46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

Time series sightability modeling of animal populations.

PubMed

ArchMiller, Althea A; Dorazio, Robert M; St Clair, Katherine; Fieberg, John R

2018-01-01

Logistic regression models-or "sightability models"-fit to detection/non-detection data from marked individuals are often used to adjust for visibility bias in later detection-only surveys, with population abundance estimated using a modified Horvitz-Thompson (mHT) estimator. More recently, a model-based alternative for analyzing combined detection/non-detection and detection-only data was developed. This approach seemed promising, since it resulted in similar estimates as the mHT when applied to data from moose (Alces alces) surveys in Minnesota. More importantly, it provided a framework for developing flexible models for analyzing multiyear detection-only survey data in combination with detection/non-detection data. During initial attempts to extend the model-based approach to multiple years of detection-only data, we found that estimates of detection probabilities and population abundance were sensitive to the amount of detection-only data included in the combined (detection/non-detection and detection-only) analysis. Subsequently, we developed a robust hierarchical modeling approach where sightability model parameters are informed only by the detection/non-detection data, and we used this approach to fit a fixed-effects model (FE model) with year-specific parameters and a temporally-smoothed model (TS model) that shares information across years via random effects and a temporal spline. The abundance estimates from the TS model were more precise, with decreased interannual variability relative to the FE model and mHT abundance estimates, illustrating the potential benefits from model-based approaches that allow information to be shared across years.

Time series sightability modeling of animal populations

USGS Publications Warehouse

ArchMiller, Althea A.; Dorazio, Robert; St. Clair, Katherine; Fieberg, John R.

2018-01-01

Logistic regression models—or “sightability models”—fit to detection/non-detection data from marked individuals are often used to adjust for visibility bias in later detection-only surveys, with population abundance estimated using a modified Horvitz-Thompson (mHT) estimator. More recently, a model-based alternative for analyzing combined detection/non-detection and detection-only data was developed. This approach seemed promising, since it resulted in similar estimates as the mHT when applied to data from moose (Alces alces) surveys in Minnesota. More importantly, it provided a framework for developing flexible models for analyzing multiyear detection-only survey data in combination with detection/non-detection data. During initial attempts to extend the model-based approach to multiple years of detection-only data, we found that estimates of detection probabilities and population abundance were sensitive to the amount of detection-only data included in the combined (detection/non-detection and detection-only) analysis. Subsequently, we developed a robust hierarchical modeling approach where sightability model parameters are informed only by the detection/non-detection data, and we used this approach to fit a fixed-effects model (FE model) with year-specific parameters and a temporally-smoothed model (TS model) that shares information across years via random effects and a temporal spline. The abundance estimates from the TS model were more precise, with decreased interannual variability relative to the FE model and mHT abundance estimates, illustrating the potential benefits from model-based approaches that allow information to be shared across years.

Assessment of soil-gas contamination at the 17th Street landfill, Fort Gordon, Georgia, 2011

USGS Publications Warehouse

Falls, W. Fred; Caldwell, Andral W.; Guimaraes, Wladmir G.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2012-01-01

Assessments of contaminants in soil gas were conducted in two study areas at Fort Gordon, Georgia, in July and August of 2011 to supplement environmental contaminant data for previous studies at the 17th Street landfill. The two study areas include northern and eastern parts of the 17th Street landfill and the adjacent wooded areas to the north and east of the landfill. These study areas were chosen because of their close proximity to the surface water in Wilkerson Lake and McCoys Creek. A total of 48 soil-gas samplers were deployed for the July 28 to August 3, 2011, assessment in the eastern study area. The assessment mostly identified detections of total petroleum hydrocarbons (TPH), and gasoline- and diesel-range compounds, but also identified the presence of chlorinated solvents in six samplers, chloroform in three samplers, 2-methyl naphthalene in one sampler, and trimethylbenzene in one sampler. The TPH masses exceeded 0.02 microgram (μg) in all 48 samplers and exceeded 0.9 μg in 24 samplers. Undecane, one of the three diesel-range compounds used to calculate the combined mass for diesel-range compounds, was detected in 17 samplers and is the second most commonly detected compound in the eastern study area, exceeded only by the number of TPH detections. Six samplers had detections of toluene, but other gasoline compounds were detected with toluene in three of the samplers, including detections of ethylbenzene, meta- and para-xylene, and octane. All detections of chlorinated organic compounds had soil-gas masses equal to or less than 0.08 μg, including three detections of trichloroethene, three detections of perchloroethene, three chloroform detections, one 1,4-dichlorobenzene detection, and one 1,1,2-trichloroethane detection. Three methylated compounds were detected in the eastern study area, but were detected at or below method detection levels. A total of 32 soil-gas samplers were deployed for the August 11–24, 2011, assessment in the northern study area. All samplers in the survey had detections of TPH, but only eight of the samplers had detections of TPH greater than 0.9 mg. Four samplers had TPH detections greater than 9 mg; the only other fuel-related compounds detected in these four samplers included toluene in three of the samplers and undecane in the fourth sampler. Three samplers deployed along the western margin of the northern landfill had detections of both diesel-and gasoline-related compounds; however, the diesel-related compounds were detected at or below method detection levels. Seven samplers in the northern study area had detections of chlorinated compounds, including three perchloroethene detections, three chloroform detections, and one 1,4-dichloro-benzene detection. One sampler on the western margin of the landfill had detections of 1,2,4-trimethylbenzene and 1,3,5-tr-methylbenene below method detection levels.

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.

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

DTIC Science & Technology

2013-04-24

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals Vernon...datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal . We have developed...As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and

Accounting for imperfect detection in ecology: a quantitative review.

PubMed

Kellner, Kenneth F; Swihart, Robert K

2014-01-01

Detection in studies of species abundance and distribution is often imperfect. Assuming perfect detection introduces bias into estimation that can weaken inference upon which understanding and policy are based. Despite availability of numerous methods designed to address this assumption, many refereed papers in ecology fail to account for non-detection error. We conducted a quantitative literature review of 537 ecological articles to measure the degree to which studies of different taxa, at various scales, and over time have accounted for imperfect detection. Overall, just 23% of articles accounted for imperfect detection. The probability that an article incorporated imperfect detection increased with time and varied among taxa studied; studies of vertebrates were more likely to incorporate imperfect detection. Among articles that reported detection probability, 70% contained per-survey estimates of detection that were less than 0.5. For articles in which constancy of detection was tested, 86% reported significant variation. We hope that our findings prompt more ecologists to consider carefully the detection process when designing studies and analyzing results, especially for sub-disciplines where incorporation of imperfect detection in study design and analysis so far has been lacking.

Improvement of the Raman detection system for pesticide residues on/in fruits and vegetables

NASA Astrophysics Data System (ADS)

Li, Yan; Peng, Yankun; Zhai, Chen; Chao, Kuanglin; Qin, Jianwei

2017-05-01

Pesticide residue is one of the major challenges to fruits safety, while the traditional detection methods of pesticide residue on fruits and vegetables can't afford the demand of rapid detection in actual production because of timeconsuming. Thus rapid identification and detection methods for pesticide residue are urgently needed at present. While most Raman detection systems in the market are spot detection systems, which limits the range of application. In the study, our lab develops a Raman detection system to achieve area-scan thorough the self-developed spot detection Raman system with a control software and two devices. In the system, the scanning area is composed of many scanning spots, which means every spot needs to be detected and more time will be taken than area-scan Raman system. But lower detection limit will be achieved in this method. And some detection device is needed towards fruits and vegetables in different shape. Two detection devices are developed to detect spherical fruits and leaf vegetables. During the detection, the device will make spherical fruit rotate along its axis of symmetry, and leaf vegetables will be pressed in the test surface smoothly. The detection probe will be set to keep a proper distance to the surface of fruits and vegetables. It should make sure the laser shins on the surface of spherical fruit vertically. And two software are used to detect spherical fruits and leaf vegetables will be integrated to one, which make the operator easier to switch. Accordingly two detection devices for spherical fruits and leaf vegetables will also be portable devices to make it easier to change. In the study, a new way is developed to achieve area-scan result by spot-scan Raman detection system.

Shadow detection of moving objects based on multisource information in Internet of things

NASA Astrophysics Data System (ADS)

Ma, Zhen; Zhang, De-gan; Chen, Jie; Hou, Yue-xian

2017-05-01

Moving object detection is an important part in intelligent video surveillance under the banner of Internet of things. The detection of moving target's shadow is also an important step in moving object detection. On the accuracy of shadow detection will affect the detection results of the object directly. Based on the variety of shadow detection method, we find that only using one feature can't make the result of detection accurately. Then we present a new method for shadow detection which contains colour information, the invariance of optical and texture feature. Through the comprehensive analysis of the detecting results of three kinds of information, the shadow was effectively determined. It gets ideal effect in the experiment when combining advantages of various methods.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOEpatents

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2015-07-28

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

[A review on polarization information in the remote sensing detection].

PubMed

Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

2010-04-01

Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

Photoacoustic Spectroscopy for Trace Vapor Detection and Standoff Detection of Explosives

DTIC Science & Technology

2016-08-01

ARL-RP-0577 ● AUG 2016 US Army Research Laboratory Photoacoustic Spectroscopy for Trace Vapor Detection and Standoff Detection...Photoacoustic Spectroscopy for Trace Vapor Detection and Standoff Detection of Explosives by Ellen L Holthoff and Paul M Pellegrino Sensors and Electron...

Wireless LAN security management with location detection capability in hospitals.

PubMed

Tanaka, K; Atarashi, H; Yamaguchi, I; Watanabe, H; Yamamoto, R; Ohe, K

2012-01-01

In medical institutions, unauthorized access points and terminals obstruct the stable operation of a large-scale wireless local area network (LAN) system. By establishing a real-time monitoring method to detect such unauthorized wireless devices, we can improve the efficiency of security management. We detected unauthorized wireless devices by using a centralized wireless LAN system and a location detection system at 370 access points at the University of Tokyo Hospital. By storing the detected radio signal strength and location information in a database, we evaluated the risk level from the detection history. We also evaluated the location detection performance in our hospital ward using Wi-Fi tags. The presence of electric waves outside the hospital and those emitted from portable game machines with wireless communication capability was confirmed from the detection result. The location detection performance showed an error margin of approximately 4 m in detection accuracy and approximately 5% in false detection. Therefore, it was effective to consider the radio signal strength as both an index of likelihood at the detection location and an index for the level of risk. We determined the location of wireless devices with high accuracy by filtering the detection results on the basis of radio signal strength and detection history. Results of this study showed that it would be effective to use the developed location database containing radio signal strength and detection history for security management of wireless LAN systems and more general-purpose location detection applications.

A study on obstacle detection method of the frontal view using a camera on highway

NASA Astrophysics Data System (ADS)

Nguyen, Van-Quang; Park, Jeonghyeon; Seo, Changjun; Kim, Heungseob; Boo, Kwangsuck

2018-03-01

In this work, we introduce an approach to detect vehicles for driver assistance, or warning system. For driver assistance system, it must detect both lanes (left and right side lane), and discover vehicles ahead of the test vehicle. Therefore, in this study, we use a camera, it is installed on the windscreen of the test vehicle. Images from the camera are used to detect three lanes, and detect multiple vehicles. In lane detection, line detection and vanishing point estimation are used. For the vehicle detection, we combine the horizontal and vertical edge detection, the horizontal edge is used to detect the vehicle candidates, and then the vertical edge detection is used to verify the vehicle candidates. The proposed algorithm works with of 480 × 640 image frame resolution. The system was tested on the highway in Korea.

78 FR 26795 - Announcement of Requirements and Registration for the National Radiological and Nuclear Detection...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-08

... Radiological and Nuclear Detection Challenge AGENCY: Domestic Nuclear Detection Office, DHS. ACTION: Notice. SUMMARY: DNDO announces the National Radiological and Nuclear Detection (Rad/Nuc) Challenge, a...), Domestic Nuclear Detection Office (DNDO), announces the National Radiological and Nuclear Detection (Rad...

49 CFR 234.227 - Train detection apparatus.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Train detection apparatus. 234.227 Section 234.227..., Inspection, and Testing Maintenance Standards § 234.227 Train detection apparatus. (a) Train detection apparatus shall be maintained to detect a train or railcar in any part of a train detection circuit, in...

49 CFR 234.227 - Train detection apparatus.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Train detection apparatus. 234.227 Section 234.227..., Inspection, and Testing Maintenance Standards § 234.227 Train detection apparatus. (a) Train detection apparatus shall be maintained to detect a train or railcar in any part of a train detection circuit, in...

Remote detection of electronic devices

DOEpatents

Judd, Stephen L [Los Alamos, NM; Fortgang, Clifford M [Los Alamos, NM; Guenther, David C [Los Alamos, NM

2012-09-25

An apparatus and method for detecting solid-state electronic devices are described. Non-linear junction detection techniques are combined with spread-spectrum encoding and cross correlation to increase the range and sensitivity of the non-linear junction detection and to permit the determination of the distances of the detected electronics. Nonlinear elements are detected by transmitting a signal at a chosen frequency and detecting higher harmonic signals that are returned from responding devices.

The design method and research status of vehicle detection system based on geomagnetic detection principle

NASA Astrophysics Data System (ADS)

Lin, Y. H.; Bai, R.; Qian, Z. H.

2018-03-01

Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

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

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using amore » combinatorial algorithm.« less

Field-effect amperometric immuno-detection of protein biomarker.

PubMed

Wang, Jiapeng; Yau, Siu-Tung

2011-11-15

The field-effect enzymatic detection technique has been applied to the amperometric immunoassay of the cancer biomarker, carcinoma antigen 125 (CA 125). The detection adopted a reagentless approach, in which the analyte, CA 125, was immobilized on the detecting electrode, which was modified using carbon nanotubes, and the detection signal was obtained by measuring the reduction peak current of the enzyme that was used to label the antibody. A gating voltage was applied to the detecting electrode, inducing increase in the signal current and therefore providing amplification of the detection signal. The voltage-controlled signal amplification of the detection system has increased the sensitivity and lowered the detection limit of the system. A detection limit of 0.9U/ml was obtained in the work. Copyright © 2011 Elsevier B.V. All rights reserved.

Rapid detection of Naegleria fowleri in water distribution pipeline biofilms and drinking water samples.

PubMed

Puzon, Geoffrey J; Lancaster, James A; Wylie, Jason T; Plumb, Iason J

2009-09-01

Rapid detection of pathogenic Naegleria fowler in water distribution networks is critical for water utilities. Current detection methods rely on sampling drinking water followed by culturing and molecular identification of purified strains. This culture-based method takes an extended amount of time (days), detects both nonpathogenic and pathogenic species, and does not account for N. fowleri cells associated with pipe wall biofilms. In this study, a total DNA extraction technique coupled with a real-time PCR method using primers specific for N. fowleri was developed and validated. The method readily detected N. fowleri without preculturing with the lowest detection limit for N. fowleri cells spiked in biofilm being one cell (66% detection rate) and five cells (100% detection rate). For drinking water, the detection limit was five cells (66% detection rate) and 10 cells (100% detection rate). By comparison, culture-based methods were less sensitive for detection of cells spiked into both biofilm (66% detection for <10 cells) and drinking water (0% detection for <10 cells). In mixed cultures of N. fowleri and nonpathogenic Naegleria, the method identified N. fowleri in 100% of all replicates, whereastests with the current consensus primers detected N. fowleri in only 5% of all replicates. Application of the new method to drinking water and pipe wall biofilm samples obtained from a distribution network enabled the detection of N. fowleri in under 6 h, versus 3+ daysforthe culture based method. Further, comparison of the real-time PCR data from the field samples and the standard curves enabled an approximation of N. fowleri cells in the biofilm and drinking water. The use of such a method will further aid water utilities in detecting and managing the persistence of N. fowleri in water distribution networks.

Comparing scat detection dogs, cameras, and hair snares for surveying carnivores

USGS Publications Warehouse

Long, Robert A.; Donovan, T.M.; MacKay, Paula; Zielinski, William J.; Buzas, Jeffrey S.

2007-01-01

Carnivores typically require large areas of habitat, exist at low natural densities, and exhibit elusive behavior - characteristics that render them difficult to study. Noninvasive survey methods increasingly provide means to collect extensive data on carnivore occupancy, distribution, and abundance. During the summers of 2003-2004, we compared the abilities of scat detection dogs, remote cameras, and hair snares to detect black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus) at 168 sites throughout Vermont. All 3 methods detected black bears; neither fishers nor bobcats were detected by hair snares. Scat detection dogs yielded the highest raw detection rate and probability of detection (given presence) for each of the target species, as well as the greatest number of unique detections (i.e., occasions when only one method detected the target species). We estimated that the mean probability of detecting the target species during a single visit to a site with a detection dog was 0.87 for black bears, 0.84 for fishers, and 0.27 for bobcats. Although the cost of surveying with detection dogs was higher than that of remote cameras or hair snares, the efficiency of this method rendered it the most cost-effective survey method.

Comparison of outliers and novelty detection to identify ionospheric TEC irregularities during geomagnetic storm and substorm

NASA Astrophysics Data System (ADS)

Pattisahusiwa, Asis; Houw Liong, The; Purqon, Acep

2016-08-01

In this study, we compare two learning mechanisms: outliers and novelty detection in order to detect ionospheric TEC disturbance by November 2004 geomagnetic storm and January 2005 substorm. The mechanisms are applied by using v-SVR learning algorithm which is a regression version of SVM. Our results show that both mechanisms are quiet accurate in learning TEC data. However, novelty detection is more accurate than outliers detection in extracting anomalies related to geomagnetic events. The detected anomalies by outliers detection are mostly related to trend of data, while novelty detection are associated to geomagnetic events. Novelty detection also shows evidence of LSTID during geomagnetic events.

Presence-nonpresence surveys of golden-cheeked warblers: detection, occupancy and survey effort

USGS Publications Warehouse

Watson, C.A.; Weckerly, F.W.; Hatfield, J.S.; Farquhar, C.C.; Williamson, P.S.

2008-01-01

Surveys to detect the presence or absence of endangered species may not consistently cover an area, account for imperfect detection or consider that detection and species presence at sample units may change within a survey season. We evaluated a detection?nondetection survey method for the federally endangered golden-cheeked warbler (GCWA) Dendroica chrysoparia. Three study areas were selected across the breeding range of GCWA in central Texas. Within each area, 28-36 detection stations were placed 200 m apart. Each detection station was surveyed nine times during the breeding season in 2 consecutive years. Surveyors remained up to 8 min at each detection station recording GCWA detected by sight or sound. To assess the potential influence of environmental covariates (e.g. slope, aspect, canopy cover, study area) on detection and occupancy and possible changes in occupancy and detection probabilities within breeding seasons, 30 models were analyzed. Using information-theoretic model selection procedures, we found that detection probabilities and occupancy varied among study areas and within breeding seasons. Detection probabilities ranged from 0.20 to 0.80 and occupancy ranged from 0.56 to 0.95. Because study areas with high detection probabilities had high occupancy, a conservative survey effort (erred towards too much surveying) was estimated using the lowest detection probability. We determined that nine surveys of 35 stations were needed to have estimates of occupancy with coefficients of variation <20%. Our survey evaluation evidently captured the key environmental variable that influenced bird detection (GCWA density) and accommodated the changes in GCWA distribution throughout the breeding season.

Unsupervised Anomaly Detection Based on Clustering and Multiple One-Class SVM

NASA Astrophysics Data System (ADS)

Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Kwon, Yongjin

Intrusion detection system (IDS) has played an important role as a device to defend our networks from cyber attacks. However, since it is unable to detect unknown attacks, i.e., 0-day attacks, the ultimate challenge in intrusion detection field is how we can exactly identify such an attack by an automated manner. Over the past few years, several studies on solving these problems have been made on anomaly detection using unsupervised learning techniques such as clustering, one-class support vector machine (SVM), etc. Although they enable one to construct intrusion detection models at low cost and effort, and have capability to detect unforeseen attacks, they still have mainly two problems in intrusion detection: a low detection rate and a high false positive rate. In this paper, we propose a new anomaly detection method based on clustering and multiple one-class SVM in order to improve the detection rate while maintaining a low false positive rate. We evaluated our method using KDD Cup 1999 data set. Evaluation results show that our approach outperforms the existing algorithms reported in the literature; especially in detection of unknown attacks.

Comparison of human and algorithmic target detection in passive infrared imagery

NASA Astrophysics Data System (ADS)

Weber, Bruce A.; Hutchinson, Meredith

2003-09-01

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

Helicopter main-rotor speed effects: A comparison of predicted ranges of detection from the aural detection program ICHIN and the electronic detection program ARCAS

NASA Technical Reports Server (NTRS)

Mueller, Arnold W.; Smith, Charles D.

1991-01-01

NASA LaRC personnel have conducted a strudy of the predicted acoustic detection ranges associated with reduced helicopter main rotor speeds. This was accomplished by providing identical input information to both the aural detection program ICHIN 6, (I Can Hear It Now, version 6) and the electronic acoustic detection program ARCAS (Assessment of Rotorcraft Detection by Acoustics Sensing). In this study, it was concluded that reducing the main rotor speed of the helicopter by 27 percent reduced both the predicted aural and electronic detection ranges by approximately 50 percent. Additionally, ARCAS was observed to function better with narrowband spectral input than with one-third octave band spectral inputs and the predicted electronic range of acoustic detection is greater than the predicted aural detection range.

A comparison of moving object detection methods for real-time moving object detection

NASA Astrophysics Data System (ADS)

Roshan, Aditya; Zhang, Yun

2014-06-01

Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

Accurate mobile malware detection and classification in the cloud.

PubMed

Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

2015-01-01

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

Research on IPv6 intrusion detection system Snort-based

NASA Astrophysics Data System (ADS)

Shen, Zihao; Wang, Hui

2010-07-01

This paper introduces the common intrusion detection technologies, discusses the work flow of Snort intrusion detection system, and analyzes IPv6 data packet encapsulation and protocol decoding technology. We propose the expanding Snort architecture to support IPv6 intrusion detection in accordance with CIDF standard combined with protocol analysis technology and pattern matching technology, and present its composition. The research indicates that the expanding Snort system can effectively detect various intrusion attacks; it is high in detection efficiency and detection accuracy and reduces false alarm and omission report, which effectively solves the problem of IPv6 intrusion detection.

Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

PubMed

Ganapathy, S; Yogesh, P; Kannan, A

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

Two-stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images.

PubMed

Emam, Mahmoud; Han, Qi; Zhang, Hongli

2018-01-01

In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods. © 2017 American Academy of Forensic Sciences.

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

PubMed Central

Ganapathy, S.; Yogesh, P.; Kannan, A.

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

Spectral methods to detect surface mines

NASA Astrophysics Data System (ADS)

Winter, Edwin M.; Schatten Silvious, Miranda

2008-04-01

Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

An integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection

NASA Astrophysics Data System (ADS)

Liu, Hai-Tao; Wen, Zhi-Yu; Xu, Yi; Shang, Zheng-Guo; Peng, Jin-Lan; Tian, Peng

2017-09-01

In this paper, an integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection was purposed based on microfluidic chips dielectrophoresis technique and electrochemical impedance detection principle. The microsystems include microfluidic chip, main control module, and drive and control module, and signal detection and processing modulet and result display unit. The main control module produce the work sequence of impedance detection system parts and achieve data communication functions, the drive and control circuit generate AC signal which amplitude and frequency adjustable, and it was applied on the foodborne pathogens impedance analysis microsystems to realize the capture enrichment and impedance detection. The signal detection and processing circuit translate the current signal into impendence of bacteria, and transfer to computer, the last detection result is displayed on the computer. The experiment sample was prepared by adding Escherichia coli standard sample into chicken sample solution, and the samples were tested on the dielectrophoresis chip capture enrichment and in-situ impedance detection microsystems with micro-array electrode microfluidic chips. The experiments show that the Escherichia coli detection limit of microsystems is 5 × 104 CFU/mL and the detection time is within 6 min in the optimization of voltage detection 10 V and detection frequency 500 KHz operating conditions. The integrated microfluidic analysis microsystems laid the solid foundation for rapid real-time in-situ detection of bacteria.

46 CFR 27.203 - What are the requirements for fire detection on towing vessels?

Code of Federal Regulations, 2010 CFR

2010-10-01

... detection on towing vessels? You must have a fire-detection system installed on your vessel to detect engine... use an existing engine-room-monitoring system (with fire-detection capability) instead of a fire-detection system, if the monitoring system is operable and complies with this section. You must ensure that...

Underwater electric field detection system based on weakly electric fish

NASA Astrophysics Data System (ADS)

Xue, Wei; Wang, Tianyu; Wang, Qi

2018-04-01

Weakly electric fish sense their surroundings in complete darkness by their active electric field detection system. However, due to the insufficient detection capacity of the electric field, the detection distance is not enough, and the detection accuracy is not high. In this paper, a method of underwater detection based on rotating current field theory is proposed to improve the performance of underwater electric field detection system. First of all, we built underwater detection system based on the theory of the spin current field mathematical model with the help of the results of previous researchers. Then we completed the principle prototype and finished the metal objects in the water environment detection experiments, laid the foundation for the further experiments.

Effects of loss on the phase sensitivity with parity detection in an SU(1,1) interferometer

NASA Astrophysics Data System (ADS)

Li, Dong; Yuan, Chun-Hua; Yao, Yao; Jiang, Wei; Li, Mo; Zhang, Weiping

2018-05-01

We theoretically study the effects of loss on the phase sensitivity of an SU(1,1) interferometer with parity detection with various input states. We show that although the sensitivity of phase estimation decreases in the presence of loss, it can still beat the shot-noise limit with small loss. To examine the performance of parity detection, the comparison is performed among homodyne detection, intensity detection, and parity detection. Compared with homodyne detection and intensity detection, parity detection has a slight better optimal phase sensitivity in the absence of loss, but has a worse optimal phase sensitivity with a significant amount of loss with one-coherent state or coherent $\\otimes$ squeezed state input.

Electrophysiological gap detection thresholds: effects of age and comparison with a behavioral measure.

PubMed

Palmer, Shannon B; Musiek, Frank E

2014-01-01

Temporal processing ability has been linked to speech understanding ability and older adults often complain of difficulty understanding speech in difficult listening situations. Temporal processing can be evaluated using gap detection procedures. There is some research showing that gap detection can be evaluated using an electrophysiological procedure. However, there is currently no research establishing gap detection threshold using the N1-P2 response. The purposes of the current study were to 1) determine gap detection thresholds in younger and older normal-hearing adults using an electrophysiological measure, 2) compare the electrophysiological gap detection threshold and behavioral gap detection threshold within each group, and 3) investigate the effect of age on each gap detection measure. This study utilized an older adult group and younger adult group to compare performance on an electrophysiological and behavioral gap detection procedure. The subjects in this study were 11 younger, normal-hearing adults (mean = 22 yrs) and 11 older, normal-hearing adults (mean = 64.36 yrs). All subjects completed an adaptive behavioral gap detection procedure in order to determine their behavioral gap detection threshold (BGDT). Subjects also completed an electrophysiologic gap detection procedure to determine their electrophysiologic gap detection threshold (EGDT). Older adults demonstrated significantly larger gap detection thresholds than the younger adults. However, EGDT and BGDT were not significantly different in either group. The mean difference between EGDT and BGDT for all subjects was 0.43 msec. Older adults show poorer gap detection ability when compared to younger adults. However, this study shows that gap detection thresholds can be measured using evoked potential recordings and yield results similar to a behavioral measure. American Academy of Audiology.

Vision-based method for detecting driver drowsiness and distraction in driver monitoring system

NASA Astrophysics Data System (ADS)

Jo, Jaeik; Lee, Sung Joo; Jung, Ho Gi; Park, Kang Ryoung; Kim, Jaihie

2011-12-01

Most driver-monitoring systems have attempted to detect either driver drowsiness or distraction, although both factors should be considered for accident prevention. Therefore, we propose a new driver-monitoring method considering both factors. We make the following contributions. First, if the driver is looking ahead, drowsiness detection is performed; otherwise, distraction detection is performed. Thus, the computational cost and eye-detection error can be reduced. Second, we propose a new eye-detection algorithm that combines adaptive boosting, adaptive template matching, and blob detection with eye validation, thereby reducing the eye-detection error and processing time significantly, which is hardly achievable using a single method. Third, to enhance eye-detection accuracy, eye validation is applied after initial eye detection, using a support vector machine based on appearance features obtained by principal component analysis (PCA) and linear discriminant analysis (LDA). Fourth, we propose a novel eye state-detection algorithm that combines appearance features obtained using PCA and LDA, with statistical features such as the sparseness and kurtosis of the histogram from the horizontal edge image of the eye. Experimental results showed that the detection accuracies of the eye region and eye states were 99 and 97%, respectively. Both driver drowsiness and distraction were detected with a success rate of 98%.

Noise suppression for the differential detection in nuclear magnetic resonance gyroscope

NASA Astrophysics Data System (ADS)

Yang, Dan; Zhou, Binquan; Chen, LinLin; Jia, YuChen; Lu, QiLin

2017-10-01

The nuclear magnetic resonance gyroscope is based on spin-exchange optical pumping of noble gases to detect and measure the angular velocity of the carrier, but it would be challenging to measure the precession signal of noble gas nuclei directly. To solve the problem, the primary detection method utilizes alkali atoms, the precession of nuclear magnetization modulates the alkali atoms at the Larmor frequency of nuclei, relatively speaking, and it is easier to detect the precession signal of alkali atoms. The precession frequency of alkali atoms is detected by the rotation angle of linearly polarized probe light; and differential detection method is commonly used in NMRG in order to detect the linearly polarized light rotation angle. Thus, the detection accuracy of differential detection system will affect the sensitivity of the NMRG. For the purpose of further improvement of the sensitivity level of the NMRG, this paper focuses on the aspects of signal detection, and aims to do an error analysis as well as an experimental research of the linearly light rotation angle detection. Through the theoretical analysis and the experimental illustration, we found that the extinction ratio σ2 and DC bias are the factors that will produce detective noise in the differential detection method.

A causal relationship between face-patch activity and face-detection behavior.

PubMed

Sadagopan, Srivatsun; Zarco, Wilbert; Freiwald, Winrich A

2017-04-04

The primate brain contains distinct areas densely populated by face-selective neurons. One of these, face-patch ML, contains neurons selective for contrast relationships between face parts. Such contrast-relationships can serve as powerful heuristics for face detection. However, it is unknown whether neurons with such selectivity actually support face-detection behavior. Here, we devised a naturalistic face-detection task and combined it with fMRI-guided pharmacological inactivation of ML to test whether ML is of critical importance for real-world face detection. We found that inactivation of ML impairs face detection. The effect was anatomically specific, as inactivation of areas outside ML did not affect face detection, and it was categorically specific, as inactivation of ML impaired face detection while sparing body and object detection. These results establish that ML function is crucial for detection of faces in natural scenes, performing a critical first step on which other face processing operations can build.

Engineering Software for Interoperability through Use of Enterprise Architecture Techniques

DTIC Science & Technology

2003-03-01

Response Home/ Business Security . To detect flood conditions (i.e. excess water levels) within the monitored area and alert authorities, as necessary...Response; Fire Detection & Response; and Flood Detection & Response. Functional Area Description Intruder Detection & Response Home/ Business ... Security . To monitor and detect unauthorized entry into the secured area and sound alarms/alert authorities, as necessary. Fire Detection

Indirect detection of radiation sources through direct detection of radiolysis products

DOEpatents

Farmer, Joseph C [Tracy, CA; Fischer, Larry E [Los Gatos, CA; Felter, Thomas E [Livermore, CA

2010-04-20

A system for indirectly detecting a radiation source by directly detecting radiolytic products. The radiation source emits radiation and the radiation produces the radiolytic products. A fluid is positioned to receive the radiation from the radiation source. When the fluid is irradiated, radiolytic products are produced. By directly detecting the radiolytic products, the radiation source is detected.

Structural and Functional Evaluations for the Early Detection of Glaucoma.

PubMed

Lucy, Katie A; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection.

Structural and Functional Evaluations for the Early Detection of Glaucoma

PubMed Central

Lucy, Katie A.; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection. PMID:28603546

Spatial and Temporal Monitoring Resolutions for CO2 Leakage Detection at Carbon Storage Sites

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Dilmore, R. M.; Daley, T. M.; Carroll, S.; Mansoor, K.; Gasperikova, E.; Harbert, W.; Wang, Z.; Bromhal, G. S.; Small, M.

2016-12-01

Different leakage monitoring techniques offer different strengths in detection sensitivity, coverage, feedback time, cost, and technology availability, such that they may complement each other when applied together. This research focuses on quantifying the spatial coverage and temporal resolution of detection response for several geophysical remote monitoring and direct groundwater monitoring techniques for an optimal monitoring plan for CO2 leakage detection. Various monitoring techniques with different monitoring depths are selected: 3D time-lapse seismic survey, wellbore pressure, groundwater chemistry and soil gas. The spatial resolution in terms of leakage detectability is quantified through the effective detection distance between two adjacent monitors, given the magnitude of leakage and specified detection probability. The effective detection distances are obtained either from leakage simulations with various monitoring densities or from information garnered from field test data. These spatial leakage detection resolutions are affected by physically feasible monitoring design and detection limits. Similarly, the temporal resolution, in terms of leakage detectability, is quantified through the effective time to positive detection of a given size of leak and a specified detection probability, again obtained either from representative leakage simulations with various monitoring densities or from field test data. The effective time to positive detection is also affected by operational feedback time (associated with sampling, sample analysis and data interpretation), with values obtained mainly through expert interviews and literature review. In additional to the spatial and temporal resolutions of these monitoring techniques, the impact of CO2 plume migration speed and leakage detection sensitivity of each monitoring technique are also discussed with consideration of how much monitoring is necessary for effective leakage detection and how these monitoring techniques can be better combined in a time-space framework. The results of the spatial and temporal leakage detection resolutions for several geophysical monitoring techniques and groundwater monitoring are summarized to inform future monitoring designs at carbon storage sites.

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

PubMed Central

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

2016-01-01

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE. PMID:27447635

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

PubMed

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

2016-07-19

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

Change Detection: Training and Transfer

PubMed Central

Gaspar, John G.; Neider, Mark B.; Simons, Daniel J.; McCarley, Jason S.; Kramer, Arthur F.

2013-01-01

Observers often fail to notice even dramatic changes to their environment, a phenomenon known as change blindness. If training could enhance change detection performance in general, then it might help to remedy some real-world consequences of change blindness (e.g. failing to detect hazards while driving). We examined whether adaptive training on a simple change detection task could improve the ability to detect changes in untrained tasks for young and older adults. Consistent with an effective training procedure, both young and older adults were better able to detect changes to trained objects following training. However, neither group showed differential improvement on untrained change detection tasks when compared to active control groups. Change detection training led to improvements on the trained task but did not generalize to other change detection tasks. PMID:23840775

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

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

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

Immunochemical Detection Methods for Gluten in Food Products: Where Do We Go from Here?

PubMed

Slot, I D Bruins; van der Fels-Klerx, H J; Bremer, M G E G; Hamer, R J

2016-11-17

Accurate and reliable quantification methods for gluten in food are necessary to ensure proper product labeling and thus safeguard the gluten sensitive consumer against exposure. Immunochemical detection is the method of choice, as it is sensitive, rapid and relatively easy to use. Although a wide range of detection kits are commercially available, there are still many difficulties in gluten detection that have not yet been overcome. This review gives an overview of the currently commercially available immunochemical detection methods, and discusses the problems that still exist in gluten detection in food. The largest problems are encountered in the extraction of gluten from food matrices, the choice of epitopes targeted by the detection method, and the use of a standardized reference material. By comparing the available techniques with the unmet needs in gluten detection, the possible benefit of a new multiplex immunoassay is investigated. This detection method would allow for the detection and quantification of multiple harmful gluten peptides at once and would, therefore, be a logical advancement in gluten detection in food.

Face detection and eyeglasses detection for thermal face recognition

NASA Astrophysics Data System (ADS)

Zheng, Yufeng

2012-01-01

Thermal face recognition becomes an active research direction in human identification because it does not rely on illumination condition. Face detection and eyeglasses detection are necessary steps prior to face recognition using thermal images. Infrared light cannot go through glasses and thus glasses will appear as dark areas in a thermal image. One possible solution is to detect eyeglasses and to exclude the eyeglasses areas before face matching. In thermal face detection, a projection profile analysis algorithm is proposed, where region growing and morphology operations are used to segment the body of a subject; then the derivatives of two projections (horizontal and vertical) are calculated and analyzed to locate a minimal rectangle of containing the face area. Of course, the searching region of a pair of eyeglasses is within the detected face area. The eyeglasses detection algorithm should produce either a binary mask if eyeglasses present, or an empty set if no eyeglasses at all. In the proposed eyeglasses detection algorithm, block processing, region growing, and priori knowledge (i.e., low mean and variance within glasses areas, the shapes and locations of eyeglasses) are employed. The results of face detection and eyeglasses detection are quantitatively measured and analyzed using the manually defined ground truths (for both face and eyeglasses). Our experimental results shown that the proposed face detection and eyeglasses detection algorithms performed very well in contrast with the predefined ground truths.

Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.

PubMed

Sabherwal, Pooja; Singh, Latika; Agrawal, Monika

2018-03-30

In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.

