detection of canine parvovirus-2 (CPV-2), canine coronavirus (CCoV), canine parainfluenza virus (CPIV), pseudorabies virus (PRV) or Newcastle disease virus (NDV), demonstrating high specificity. The analytical sensitivity of RT-RPA was 31.8 copies in vitro transcribed CDV RNA, which is 10 times lower than the real-time RT-PCR. The assay performance was validated by testing 32 field samples and compared to real-time RT-PCR. The results indicated an excellent correlation between RT-RPA and a reference real-time RT-PCR method. Both assays provided the same results, and R 2 value of the positive results was 0.947. The results demonstrated that the RT-RPA assay offers an alternative tool for simple, rapid, and reliable detection of CDV both in the laboratory and point-of-care facility, especially in the resource-limited settings.

Utility of a fecal real-time PCR protocol for detection of Mycobacterium bovis infection in African buffalo (Syncerus caffer).

PubMed

Roug, Annette; Geoghegan, Claire; Wellington, Elizabeth; Miller, Woutrina A; Travis, Emma; Porter, David; Cooper, David; Clifford, Deana L; Mazet, Jonna A K; Parsons, Sven

2014-01-01

A real-time PCR protocol for detecting Mycobacterium bovis in feces was evaluated in bovine tuberculosis-infected African buffalo (Syncerus caffer). Fecal samples spiked with 1.42 × 10(3) cells of M. bovis culture/g and Bacille Calmette-Guérin standards with 1.58 × 10(1) genome copies/well were positive by real-time PCR but all field samples were negative.

Real-time radiography at the NECTAR facility

NASA Astrophysics Data System (ADS)

Bücherl, T.; Lierse von Gostomski, Ch.

2011-09-01

A feasibility study has shown that real-time radiography using fission neutrons is possible at the NECTAR facility, when using an improved detection system for fast variations (Bücherl et al., 2009 [1]). Continuing this study, real-time measurements of slowly varying processes like the water uptake in medium sized trunks (diameter about 12 cm) and of slow periodic processes (e.g. a slowly rotating iron disk) are investigated successfully using the existing detection system.

An Undergraduate Laboratory Experiment for Upper-Level Forensic Science, Biochemistry, or Molecular Biology Courses: Human DNA Amplification Using STR Single Locus Primers by Real-Time PCR with SYBR Green Detection

ERIC Educational Resources Information Center

Elkins, Kelly M.; Kadunc, Raelynn E.

2012-01-01

In this laboratory experiment, real-time polymerase chain reaction (real-time PCR) was conducted using published human TPOX single-locus DNA primers for validation and various student-designed short tandem repeat (STR) primers for Combined DNA Index System (CODIS) loci. SYBR Green was used to detect the amplification of the expected amplicons. The…

Ultrafast, sensitive and large-volume on-chip real-time PCR for the molecular diagnosis of bacterial and viral infections.

PubMed

Houssin, Timothée; Cramer, Jérémy; Grojsman, Rébecca; Bellahsene, Lyes; Colas, Guillaume; Moulet, Hélène; Minnella, Walter; Pannetier, Christophe; Leberre, Maël; Plecis, Adrien; Chen, Yong

2016-04-21

To control future infectious disease outbreaks, like the 2014 Ebola epidemic, it is necessary to develop ultrafast molecular assays enabling rapid and sensitive diagnoses. To that end, several ultrafast real-time PCR systems have been previously developed, but they present issues that hinder their wide adoption, notably regarding their sensitivity and detection volume. An ultrafast, sensitive and large-volume real-time PCR system based on microfluidic thermalization is presented herein. The method is based on the circulation of pre-heated liquids in a microfluidic chip that thermalize the PCR chamber by diffusion and ultrafast flow switches. The system can achieve up to 30 real-time PCR cycles in around 2 minutes, which makes it the fastest PCR thermalization system for regular sample volume to the best of our knowledge. After biochemical optimization, anthrax and Ebola simulating agents could be respectively detected by a real-time PCR in 7 minutes and a reverse transcription real-time PCR in 7.5 minutes. These detections are respectively 6.4 and 7.2 times faster than with an off-the-shelf apparatus, while conserving real-time PCR sample volume, efficiency, selectivity and sensitivity. The high-speed thermalization also enabled us to perform sharp melting curve analyses in only 20 s and to discriminate amplicons of different lengths by rapid real-time PCR. This real-time PCR microfluidic thermalization system is cost-effective, versatile and can be then further developed for point-of-care, multiplexed, ultrafast and highly sensitive molecular diagnoses of bacterial and viral diseases.

Image analysis of multiple moving wood pieces in real time

NASA Astrophysics Data System (ADS)

Wang, Weixing

2006-02-01

This paper presents algorithms for image processing and image analysis of wood piece materials. The algorithms were designed for auto-detection of wood piece materials on a moving conveyor belt or a truck. When wood objects on moving, the hard task is to trace the contours of the objects in n optimal way. To make the algorithms work efficiently in the plant, a flexible online system was designed and developed, which mainly consists of image acquisition, image processing, object delineation and analysis. A number of newly-developed algorithms can delineate wood objects with high accuracy and high speed, and in the wood piece analysis part, each wood piece can be characterized by a number of visual parameters which can also be used for constructing experimental models directly in the system.

Detection of Common Respiratory Viruses and Mycoplasma pneumoniae in Patient-Occupied Rooms in Pediatric Wards.

PubMed

Wan, Gwo-Hwa; Huang, Chung-Guei; Chung, Fen-Fang; Lin, Tzou-Yien; Tsao, Kuo-Chien; Huang, Yhu-Chering

2016-04-01

Few studies have assessed viral contamination in the rooms of hospital wards. This cross-sectional study evaluated the air and objects in patient-occupied rooms in pediatric wards for the presence of common respiratory viruses and Mycoplasma pneumoniae.Air samplers were placed at a short (60-80 cm) and long (320 cm) distance from the head of the beds of 58 pediatric patients, who were subsequently confirmed to be infected with enterovirus (n = 17), respiratory syncytial virus (RSV) (n = 13), influenza A virus (n = 13), adenovirus (n = 9), or M pneumoniae (n = 6). Swab samples were collected from the surfaces of 5 different types of objects in the patients' rooms. All air and swab samples were analyzed via real-time quantitative polymerase chain reaction assay for the presence of the above pathogens.All pathogens except enterovirus were detected in the air, on the objects, or in both locations in the patients' rooms. The detection rates of influenza A virus, adenovirus, and M pneumoniae for the long distance air sampling were 15%, 67%, and 17%, respectively. Both adenovirus and M pneumoniae were detected at very high rates, with high concentrations, on all sampled objects.The respiratory pathogens RSV, influenza A virus, adenovirus, and M pneumoniae were detected in the air and/or on the objects in the pediatric ward rooms. Appropriate infection control measures should be strictly implemented when caring for such patients.