Nucleic acid detection system and method for detecting influenza

DOEpatents

Cai, Hong; Song, Jian

2015-03-17

The invention provides a rapid, sensitive and specific nucleic acid detection system which utilizes isothermal nucleic acid amplification in combination with a lateral flow chromatographic device, or DNA dipstick, for DNA-hybridization detection. The system of the invention requires no complex instrumentation or electronic hardware, and provides a low cost nucleic acid detection system suitable for highly sensitive pathogen detection. Hybridization to single-stranded DNA amplification products using the system of the invention provides a sensitive and specific means by which assays can be multiplexed for the detection of multiple target sequences.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

Analysis of the infrared detection system operating range based on polarization degree

NASA Astrophysics Data System (ADS)

Jiang, Kai; Liu, Wen; Liu, Kai; Duan, Jing; Yan, Pei-pei; Shan, Qiu-sha

2018-02-01

Infrared polarization detection technology has unique advantages in the field of target detection and identification because of using the polarization information of radiation. The mechanism of infrared polarization is introduced. Comparing with traditional infrared detection distance model, infrared detection operating range and Signal to Noise Ratio (SNR) model is built according to the polarization degree and noise. The influence of polarization degree on the SNR of infrared system is analyzed. At last, the basic condition of polarization detection SNR better than traditional infrared detection SNR is obtained.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

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

PubMed

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

2014-10-01

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

Object detection in MOUT: evaluation of a hybrid approach for confirmation and rejection of object detection hypotheses

NASA Astrophysics Data System (ADS)

Manger, Daniel; Metzler, Jürgen

2014-03-01

Military Operations in Urban Terrain (MOUT) require the capability to perceive and to analyze the situation around a patrol in order to recognize potential threats. A permanent monitoring of the surrounding area is essential in order to appropriately react to the given situation, where one relevant task is the detection of objects that can pose a threat. Especially the robust detection of persons is important, as in MOUT scenarios threats usually arise from persons. This task can be supported by image processing systems. However, depending on the scenario, person detection in MOUT can be challenging, e.g. persons are often occluded in complex outdoor scenes and the person detection also suffers from low image resolution. Furthermore, there are several requirements on person detection systems for MOUT such as the detection of non-moving persons, as they can be a part of an ambush. Existing detectors therefore have to operate on single images with low thresholds for detection in order to not miss any person. This, in turn, leads to a comparatively high number of false positive detections which renders an automatic vision-based threat detection system ineffective. In this paper, a hybrid detection approach is presented. A combination of a discriminative and a generative model is examined. The objective is to increase the accuracy of existing detectors by integrating a separate hypotheses confirmation and rejection step which is built by a discriminative and generative model. This enables the overall detection system to make use of both the discriminative power and the capability to detect partly hidden objects with the models. The approach is evaluated on benchmark data sets generated from real-world image sequences captured during MOUT exercises. The extension shows a significant improvement of the false positive detection rate.

Robust obstacle detection for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Qin, Yueming; Zhang, Xiuzhi

2018-03-01

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Detecting of foreign object debris on airfield pavement using convolution neural network

NASA Astrophysics Data System (ADS)

Cao, Xiaoguang; Gu, Yufeng; Bai, Xiangzhi

2017-11-01

It is of great practical significance to detect foreign object debris (FOD) timely and accurately on the airfield pavement, because the FOD is a fatal threaten for runway safety in airport. In this paper, a new FOD detection framework based on Single Shot MultiBox Detector (SSD) is proposed. Two strategies include making the detection network lighter and using dilated convolution, which are proposed to better solve the FOD detection problem. The advantages mainly include: (i) the network structure becomes lighter to speed up detection task and enhance detection accuracy; (ii) dilated convolution is applied in network structure to handle smaller FOD. Thus, we get a faster and more accurate detection system.

Development of a HIV-1 Virus Detection System Based on Nanotechnology.

PubMed

Lee, Jin-Ho; Oh, Byung-Keun; Choi, Jeong-Woo

2015-04-27

Development of a sensitive and selective detection system for pathogenic viral agents is essential for medical healthcare from diagnostics to therapeutics. However, conventional detection systems are time consuming, resource-intensive and tedious to perform. Hence, the demand for sensitive and selective detection system for virus are highly increasing. To attain this aim, different aspects and techniques have been applied to develop virus sensor with improved sensitivity and selectivity. Here, among those aspects and techniques, this article reviews HIV virus particle detection systems incorporated with nanotechnology to enhance the sensitivity. This review mainly focused on four different detection system including vertically configured electrical detection based on scanning tunneling microscopy (STM), electrochemical detection based on direct electron transfer in virus, optical detection system based on localized surface plasmon resonance (LSPR) and surface enhanced Raman spectroscopy (SERS) using plasmonic nanoparticle.

Laser-based standoff detection of explosives: a critical review.

PubMed

Wallin, Sara; Pettersson, Anna; Ostmark, Henric; Hobro, Alison

2009-09-01

A review of standoff detection technologies for explosives has been made. The review is focused on trace detection methods (methods aiming to detect traces from handling explosives or the vapours surrounding an explosive charge due to the vapour pressure of the explosive) rather than bulk detection methods (methods aiming to detect the bulk explosive charge). The requirements for standoff detection technologies are discussed. The technologies discussed are mostly laser-based trace detection technologies, such as laser-induced-breakdown spectroscopy, Raman spectroscopy, laser-induced-fluorescence spectroscopy and IR spectroscopy but the bulk detection technologies millimetre wave imaging and terahertz spectroscopy are also discussed as a complement to the laser-based methods. The review includes novel techniques, not yet tested in realistic environments, more mature technologies which have been tested outdoors in realistic environments as well as the most mature millimetre wave imaging technique.

Vision-based vehicle detection and tracking algorithm design

NASA Astrophysics Data System (ADS)

Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

2009-12-01

The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

Conditional anomaly detection methods for patient–management alert systems

PubMed Central

Valko, Michal; Cooper, Gregory; Seybert, Amy; Visweswaran, Shyam; Saul, Melissa; Hauskrecht, Milos

2010-01-01

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses on instance–based methods for detecting conditional anomalies. The methods rely on the distance metric to identify examples in the dataset that are most critical for detecting the anomaly. We investigate various metrics and metric learning methods to optimize the performance of the instance–based anomaly detection methods. We show the benefits of the instance–based methods on two real–world detection problems: detection of unusual admission decisions for patients with the community–acquired pneumonia and detection of unusual orders of an HPF4 test that is used to confirm Heparin induced thrombocytopenia — a life–threatening condition caused by the Heparin therapy. PMID:25392850

Fusion of local and global detection systems to detect tuberculosis in chest radiographs.

PubMed

Hogeweg, Laurens; Mol, Christian; de Jong, Pim A; Dawson, Rodney; Ayles, Helen; van Ginneken, Bramin

2010-01-01

Automatic detection of tuberculosis (TB) on chest radiographs is a difficult problem because of the diverse presentation of the disease. A combination of detection systems for abnormalities and normal anatomy is used to improve detection performance. A textural abnormality detection system operating at the pixel level is combined with a clavicle detection system to suppress false positive responses. The output of a shape abnormality detection system operating at the image level is combined in a next step to further improve performance by reducing false negatives. Strategies for combining systems based on serial and parallel configurations were evaluated using the minimum, maximum, product, and mean probability combination rules. The performance of TB detection increased, as measured using the area under the ROC curve, from 0.67 for the textural abnormality detection system alone to 0.86 when the three systems were combined. The best result was achieved using the sum and product rule in a parallel combination of outputs.

Deep UV laser-induced fluorescence detection of unlabeled drugs and proteins in microchip electrophoresis.

PubMed

Schulze, Philipp; Ludwig, Martin; Kohler, Frank; Belder, Detlev

2005-03-01

Deep UV fluorescence detection at 266-nm excitation wavelength has been realized for sensitive detection in microchip electrophoresis. For this purpose, an epifluorescence setup was developed enabling the coupling of a deep UV laser into a commercial fluorescence microscope. Deep UV laser excitation utilizing a frequency quadrupled pulsed laser operating at 266 nm shows an impressive performance for native fluorescence detection of various compounds in fused-silica microfluidic devices. Aromatic low molecular weight compounds such as serotonin, propranolol, a diol, and tryptophan could be detected at low-micromolar concentrations. Deep UV fluorescence detection was also successfully employed for the detection of unlabeled basic proteins. For this purpose, fused-silica chips dynamically coated with hydroxypropylmethyl cellulose were employed to suppress analyte adsorption. Utilizing fused-silica chips permanently coated with poly(vinyl alcohol), it was also possible to separate and detect egg white chicken proteins. These data show that deep UV fluorescence detection significantly widens the application range of fluorescence detection in chip-based analysis techniques.

Multiview road sign detection via self-adaptive color model and shape context matching

NASA Astrophysics Data System (ADS)

Liu, Chunsheng; Chang, Faliang; Liu, Chengyun

2016-09-01

The multiview appearance of road signs in uncontrolled environments has made the detection of road signs a challenging problem in computer vision. We propose a road sign detection method to detect multiview road signs. This method is based on several algorithms, including the classical cascaded detector, the self-adaptive weighted Gaussian color model (SW-Gaussian model), and a shape context matching method. The classical cascaded detector is used to detect the frontal road signs in video sequences and obtain the parameters for the SW-Gaussian model. The proposed SW-Gaussian model combines the two-dimensional Gaussian model and the normalized red channel together, which can largely enhance the contrast between the red signs and background. The proposed shape context matching method can match shapes with big noise, which is utilized to detect road signs in different directions. The experimental results show that compared with previous detection methods, the proposed multiview detection method can reach higher detection rate in detecting signs with different directions.

A Survey on Anomaly Based Host Intrusion Detection System

NASA Astrophysics Data System (ADS)

Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

2018-04-01

An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

Research on vehicle detection based on background feature analysis in SAR images

NASA Astrophysics Data System (ADS)

Zhang, Bochuan; Tang, Bo; Zhang, Cong; Hu, Ruiguang; Yun, Hongquan; Xiao, Liping

2017-10-01

Aiming at vehicle detection on the ground through low resolution SAR images, a method is proposed for determining the region of the vehicles first and then detecting the target in the specific region. The experimental results show that this method not only reduces the target detection area, but also reduces the influence of terrain clutter on the detection, which greatly improves the reliability of the target detection.

A Novel Zero Velocity Interval Detection Algorithm for Self-Contained Pedestrian Navigation System with Inertial Sensors

PubMed Central

Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan

2016-01-01

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266

Impaired face detection may explain some but not all cases of developmental prosopagnosia.

PubMed

Dalrymple, Kirsten A; Duchaine, Brad

2016-05-01

Developmental prosopagnosia (DP) is defined by severe face recognition difficulties due to the failure to develop the visual mechanisms for processing faces. The two-process theory of face recognition (Morton & Johnson, 1991) implies that DP could result from a failure of an innate face detection system; this failure could prevent an individual from then tuning higher-level processes for face recognition (Johnson, 2005). Work with adults indicates that some individuals with DP have normal face detection whereas others are impaired. However, face detection has not been addressed in children with DP, even though their results may be especially informative because they have had less opportunity to develop strategies that could mask detection deficits. We tested the face detection abilities of seven children with DP. Four were impaired at face detection to some degree (i.e. abnormally slow, or failed to find faces) while the remaining three children had normal face detection. Hence, the cases with impaired detection are consistent with the two-process account suggesting that DP could result from a failure of face detection. However, the cases with normal detection implicate a higher-level origin. The dissociation between normal face detection and impaired identity perception also indicates that these abilities depend on different neurocognitive processes. © 2015 John Wiley & Sons Ltd.

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2000-01-01

We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.

Object memory and change detection: dissociation as a function of visual and conceptual similarity.

PubMed

Yeh, Yei-Yu; Yang, Cheng-Ta

2008-01-01

People often fail to detect a change between two visual scenes, a phenomenon referred to as change blindness. This study investigates how a post-change object's similarity to the pre-change object influences memory of the pre-change object and affects change detection. The results of Experiment 1 showed that similarity lowered detection sensitivity but did not affect the speed of identifying the pre-change object, suggesting that similarity between the pre- and post-change objects does not degrade the pre-change representation. Identification speed for the pre-change object was faster than naming the new object regardless of detection accuracy. Similarity also decreased detection sensitivity in Experiment 2 but improved the recognition of the pre-change object under both correct detection and detection failure. The similarity effect on recognition was greatly reduced when 20% of each pre-change stimulus was masked by random dots in Experiment 3. Together the results suggest that the level of pre-change representation under detection failure is equivalent to the level under correct detection and that the pre-change representation is almost complete. Similarity lowers detection sensitivity but improves explicit access in recognition. Dissociation arises between recognition and change detection as the two judgments rely on the match-to-mismatch signal and mismatch-to-match signal, respectively.

Respiratory Viral Detections During Symptomatic and Asymptomatic Periods in Young Andean Children

PubMed Central

Howard, Leigh M.; Johnson, Monika; Williams, John V.; Zhu, Yuwei; Gil, Ana I.; Edwards, Kathryn M.; Griffin, Marie R.; Lanata, Claudio F.; Grijalva, Carlos G.

2015-01-01

Background Viruses are commonly detected in children with acute respiratory illnesses (ARI) and in asymptomatic children. Longitudinal studies of viral detections during asymptomatic periods surrounding ARI could facilitate interpretation of viral detections but are currently scant. Methods We used reverse transcription-polymerase chain reaction (RT-PCR) to analyze respiratory samples from young Andean children for viruses during asymptomatic periods within 8-120 days of index ARI (cough or fever). We compared viral detections over time within children and explored RT-PCR cycle thresholds (CT) as surrogates for viral loads. Results At least one respiratory virus was detected in 367 (43%) of 859 samples collected during asymptomatic periods, with more frequent detections in periods with rhinorrhea (49%) than those without (34%, p<0.001). Relative to index ARI with human rhinovirus (HRV), adenovirus (AdV), respiratory syncytial virus (RSV), and parainfluenza virus (PIV) detected, the same virus was also detected during 32%, 22%, 10%, and 3% of asymptomatic periods, respectively. RSV was only detected 8-30 days after index RSV ARI, whereas HRV and AdV were detected throughout asymptomatic periods. Human metapneumovirus (MPV) and influenza were rarely detected during asymptomatic periods (<3%). No significant differences were observed in the CT for HRV or AdV during asymptomatic periods relative to ARI. For RSV, CT were significantly lower during ARI relative to the asymptomatic period (p=0.03). Conclusions These findings indicate that influenza, MPV, PIV, and RSV detections in children with ARI usually indicate a causal relationship. When HRV or AdV is detected during ARI, the causal relationship is less certain. PMID:26121205

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

PubMed

Geertsema, Evelien E; Thijs, Roland D; Gutter, Therese; Vledder, Ben; Arends, Johan B; Leijten, Frans S; Visser, Gerhard H; Kalitzin, Stiliyan N

2018-06-01

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting. The algorithm calculates power in the 2-6 Hz range relative to 0.5-12.5 Hz range in group velocity signals derived from video-sequence optical flow. A detection threshold was found using a training set consisting of video-electroencephalogaphy (EEG) recordings of 72 CS. A test set consisting of 24 full nights of 12 new subjects in residential care and additional recordings of 50 CS selected randomly was used to estimate performance. All data were analyzed retrospectively. The start and end of CS (generalized clonic and tonic-clonic seizures) and other seizures considered desirable to detect (long generalized tonic, hyperkinetic, and other major seizures) were annotated. The detection threshold was set to the value that obtained 97% sensitivity in the training set. Sensitivity, latency, and false detection rate (FDR) per night were calculated in the test set. A seizure was detected when the algorithm output exceeded the threshold continuously for 2 seconds. With the detection threshold determined in the training set, all CS were detected in the test set (100% sensitivity). Latency was ≤10 seconds in 78% of detections. Three/five hyperkinetic and 6/9 other major seizures were detected. Median FDR was 0.78 per night and no false detections occurred in 9/24 nights. Our algorithm could improve safety unobtrusively by automated real-time detection of CS in video registrations, with an acceptable latency and FDR. The algorithm can also detect some other motor seizures requiring assistance. © 2018 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

Incipient failure detection of space shuttle main engine turbopump bearings using vibration envelope detection

NASA Technical Reports Server (NTRS)

Hopson, Charles B.

1987-01-01

The results of an analysis performed on seven successive Space Shuttle Main Engine (SSME) static test firings, utilizing envelope detection of external accelerometer data are discussed. The results clearly show the great potential for using envelope detection techniques in SSME incipient failure detection.

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 7 2013-10-01 2013-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 7 2012-10-01 2012-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 7 2011-10-01 2011-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 7 2014-10-01 2014-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Fire detecting, manual alarm, and supervised patrol... AND MISCELLANEOUS VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 95.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Fire detecting, manual alarm, and supervised patrol... AND MISCELLANEOUS VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 95.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 7 2010-10-01 2010-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Fire detecting, manual alarm, and supervised patrol... AND MISCELLANEOUS VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 95.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

Detectable Warnings : Detectability by Individuals with Visual Impairments, and Safety and Negotiability on Slopes for Persons with Physical Impairment

DOT National Transportation Integrated Search

1994-09-01

This report presents the results of research on human performance on detectable warning surfaces. The first portion of the report presents an evaluation of the underfoot detectability of nine detectable warning surfaces for persons having varied phys...

46 CFR 111.05-21 - Ground detection.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Ground detection. 111.05-21 Section 111.05-21 Shipping... REQUIREMENTS Equipment Ground, Ground Detection, and Grounded Systems § 111.05-21 Ground detection. There must be ground detection for each: (a) Electric propulsion system; (b) Ship's service power system; (c...

46 CFR 111.05-21 - Ground detection.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Ground detection. 111.05-21 Section 111.05-21 Shipping... REQUIREMENTS Equipment Ground, Ground Detection, and Grounded Systems § 111.05-21 Ground detection. There must be ground detection for each: (a) Electric propulsion system; (b) Ship's service power system; (c...

Noise canceling in-situ detection

DOEpatents

Walsh, David O.

2014-08-26

Technologies applicable to noise canceling in-situ NMR detection and imaging are disclosed. An example noise canceling in-situ NMR detection apparatus may comprise one or more of a static magnetic field generator, an alternating magnetic field generator, an in-situ NMR detection device, an auxiliary noise detection device, and a computer.

Detection of Neutrons with Scintillation Counters

DOE R&D Accomplishments Database

Hofstadter, R.

1948-11-01

Detection of slow neutrons by: detection of single gamma rays following capture by cadmium or mercury; detection of more than one gamma ray by observing coincidences after capture; detection of heavy charged particles after capture in lithium or baron nuclei; possible use of anthracene for counting fast neutrons investigated briefly.

Detection and Prevention of Android Malware Attempting to Root the Device

DTIC Science & Technology

2014-03-01

detect the operation of malware trying to root the phone. This research aims to detect the Exploid, RageAgainstTheCage, and Gingerbreak exploits on...attackers can use malware to root the system. By placing sensors inside the critical paths, the research detected all 379 malware samples trying the root...zero false positive results. Unlike static signature detection at the application level, this research provides dynamic detection at the kernel level

Methods for the selective detection of alkyne-presenting molecules and related compositions and systems

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

Valdez, Carlos A.; Vu, Alexander K.

Provided herein are methods for selectively detecting an alkyne-presenting molecule in a sample and related detection reagents, compositions, methods and systems. The methods include contacting a detection reagent with the sample for a time and under a condition to allow binding of the detection reagent to the one or more alkyne-presenting molecules possibly present in the matrix to the detection reagent. The detection reagent includes an organic label moiety presenting an azide group. The binding of the azide group to the alkyne-presenting molecules results in emission of a signal from the organic label moiety.

Revolution in nuclear detection affairs

NASA Astrophysics Data System (ADS)

Stern, Warren M.

2014-05-01

The detection of nuclear or radioactive materials for homeland or national security purposes is inherently difficult. This is one reason detection efforts must be seen as just one part of an overall nuclear defense strategy which includes, inter alia, material security, detection, interdiction, consequence management and recovery. Nevertheless, one could argue that there has been a revolution in detection affairs in the past several decades as the innovative application of new technology has changed the character and conduct of detection operations. This revolution will likely be most effectively reinforced in the coming decades with the networking of detectors and innovative application of anomaly detection algorithms.

Ergonomics for enhancing detection of machine abnormalities.

PubMed

Illankoon, Prasanna; Abeysekera, John; Singh, Sarbjeet

2016-10-17

Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined. This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections. Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics. As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

Communication: atomic force detection of single-molecule nonlinear optical vibrational spectroscopy.

PubMed

Saurabh, Prasoon; Mukamel, Shaul

2014-04-28

Atomic Force Microscopy (AFM) allows for a highly sensitive detection of spectroscopic signals. This has been first demonstrated for NMR of a single molecule and recently extended to stimulated Raman in the optical regime. We theoretically investigate the use of optical forces to detect time and frequency domain nonlinear optical signals. We show that, with proper phase matching, the AFM-detected signals closely resemble coherent heterodyne-detected signals. Applications are made to AFM-detected and heterodyne-detected vibrational resonances in Coherent Anti-Stokes Raman Spectroscopy (χ((3))) and sum or difference frequency generation (χ((2))).

Methods of DNA methylation detection

NASA Technical Reports Server (NTRS)

Maki, Wusi Chen (Inventor); Filanoski, Brian John (Inventor); Mishra, Nirankar (Inventor); Rastogi, Shiva (Inventor)

2010-01-01

The present invention provides for methods of DNA methylation detection. The present invention provides for methods of generating and detecting specific electronic signals that report the methylation status of targeted DNA molecules in biological samples.Two methods are described, direct and indirect detection of methylated DNA molecules in a nano transistor based device. In the direct detection, methylated target DNA molecules are captured on the sensing surface resulting in changes in the electrical properties of a nano transistor. These changes generate detectable electronic signals. In the indirect detection, antibody-DNA conjugates are used to identify methylated DNA molecules. RNA signal molecules are generated through an in vitro transcription process. These RNA molecules are captured on the sensing surface change the electrical properties of nano transistor thereby generating detectable electronic signals.

Evaluation of harmonic direction-finding systems for detecting locomotor activity

USGS Publications Warehouse

Boyarski, V.L.; Rodda, G.H.; Savidge, J.A.

2007-01-01

We conducted a physical simulation experiment to test the efficacy of harmonic direction finding for remotely detecting locomotor activity in animals. The ability to remotely detect movement helps to avoid disturbing natural movement behavior. Remote detection implies that the observer can sense only a change in signal bearing. In our simulated movements, small changes in bearing (<5.7??) were routinely undetectable. Detectability improved progressively with the size of the simulated animal movement. The average (??SD) of reflector tag movements correctly detected for 5 observers was 93.9 ?? 12.8% when the tag was moved ???11.5??; most observers correctly detected tag movements ???20.1??. Given our data, one can assess whether the technique will be effective for detecting movements at an observation distance appropriate for the study organism. We recommend that both habitat and behavior of the organism be taken into consideration when contemplating use of this technique for detecting locomotion.

Planetary Gearbox Fault Detection Using Vibration Separation Techniques

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Rapid and sensitive microRNA detection with laminar flow-assisted dendritic amplification on power-free microfluidic chip.

PubMed

Arata, Hideyuki; Komatsu, Hiroshi; Hosokawa, Kazuo; Maeda, Mizuo

2012-01-01

Detection of microRNAs, small noncoding single-stranded RNAs, is one of the key topics in the new generation of cancer research because cancer in the human body can be detected or even classified by microRNA detection. This report shows rapid and sensitive microRNA detection using a power-free microfluidic device, which is driven by degassed poly(dimethylsiloxane), thus eliminating the need for an external power supply. MicroRNA is detected by sandwich hybridization, and the signal is amplified by laminar flow-assisted dendritic amplification. This method allows us to detect microRNA of specific sequences at a limit of detection of 0.5 pM from a 0.5 µL sample solution with a detection time of 20 min. Together with the advantages of self-reliance of this device, this method might contribute substantially to future point-of-care early-stage cancer diagnosis.

Microcontroller based driver alertness detection systems to detect drowsiness

NASA Astrophysics Data System (ADS)

Adenin, Hasibah; Zahari, Rahimi; Lim, Tiong Hoo

2018-04-01

The advancement of embedded system for detecting and preventing drowsiness in a vehicle is a major challenge for road traffic accident systems. To prevent drowsiness while driving, it is necessary to have an alert system that can detect a decline in driver concentration and send a signal to the driver. Studies have shown that traffc accidents usually occur when the driver is distracted while driving. In this paper, we have reviewed a number of detection systems to monitor the concentration of a car driver and propose a portable Driver Alertness Detection System (DADS) to determine the level of concentration of the driver based on pixelated coloration detection technique using facial recognition. A portable camera will be placed at the front visor to capture facial expression and the eye activities. We evaluate DADS using 26 participants and have achieved 100% detection rate with good lighting condition and a low detection rate at night.

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.

Data acquisition system

DOEpatents

Shapiro, Stephen L.; Mani, Sudhindra; Atlas, Eugene L.; Cords, Dieter H. W.; Holbrook, Britt

1997-01-01

A data acquisition circuit for a particle detection system that allows for time tagging of particles detected by the system. The particle detection system screens out background noise and discriminate between hits from scattered and unscattered particles. The detection system can also be adapted to detect a wide variety of particle types. The detection system utilizes a particle detection pixel array, each pixel containing a back-biased PIN diode, and a data acquisition pixel array. Each pixel in the particle detection pixel array is in electrical contact with a pixel in the data acquisition pixel array. In response to a particle hit, the affected PIN diodes generate a current, which is detected by the corresponding data acquisition pixels. This current is integrated to produce a voltage across a capacitor, the voltage being related to the amount of energy deposited in the pixel by the particle. The current is also used to trigger a read of the pixel hit by the particle.

Detection principles of biological and chemical FET sensors.

PubMed

Kaisti, Matti

2017-12-15

The seminal importance of detecting ions and molecules for point-of-care tests has driven the search for more sensitive, specific, and robust sensors. Electronic detection holds promise for future miniaturized in-situ applications and can be integrated into existing electronic manufacturing processes and technology. The resulting small devices will be inherently well suited for multiplexed and parallel detection. In this review, different field-effect transistor (FET) structures and detection principles are discussed, including label-free and indirect detection mechanisms. The fundamental detection principle governing every potentiometric sensor is introduced, and different state-of-the-art FET sensor structures are reviewed. This is followed by an analysis of electrolyte interfaces and their influence on sensor operation. Finally, the fundamentals of different detection mechanisms are reviewed and some detection schemes are discussed. In the conclusion, current commercial efforts are briefly considered. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Effects of Phasor Measurement Uncertainty on Power Line Outage Detection

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

Chen, Chen; Wang, Jianhui; Zhu, Hao

2014-12-01

Phasor measurement unit (PMU) technology provides an effective tool to enhance the wide-area monitoring systems (WAMSs) in power grids. Although extensive studies have been conducted to develop several PMU applications in power systems (e.g., state estimation, oscillation detection and control, voltage stability analysis, and line outage detection), the uncertainty aspects of PMUs have not been adequately investigated. This paper focuses on quantifying the impact of PMU uncertainty on power line outage detection and identification, in which a limited number of PMUs installed at a subset of buses are utilized to detect and identify the line outage events. Specifically, the linemore » outage detection problem is formulated as a multi-hypothesis test, and a general Bayesian criterion is used for the detection procedure, in which the PMU uncertainty is analytically characterized. We further apply the minimum detection error criterion for the multi-hypothesis test and derive the expected detection error probability in terms of PMU uncertainty. The framework proposed provides fundamental guidance for quantifying the effects of PMU uncertainty on power line outage detection. Case studies are provided to validate our analysis and show how PMU uncertainty influences power line outage detection.« less

Pesticides detected in urban streams in King County, Washington, 1998-2003

USGS Publications Warehouse

Frans, Lonna M.

2004-01-01

The U.S. Geological Survey and the King County Department of Natural Resources collected water samples from 14 sites on urban streams in King County during storms and during base flow between 1998 and 2003. The samples were analyzed for the presence of 155 pesticides and pesticide transformation products. Thirty-nine of the compounds were detected at least once during the study: 20 herbicides, 9 insecticides, 2 fungicides, 6 pesticide transformation products, and 2 other types of compounds. The most widespread compound was 4-nitrophenol, which was detected at all 14 sampling sites. The most frequently detected compound was pentachlorophenol, a fungicide, which occurred in more than 80 percent of the samples. The most frequently detected herbicides were prometon, trichlopyr, 2,4-D, and MCPP, and the most frequently detected insecticides were diazinon and carbaryl. All of the most frequently detected herbicides and insecticides were sold for homeowner use over the timeframe of this study. More compounds were detected during storms than during base flow, and were detected more frequently and typically at high concentrations during storms. Seven compounds were detected only during storms. Most of the compounds that were detected during storms occurred more frequently during spring storms than during autumn storms.

Accuracy of ultrasound versus computed tomography urogram in detecting urinary tract calculi.

PubMed

Salinawati, B; Hing, E Y; Fam, X I; Zulfiqar, M A

2015-08-01

To determine the (i) sensitivity and specificity of ultrasound (USG) in the detection of urinary tract calculi, (ii) size of renal calculi detected on USG, and (iii) size of renal calculi not seen on USG but detected on computed tomography urogram (CTU). A total of 201 patients' USG and CTU were compared retrospectively for the presence of calculi. Sensitivity, specificity, accuracy, positive predictive value and negative predictive value of USG were calculated with CTU as the gold standard. From the 201 sets of data collected, 59 calculi were detected on both USG and CTU. The sensitivity and specificity of renal calculi detection on USG were 53% and 85% respectively. The mean size of the renal calculus detected on USG was 7.6 mm ± 4.1 mm and the mean size of the renal calculus not visualised on USG but detected on CTU was 4 mm ± 2.4 mm. The sensitivity and specificity of ureteric calculi detection on USG were 12% and 97% respectively. The sensitivity and specificity of urinary bladder calculi detection on USG were 20% and 100% respectively. This study showed that the accuracy of US in detecting renal, ureteric and urinary bladder calculi were 67%, 80% and 98% respectively.

Robust Spacecraft Component Detection in Point Clouds.

PubMed

Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng

2018-03-21

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

Improving detection of low SNR targets using moment-based detection

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Robust Spacecraft Component Detection in Point Clouds

PubMed Central

Wei, Quanmao; Jiang, Zhiguo

2018-01-01

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density. PMID:29561828

Object Detection in Natural Backgrounds Predicted by Discrimination Performance and Models

NASA Technical Reports Server (NTRS)

Ahumada, A. J., Jr.; Watson, A. B.; Rohaly, A. M.; Null, Cynthia H. (Technical Monitor)

1995-01-01

In object detection, an observer looks for an object class member in a set of backgrounds. In discrimination, an observer tries to distinguish two images. Discrimination models predict the probability that an observer detects a difference between two images. We compare object detection and image discrimination with the same stimuli by: (1) making stimulus pairs of the same background with and without the target object and (2) either giving many consecutive trials with the same background (discrimination) or intermixing the stimuli (object detection). Six images of a vehicle in a natural setting were altered to remove the vehicle and mixed with the original image in various proportions. Detection observers rated the images for vehicle presence. Discrimination observers rated the images for any difference from the background image. Estimated detectabilities of the vehicles were found by maximizing the likelihood of a Thurstone category scaling model. The pattern of estimated detectabilities is similar for discrimination and object detection, and is accurately predicted by a Cortex Transform discrimination model. Predictions of a Contrast- Sensitivity- Function filter model and a Root-Mean-Square difference metric based on the digital image values are less accurate. The discrimination detectabilities averaged about twice those of object detection.

Comparison of soft-input-soft-output detection methods for dual-polarized quadrature duobinary system

NASA Astrophysics Data System (ADS)

Chang, Chun; Huang, Benxiong; Xu, Zhengguang; Li, Bin; Zhao, Nan

2018-02-01

Three soft-input-soft-output (SISO) detection methods for dual-polarized quadrature duobinary (DP-QDB), including maximum-logarithmic-maximum-a-posteriori-probability-algorithm (Max-log-MAP)-based detection, soft-output-Viterbi-algorithm (SOVA)-based detection, and a proposed SISO detection, which can all be combined with SISO decoding, are presented. The three detection methods are investigated at 128 Gb/s in five-channel wavelength-division-multiplexing uncoded and low-density-parity-check (LDPC) coded DP-QDB systems by simulations. Max-log-MAP-based detection needs the returning-to-initial-states (RTIS) process despite having the best performance. When the LDPC code with a code rate of 0.83 is used, the detecting-and-decoding scheme with the SISO detection does not need RTIS and has better bit error rate (BER) performance than the scheme with SOVA-based detection. The former can reduce the optical signal-to-noise ratio (OSNR) requirement (at BER=10-5) by 2.56 dB relative to the latter. The application of the SISO iterative detection in LDPC-coded DP-QDB systems makes a good trade-off between requirements on transmission efficiency, OSNR requirement, and transmission distance, compared with the other two SISO methods.

Visual detection of glial cell line-derived neurotrophic factor based on a molecular translator and isothermal strand-displacement polymerization reaction.

PubMed

Zhang, Li-Yong; Xing, Tao; Du, Li-Xin; Li, Qing-Min; Liu, Wei-Dong; Wang, Ji-Yue; Cai, Jing

2015-01-01

Glial cell line-derived neurotrophic factor (GDNF) is a small protein that potently promotes the survival of many types of neurons. Detection of GDNF is vital to monitoring the survival of sympathetic and sensory neurons. However, the specific method for GDNF detection is also un-discovered. The purpose of this study is to explore the method for protein detection of GDNF. A novel visual detection method based on a molecular translator and isothermal strand-displacement polymerization reaction (ISDPR) has been proposed for the detection of GDNF. In this study, a molecular translator was employed to convert the input protein to output deoxyribonucleic acid signal, which was further amplified by ISDPR. The product of ISDPR was detected by a lateral flow biosensor within 30 minutes. This novel visual detection method based on a molecular translator and ISDPR has very high sensitivity and selectivity, with a dynamic response ranging from 1 pg/mL to 10 ng/mL, and the detection limit was 1 pg/mL of GDNF. This novel visual detection method exhibits high sensitivity and selectivity, which is very simple and universal for GDNF detection to help disease therapy in clinical practice.

Fast obstacle detection based on multi-sensor information fusion

NASA Astrophysics Data System (ADS)

Lu, Linli; Ying, Jie

2014-11-01

Obstacle detection is one of the key problems in areas such as driving assistance and mobile robot navigation, which cannot meet the actual demand by using a single sensor. A method is proposed to realize the real-time access to the information of the obstacle in front of the robot and calculating the real size of the obstacle area according to the mechanism of the triangle similarity in process of imaging by fusing datum from a camera and an ultrasonic sensor, which supports the local path planning decision. In the part of image analyzing, the obstacle detection region is limited according to complementary principle. We chose ultrasonic detection range as the region for obstacle detection when the obstacle is relatively near the robot, and the travelling road area in front of the robot is the region for a relatively-long-distance detection. The obstacle detection algorithm is adapted from a powerful background subtraction algorithm ViBe: Visual Background Extractor. We extracted an obstacle free region in front of the robot in the initial frame, this region provided a reference sample set of gray scale value for obstacle detection. Experiments of detecting different obstacles at different distances respectively, give the accuracy of the obstacle detection and the error percentage between the calculated size and the actual size of the detected obstacle. Experimental results show that the detection scheme can effectively detect obstacles in front of the robot and provide size of the obstacle with relatively high dimensional accuracy.

Studying Irony Detection Beyond Ironic Criticism: Let's Include Ironic Praise

PubMed Central

Bruntsch, Richard; Ruch, Willibald

2017-01-01

Studies of irony detection have commonly used ironic criticisms (i.e., mock positive evaluation of negative circumstances) as stimulus materials. Another basic type of verbal irony, ironic praise (i.e., mock negative evaluation of positive circumstances) is largely absent from studies on individuals' aptitude to detect verbal irony. However, it can be argued that ironic praise needs to be considered in order to investigate the detection of irony in the variety of its facets. To explore whether the detection ironic praise has a benefit beyond ironic criticism, three studies were conducted. In Study 1, an instrument (Test of Verbal Irony Detection Aptitude; TOVIDA) was constructed and its factorial structure was tested using N = 311 subjects. The TOVIDA contains 26 scenario-based items and contains two scales for the detection of ironic criticism vs. ironic praise. To validate the measurement method, the two scales of the TOVIDA were experimentally evaluated with N = 154 subjects in Study 2. In Study 3, N = 183 subjects were tested to explore personality and ability correlates of the two TOVIDA scales. Results indicate that the co-variance between the ironic TOVIDA items was organized by two inter-correlated but distinct factors: one representing ironic praise detection aptitude and one representing ironic criticism detection aptitude. Experimental validation showed that the TOVIDA items truly contain irony and that item scores reflect irony detection. Trait bad mood and benevolent humor (as a facet of the sense of humor) were found as joint correlates for both ironic criticism and ironic praise detection scores. In contrast, intelligence, trait cheerfulness, and corrective humor were found as unique correlates of ironic praise detection scores, even when statistically controlling for the aptitude to detect ironic criticism. Our results indicate that the aptitude to detect ironic praise can be seen as distinct from the aptitude to detect ironic criticism. Generating unique variance in irony detection, ironic praise can be postulated as worthwhile to include in future studies—especially when studying the role of mental ability, personality, and humor in irony detection. PMID:28484409

Modelling detection probabilities to evaluate management and control tools for an invasive species

USGS Publications Warehouse

Christy, M.T.; Yackel Adams, A.A.; Rodda, G.H.; Savidge, J.A.; Tyrrell, C.L.