Real time avalanche detection for high risk areas.

DOT National Transportation Integrated Search

2014-12-01

Avalanches routinely occur on State Highway 21 (SH21) between Lowman and Stanley, Idaho each winter. The avalanches pose : a threat to the safety of maintenance workers and the traveling public. A real-time avalanche detection system will allow the :...

Real-Time, Single-Step Bioassay Using Nanoplasmonic Resonator With Ultra-High Sensitivity

NASA Technical Reports Server (NTRS)

Zhang, Xiang (Inventor); Chen, Fanqing Frank (Inventor); Su, Kai-Hang (Inventor); Wei, Qi-Huo (Inventor); Ellman, Jonathan A. (Inventor); Sun, Cheng (Inventor)

2014-01-01

A nanoplasmonic resonator (NPR) comprising a metallic nanodisk with alternating shielding layer(s), having a tagged biomolecule conjugated or tethered to the surface of the nanoplasmonic resonator for highly sensitive measurement of enzymatic activity. NPRs enhance Raman signals in a highly reproducible manner, enabling fast detection of protease and enzyme activity, such as Prostate Specific Antigen (paPSA), in real-time, at picomolar sensitivity levels. Experiments on extracellular fluid (ECF) from paPSA-positive cells demonstrate specific detection in a complex bio-fluid background in real-time single-step detection in very small sample volumes.

Real-time, single-step bioassay using nanoplasmonic resonator with ultra-high sensitivity

DOEpatents

Zhang, Xiang; Ellman, Jonathan A; Chen, Fanqing Frank; Su, Kai-Hang; Wei, Qi-Huo; Sun, Cheng

2014-04-01

A nanoplasmonic resonator (NPR) comprising a metallic nanodisk with alternating shielding layer(s), having a tagged biomolecule conjugated or tethered to the surface of the nanoplasmonic resonator for highly sensitive measurement of enzymatic activity. NPRs enhance Raman signals in a highly reproducible manner, enabling fast detection of protease and enzyme activity, such as Prostate Specific Antigen (paPSA), in real-time, at picomolar sensitivity levels. Experiments on extracellular fluid (ECF) from paPSA-positive cells demonstrate specific detection in a complex bio-fluid background in real-time single-step detection in very small sample volumes.

Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

NASA Astrophysics Data System (ADS)

Li, Jia; Tian, Yonghong; Gao, Wen

2008-01-01

In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

Development of an isothermal recombinase polymerase amplification assay for rapid detection of pseudorabies virus.

PubMed

Yang, Yang; Qin, Xiaodong; Zhang, Wei; Li, Zhiyong; Zhang, Shuaijun; Li, Yanmin; Zhang, Zhidong

2017-06-01

Recombinase polymerase amplification assays using real-time fluorescent detection (real-time RPA assay) and lateral flow dipstick (RPA LFD assay) were developed targeting the gD gene of pseudorabies virus (PRV). Both assays were performed at 39 °C within 20 min. The sensitivity of the real-time RPA assay and the RPA LFD assay was 100 copies per reaction and 160 copies per reaction, respectively. Both assays did not detect DNAs from other virus or PRV negative samples. Therefore, the developed RPA assays provide a rapid, simple, sensitive and specific alternative tool for detection of PRV. Copyright © 2017. Published by Elsevier Ltd.

A Framework for Testing Automated Detection, Diagnosis, and Remediation Systems on the Smart Grid

NASA Technical Reports Server (NTRS)

Lau, Shing-hon

2011-01-01

America's electrical grid is currently undergoing a multi-billion dollar modernization effort aimed at producing a highly reliable critical national infrastructure for power - a Smart Grid. While the goals for the Smart Grid include upgrades to accommodate large quantities of clean, but transient, renewable energy and upgrades to provide customers with real-time pricing information, perhaps the most important objective is to create an electrical grid with a greatly increased robustness.

[A novel TaqMan® MGB probe for specifically detecting Streptococcus mutans].

PubMed

Zheng, Hui; Lin, Jiu-Xiang; DU, Ning; Chen, Feng

2013-10-18

To design a new TaqMan® MGB probe for improving the specificity of Streptococcus mutans's detection. We extracted six DNA samples from different streptococcal strains for PCR reaction. Conventional nested PCR and TaqMan® MGB real-time PCR were applied independently. The first round of nested PCR was carried out with the bacterial universal primers, while a second PCR was conducted by using primers specific for the 16S rRNA gene of Streptococcus mutans. The TaqMan® MGB probe for Streptococcus mutans was designed from sequence analyses, and the primers were the same as nested PCR. Streptococcus mutans DNA with 2.5 mg/L was sequentially diluted at 5-fold intervals to 0.16 μg/L. Standard DNA samples were used to generate standard curves by TaqMan® MGB real-time PCR. In the nested PCR, the primers specific for Streptococcus mutans also detected Streptococcus gordonii with visible band of 282 bp, giving false-positive results. In the TaqMan® MGB real-time PCR reaction, only Streptococcus mutans was detected. The detection limitation of TaqMan® MGB real-time PCR for Streptococcus mutans 16S rRNA gene was 20 μg/L. We designed a new TaqMan® MGB probe, and successfully set up a PCR based method for detecting oral Streptococcus mutans. TaqMan® MGB real-time PCR is a both specific and sensitive bacterial detection method.

Novel and highly sensitive sybr® green real-time pcr for poxvirus detection in odontocete cetaceans.