2010-01-01

For most ecologists, detection probability (p) is a nuisance variable that must be modelled to estimate the state variable of interest (i.e. survival, abundance, or occupancy). However, in the realm of invasive species control, the rate of detection and removal is the rate-limiting step for management of this pervasive environmental problem. For strategic planning of an eradication (removal of every individual), one must identify the least likely individual to be removed, and determine the probability of removing it. To evaluate visual searching as a control tool for populations of the invasive brown treesnake Boiga irregularis, we designed a mark-recapture study to evaluate detection probability as a function of time, gender, size, body condition, recent detection history, residency status, searcher team and environmental covariates. We evaluated these factors using 654 captures resulting from visual detections of 117 snakes residing in a 5-ha semi-forested enclosure on Guam, fenced to prevent immigration and emigration of snakes but not their prey. Visual detection probability was low overall (= 0??07 per occasion) but reached 0??18 under optimal circumstances. Our results supported sex-specific differences in detectability that were a quadratic function of size, with both small and large females having lower detection probabilities than males of those sizes. There was strong evidence for individual periodic changes in detectability of a few days duration, roughly doubling detection probability (comparing peak to non-elevated detections). Snakes in poor body condition had estimated mean detection probabilities greater than snakes with high body condition. Search teams with high average detection rates exhibited detection probabilities about twice that of search teams with low average detection rates. Surveys conducted with bright moonlight and strong wind gusts exhibited moderately decreased probabilities of detecting snakes. Synthesis and applications. By emphasizing and modelling detection probabilities, we now know: (i) that eradication of this species by searching is possible, (ii) how much searching effort would be required, (iii) under what environmental conditions searching would be most efficient, and (iv) several factors that are likely to modulate this quantification when searching is applied to new areas. The same approach can be use for evaluation of any control technology or population monitoring programme. ?? 2009 The Authors. Journal compilation ?? 2009 British Ecological Society.

Locally adaptive decision in detection of clustered microcalcifications in mammograms.

PubMed

Sainz de Cea, María V; Nishikawa, Robert M; Yang, Yongyi

2018-02-15

In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value  <10 -4 ). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.

Evaluation of Traditional and Contemporary Methods for Detecting Syphacia obvelata and Aspiculuris tetraptera in Laboratory Mice

PubMed Central

Gerwin, Philip M; Arbona, Rodolfo J Ricart; Riedel, Elyn R; Lepherd, Michelle L; Henderson, Ken S; Lipman, Neil S

2017-01-01

There is no consensus regarding the best practice for detecting murine pinworm infections. Initially, we evaluated 7 fecal concentration methods by using feces containing Aspiculuris tetraptera (AT) eggs (n = 20 samples per method). Sodium nitrate flotation, sodium nitrate centrifugation, Sheather sugar centrifugation, and zinc sulfate centrifugation detected eggs in 100% of samples; zinc sulfate flotation and water sedimentation detected eggs in 90%. All had better detection rates than Sheather sugar flotation (50%). To determine optimal detection methods, Swiss Webster mice were exposed to Syphacia obvelata (SO; n = 60) or AT (n = 60). We compared the following methods at days 0, 30, and 90, beginning 21 or 28 d after SO and AT exposure, respectively: fecal concentration (AT only), anal tape test (SO only), direct examination of intestinal contents (cecum and colon), Swiss roll histology (cecum and colon), and PCR analysis (pooled fur swab and feces). Detection rates for SO-exposed mice were: PCR analysis, 45%; Swiss roll histology, 30%; intestinal content exam, 27%; and tape test, 27%. The SO detection rate for PCR analysis was significantly greater than that for the tape test. Detection rates for AT-exposed mice were: intestinal content exam, 53%; PCR analysis, 33%; fecal flotation, 22%; and Swiss roll histology, 17%. The AT detection rate of PCR analysis combined with intestinal content examination was greater than for PCR analysis only and the AT detection rate of intestinal content examination was greater than for Swiss roll histology. Combining PCR analysis with intestinal content examination detected 100% of infected animals. No single test detected all positive animals. We recommend combining PCR analysis with intestinal content examination for optimal pinworm detection. PMID:28905712

Modeling stream fish distributions using interval-censored detection times.

PubMed

Ferreira, Mário; Filipe, Ana Filipa; Bardos, David C; Magalhães, Maria Filomena; Beja, Pedro

2016-08-01

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it uses simple data that can be readily collected by field ecologists.

Locally adaptive decision in detection of clustered microcalcifications in mammograms

NASA Astrophysics Data System (ADS)

Sainz de Cea, María V.; Nishikawa, Robert M.; Yang, Yongyi

2018-02-01

In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value  <10-4). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.

Deterrence Requirements and Arms Control Responsibilities: The United State’s Obligation to Ratify the Comprehensive Nuclear Test Ban Treaty

DTIC Science & Technology

2010-02-17

systems to detect a nuclear explosion; seismic, hydroacoustic, infrasound , and radionuclide. These stations are able to detect a nuclear explosion as...These sites detect thousands of seismic events a year, mainly from earthquakes and mining explosions, and have proved effective in detecting past...that detect sound waves in the oceans, and the 60 infrasound stations above ground that detect ultra-low frequency sound waves emitted by nuclear

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

DTIC Science & Technology

2010-11-01

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

An Underwater Target Detection System for Electro-Optical Imagery Data

DTIC Science & Technology

2010-06-01

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

Signal Detection Theory-Based Information Processing for the Detection of Breast Cancer at Microwave Frequencies

DTIC Science & Technology

2002-08-01

the measurement noise, as well as the physical model of the forward scattered electric field. The Bayesian algorithms for the Uncertain Permittivity...received at multiple sensors. In this research project a tissue- model -based signal-detection theory approach for the detection of mammary tumors in the...oriented information processors. In this research project a tissue- model - based signal detection theory approach for the detection of mammary tumors in the

Real-time detection system for tumor localization during minimally invasive surgery for gastric and colon cancer removal: In vivo feasibility study in a swine model.

PubMed

Choi, Won Jung; Moon, Jin-Hee; Min, Jae Seok; Song, Yong Keun; Lee, Seung A; Ahn, Jin Woo; Lee, Sang Hun; Jung, Ha Chul

2018-03-01

During minimally invasive surgery (MIS), it is impossible to directly detect marked clips around tumors via palpation. Therefore, we developed a novel method and device using Radio Frequency IDentification (RFID) technology to detect the position of clips during minimally invasive gastrectomy or colectomy. The feasibility of the RFID-based detection system was evaluated in an animal experiment consisting of seven swine. The primary outcome was to successfully detect the location of RFID clips in the stomach and colon. The secondary outcome measures were to detect time (time during the intracorporeal detection of the RFID clip), and accuracy (distance between the RFID clip and the detected site). A total of 25 detection attempts (14 in the stomach and 11 in the colon) using the RFID antenna had a 100% success rate. The median detection time was 32.5 s (range, 15-119 s) for the stomach and 28.0 s (range, 8-87 s) for the colon. The median detection distance was 6.5 mm (range, 4-18 mm) for the stomach and 6.0 mm (range, 3-13 mm) for the colon. We demonstrated favorable results for a RFID system that detects the position of gastric and colon tumors in real-time during MIS. © 2017 Wiley Periodicals, Inc.

Sensitivity quantification of remote detection NMR and MRI

NASA Astrophysics Data System (ADS)

Granwehr, J.; Seeley, J. A.

2006-04-01

A sensitivity analysis is presented of the remote detection NMR technique, which facilitates the spatial separation of encoding and detection of spin magnetization. Three different cases are considered: remote detection of a transient signal that must be encoded point-by-point like a free induction decay, remote detection of an experiment where the transient dimension is reduced to one data point like phase encoding in an imaging experiment, and time-of-flight (TOF) flow visualization. For all cases, the sensitivity enhancement is proportional to the relative sensitivity between the remote detector and the circuit that is used for encoding. It is shown for the case of an encoded transient signal that the sensitivity does not scale unfavorably with the number of encoded points compared to direct detection. Remote enhancement scales as the square root of the ratio of corresponding relaxation times in the two detection environments. Thus, remote detection especially increases the sensitivity of imaging experiments of porous materials with large susceptibility gradients, which cause a rapid dephasing of transverse spin magnetization. Finally, TOF remote detection, in which the detection volume is smaller than the encoded fluid volume, allows partial images corresponding to different time intervals between encoding and detection to be recorded. These partial images, which contain information about the fluid displacement, can be recorded, in an ideal case, with the same sensitivity as the full image detected in a single step with a larger coil.

Gastrointestinal symptoms and quality of life in screen-detected celiac disease.

PubMed

Paavola, Aku; Kurppa, Kalle; Ukkola, Anniina; Collin, Pekka; Lähdeaho, Marja-Leena; Huhtala, Heini; Mäki, Markku; Kaukinen, Katri

2012-10-01

Active serological screening has proved an effective means of increasing the diagnostic rate in celiac disease. The effects of a long-term gluten-free diet on possible gastrointestinal symptoms and psychological well-being in screen-detected patients have nevertheless remained obscure. Abdominal symptoms and quality of life were measured in a large cohort of treated screen-detected celiac adults. Comparisons were made with corresponding symptom-detected patients and with non-celiac controls. Dietary adherence was assessed both by structured interview and by serological testing. In both screen- and symptom-detected celiac groups, 88% of the patients were adherent. On a diet, both screen- and symptom-detected patients reported significantly more gastrointestinal symptoms than non-celiac controls. Those screen-detected patients who reported having no symptoms at the time of diagnosis, also remained asymptomatic during the diet. Despite persistent symptoms, psychological well-being in screen-detected patients was comparable with that in non-celiac controls, whereas the symptom-detected patients showed lower quality of life. Long-term treated screen-detected celiac patients, especially women, suffer from gastrointestinal symptoms on a gluten free diet similarly to symptom-detected patients. However, despite a similar frequency of persistent symptoms, the quality of life was unimpaired in the screen found, but remained low in the symptom-detected group. Copyright © 2012 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Mode of detection: an independent prognostic factor for women with breast cancer.

PubMed

Hofvind, Solveig; Holen, Åsne; Román, Marta; Sebuødegård, Sofie; Puig-Vives, Montse; Akslen, Lars

2016-06-01

To investigate breast cancer survival and risk of breast cancer death by detection mode (screen-detected, interval, and detected outside the screening programme), adjusting for prognostic and predictive tumour characteristics. Information about detection mode, prognostic (age, tumour size, histologic grade, lymph node status) and predictive factors (molecular subtypes based on immunohistochemical analyses of hormone receptor status (estrogen and progesterone) and Her2 status) were available for 8344 women in Norway aged 50-69 at diagnosis of breast cancer, 2005-2011. A total of 255 breast cancer deaths were registered by the end of 2011. Kaplan-Meier method was used to estimate six years breast cancer specific survival and Cox proportional hazard model to estimate hazard ratio (HR) for breast cancer death by detection mode, adjusting for prognostic and predictive factors. Women with screen-detected cancer had favourable prognostic and predictive tumour characteristics compared with interval cancers and those detected outside the screening programme. The favourable characteristics were present for screen-detected cancers, also within the subtypes. Adjusted HR of dying from breast cancer was two times higher for women with symptomatic breast cancer (interval or outside the screening), using screen-detected tumours as the reference. Detection mode is an independent prognostic factor for women diagnosed with breast cancer. Information on detection mode might be relevant for patient management to avoid overtreatment. © The Author(s) 2015.

Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.

46 CFR 108.405 - Fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Fire detection system. 108.405 Section 108.405 Shipping... EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and each smoke detection system on a unit must— (1) Be approved by the Commandant; and (2) Have a visual...

Sensitivity and accuracy of DNA based methods used to describe aquatic communities for early detection of invasive fish species

EPA Science Inventory

For biomonitoring efforts aimed at early detection of aquatic invasive species (AIS), the ability to detect rare individuals is key and requires accurate species level identification to maintain a low occurrence probability of non-detection errors (failure to detect a present spe...

75 FR 76742 - Detecting Oil Leaks From Vessels Into the Water

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-09

... to detect leaks from oil tanks into the water? (E) What is the threshold for detection, accuracy... than leak detection from oil cargo tanks into the water? (H) Are methods or equipment being applied for... DEPARTMENT OF HOMELAND SECURITY Coast Guard [Docket No. USCG-2010-1085] Detecting Oil Leaks From...

12 CFR Appendix J to Part 571 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2013 CFR

2013-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

12 CFR Appendix J to Part 171 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2014 CFR

2014-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

12 CFR Appendix J to Part 171 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2012 CFR

2012-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

12 CFR Appendix J to Part 571 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2012 CFR

2012-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

12 CFR Appendix J to Part 571 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2014 CFR

2014-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

12 CFR Appendix J to Part 571 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2011 CFR

2011-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

12 CFR Appendix J to Part 171 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2013 CFR

2013-01-01

.... III. Detecting Red Flags The Program's policies and procedures should address the detection of Red... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of...

Canine Detection of the Volatilome: A Review of Implications for Pathogen and Disease Detection.

PubMed

Angle, Craig; Waggoner, Lowell Paul; Ferrando, Arny; Haney, Pamela; Passler, Thomas

2016-01-01

The volatilome is the entire set of volatile organic compounds (VOC) produced by an organism. The accumulation of VOC inside and outside of the body reflects the unique metabolic state of an organism. Scientists are developing technologies to non-invasively detect VOC for the purposes of medical diagnosis, therapeutic monitoring, disease outbreak containment, and disease prevention. Detection dogs are proven to be a valuable real-time mobile detection technology for the detection of VOC related to explosives, narcotics, humans, and many other targets of interests. Little is known about what dogs are detecting when searching for biological targets. It is important to understand where biological VOC originates and how dogs might be able to detect biological targets. This review paper discusses the recent scientific literature involving VOC analysis and postulates potential biological targets for canine detection. Dogs have shown their ability to detect pathogen and disease-specific VOC. Future research will determine if dogs can be employed operationally in hospitals, on borders, in underserved areas, on farms, and in other operational environments to give real-time feedback on the presence of a biological target.

Robust vehicle detection under various environments to realize road traffic flow surveillance using an infrared thermal camera.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized.

The application of the detection filter to aircraft control surface and actuator failure detection and isolation

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Wagner, E.; Motyka, P.; Hall, S. R.

1985-01-01

The performance of the detection filter in detecting and isolating aircraft control surface and actuator failures is evaluated. The basic detection filter theory assumption of no direct input-output coupling is violated in this application due to the use of acceleration measurements for detecting and isolating failures. With this coupling, residuals produced by control surface failures may only be constrained to a known plane rather than to a single direction. A detection filter design with such planar failure signatures is presented, with the design issues briefly addressed. In addition, a modification to constrain the residual to a single known direction even with direct input-output coupling is also presented. Both the detection filter and the modification are tested using a nonlinear aircraft simulation. While no thresholds were selected, both filters demonstrated an ability to detect control surface and actuator failures. Failure isolation may be a problem if there are several control surfaces which produce similar effects on the aircraft. In addition, the detection filter was sensitive to wind turbulence and modeling errors.

Detection system of capillary array electrophoresis microchip based on optical fiber

NASA Astrophysics Data System (ADS)

Yang, Xiaobo; Bai, Haiming; Yan, Weiping

2009-11-01

To meet the demands of the post-genomic era study and the large parallel detections of epidemic diseases and drug screening, the high throughput micro-fluidic detection system is needed urgently. A scanning laser induced fluorescence detection system based on optical fiber has been established by using a green laser diode double-pumped solid-state laser as excitation source. It includes laser induced fluorescence detection subsystem, capillary array electrophoresis micro-chip, channel identification unit and fluorescent signal processing subsystem. V-shaped detecting probe composed with two optical fibers for transmitting the excitation light and detecting induced fluorescence were constructed. Parallel four-channel signal analysis of capillary electrophoresis was performed on this system by using Rhodamine B as the sample. The distinction of different samples and separation of samples were achieved with the constructed detection system. The lowest detected concentration is 1×10-5 mol/L for Rhodamine B. The results show that the detection system possesses some advantages, such as compact structure, better stability and higher sensitivity, which are beneficial to the development of microminiaturization and integration of capillary array electrophoresis chip.

A fuzzy pattern matching method based on graph kernel for lithography hotspot detection

NASA Astrophysics Data System (ADS)

Nitta, Izumi; Kanazawa, Yuzi; Ishida, Tsutomu; Banno, Koji

2017-03-01

In advanced technology nodes, lithography hotspot detection has become one of the most significant issues in design for manufacturability. Recently, machine learning based lithography hotspot detection has been widely investigated, but it has trade-off between detection accuracy and false alarm. To apply machine learning based technique to the physical verification phase, designers require minimizing undetected hotspots to avoid yield degradation. They also need a ranking of similar known patterns with a detected hotspot to prioritize layout pattern to be corrected. To achieve high detection accuracy and to prioritize detected hotspots, we propose a novel lithography hotspot detection method using Delaunay triangulation and graph kernel based machine learning. Delaunay triangulation extracts features of hotspot patterns where polygons locate irregularly and closely one another, and graph kernel expresses inner structure of graphs. Additionally, our method provides similarity between two patterns and creates a list of similar training patterns with a detected hotspot. Experiments results on ICCAD 2012 benchmarks show that our method achieves high accuracy with allowable range of false alarm. We also show the ranking of the similar known patterns with a detected hotspot.

Robust Vehicle Detection under Various Environments to Realize Road Traffic Flow Surveillance Using an Infrared Thermal Camera

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized. PMID:25763384

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

PubMed Central

Wang, Jianqiang; Sun, Xiaoyan; Guo, Junbin

2013-01-01

The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS). This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR) of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

Intrusion Detection in Control Systems using Sequence Characteristics

NASA Astrophysics Data System (ADS)

Kiuchi, Mai; Onoda, Takashi

Intrusion detection is considered effective in control systems. Sequences of the control application behavior observed in the communication, such as the order of the control device to be controlled, are important in control systems. However, most intrusion detection systems do not effectively reflect sequences in the application layer into the detection rules. In our previous work, we considered utilizing sequences for intrusion detection in control systems, and demonstrated the usefulness of sequences for intrusion detection. However, manually writing the detection rules for a large system can be difficult, so using machine learning methods becomes feasible. Also, in the case of control systems, there have been very few observed cyber attacks, so we have very little knowledge of the attack data that should be used to train the intrusion detection system. In this paper, we use an approach that combines CRF (Conditional Random Field) considering the sequence of the system, thus able to reflect the characteristics of control system sequences into the intrusion detection system, and also does not need the knowledge of attack data to construct the detection rules.

Cellular telephone-based radiation sensor and wide-area detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2006-12-12

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Search times and probability of detection in time-limited search

NASA Astrophysics Data System (ADS)

Wilson, David; Devitt, Nicole; Maurer, Tana

2005-05-01

When modeling the search and target acquisition process, probability of detection as a function of time is important to war games and physical entity simulations. Recent US Army RDECOM CERDEC Night Vision and Electronics Sensor Directorate modeling of search and detection has focused on time-limited search. Developing the relationship between detection probability and time of search as a differential equation is explored. One of the parameters in the current formula for probability of detection in time-limited search corresponds to the mean time to detect in time-unlimited search. However, the mean time to detect in time-limited search is shorter than the mean time to detect in time-unlimited search and the relationship between them is a mathematical relationship between these two mean times. This simple relationship is derived.

Wavelet threshold method of resolving noise interference in periodic short-impulse signals chaotic detection

NASA Astrophysics Data System (ADS)

Deng, Ke; Zhang, Lu; Luo, Mao-Kang

2010-03-01

The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscillator detection system cannot guarantee the immunity to noises (even white noise). In fact the randomness of noises has a serious or even a destructive effect on the detection results in many cases. To solve this problem, we present a new detecting method based on wavelet threshold processing that can detect the chaotic weak signal accompanied with noise. All theoretical analyses and simulation experiments indicate that the new method reduces the noise interferences to detection significantly, thereby making the corresponding chaotic oscillator that detects the weak signals accompanied with noises more stable and reliable.

An affordable and easy-to-use diagnostic method for keratoconus detection using a smartphone

NASA Astrophysics Data System (ADS)

Askarian, Behnam; Tabei, Fatemehsadat; Askarian, Amin; Chong, Jo Woon

2018-02-01

Recently, smartphones are used for disease diagnosis and healthcare. In this paper, we propose a novel affordable diagnostic method of detecting keratoconus using a smartphone. Keratoconus is usually detected in clinics with ophthalmic devices, which are large, expensive and not portable, and need to be operated by trained technicians. However, our proposed smartphone-based eye disease detection method is small, affordable, portable, and it can be operated by patients in a convenient way. The results show that the proposed keratoconus detection method detects severe, advanced, and moderate keratoconus with accuracies of 93%, 86%, 67%, respectively. Due to its convenience with these accuracies, the proposed keratoconus detection method is expected to be applied in detecting keratoconus at an earlier stage in an affordable way.

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.

Detection Progress of Selected Drugs in TLC

PubMed Central

Pyka, Alina

2014-01-01

This entry describes applications of known indicators and dyes as new visualizing reagents and various visualizing systems as well as photocatalytic reactions and bioautography method for the detection of bioactive compounds including drugs and compounds isolated from herbal extracts. Broadening index, detection index, characteristics of densitometric band, modified contrast index, limit of detection, densitometric visualizing index, and linearity range of detected compounds were used for the evaluation of visualizing effects of applied visualizing reagents. It was shown that visualizing effect depends on the chemical structure of the visualizing reagent, the structure of the substance detected, and the chromatographic adsorbent applied. The usefulness of densitometry to direct detection of some drugs was also shown. Quoted papers indicate the detection progress of selected drugs investigated by thin-layer chromatography (TLC). PMID:24551853

Capillary electrophoretic determination of main components of natural dyes with MS detection.

PubMed

Surowiec, Izabella; Pawelec, Katarzyna; Rezeli, Melinda; Kilar, Ferenc; Trojanowicz, Marek

2008-07-01

CE with UV-Vis and MS detections was investigated as a technique for detection of main components of selected natural dyes of plant and insect origin. The BGE giving the best separation of the investigated flavonoids and anthraquinoids, suitable for MS detection consisted of 40 mM ammonium acetate solution of pH 9.5 with 40% ACN. LODs obtained with MS detection were even one order of magnitude lower than the ones obtained with UV-Vis detection. Application of MS detection enabled determination of eleven dye compounds from three different chemical groups in 15 min. and proved to be more satisfactory than diode-array detection in the electrophoretic analysis of main classes of natural dyes both in terms of selectivity and sensitivity of analysis.

Cellular telephone-based radiation detection instrument

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2011-06-14

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Cellular telephone-based wide-area radiation detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2009-06-09

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010

USGS Publications Warehouse

Guimaraes, Wladmir B.; Falls, W. Fred; Caldwell, Andral W.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the hyporheic zone, flood plain, soil gas, soil, and surface water for contaminants at the McCoys Creek Chemical Training Area (MCTA) at Fort Gordon, from October 2009 to September 2010. The assessment included the detection of organic contaminants in the hyporheic zone, flood plain, soil gas, and surface water. In addition, the organic contaminant assessment included the analysis of organic compounds classified as explosives and chemical agents in selected areas. Inorganic contaminants were assessed in soil and surface-water samples. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Ten passive samplers were deployed in the hyporheic zone and flood plain, and total petroleum hydrocarbons (TPH) and octane were detected above the method detection level in every sampler. Other organic compounds detected above the method detection level in the hyporheic zone and flood-plain samplers were trichloroethylene, and cis- and trans- 1, 2-dichloroethylene. One trip blank detected TPH below the method detection level but above the nondetection level. The concentrations of TPH in the samplers were many times greater than the concentrations detected in the blank; therefore, all other TPH concentrations detected are considered to represent environmental conditions. Seventy-one soil-gas samplers were deployed in a grid pattern across the MCTA. Three trip blanks and three method blanks were used and not deployed, and TPH was detected above the method detection level in two trip blanks and one method blank. Detection of TPH was observed at all 71 samplers, but because TPH was detected in the trip and method blanks, TPH was censored and, therefore, only 7 of the 71 samplers were reported as detecting TPH. In addition, benzene, toluene, ethylbenzene, and total xylene were detected above the method detection level in 22 samplers. Other compounds detected above the method detection level included naphthalene, octane, undecane, tridecane, 1,2,4-trimethylbenzene, trichloroethylene, perchloroethylene, chloroform, and 1,4-dichlorobenzene. Subsequent to the soil-gas survey, five locations with elevated contaminant mass were selected and a passive sampler was deployed at those locations to detect the presence of organic compounds classified as explosives or chemical agents. No explosives or chemical agents were detected above the method detection level, but some compounds were detected below the method detection level but above the nondetection level. Dimethyl disulfide, benzothiazole, chloroacetophenones, and para-chlorophenyl methyl sulfide were all detected below the method detection level but above the nondetection level. The compounds 2,4-dinitrotoluene, and para-chlorophenyl methyl sulfone were detected in samplers but also were detected in trip blanks and are not considered as present in the MCTA. The same five locations that were selected for sampling of explosives and chemical agents were selected for soil sampling. Metal concentrations in composite soil samples collected at five locations from land surface to a depth of 6 inches did not exceed the U.S. Environmental Protection Agency Regional Screening Levels for Industrial Soil. Concentrations in some compounds were higher than the South Carolina Department of Health and Environmental Control background levels for nearby South Carolina, including aluminum, arsenic, barium, beryllium, chromium, copper, iron, lead, manganese, nickel, and potassium. A surface-water sample was collected from McCoys Creek and analyzed for volatile organic compounds, semivolatile organic compounds, and inorganic compounds (metals). No volatile organic compounds and (or) semivolatile organic compounds were detected at levels above the maximum contaminant level of the U.S. Environmental Protection Agency (USEPA) National Primary Drinking Water Standard, and no inorganic compounds exceeded the maximum contaminant level of the USEPA National Primary Drinking Water Standard or the Georgia In-Stream Water-Quality Standard. Iron was the only inorganic compound detected in the surface-water sample (578 micrograms per liter) that exceeded the USEPA National Secondary Drinking Water Standard of 300 micrograms per liter.

Fluorescence detection system for microfluidic droplets

NASA Astrophysics Data System (ADS)

Chen, Binyu; Han, Xiaoming; Su, Zhen; Liu, Quanjun

2018-05-01

In microfluidic detection technology, because of the universality of optical methods in laboratory, optical detection is an attractive solution for microfluidic chip laboratory equipment. In addition, the equipment with high stability and low cost can be realized by integrating appropriate optical detection technology on the chip. This paper reports a detection system for microfluidic droplets. Photomultiplier tubes (PMT) is used as a detection device to improve the sensitivity of detection. This system improves the signal to noise ratio by software filtering and spatial filter. The fluorescence intensity is proportional to the concentration of the fluorescence and intensity of the laser. The fluorescence micro droplets of different concentrations can be distinguished by this system.

Detection of Neutrinos from Galactic and Cosmic Supernovae

NASA Astrophysics Data System (ADS)

Beacom, John

2010-11-01

Detecting neutrinos is the key to understanding core-collapse supernovae, but this is notoriously difficult due to the small interaction cross section of neutrinos and the low frequency of supernovae. The prospects for detecting Galactic supernovae depend almost completely on the probability of a fluctuation from the low supernova rate; the detection aspects are largely under control. The prospects for detecting Cosmic supernovae instead depend almost completely on the detection aspects, especially regarding reducing detector backgrounds; the supernova rate and neutrino flux of the universe are now rather well measured or predicted. After decades of effort and patience, we have good reasons to anticipate that detecting supernova neutrinos is within reach.

Revolution in Detection Affairs

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

Stern W.

The detection of nuclear or radioactive materials for homeland or national security purposes is inherently difficult. This is one reason detection efforts must be seen as just one part of an overall nuclear defense strategy which includes, inter alia, material security, detection, interdiction, consequence management and recovery. Nevertheless, one could argue that there has been a revolution in detection affairs in the past several decades as the innovative application of new technology has changed the character and conduct of detection operations. This revolution will likely be most effectively reinforced in the coming decades with the networking of detectors and innovativemore » application of anomaly detection algorithms.« less

Revolution in nuclear detection affairs

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

Stern, Warren M.

The detection of nuclear or radioactive materials for homeland or national security purposes is inherently difficult. This is one reason detection efforts must be seen as just one part of an overall nuclear defense strategy which includes, inter alia, material security, detection, interdiction, consequence management and recovery. Nevertheless, one could argue that there has been a revolution in detection affairs in the past several decades as the innovative application of new technology has changed the character and conduct of detection operations. This revolution will likely be most effectively reinforced in the coming decades with the networking of detectors and innovativemore » application of anomaly detection algorithms.« less

An improvement of vehicle detection under shadow regions in satellite imagery

NASA Astrophysics Data System (ADS)

Karim, Shahid; Zhang, Ye; Ali, Saad; Asif, Muhammad Rizwan

2018-04-01

The processing of satellite imagery is dependent upon the quality of imagery. Due to low resolution, it is difficult to extract accurate information according to the requirements of applications. For the purpose of vehicle detection under shadow regions, we have used HOG for feature extraction, SVM is used for classification and HOG is discerned worthwhile tool for complex environments. Shadow images have been scrutinized and found very complex for detection as observed very low detection rates therefore our dedication is towards enhancement of detection rate under shadow regions by implementing appropriate preprocessing. Vehicles are precisely detected under non-shadow regions with high detection rate than shadow regions.

Study on the Automatic Detection Method and System of Multifunctional Hydrocephalus Shunt

NASA Astrophysics Data System (ADS)

Sun, Xuan; Wang, Guangzhen; Dong, Quancheng; Li, Yuzhong

2017-07-01

Aiming to the difficulty of micro pressure detection and the difficulty of micro flow control in the testing process of hydrocephalus shunt, the principle of the shunt performance detection was analyzed.In this study, the author analyzed the principle of several items of shunt performance detection,and used advanced micro pressure sensor and micro flow peristaltic pump to overcome the micro pressure detection and micro flow control technology.At the same time,This study also puted many common experimental projects integrated, and successfully developed the automatic detection system for a shunt performance detection function, to achieve a test with high precision, high efficiency and automation.

Fast linear feature detection using multiple directional non-maximum suppression.

PubMed

Sun, C; Vallotton, P

2009-05-01

The capacity to detect linear features is central to image analysis, computer vision and pattern recognition and has practical applications in areas such as neurite outgrowth detection, retinal vessel extraction, skin hair removal, plant root analysis and road detection. Linear feature detection often represents the starting point for image segmentation and image interpretation. In this paper, we present a new algorithm for linear feature detection using multiple directional non-maximum suppression with symmetry checking and gap linking. Given its low computational complexity, the algorithm is very fast. We show in several examples that it performs very well in terms of both sensitivity and continuity of detected linear features.

Thermo-optical Characterization of Photothermal Optical Phase Shift Detection in Extended-Nano Channels and UV Detection of Biomolecules.

PubMed

Shimizu, Hisashi; Miyawaki, Naoya; Asano, Yoshihiro; Mawatari, Kazuma; Kitamori, Takehiko

2017-06-06

The expansion of microfluidics research to nanofluidics requires absolutely sensitive and universal detection methods. Photothermal detection, which utilizes optical absorption and nonradiative relaxation, is promising for the sensitive detection of nonlabeled biomolecules in nanofluidic channels. We have previously developed a photothermal optical phase shift (POPS) detection method to detect nonfluorescent molecules sensitively, while a rapid decrease of the sensitivity in nanochannels and the introduction of an ultraviolet (UV) excitation system were issues to be addressed. In the present study, our primary aim is to characterize the POPS signal in terms of the thermo-optical properties and quantitatively evaluate the causes for the decrease in sensitivity. The UV excitation system is then introduced into the POPS detector to realize the sensitive detection of nonlabeled biomolecules. The UV-POPS detection system is designed and constructed from scratch based on a symmetric microscope. The results of simulations and experiments reveal that the sensitivity decreases due to a reduction of the detection volume, dissipation of the heat, and cancellation of the changes in the refractive indices. Finally, determination of the concentration of a nonlabeled protein (bovine serum albumin) is performed in a very thin 900 nm deep nanochannel. As a result, the limit of detection (LOD) is 2.3 μM (600 molecules in the 440 attoliter detection volume), which is as low as that previously obtained for our visible POPS detector. UV-POPS detection is thus expected be a powerful technique for the study of biomolecules, including DNAs and proteins confined in nanofluidic channels.

Quality control for normal liquid-based cytology: Rescreening, high-risk HPV targeted reviewing and/or high-risk HPV detection?

PubMed Central

Depuydt, Christophe E; Arbyn, Marc; Benoy, Ina H; Vandepitte, Johan; Vereecken, Annie J; Bogers, Johannes J

2009-01-01

The objective of this prospective study was to compare the number of CIN2+cases detected in negative cytology by different quality control (QC) methods. Full rescreening, high-risk (HR) human papillomavirus (HPV)-targeted reviewing and HR HPV detection were compared. Randomly selected negative cytology detected by BD FocalPoint™ (NFR), by guided screening of the prescreened which needed further review (GS) and by manual screening (MS) was used. A 3-year follow-up period was available. Full rescreening of cytology only detected 23.5% of CIN2+ cases, whereas the cytological rescreening of oncogenic positive slides (high-risk HPV-targeted reviewing) detected 7 of 17 CIN2+ cases (41.2%). Quantitative real-time PCR for 15 oncogenic HPV types detected all CIN2+ cases. Relative sensitivity to detect histological CIN2+ was 0.24 for full rescreening, 0.41 for HR-targeted reviewing and 1.00 for HR HPV detection. In more than half of the reviewed negative cytological preparations associated with histological CIN2+cases no morphologically abnormal cells were detected despite a positive HPV test. The visual cut-off for the detection of abnormal cytology was established at 6.5 HR HPV copies/cell. High-risk HPV detection has a higher yield for detection of CIN2+ cases as compared to manual screening followed by 5% full review, or compared to targeted reviewing of smears positive for oncogenic HPV types, and show diagnostic properties that support its use as a QC procedure in cytologic laboratories. PMID:18544049

Magnetic bead-quantum dot assay for detection of a biomarker for traumatic brain injury

NASA Astrophysics Data System (ADS)

Kim, Chloe; Searson, Peter C.

2015-10-01

Current diagnostic methods for traumatic brain injury (TBI), which accounts for 15% of all emergency room visits, are limited to neuroimaging modalities. The challenges of accurate diagnosis and monitoring of TBI have created the need for a simple and sensitive blood test to detect brain-specific biomarkers. Here we report on an assay for detection of S100B, a putative biomarker for TBI, using antibody-conjugated magnetic beads for capture of the protein, and antibody-conjugated quantum dots for optical detection. From Western Blot, we show efficient antigen capture and concentration by the magnetic beads. Using magnetic bead capture and quantum dot detection in serum samples, we show a wide detection range and detection limit below the clinical cut-off level.Current diagnostic methods for traumatic brain injury (TBI), which accounts for 15% of all emergency room visits, are limited to neuroimaging modalities. The challenges of accurate diagnosis and monitoring of TBI have created the need for a simple and sensitive blood test to detect brain-specific biomarkers. Here we report on an assay for detection of S100B, a putative biomarker for TBI, using antibody-conjugated magnetic beads for capture of the protein, and antibody-conjugated quantum dots for optical detection. From Western Blot, we show efficient antigen capture and concentration by the magnetic beads. Using magnetic bead capture and quantum dot detection in serum samples, we show a wide detection range and detection limit below the clinical cut-off level. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr05608j

Narrowband signal detection in the SETI field test

NASA Technical Reports Server (NTRS)

Cullers, D. Kent; Deans, Stanley R.

1986-01-01

Various methods for detecting narrow-band signals are evaluated. The characteristics of synchronized and unsynchronized pulses are examined. Synchronous, square law, regular pulse, and the general form detections are discussed. The CW, single pulse, synchronous, and four pulse detections are analyzed in terms of false alarm rate and threshold relative to average noise power. Techniques for saving memory and retaining sensitivity are described. Consideration is given to nondrifting CW detection, asynchronous pulse detection, interpolative and extrapolative pulse detectors, and finite and infinite pulses.

Critical review of dog detection and the influences of physiology, training, and analytical methodologies.

PubMed

Hayes, J E; McGreevy, P D; Forbes, S L; Laing, G; Stuetz, R M

2018-08-01

Detection dogs serve a plethora of roles within modern society, and are relied upon to identify threats such as explosives and narcotics. Despite their importance, research and training regarding detection dogs has involved ambiguity. This is partially due to the fact that the assessment of effectiveness regarding detection dogs continues to be entrenched within a traditional, non-scientific understanding. Furthermore, the capabilities of detection dogs are also based on their olfactory physiology and training methodologies, both of which are hampered by knowledge gaps. Additionally, the future of detection dogs is strongly influenced by welfare and social implications. Most importantly however, is the emergence of progressively inexpensive and efficacious analytical methodologies including gas chromatography related techniques, "e-noses", and capillary electrophoresis. These analytical methodologies provide both an alternative and assistor for the detection dog industry, however the interrelationship between these two detection paradigms requires clarification. These factors, when considering their relative contributions, illustrate a need to address research gaps, formalise the detection dog industry and research process, as well as take into consideration analytical methodologies and their influence on the future status of detection dogs. This review offers an integrated assessment of the factors involved in order to determine the current and future status of detection dogs. Copyright © 2018 Elsevier B.V. All rights reserved.

Design of stepwise screening for prediabetes and type 2 diabetes based on costs and cases detected.