PubMed

Sacristán, Carlos; Luiz Catão-Dias, José; Ewbank, Ana Carolina; Machado, Eduardo Ferreira; Neves, Elena; Santos-Neto, Elitieri Batista; Azevedo, Alexandre; Laison-Brito, José; De Castilho, Pedro Volkmer; Daura-Jorge, Fábio Gonçalves; Simões-Lopes, Paulo César; Carballo, Matilde; García-Párraga, Daniel; Manuel Sánchez-Vizcaíno, José; Esperón, Fernando

2018-06-08

Poxviruses are emerging pathogens in cetaceans, temporarily named 'Cetaceanpoxvirus' (CePV, family Poxviridae), classified into two main lineages: CePV-1 in odontocetes and CePV-2 in mysticetes. Only a few studies performed the molecular detection of CePVs, based on DNA-polymerase gene and/or DNA-topoisomerase I gene amplification. Herein we describe a new real-time PCR assay based on SYBR ® Green and a new primer set to detect a 150 bp fragment of CePV DNA-polymerase gene, also effective for conventional PCR detection. The novel real-time PCR was able to detect 5 up to 5 × 10 6 copies per reaction of a cloned positive control. Both novel PCR methods were 1000 to 100,000-fold more sensitive than those previously described in the literature. Samples of characteristic poxvirus skin lesions ('tattoo') from one Risso's dolphin (Grampus griseus), two striped dolphins (Stenella coeruleoalba) and two Guiana dolphins (Sotalia guianensis) were all positive to both our novel real time- and conventional PCR methods, even though three of these animals (a Risso's dolphin, a striped dolphin, and a Guiana dolphin) were previously negative to the conventional PCRs previously available. To our knowledge, this is the first real-time PCR detection method for Cetaceanpoxvirus, a much more sensitive tool for the detection of CePV-1 infections. Copyright © 2018 Elsevier B.V. All rights reserved.

A broadly reactive one-step real-time RT-PCR assay for rapid and sensitive detection of hepatitis E virus.

PubMed

Jothikumar, Narayanan; Cromeans, Theresa L; Robertson, Betty H; Meng, X J; Hill, Vincent R

2006-01-01

Hepatitis E virus (HEV) is transmitted by the fecal-oral route and causes sporadic and epidemic forms of acute hepatitis. Large waterborne HEV epidemics have been documented exclusively in developing countries. At least four major genotypes of HEV have been reported worldwide: genotype 1 (found primarily in Asian countries), genotype 2 (isolated from a single outbreak in Mexico), genotype 3 (identified in swine and humans in the United States and many other countries), and genotype 4 (identified in humans, swine and other animals in Asia). To better detect and quantitate different HEV strains that may be present in clinical and environmental samples, we developed a rapid and sensitive real-time RT-PCR assay for the detection of HEV RNA. Primers and probes for the real-time RT-PCR were selected based on the multiple sequence alignments of 27 sequences of the ORF3 region. Thirteen HEV isolates representing genotypes 1-4 were used to standardize the real-time RT-PCR assay. The TaqMan assay detected as few as four genome equivalent (GE) copies of HEV plasmid DNA and detected as low as 0.12 50% pig infectious dose (PID50) of swine HEV. Different concentrations of swine HEV (120-1.2PID50) spiked into a surface water concentrate were detected in the real-time RT-PCR assay. This is the first reporting of a broadly reactive TaqMan RT-PCR assay for the detection of HEV in clinical and environmental samples.

Real-Time Network Management

DTIC Science & Technology

1998-07-01

Report No. WH97JR00-A002 Sponsored by REAL-TIME NETWORK MANAGEMENT FINAL TECHNICAL REPORT K CD July 1998 CO CO O W O Defense Advanced...Approved for public release; distribution unlimited. t^GquALmmsPEami Report No. WH97JR00-A002 REAL-TIME NETWORK MANAGEMENT Synectics Corporation...2.1.2.1 WAN-class Networks 12 2.1.2.2 IEEE 802.3-class Networks 13 2.2 Task 2 - Object Modeling for Architecture 14 2.2.1 Managed Objects 14 2.2.2

Real-time optical holographic tracking of multiple objects

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Liu, Hua-Kuang

1989-01-01

A coherent optical correlation technique for real-time simultaneous tracking of several different objects making independent movements is described, and experimental results are presented. An evaluation of this system compared with digital computing systems is made. The real-time processing capability is obtained through the use of a liquid crystal television spatial light modulator and a dichromated gelatin multifocus hololens. A coded reference beam is utilized in the separation of the output correlation plane associated with each input target so that independent tracking can be achieved.

Polymeric LabChip Real-Time PCR as a Point-of-Care-Potential Diagnostic Tool for Rapid Detection of Influenza A/H1N1 Virus in Human Clinical Specimens

PubMed Central

Song, Hyun-Ok; Kim, Je-Hyoung; Ryu, Ho-Sun; Lee, Dong-Hoon; Kim, Sun-Jin; Kim, Deog-Joong; Suh, In Bum; Choi, Du Young; In, Kwang-Ho; Kim, Sung-Woo; Park, Hyun

2012-01-01

It is clinically important to be able to detect influenza A/H1N1 virus using a fast, portable, and accurate system that has high specificity and sensitivity. To achieve this goal, it is necessary to develop a highly specific primer set that recognizes only influenza A viral genes and a rapid real-time PCR system that can detect even a single copy of the viral gene. In this study, we developed and validated a novel fluidic chip-type real-time PCR (LabChip real-time PCR) system that is sensitive and specific for the detection of influenza A/H1N1, including the pandemic influenza strain A/H1N1 of 2009. This LabChip real-time PCR system has several remarkable features: (1) It allows rapid quantitative analysis, requiring only 15 min to perform 30 cycles of real-time PCR. (2) It is portable, with a weight of only 5.5 kg. (3) The reaction cost is low, since it uses disposable plastic chips. (4) Its high efficiency is equivalent to that of commercially available tube-type real-time PCR systems. The developed disposable LabChip is an economic, heat-transferable, light-transparent, and easy-to-fabricate polymeric chip compared to conventional silicon- or glass-based labchip. In addition, our LabChip has large surface-to-volume ratios in micro channels that are required for overcoming time consumed for temperature control during real-time PCR. The efficiency of the LabChip real-time PCR system was confirmed using novel primer sets specifically targeted to the hemagglutinin (HA) gene of influenza A/H1N1 and clinical specimens. Eighty-five human clinical swab samples were tested using the LabChip real-time PCR. The results demonstrated 100% sensitivity and specificity, showing 72 positive and 13 negative cases. These results were identical to those from a tube-type real-time PCR system. This indicates that the novel LabChip real-time PCR may be an ultra-fast, quantitative, point-of-care-potential diagnostic tool for influenza A/H1N1 with a high sensitivity and specificity. PMID:23285281