PubMed

de Graaf, Gimon; Postmus, Douwe; Bakker, Stephan J L; Buskens, Erik

2015-09-01

To provide insight into the trade-off between cost per case detected (CPCD) and the detection rate in questionnaire-based stepwise screening for impaired fasting glucose and undiagnosed type 2 diabetes. We considered a stepwise screening in which individuals whose risk score exceeds a predetermined cutoff value are invited for further blood glucose testing. Using individual patient data to determine questionnaire sensitivity and specificity and external sources to determine screening costs and patient response rates, we rolled back a decision tree to estimate the CPCD and the detection rate for all possible cutoffs on the questionnaire. We found a U-shaped relation between CPCD and detection rate, with high costs per case detected at very low and very high detection rates. Changes in patient response rates had a large impact on both the detection rate and the CPCD, whereas screening costs and questionnaire accuracy mainly impacted the CPCD. Our applied method makes it possible to identify a range of efficient cutoffs where higher detection rates can be achieved at an additional cost per detected patient. This enables decision makers to choose an optimal cutoff based on their willingness to pay for additional detected patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Designing and Implementing a Retrospective Earthquake Detection Framework at the U.S. Geological Survey National Earthquake Information Center

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W.; Benz, H.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (USGS NEIC) is implementing and integrating new signal detection methods such as subspace correlation, continuous beamforming, multi-band picking and automatic phase identification into near-real-time monitoring operations. Leveraging the additional information from these techniques help the NEIC utilize a large and varied network on local to global scales. The NEIC is developing an ordered, rapid, robust, and decentralized framework for distributing seismic detection data as well as a set of formalized formatting standards. These frameworks and standards enable the NEIC to implement a seismic event detection framework that supports basic tasks, including automatic arrival time picking, social media based event detections, and automatic association of different seismic detection data into seismic earthquake events. In addition, this framework enables retrospective detection processing such as automated S-wave arrival time picking given a detected event, discrimination and classification of detected events by type, back-azimuth and slowness calculations, and ensuring aftershock and induced sequence detection completeness. These processes and infrastructure improve the NEIC's capabilities, accuracy, and speed of response. In addition, this same infrastructure provides an improved and convenient structure to support access to automatic detection data for both research and algorithmic development.

A feasibility study of stateful automaton packet inspection for streaming application detection systems

NASA Astrophysics Data System (ADS)

Tseng, Kuo-Kun; Lo, Jiao; Liu, Yiming; Chang, Shih-Hao; Merabti, Madjid; Ng, Felix, C. K.; Wu, C. H.

2017-10-01

The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.

Molecular Evolution of Enterovirus 68 Detected in the Philippines

PubMed Central

Imamura, Tadatsugu; Suzuki, Akira; Lupisan, Socorro; Okamoto, Michiko; Aniceto, Rapunzel; Egos, Rutchie J.; Daya, Edgardo E.; Tamaki, Raita; Saito, Mariko; Fuji, Naoko; Roy, Chandra Nath; Opinion, Jaime M.; Santo, Arlene V.; Macalalad, Noel G.; Tandoc, Amado; Sombrero, Lydia; Olveda, Remigio; Oshitani, Hitoshi

2013-01-01

Background Detection of Enterovirus 68 (EV68) has recently been increased. However, underlying evolutionary mechanism of this increasing trend is not fully understood. Methods Nasopharyngeal swabs were collected from 5,240 patients with acute respiratory infections in the Philippines from June 2009 to December 2011. EV68 was detected by polymerase chain reaction (PCR) targeting for 5′ untranslated region (5′UTR), viral protein 1 (VP1), and VP4/VP2. Phylogenetic trees were generated using the obtained sequences. Results Of the 5,240 tested samples, 12 EV68 positive cases were detected between August and December in 2011 (detection rate, 0.23%). The detection rate was higher among inpatients than outpatients (p<0.0001). Among VP1 sequences detected from 7 patients in 2011, 5 in lineage 2 were diverged from those detected in the Philippines in 2008, however, 2 in lineage 3 were not diverged from strains detected in the Philippines in 2008 but closely associated with strains detected in the United States. Combined with our previous report, EV68 occurrences were observed twice in the Philippines within the last four years. Conclusions EV68 detections might be occurring in cyclic patterns, and viruses might have been maintained in the community while some strains might have been newly introduced. PMID:24073203

Automatic multimodal detection for long-term seizure documentation in epilepsy.

PubMed

Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Visual detection of glial cell line-derived neurotrophic factor based on a molecular translator and isothermal strand-displacement polymerization reaction

PubMed Central

Zhang, Li-Yong; Xing, Tao; Du, Li-Xin; Li, Qing-Min; Liu, Wei-Dong; Wang, Ji-Yue; Cai, Jing

2015-01-01

Background Glial cell line-derived neurotrophic factor (GDNF) is a small protein that potently promotes the survival of many types of neurons. Detection of GDNF is vital to monitoring the survival of sympathetic and sensory neurons. However, the specific method for GDNF detection is also un-discovered. The purpose of this study is to explore the method for protein detection of GDNF. Methods A novel visual detection method based on a molecular translator and isothermal strand-displacement polymerization reaction (ISDPR) has been proposed for the detection of GDNF. In this study, a molecular translator was employed to convert the input protein to output deoxyribonucleic acid signal, which was further amplified by ISDPR. The product of ISDPR was detected by a lateral flow biosensor within 30 minutes. Results This novel visual detection method based on a molecular translator and ISDPR has very high sensitivity and selectivity, with a dynamic response ranging from 1 pg/mL to 10 ng/mL, and the detection limit was 1 pg/mL of GDNF. Conclusion This novel visual detection method exhibits high sensitivity and selectivity, which is very simple and universal for GDNF detection to help disease therapy in clinical practice. PMID:25848224

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares

PubMed Central

Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen

2017-01-01

Simple Summary Most prototypes of systems to automatically detect lameness in dairy cattle are still not available on the market. Estimating their potential adoption rate could support developers in defining development goals towards commercially viable and well-adopted systems. We simulated the potential market shares of such prototypes to assess the effect of altering the system cost and detection performance on the potential adoption rate. We found that system cost and lameness detection performance indeed substantially influence the potential adoption rate. In order for farmers to prefer automatic detection over current visual detection, the usefulness that farmers attach to a system with specific characteristics should be higher than that of visual detection. As such, we concluded that low system costs and high detection performances are required before automatic lameness detection systems become applicable in practice. Abstract Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system’s potential adoption rate. PMID:28991188

Portable modular detection system

DOEpatents

Brennan, James S [Rodeo, CA; Singh, Anup [Danville, CA; Throckmorton, Daniel J [Tracy, CA; Stamps, James F [Livermore, CA

2009-10-13

Disclosed herein are portable and modular detection devices and systems for detecting electromagnetic radiation, such as fluorescence, from an analyte which comprises at least one optical element removably attached to at least one alignment rail. Also disclosed are modular detection devices and systems having an integrated lock-in amplifier and spatial filter and assay methods using the portable and modular detection devices.

46 CFR 108.409 - Location and spacing of tubing in pneumatic fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... detection system. 108.409 Section 108.409 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED... and spacing of tubing in pneumatic fire detection system. (a) All tubing in a pneumatic fire detection... exposed in the space. (c) A pneumatic fire detection system must be set to activate after approximately a...

Evaluation of 3M molecular detection system and ANSR pathogen detection system for rapid detection of salmonella from egg products

USDA-ARS?s Scientific Manuscript database

Loop-mediated isothermal amplification (LAMP) is a novel simple detection technology that amplifies DNA with high speed, efficiency, and specificity under isothermal conditions. The objective of this study was to evaluate the effectiveness of 3M Molecular Detection System (MDS) and ANSR Pathogen Det...

21 CFR 866.5900 - Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutation detection system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... regulator (CFTR) gene mutation detection system. 866.5900 Section 866.5900 Food and Drugs FOOD AND DRUG...) gene mutation detection system. (a) Identification. The CFTR gene mutation detection system is a device used to simultaneously detect and identify a panel of mutations and variants in the CFTR gene. It is...

21 CFR 866.5900 - Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutation detection system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... regulator (CFTR) gene mutation detection system. 866.5900 Section 866.5900 Food and Drugs FOOD AND DRUG...) gene mutation detection system. (a) Identification. The CFTR gene mutation detection system is a device used to simultaneously detect and identify a panel of mutations and variants in the CFTR gene. It is...

21 CFR 866.5900 - Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutation detection system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... regulator (CFTR) gene mutation detection system. 866.5900 Section 866.5900 Food and Drugs FOOD AND DRUG...) gene mutation detection system. (a) Identification. The CFTR gene mutation detection system is a device used to simultaneously detect and identify a panel of mutations and variants in the CFTR gene. It is...

21 CFR 866.5900 - Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutation detection system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... regulator (CFTR) gene mutation detection system. 866.5900 Section 866.5900 Food and Drugs FOOD AND DRUG...) gene mutation detection system. (a) Identification. The CFTR gene mutation detection system is a device used to simultaneously detect and identify a panel of mutations and variants in the CFTR gene. It is...

A Temporal Model of Level-Invariant, Tone-in-Noise Detection

ERIC Educational Resources Information Center

Berg, Bruce G.

2004-01-01

Level-invariant detection refers to findings that thresholds in tone-in-noise detection are unaffected by roving-level procedures that degrade energy cues. Such data are inconsistent with ideas that detection is based on the energy passed by an auditory filter. A hypothesis that detection is based on a level-invariant temporal cue is advanced.…

12 CFR Appendix J to Part 717 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2013 CFR

2013-01-01

.... Detecting Red Flags The Program's policies and procedures should address the detection of Red Flags in... Detection, Prevention, and Mitigation J Appendix J to Part 717 Banks and Banking NATIONAL CREDIT UNION...—Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation Section 717.90 of this part...

12 CFR Appendix J to Part 717 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2012 CFR

2012-01-01

.... Detecting Red Flags The Program's policies and procedures should address the detection of Red Flags in... Detection, Prevention, and Mitigation J Appendix J to Part 717 Banks and Banking NATIONAL CREDIT UNION...—Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation Section 717.90 of this part...

12 CFR Appendix J to Part 717 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2014 CFR

2014-01-01

.... Detecting Red Flags The Program's policies and procedures should address the detection of Red Flags in... Detection, Prevention, and Mitigation J Appendix J to Part 717 Banks and Banking NATIONAL CREDIT UNION...—Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation Section 717.90 of this part...

12 CFR Appendix J to Part 717 - Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation

Code of Federal Regulations, 2011 CFR

2011-01-01

.... Detecting Red Flags The Program's policies and procedures should address the detection of Red Flags in... Detection, Prevention, and Mitigation J Appendix J to Part 717 Banks and Banking NATIONAL CREDIT UNION...—Interagency Guidelines on Identity Theft Detection, Prevention, and Mitigation Section 717.90 of this part...

Noise detection in heart sound recordings.

PubMed

Zia, Mohammad K; Griffel, Benjamin; Fridman, Vladimir; Saponieri, Cesare; Semmlow, John L

2011-01-01

Coronary artery disease (CAD) is the leading cause of death in the United States. Although progression of CAD can be controlled using drugs and diet, it is usually detected in advanced stages when invasive treatment is required. Current methods to detect CAD are invasive and/or costly, hence not suitable as a regular screening tool to detect CAD in early stages. Currently, we are developing a noninvasive and cost-effective system to detect CAD using the acoustic approach. This method identifies sounds generated by turbulent flow through partially narrowed coronary arteries to detect CAD. The limiting factor of this method is sensitivity to noises commonly encountered in the clinical setting. Because the CAD sounds are faint, these noises can easily obscure the CAD sounds and make detection impossible. In this paper, we propose a method to detect and eliminate noise encountered in the clinical setting using a reference channel. We show that our method is effective in detecting noise, which is essential to the success of the acoustic approach.

Small-size pedestrian detection in large scene based on fast R-CNN

NASA Astrophysics Data System (ADS)

Wang, Shengke; Yang, Na; Duan, Lianghua; Liu, Lu; Dong, Junyu

2018-04-01

Pedestrian detection is a canonical sub-problem of object detection with high demand during recent years. Although recent deep learning object detectors such as Fast/Faster R-CNN have shown excellent performance for general object detection, they have limited success for small size pedestrian detection in large-view scene. We study that the insufficient resolution of feature maps lead to the unsatisfactory accuracy when handling small instances. In this paper, we investigate issues involving Fast R-CNN for pedestrian detection. Driven by the observations, we propose a very simple but effective baseline for pedestrian detection based on Fast R-CNN, employing the DPM detector to generate proposals for accuracy, and training a fast R-CNN style network to jointly optimize small size pedestrian detection with skip connection concatenating feature from different layers to solving coarseness of feature maps. And the accuracy is improved in our research for small size pedestrian detection in the real large scene.

CAD scheme for detection of hemorrhages and exudates in ocular fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Mizukusa, Yutaka; Fujita, Akihiro; Kakogawa, Masakatsu; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2007-03-01

This paper describes a method for detecting hemorrhages and exudates in ocular fundus images. The detection of hemorrhages and exudates is important in order to diagnose diabetic retinopathy. Diabetic retinopathy is one of the most significant factors contributing to blindness, and early detection and treatment are important. In this study, hemorrhages and exudates were automatically detected in fundus images without using fluorescein angiograms. Subsequently, the blood vessel regions incorrectly detected as hemorrhages were eliminated by first examining the structure of the blood vessels and then evaluating the length-to-width ratio. Finally, the false positives were eliminated by checking the following features extracted from candidate images: the number of pixels, contrast, 13 features calculated from the co-occurrence matrix, two features based on gray-level difference statistics, and two features calculated from the extrema method. The sensitivity of detecting hemorrhages in the fundus images was 85% and that of detecting exudates was 77%. Our fully automated scheme could accurately detect hemorrhages and exudates.

Quantile regression for the statistical analysis of immunological data with many non-detects.

PubMed

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Detection of new-onset choroidal neovascularization.

PubMed

Do, Diana V

2013-05-01

To highlight the most common methods that are used to detect new-onset choroidal neovascularization (CNV) as a result of age-related macular degeneration (AMD). Numerous modalities are available to try to detect CNV. Amsler grid testing, preferential hyperacuity perimetry (PHP), optical coherence tomography (OCT), and fluorescein angiography are tools that may be used to detect CNV. The Age-Related Macular Degeneration: Detection of Onset of new Choroidal neovascularization Study (AMD DOC Study) evaluated the sensitivity of time domain OCT, relative to fluorescein angiography, in detecting new-onset neovascular AMD within a 2-year period. The sensitivity of each modality for detecting CNV was OCT 0.40 [(95% confidence interval (95% CI) (0.16-0.68), supervised Amsler grid 0.42 (95% CI 0.15-0.72), and PHP 0.50 (95% CI 0.23-0.77)]. Numerous modalities are available to try to detect CNV. The prospective AMD DOC Study demonstrated that fluorescein angiography still remains the best method to detect new-onset CNV.

Domain Anomaly Detection in Machine Perception: A System Architecture and Taxonomy.

PubMed

Kittler, Josef; Christmas, William; de Campos, Teófilo; Windridge, David; Yan, Fei; Illingworth, John; Osman, Magda

2014-05-01

We address the problem of anomaly detection in machine perception. The concept of domain anomaly is introduced as distinct from the conventional notion of anomaly used in the literature. We propose a unified framework for anomaly detection which exposes the multifaceted nature of anomalies and suggest effective mechanisms for identifying and distinguishing each facet as instruments for domain anomaly detection. The framework draws on the Bayesian probabilistic reasoning apparatus which clearly defines concepts such as outlier, noise, distribution drift, novelty detection (object, object primitive), rare events, and unexpected events. Based on these concepts we provide a taxonomy of domain anomaly events. One of the mechanisms helping to pinpoint the nature of anomaly is based on detecting incongruence between contextual and noncontextual sensor(y) data interpretation. The proposed methodology has wide applicability. It underpins in a unified way the anomaly detection applications found in the literature. To illustrate some of its distinguishing features, in here the domain anomaly detection methodology is applied to the problem of anomaly detection for a video annotation system.

A Field-Based Cleaning Protocol for Sampling Devices Used in Life-Detection Studies

NASA Astrophysics Data System (ADS)

Eigenbrode, Jennifer; Benning, Liane G.; Maule, Jake; Wainwright, Norm; Steele, Andrew; Amundsen, Hans E. F.

2009-06-01

Analytical approaches to extant and extinct life detection involve molecular detection often at trace levels. Thus, removal of biological materials and other organic molecules from the surfaces of devices used for sampling is essential for ascertaining meaningful results. Organic decontamination to levels consistent with null values on life-detection instruments is particularly challenging at remote field locations where Mars analog field investigations are carried out. Here, we present a seven-step, multi-reagent decontamination method that can be applied to sampling devices while in the field. In situ lipopolysaccharide detection via low-level endotoxin assays and molecular detection via gas chromatography-mass spectrometry were used to test the effectiveness of the decontamination protocol for sampling of glacial ice with a coring device and for sampling of sediments with a rover scoop during deployment at Arctic Mars-analog sites in Svalbard, Norway. Our results indicate that the protocols and detection technique sufficiently remove and detect low levels of molecular constituents necessary for life-detection tests.

Improved detection and false alarm rejection using FLGPR and color imagery in a forward-looking system

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Spain, Christopher J.; Ho, K. C.; Keller, James M.; Ton, Tuan T.; Wong, David C.; Soumekh, Mehrdad

2010-04-01

Forward-looking ground-penetrating radar (FLGPR) has received a significant amount of attention for use in explosivehazards detection. A drawback to FLGPR is that it results in an excessive number of false detections. This paper presents our analysis of the explosive-hazards detection system tested by the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD). The NVESD system combines an FLGPR with a visible-spectrum color camera. We present a target detection algorithm that uses a locally-adaptive detection scheme with spectrum-based features. The remaining FLGPR detections are then projected into the camera imagery and image-based features are collected. A one-class classifier is then used to reduce the number of false detections. We show that our proposed FLGPR target detection algorithm, coupled with our camera-based false alarm (FA) reduction method, is effective at reducing the number of FAs in test data collected at a US Army test facility.

A field-based cleaning protocol for sampling devices used in life-detection studies.

PubMed

Eigenbrode, Jennifer; Benning, Liane G; Maule, Jake; Wainwright, Norm; Steele, Andrew; Amundsen, Hans E F

2009-06-01

Analytical approaches to extant and extinct life detection involve molecular detection often at trace levels. Thus, removal of biological materials and other organic molecules from the surfaces of devices used for sampling is essential for ascertaining meaningful results. Organic decontamination to levels consistent with null values on life-detection instruments is particularly challenging at remote field locations where Mars analog field investigations are carried out. Here, we present a seven-step, multi-reagent decontamination method that can be applied to sampling devices while in the field. In situ lipopolysaccharide detection via low-level endotoxin assays and molecular detection via gas chromatography-mass spectrometry were used to test the effectiveness of the decontamination protocol for sampling of glacial ice with a coring device and for sampling of sediments with a rover scoop during deployment at Arctic Mars-analog sites in Svalbard, Norway. Our results indicate that the protocols and detection technique sufficiently remove and detect low levels of molecular constituents necessary for life-detection tests.

21 CFR 872.1870 - Sulfide detection device.

Code of Federal Regulations, 2012 CFR

2012-04-01

.... A sulfide detection device is a device consisting of an AC-powered control unit, probe handle, probe... periodontal pocket probing depths, detect the presence or absence of bleeding on probing, and detect the...

21 CFR 872.1870 - Sulfide detection device.

Code of Federal Regulations, 2010 CFR

2010-04-01

.... A sulfide detection device is a device consisting of an AC-powered control unit, probe handle, probe... periodontal pocket probing depths, detect the presence or absence of bleeding on probing, and detect the...

21 CFR 872.1870 - Sulfide detection device.

Code of Federal Regulations, 2013 CFR

2013-04-01

.... A sulfide detection device is a device consisting of an AC-powered control unit, probe handle, probe... periodontal pocket probing depths, detect the presence or absence of bleeding on probing, and detect the...

21 CFR 872.1870 - Sulfide detection device.

Code of Federal Regulations, 2011 CFR

2011-04-01

.... A sulfide detection device is a device consisting of an AC-powered control unit, probe handle, probe... periodontal pocket probing depths, detect the presence or absence of bleeding on probing, and detect the...

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

A study of malware detection on smart mobile devices

NASA Astrophysics Data System (ADS)

Yu, Wei; Zhang, Hanlin; Xu, Guobin

2013-05-01

The growing in use of smart mobile devices for everyday applications has stimulated the spread of mobile malware, especially on popular mobile platforms. As a consequence, malware detection becomes ever more critical in sustaining the mobile market and providing a better user experience. In this paper, we review the existing malware and detection schemes. Using real-world malware samples with known signatures, we evaluate four popular commercial anti-virus tools and our data shows that these tools can achieve high detection accuracy. To deal with the new malware with unknown signatures, we study the anomaly based detection using decision tree algorithm. We evaluate the effectiveness of our detection scheme using malware and legitimate software samples. Our data shows that the detection scheme using decision tree can achieve a detection rate up to 90% and a false positive rate as low as 10%.

Smart materials: strain sensing and stress determination by means of nanotube sensing systems, composites, and devices

NASA Technical Reports Server (NTRS)

Kim, Jong Dae (Inventor); Nagarajaiah, Satish (Inventor); Barrera, Enrique V. (Inventor); Dharap, Prasad (Inventor); Zhiling, Li (Inventor)

2010-01-01

The present invention is directed toward devices comprising carbon nanotubes that are capable of detecting displacement, impact, stress, and/or strain in materials, methods of making such devices, methods for sensing/detecting/monitoring displacement, impact, stress, and/or strain via carbon nanotubes, and various applications for such methods and devices. The devices and methods of the present invention all rely on mechanically-induced electronic perturbations within the carbon nanotubes to detect and quantify such stress/strain. Such detection and quantification can rely on techniques which include, but are not limited to, electrical conductivity/conductance and/or resistivity/resistance detection/measurements, thermal conductivity detection/measurements, electroluminescence detection/measurements, photoluminescence detection/measurements, and combinations thereof. All such techniques rely on an understanding of how such properties change in response to mechanical stress and/or strain.

Absolute ion detection efficiencies of microchannel plates and funnel microchannel plates for multi-coincidence detection

NASA Astrophysics Data System (ADS)

Fehre, K.; Trojanowskaja, D.; Gatzke, J.; Kunitski, M.; Trinter, F.; Zeller, S.; Schmidt, L. Ph. H.; Stohner, J.; Berger, R.; Czasch, A.; Jagutzki, O.; Jahnke, T.; Dörner, R.; Schöffler, M. S.

2018-04-01

Modern momentum imaging techniques allow for the investigation of complex molecules in the gas phase by detection of several fragment ions in coincidence. For these studies, it is of great importance that the single-particle detection efficiency ɛ is as high as possible, as the overall efficiency scales with ɛn, i.e., the power of the number of detected particles. Here we present measured absolute detection efficiencies for protons of several micro-channel plates (MCPs), including efficiency enhanced "funnel MCPs." Furthermore, the relative detection efficiency for two-, three-, four-, and five-body fragmentation of CHBrClF has been examined. The "funnel" MCPs exhibit an efficiency of approximately 90%, gaining a factor of 24 (as compared to "normal" MCPs) in the case of a five-fold ion coincidence detection.

Method for oil pipeline leak detection based on distributed fiber optic technology

NASA Astrophysics Data System (ADS)

Chen, Huabo; Tu, Yaqing; Luo, Ting

1998-08-01

Pipeline leak detection is a difficult problem to solve up to now. Some traditional leak detection methods have such problems as high rate of false alarm or missing detection, low location estimate capability. For the problems given above, a method for oil pipeline leak detection based on distributed optical fiber sensor with special coating is presented. The fiber's coating interacts with hydrocarbon molecules in oil, which alters the refractive indexed of the coating. Therefore the light-guiding properties of the fiber are modified. Thus pipeline leak location can be determined by OTDR. Oil pipeline lead detection system is designed based on the principle. The system has some features like real time, multi-point detection at the same time and high location accuracy. In the end, some factors that probably influence detection are analyzed and primary improving actions are given.

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.

A model for anomaly classification in intrusion detection systems

NASA Astrophysics Data System (ADS)

Ferreira, V. O.; Galhardi, V. V.; Gonçalves, L. B. L.; Silva, R. C.; Cansian, A. M.

2015-09-01

Intrusion Detection Systems (IDS) are traditionally divided into two types according to the detection methods they employ, namely (i) misuse detection and (ii) anomaly detection. Anomaly detection has been widely used and its main advantage is the ability to detect new attacks. However, the analysis of anomalies generated can become expensive, since they often have no clear information about the malicious events they represent. In this context, this paper presents a model for automated classification of alerts generated by an anomaly based IDS. The main goal is either the classification of the detected anomalies in well-defined taxonomies of attacks or to identify whether it is a false positive misclassified by the IDS. Some common attacks to computer networks were considered and we achieved important results that can equip security analysts with best resources for their analyses.

Investigation of an Optimum Detection Scheme for a Star-Field Mapping System

NASA Technical Reports Server (NTRS)

Aldridge, M. D.; Credeur, L.

1970-01-01

An investigation was made to determine the optimum detection scheme for a star-field mapping system that uses coded detection resulting from starlight shining through specially arranged multiple slits of a reticle. The computer solution of equations derived from a theoretical model showed that the greatest probability of detection for a given star and background intensity occurred with the use of a single transparent slit. However, use of multiple slits improved the system's ability to reject the detection of undesirable lower intensity stars, but only by decreasing the probability of detection for lower intensity stars to be mapped. Also, it was found that the coding arrangement affected the root-mean-square star-position error and that detection is possible with error in the system's detected spin rate, though at a reduced probability.

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.

Single-Molecule Plasmon Sensing: Current Status and Future Prospects

PubMed Central

2017-01-01

Single-molecule detection has long relied on fluorescent labeling with high quantum-yield fluorophores. Plasmon-enhanced detection circumvents the need for labeling by allowing direct optical detection of weakly emitting and completely nonfluorescent species. This review focuses on recent advances in single molecule detection using plasmonic metal nanostructures as a sensing platform, particularly using a single particle–single molecule approach. In the past decade two mechanisms for plasmon-enhanced single-molecule detection have been demonstrated: (1) by plasmonically enhancing the emission of weakly fluorescent biomolecules, or (2) by monitoring shifts of the plasmon resonance induced by single-molecule interactions. We begin with a motivation regarding the importance of single molecule detection, and advantages plasmonic detection offers. We describe both detection mechanisms and discuss challenges and potential solutions. We finalize by highlighting the exciting possibilities in analytical chemistry and medical diagnostics. PMID:28762723

Metallic orthopaedic implants and airport metal detectors.

PubMed

Kamineni, S; Legge, S; Ware, H

2002-01-01

Airport security can detect in vivo metallic implants. We hypothesized that a soft tissue shield and fast transit through archway detectors would decrease implant detectability, whereas greater implant mass would increase detectability. Twelve patients with 8 orthopaedic implants in vivo and 60 trauma and arthroplasty implants in vitro were subjected to standard airport security measures at Stanstead Airport (British Airports Authority), including arch and standard and nonstandard hand-held detectors. Archway detectors failed to detect some implants; hand-held detectors detected almost all implants except an ankle arthroplasty. Positive archway detection was related to implant transit speed through the detection field. The implant mass consistently affected detection in stainless steel and titanium implants, and a 1-inch wax shield had no effect. Patients with metallic implants should prepare routinely with documentation of their implant before traveling through security ports.

Preparation of genosensor for detection of specific DNA sequence of the hepatitis B virus

NASA Astrophysics Data System (ADS)

Honorato Castro, Ana C.; França, Erick G.; de Paula, Lucas F.; Soares, Marcia M. C. N.; Goulart, Luiz R.; Madurro, João M.; Brito-Madurro, Ana G.

2014-09-01

An electrochemical genosensor was constructed for detection of specific DNA sequence of the hepatitis B virus, based on graphite electrodes modified with poly(4-aminophenol) and incorporating a specific oligonucleotide probe. The modified electrode containing the probe was evaluated by differential pulse voltammetry, before and after incubation with the complementary oligonucleotide target. Detection was performed by monitoring oxidizable DNA bases (direct detection) or using ethidium bromide as indicator of the hybridization process (indirect detection). The device showed a detection limit for the oligonucleotide target of 2.61 nmol L-1. Indirect detection using ethidium bromide was promising in discriminating mismatches, which is a very desirable attribute for detection of disease-related point mutations. In addition, it was possible to observe differences between hybridized and non-hybridized surfaces by atomic force microscopy.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Data fusion for QRS complex detection in multi-lead electrocardiogram recordings

NASA Astrophysics Data System (ADS)

Ledezma, Carlos A.; Perpiñan, Gilberto; Severeyn, Erika; Altuve, Miguel

2015-12-01

Heart diseases are the main cause of death worldwide. The first step in the diagnose of these diseases is the analysis of the electrocardiographic (ECG) signal. In turn, the ECG analysis begins with the detection of the QRS complex, which is the one with the most energy in the cardiac cycle. Numerous methods have been proposed in the bibliography for QRS complex detection, but few authors have analyzed the possibility of taking advantage of the information redundancy present in multiple ECG leads (simultaneously acquired) to produce accurate QRS detection. In our previous work we presented such an approach, proposing various data fusion techniques to combine the detections made by an algorithm on multiple ECG leads. In this paper we present further studies that show the advantages of this multi-lead detection approach, analyzing how many leads are necessary in order to observe an improvement in the detection performance. A well known QRS detection algorithm was used to test the fusion techniques on the St. Petersburg Institute of Cardiological Technics database. Results show improvement in the detection performance with as little as three leads, but the reliability of these results becomes interesting only after using seven or more leads. Results were evaluated using the detection error rate (DER). The multi-lead detection approach allows an improvement from DER = 3:04% to DER = 1:88%. Further works are to be made in order to improve the detection performance by implementing further fusion steps.

Evaluation of real-time PCR detection methods for detecting rice products contaminated by rice genetically modified with a CpTI-KDEL-T-nos transgenic construct.

PubMed

Nakamura, Kosuke; Akiyama, Hiroshi; Kawano, Noriaki; Kobayashi, Tomoko; Yoshimatsu, Kayo; Mano, Junichi; Kitta, Kazumi; Ohmori, Kiyomi; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko

2013-12-01

Genetically modified (GM) rice (Oryza sativa) lines, such as insecticidal Kefeng and Kemingdao, have been developed and found unauthorised in processed rice products in many countries. Therefore, qualitative detection methods for the GM rice are required for the GM food regulation. A transgenic construct for expressing cowpea (Vigna unguiculata) trypsin inhibitor (CpTI) was detected in some imported processed rice products contaminated with Kemingdao. The 3' terminal sequence of the identified transgenic construct for expression of CpTI included an endoplasmic reticulum retention signal coding sequence (KDEL) and nopaline synthase terminator (T-nos). The sequence was identical to that in a report on Kefeng. A novel construct-specific real-time polymerase chain reaction (PCR) detection method for detecting the junction region sequence between the CpTI-KDEL and T-nos was developed. The imported processed rice products were evaluated for the contamination of the GM rice using the developed construct-specific real-time PCR methods, and detection frequency was compared with five event-specific detection methods. The construct-specific detection methods detected the GM rice at higher frequency than the event-specific detection methods. Therefore, we propose that the construct-specific detection method is a beneficial tool for screening the contamination of GM rice lines, such as Kefeng, in processed rice products for the GM food regulation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiplex nucleic acid sequence-based amplification for simultaneous detection of several enteric viruses in model ready-to-eat foods.

PubMed

Jean, Julie; D'Souza, Doris H; Jaykus, Lee-Ann

2004-11-01

Human enteric viruses are currently recognized as one of the most important causes of food-borne disease. Implication of enteric viruses in food-borne outbreaks can be difficult to confirm due to the inadequacy of the detection methods available. In this study, a nucleic acid sequence-based amplification (NASBA) method was developed in a multiplex format for the specific, simultaneous, and rapid detection of epidemiologically relevant human enteric viruses. Three previously reported primer sets were used in a single reaction for the amplification of RNA target fragments of 474, 371, and 165 nucleotides for the detection of hepatitis A virus and genogroup I and genogroup II noroviruses, respectively. Amplicons were detected by agarose gel electrophoresis and confirmed by electrochemiluminescence and Northern hybridization. Endpoint detection sensitivity for the multiplex NASBA assay was approximately 10(-1) reverse transcription-PCR-detectable units (or PFU, as appropriate) per reaction. When representative ready-to-eat foods (deli sliced turkey and lettuce) were inoculated with various concentrations of each virus and processed for virus detection with the multiplex NASBA method, all three human enteric viruses were simultaneously detected at initial inoculum levels of 10(0) to 10(2) reverse transcription-PCR-detectable units (or PFU)/9 cm2 in both food commodities. The multiplex NASBA system provides rapid and simultaneous detection of clinically relevant food-borne viruses in a single reaction tube and may be a promising alternative to reverse transcription-PCR for the detection of viral contamination of foods.

Multi-Dimensional Damage Detection for Surfaces and Structures

NASA Technical Reports Server (NTRS)

Williams, Martha; Lewis, Mark; Roberson, Luke; Medelius, Pedro; Gibson, Tracy; Parks, Steen; Snyder, Sarah

2013-01-01

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or sensory system, which may include a time domain reflectometer, resistivity monitoring hardware, or other resistance-based systems. To begin, a layered composite consisting of thin-film damage detection layers separated by non-damage detection layers is fabricated. The damage detection layers are attached to a detector that provides details regarding the physical health of each detection layer individually. If damage occurs to any of the detection layers, a change in the electrical properties of the detection layers damaged occurs, and a response is generated. Real-time analysis of these responses will provide details regarding the depth, location, and size estimation of the damage. Multiple damages can be detected, and the extent (depth) of the damage can be used to generate prognostic information related to the expected lifetime of the layered composite system. The detection system can be fabricated very easily using off-the-shelf equipment, and the detection algorithms can be written and updated (as needed) to provide the level of detail needed based on the system being monitored. Connecting to the thin film detection layers is very easy as well. The truly unique feature of the system is its flexibility; the system can be designed to gather as much (or as little) information as the end user feels necessary. Individual detection layers can be turned on or off as necessary, and algorithms can be used to optimize performance. The system can be used to generate both diagnostic and prognostic information related to the health of layer composite structures, which will be essential if such systems are utilized for space exploration. The technology is also applicable to other in-situ health monitoring systems for structure integrity.

Assessment of soil-gas and groundwater contamination at the Gibson Road landfill, Fort Gordon, Georgia, 2011

USGS Publications Warehouse

Falls, W. Fred; Caldwell, Andral W.; Guimaraes, Wladmir G.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2012-01-01

Soil-gas and groundwater assessments were conducted at the Gibson Road landfill in 201 to provide screening-level environmental contamination data to supplement the data collected during previous environmental studies at the landfill. Passive samplers were used in both assessments to detect volatile and semivolatile organic compounds and polycyclic aromatic hydrocarbons in soil gas and groundwater. A total of 56 passive samplers were deployed in the soil in late July and early August for the soil-gas assessment. Total petroleum hydrocarbons (TPH) were detected at masses greater than the method detection level of 0.02 microgram in all samplers and masses greater than 2.0 micrograms in 13 samplers. Three samplers located between the landfill and a nearby wetland had TPH masses greater than 20 micrograms. Diesel was detected in 28 of the 56 soil-gas samplers. Undecane, tridecane, and pentadecane were detected, but undecane was the most common diesel compound with 23 detections. Only five detections exceeded a combined diesel mass of 0.10 microgram, including the highest mass of 0.27 microgram near the wetland. Toluene was detected in only five passive samplers, including masses of 0.65 microgram near the wetland and 0.85 microgram on the southwestern side of the landfill. The only other gasoline-related compound detected was octane in two samplers. Naphthalene was detected in two samplers in the gully near the landfill and two samplers along the southwestern side of the landfill, but had masses less than or equal to 0.02 microgram. Six samplers located southeast of the landfill had detections of chlorinated compounds, including one perchloroethene detections (0.04 microgram) and five chloroform detections (0.05 to0.08 microgram). Passive samplers were deployed and recovered on August 8, 2011, in nine monitoring wells along the southwestern, southeastern and northeastern sides of the landfill and down gradient from the eastern corner of the landfill. Six of the nine samplers had TPH concentrations greater than 100 micrograms per liter. TPH concentrations declined from 320 micrograms per liter in a sampler near the landfill to 18 micrograms in a sampler near the wetland. Five of the samplers had detections of one or more diesel compounds but detections of individual diesel compounds had concentrations below a method detection level of 0.01 microgram per liter. Benzene was detected in three samplers and exceeded the national primary drinking-water standard of 5 micrograms per liter set by the U.S. Environmental Protection Agency. The concentrations of benzene, and therefore BTEX, were 6.1 micrograms per liter in the sampler near the eastern corner of the landfill, 27 micrograms per liter in the sampler near the wetland, and 37 micrograms per liter in the sampler at the southern corner of the landfill. Nonfuel-related compounds were detected in the four wells that are aligned between the eastern corner of the landfill and the wetland. The sampler deployed nearest the eastern corner of the landfill had the greatest number of detected organic compounds and had the only detections of two trimethylbenzene compounds, naphthalene, 2-methyl naphthalene, and 1,4-dichlorobenzene. The two up gradient samplers had the greatest number of chlorinated compounds with five compounds each, compared to detections of four compounds and one compound in the two down gradient samplers. All four samplers had detections of 1,1-dichloroethane which ranged from 42 to 1,300 micrograms per liter. Other detections of chlorinated compounds included trichloroethene, perchloroethene, cis-1,2-dichloroethene, 1,1,1-trichloroethane and chloroform.

An optimized one-tube, semi-nested PCR assay for Paracoccidioides brasiliensis detection.

PubMed

Pitz, Amanda de Faveri; Koishi, Andrea Cristine; Tavares, Eliandro Reis; Andrade, Fábio Goulart de; Loth, Eduardo Alexandre; Gandra, Rinaldo Ferreira; Venancio, Emerson José

2013-01-01

Herein, we report a one-tube, semi-nested-polymerase chain reaction (OTsn-PCR) assay for the detection of Paracoccidioides brasiliensis. We developed the OTsn-PCR assay for the detection of P. brasiliensis in clinical specimens and compared it with other PCR methods. The OTsn-PCR assay was positive for all clinical samples, and the detection limit was better or equivalent to the other nested or semi-nested PCR methods for P. brasiliensis detection. The OTsn-PCR assay described in this paper has a detection limit similar to other reactions for the molecular detection of P. brasiliensis, but this approach is faster and less prone to contamination than other conventional nested or semi-nested PCR assays.

Alpha-ray detection with a MgB 2 transition edge sensor

NASA Astrophysics Data System (ADS)

Okayasu, S.; Katagiri, M.; Hojou, K.; Morii, Y.; Miki, S.; Shimakage, H.; Wang, Z.; Ishida, T.

2008-09-01

We have been investigating for neutron detection with the MgB 2 transition edge sensor (TES). For the purpose, we have been developing a low noise measurement system for the detection. To confirm the performance of the detecting sensor, alpha ray detection from an americium-241 ( 241Am) alpha-ray source was achieved. A short microfabricated sample with 10 μm length and 1 μm width is used to improve the S/N ratio. The detection is achieved under a constant current condition in the range between 1 and 6 μA bias current, and the resistivity changes at the sample due to the alpha ray irradiation is detected just on the transition edge.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Natural gas pipeline leak detector based on NIR diode laser absorption spectroscopy.

PubMed

Gao, Xiaoming; Fan, Hong; Huang, Teng; Wang, Xia; Bao, Jian; Li, Xiaoyun; Huang, Wei; Zhang, Weijun

2006-09-01

The paper reports on the development of an integrated natural gas pipeline leak detector based on diode laser absorption spectroscopy. The detector transmits a 1.653 microm DFB diode laser with 10 mW and detects a fraction of the backscatter reflected from the topographic targets. To eliminate the effect of topographic scatter targets, a ratio detection technique was used. Wavelength modulation and harmonic detection were used to improve the detection sensitivity. The experimental detection limit is 50 ppmm, remote detection for a distance up to 20 m away topographic scatter target is demonstrated. Using a known simulative leak pipe, minimum detectable pipe leak flux is less than 10 ml/min.

Pulsar timing arrays: the promise of gravitational wave detection.

PubMed

Lommen, Andrea N

2015-12-01

We describe the history, methods, tools, and challenges of using pulsars to detect gravitational waves. Pulsars act as celestial clocks detecting gravitational perturbations in space-time at wavelengths of light-years. The field is poised to make its first detection of nanohertz gravitational waves in the next 10 years. Controversies remain over how far we can reduce the noise in the pulsars, how many pulsars should be in the array, what kind of source we will detect first, and how we can best accommodate our large bandwidth systems. We conclude by considering the important question of how to plan for a post-detection era, beyond the first detection of gravitational waves.

Mobile/android application for QRS detection using zero cross method

NASA Astrophysics Data System (ADS)

Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

2018-03-01

In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

40 CFR 63.1184 - What do I need to know about the design specifications, installation, and operation of a bag leak...

Code of Federal Regulations, 2010 CFR

2010-07-01

... design specifications, installation, and operation of a bag leak detection system? 63.1184 Section 63... bag leak detection system? A bag leak detection system must meet the following requirements: (a) The bag leak detection system must be certified by the manufacturer to be capable of detecting PM...

An Advanced Platform for Biomolecular Detection and Analysis Systems

DTIC Science & Technology

2005-02-01

AFRL-IF-RS-TR-2005-54 Final Technical Report February 2005 AN ADVANCED PLATFORM FOR BIOMOLECULAR DETECTION AND ANALYSIS SYSTEMS...SUBTITLE AN ADVANCED PLATFORM FOR BIOMOLECULAR DETECTION AND ANALYSIS SYSTEMS 6. AUTHOR(S) David J. Beebe 5. FUNDING NUMBERS G...detection, analysis and response as well as many non BC warfare applications such as environmental toxicology, clinical detection and diagnosis

Rapid assessment of assignments using plagiarism detection software.

PubMed

Bischoff, Whitney R; Abrego, Patricia C

2011-01-01

Faculty members most often use plagiarism detection software to detect portions of students' written work that have been copied and/or not attributed to their authors. The rise in plagiarism has led to a parallel rise in software products designed to detect plagiarism. Some of these products are configurable for rapid assessment and teaching, as well as for plagiarism detection.

Automated Corrosion Detection Program

DTIC Science & Technology

2001-10-01

More detailed explanations of the methodology development can be found in Hidden Corrosion Detection Technology Assessment, a paper presented at...Detection Program, a paper presented at the Fourth Joint DoD/FAA/NASA Conference on Aging Aircraft, 2000. AS&M PULSE. The PULSE system, developed...selection can be found in The Evaluation of Hidden Corrosion Detection Technologies on the Automated Corrosion Detection Program, a paper presented

Pothole Detection System Using a Black-box Camera.

PubMed

Jo, Youngtae; Ryu, Seungki

2015-11-19

Aging roads and poor road-maintenance systems result a large number of potholes, whose numbers increase over time. Potholes jeopardize road safety and transportation efficiency. Moreover, they are often a contributing factor to car accidents. To address the problems associated with potholes, the locations and size of potholes must be determined quickly. Sophisticated road-maintenance strategies can be developed using a pothole database, which requires a specific pothole-detection system that can collect pothole information at low cost and over a wide area. However, pothole repair has long relied on manual detection efforts. Recent automatic detection systems, such as those based on vibrations or laser scanning, are insufficient to detect potholes correctly and inexpensively owing to the unstable detection of vibration-based methods and high costs of laser scanning-based methods. Thus, in this paper, we introduce a new pothole-detection system using a commercial black-box camera. The proposed system detects potholes over a wide area and at low cost. We have developed a novel pothole-detection algorithm specifically designed to work with the embedded computing environments of black-box cameras. Experimental results are presented with our proposed system, showing that potholes can be detected accurately in real-time.

Sensitivity Comparison of Vapor Trace Detection of Explosives Based on Chemo-Mechanical Sensing with Optical Detection and Capacitive Sensing with Electronic Detection

PubMed Central

Strle, Drago; Štefane, Bogdan; Zupanič, Erik; Trifkovič, Mario; Maček, Marijan; Jakša, Gregor; Kvasič, Ivan; Muševič, Igor

2014-01-01

The article offers a comparison of the sensitivities for vapour trace detection of Trinitrotoluene (TNT) explosives of two different sensor systems: a chemo-mechanical sensor based on chemically modified Atomic Force Microscope (AFM) cantilevers based on Micro Electro Mechanical System (MEMS) technology with optical detection (CMO), and a miniature system based on capacitive detection of chemically functionalized planar capacitors with interdigitated electrodes with a comb-like structure with electronic detection (CE). In both cases (either CMO or CE), the sensor surfaces are chemically functionalized with a layer of APhS (trimethoxyphenylsilane) molecules, which give the strongest sensor response for TNT. The construction and calibration of a vapour generator is also presented. The measurements of the sensor response to TNT are performed under equal conditions for both systems, and the results show that CE system with ultrasensitive electronics is far superior to optical detection using MEMS. Using CMO system, we can detect 300 molecules of TNT in 10+12 molecules of N2 carrier gas, whereas the CE system can detect three molecules of TNT in 10+12 molecules of carrier N2. PMID:24977388

Peak tree: a new tool for multiscale hierarchical representation and peak detection of mass spectrometry data.

PubMed

Zhang, Peng; Li, Houqiang; Wang, Honghui; Wong, Stephen T C; Zhou, Xiaobo

2011-01-01

Peak detection is one of the most important steps in mass spectrometry (MS) analysis. However, the detection result is greatly affected by severe spectrum variations. Unfortunately, most current peak detection methods are neither flexible enough to revise false detection results nor robust enough to resist spectrum variations. To improve flexibility, we introduce peak tree to represent the peak information in MS spectra. Each tree node is a peak judgment on a range of scales, and each tree decomposition, as a set of nodes, is a candidate peak detection result. To improve robustness, we combine peak detection and common peak alignment into a closed-loop framework, which finds the optimal decomposition via both peak intensity and common peak information. The common peak information is derived and loopily refined from the density clustering of the latest peak detection result. Finally, we present an improved ant colony optimization biomarker selection method to build a whole MS analysis system. Experiment shows that our peak detection method can better resist spectrum variations and provide higher sensitivity and lower false detection rates than conventional methods. The benefits from our peak-tree-based system for MS disease analysis are also proved on real SELDI data.

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

Dual fluorescence/contactless conductivity detection for microfluidic chip.

PubMed

Liu, Cui; Mo, Yun-yan; Chen, Zuan-guang; Li, Xiang; Li, Ou-lian; Zhou, Xie

2008-07-28

A new dual detection system for microchip is reported. Both fluorescence detector (FD) and contactless conductivity detector (CCD) were combined together and integrated on a microfluidic chip. They shared a common detection position and responded simultaneously. A blue light-emitting diode was used as excitation source and a small planar photodiode was used to collect the emitted fluorescence in fluorescence detection, which made the device more compact and portable. The coupling of the fluorescence and contactless conductivity modes at the same position of a single separation channel enhanced the detection characterization of sample and offered simultaneous detection information of both fluorescent and charged specimen. The detection conditions of the system were optimized. K(+), Na(+), fluorescein sodium, fluorescein isothiocyanate (FITC) and FITC-labeled amino acids were used to evaluate the performance of the dual detection system. The limits of detection (LOD) of FD for fluorescein Na(+), FITC, FITC-labeled arginine (Arg), glycine (Gly) and phenylalanine (Phe) were 0.02micromolL(-1), 0.05micromolL(-1), 0.16micromolL(-1), 0.15micromolL(-1), 0.12micromolL(-1) respectively, and the limits of detection (LOD) of CCD achieved 0.58micromolL(-1) and 0.39micromolL(-1) for K(+) and Na(+) respectively.

Bayesian methods for outliers detection in GNSS time series

NASA Astrophysics Data System (ADS)

Qianqian, Zhang; Qingming, Gui

2013-07-01

This article is concerned with the problem of detecting outliers in GNSS time series based on Bayesian statistical theory. Firstly, a new model is proposed to simultaneously detect different types of outliers based on the conception of introducing different types of classification variables corresponding to the different types of outliers; the problem of outlier detection is converted into the computation of the corresponding posterior probabilities, and the algorithm for computing the posterior probabilities based on standard Gibbs sampler is designed. Secondly, we analyze the reasons of masking and swamping about detecting patches of additive outliers intensively; an unmasking Bayesian method for detecting additive outlier patches is proposed based on an adaptive Gibbs sampler. Thirdly, the correctness of the theories and methods proposed above is illustrated by simulated data and then by analyzing real GNSS observations, such as cycle slips detection in carrier phase data. Examples illustrate that the Bayesian methods for outliers detection in GNSS time series proposed by this paper are not only capable of detecting isolated outliers but also capable of detecting additive outlier patches. Furthermore, it can be successfully used to process cycle slips in phase data, which solves the problem of small cycle slips.

Electrochemical and Infrared Absorption Spectroscopy Detection of SF₆ Decomposition Products.

PubMed

Dong, Ming; Zhang, Chongxing; Ren, Ming; Albarracín, Ricardo; Ye, Rixin

2017-11-15

Sulfur hexafluoride (SF₆) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF₆ decomposition and ultimately generates several types of decomposition products. These SF₆ decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF₆ decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF₆ gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF₆ decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF₆ gas decomposition and is verified to reliably and accurately detect the gas components and concentrations.

Exploiting semantics for sensor re-calibration in event detection systems

NASA Astrophysics Data System (ADS)

Vaisenberg, Ronen; Ji, Shengyue; Hore, Bijit; Mehrotra, Sharad; Venkatasubramanian, Nalini

2008-01-01

Event detection from a video stream is becoming an important and challenging task in surveillance and sentient systems. While computer vision has been extensively studied to solve different kinds of detection problems over time, it is still a hard problem and even in a controlled environment only simple events can be detected with a high degree of accuracy. Instead of struggling to improve event detection using image processing only, we bring in semantics to direct traditional image processing. Semantics are the underlying facts that hide beneath video frames, which can not be "seen" directly by image processing. In this work we demonstrate that time sequence semantics can be exploited to guide unsupervised re-calibration of the event detection system. We present an instantiation of our ideas by using an appliance as an example--Coffee Pot level detection based on video data--to show that semantics can guide the re-calibration of the detection model. This work exploits time sequence semantics to detect when re-calibration is required to automatically relearn a new detection model for the newly evolved system state and to resume monitoring with a higher rate of accuracy.

Detection of adenoviruses in shellfish by means of conventional-PCR, nested-PCR, and integrated cell culture PCR (ICC/PCR).

PubMed

Rigotto, C; Sincero, T C M; Simões, C M O; Barardi, C R M

2005-01-01

We tested three PCR based methodologies to detect adenoviruses associated with cultivated oysters. Conventional-PCR, nested-PCR, and integrated cell culture-PCR (ICC/PCR) were first optimized using oysters seeded with know amounts of Adenovirus serotype 5 (Ad5). The maximum sensitivity for Ad5 detection was determined for each method, and then used to detect natural adenovirus contamination in oysters from three aquiculture farms in Florianopolis, Santa Catarina State, Brazil, over a period of 6 months. The results showed that the nested-PCR was more sensitive (limit of detection: 1.2 PFU/g of tissue) than conventional-PCR and ICC-PCR (limit of detection for both: 1.2 x 10(2)PFU/g of tissue) for detection of Ad5 in oyster extracts. Nested-PCR was able to detect 90% of Ad5 contamination in harvested oyster samples, while conventional-PCR was unable to detect Ad5 in any of the samples. The present work suggests that detection of human adenoviruses can be used as a tool to monitor the presence of human viruses in marine environments where shellfish grow, and that nested-PCR is the method of choice.

Factors associated with depression detection in a New Hampshire mental health outreach program.

PubMed

Ghesquiere, Angela R; Pepin, Renee; Kinsey, Jennifer; Bartels, Stephen J; Bruce, Martha L

2017-08-16

For mental health outreach programs for older adults, accurately detecting depression is key to quality service provision. Multiple factors, including gender, cognitive impairment, or recent bereavement may affect depression detection, but this is under-studied. Therefore, we sought to both establish rates of depressive symptom detection and to examine factors associated with inaccuracies of detecting depression among participants in a mental health outreach program serving older adults. We conducted a chart review of 1126 cases in an older adult-focused mental health outreach program in New Hampshire, the Referral Education Assistance & Prevention (REAP) program. Accuracy of depression detection was identified by comparing screen-positive scores for depressive symptoms on the 15-item Geriatric Depression Scale (GDS) to depression identification by counselors on a 'presenting concerns' list. Inaccurate depression detection (positive on the GDS but depression not identified by counselors) occurred in 27.6% of cases. Multivariate regression analyses indicated that anxiety, cognitive concerns, and rurality were all associated with detection innaccuracy. This study appears to be the first to examine factors influencing depression detection in a mental health outreach program. Future efforts should help ensure that all older mental health outreach clients have depression detected at optimal rates.

A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data.

PubMed

Goldstein, Markus; Uchida, Seiichi

2016-01-01

Anomaly detection is the process of identifying unexpected items or events in datasets, which differ from the norm. In contrast to standard classification tasks, anomaly detection is often applied on unlabeled data, taking only the internal structure of the dataset into account. This challenge is known as unsupervised anomaly detection and is addressed in many practical applications, for example in network intrusion detection, fraud detection as well as in the life science and medical domain. Dozens of algorithms have been proposed in this area, but unfortunately the research community still lacks a comparative universal evaluation as well as common publicly available datasets. These shortcomings are addressed in this study, where 19 different unsupervised anomaly detection algorithms are evaluated on 10 different datasets from multiple application domains. By publishing the source code and the datasets, this paper aims to be a new well-funded basis for unsupervised anomaly detection research. Additionally, this evaluation reveals the strengths and weaknesses of the different approaches for the first time. Besides the anomaly detection performance, computational effort, the impact of parameter settings as well as the global/local anomaly detection behavior is outlined. As a conclusion, we give an advise on algorithm selection for typical real-world tasks.

Biosensor technology for the detection of illegal drugs II: antibody development and detection techniques

NASA Astrophysics Data System (ADS)

Hilpert, Reinhold; Bauer, Christian; Binder, Florian; Grol, Michael; Hallermayer, Klaus; Josel, Hans-Peter; Klein, Christian; Maier, Josef; Makower, Alexander; Oberpriller, Helmut; Ritter, Josef

1994-10-01

In a joint project of Deutsche Aerospace, Boehringer Mannheim and the University of Potsdam portable devices for the detection of illegal drugs, based on biosensor technology, are being developed. The concept enrichment of the drug from the gas phase and detection by immunological means. This publication covers the development of specific antibodies and various detection procedures. Antibodies with a high affinity for cocaine have been developed with the aid of specially synthesized immunogens. A competitive detection procedure with biosensors based on optical grating couplers and applying particulate labels has been established, showing a lower detection limit of 10-10 mol/l for cocaine. Additionally, a combination of a displacement-immunoreactor and an enzymatically amplified electrode was investigated, which at present still suffers from insufficient sensitivity of the immunoreactor. An alternative, fleece-matrix based test procedure, where enrichment and detection steps are integrated in a single unit, is promising in terms of simplicity and sensitivity. A simple swab-test for the detection of cocaine at surfaces has been developed, which has a lower detection limit of about 10 ng and which can be performed within one minute.

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

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

The comparison of detection methods of asymptomatic malaria in hypoendemic areas

NASA Astrophysics Data System (ADS)

Siahaan, L.; Panggabean, M.; Panggabean, Y. C.

2018-03-01

Malaria is still a problem that disrupts public health in North Sumatera. Late diagnosis will increase the chances of increased morbidity and mortality due to malaria. The early detection of asymptomatic malaria is one of the best efforts to reduce the transmission of the disease. Early detection is certainly must be done on suspect patients who have no malaria complaints. Passive Case Detection (PCD) methods seem hard to find asymptomatic malaria. This study was conducted to compare ACD (Active Case Detection) and PCD methods in asymptomatic malaria detection in the hypoendemic areas of malaria. ACD method is done by going to the sample based on secondary data. Meanwhile, PCD is done on samples that come to health services. Samples were taken randomly and diagnosis was confirmed by microscopic examination with 3% Giemsa staining, as gold standard of malaria diagnostics. There was a significant difference between ACD and PCD detection methods (p = 0.034), where ACD method was seen superior in detecting malaria patients in all categories, such as: clinical malaria (65.2%), asymptomatic malaria (65.1%) and submicroscopic malaria (58.5%). ACD detection methods are superior in detecting malaria sufferers, especially asymptomatic malaria sufferers.

Fishing in the Water: Effect of Sampled Water Volume on Environmental DNA-Based Detection of Macroinvertebrates.

PubMed

Mächler, Elvira; Deiner, Kristy; Spahn, Fabienne; Altermatt, Florian

2016-01-05

Accurate detection of organisms is crucial for the effective management of threatened and invasive species because false detections directly affect the implementation of management actions. The use of environmental DNA (eDNA) as a species detection tool is in a rapid development stage; however, concerns about accurate detections using eDNA have been raised. We evaluated the effect of sampled water volume (0.25 to 2 L) on the detection rate for three macroinvertebrate species. Additionally, we tested (depending on the sampled water volume) what amount of total extracted DNA should be screened to reduce uncertainty in detections. We found that all three species were detected in all volumes of water. Surprisingly, however, only one species had a positive relationship between an increased sample volume and an increase in the detection rate. We conclude that the optimal sample volume might depend on the species-habitat combination and should be tested for the system where management actions are warranted. Nevertheless, we minimally recommend sampling water volumes of 1 L and screening at least 14 μL of extracted eDNA for each sample to reduce uncertainty in detections when studying macroinvertebrates in rivers and using our molecular workflow.

Development and validation of a dual sensing scheme to improve accuracy of bradycardia and pause detection in an insertable cardiac monitor.

PubMed

Passman, Rod S; Rogers, John D; Sarkar, Shantanu; Reiland, Jerry; Reisfeld, Erin; Koehler, Jodi; Mittal, Suneet

2017-07-01

Undersensing of premature ventricular beats and low-amplitude R waves are primary causes for inappropriate bradycardia and pause detections in insertable cardiac monitors (ICMs). The purpose of this study was to develop and validate an enhanced algorithm to reduce inappropriately detected bradycardia and pause episodes. Independent data sets to develop and validate the enhanced algorithm were derived from a database of ICM-detected bradycardia and pause episodes in de-identified patients monitored for unexplained syncope. The original algorithm uses an auto-adjusting sensitivity threshold for R-wave sensing to detect tachycardia and avoid T-wave oversensing. In the enhanced algorithm, a second sensing threshold is used with a long blanking and fixed lower sensitivity threshold, looking for evidence of undersensed signals. Data reported includes percent change in appropriate and inappropriate bradycardia and pause detections as well as changes in episode detection sensitivity and positive predictive value with the enhanced algorithm. The validation data set, from 663 consecutive patients, consisted of 4904 (161 patients) bradycardia and 2582 (133 patients) pause episodes, of which 2976 (61%) and 996 (39%) were appropriately detected bradycardia and pause episodes. The enhanced algorithm reduced inappropriate bradycardia and pause episodes by 95% and 47%, respectively, with 1.7% and 0.6% reduction in appropriate episodes, respectively. The average episode positive predictive value improved by 62% (P < .001) for bradycardia detection and by 26% (P < .001) for pause detection, with an average relative sensitivity of 95% (P < .001) and 99% (P = .5), respectively. The enhanced dual sense algorithm for bradycardia and pause detection in ICMs substantially reduced inappropriate episode detection with a minimal reduction in true episode detection. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

The role of supplementary environmental surveillance to complement acute flaccid paralysis surveillance for wild poliovirus in Pakistan - 2011-2013.

PubMed

Cowger, Tori L; Burns, Cara C; Sharif, Salmaan; Gary, Howard E; Iber, Jane; Henderson, Elizabeth; Malik, Farzana; Zahoor Zaidi, Syed Sohail; Shaukat, Shahzad; Rehman, Lubna; Pallansch, Mark A; Orenstein, Walter A

2017-01-01

More than 99% of poliovirus infections are non-paralytic and therefore, not detected by acute flaccid paralysis (AFP) surveillance. Environmental surveillance (ES) can detect circulating polioviruses from sewage without relying on clinical presentation. With extensive ES and continued circulation of polioviruses, Pakistan presents a unique opportunity to quantify the impact of ES as a supplement to AFP surveillance on overall completeness and timeliness of poliovirus detection. Genetic, geographic and temporal data were obtained for all wild poliovirus (WPV) isolates detected in Pakistan from January 2011 through December 2013. We used viral genetics to assess gaps in AFP surveillance and ES as measured by detection of 'orphan viruses' (≥1.5% different in VP1 capsid nucleotide sequence). We compared preceding detection of closely related circulating isolates (≥99% identity) detected by AFP surveillance or ES to determine which surveillance system first detected circulation before the presentation of each polio case. A total of 1,127 WPV isolates were detected by AFP surveillance and ES in Pakistan from 2011-2013. AFP surveillance and ES combined exhibited fewer gaps (i.e., % orphan viruses) in detection than AFP surveillance alone (3.3% vs. 7.7%, respectively). ES detected circulation before AFP surveillance in nearly 60% of polio cases (200 of 346). For polio cases reported from provinces conducting ES, ES detected circulation nearly four months sooner on average (117.6 days) than did AFP surveillance. Our findings suggest ES in Pakistan is providing earlier, more sensitive detection of wild polioviruses than AFP surveillance alone. Overall, targeted ES through strategic selection of sites has important implications in the eradication endgame strategy.

The role of supplementary environmental surveillance to complement acute flaccid paralysis surveillance for wild poliovirus in Pakistan – 2011–2013

PubMed Central

Burns, Cara C.; Sharif, Salmaan; Gary, Howard E.; Iber, Jane; Henderson, Elizabeth; Malik, Farzana; Zahoor Zaidi, Syed Sohail; Shaukat, Shahzad; Rehman, Lubna; Pallansch, Mark A.; Orenstein, Walter A.

2017-01-01

Background More than 99% of poliovirus infections are non-paralytic and therefore, not detected by acute flaccid paralysis (AFP) surveillance. Environmental surveillance (ES) can detect circulating polioviruses from sewage without relying on clinical presentation. With extensive ES and continued circulation of polioviruses, Pakistan presents a unique opportunity to quantify the impact of ES as a supplement to AFP surveillance on overall completeness and timeliness of poliovirus detection. Methods Genetic, geographic and temporal data were obtained for all wild poliovirus (WPV) isolates detected in Pakistan from January 2011 through December 2013. We used viral genetics to assess gaps in AFP surveillance and ES as measured by detection of ‘orphan viruses’ (≥1.5% different in VP1 capsid nucleotide sequence). We compared preceding detection of closely related circulating isolates (≥99% identity) detected by AFP surveillance or ES to determine which surveillance system first detected circulation before the presentation of each polio case. Findings A total of 1,127 WPV isolates were detected by AFP surveillance and ES in Pakistan from 2011–2013. AFP surveillance and ES combined exhibited fewer gaps (i.e., % orphan viruses) in detection than AFP surveillance alone (3.3% vs. 7.7%, respectively). ES detected circulation before AFP surveillance in nearly 60% of polio cases (200 of 346). For polio cases reported from provinces conducting ES, ES detected circulation nearly four months sooner on average (117.6 days) than did AFP surveillance. Interpretation Our findings suggest ES in Pakistan is providing earlier, more sensitive detection of wild polioviruses than AFP surveillance alone. Overall, targeted ES through strategic selection of sites has important implications in the eradication endgame strategy. PMID:28742803

Effectiveness of scat detection dogs for detecting forest carnivores

USGS Publications Warehouse

Long, Robert A.; Donovan, T.M.; MacKay, Paula; Zielinski, William J.; Buzas, Jeffrey S.

2007-01-01

We assessed the detection and accuracy rates of detection dogs trained to locate scats from free-ranging black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus). During the summers of 2003-2004, 5 detection teams located 1,565 scats (747 putative black bear, 665 putative fisher, and 153 putative bobcat) at 168 survey sites throughout Vermont, USA. Of 347 scats genetically analyzed for species identification, 179 (51.6%) yielded a positive identification, 131 (37.8%) failed to yield DNA information, and 37 (10.7%) yielded DNA but provided no species confirmation. For 70 survey sites where confirmation of a putative target species' scat was not possible, we assessed the probability that ???1 of the scats collected at the site was deposited by the target species (probability of correct identification; P ID). Based on species confirmations or PID values, we detected bears at 57.1% (96) of sites, fishers at 61.3% (103) of sites, and bobcats at 12.5%o (21) of sites. We estimated that the mean probability of detecting the target species (when present) during a single visit to a site was 0.86 for black bears, 0.95 for fishers, and 0.40 for bobcats. The probability of detecting black bears was largely unaffected by site- or visit-specific covariates, but the probability of detecting fishers varied by detection team. We found little or no effect of topographic ruggedness, vegetation density, or local weather (e.g., temp, humidity) on detection probability for fishers or black bears (data were insufficient for bobcat analyses). Detection dogs were highly effective at locating scats from forest carnivores and provided an efficient and accurate method for collecting detection-nondetection data on multiple species.

Variation in Breast Cancer-Risk Factor Associations by Method of Detection: Results From a Series of Case-Control Studies.

PubMed

Sprague, Brian L; Gangnon, Ronald E; Hampton, John M; Egan, Kathleen M; Titus, Linda J; Kerlikowske, Karla; Remington, Patrick L; Newcomb, Polly A; Trentham-Dietz, Amy

2015-06-15

Concerns about breast cancer overdiagnosis have increased the need to understand how cancers detected through screening mammography differ from those first detected by a woman or her clinician. We investigated risk factor associations for invasive breast cancer by method of detection within a series of case-control studies (1992-2007) carried out in Wisconsin, Massachusetts, and New Hampshire (n=15,648 invasive breast cancer patients and 17,602 controls aged 40-79 years). Approximately half of case women reported that their cancer had been detected by mammographic screening and half that they or their clinician had detected it. In polytomous logistic regression models, parity and age at first birth were more strongly associated with risk of mammography-detected breast cancer than with risk of woman/clinician-detected breast cancer (P≤0.01; adjusted for mammography utilization). Among postmenopausal women, estrogen-progestin hormone use was predominantly associated with risk of woman/clinician-detected breast cancer (odds ratio (OR)=1.49, 95% confidence interval (CI): 1.29, 1.72), whereas obesity was predominantly associated with risk of mammography-detected breast cancer (OR=1.72, 95% CI: 1.54, 1.92). Among regularly screened premenopausal women, obesity was not associated with increased risk of mammography-detected breast cancer (OR=0.99, 95% CI: 0.83, 1.18), but it was associated with reduced risk of woman/clinician-detected breast cancer (OR=0.53, 95% CI: 0.43, 0.64). These findings indicate important differences in breast cancer risk factors according to method of detection. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Testing the importance of auditory detections in avian point counts

USGS Publications Warehouse

Brewster, J.P.; Simons, T.R.

2009-01-01

Recent advances in the methods used to estimate detection probability during point counts suggest that the detection process is shaped by the types of cues available to observers. For example, models of the detection process based on distance-sampling or time-of-detection methods may yield different results for auditory versus visual cues because of differences in the factors that affect the transmission of these cues from a bird to an observer or differences in an observer's ability to localize cues. Previous studies suggest that auditory detections predominate in forested habitats, but it is not clear how often observers hear birds prior to detecting them visually. We hypothesized that auditory cues might be even more important than previously reported, so we conducted an experiment in a forested habitat in North Carolina that allowed us to better separate auditory and visual detections. Three teams of three observers each performed simultaneous 3-min unlimited-radius point counts at 30 points in a mixed-hardwood forest. One team member could see, but not hear birds, one could hear, but not see, and the third was nonhandicapped. Of the total number of birds detected, 2.9% were detected by deafened observers, 75.1% by blinded observers, and 78.2% by nonhandicapped observers. Detections by blinded and nonhandicapped observers were the same only 54% of the time. Our results suggest that the detection of birds in forest habitats is almost entirely by auditory cues. Because many factors affect the probability that observers will detect auditory cues, the accuracy and precision of avian point count estimates are likely lower than assumed by most field ornithologists. ?? 2009 Association of Field Ornithologists.

A double-observer approach for estimating detection probability and abundance from point counts

USGS Publications Warehouse

Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.

2000-01-01

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

Colonic polyps: application value of computer-aided detection in computed tomographic colonography.

PubMed

Zhang, Hui-Mao; Guo, Wei; Liu, Gui-Feng; An, Dong-Hong; Gao, Shuo-Hui; Sun, Li-Bo; Yang, Hai-Shan

2011-02-01

Colonic polyps are frequently encountered in clinics. Computed tomographic colonography (CTC), as a painless and quick detection, has high values in clinics. In this study, we evaluated the application value of computer-aided detection (CAD) in CTC detection of colonic polyps in the Chinese population. CTC was performed with a GE 64-row multidetector computed tomography (MDCT) scanner. Data of 50 CTC patients (39 patients positive for at least one polyp of ≥ 0.5 cm in size and the other 11 patients negative by endoscopic detection) were retrospectively reviewed first without computer-aided detection (CAD) and then with CAD by four radiologists (two were experienced and another two inexperienced) blinded to colonoscopy findings. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of detected colonic polyps, as well as the areas under the ROC curves (Az value) with and without CAD were calculated. CAD increased the overall sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the colonic polyps detected by experienced and inexperienced readers. The sensitivity in detecting small polyps (5 - 9 mm) with CAD in experienced and inexperienced readers increased from 82% and 44% to 93% and 82%, respectively (P > 0.05 and P < 0.001). With the use of CAD, the overall false positive rate and false negative rate for the detection of polyps by experienced and inexperienced readers decreased in different degrees. Among 13 sessile polyps not detected by CAD, two were ≥ 1.0 cm, eleven were 5 - 9 mm in diameter, and nine were flat-shaped lesions. The application of CAD in combination with CTC can increase the ability to detect colonic polyps, particularly for inexperienced readers. However, CAD is of limited value for the detection of flat polyps.

Human papillomavirus detection with genotyping by the cobas and Aptima assays: Significant differences in HPV 16 detection?

PubMed

Chorny, Joseph A; Frye, Teresa C; Fisher, Beth L; Remmers, Carol L

2018-03-23

The primary high-risk human papillomavirus (hrHPV) assays in the United States are the cobas (Roche) and the Aptima (Hologic). The cobas assay detects hrHPV by DNA analysis while the Aptima detects messenger RNA (mRNA) oncogenic transcripts. As the Aptima assay identifies oncogenic expression, it should have a lower rate of hrHPV and genotype detection. The Kaiser Permanente Regional Reference Laboratory in Denver, Colorado changed its hrHPV assay from the cobas to the Aptima assay. The rates of hrHPV detection and genotyping were compared over successive six-month periods. The overall hrHPV detection rates by the two platforms were similar (9.5% versus 9.1%) and not statistically different. For genotyping, the HPV 16 rate by the cobas was 1.6% and by the Aptima it was 1.1%. These differences were statistically different with the Aptima detecting nearly one-third less HPV 16 infections. With the HPV 18 and HPV 18/45, there was a slightly higher detection rate of HPV 18/45 by the Aptima platform (0.5% versus 0.9%) and this was statistically significant. While HPV 16 represents a low percentage of hrHPV infections, it was detected significantly less by the Aptima assay compared to the cobas assay. This has been previously reported, although not highlighted. Given the test methodologies, one would expect the Aptima to detect less HPV 16. This difference appears to be mainly due to a significantly increased number of non-oncogenic HPV 16 infections detected by the cobas test as there were no differences in HPV 16 detection rates in the high-grade squamous intraepithelial lesions indicating that the two tests have similar sensitivities for oncogenic HPV 16. © 2018 Wiley Periodicals, Inc.

Adapting detection sensitivity based on evidence of irregular sinus arrhythmia to improve atrial fibrillation detection in insertable cardiac monitors.

PubMed

Pürerfellner, Helmut; Sanders, Prashanthan; Sarkar, Shantanu; Reisfeld, Erin; Reiland, Jerry; Koehler, Jodi; Pokushalov, Evgeny; Urban, Luboš; Dekker, Lukas R C

2017-10-03

Intermittent change in p-wave discernibility during periods of ectopy and sinus arrhythmia is a cause of inappropriate atrial fibrillation (AF) detection in insertable cardiac monitors (ICM). To address this, we developed and validated an enhanced AF detection algorithm. Atrial fibrillation detection in Reveal LINQ ICM uses patterns of incoherence in RR intervals and absence of P-wave evidence over a 2-min period. The enhanced algorithm includes P-wave evidence during RR irregularity as evidence of sinus arrhythmia or ectopy to adaptively optimize sensitivity for AF detection. The algorithm was developed and validated using Holter data from the XPECT and LINQ Usability studies which collected surface electrocardiogram (ECG) and continuous ICM ECG over a 24-48 h period. The algorithm detections were compared with Holter annotations, performed by multiple reviewers, to compute episode and duration detection performance. The validation dataset comprised of 3187 h of valid Holter and LINQ recordings from 138 patients, with true AF in 37 patients yielding 108 true AF episodes ≥2-min and 449 h of AF. The enhanced algorithm reduced inappropriately detected episodes by 49% and duration by 66% with <1% loss in true episodes or duration. The algorithm correctly identified 98.9% of total AF duration and 99.8% of total sinus or non-AF rhythm duration. The algorithm detected 97.2% (99.7% per-patient average) of all AF episodes ≥2-min, and 84.9% (95.3% per-patient average) of detected episodes involved AF. An enhancement that adapts sensitivity for AF detection reduced inappropriately detected episodes and duration with minimal reduction in sensitivity. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Cardiology

Cost and detection rate of glaucoma screening with imaging devices in a primary care center

PubMed Central

Anton, Alfonso; Fallon, Monica; Cots, Francesc; Sebastian, María A; Morilla-Grasa, Antonio; Mojal, Sergi; Castells, Xavier

2017-01-01

Purpose To analyze the cost and detection rate of a screening program for detecting glaucoma with imaging devices. Materials and methods In this cross-sectional study, a glaucoma screening program was applied in a population-based sample randomly selected from a population of 23,527. Screening targeted the population at risk of glaucoma. Examinations included optic disk tomography (Heidelberg retina tomograph [HRT]), nerve fiber analysis, and tonometry. Subjects who met at least 2 of 3 endpoints (HRT outside normal limits, nerve fiber index ≥30, or tonometry ≥21 mmHg) were referred for glaucoma consultation. The currently established (“conventional”) detection method was evaluated by recording data from primary care and ophthalmic consultations in the same population. The direct costs of screening and conventional detection were calculated by adding the unit costs generated during the diagnostic process. The detection rate of new glaucoma cases was assessed. Results The screening program evaluated 414 subjects; 32 cases were referred for glaucoma consultation, 7 had glaucoma, and 10 had probable glaucoma. The current detection method assessed 677 glaucoma suspects in the population, of whom 29 were diagnosed with glaucoma or probable glaucoma. Glaucoma screening and the conventional detection method had detection rates of 4.1% and 3.1%, respectively, and the cost per case detected was 1,410 and 1,435€, respectively. The cost of screening 1 million inhabitants would be 5.1 million euros and would allow the detection of 4,715 new cases. Conclusion The proposed screening method directed at population at risk allows a detection rate of 4.1% and a cost of 1,410 per case detected. PMID:28243057

A-Track: Detecting Moving Objects in FITS images

NASA Astrophysics Data System (ADS)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2017-04-01

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

Acoustic detection and monitoring for transportation infrastructure security.

DOT National Transportation Integrated Search

2009-09-01

Acoustical methods have been extensively used to locate, identify, and track objects underwater. Some of these applications include detecting and tracking submarines, marine mammal detection and identification, detection of mines and ship wrecks and ...

Fluorescence Immunoassay for Cocaine Detection.