Video-based real-time on-street parking occupancy detection system

NASA Astrophysics Data System (ADS)

Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

2013-10-01

Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

Surface Plasmon Resonance Label-Free Monitoring of Antibody Antigen Interactions in Real Time

ERIC Educational Resources Information Center

Kausaite, Asta; van Dijk, Martijn; Castrop, Jan; Ramanaviciene, Almira; Baltrus, John P.; Acaite, Juzefa; Ramanavicius, Arunas

2007-01-01

Detection of biologically active compounds is one of the most important topics in molecular biology and biochemistry. One of the most promising detection methods is based on the application of surface plasmon resonance for label-free detection of biologically active compounds. This method allows one to monitor binding events in real time without…

Early warning by near-real time disturbance monitoring (Invited)

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Zeileis, A.; Herold, M.

2013-12-01

Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a multi-purpose time-series-based disturbance detection approach that identifies and models stable historical variation to enable change detection within newly acquired data. Satellite image time series of vegetation greenness provide a global record of terrestrial vegetation productivity over the past decades. Here, we assess and demonstrate the method by applying it to (1) real-world satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought-related vegetation disturbances (2) landsat image time series to detect forest disturbances. First, results illustrate that disturbances are successfully detected in near real-time while being robust to seasonality and noise. Second, major drought-related disturbance corresponding with most drought-stressed regions in Somalia are detected from mid-2010 onwards. Third, the method can be applied to landsat image time series having a lower temporal data density. Furthermore the method can analyze in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds and does not require time series gap filling. While the data and methods used are appropriate for proof-of-concept development of global scale disturbance monitoring, specific applications (e.g., drought or deforestation monitoring) mandates integration within an operational monitoring framework. Furthermore, the real-time monitoring method is implemented in open-source environment and is freely available in the BFAST package for R software. Information illustrating how to apply the method on satellite image time series are available at http://bfast.R-Forge.R-project.org/ and the example section of the bfastmonitor() function within the BFAST package.

Object detection in cinematographic video sequences for automatic indexing

NASA Astrophysics Data System (ADS)

Stauder, Jurgen; Chupeau, Bertrand; Oisel, Lionel

2003-06-01

This paper presents an object detection framework applied to cinematographic post-processing of video sequences. Post-processing is done after production and before editing. At the beginning of each shot of a video, a slate (also called clapperboard) is shown. The slate contains notably an electronic audio timecode that is necessary for audio-visual synchronization. This paper presents an object detection framework to detect slates in video sequences for automatic indexing and post-processing. It is based on five steps. The first two steps aim to reduce drastically the video data to be analyzed. They ensure high recall rate but have low precision. The first step detects images at the beginning of a shot possibly showing up a slate while the second step searches in these images for candidates regions with color distribution similar to slates. The objective is to not miss any slate while eliminating long parts of video without slate appearance. The third and fourth steps are statistical classification and pattern matching to detected and precisely locate slates in candidate regions. These steps ensure high recall rate and high precision. The objective is to detect slates with very little false alarms to minimize interactive corrections. In a last step, electronic timecodes are read from slates to automize audio-visual synchronization. The presented slate detector has a recall rate of 89% and a precision of 97,5%. By temporal integration, much more than 89% of shots in dailies are detected. By timecode coherence analysis, the precision can be raised too. Issues for future work are to accelerate the system to be faster than real-time and to extend the framework for several slate types.

A new real-time PCR protocol for detection of avian haemosporidians.

PubMed

Bell, Jeffrey A; Weckstein, Jason D; Fecchio, Alan; Tkach, Vasyl V

2015-07-19

Birds possess the most diverse assemblage of haemosporidian parasites; including three genera, Plasmodium, Haemoproteus, and Leucocytozoon. Currently there are over 200 morphologically identified avian haemosporidian species, although true species richness is unknown due to great genetic diversity and insufficient sampling in highly diverse regions. Studies aimed at surveying haemosporidian diversity involve collecting and screening samples from hundreds to thousands of individuals. Currently, screening relies on microscopy and/or single or nested standard PCR. Although effective, these methods are time and resource consuming, and in the case of microscopy require substantial expertise. Here we report a newly developed real-time PCR protocol designed to quickly and reliably detect all three genera of avian haemosporidians in a single biochemical reaction. Using available DNA sequences from avian haemosporidians we designed primers R330F and R480RL, which flank a 182 base pair fragment of mitochondrial conserved rDNA. These primers were initially tested using real-time PCR on samples from Malawi, Africa, previously screened for avian haemosporidians using traditional nested PCR. Our real time protocol was further tested on 94 samples from the Cerrado biome of Brazil, previously screened using a single PCR assay for haemosporidian parasites. These samples were also amplified using modified nested PCR protocols, allowing for comparisons between the three different screening methods (single PCR, nested PCR, real-time PCR). The real-time PCR protocol successfully identified all three genera of avian haemosporidians from both single and mixed infections previously detected from Malawi. There was no significant difference between the three different screening protocols used for the 94 samples from the Brazilian Cerrado (χ(2) = 0.3429, df = 2, P = 0.842). After proving effective, the real-time protocol was used to screen 2113 Brazilian samples, identifying 693 positive samples. Our real-time PCR assay proved as effective as two widely used molecular screening techniques, single PCR and nested PCR. However, the real-time protocol has the distinct advantage of detecting all three genera in a single reaction, which significantly increases efficiency by greatly decreasing screening time and cost. Our real-time PCR protocol is therefore a valuable tool in the quickly expanding field of avian haemosporidian research.

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

Dynamic Engagement of Cognitive Control Modulates Recovery From Misinterpretation During Real-Time Language Processing.