PubMed

Nakayama, Hiroshi; Kenjjou, Noriko; Shigetoh, Nobuyuki; Ito, Yuji

2016-04-01

A fluorescence immunoassay (FIA) has been developed for the detection of cocaine using norcocaine labeled with merocyanine dye and a monoclonal antibody specific to cocaine. Using this FIA, the detection range for cocaine was between 20.0 and 1700 μg/L with a limit of detection of 20.0 μg/L. Other cocaine derivatives did not interfere significantly with the detection when using this immunoassay technique with cross-reactivity values of less than 20%. Thus this FIA could be considered a useful tool for the detection of cocaine.

Material-specific detection and classification of single nanoparticles

PubMed Central

Person, Steven; Deutsch, Bradley; Mitra, Anirban; Novotny, Lukas

2010-01-01

Detection and classification of nanoparticles is important for environmental monitoring, contamination mitigation, biological label tracking, and bio-defense. Detection techniques involve a trade-off between sensitivity, discrimination, and speed. This paper presents a material-specific dual-color common-path interferometric detection system. Two wavelengths are simultaneously used to discriminate between 60 nm silver and 80 nm diameter gold particles in solution with a detection time of τ ≈ 1 ms. The detection technique is applicable to situations where both particle size and material are of interest. PMID:21142033

Spectral analysis method for detecting an element

DOEpatents

Blackwood, Larry G [Idaho Falls, ID; Edwards, Andrew J [Idaho Falls, ID; Jewell, James K [Idaho Falls, ID; Reber, Edward L [Idaho Falls, ID; Seabury, Edward H [Idaho Falls, ID

2008-02-12

A method for detecting an element is described and which includes the steps of providing a gamma-ray spectrum which has a region of interest which corresponds with a small amount of an element to be detected; providing nonparametric assumptions about a shape of the gamma-ray spectrum in the region of interest, and which would indicate the presence of the element to be detected; and applying a statistical test to the shape of the gamma-ray spectrum based upon the nonparametric assumptions to detect the small amount of the element to be detected.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.; Marino, J. T., Jr.

1974-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-emperical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. Bit error probabilities for non-optimum threshold detection system were also investigated.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.

1975-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-empirical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. The bit error probabilities for nonoptimum threshold detection systems were also investigated.

Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhong, Yanfei; Han, Xiaobing; Zhang, Liangpei

2018-04-01

Multi-class geospatial object detection from high spatial resolution (HSR) remote sensing imagery is attracting increasing attention in a wide range of object-related civil and engineering applications. However, the distribution of objects in HSR remote sensing imagery is location-variable and complicated, and how to accurately detect the objects in HSR remote sensing imagery is a critical problem. Due to the powerful feature extraction and representation capability of deep learning, the deep learning based region proposal generation and object detection integrated framework has greatly promoted the performance of multi-class geospatial object detection for HSR remote sensing imagery. However, due to the translation caused by the convolution operation in the convolutional neural network (CNN), although the performance of the classification stage is seldom influenced, the localization accuracies of the predicted bounding boxes in the detection stage are easily influenced. The dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage has not been addressed for HSR remote sensing imagery, and causes position accuracy problems for multi-class geospatial object detection with region proposal generation and object detection. In order to further improve the performance of the region proposal generation and object detection integrated framework for HSR remote sensing imagery object detection, a position-sensitive balancing (PSB) framework is proposed in this paper for multi-class geospatial object detection from HSR remote sensing imagery. The proposed PSB framework takes full advantage of the fully convolutional network (FCN), on the basis of a residual network, and adopts the PSB framework to solve the dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage. In addition, a pre-training mechanism is utilized to accelerate the training procedure and increase the robustness of the proposed algorithm. The proposed algorithm is validated with a publicly available 10-class object detection dataset.

Accounting for imperfect detection of groups and individuals when estimating abundance.

PubMed

Clement, Matthew J; Converse, Sarah J; Royle, J Andrew

2017-09-01

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

Quantifying seining detection probability for fishes of Great Plains sand‐bed rivers

USGS Publications Warehouse

Mollenhauer, Robert; Logue, Daniel R.; Brewer, Shannon K.

2018-01-01

Species detection error (i.e., imperfect and variable detection probability) is an essential consideration when investigators map distributions and interpret habitat associations. When fish detection error that is due to highly variable instream environments needs to be addressed, sand‐bed streams of the Great Plains represent a unique challenge. We quantified seining detection probability for diminutive Great Plains fishes across a range of sampling conditions in two sand‐bed rivers in Oklahoma. Imperfect detection resulted in underestimates of species occurrence using naïve estimates, particularly for less common fishes. Seining detection probability also varied among fishes and across sampling conditions. We observed a quadratic relationship between water depth and detection probability, in which the exact nature of the relationship was species‐specific and dependent on water clarity. Similarly, the direction of the relationship between water clarity and detection probability was species‐specific and dependent on differences in water depth. The relationship between water temperature and detection probability was also species dependent, where both the magnitude and direction of the relationship varied among fishes. We showed how ignoring detection error confounded an underlying relationship between species occurrence and water depth. Despite imperfect and heterogeneous detection, our results support that determining species absence can be accomplished with two to six spatially replicated seine hauls per 200‐m reach under average sampling conditions; however, required effort would be higher under certain conditions. Detection probability was low for the Arkansas River Shiner Notropis girardi, which is federally listed as threatened, and more than 10 seine hauls per 200‐m reach would be required to assess presence across sampling conditions. Our model allows scientists to estimate sampling effort to confidently assess species occurrence, which maximizes the use of available resources. Increased implementation of approaches that consider detection error promote ecological advancements and conservation and management decisions that are better informed.

Embedded security system for multi-modal surveillance in a railway carriage

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

2015-10-01

Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

SNIa detection in the SNLS photometric analysis using Morphological Component Analysis

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

Möller, A.; Ruhlmann-Kleider, V.; Neveu, J.

2015-04-01

Detection of supernovae (SNe) and, more generally, of transient events in large surveys can provide numerous false detections. In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources. Optimizing the detection of transient events is thus an important issue for both present and future surveys. We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation. The 3-year analysis provided 300,000more » detections dominated by signals of bright objects that were not perfectly subtracted. Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination. We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis. This technique exploits the morphological diversity of objects to be detected to extract the signal of interest. At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes. A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction. We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal. SNIa Monte-Carlo (MC) generated images were used to study detection efficiency and coordinate resolution. When tested on SNLS 3-year data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint ones. MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.« less

Evaluation of a near-infrared-type contrast medium extravasation detection system using a swine model.

PubMed

Ishihara, Toshihiro; Kobayashi, Tatsushi; Ikeno, Naoya; Hayashi, Takayuki; Sakakibara, Masahiro; Niki, Noboru; Satake, Mitsuo; Moriyama, Noriyuki

2014-01-01

To refine the development and evaluate the near-infrared (NIR) extravasation detection system and its ability to detect extravasation during a contrast-enhanced computed tomography (CT) examination. The NIR extravasation detection system projects the NIR light through the surface of the human skin then, using its sensory system, will monitor the changes in the amount of NIR that reflected, which varies based on absorption properties.Seven female pigs were used to evaluate the contrast media extravasation detection system, using a 20-gauge intravenous catheter, when injected at a rate of 1 mL/s into 4 different locations just under the skin in the thigh section. Using 3-dimensional CT images, we evaluated the extravasations between time and volume, depth and volume, and finally depth and time to detect. We confirmed that the NIR light, 950-nm wavelength, used by the extravasation detection system is well absorbed by contrast media, making changes easy to detect. The average time to detect an extravasation was 2.05 seconds at a depth of 2.0 mm below the skin with a volume of 1.3 mL, 2.57 seconds at a depth between 2.1 and 5 mm below the skin and a volume of 3.47 mL, 10.5 seconds for depths greater than 5.1 mm and a volume of 11.1 mL. The detection accuracy was significantly deteriorated when the depth exceeded 5.0 mm (Tukey-Kramer, P < 0.05) CONCLUSIONS: The extravasation system detection system that is using NIR has a high level of detection sensitivity. The sensitivity enables the system to detect extravasation at depths less than 2 mm with a volume of 1.5 mL and at depths less than 5 mm with a volume of 3.5 mL. The extravasation detection system could be suitable for use during examinations.

Accounting for imperfect detection of groups and individuals when estimating abundance

USGS Publications Warehouse

Clement, Matthew J.; Converse, Sarah J.; Royle, J. Andrew

2017-01-01

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

The technology on noise reduction of the APD detection circuit

NASA Astrophysics Data System (ADS)

Wu, Xue-ying; Zheng, Yong-chao; Cui, Jian-yong

2013-09-01

The laser pulse detection is widely used in the field of laser range finders, laser communications, laser radar, laser Identification Friend or Foe, et al, for the laser pulse detection has the advantage of high accuracy, high sensitivity and strong anti-interference. The avalanche photodiodes (APD) has the advantage of high quantum efficiency, high response speed and huge gain. The APD is particularly suitable for weak signal detection. The technology that APD acts as the photodetector for weak signal reception and amplification is widely used in laser pulse detection. The APD will convert the laser signal to weak electrical signal. The weak signal is amplified, processed and exported by the circuit. In the circuit design, the optimal signal detection is one key point in photoelectric detection system. The issue discusses how to reduce the noise of the photoelectric signal detection circuit and how to improve the signal-to-noise ratio, related analysis and practice included. The essay analyzes the mathematical model of the signal-to-noise ratio for photoelectric conversion and the noise of the APD photoelectric detection system. By analysis the bandwidth of the detection system is determined, and the circuit devices are selected that match the APD. In the circuit design separated devices with low noise are combined with integrated operational amplifier for the purpose of noise reduction. The methods can effectively suppress the noise, and improve the detection sensitivity.

Detection of low frequency external electronic identification devices using commercial panel readers.

PubMed

Stewart, S C; Rapnicki, P; Lewis, J R; Perala, M

2007-09-01

The ability of a commercially available panel reader system to read International Standards Organization-compliant electronic identification devices under commercial dairy conditions was examined. Full duplex (FDX-B) and half-duplex (HDX) low frequency radio-frequency identification external ear tags were utilized. The study involved 498 Holstein cows in the final 6 wk of gestation. There were 516 total electronic identification devices (n = 334 HDX and n = 182 FDX-B). Eighteen FDX-B were replaced with HDX during the study due to repeated detection failure. There were 6,679 HDX and 3,401 FDX-B device detection attempts. There were 220 (2.2%) unsuccessful and 9,860 (97.8%) successful identification detection attempts. There were 9 unsuccessful detection attempts for HDX (6,670/6,679 = 99.9% successful detection attempts) and 211 unsuccessful detection attempts for FDX-B (3,190/3,401 = 93.8% successful detection attempts). These results demonstrate that this panel system can achieve high detection rates of HDX devices and meet the needs of the most demanding management applications. The FDX-B detection rate was not sufficient for the most demanding applications, requiring a high degree of detection by panel readers. The lower FDX-B rate may not be inherent in the device technology itself, but could be due to other factors, including the particular panel reader utilized or the tuning of the panel reader.

Raman Spectroscopic Detection for Simulants of Chemical Warfare Agents Using a Spatial Heterodyne Spectrometer.

PubMed

Hu, Guangxiao; Xiong, Wei; Luo, Haiyan; Shi, Hailiang; Li, Zhiwei; Shen, Jing; Fang, Xuejing; Xu, Biao; Zhang, Jicheng

2018-01-01

Raman spectroscopic detection is one of the suitable methods for the detection of chemical warfare agents (CWAs) and simulants. Since the 1980s, many researchers have been dedicated to the research of chemical characteristic of CWAs and simulants and instrumental improvement for their analysis and detection. The spatial heterodyne Raman spectrometer (SHRS) is a new developing instrument for Raman detection that appeared in 2011. It is already well-known that SHRS has the characteristics of high spectral resolution, a large field-of-view, and high throughput. Thus, it is inherently suitable for the analysis and detection of these toxic chemicals and simulants. The in situ and standoff detection of some typical simulants of CWAs, such as dimethyl methylphosphonate (DMMP), diisopropyl methylphosphonate (DIMP), triethylphosphate (TEP), diethyl malonate (DEM), methyl salicylate (MES), 2-chloroethyl ethyl sulfide (CEES), and malathion, were tried. The achieved results show that SHRS does have the ability of in situ analysis or standoff detection for simulants of CWAs. When the laser power was set to as low as 26 mW, the SHRS still has a signal-to-noise ratio higher than 5 in in situ detection. The standoff Raman spectra detection of CWAs simulants was realized at a distance of 11 m. The potential feasibility of standoff detection of SHRS for CWAs simulants has been proved.

Indirect fluorometric detection techniques on thin layer chromatography and effect of ultrasound on gel electrophoresis

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

Yinfa, Ma.

Thin-layer chromatography (TLC) is a broadly applicable separation technique. It offers many advantages over high performance liquid chromatography (HPLC), such as easily adapted for two-dimensional separation, for whole-column'' detection and for handling multiple samples, etc. However, due to its draggy development of detection techniques comparing with HPLC, TLC has not received the attention it deserves. Therefore, exploring new detection techniques is very important to the development of TLC. It is the principal of this dissertation to present a new detection method for TLC -- indirect fluorometric detection method. This detection technique is universal sensitive, nondestructive, and simple. This will bemore » described in detail from Sections 1 through Section 5. Section 1 and 3 describe the indirect fluorometric detection of anions and nonelectrolytes in TLC. In Section 2, a detection method for cations based on fluorescence quenching of ethidium bromide is presented. In Section 4, a simple and interesting TLC experiment is designed, three different fluorescence detection principles are used for the determination of caffeine, saccharin and sodium benzoate in beverages. A laser-based indirect fluorometric detection technique in TLC is developed in Section 5. Section 6 is totally different from Sections 1 through 5. An ultrasonic effect on the separation of DNA fragments in agarose gel electrophoresis is investigated. 262 refs.« less

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

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

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

Automatic QRS complex detection using two-level convolutional neural network.

PubMed

Xiang, Yande; Lin, Zhitao; Meng, Jianyi

2018-01-29

The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances. In this study, based on 1-D convolutional neural network (CNN), an accurate method for QRS complex detection is proposed. The CNN consists of object-level and part-level CNNs for extracting different grained ECG morphological features automatically. All the extracted morphological features are used by multi-layer perceptron (MLP) for QRS complex detection. Additionally, a simple ECG signal preprocessing technique which only contains difference operation in temporal domain is adopted. Based on the MIT-BIH arrhythmia (MIT-BIH-AR) database, the proposed detection method achieves overall sensitivity Sen = 99.77%, positive predictivity rate PPR = 99.91%, and detection error rate DER = 0.32%. In addition, the performance variation is performed according to different signal-to-noise ratio (SNR) values. An automatic QRS detection method using two-level 1-D CNN and simple signal preprocessing technique is proposed for QRS complex detection. Compared with the state-of-the-art QRS complex detection approaches, experimental results show that the proposed method acquires comparable accuracy.

The relationship between stereoacuity and stereomotion thresholds.

PubMed

Cumming, B G

1995-01-01

There are in principle at least two binocular sources of information that could be used to determine the motion of an object towards or away from an observer; such motion produces changes in binocular disparities over time and also generates different image velocities in the two eyes. It has been argued in the past that stereomotion is detected by a mechanism that is independent of that which detects static disparities. More recently this conclusion has been questioned. If stereomotion detection in fact depends upon detecting disparities, there should be a clear correlation between static stereo-detection thresholds and stereomotion thresholds. If the systems are separate, there need be no such correlation. Four types of threshold measurement were performed by means of random-dot stereograms: (1) static stereo detection/discrimination; (2) stereomotion detection in random-dot stereograms (temporally uncorrelated); (3) stereomotion detection in temporally correlated random-dot stereograms; and (4) binocular detection of frontoparallel motion. Three normal subjects and five subjects with unusually high stereoacuities were studied. In addition, two manipulations were performed that altered stereomotion thresholds: changes in mean disparity, and image defocus produced by positive spectacle lenses. Across subjects and conditions, stereomotion thresholds were well correlated with stereo-discrimination thresholds. Stereomotion was poorly correlated with binocular frontoparallel-motion thresholds. These results suggest that stereomotion is detected by means of registering changes in the output of the same disparity detectors that are used to detect static disparities.

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.

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

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

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

An experimental validation of a statistical-based damage detection approach.

DOT National Transportation Integrated Search

2011-01-01

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to : autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and : predicted beha...

Laser-induced photo emission detection: data acquisition based on light intensity counting

NASA Astrophysics Data System (ADS)

Yulianto, N.; Yudasari, N.; Putri, K. Y.

2017-04-01

Laser Induced Breakdown Detection (LIBD) is one of the quantification techniques for colloids. There are two ways of detection in LIBD: optical detection and acoustic detection. LIBD is based on the detection of plasma emission due to the interaction between particle and laser beam. In this research, the changing of light intensity during plasma formations was detected by a photodiode sensor. A photo emission data acquisition system was built to collect and transform them into digital counts. The real-time system used data acquisition device National Instrument DAQ 6009 and LABVIEW software. The system has been tested on distilled water and tap water samples. The result showed 99.8% accuracy by using counting technique in comparison to the acoustic detection with sample rate of 10 Hz, thus the acquisition system can be applied as an alternative method to the existing LIBD acquisition system.

Detecting text in natural scenes with multi-level MSER and SWT

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Liu, Renjun

2018-04-01

The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.

Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection

NASA Astrophysics Data System (ADS)

Amiri, Ali; Fathy, Mahmood

2010-12-01

This article explores the problem of video shot boundary detection and examines a novel shot boundary detection algorithm by using QR-decomposition and modeling of gradual transitions by Gaussian functions. Specifically, the authors attend to the challenges of detecting gradual shots and extracting appropriate spatiotemporal features that affect the ability of algorithms to efficiently detect shot boundaries. The algorithm utilizes the properties of QR-decomposition and extracts a block-wise probability function that illustrates the probability of video frames to be in shot transitions. The probability function has abrupt changes in hard cut transitions, and semi-Gaussian behavior in gradual transitions. The algorithm detects these transitions by analyzing the probability function. Finally, we will report the results of the experiments using large-scale test sets provided by the TRECVID 2006, which has assessments for hard cut and gradual shot boundary detection. These results confirm the high performance of the proposed algorithm.

Spectral surface plasmon resonance biosensor for detection of staphylococcal enterotoxin B in milk.

PubMed

Homola, Jirí; Dostálek, Jakub; Chen, Shengfu; Rasooly, Avraham; Jiang, Shaoyi; Yee, Sinclair S

2002-05-05

This work evaluates a newly developed wavelength modulation-based SPR biosensor for the detection of staphylococcal enterotoxin B (SEB) in milk. Two modes of operation of the SPR biosensor are described: direct detection of SEB and sandwich assay. In the sandwich assay detection mode, secondary antibodies are bound to the already captured toxin to amplify sensor response. Samples including SEB in buffer and SEB in milk were analyzed in this work. The SPR biosensor has been shown to be capable of directly detecting concentrations of SEB in buffer as low as 5 ng/ml. In sandwich detection mode, the lowest detection limit was determined to be 0.5 ng/ml for both buffer and milk samples. The reported wavelength modulation-based SPR sensor provides a generic platform which can be tailored for detection of various foodborne pathogens and agents for food analysis and testing.

Geostationary microwave imagers detection criteria

NASA Technical Reports Server (NTRS)

Stacey, J. M.

1986-01-01

Geostationary orbit is investigated as a vantage point from which to sense remotely the surface features of the planet and its atmosphere, with microwave sensors. The geometrical relationships associated with geostationary altitude are developed to produce an efficient search pattern for the detection of emitting media and metal objects. Power transfer equations are derived from the roots of first principles and explain the expected values of the signal-to-clutter ratios for the detection of aircraft, ships, and buoys and for the detection of natural features where they are manifested as cold and warm eddies. The transport of microwave power is described for modeled detection where the direction of power flow is explained by the Zeroth and Second Laws of Thermodynamics. Mathematical expressions are derived that elucidate the detectability of natural emitting media and metal objects. Signal-to-clutter ratio comparisons are drawn among detectable objects that show relative detectability with a thermodynamic sensor and with a short-pulse radar.

Memory Detection 2.0: The First Web-Based Memory Detection Test

PubMed Central

Kleinberg, Bennett; Verschuere, Bruno

2015-01-01

There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research. PMID:25874966

Research of detection depth for graphene-based optical sensor

NASA Astrophysics Data System (ADS)

Yang, Yong; Sun, Jialve; Liu, Lu; Zhu, Siwei; Yuan, Xiaocong

2018-03-01

Graphene-based optical sensors have been developed for research into the biological intercellular refractive index (RI) because they offer greater detection depths than those provided by the surface plasmon resonance technique. In this Letter, we propose an experimental approach for measurement of the detection depth in a graphene-based optical sensor system that uses transparent polydimethylsiloxane layers with different thicknesses. The experimental results show that detection depths of 2.5 μm and 3 μm can be achieved at wavelengths of 532 nm and 633 nm, respectively. These results prove that graphene-based optical sensors can realize long-range RI detection and are thus promising for use as tools in the biological cell detection field. Additionally, we analyze the factors that influence the detection depth and provide a feasible approach for detection depth control based on adjustment of the wavelength and the angle of incidence. We believe that this approach will be useful in RI tomography applications.

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

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

PCR method of detecting pork in foods for verifying allergen labeling and for identifying hidden pork ingredients in processed foods.

PubMed

Tanabe, Soichi; Miyauchi, Eiji; Muneshige, Akemi; Mio, Kazuhiro; Sato, Chikara; Sato, Masahiko

2007-07-01

A PCR method to detect porcine DNA was developed for verifying the allergen labeling of foods and for identifying hidden pork ingredients in processed foods. The primer pair, F2/R1, was designed to detect the gene encoding porcine cytochrome b for the specific detection of pork with high sensitivity. The amplified DNA fragment (130 bp) was specifically detected from porcine DNA, while no amplification occurred with other species such as cattle, chicken, sheep, and horse. When the developed PCR method was used for investigating commercial food products, porcine DNA was clearly detected in those containing pork in the list of ingredients. In addition, 100 ppb of pork in heated gyoza (pork and vegetable dumpling) could be detected by this method. This method is rapid, specific and sensitive, making it applicable for detecting trace amounts of pork in processed foods.

SmartMal: a service-oriented behavioral malware detection framework for mobile devices.

PubMed

Wang, Chao; Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C K

2014-01-01

This paper presents SmartMal--a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.

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.

Standoff detection of explosives: a challenging approach for optical technologies

NASA Astrophysics Data System (ADS)

Désilets, S.; Hô, N.; Mathieu, P.; Simard, J. R.; Puckrin, E.; Thériault, J. M.; Lavoie, H.; Théberge, F.; Babin, F.; Gay, D.; Forest, R.; Maheux, J.; Roy, G.; Châteauneuf, M.

2011-06-01

Standoff detection of explosives residues on surfaces at few meters was made using optical technologies based on Raman scattering, Laser-Induced Breakdown Spectroscopy (LIBS) and passive standoff FTIR radiometry. By comparison, detection and analysis of nanogram samples of different explosives was made with a microscope system where Raman scattering from a micron-size single point illuminated crystal of explosive was observed. Results from standoff detection experiments using a telescope were compared to experiments using a microscope to find out important parameters leading to the detection. While detection and spectral identification of the micron-size explosive particles was possible with a microscope, standoff detection of these particles was very challenging due to undesired light reflected and produced by the background surface or light coming from other contaminants. Results illustrated the challenging approach of detecting at a standoff distance the presence of low amount of micron or submicron explosive particles.

Adaboost multi-view face detection based on YCgCr skin color model

NASA Astrophysics Data System (ADS)

Lan, Qi; Xu, Zhiyong

2016-09-01

Traditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors.

Distributed road assessment system

DOEpatents

Beer, N. Reginald; Paglieroni, David W

2014-03-25

A system that detects damage on or below the surface of a paved structure or pavement is provided. A distributed road assessment system includes road assessment pods and a road assessment server. Each road assessment pod includes a ground-penetrating radar antenna array and a detection system that detects road damage from the return signals as the vehicle on which the pod is mounted travels down a road. Each road assessment pod transmits to the road assessment server occurrence information describing each occurrence of road damage that is newly detected on a current scan of a road. The road assessment server maintains a road damage database of occurrence information describing the previously detected occurrences of road damage. After the road assessment server receives occurrence information for newly detected occurrences of road damage for a portion of a road, the road assessment server determines which newly detected occurrences correspond to which previously detected occurrences of road damage.

Highly sensitive detection of dipicolinic acid with a water-dispersible terbium-metal organic framework.

PubMed

Bhardwaj, Neha; Bhardwaj, Sanjeev; Mehta, Jyotsana; Kim, Ki-Hyun; Deep, Akash

2016-12-15

The sensitive detection of dipicolinic acid (DPA) is strongly associated with the sensing of bacterial organisms in food and many types of environmental samples. To date, the demand for a sensitive detection method for bacterial toxicity has increased remarkably. Herein, we investigated the DPA detection potential of a water-dispersible terbium-metal organic framework (Tb-MOF) based on the fluorescence quenching mechanism. The Tb-MOF showed a highly sensitive ability to detect DPA at a limit of detection of 0.04nM (linear range of detection: 1nM to 5µM) and also offered enhanced selectivity from other commonly associated organic molecules. The present study provides a basis for the application of Tb-MOF for direct, convenient, highly sensitive, and specific detection of DPA in the actual samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Fundamentals and practice for ultrasensitive laser-induced fluorescence detection in microanalytical systems.

PubMed

Johnson, Mitchell E; Landers, James P

2004-11-01

Laser-induced fluorescence is an extremely sensitive method for detection in chemical separations. In addition, it is well-suited to detection in small volumes, and as such is widely used for capillary electrophoresis and microchip-based separations. This review explores the detailed instrumental conditions required for sub-zeptomole, sub-picomolar detection limits. The key to achieving the best sensitivity is to use an excitation and emission volume that is matched to the separation system and that, simultaneously, will keep scattering and luminescence background to a minimum. We discuss how this is accomplished with confocal detection, 90 degrees on-capillary detection, and sheath-flow detection. It is shown that each of these methods have their advantages and disadvantages, but that all can be used to produce extremely sensitive detectors for capillary- or microchip-based separations. Analysis of these capabilities allows prediction of the optimal means of achieving ultrasensitive detection on microchips.

The relationship between malingerers' intelligence and MMPI-2 knowledge and their ability to avoid detection.

PubMed

Pelfrey, William V

2004-12-01

One of the most frequently administered psychometrics is the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Occasionally, those participants taking the MMPI-2 will malinger or exaggerate their symptoms. Several malingering detection devices are available, and a significant body of literature exists concerning their efficacy. However, little research is available considering those factors that facilitate successfully evading detection as a malingerer. Some of these studies have identified general intelligence and knowledge of the MMPI-2 as key variables in the likelihood of escaping detection as a malingerer. The extant research considered the utility of general intelligence and knowledge of the MMPI-2 as predictors in avoiding detection as a malingerer. To detect malingering, the two traditional detection devices were employed: the F-Scale and the F - K Index. Results indicate that intelligence and MMPI-2 knowledge contribute significantly to the likelihood of successfully escaping detection as a malingerer.

A novel radar sensor for the non-contact detection of speech signals.

PubMed

Jiao, Mingke; Lu, Guohua; Jing, Xijing; Li, Sheng; Li, Yanfeng; Wang, Jianqi

2010-01-01

Different speech detection sensors have been developed over the years but they are limited by the loss of high frequency speech energy, and have restricted non-contact detection due to the lack of penetrability. This paper proposes a novel millimeter microwave radar sensor to detect speech signals. The utilization of a high operating frequency and a superheterodyne receiver contributes to the high sensitivity of the radar sensor for small sound vibrations. In addition, the penetrability of microwaves allows the novel sensor to detect speech signals through nonmetal barriers. Results show that the novel sensor can detect high frequency speech energies and that the speech quality is comparable to traditional microphone speech. Moreover, the novel sensor can detect speech signals through a nonmetal material of a certain thickness between the sensor and the subject. Thus, the novel speech sensor expands traditional speech detection techniques and provides an exciting alternative for broader application prospects.

SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices

PubMed Central

Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C. K.

2014-01-01

This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices. PMID:25165729

A Novel Radar Sensor for the Non-Contact Detection of Speech Signals

PubMed Central

Jiao, Mingke; Lu, Guohua; Jing, Xijing; Li, Sheng; Li, Yanfeng; Wang, Jianqi

2010-01-01

Different speech detection sensors have been developed over the years but they are limited by the loss of high frequency speech energy, and have restricted non-contact detection due to the lack of penetrability. This paper proposes a novel millimeter microwave radar sensor to detect speech signals. The utilization of a high operating frequency and a superheterodyne receiver contributes to the high sensitivity of the radar sensor for small sound vibrations. In addition, the penetrability of microwaves allows the novel sensor to detect speech signals through nonmetal barriers. Results show that the novel sensor can detect high frequency speech energies and that the speech quality is comparable to traditional microphone speech. Moreover, the novel sensor can detect speech signals through a nonmetal material of a certain thickness between the sensor and the subject. Thus, the novel speech sensor expands traditional speech detection techniques and provides an exciting alternative for broader application prospects. PMID:22399895

Detection of Antibiotics and Evaluation of Antibacterial Activity with Screen-Printed Electrodes

PubMed Central

Titoiu, Ana Maria; Marty, Jean-Louis

2018-01-01

This review provides a brief overview of the fabrication and properties of screen-printed electrodes and details the different opportunities to apply them for the detection of antibiotics, detection of bacteria and antibiotic susceptibility. Among the alternative approaches to costly chromatographic or ELISA methods for antibiotics detection and to lengthy culture methods for bacteria detection, electrochemical biosensors based on screen-printed electrodes present some distinctive advantages. Chemical and (bio)sensors for the detection of antibiotics and assays coupling detection with screen-printed electrodes with immunomagnetic separation are described. With regards to detection of bacteria, the emphasis is placed on applications targeting viable bacterial cells. While the electrochemical sensors and biosensors face many challenges before replacing standard analysis methods, the potential of screen-printed electrodes is increasingly exploited and more applications are anticipated to advance towards commercial analytical tools. PMID:29562637

Rapid Detection of Ebola Virus with a Reagent-Free, Point-of-Care Biosensor

PubMed Central

Baca, Justin T.; Severns, Virginia; Lovato, Debbie; Branch, Darren W.; Larson, Richard S.

2015-01-01

Surface acoustic wave (SAW) sensors can rapidly detect Ebola antigens at the point-of-care without the need for added reagents, sample processing, or specialized personnel. This preliminary study demonstrates SAW biosensor detection of the Ebola virus in a concentration-dependent manner. The detection limit with this methodology is below the average level of viremia detected on the first day of symptoms by PCR. We observe a log-linear sensor response for highly fragmented Ebola viral particles, with a detection limit corresponding to 1.9 × 104 PFU/mL prior to virus inactivation. We predict greatly improved sensitivity for intact, infectious Ebola virus. This point-of-care methodology has the potential to detect Ebola viremia prior to symptom onset, greatly enabling infection control and rapid treatment. This biosensor platform is powered by disposable AA batteries and can be rapidly adapted to detect other emerging diseases in austere conditions. PMID:25875186

Methods and apparatus using commutative error detection values for fault isolation in multiple node computers

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

Almasi, Gheorghe; Blumrich, Matthias Augustin; Chen, Dong

Methods and apparatus perform fault isolation in multiple node computing systems using commutative error detection values for--example, checksums--to identify and to isolate faulty nodes. When information associated with a reproducible portion of a computer program is injected into a network by a node, a commutative error detection value is calculated. At intervals, node fault detection apparatus associated with the multiple node computer system retrieve commutative error detection values associated with the node and stores them in memory. When the computer program is executed again by the multiple node computer system, new commutative error detection values are created and stored inmore » memory. The node fault detection apparatus identifies faulty nodes by comparing commutative error detection values associated with reproducible portions of the application program generated by a particular node from different runs of the application program. Differences in values indicate a possible faulty node.« less

Neural Detection of Malicious Network Activities Using a New Direct Parsing and Feature Extraction Technique

DTIC Science & Technology

2015-09-01

intrusion detection systems , neural networks 15. NUMBER OF PAGES 75 16. PRICE CODE 17. SECURITY CLASSIFICATION OF... detection system (IDS) software, which learns to detect and classify network attacks and intrusions through prior training data. With the added criteria of...BACKGROUND The growing threat of malicious network activities and intrusion attempts makes intrusion detection systems (IDS) a

Acoustic enhancement for photo detecting devices

DOEpatents

Thundat, Thomas G; Senesac, Lawrence R; Van Neste, Charles W

2013-02-19

Provided are improvements to photo detecting devices and methods for enhancing the sensitivity of photo detecting devices. A photo detecting device generates an electronic signal in response to a received light pulse. An electro-mechanical acoustic resonator, electrically coupled to the photo detecting device, damps the electronic signal and increases the signal noise ratio (SNR) of the electronic signal. Increased photo detector standoff distances and sensitivities will result.

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'.

Novel Application of FTIR Spectroscopy for the Passive Standoff Detection of Radiological Materials

DTIC Science & Technology

2006-08-01

possibility of applying the long-wave passive standoff detection technique to the identification of radiological materials. This work is based on...infrared (FTIR) radiometry is a well-known technique for detecting and identifying chemical warfare agents. In addition to these potential threats...necessary tools and techniques available for detecting and identifying radioactive products. At present, the main detection techniques depend on methods

Acoustic sensors using microstructures tunable with energy other than acoustic energy

DOEpatents

Datskos, Panagiotis G.

2003-11-25

A sensor for detecting acoustic energy includes a microstructure tuned to a predetermined acoustic frequency and a device for detecting movement of the microstructure. A display device is operatively linked to the movement detecting device. When acoustic energy strikes the acoustic sensor, acoustic energy having a predetermined frequency moves the microstructure, where the movement is detected by the movement detecting device.

Acoustic sensors using microstructures tunable with energy other than acoustic energy

DOEpatents

Datskos, Panagiotis G.

2005-06-07

A sensor for detecting acoustic energy includes a microstructure tuned to a predetermined acoustic frequency and a device for detecting movement of the microstructure. A display device is operatively linked to the movement detecting device. When acoustic energy strikes the acoustic sensor, acoustic energy having a predetermined frequency moves the microstructure, where the movement is detected by the movement detecting device.

Submarine Combat Systems Engineering Project Capstone Project

DTIC Science & Technology

2011-06-06

sonar , imaging, Electronic Surveillance (ES) and communications. These sensors passively detect contacts, which emit... passive sensors is included. A Search Detect Identify Track Decide Engage Assess 3 contact can be sensed by the system as either surface or... Detect Track Avoid Search Detect Identify Track Search Engage Assess Detect Track Avoid Search • SONAR •Imagery •TC • SONAR • SONAR •EW •Imagery •ESM

Occurrence of Pesticides in Ground Water of Wyoming, 1995-2006

USGS Publications Warehouse

Bartos, Timothy T.; Eddy-Miller, Cheryl A.; Hallberg, Laura L.

2009-01-01

Little existing information was available describing pesticide occurrence in ground water of Wyoming, so the U.S. Geological Survey, in cooperation with the Wyoming Department of Agriculture and the Wyoming Department of Environmental Quality on behalf of the Wyoming Ground-water and Pesticides Strategy Committee, collected ground-water samples twice (during late summer/early fall and spring) from 296 wells during 1995-2006 to characterize pesticide occurrence. Sampling focused on the State's ground water that was mapped as the most vulnerable to pesticide contamination because of either inherent hydrogeologic sensitivity (for example, shallow water table or highly permeable aquifer materials) or a combination of sensitivity and associated land use. Because of variations in reporting limits among different compounds and for the same compound during this study, pesticide detections were recensored to two different assessment levels to facilitate qualitative and quantitative examination of pesticide detection frequencies - a common assessment level (CAL) of 0.07 microgram per liter and an assessment level that differed by compound, referred to herein as a compound-specific assessment level (CSAL). Because of severe data censoring (fewer than 50 percent of the data are greater than laboratory reporting limits), categorical statistical methods were used exclusively for quantitative comparisons of pesticide detection frequencies between seasons and among various natural and anthropogenic (human-related) characteristics. One or more pesticides were detected at concentrations greater than the CAL in water from about 23 percent of wells sampled in the fall and from about 22 percent of wells sampled in the spring. Mixtures of two or more pesticides occurred at concentrations greater than the CAL in about 9 percent of wells sampled in the fall and in about 10 percent of wells sampled in the spring. At least 74 percent of pesticides detected were classified as herbicides. Considering only detections using the CAL, triazine pesticides were detected much more frequently than all other pesticide classes, and the number of different pesticides classified as triazines was the largest of all classes. More pesticides were detected at concentrations greater than the CSALs in water from wells sampled in the fall (28 different pesticides) than in the spring (21 different pesticides). Many pesticides were detected infrequently as nearly one-half of pesticides detected in the fall and spring at concentrations greater than the CSALs were detected only in one well. Using the CSALs for pesticides analyzed for in 11 or more wells, only five pesticides (atrazine, prometon, tebuthiuron, picloram, and 3,4-dichloroaniline, listed in order of decreasing detection frequency) were each detected in water from more than 5 percent of sampled wells. Atrazine was the pesticide detected most frequently at concentrations greater than the CSAL. Concentrations of detected pesticides generally were small (less than 1 microgram per liter), although many infrequent detections at larger concentrations were noted. All detected pesticide concentrations were smaller than U.S. Environmental Protection Agency (USEPA) drinking-water standards or applicable health advisories. Most concentrations were at least an order of magnitude smaller; however, many pesticides did not have standards or advisories. The largest percentage of pesticide detections and the largest number of different pesticides detected were in samples from wells located in the Bighorn Basin and High Plains/ Casper Arch geographic areas of north-central and southeastern Wyoming. Prometon was the only pesticide detected in all eight geographic areas of the State. Pesticides were detected much more frequently in samples from wells located in predominantly urban areas than in samples from wells located in predominantly agricultural or mixed areas. Pesticides were detected distinctly less often in sa

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Multi-dynamic range compressional wave detection using optical-frequency comb

NASA Astrophysics Data System (ADS)

Minamikawa, Takeo; Masuoka, Takashi; Oe, Ryo; Nakajima, Yoshiaki; Yamaoka, Yoshihisa; Minoshima, Kaoru; Yasui, Takeshi

2018-02-01

Compressional wave detection is useful means for health monitoring of building, detection of abnormal vibration of moving objects, defect evaluation, and biomedical imaging such as echography and photoacoustic imaging. The frequency of the compressional wave is varied from quasi-static to a few tens of megahertz depending on applications. Since the dynamic range of general compressional wave detectors is limited, we need to choose a proper compressional wave detector depending on applications. For the compressional wave detection with wide dynamic range, two or more detectors with different detection ranges is required. However, these detectors with different detection ranges generally has different accuracy and precision, disabling the seamless detection over these detection ranges. In this study, we proposed a compressional wave detector employing optical frequency comb (OFC). The compressional wave was sensed with a part of an OFC cavity, being encoded into OFC. The spectrally encoded OFC was converted to radio-frequency by the frequency link nature of OFC. The compressional wave-encoded radio-frequency can therefore be directly measured with a high-speed photodetector. To enhance the dynamic range of the compressional wave detection, we developed a cavityfeedback-based system and a phase-sensitive detection system, both of which the accuracy and precision are coherently linked to these of the OFC. We provided a proof-of-principle demonstration of the detection of compressional wave from quasi-static to ultrasound wave by using the OFC-based compressional wave sensor. Our proposed approach will serve as a unique and powerful tool for detecting compressional wave versatile applications in the future.

Detection and discrimination of herpes simplex viruses, Haemophilus ducreyi, Treponema pallidum, and Calymmatobacterium (Klebsiella) granulomatis from genital ulcers.

PubMed

Mackay, Ian M; Harnett, Gerry; Jeoffreys, Neisha; Bastian, Ivan; Sriprakash, Kadaba S; Siebert, David; Sloots, Theo P

2006-05-15

Genital ulcer disease (GUD) is commonly caused by pathogens for which suitable therapies exist, but clinical and laboratory diagnoses may be problematic. This collaborative project was undertaken to address the need for a rapid, economical, and sensitive approach to the detection and diagnosis of GUD using noninvasive techniques to sample genital ulcers. The genital ulcer disease multiplex polymerase chain reaction (GUMP) was developed as an inhouse nucleic acid amplification technique targeting serious causes of GUD, namely, herpes simplex viruses (HSVs), H. ducreyi, Treponema pallidum, and Klebsiella species. In addition, the GUMP assay included an endogenous internal control. Amplification products from GUMP were detected by enzyme linked amplicon hybridization assay (ELAHA). GUMP-ELAHA was sensitive and specific in detecting a target microbe in 34.3% of specimens, including 1 detection of HSV-1, three detections of HSV-2, and 18 detections of T. pallidum. No H. ducreyi has been detected in Australia since 1998, and none was detected here. No Calymmatobacterium (Klebsiella) granulomatis was detected in the study, but there were 3 detections during ongoing diagnostic use of GUMP-ELAHA in 2004 and 2005. The presence of C. granulomatis was confirmed by restriction enzyme digestion and nucleotide sequencing of the 16S rRNA gene for phylogenetic analysis. GUMP-ELAHA permitted comprehensive detection of common and rare causes of GUD and incorporated noninvasive sampling techniques. Data obtained by using GUMP-ELAHA will aid specific treatment of GUD and better define the prevalence of each microbe among at-risk populations with a view to the eradication of chancroid and donovanosis in Australia.

Radiation Detection Center on the Front Lines

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

Hazi, A

2005-09-20

Many of today's radiation detection tools were developed in the 1960s. For years, the Laboratory's expertise in radiation detection resided mostly within its nuclear test program. When nuclear testing was halted in the 1990s, many of Livermore's radiation detection experts were dispersed to other parts of the Laboratory, including the directorates of Chemistry and Materials Science (CMS); Physics and Advanced Technologies (PAT); Defense and Nuclear Technologies (DNT); and Nonproliferation, Arms Control, and International Security (NAI). The RDC was formed to maximize the benefit of radiation detection technologies being developed in 15 to 20 research and development (R&D) programs. These effortsmore » involve more than 200 Laboratory employees across eight directorates, in areas that range from electronics to computer simulations. The RDC's primary focus is the detection, identification, and analysis of nuclear materials and weapons. A newly formed outreach program within the RDC is responsible for conducting radiation detection workshops and seminars across the country and for coordinating university student internships. Simon Labov, director of the RDC, says, ''Virtually all of the Laboratory's programs use radiation detection devices in some way. For example, DNT uses radiation detection to create radiographs for their work in stockpile stewardship and in diagnosing explosives; CMS uses it to develop technology for advancing the detection, diagnosis, and treatment of cancer; and the Energy and Environment Directorate uses radiation detection in the Marshall Islands to monitor the aftermath of nuclear testing in the Pacific. In the future, the National Ignition Facility will use radiation detection to probe laser targets and study shock dynamics.''« less

Multiplex Nucleic Acid Sequence-Based Amplification for Simultaneous Detection of Several Enteric Viruses in Model Ready-To-Eat Foods†

PubMed Central

Jean, Julie; D'Souza, Doris H.; Jaykus, Lee-Ann

2004-01-01

Human enteric viruses are currently recognized as one of the most important causes of food-borne disease. Implication of enteric viruses in food-borne outbreaks can be difficult to confirm due to the inadequacy of the detection methods available. In this study, a nucleic acid sequence-based amplification (NASBA) method was developed in a multiplex format for the specific, simultaneous, and rapid detection of epidemiologically relevant human enteric viruses. Three previously reported primer sets were used in a single reaction for the amplification of RNA target fragments of 474, 371, and 165 nucleotides for the detection of hepatitis A virus and genogroup I and genogroup II noroviruses, respectively. Amplicons were detected by agarose gel electrophoresis and confirmed by electrochemiluminescence and Northern hybridization. Endpoint detection sensitivity for the multiplex NASBA assay was approximately 10−1 reverse transcription-PCR-detectable units (or PFU, as appropriate) per reaction. When representative ready-to-eat foods (deli sliced turkey and lettuce) were inoculated with various concentrations of each virus and processed for virus detection with the multiplex NASBA method, all three human enteric viruses were simultaneously detected at initial inoculum levels of 100 to 102 reverse transcription-PCR-detectable units (or PFU)/9 cm2 in both food commodities. The multiplex NASBA system provides rapid and simultaneous detection of clinically relevant food-borne viruses in a single reaction tube and may be a promising alternative to reverse transcription-PCR for the detection of viral contamination of foods. PMID:15528524

The simulation study on optical target laser active detection performance

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

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

Object detection with a multistatic array using singular value decomposition

DOEpatents

Hallquist, Aaron T.; Chambers, David H.

2014-07-01

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across a surface and that travels down the surface. The detection system converts the return signals from a time domain to a frequency domain, resulting in frequency return signals. The detection system then performs a singular value decomposition for each frequency to identify singular values for each frequency. The detection system then detects the presence of a subsurface object based on a comparison of the identified singular values to expected singular values when no subsurface object is present.

Laser-ultrasound spectroscopy apparatus and method with detection of shear resonances for measuring anisotropy, thickness, and other properties

DOEpatents

Levesque, Daniel; Moreau, Andre; Dubois, Marc; Monchalin, Jean-Pierre; Bussiere, Jean; Lord, Martin; Padioleau, Christian

2000-01-01

Apparatus and method for detecting shear resonances includes structure and steps for applying a radiation pulse from a pulsed source of radiation to an object to generate elastic waves therein, optically detecting the elastic waves generated in the object, and analyzing the elastic waves optically detected in the object. These shear resonances, alone or in combination with other information, may be used in the present invention to improve thickness measurement accuracy and to determine geometrical, microstructural, and physical properties of the object. At least one shear resonance in the object is detected with the elastic waves optically detected in the object. Preferably, laser-ultrasound spectroscopy is utilized to detect the shear resonances.

Integrated analysis of error detection and recovery

NASA Technical Reports Server (NTRS)

Shin, K. G.; Lee, Y. H.

1985-01-01

An integrated modeling and analysis of error detection and recovery is presented. When fault latency and/or error latency exist, the system may suffer from multiple faults or error propagations which seriously deteriorate the fault-tolerant capability. Several detection models that enable analysis of the effect of detection mechanisms on the subsequent error handling operations and the overall system reliability were developed. Following detection of the faulty unit and reconfiguration of the system, the contaminated processes or tasks have to be recovered. The strategies of error recovery employed depend on the detection mechanisms and the available redundancy. Several recovery methods including the rollback recovery are considered. The recovery overhead is evaluated as an index of the capabilities of the detection and reconfiguration mechanisms.

Detection technique of targets for missile defense system

NASA Astrophysics Data System (ADS)

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

2009-11-01

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

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

Li, Wenfang; Du, Jinjin; Wen, Ruijuan

We have investigated the transmission spectra of a Fabry-Perot interferometer (FPI) with squeezed vacuum state injection and non-Gaussian detection, including photon number resolving detection and parity detection. In order to show the suitability of the system, parallel studies were made of the performance of two other light sources: coherent state of light and Fock state of light either with classical mean intensity detection or with non-Gaussian detection. This shows that by using the squeezed vacuum state and non-Gaussian detection simultaneously, the resolution of the FPI can go far beyond the cavity standard bandwidth limit based on the current techniques. Themore » sensitivity of the scheme has also been explored and it shows that the minimum detectable sensitivity is better than that of the other schemes.« less

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy. PMID:29485990

An intelligent detection method for high-field asymmetric waveform ion mobility spectrometry.

PubMed

Li, Yue; Yu, Jianwen; Ruan, Zhiming; Chen, Chilai; Chen, Ran; Wang, Han; Liu, Youjiang; Wang, Xiaozhi; Li, Shan

2018-04-01

In conventional high-field asymmetric waveform ion mobility spectrometry signal acquisition, multi-cycle detection is time consuming and limits somewhat the technique's scope for rapid field detection. In this study, a novel intelligent detection approach has been developed in which a threshold was set on the relative error of α parameters, which can eliminate unnecessary time spent on detection. In this method, two full-spectrum scans were made in advance to obtain the estimated compensation voltage at different dispersion voltages, resulting in a narrowing down of the whole scan area to just the peak area(s) of interest. This intelligent detection method can reduce the detection time to 5-10% of that of the original full-spectrum scan in a single cycle.

Rigid particulate matter sensor

DOEpatents

Hall, Matthew [Austin, TX

2011-02-22

A sensor to detect particulate matter. The sensor includes a first rigid tube, a second rigid tube, a detection surface electrode, and a bias surface electrode. The second rigid tube is mounted substantially parallel to the first rigid tube. The detection surface electrode is disposed on an outer surface of the first rigid tube. The detection surface electrode is disposed to face the second rigid tube. The bias surface electrode is disposed on an outer surface of the second rigid tube. The bias surface electrode is disposed to face the detection surface electrode on the first rigid tube. An air gap exists between the detection surface electrode and the bias surface electrode to allow particulate matter within an exhaust stream to flow between the detection and bias surface electrodes.

Combined PET/MRI scanner

DOEpatents

Schlyer, David; Woody, Craig L.; Rooney, William; Vaska, Paul; Stoll, Sean; Pratte, Jean-Francois; O'Connor, Paul

2007-10-23

A combined PET/MRI scanner generally includes a magnet for producing a magnetic field suitable for magnetic resonance imaging, a radiofrequency (RF) coil disposed within the magnetic field produced by the magnet and a ring tomograph disposed within the magnetic field produced by the magnet. The ring tomograph includes a scintillator layer for outputting at least one photon in response to an annihilation event, a detection array coupled to the scintillator layer for detecting the at least one photon outputted by the scintillator layer and for outputting a detection signal in response to the detected photon and a front-end electronic array coupled to the detection array for receiving the detection signal, wherein the front-end array has a preamplifier and a shaper network for conditioning the detection signal.

Co-detection: ultra-reliable nanoparticle-based electrical detection of biomolecules in the presence of large background interference.

PubMed

Liu, Yang; Gu, Ming; Alocilja, Evangelyn C; Chakrabartty, Shantanu

2010-11-15

An ultra-reliable technique for detecting trace quantities of biomolecules is reported. The technique called "co-detection" exploits the non-linear redundancy amongst synthetically patterned biomolecular logic circuits for deciphering the presence or absence of target biomolecules in a sample. In this paper, we verify the "co-detection" principle on gold-nanoparticle-based conductimetric soft-logic circuits which use a silver-enhancement technique for signal amplification. Using co-detection, we have been able to demonstrate a great improvement in the reliability of detecting mouse IgG at concentration levels that are 10(5) lower than the concentration of rabbit IgG which serves as background interference. Copyright © 2010 Elsevier B.V. All rights reserved.

Diode laser detection of greenhouse gases in the near-infrared region by wavelength modulation spectroscopy: pressure dependence of the detection sensitivity.

PubMed

Asakawa, Takashi; Kanno, Nozomu; Tonokura, Kenichi

2010-01-01

We have investigated the pressure dependence of the detection sensitivity of CO(2), N(2)O and CH(4) using wavelength modulation spectroscopy (WMS) with distributed feed-back diode lasers in the near infrared region. The spectral line shapes and the background noise of the second harmonics (2f) detection of the WMS were analyzed theoretically. We determined the optimum pressure conditions in the detection of CO(2), N(2)O and CH(4), by taking into consideration the background noise in the WMS. At the optimum total pressure for the detection of CO(2), N(2)O and CH(4), the limits of detection in the present system were determined.

Salient object detection method based on multiple semantic features

NASA Astrophysics Data System (ADS)

Wang, Chunyang; Yu, Chunyan; Song, Meiping; Wang, Yulei

2018-04-01

The existing salient object detection model can only detect the approximate location of salient object, or highlight the background, to resolve the above problem, a salient object detection method was proposed based on image semantic features. First of all, three novel salient features were presented in this paper, including object edge density feature (EF), object semantic feature based on the convex hull (CF) and object lightness contrast feature (LF). Secondly, the multiple salient features were trained with random detection windows. Thirdly, Naive Bayesian model was used for combine these features for salient detection. The results on public datasets showed that our method performed well, the location of salient object can be fixed and the salient object can be accurately detected and marked by the specific window.

Topological anomaly detection performance with multispectral polarimetric imagery

NASA Astrophysics Data System (ADS)

Gartley, M. G.; Basener, W.,

2009-05-01

Polarimetric imaging has demonstrated utility for increasing contrast of manmade targets above natural background clutter. Manual detection of manmade targets in multispectral polarimetric imagery can be challenging and a subjective process for large datasets. Analyst exploitation may be improved utilizing conventional anomaly detection algorithms such as RX. In this paper we examine the performance of a relatively new approach to anomaly detection, which leverages topology theory, applied to spectral polarimetric imagery. Detection results for manmade targets embedded in a complex natural background will be presented for both the RX and Topological Anomaly Detection (TAD) approaches. We will also present detailed results examining detection sensitivities relative to: (1) the number of spectral bands, (2) utilization of Stoke's images versus intensity images, and (3) airborne versus spaceborne measurements.

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... provided a smoke detecting or other suitable type fire detecting system. (c) Enclosed spaces which are “specially suitable for vehicles” shall be fitted with an approved fire or smoke detecting system. [CGFR 66...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... provided a smoke detecting or other suitable type fire detecting system. (c) Enclosed spaces which are “specially suitable for vehicles” shall be fitted with an approved fire or smoke detecting system. [CGFR 66...

Predicting species distributions from checklist data using site-occupancy models

USGS Publications Warehouse

Kery, M.; Gardner, B.; Monnerat, C.

2010-01-01

Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site-occupancy models applied to replicated detection/non-detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of 'cheap' checklist data greatly enhances the scope of applications of this useful class of models. ?? 2010 Blackwell Publishing Ltd.

Interferometric biosensing platform for multiplexed digital detection of viral pathogens and biomarkers

NASA Astrophysics Data System (ADS)

Daaboul, George

Label-free optical biosensors have been established as proven tools for monitoring specific biomolecular interactions. However, compact and robust embodiments of such instruments have yet to be introduced in order to provide sensitive, quantitative, and high-throughput biosensing for low-cost research and clinical applications. Here we present the interferometric reflectance-imaging sensor (IRIS). IRIS allows sensitive label free analysis using an inexpensive and durable multi-color LED illumination source on a silicon based surface. IRIS monitors biomolecular interaction through measurement of biomass addition to the sensor's surface. We demonstrate the capability of this system to dynamically monitor antigen---antibody interactions with a noise floor of 5.2 pg/mm 2 and DNA single mismatch detection under isothermal melting conditions in an array format. Ensemble detection of binding events using IRIS did not provide the sensitivity needed for detection of infectious disease and biomarkers at clinically relevant concentrations. Therefore, a new approach was adapted to the IRIS platform that allowed the detection and identification of individual nanoparticles on the sensor's surface. The new detection method was termed single-particle IRIS (SP-IRIS). We developed two detection modalities for SP-IRIS. The first modality is when the target is a nanoparticle such as a virus. We verified that SP-IRIS can accurately detect and size individual viral particles. Then we demonstrated that single nanoparticle counting and sizing methodology on SP-IRIS leads to a specific and sensitive virus sensor that can be multiplexed. Finally, we developed an assay for the detection of Ebola and Marburg. A detection limit of 3 x 103 PFU/ml was demonstrated for vesicular stomatitis virus (VSV) pseudotyped with Ebola or Marburg virus glycoprotein. We have demonstrated that virus detection can be done in human whole blood directly without the need for sample preparation. The second modality of SP-IRIS we developed was single molecule counting of biomarkers utilizing a sandwich assay with detection probes labeled with gold nanoparticles. We demonstrated the use of single molecule counting in a nucleic acid assay for melanoma biomarker detection. We showed that a single molecule counting assay can lead to detection limits in the attomolar range. The improved sensitivity of IRIS utilizing single nanoparticle detection holds promise for a simple and low-cost technology for rapid virus detection and multiplexed molecular screening for clinical applications.

Bayesian analysis of energy and count rate data for detection of low count rate radioactive sources.

PubMed

Klumpp, John; Brandl, Alexander

2015-03-01

A particle counting and detection system is proposed that searches for elevated count rates in multiple energy regions simultaneously. The system analyzes time-interval data (e.g., time between counts), as this was shown to be a more sensitive technique for detecting low count rate sources compared to analyzing counts per unit interval (Luo et al. 2013). Two distinct versions of the detection system are developed. The first is intended for situations in which the sample is fixed and can be measured for an unlimited amount of time. The second version is intended to detect sources that are physically moving relative to the detector, such as a truck moving past a fixed roadside detector or a waste storage facility under an airplane. In both cases, the detection system is expected to be active indefinitely; i.e., it is an online detection system. Both versions of the multi-energy detection systems are compared to their respective gross count rate detection systems in terms of Type I and Type II error rates and sensitivity.

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

NASA Astrophysics Data System (ADS)

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

1999-02-01

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

Minimum detectable gas concentration performance evaluation method for gas leak infrared imaging detection systems.

PubMed

Zhang, Xu; Jin, Weiqi; Li, Jiakun; Wang, Xia; Li, Shuo

2017-04-01

Thermal imaging technology is an effective means of detecting hazardous gas leaks. Much attention has been paid to evaluation of the performance of gas leak infrared imaging detection systems due to several potential applications. The minimum resolvable temperature difference (MRTD) and the minimum detectable temperature difference (MDTD) are commonly used as the main indicators of thermal imaging system performance. This paper establishes a minimum detectable gas concentration (MDGC) performance evaluation model based on the definition and derivation of MDTD. We proposed the direct calculation and equivalent calculation method of MDGC based on the MDTD measurement system. We build an experimental MDGC measurement system, which indicates the MDGC model can describe the detection performance of a thermal imaging system to typical gases. The direct calculation, equivalent calculation, and direct measurement results are consistent. The MDGC and the minimum resolvable gas concentration (MRGC) model can effectively describe the performance of "detection" and "spatial detail resolution" of thermal imaging systems to gas leak, respectively, and constitute the main performance indicators of gas leak detection systems.

Lining seam elimination algorithm and surface crack detection in concrete tunnel lining

NASA Astrophysics Data System (ADS)

Qu, Zhong; Bai, Ling; An, Shi-Quan; Ju, Fang-Rong; Liu, Ling

2016-11-01

Due to the particularity of the surface of concrete tunnel lining and the diversity of detection environments such as uneven illumination, smudges, localized rock falls, water leakage, and the inherent seams of the lining structure, existing crack detection algorithms cannot detect real cracks accurately. This paper proposed an algorithm that combines lining seam elimination with the improved percolation detection algorithm based on grid cell analysis for surface crack detection in concrete tunnel lining. First, check the characteristics of pixels within the overlapping grid to remove the background noise and generate the percolation seed map (PSM). Second, cracks are detected based on the PSM by the accelerated percolation algorithm so that the fracture unit areas can be scanned and connected. Finally, the real surface cracks in concrete tunnel lining can be obtained by removing the lining seam and performing percolation denoising. Experimental results show that the proposed algorithm can accurately, quickly, and effectively detect the real surface cracks. Furthermore, it can fill the gap in the existing concrete tunnel lining surface crack detection by removing the lining seam.

Standoff chemical D and Id with extended LWIR hyperspectral imaging spectroradiometer

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Thériault, Jean-Marc; Vallieres, Christian; Roy, Claude; Dubé, Denis

2013-05-01

Standoff detection and identification (D and Id) of unknown volatile chemicals such as chemical pollutants and consequences of industrial incidents has been increasingly desired for first responders and for environmental monitoring. On site gas detection sensors are commercially available and several of them can even detect more than one chemical species, however only few of them have the capabilities of detecting a wide variety of gases at long and safe distances. The ABB Hyperspectral Imaging Spectroradiometer (MR-i), configured for gas detection detects and identifies a wide variety of chemical species including toxic industrial chemicals (TICs) and surrogates several kilometers away from the sensor. This configuration is called iCATSI for improved Compact Atmospheric Sounding Interferometer. iCATSI is a standoff passive system. The modularity of the MR-i platform allows optimization of the detection configuration with a 256 x 256 Focal Plane Array imager or a line scanning imager both covering the long wave IR atmospheric window up to 14 μm. The uniqueness of its extended LWIR cut off enables to detect more chemicals as well as provide higher probability of detection than usual LWIR sensors.

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

First Detected Arrival of a Quantum Walker on an Infinite Line

NASA Astrophysics Data System (ADS)

Thiel, Felix; Barkai, Eli; Kessler, David A.

2018-01-01

The first detection of a quantum particle on a graph is shown to depend sensitively on the distance ξ between the detector and initial location of the particle, and on the sampling time τ . Here, we use the recently introduced quantum renewal equation to investigate the statistics of first detection on an infinite line, using a tight-binding lattice Hamiltonian with nearest-neighbor hops. Universal features of the first detection probability are uncovered and simple limiting cases are analyzed. These include the large ξ limit, the small τ limit, and the power law decay with the attempt number of the detection probability over which quantum oscillations are superimposed. For large ξ the first detection probability assumes a scaling form and when the sampling time is equal to the inverse of the energy band width nonanalytical behaviors arise, accompanied by a transition in the statistics. The maximum total detection probability is found to occur for τ close to this transition point. When the initial location of the particle is far from the detection node we find that the total detection probability attains a finite value that is distance independent.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

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

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

2001-09-01

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

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%.

A Novel Technique to Detect Code for SAC-OCDMA System

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group.

PubMed

Buehler, James W; Hopkins, Richard S; Overhage, J Marc; Sosin, Daniel M; Tong, Van

2004-05-07

The threat of terrorism and high-profile disease outbreaks has drawn attention to public health surveillance systems for early detection of outbreaks. State and local health departments are enhancing existing surveillance systems and developing new systems to better detect outbreaks through public health surveillance. However, information is limited about the usefulness of surveillance systems for outbreak detection or the best ways to support this function. This report supplements previous guidelines for evaluating public health surveillance systems. Use of this framework is intended to improve decision-making regarding the implementation of surveillance for outbreak detection. Use of a standardized evaluation methodology, including description of system design and operation, also will enhance the exchange of information regarding methods to improve early detection of outbreaks. The framework directs particular attention to the measurement of timeliness and validity for outbreak detection. The evaluation framework is designed to support assessment and description of all surveillance approaches to early detection, whether through traditional disease reporting, specialized analytic routines for aberration detection, or surveillance using early indicators of disease outbreaks, such as syndromic surveillance.

Evaluation of the efficacy of a portable LIBS system for detection of CWA on surfaces.

PubMed

L'Hermite, D; Vors, E; Vercouter, T; Moutiers, G

2016-05-01

Laser-induced breakdown spectroscopy (LIBS) is a laser-based optical technique particularly suited for in situ surface analysis. A portable LIBS instrument was tested to detect surface chemical contamination by chemical warfare agents (CWAs). Test of detection of surface contamination was carried out in a toxlab facility with four CWAs, sarin (GB), lewisite (L1), mustard gas (HD), and VX, which were deposited on different substrates, wood, concrete, military green paint, gloves, and ceramic. The CWAs were detected by means of the detection of atomic markers (As, P, F, Cl, and S). The LIBS instrument can give a direct response in terms of detection thanks to an integrated interface for non-expert users or so called end-users. We have evaluated the capability of automatic detection of the selected CWAs. The sensitivity of our portable LIBS instrument was confirmed for the detection of a CWA at surface concentrations above 15 μg/cm(2). The simultaneous detection of two markers may lead to a decrease of the number of false positive.

Robust automatic line scratch detection in films.

PubMed

Newson, Alasdair; Almansa, Andrés; Gousseau, Yann; Pérez, Patrick

2014-03-01

Line scratch detection in old films is a particularly challenging problem due to the variable spatiotemporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This step's robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture, and slanted or partial scratches. Comparisons show significant advantages over previous work.

Numerical study on the sequential Bayesian approach for radioactive materials detection

NASA Astrophysics Data System (ADS)

Qingpei, Xiang; Dongfeng, Tian; Jianyu, Zhu; Fanhua, Hao; Ge, Ding; Jun, Zeng

2013-01-01

A new detection method, based on the sequential Bayesian approach proposed by Candy et al., offers new horizons for the research of radioactive detection. Compared with the commonly adopted detection methods incorporated with statistical theory, the sequential Bayesian approach offers the advantages of shorter verification time during the analysis of spectra that contain low total counts, especially in complex radionuclide components. In this paper, a simulation experiment platform implanted with the methodology of sequential Bayesian approach was developed. Events sequences of γ-rays associating with the true parameters of a LaBr3(Ce) detector were obtained based on an events sequence generator using Monte Carlo sampling theory to study the performance of the sequential Bayesian approach. The numerical experimental results are in accordance with those of Candy. Moreover, the relationship between the detection model and the event generator, respectively represented by the expected detection rate (Am) and the tested detection rate (Gm) parameters, is investigated. To achieve an optimal performance for this processor, the interval of the tested detection rate as a function of the expected detection rate is also presented.

Development of an immunochromatographic test with anti-LipL32-coupled gold nanoparticles for Leptospira detection.

PubMed

Chirathaworn, Chintana; Janwitthayanan, Weena; Sereemaspun, Amornpun; Lertpocasombat, Kanchalee; Rungpanich, Utane; Ekpo, Pattama; Suwancharoen, Duangjai

2014-04-01

Detection of antibody specific to Leptospira by various immunological techniques has been used for leptospirosis diagnosis. However, the sensitivity of antibody detection during the first few days after infection is low. Molecular techniques are suggested to provide earlier diagnosis than antibody detection, but a rapid and easy to perform assay for Leptospira antigen detection would provide an additional useful tool for disease diagnosis. In this study, we coupled gold nanoparticles with antibody to LipL32, a protein commonly found in pathogenic Leptospira. This coupled gold reagent was used in the immunochromatographic strip for Leptospira detection. We demonstrated that the sensitivity of Leptospira detection by this strip was 10(3) ml(-1). There was no positive result detected when strips were tested with non-pathogenic Leptospira, Staphylococcus aureus, Streptococcus group B, Acinetobacter baumannii, Escherichia coli, Salmonella typhi, Klebsiella pneumoniae, Enterococcus faecalis or Enterococcus faecium. These data suggest that gold nanoparticles coupled with antibody to LipL32 could be used for Leptospira detection by a rapid test based on an immunochromatographic technique.

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

PubMed

Luo, Xiaoteng; Hsing, I-Ming

2009-10-01

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

Pesticide concentrations in wetlands on the Lake Traverse Indian Reservation, South and North Dakota, July 2015

USGS Publications Warehouse

Carter, Janet M.; Thompson, Ryan F.

2016-05-04

During July 2015, water samples were collected from 18 wetlands on the Lake Traverse Indian Reservation in northeastern South Dakota and southeastern North Dakota and analyzed for physical properties and 54 pesticides. This study by the U.S. Geological Survey in cooperation with the Sisseton-Wahpeton Oyate was designed to provide an update on pesticide concentrations of the same 18 wetlands that were sampled for a reconnaissance-level assessment during July 2006. The purpose of this report is to present the results of the assessment of pesticide concentrations in selected Lake Traverse Indian Reservation wetlands during July 2015 and provide a comparison of pesticide concentrations between 2006 and 2015.Of the 54 pesticides that were analyzed for in the samples collected during July 2015, 47 pesticides were not detected in any samples. Seven pesticides—2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT); 2,4–D; acetachlor; atrazine; glyphosate; metolachlor; and prometon—were detected in the 2015 samples with estimated concentrations or concentrations greater than the laboratory reporting level, and most pesticides were detected at low concentrations in only a few samples. Samples from all wetlands contained at least one detected pesticide. The maximum number of pesticides detected in a wetland sample was six, and the median number of pesticides detected was three.The most commonly detected pesticides in the 2015 samples were atrazine and the atrazine degradate CIAT (also known as deethylatrazine), which were detected in 14 and 13 of the wetlands sampled, respectively. Glyphosate was detected in samples from 11 wetlands, and metolachlor was detected in samples from 10 wetlands. The other detected pesticides were 2,4–D (4 wetlands), acetochlor (3 wetlands), and prometon (1 wetland).The same pesticides that were detected in the 2006 samples were detected in the 2015 samples, with the exception of simazine, which was detected only in one sample in 2006. Atrazine and CIAT were the most commonly detected pesticides in both sampling years; however, atrazine and CIAT were detected in fewer wetlands in 2015 (14 and 13 wetlands, respectively) than in 2006 (17 wetlands for both pesticides). The pesticides 2,4–D and prometon also were detected in fewer wetlands in 2015 than 2006, and simazine was only detected in 2006. In contrast, acetochlor, glyphosate, and metolachlor were detected in samples from more wetlands in 2015 than in 2006. In samples from individual wetlands, the number of pesticides detected was similar between 2006 and 2015. At least one pesticide was detected in all wetlands in 2015, and all but one wetland had pesticide detections in 2006.Concentrations of pesticides detected in samples from wetlands were compared to selected water-quality (human-health and aquatic-life) benchmarks. None of the concentrations in either 2006 or 2015 were greater than water-quality benchmarks, with the exception of atrazine. All detections of atrazine in the 2006 and 2015 samples were greater than the acute benchmark of 0.001 microgram per liter (μg/L) for vascular plants. In addition, some concentrations of 2,4–D and atrazine were within an order of magnitude of a water-quality benchmark. The 2,4–D concentrations in the 2015 samples from three wetlands were within an order of magnitude of the U.S. Environmental Protection Agency’s Maximum Contaminant Level of 70 μg/L (that is, sample concentrations were greater than 7.0 μg/L). The maximum dissolved atrazine concentration of 0.185 μg/L in the 2015 samples along with the concentrations in 2006 samples from two wetlands were within an order of magnitude of the acute benchmark of less than 1 μg/L for nonvascular plants (that is, concentrations were greater than 0.1 μg/L).

USGS Tweet Earthquake Dispatch (@USGSted): Using Twitter for Earthquake Detection and Characterization

NASA Astrophysics Data System (ADS)

Liu, S. B.; Bouchard, B.; Bowden, D. C.; Guy, M.; Earle, P.

2012-12-01

The U.S. Geological Survey (USGS) is investigating how online social networking services like Twitter—a microblogging service for sending and reading public text-based messages of up to 140 characters—can augment USGS earthquake response products and the delivery of hazard information. The USGS Tweet Earthquake Dispatch (TED) system is using Twitter not only to broadcast seismically-verified earthquake alerts via the @USGSted and @USGSbigquakes Twitter accounts, but also to rapidly detect widely felt seismic events through a real-time detection system. The detector algorithm scans for significant increases in tweets containing the word "earthquake" or its equivalent in other languages and sends internal alerts with the detection time, tweet text, and the location of the city where most of the tweets originated. It has been running in real-time for 7 months and finds, on average, two or three felt events per day with a false detection rate of less than 10%. The detections have reasonable coverage of populated areas globally. The number of detections is small compared to the number of earthquakes detected seismically, and only a rough location and qualitative assessment of shaking can be determined based on Tweet data alone. However, the Twitter detections are generally caused by widely felt events that are of more immediate interest than those with no human impact. The main benefit of the tweet-based detections is speed, with most detections occurring between 19 seconds and 2 minutes from the origin time. This is considerably faster than seismic detections in poorly instrumented regions of the world. Going beyond the initial detection, the USGS is developing data mining techniques to continuously archive and analyze relevant tweets for additional details about the detected events. The information generated about an event is displayed on a web-based map designed using HTML5 for the mobile environment, which can be valuable when the user is not able to access a desktop computer at the time of the detections. The continuously updating map displays geolocated tweets arriving after the detection and plots epicenters of recent earthquakes. When available, seismograms from nearby stations are displayed as an additional form of verification. A time series of tweets-per-minute is also shown to illustrate the volume of tweets being generated for the detected event. Future additions are being investigated to provide a more in-depth characterization of the seismic events based on an analysis of tweet text and content from other social media sources.

Distribution System Audits, Leak Detection, and Repair: Kirtland Air Force Base Leak Detection and Repair Program

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

None

Water Best Management Practice #3 Fact Seet: Outlines how a leak detection and repair program helped Kirtland Air Force Base perform distribution system audits, leak detection, and repair to conserve water site-wide.

Thermal background noise limitations

NASA Technical Reports Server (NTRS)

Gulkis, S.

1982-01-01

Modern detection systems are increasingly limited in sensitivity by the background thermal photons which enter the receiving system. Expressions for the fluctuations of detected thermal radiation are derived. Incoherent and heterodyne detection processes are considered. References to the subject of photon detection statistics are given.

Methods of detection and identificationoc carbon- and nitrogen-containing materials

DOEpatents

Karev, Alexander Ivanovich; Raevsky, Valery Georgievich; Dzhalivyan, Leonid Zavenovich; Brothers, Louis Joseph; Wilhide, Larry K

2013-11-12

Methods for detecting and identifying carbon- and/or nitrogen-containing materials are disclosed. The methods may comprise detection of photo-nuclear reaction products of nitrogen and carbon to detect and identify the carbon- and/or nitrogen-containing materials.

Getting a Grip on Social Gaze: Control over Others' Gaze Helps Gaze Detection in High-Functioning Autism

ERIC Educational Resources Information Center

Dratsch, Thomas; Schwartz, Caroline; Yanev, Kliment; Schilbach, Leonhard; Vogeley, Kai; Bente, Gary

2013-01-01

We investigated the influence of control over a social stimulus on the ability to detect direct gaze in high-functioning autism (HFA). In a pilot study, 19 participants with and 19 without HFA were compared on a gaze detection and a gaze setting task. Participants with HFA were less accurate in detecting direct gaze in the detection task, but did…

40 CFR Appendix B to Part 136 - Definition and Procedure for the Determination of the Method Detection Limit-Revision 1.11

Code of Federal Regulations, 2010 CFR

2010-07-01

... calculated method detection limit. To insure that the estimate of the method detection limit is a good...) where: MDL = the method detection limit t(n-1,1- α=.99) = the students' t value appropriate for a 99... Determination of the Method Detection Limit-Revision 1.11 B Appendix B to Part 136 Protection of Environment...