PubMed

Hsu, Nina S; Novick, Jared M

2016-04-01

Speech unfolds swiftly, yet listeners keep pace by rapidly assigning meaning to what they hear. Sometimes, though, initial interpretations turn out to be wrong. How do listeners revise misinterpretations of language input moment by moment to avoid comprehension errors? Cognitive control may play a role by detecting when processing has gone awry and then initiating behavioral adjustments accordingly. However, no research to date has investigated a cause-and-effect interplay between cognitive-control engagement and the overriding of erroneous interpretations in real time. Using a novel cross-task paradigm, we showed that Stroop-conflict detection, which mobilizes cognitive-control procedures, subsequently facilitates listeners' incremental processing of temporarily ambiguous spoken instructions that induce brief misinterpretation. When instructions followed incongruent Stroop items, compared with congruent Stroop items, listeners' eye movements to objects in a scene reflected more transient consideration of the false interpretation and earlier recovery of the correct one. Comprehension errors also decreased. Cognitive-control engagement therefore accelerates sentence-reinterpretation processes, even as linguistic input is still unfolding. © The Author(s) 2016.

Effects of Night Work, Sleep Loss and Time on Task on Simulated Threat Detection Performance

PubMed Central

Basner, Mathias; Rubinstein, Joshua; Fomberstein, Kenneth M.; Coble, Matthew C.; Ecker, Adrian; Avinash, Deepa; Dinges, David F.

2008-01-01

Study Objectives: To investigate the effects of night work and sleep loss on a simulated luggage screening task (SLST) that mimicked the x-ray system used by airport luggage screeners. Design: We developed more than 5,800 unique simulated x-ray images of luggage organized into 31 stimulus sets of 200 bags each. 25% of each set contained either a gun or a knife with low or high target difficulty. The 200-bag stimuli sets were then run on software that simulates an x-ray screening system (SLST). Signal detection analysis was used to obtain measures of hit rate (HR), false alarm rate (FAR), threat detection accuracy (A′), and response bias (B″D). Setting: Experimental laboratory study Participants: 24 healthy nonprofessional volunteers (13 women, mean age ± SD = 29.9 ± 6.5 years). Interventions: Subjects performed the SLST every 2 h during a 5-day period that included a 35 h period of wakefulness that extended to night work and then another day work period after the night without sleep. Results: Threat detection accuracy A′ decreased significantly (P < 0.001) while FAR increased significantly (P < 0.001) during night work, while both A′ (P = 0.001) and HR decreased (P = 0.008) during day work following sleep loss. There were prominent time-on-task effects on response bias B″D (P = 0.002) and response latency (P = 0.004), but accuracy A′ was unaffected. Both HR and FAR increased significantly with increasing study duration (both P < 0.001), while response latency decreased significantly (P < 0.001). Conclusions: This study provides the first systematic evidence that night work and sleep loss adversely affect the accuracy of detecting complex real world objects among high levels of background clutter. If the results can be replicated in professional screeners and real work environments, fatigue in luggage screening personnel may pose a threat for air traffic safety unless countermeasures for fatigue are deployed. Citation: Basner M; Rubinstein J; Fomberstein KM; Coble MC; Avinash D; Dinges DF. Effects of Night Work, Sleep Loss and Time on Task on Simulated Threat Detection Performance. SLEEP 2008;31(9):1251-1259. PMID:18788650

Internal control for real-time polymerase chain reaction based on MS2 bacteriophage for RNA viruses diagnostics

PubMed Central

Zambenedetti, Miriam Ribas; Pavoni, Daniela Parada; Dallabona, Andreia Cristine; Dominguez, Alejandro Correa; Poersch, Celina de Oliveira; Fragoso, Stenio Perdigão; Krieger, Marco Aurélio

2017-01-01

BACKGROUND Real-time reverse transcription polymerase chain reaction (RT-PCR) is routinely used to detect viral infections. In Brazil, it is mandatory the use of nucleic acid tests to detect hepatitis C virus (HCV), hepatitis B virus and human immunodeficiency virus in blood banks because of the immunological window. The use of an internal control (IC) is necessary to differentiate the true negative results from those consequent from a failure in some step of the nucleic acid test. OBJECTIVES The aim of this study was the construction of virus-modified particles, based on MS2 bacteriophage, to be used as IC for the diagnosis of RNA viruses. METHODS The MS2 genome was cloned into the pET47b(+) plasmid, generating pET47b(+)-MS2. MS2-like particles were produced through the synthesis of MS2 RNA genome by T7 RNA polymerase. These particles were used as non-competitive IC in assays for RNA virus diagnostics. In addition, a competitive control for HCV diagnosis was developed by cloning a mutated HCV sequence into the MS2 replicase gene of pET47b(+)-MS2, which produces a non-propagating MS2 particle. The utility of MS2-like particles as IC was evaluated in a one-step format multiplex real-time RT-PCR for HCV detection. FINDINGS We demonstrated that both competitive and non-competitive IC could be successfully used to monitor the HCV amplification performance, including the extraction, reverse transcription, amplification and detection steps, without compromising the detection of samples with low target concentrations. In conclusion, MS2-like particles generated by this strategy proved to be useful IC for RNA virus diagnosis, with advantage that they are produced by a low cost protocol. An attractive feature of this system is that it allows the construction of a multicontrol by the insertion of sequences from more than one pathogen, increasing its applicability for diagnosing different RNA viruses. PMID:28403327

Transient thermal camouflage and heat signature control

NASA Astrophysics Data System (ADS)

Yang, Tian-Zhi; Su, Yishu; Xu, Weikai; Yang, Xiao-Dong

2016-09-01

Thermal metamaterials have been proposed to manipulate heat flux as a new way to cloak or camouflage objects in the infrared world. To date, however, thermal metamaterials only operate in the steady-state and exhibit detectable, transient heat signatures. In this letter, the theoretical basis for a thermal camouflaging technique with controlled transient diffusion is presented. This technique renders an object invisible in real time. More importantly, the thermal camouflaging device instantaneously generates a pre-designed heat signature and behaves as a perfect thermal illusion device. A metamaterial coating with homogeneous and isotropic thermal conductivity, density, and volumetric heat capacity was fabricated and very good camouflaging performance was achieved.

Real-time, wide-area hyperspectral imaging sensors for standoff detection of explosives and chemical warfare agents

NASA Astrophysics Data System (ADS)

Gomer, Nathaniel R.; Tazik, Shawna; Gardner, Charles W.; Nelson, Matthew P.

2017-05-01

Hyperspectral imaging (HSI) is a valuable tool for the detection and analysis of targets located within complex backgrounds. HSI can detect threat materials on environmental surfaces, where the concentration of the target of interest is often very low and is typically found within complex scenery. Unfortunately, current generation HSI systems have size, weight, and power limitations that prohibit their use for field-portable and/or real-time applications. Current generation systems commonly provide an inefficient area search rate, require close proximity to the target for screening, and/or are not capable of making real-time measurements. ChemImage Sensor Systems (CISS) is developing a variety of real-time, wide-field hyperspectral imaging systems that utilize shortwave infrared (SWIR) absorption and Raman spectroscopy. SWIR HSI sensors provide wide-area imagery with at or near real time detection speeds. Raman HSI sensors are being developed to overcome two obstacles present in standard Raman detection systems: slow area search rate (due to small laser spot sizes) and lack of eye-safety. SWIR HSI sensors have been integrated into mobile, robot based platforms and handheld variants for the detection of explosives and chemical warfare agents (CWAs). In addition, the fusion of these two technologies into a single system has shown the feasibility of using both techniques concurrently to provide higher probability of detection and lower false alarm rates. This paper will provide background on Raman and SWIR HSI, discuss the applications for these techniques, and provide an overview of novel CISS HSI sensors focusing on sensor design and detection results.

Development of real-time and lateral flow dipstick recombinase polymerase amplification assays for rapid detection of goatpox virus and sheeppox virus.

PubMed

Yang, Yang; Qin, Xiaodong; Zhang, Xiangle; Zhao, Zhixun; Zhang, Wei; Zhu, Xueliang; Cong, Guozheng; Li, Yanmin; Zhang, Zhidong

2017-07-17

Goatpox virus (GTPV) and sheeppox virus (SPPV), which belong to the Capripoxvirus (CaPV), are economically important pathogens of small ruminants. Therefore, a sensitive, specific and rapid diagnostic assay for detection of GTPV and SPPV is necessary to accurately and promptly control these diseases. Recombinase polymerase amplification (RPA) assays combined with a real-time fluorescent detection (real-time RPA assay) and lateral flow dipstick (RPA LFD assay) were developed targeting the CaPV G-protein-coupled chemokine receptor (GPCR) gene, respectively. The sensitivity of both CaPV real-time RPA assay and CaPV RPA LFD assay were 3 × 10 2 copies per reaction within 20 min at 38 °C. Both assays were highly specific for CaPV, with no cross-reactions with peste des petits ruminants virus, foot-and-mouth disease virus and Orf virus. The evaluation of the performance of these two assays with clinical sample (n = 107) showed that the CaPV real-time RPA assay and CaPV RPA LFD assay were able to specially detect SPPV or GTPV present in samples of ovine in liver, lung, kidney, spleen, skin and blood. This study provided a highly time-efficient and simple alternative for rapid detection of GTPV and SPPV.

Development and validation of a real-time PCR assay for the detection of Toxoplasma gondii DNA in animal and meat samples.

PubMed

Marino, Anna Maria Fausta; Percipalle, Maurizio; Giunta, Renato Paolo; Salvaggio, Antonio; Caracappa, Giulia; Alfonzetti, Tiziana; Aparo, Alessandra; Reale, Stefano

2017-03-01

We report a rapid and reliable method for the detection of Toxoplasma gondii in meat and animal tissues based on real-time polymerase chain reaction (PCR). Samples were collected from cattle, small ruminants, horses, and pigs raised or imported into Sicily, Italy. All DNA preparations were assayed by real-time PCR tests targeted to a 98-bp long fragment in the AF 529-bp repeat element and to the B1 gene using specific primers. Diagnostic sensitivity (100%), diagnostic specificity (100%), limit of detection (0.01 pg), efficiency (92-109%), and precision (mean coefficient of variation = 0.60%), repeatability (100%), reproducibility (100%), and robustness were evaluated using 240 DNA extracted samples (120 positives and 120 negative as per the OIE nested PCR method) from different matrices. Positive results were confirmed by the repetition of both real-time and nested PCR assays. Our study demonstrates the viability of a reliable, rapid, and specific real-time PCR on a large scale to monitor contamination with Toxoplasma cysts in meat and animal specimens. This validated method can be used for postmortem detection in domestic and wild animals and for food safety purposes.

Quantitative detection of pork in commercial meat products by TaqMan® real-time PCR assay targeting the mitochondrial D-loop region.

PubMed

Kim, Miju; Yoo, Insuk; Lee, Shin-Young; Hong, Yeun; Kim, Hae-Yeong

2016-11-01

The TaqMan® real-time PCR assay using the mitochondrial D-loop region was developed for the quantitative detection of pork in processed meat products. The newly designed primers and probe specifically amplified pork without any cross-reactivity with non-target animal species. The limit of detection of the real-time PCR assay was 0.1pg of heat-treated pork meat and 0.1% (w/w) pork meat in beef and chicken meat mixtures. The quantitative real-time PCR assay was applied to analyze the pork meat content in 22 commercial processed meat products including jerkies, press hams, sausages, hamburger patties and steaks, grilled short rib patties, and nuggets. The developed real-time PCR method was able to detect pork meat in various types of processed meat products that declared the use of pork meat on their label. All processed meat products that declared no use of pork meat showed a negative result in the assay. The method developed in this study showed sensitivity and specificity in the quantification of pork meat in commercial processed meat products. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bluetongue virus RNA detection by real-time rt-PCR in post-vaccination samples from cattle.

PubMed

De Leeuw, I; Garigliany, M; Bertels, G; Willems, T; Desmecht, D; De Clercq, K

2015-04-01

Bluetongue virus serotype 8 (BTV-8) was responsible for a large outbreak among European ruminant populations in 2006-2009. In spring 2008, a massive vaccination campaign was undertaken, leading to the progressive disappearance of the virus. During surveillance programmes in Western Europe in 2010-2011, a low but significant number of animals were found weakly positive using BTV-specific real-time RT-PCR, raising questions about a possible low level of virus circulation. An interference of the BTV-8 inactivated vaccine on the result of the real-time RT-PCR was also hypothesized. Several studies specifically addressed the potential association between a recent vaccination and BTV-8 RNA detection in the blood of sheep. Results were contradictory and cattles were not investigated. To enlighten this point, a large study was performed to determine the risks of detection of bluetongue vaccine-associated RNA in the blood and spleen of cattle using real-time RT-PCR. Overall, the results presented clearly demonstrate that vaccine viral RNA can reach the blood circulation in sufficient amounts to be detected by real-time RT-PCR in cattle. This BTV-8 vaccine RNA carriage appears as short lasting. © 2013 Blackwell Verlag GmbH.

Comparison of Nested Polymerase Chain Reaction and Real-Time Polymerase Chain Reaction with Parasitological Methods for Detection of Strongyloides stercoralis in Human Fecal Samples

PubMed Central

Sharifdini, Meysam; Mirhendi, Hossein; Ashrafi, Keyhan; Hosseini, Mostafa; Mohebali, Mehdi; Khodadadi, Hossein; Kia, Eshrat Beigom

2015-01-01

This study was performed to evaluate nested polymerase chain reaction (PCR) and real-time PCR methods for detection of Strongyloides stercoralis in fecal samples compared with parasitological methods. A total of 466 stool samples were examined by conventional parasitological methods (formalin ether concentration [FEC] and agar plate culture [APC]). DNA was extracted using an in-house method, and mitochondrial cytochrome c oxidase subunit 1 and 18S ribosomal genes were amplified by nested PCR and real-time PCR, respectively. Among 466 samples, 12.7% and 18.2% were found infected with S. stercoralis by FEC and APC, respectively. DNA of S. stercoralis was detected in 18.9% and 25.1% of samples by real-time PCR and nested PCR, respectively. Considering parasitological methods as the diagnostic gold standard, the sensitivity and specificity of nested PCR were 100% and 91.6%, respectively, and that of real-time PCR were 84.7% and 95.8%, respectively. However, considering sequence analyzes of the selected nested PCR products, the specificity of nested PCR is increased. In general, molecular methods were superior to parasitological methods. They were more sensitive and more reliable in detection of S. stercoralis in comparison with parasitological methods. Between the two molecular methods, the sensitivity of nested PCR was higher than real-time PCR. PMID:26350449

Approaching near real-time biosensing: microfluidic microsphere based biosensor for real-time analyte detection.

PubMed

Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania

2015-04-15

In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays. Copyright © 2014 Elsevier B.V. All rights reserved.

On Gamma Ray Instrument On-Board Data Processing Real-Time Computational Algorithm for Cosmic Ray Rejection

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Hunter, Stanley D.; Hanu, Andrei R.; Sheets, Teresa B.

2016-01-01

Richard O. Duda and Peter E. Hart of Stanford Research Institute in [1] described the recurring problem in computer image processing as the detection of straight lines in digitized images. The problem is to detect the presence of groups of collinear or almost collinear figure points. It is clear that the problem can be solved to any desired degree of accuracy by testing the lines formed by all pairs of points. However, the computation required for n=NxM points image is approximately proportional to n2 or O(n2), becoming prohibitive for large images or when data processing cadence time is in milliseconds. Rosenfeld in [2] described an ingenious method due to Hough [3] for replacing the original problem of finding collinear points by a mathematically equivalent problem of finding concurrent lines. This method involves transforming each of the figure points into a straight line in a parameter space. Hough chose to use the familiar slope-intercept parameters, and thus his parameter space was the two-dimensional slope-intercept plane. A parallel Hough transform running on multi-core processors was elaborated in [4]. There are many other proposed methods of solving a similar problem, such as sampling-up-the-ramp algorithm (SUTR) [5] and algorithms involving artificial swarm intelligence techniques [6]. However, all state-of-the-art algorithms lack in real time performance. Namely, they are slow for large images that require performance cadence of a few dozens of milliseconds (50ms). This problem arises in spaceflight applications such as near real-time analysis of gamma ray measurements contaminated by overwhelming amount of traces of cosmic rays (CR). Future spaceflight instruments such as the Advanced Energetic Pair Telescope instrument (AdEPT) [7-9] for cosmos gamma ray survey employ large detector readout planes registering multitudes of cosmic ray interference events and sparse science gamma ray event traces' projections. The AdEPT science of interest is in the gamma ray events and the problem is to detect and reject the much more voluminous cosmic ray projections, so that the remaining science data can be telemetered to the ground over the constrained communication link. The state-of-the-art in cosmic rays detection and rejection does not provide an adequate computational solution. This paper presents a novel approach to the AdEPT on-board data processing burdened with the CR detection top pole bottleneck problem. This paper is introducing the data processing object, demonstrates object segmentation and distribution for processing among many processing elements (PEs) and presents solution algorithm for the processing bottleneck - the CR-Algorithm. The algorithm is based on the a priori knowledge that a CR pierces the entire instrument pressure vessel. This phenomenon is also the basis for a straightforward CR simulator, allowing the CR-Algorithm performance testing. Parallel processing of the readout image's (2(N+M) - 4) peripheral voxels is detecting all CRs, resulting in O(n) computational complexity. This algorithm near real-time performance is making AdEPT class spaceflight instruments feasible.

Avian influenza virus detection and quantitation by real-time RT-PCR

USDA-ARS?s Scientific Manuscript database

Real-time RT-PCR (rRT-PCR) has been used for avian influenza virus (AIV) detection since the early 2000’s for routine surveillance, during outbreaks and for research. Some of the advantages of rRT-PCR are: high sensitivity, high specificity, rapid time-to-result, scalability, cost, and its inherentl...

Evaluation of a new single-tube multiprobe real-time PCR for diagnosis of Entamoeba histolytica and Entamoeba dispar.

PubMed

Liang, Shih-Yu; Hsia, Kan-Tai; Chan, Yun-Hsien; Fan, Chia-Kwung; Jiang, Donald Dah-Shyong; Landt, Olfert; Ji, Dar-Der

2010-08-01

A single-tube multiprobe real-time PCR assay for simultaneous detection of Entamoeba histolytica and Entamoeba dispar was developed. One primer pair with 2 species-specific probes was designed based on new SSU RNA regions of the ribosomal DNA-containing episome. The sensitivity is 1 parasite per milliliter of feces and thus superior to the conventional nested PCR and comparable to other published real-time PCR protocols. The applicability for clinical diagnosis was validated with 218 stool specimens from patients. A total of 51 E. histolytica and 39 E. dispar positive samples was detected by the multiprobe real-time PCR compared to 39 and 22 by routine nested PCR diagnosis. The detection rate of Entamoeba species for the multiprobe real-time PCR assays was significantly higher than the nested PCR (40.8% vs. 28.0%, P < 0.01). The test did not show cross reactivity with DNA from Entamoeba moshkovskii, Giardia lamblia , Cryptosporidium sp., Escherichia coli , or other nonpathogenic enteric parasites. The multiprobe real-time PCR assay is simple and rapid and has high specificity and sensitivity. The assay could streamline the laboratory diagnosis procedure and facilitate epidemiological investigation.

[Rapid identification of meningitis due to bacterial pathogens].

PubMed

Ubukata, Kimiko

2013-01-01

We constructed a new real-time PCR method to detect causative pathogens in cerebrospinal fluid (CSF) from patient due to bacterial meningitis. The eight pathogens targeted in the PCR are Streptococcus pneumoniae, Haemophilus influenzae, Streptococcus agalactiae, Staphylococcus aurues, Neisseria meningitides, Listeria monocytogenes, Esherichia coli, and Mycoplasma pneumoniae. The total time from DNA extraction from CSF to PCR analysis was 1.5 hour. The pathogens were detected in 72% of the CSF samples (n=115) by real-time PCR, but in only 48% by culture, although the microorganisms were completely concordant. The detection rate of pathogens with PCR was significantly better than that with cultures in patients with antibiotic administration.In conclusion, detection with real-time PCR is useful for rapidly identifying the causative pathogens of meningitis and for examining the clinical course of chemotherapy.

Near real-time shadow detection and removal in aerial motion imagery application

NASA Astrophysics Data System (ADS)

Silva, Guilherme F.; Carneiro, Grace B.; Doth, Ricardo; Amaral, Leonardo A.; Azevedo, Dario F. G. de

2018-06-01

This work presents a method to automatically detect and remove shadows in urban aerial images and its application in an aerospace remote monitoring system requiring near real-time processing. Our detection method generates shadow masks and is accelerated by GPU programming. To obtain the shadow masks, we converted images from RGB to CIELCh model, calculated a modified Specthem ratio, and applied multilevel thresholding. Morphological operations were used to reduce shadow mask noise. The shadow masks are used in the process of removing shadows from the original images using the illumination ratio of the shadow/non-shadow regions. We obtained shadow detection accuracy of around 93% and shadow removal results comparable to the state-of-the-art while maintaining execution time under real-time constraints.

Detection of Mycoplasma pneumoniae by real-time PCR.

PubMed

Winchell, Jonas M; Mitchell, Stephanie L

2013-01-01

Mycoplasma pneumoniae is a significant cause of respiratory disease, accounting for approximately 20% of cases of community-acquired pneumonia. Although several diagnostic methods exist to detect M. pneumoniae in respiratory specimens, real-time PCR has emerged as a significant improvement for the rapid diagnosis of this pathogen. The method described herein details the procedure for the detection of M. pneumoniae by real-time PCR (qPCR). The qPCR assay described can be performed with three targets specific for M. pneumoniae (Mp181, Mp3, and Mp7) and one marker for the detection of the RNaseP gene found in human nucleic acid as an internal control reaction. Recent studies have demonstrated the ability of this procedure to reliably identify this agent and facilitate the timely recognition of an outbreak.

Real-Time and Post-Processed Georeferencing for Hyperpspectral Drone Remote Sensing

NASA Astrophysics Data System (ADS)

Oliveira, R. A.; Khoramshahi, E.; Suomalainen, J.; Hakala, T.; Viljanen, N.; Honkavaara, E.

2018-05-01

The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5 m. The results showed that the real-time remote sensing is promising and feasible in both test sites.

Real-world spatial regularities affect visual working memory for objects.

PubMed

Kaiser, Daniel; Stein, Timo; Peelen, Marius V

2015-12-01

Traditional memory research has focused on measuring and modeling the capacity of visual working memory for simple stimuli such as geometric shapes or colored disks. Although these studies have provided important insights, it is unclear how their findings apply to memory for more naturalistic stimuli. An important aspect of real-world scenes is that they contain a high degree of regularity: For instance, lamps appear above tables, not below them. In the present study, we tested whether such real-world spatial regularities affect working memory capacity for individual objects. Using a delayed change-detection task with concurrent verbal suppression, we found enhanced visual working memory performance for objects positioned according to real-world regularities, as compared to irregularly positioned objects. This effect was specific to upright stimuli, indicating that it did not reflect low-level grouping, because low-level grouping would be expected to equally affect memory for upright and inverted displays. These results suggest that objects can be held in visual working memory more efficiently when they are positioned according to frequently experienced real-world regularities. We interpret this effect as the grouping of single objects into larger representational units.

A novel adaptive, real-time algorithm to detect gait events from wearable sensors.

PubMed

Chia Bejarano, Noelia; Ambrosini, Emilia; Pedrocchi, Alessandra; Ferrigno, Giancarlo; Monticone, Marco; Ferrante, Simona

2015-05-01

A real-time, adaptive algorithm based on two inertial and magnetic sensors placed on the shanks was developed for gait-event detection. For each leg, the algorithm detected the Initial Contact (IC), as the minimum of the flexion/extension angle, and the End Contact (EC) and the Mid-Swing (MS), as minimum and maximum of the angular velocity, respectively. The algorithm consisted of calibration, real-time detection, and step-by-step update. Data collected from 22 healthy subjects (21 to 85 years) walking at three self-selected speeds were used to validate the algorithm against the GaitRite system. Comparable levels of accuracy and significantly lower detection delays were achieved with respect to other published methods. The algorithm robustness was tested on ten healthy subjects performing sudden speed changes and on ten stroke subjects (43 to 89 years). For healthy subjects, F1-scores of 1 and mean detection delays lower than 14 ms were obtained. For stroke subjects, F1-scores of 0.998 and 0.944 were obtained for IC and EC, respectively, with mean detection delays always below 31 ms. The algorithm accurately detected gait events in real time from a heterogeneous dataset of gait patterns and paves the way for the design of closed-loop controllers for customized gait trainings and/or assistive devices.