A Technology Analysis to Support Acquisition of UAVs for Gulf Coalition Forces Operations

DTIC Science & Technology

2017-06-01

their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non ...being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and...aerial vehicles to support detection operations. We use Map Aware Non - Uniform Automata, an agent-based simulation software platform, for the

The April 2009 Gulf of Alaska Line-Transect Survey (Goals) in the Navy Training Exercise Area

DTIC Science & Technology

2009-10-01

acoustic detections and localizations of sperm whales in comparison with previous surveys, there were not enough positive range ... Acoustic effort and detections during GOALS 2009 research cruise (red = killer whale , blue = sperm whale ). 15    Table 4 – Acoustic Detections ... detections of baleen whales . While a loss of this component prevented potential acoustic detections of some rare species like

Joint Sensing/Sampling Optimization for Surface Drifting Mine Detection with High-Resolution Drift Model

DTIC Science & Technology

2012-09-01

as potential tools for large area detection coverage while being moderately inexpensive (Wettergren, Performance of Search via Track - Before - Detect for...via Track - Before - Detect for Distribute 34 Sensor Networks, 2008). These statements highlight three specific needs to further sensor network research...Bay hydrography. Journal of Marine Systems, 12, 221–236. Wettergren, T. A. (2008). Performance of search via track - before - detect for distributed

Grand Challenges Emerging Perspectives For Embedded Processing (BRIEFING CHARTS)

DTIC Science & Technology

2007-03-06

track before detect Small... Track - before - detect (dim targets) Change detection 16Mpixel 2 Hz 1 km2 1 ft res. STAPBOY Φ1 60W .3k$ AMD server 120 W ~.8k...60 X (m) Y ( m ) −50 0 50 −60 −40 −20 0 20 40 60 X (m) Y ( m ) EO/IR Track - before - detect (dim targets) Change detection RISC/DSP AMD

Performance Analysis of a Link-16/JTIDS Compatible Waveform With Noncoherent Detection, Diversity and Side Information

DTIC Science & Technology

2009-09-01

OF A LINK-16/JTIDS COMPATIBLE WAVEFORM WITH NONCOHERENT DETECTION, DIVERSITY AND SIDE INFORMATION by Ioannis Kagioglidis September 2009... Noncoherent Detection, Diversity and Side Information. 6. AUTHOR Ioannis Kagioglidis 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES...baseband waveforms and detected noncoherently . For noncoherent detection, only one five bit symbol is transmitted on both the I and Q components of

A probe-based quantitative PCR assay for detecting Tetracapsuloides bryosalmonae in fish tissue and environmental DNA water samples

USGS Publications Warehouse

Hutchins, Patrick; Sepulveda, Adam; Martin, Renee; Hopper, Lacey

2017-01-01

A probe-based quantitative real-time PCR assay was developed to detect Tetracapsuloides bryosalmonae, which causes proliferative kidney disease in salmonid fish, in kidney tissue and environmental DNA (eDNA) water samples. The limits of detection and quantification were 7 and 100 DNA copies for calibration standards and T. bryosalmonae was reliably detected down to 100 copies in tissue and eDNA samples. The assay presented here is a highly sensitive and quantitative tool for detecting T. bryosalmonae with potential applications for tissue diagnostics and environmental detection.

Life expectancy and the value of early detection.

PubMed

Howard, David H

2005-09-01

This paper presents a model of the benefits and costs of early detection of asymptomatic disease as they vary by age. The benefits of early detection tend toward zero as the risk of death from competing causes increases. Costs per detected case also decline with age, assuming that disease incidence rises with age, but are always strictly positive. On balance, there is always an age limit beyond which the costs associated with early detection outweigh the benefits. Application of the model to prostate cancer screening suggests that early detection above age 70 or so is not cost-effective.

Optical Production and Detection of Ultrasonic Waves in Metals for Nondestructive Testing

NASA Technical Reports Server (NTRS)

Morrison, R. A.

1972-01-01

Ultrasonic waves were produced by striking the surface of a metal with the focused one-joule pulse of a Q-switched ruby laser. Rayleigh (surface) waves and longitudinal waves were detected with conventional transducers. Optical methods of detection were tested and developed. Rayleigh waves were produced with an oscillator and transducer. They were optically detected on curved polished surfaces, and on unpolished surfaces. The technique uses a knife edge to detect small angle changes of the surface as the wave pulse passes the illuminated spot. Optical flaw detection using pulse echo and attenuation is demonstrated.

Comparing CNV detection methods for SNP arrays.

PubMed

Winchester, Laura; Yau, Christopher; Ragoussis, Jiannis

2009-09-01

Data from whole genome association studies can now be used for dual purposes, genotyping and copy number detection. In this review we discuss some of the methods for using SNP data to detect copy number events. We examine a number of algorithms designed to detect copy number changes through the use of signal-intensity data and consider methods to evaluate the changes found. We describe the use of several statistical models in copy number detection in germline samples. We also present a comparison of data using these methods to assess accuracy of prediction and detection of changes in copy number.

Leak detection by mass balance effective for Norman Wells line

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

Liou, J.C.P.

Mass-balance calculations for leak detection have been shown as effective as a leading software system, in a comparison based on a major Canadian crude-oil pipeline. The calculations and NovaCorp`s Leakstop software each detected 4% (approximately) or greater leaks on Interprovincial Pipe Line (IPL) Inc.`s Norman Wells pipeline. Insufficient data exist to assess performances of the two methods for leaks smaller than 4%. Pipeline leak detection using such software-based systems are common. Their effectiveness is measured by how small and how quickly a leak can be detected. Algorithms used and measurement uncertainties determine leak detectability.

Chemical analysis kit for the presence of explosives

DOEpatents

Eckels, Joel Del [Livermore, CA; Nunes,; Peter, J [Danville, CA; Alcaraz, Armando [Livermore, CA; Whipple, Richard E [Livermore, CA

2011-05-10

A tester for testing for explosives associated with a test location comprising a first explosives detecting reagent; a first reagent holder, the first reagent holder containing the first explosives detecting reagent; a second explosives detecting reagent; a second reagent holder, the second reagent holder containing the second explosives detecting reagent; a sample collection unit for exposure to the test location, exposure to the first explosives detecting reagent, and exposure to the second explosives detecting reagent; and a body unit containing a heater for heating the sample collection unit for testing the test location for the explosives.

Remote detection of single emitters via optical waveguides

NASA Astrophysics Data System (ADS)

Then, Patrick; Razinskas, Gary; Feichtner, Thorsten; Haas, Philippe; Wild, Andreas; Bellini, Nicola; Osellame, Roberto; Cerullo, Giulio; Hecht, Bert

2014-05-01

The integration of lab-on-a-chip technologies with single-molecule detection techniques may enable new applications in analytical chemistry, biotechnology, and medicine. We describe a method based on the reciprocity theorem of electromagnetic theory to determine and optimize the detection efficiency of photons emitted by single quantum emitters through truncated dielectric waveguides of arbitrary shape positioned in their proximity. We demonstrate experimentally that detection of single quantum emitters via such waveguides is possible, confirming the predicted behavior of the detection efficiency. Our findings blaze the trail towards efficient lensless single-emitter detection compatible with large-scale optofluidic integration.

Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-06-17

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as "our previous method") using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as "our new method"). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal.

Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

PubMed Central

Rodríguez-Canosa, Gonzalo; Giner, Jaime del Cerro; Barrientos, Antonio

2014-01-01

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. PMID:24526305

Computerized scheme for vertebra detection in CT scout image

NASA Astrophysics Data System (ADS)

Guo, Wei; Chen, Qiang; Zhou, Hanxun; Zhang, Guodong; Cong, Lin; Li, Qiang

2016-03-01

Our purposes are to develop a vertebra detection scheme for automated scan planning, which would assist radiological technologists in their routine work for the imaging of vertebrae. Because the orientations of vertebrae were various, and the Haar-like features were only employed to represent the subject on the vertical, horizontal, or diagonal directions, we rotated the CT scout image seven times to make the vertebrae roughly horizontal in least one of the rotated images. Then, we employed Adaboost learning algorithm to construct a strong classifier for the vertebra detection by use of Haar-like features, and combined the detection results with the overlapping region according to the number of times they were detected. Finally, most of the false positives were removed by use of the contextual relationship between them. The detection scheme was evaluated on a database with 76 CT scout image. Our detection scheme reported 1.65 false positives per image at a sensitivity of 94.3% for initial detection of vertebral candidates, and then the performance of detection was improved to 0.95 false positives per image at a sensitivity of 98.6% for the further steps of false positive reduction. The proposed scheme achieved a high performance for the detection of vertebrae with different orientations.

Real-Time Event Detection for Monitoring Natural and Source ...

EPA Pesticide Factsheets

The use of event detection systems in finished drinking water systems is increasing in order to monitor water quality in both operational and security contexts. Recent incidents involving harmful algal blooms and chemical spills into watersheds have increased interest in monitoring source water quality prior to treatment. This work highlights the use of the CANARY event detection software in detecting suspected illicit events in an actively monitored watershed in South Carolina. CANARY is an open source event detection software that was developed by USEPA and Sandia National Laboratories. The software works with any type of sensor, utilizes multiple detection algorithms and approaches, and can incorporate operational information as needed. Monitoring has been underway for several years to detect events related to intentional or unintentional dumping of materials into the monitored watershed. This work evaluates the feasibility of using CANARY to enhance the detection of events in this watershed. This presentation will describe the real-time monitoring approach used in this watershed, the selection of CANARY configuration parameters that optimize detection for this watershed and monitoring application, and the performance of CANARY during the time frame analyzed. Further, this work will highlight how rainfall events impacted analysis, and the innovative application of CANARY taken in order to effectively detect the suspected illicit events. This presentation d

The feasibility test of state-of-the-art face detection algorithms for vehicle occupant detection

NASA Astrophysics Data System (ADS)

Makrushin, Andrey; Dittmann, Jana; Vielhauer, Claus; Langnickel, Mirko; Kraetzer, Christian

2010-01-01

Vehicle seat occupancy detection systems are designed to prevent the deployment of airbags at unoccupied seats, thus avoiding the considerable cost imposed by the replacement of airbags. Occupancy detection can also improve passenger comfort, e.g. by activating air-conditioning systems. The most promising development perspectives are seen in optical sensing systems which have become cheaper and smaller in recent years. The most plausible way to check the seat occupancy by occupants is the detection of presence and location of heads, or more precisely, faces. This paper compares the detection performances of the three most commonly used and widely available face detection algorithms: Viola- Jones, Kienzle et al. and Nilsson et al. The main objective of this work is to identify whether one of these systems is suitable for use in a vehicle environment with variable and mostly non-uniform illumination conditions, and whether any one face detection system can be sufficient for seat occupancy detection. The evaluation of detection performance is based on a large database comprising 53,928 video frames containing proprietary data collected from 39 persons of both sexes and different ages and body height as well as different objects such as bags and rearward/forward facing child restraint systems.

Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

PubMed

Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

2016-12-01

In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving average (EWMA) monitoring scheme to detect a potential fall in the accelerometric data. We used an EWMA to identify features that correspond with a particular type of fall allowing us to classify falls. Only features corresponding with detected falls were used in the classification phase. A benefit of using a subset of the original data to design classification models minimizes training time and simplifies models. Based on features corresponding to detected falls, we used the support vector machine (SVM) algorithm to distinguish between true falls and fall-like events. We apply this strategy to the publicly available fall detection databases from the university of Rzeszow's. Results indicated that our strategy accurately detected and classified fall events, suggesting its potential application to early alert mechanisms in the event of fall situations and its capability for classification of detected falls. Comparison of the classification results using the EWMA-based SVM classifier method with those achieved using three commonly used machine learning classifiers, neural network, K-nearest neighbor and naïve Bayes, proved our model superior.

Distinct frontal and amygdala correlates of change detection for facial identity and expression

PubMed Central

Achaibou, Amal; Loth, Eva

2016-01-01

Recruitment of ‘top-down’ frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in ‘bottom-up’ attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate ‘hit’ from ‘miss’ trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience. PMID:26245835

New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull's eye focus detection with an improved target system: opto-mechanical design and operation

NASA Astrophysics Data System (ADS)

Irsch, Kristina; Gramatikov, Boris I.; Wu, Yi-Kai; Guyton, David L.

2014-06-01

Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.

Electrochemical and Infrared Absorption Spectroscopy Detection of SF6 Decomposition Products

PubMed Central

Dong, Ming; Ren, Ming; Ye, Rixin

2017-01-01

Sulfur hexafluoride (SF6) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF6 decomposition and ultimately generates several types of decomposition products. These SF6 decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF6 decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF6 gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF6 decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF6 gas decomposition and is verified to reliably and accurately detect the gas components and concentrations. PMID:29140268

A novel sulfate-reducing bacteria detection method based on inhibition of cysteine protease activity.

PubMed

Qi, Peng; Zhang, Dun; Wan, Yi

2014-11-01

Sulfate-reducing bacteria (SRB) have been extensively studied in corrosion and environmental science. However, fast enumeration of SRB population is still a difficult task. This work presents a novel specific SRB detection method based on inhibition of cysteine protease activity. The hydrolytic activity of cysteine protease was inhibited by taking advantage of sulfide, the characteristic metabolic product of SRB, to attack active cysteine thiol group in cysteine protease catalytic sites. The active thiol S-sulfhydration process could be used for SRB detection, since the amount of sulfide accumulated in culture medium was highly related with initial bacterial concentration. The working conditions of cysteine protease have been optimized to obtain better detection capability, and the SRB detection performances have been evaluated in this work. The proposed SRB detection method based on inhibition of cysteine protease activity avoided the use of biological recognition elements. In addition, compared with the widely used most probable number (MPN) method which would take up to at least 15days to accomplish whole detection process, the method based on inhibition of papain activity could detect SRB in 2 days, with a detection limit of 5.21×10(2) cfu mL(-1). The detection time for SRB population quantitative analysis was greatly shortened. Copyright © 2014 Elsevier B.V. All rights reserved.

Microwave-Accelerated Method for Ultra-Rapid Extraction of Neisseria gonorrhoeae DNA for Downstream Detection

PubMed Central

Melendez, Johan H.; Santaus, Tonya M.; Brinsley, Gregory; Kiang, Daniel; Mali, Buddha; Hardick, Justin; Gaydos, Charlotte A.; Geddes, Chris D.

2016-01-01

Nucleic acid-based detection of gonorrhea infections typically require a two-step process involving isolation of the nucleic acid, followed by the detection of the genomic target often involving PCR-based approaches. In an effort to improve on current detection approaches, we have developed a unique two-step microwave-accelerated approach for rapid extraction and detection of Neisseria gonorrhoeae (GC) DNA. Our approach is based on the use of highly-focused microwave radiation to rapidly lyse bacterial cells, release, and subsequently fragment microbial DNA. The DNA target is then detected by a process known as microwave-accelerated metal-enhanced fluorescence (MAMEF), an ultra-sensitive direct DNA detection analytical technique. In the present study, we show that highly focused microwaves at 2.45 GHz, using 12.3 mm gold film equilateral triangles, are able to rapidly lyse both bacteria cells and fragment DNA in a time- and microwave power-dependent manner. Detection of the extracted DNA can be performed by MAMEF, without the need for DNA amplification in less than 10 minutes total time or by other PCR-based approaches. Collectively, the use of a microwave-accelerated method for the release and detection of DNA represents a significant step forward towards the development of a point-of-care (POC) platform for detection of gonorrhea infections. PMID:27325503

A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Becker, D.; Cain, S.

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Earthquake Detection

NASA Astrophysics Data System (ADS)

Bergen, K.; Yoon, C. E.; OReilly, O. J.; Beroza, G. C.

2015-12-01

Recent improvements in computational efficiency for waveform correlation-based detections achieved by new methods such as Fingerprint and Similarity Thresholding (FAST) promise to allow large-scale blind search for similar waveforms in long-duration continuous seismic data. Waveform similarity search applied to datasets of months to years of continuous seismic data will identify significantly more events than traditional detection methods. With the anticipated increase in number of detections and associated increase in false positives, manual inspection of the detection results will become infeasible. This motivates the need for new approaches to process the output of similarity-based detection. We explore data mining techniques for improved detection post-processing. We approach this by considering similarity-detector output as a sparse similarity graph with candidate events as vertices and similarities as weighted edges. Image processing techniques are leveraged to define candidate events and combine results individually processed at multiple stations. Clustering and graph analysis methods are used to identify groups of similar waveforms and assign a confidence score to candidate detections. Anomaly detection and classification are applied to waveform data for additional false detection removal. A comparison of methods will be presented and their performance will be demonstrated on a suspected induced and non-induced earthquake sequence.

New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull's eye focus detection with an improved target system: opto-mechanical design and operation.

PubMed

Irsch, Kristina; Gramatikov, Boris I; Wu, Yi-Kai; Guyton, David L

2014-06-01

Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.

Development of Abnormality Detection System for Bathers using Ultrasonic Sensors

NASA Astrophysics Data System (ADS)

Ohnishi, Yosuke; Abe, Takehiko; Nambo, Hidetaka; Kimura, Haruhiko; Ogoshi, Yasuhiro

This paper proposes an abnormality detection system for bather sitting in bathtub. Increasing number of in-bathtub drowning accidents in Japan draws attention. Behind this large number of bathing accidents, Japan's unique social and cultural background come surface. For majority of people in Japan, bathing serves purpose in deep warming up of body, relax and enjoyable time. Therefore it is the custom for the Japanese to soak in bathtub. However overexposure to hot water may cause dizziness or fainting, which is possible to cause in-bathtub drowning. For drowning prevention, the system detects bather's abnormal state using an ultrasonic sensor array. The array, which has many ultrasonic sensors, is installed on the ceiling of bathroom above bathtub. The abnormality detection system uses the following two methods: posture detection and behavior detection. The function of posture detection is to estimate the risk of drowning by monitoring bather's posture. Meanwhile, the function of behavior detection is to estimate the risk of drowning by monitoring bather's behavior. By using these methods, the system detects bathers' different state from normal. As a result of experiment with a subject in the bathtub, the system was possible to detect abnormal state using subject's posture and behavior. Therefore the system is useful for monitoring bather to prevent drowning in bathtub.

A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data

PubMed Central

Goldstein, Markus; Uchida, Seiichi

2016-01-01

Anomaly detection is the process of identifying unexpected items or events in datasets, which differ from the norm. In contrast to standard classification tasks, anomaly detection is often applied on unlabeled data, taking only the internal structure of the dataset into account. This challenge is known as unsupervised anomaly detection and is addressed in many practical applications, for example in network intrusion detection, fraud detection as well as in the life science and medical domain. Dozens of algorithms have been proposed in this area, but unfortunately the research community still lacks a comparative universal evaluation as well as common publicly available datasets. These shortcomings are addressed in this study, where 19 different unsupervised anomaly detection algorithms are evaluated on 10 different datasets from multiple application domains. By publishing the source code and the datasets, this paper aims to be a new well-funded basis for unsupervised anomaly detection research. Additionally, this evaluation reveals the strengths and weaknesses of the different approaches for the first time. Besides the anomaly detection performance, computational effort, the impact of parameter settings as well as the global/local anomaly detection behavior is outlined. As a conclusion, we give an advise on algorithm selection for typical real-world tasks. PMID:27093601

Optics detection and laser countermeasures on a combat vehicle

NASA Astrophysics Data System (ADS)

Sjöqvist, Lars; Allard, Lars; Pettersson, Magnus; Börjesson, Per; Lindskog, Nils; Bodin, Johan; Widén, Anders; Persson, Hâkan; Fredriksson, Jan; Edström, Sten

2016-10-01

Magnifying optical assemblies used for weapon guidance or rifle scopes may possess a threat for a combat vehicle and its personnel. Detection and localisation of optical threats is consequently of interest in military applications. Typically a laser system is used in optics detection, or optical augmentation, to interrogate a scene of interest to localise retroreflected laser radiation. One interesting approach for implementing optics detection on a combat vehicle is to use a continuous scanning scheme. In addition, optics detection can be combined with laser countermeasures, or a laser dazzling function, to efficiently counter an optical threat. An optics detection laser sensor demonstrator has been implemented on a combat vehicle. The sensor consists of a stabilised gimbal and was integrated together with a LEMUR remote electro-optical sight. A narrow laser slit is continuously scanned around the horizon to detect and locate optical threats. Detected threats are presented for the operator within the LEMUR presentation system, and by cueing a countermeasure laser installed in the LEMUR sensor housing threats can be defeated. Results obtained during a field demonstration of the optics detection sensor and the countermeasure laser will be presented. In addition, results obtained using a dual-channel optics detection system designed for false alarm reduction are also discussed.

Detecting and visualizing weak signatures in hyperspectral data

NASA Astrophysics Data System (ADS)

MacPherson, Duncan James

This thesis evaluates existing techniques for detecting weak spectral signatures from remotely sensed hyperspectral data. Algorithms are presented that successfully detect hard-to-find 'mystery' signatures in unknown cluttered backgrounds. The term 'mystery' is used to describe a scenario where the spectral target and background endmembers are unknown. Sub-Pixel analysis and background suppression are used to find deeply embedded signatures which can be less than 10% of the total signal strength. Existing 'mystery target' detection algorithms are derived and compared. Several techniques are shown to be superior both visually and quantitatively. Detection performance is evaluated using confidence metrics that are developed. A multiple algorithm approach is shown to improve detection confidence significantly. Although the research focuses on remote sensing applications, the algorithms presented can be applied to a wide variety of diverse fields such as medicine, law enforcement, manufacturing, earth science, food production, and astrophysics. The algorithms are shown to be general and can be applied to both the reflective and emissive parts of the electromagnetic spectrum. The application scope is a broad one and the final results open new opportunities for many specific applications including: land mine detection, pollution and hazardous waste detection, crop abundance calculations, volcanic activity monitoring, detecting diseases in food, automobile or airplane target recognition, cancer detection, mining operations, extracting galactic gas emissions, etc.

An Adaptive Failure Detector Based on Quality of Service in Peer-to-Peer Networks

PubMed Central

Dong, Jian; Ren, Xiao; Zuo, Decheng; Liu, Hongwei

2014-01-01

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen's classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen's model. Moreover, B-AFD has better adaptability to P2P network. PMID:25198005

The Ladder of Life Detection.

PubMed

Neveu, Marc; Hays, Lindsay E; Voytek, Mary A; New, Michael H; Schulte, Mitchell D

2018-06-04

We describe the history and features of the Ladder of Life Detection, a tool intended to guide the design of investigations to detect microbial life within the practical constraints of robotic space missions. To build the Ladder, we have drawn from lessons learned from previous attempts at detecting life and derived criteria for a measurement (or suite of measurements) to constitute convincing evidence for indigenous life. We summarize features of life as we know it, how specific they are to life, and how they can be measured, and sort these features in a general sense based on their likelihood of indicating life. Because indigenous life is the hypothesis of last resort in interpreting life-detection measurements, we propose a small but expandable set of decision rules determining whether the abiotic hypothesis is disproved. In light of these rules, we evaluate past and upcoming attempts at life detection. The Ladder of Life Detection is not intended to endorse specific biosignatures or instruments for life-detection measurements, and is by no means a definitive, final product. It is intended as a starting point to stimulate discussion, debate, and further research on the characteristics of life, what constitutes a biosignature, and the means to measure them. Key Words: Life detection-Life-detection instruments-Biosignatures-Biomarkers. Astrobiology 18, xxx-xxx.

Indirect ultraviolet detection of alkaline earth metal ions using an imidazolium ionic liquid as an ultraviolet absorption reagent in ion chromatography.

PubMed

Liu, Yong-Qiang; Yu, Hong

2017-04-01

A convenient and versatile method was developed for the separation and detection of alkaline earth metal ions by ion chromatography with indirect UV detection. The chromatographic separation of Mg 2+ , Ca 2+ , and Sr 2+ was performed on a carboxylic acid base cation exchange column using imidazolium ionic liquid/acid as the mobile phase, in which the imidazolium ionic liquid acted as an UV-absorption reagent. The effects of imidazolium ionic liquids, detection wavelength, acids in the mobile phase, and column temperature on the retention of Mg 2+ , Ca 2+ , and Sr 2+ were investigated. The main factors influencing the separation and detection were the background UV absorption reagent and the concentration of hydrogen ion in ion chromatography with indirect UV detection. The successful separation and detection of Mg 2+ , Ca 2+ , and Sr 2+ within 14 min were achieved using the selected chromatographic conditions, and the detection limits (S/N = 3) were 0.06, 0.12, and 0.23 mg/L, respectively. A new separation and detection method of alkaline earth metal ions by ion chromatography with indirect UV detection was developed, and the application range of ionic liquids was expanded. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

in silico Surveillance: evaluating outbreak detection with simulation models

PubMed Central

2013-01-01

Background Detecting outbreaks is a crucial task for public health officials, yet gaps remain in the systematic evaluation of outbreak detection protocols. The authors’ objectives were to design, implement, and test a flexible methodology for generating detailed synthetic surveillance data that provides realistic geographical and temporal clustering of cases and use to evaluate outbreak detection protocols. Methods A detailed representation of the Boston area was constructed, based on data about individuals, locations, and activity patterns. Influenza-like illness (ILI) transmission was simulated, producing 100 years of in silico ILI data. Six different surveillance systems were designed and developed using gathered cases from the simulated disease data. Performance was measured by inserting test outbreaks into the surveillance streams and analyzing the likelihood and timeliness of detection. Results Detection of outbreaks varied from 21% to 95%. Increased coverage did not linearly improve detection probability for all surveillance systems. Relaxing the decision threshold for signaling outbreaks greatly increased false-positives, improved outbreak detection slightly, and led to earlier outbreak detection. Conclusions Geographical distribution can be more important than coverage level. Detailed simulations of infectious disease transmission can be configured to represent nearly any conceivable scenario. They are a powerful tool for evaluating the performance of surveillance systems and methods used for outbreak detection. PMID:23343523

To See or Not to See: Investigating Detectability of Ganges River Dolphins Using a Combined Visual-Acoustic Survey

PubMed Central

Richman, Nadia I.; Gibbons, James M.; Turvey, Samuel T.; Akamatsu, Tomonari; Ahmed, Benazir; Mahabub, Emile; Smith, Brian D.; Jones, Julia P. G.

2014-01-01

Detection of animals during visual surveys is rarely perfect or constant, and failure to account for imperfect detectability affects the accuracy of abundance estimates. Freshwater cetaceans are among the most threatened group of mammals, and visual surveys are a commonly employed method for estimating population size despite concerns over imperfect and unquantified detectability. We used a combined visual-acoustic survey to estimate detectability of Ganges River dolphins (Platanista gangetica gangetica) in four waterways of southern Bangladesh. The combined visual-acoustic survey resulted in consistently higher detectability than a single observer-team visual survey, thereby improving power to detect trends. Visual detectability was particularly low for dolphins close to meanders where these habitat features temporarily block the view of the preceding river surface. This systematic bias in detectability during visual-only surveys may lead researchers to underestimate the importance of heavily meandering river reaches. Although the benefits of acoustic surveys are increasingly recognised for marine cetaceans, they have not been widely used for monitoring abundance of freshwater cetaceans due to perceived costs and technical skill requirements. We show that acoustic surveys are in fact a relatively cost-effective approach for surveying freshwater cetaceans, once it is acknowledged that methods that do not account for imperfect detectability are of limited value for monitoring. PMID:24805782

To see or not to see: investigating detectability of Ganges River dolphins using a combined visual-acoustic survey.

PubMed

Richman, Nadia I; Gibbons, James M; Turvey, Samuel T; Akamatsu, Tomonari; Ahmed, Benazir; Mahabub, Emile; Smith, Brian D; Jones, Julia P G

2014-01-01

Detection of animals during visual surveys is rarely perfect or constant, and failure to account for imperfect detectability affects the accuracy of abundance estimates. Freshwater cetaceans are among the most threatened group of mammals, and visual surveys are a commonly employed method for estimating population size despite concerns over imperfect and unquantified detectability. We used a combined visual-acoustic survey to estimate detectability of Ganges River dolphins (Platanista gangetica gangetica) in four waterways of southern Bangladesh. The combined visual-acoustic survey resulted in consistently higher detectability than a single observer-team visual survey, thereby improving power to detect trends. Visual detectability was particularly low for dolphins close to meanders where these habitat features temporarily block the view of the preceding river surface. This systematic bias in detectability during visual-only surveys may lead researchers to underestimate the importance of heavily meandering river reaches. Although the benefits of acoustic surveys are increasingly recognised for marine cetaceans, they have not been widely used for monitoring abundance of freshwater cetaceans due to perceived costs and technical skill requirements. We show that acoustic surveys are in fact a relatively cost-effective approach for surveying freshwater cetaceans, once it is acknowledged that methods that do not account for imperfect detectability are of limited value for monitoring.

DNA aptamer-based colorimetric detection platform for Salmonella Enteritidis.

PubMed

Bayraç, Ceren; Eyidoğan, Füsun; Avni Öktem, Hüseyin

2017-12-15

Food safety is a major issue to protect public health and a key challenge is to find detection methods for identification of hazards in food. Food borne infections affects millions of people each year and among pathogens, Salmonella Enteritidis is most widely found bacteria causing food borne diseases. Therefore, simple, rapid, and specific detection methods are needed for food safety. In this study, we demonstrated the selection of DNA aptamers with high affinity and specificity against S. Enteritidis via Cell Systematic Evolution of Ligands by Exponential Enrichment (Cell-SELEX) and development of sandwich type aptamer-based colorimetric platforms for its detection. Two highly specific aptamers, crn-1 and crn-2, were developed through 12 rounds of selection with K d of 0.971µM and 0.309µM, respectively. Both aptamers were used to construct sandwich type capillary detection platforms. With the detection limit of 10 3 CFU/mL, crn-1 and crn-2 based platforms detected target bacteria specifically based on color change. This platform is also suitable for detection of S. Enteritidis in complex food matrix. Thus, this is the first to demonstrate use of Salmonella aptamers for development of the colorimetric aptamer-based detection platform in its identification and detection with naked eye in point-of-care. Copyright © 2017 Elsevier B.V. All rights reserved.

Dual chronoamperometric detection of enzymatic biomarkers using magnetic beads and a low-cost flow cell.

PubMed

Moral-Vico, Javier; Barallat, Jaume; Abad, Llibertat; Olivé-Monllau, Rosa; Muñoz-Pascual, Francesc Xavier; Galán Ortega, Amparo; del Campo, F Javier; Baldrich, Eva

2015-07-15

In this work we report on the production of a low cost microfluidic device for the multiplexed electrochemical detection of magneto bioassays. As a proof of concept, the device has been used to detect myeloperoxidase (MPO), a cardiovascular biomarker. With this purpose, two bioassays have been optimized in parallel onto magnetic beads (MBs) for the simultaneous detection of MPO endogenous peroxidase activity and quantification of total MPO. Since the two bioassays produced signals of different magnitude for each concentration of MPO tested, two detection strategies have been compared, which entailed registering steady state currents (Iss) under substrate flow, and measuring the peak currents (Ip) produced in a stopped flow approach. As it will be shown, appropriate tuning of the detection and flow conditions can provide extremely sensitive detection, but also allow simultaneous detection of assays or parameters that would produce signals of different orders of magnitude when measured by a single detection strategy. In order to demonstrate the feasibility of the detection strategy reported, a dual MPO mass and activity assay has been finally applied to the study of 10 real plasma samples, allowing patient classification according to the risk of suffering a cardiovascular event. Copyright © 2015 Elsevier B.V. All rights reserved.

Face detection assisted auto exposure: supporting evidence from a psychophysical study

NASA Astrophysics Data System (ADS)

Jin, Elaine W.; Lin, Sheng; Dharumalingam, Dhandapani

2010-01-01

Face detection has been implemented in many digital still cameras and camera phones with the promise of enhancing existing camera functions (e.g. auto exposure) and adding new features to cameras (e.g. blink detection). In this study we examined the use of face detection algorithms in assisting auto exposure (AE). The set of 706 images, used in this study, was captured using Canon Digital Single Lens Reflex cameras and subsequently processed with an image processing pipeline. A psychophysical study was performed to obtain optimal exposure along with the upper and lower bounds of exposure for all 706 images. Three methods of marking faces were utilized: manual marking, face detection algorithm A (FD-A), and face detection algorithm B (FD-B). The manual marking method found 751 faces in 426 images, which served as the ground-truth for face regions of interest. The remaining images do not have any faces or the faces are too small to be considered detectable. The two face detection algorithms are different in resource requirements and in performance. FD-A uses less memory and gate counts compared to FD-B, but FD-B detects more faces and has less false positives. A face detection assisted auto exposure algorithm was developed and tested against the evaluation results from the psychophysical study. The AE test results showed noticeable improvement when faces were detected and used in auto exposure. However, the presence of false positives would negatively impact the added benefit.

Development of array piezoelectric fingers towards in vivo breast tumor detection

NASA Astrophysics Data System (ADS)

Xu, Xin; Chung, Youngsoo; Brooks, Ari D.; Shih, Wei-Heng; Shih, Wan Y.

2016-12-01

We have investigated the development of a handheld 4 × 1 piezoelectric finger (PEF) array breast tumor detector system towards in vivo patient testing, particularly, on how the duration of the DC applied voltage, the depression depth of the handheld unit, and breast density affect the PEF detection sensitivity on 40 patients. The tests were blinded and carried out in four phases: with DC voltage durations 5, 3, 2, to 0.8 s corresponding to scanning a quadrant, a half, a whole breast, and both breasts within 30 min, respectively. The results showed that PEF detection sensitivity was unaffected by shortening the applied voltage duration from 5 to 0.8 s nor was it affected by increasing the depression depth from 2 to 6 mm. Over the 40 patients, PEF detected 46 of the 48 lesions (46/48)—with the smallest lesion detected being 5 mm in size. Of 28 patients (some have more than one lesion) with mammography records, PEF detected 31/33 of all lesions (94%) and 14/15 of malignant lesions (93%), while mammography detected 30/33 of all lesions (91%) and 12/15 of malignant lesions (80%), indicating that PEF could detect malignant lesions not detectable by mammography without significantly increasing false positives. PEF's detection sensitivity is also shown to be independent of breast density, suggesting that PEF could be a potential tool for detecting breast cancer in young women and women with dense breasts.

Modeling peripheral vision for moving target search and detection.

PubMed

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

2012-06-01

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

Variation in detection of ductal carcinoma in situ (DCIS) during screening mammography A survey within the International Cancer Screening Network (ICSN)

PubMed Central

Lynge, Elsebeth; Ponti, Antonio; James, Ted; Májek, Ondřej; von Euler-Chelpin, My; Anttila, Ahti; Fitzpatrick, Patricia; Frigerio, Alfonso; Kawai, Masaaki; Scharpantgen, Astrid; Broeders, Mireille; Hofvind, Solveig; Vidal, Carmen; Ederra, Maria; Salas, Dolores; Bulliard, Jean-Luc; Tomatis, Mariano; Kerlikowske, Karla; Taplin, Stephen

2013-01-01

Background There is concern about detection of Ductal Carcinoma in Situ (DCIS) in screening mammography. DCIS accounts for a substantial proportion of screen detected lesions but its effect on breast cancer mortality is debated. The International Cancer Screening Network conducted a comparative analysis to determine variation in DCIS detection. Patients and Methods Data were collected during 2004–2008 on number of screening examinations, detected breast cancers, DCIS cases, and Globocan 2008 breast cancer incidence rates derived from national or regional cancer registers. We calculated screen-detection rates for breast cancers and DCIS. Results Data were obtained from 15 screening settings in 12 countries; 7,176,050 screening examinations; 29,605 breast cancers; and 5,324 DCIS cases. The ratio between highest and lowest breast cancer incidence was 2.88 (95% confidence interval (CI) 2.76–3.00); 2.97 (95% CI 2.51–3.51) for detection of breast cancer; and 3.49 (95% CI 2.70–4.51) for detection of DCIS. Conclusions Considerable international variation was found in DCIS detection. This variation could not be fully explained by variation in incidence nor in breast cancer detection rates. It suggests the potential for wide discrepancies in management of DCIS resulting in overtreatment of indolent DCIS or undertreatment of potentially curable disease. Comprehensive cancer registration is needed to monitor DCIS detection. Efforts to understand discrepancies and standardize management may improve care. PMID:24041876

Sentinel lymph node detection in early cervical cancer with combination 99mTc phytate and patent blue.

PubMed

Niikura, Hitoshi; Okamura, Chikako; Akahira, Junichi; Takano, Tadao; Ito, Kiyoshi; Okamura, Kunihiro; Yaegashi, Nobuo

2004-08-01

The purpose of this study was to examine sentinel lymph node (SLN) detection in patients with early stage cervical cancer using (99m)Tc phytate and patent blue dye and to compare our method with published findings utilizing other radioisotopic tracers. A total of 20 consecutive patients with cervical cancer scheduled for radical hysterectomy and total pelvic lymphadenectomy at our hospital underwent SLN detection study. The day before surgery, lymphoscintigraphy was performed with injection of 99m-technetium ((99m)Tc)-labeled phytate into the uterine cervix. At surgery, patients underwent lymphatic mapping with a gamma-detecting probe and patent blue injected into the same points as the phytate solution. At least one positive node was detected in 18 patients (90%). A total of 46 sentinel nodes were detected (mean, 2.3; range, 1-5). Most sentinel nodes were in one of the following sites: external iliac (21 nodes), obturator (15 nodes), and parametrial (7 nodes). Eleven (24%) sentinel nodes were detected only through radioactivity and two (4%) were detected only with blue dye. The sensitivity, specificity, and negative predictive value for SLN detection were all 100%. Nine published studies involving 295 patients had a summarized detection rate of 85%. Summarized sensitivity, specificity, and negative predictive value were 93%, 100%, and 99%, respectively. Combination of (99m)Tc phytate and patent blue is effective in SLN detection in early stage cervical cancer.

Object detection in natural scenes: Independent effects of spatial and category-based attention.

PubMed

Stein, Timo; Peelen, Marius V

2017-04-01

Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.

The Gap Detection Test: Can It Be Used to Diagnose Tinnitus?

PubMed

Boyen, Kris; Başkent, Deniz; van Dijk, Pim

2015-01-01

Animals with induced tinnitus showed difficulties in detecting silent gaps in sounds, suggesting that the tinnitus percept may be filling the gap. The main purpose of this study was to evaluate the applicability of this approach to detect tinnitus in human patients. The authors first hypothesized that gap detection would be impaired in patients with tinnitus, and second, that gap detection would be more impaired at frequencies close to the tinnitus frequency of the patient. Twenty-two adults with bilateral tinnitus, 20 age-matched and hearing loss-matched subjects without tinnitus, and 10 young normal-hearing subjects participated in the study. To determine the characteristics of the tinnitus, subjects matched an external sound to their perceived tinnitus in pitch and loudness. To determine the minimum detectable gap, the gap threshold, an adaptive psychoacoustic test was performed three times by each subject. In this gap detection test, four different stimuli, with various frequencies and bandwidths, were presented at three intensity levels each. Similar to previous reports of gap detection, increasing sensation level yielded shorter gap thresholds for all stimuli in all groups. Interestingly, the tinnitus group did not display elevated gap thresholds in any of the four stimuli. Moreover, visual inspection of the data revealed no relation between gap detection performance and perceived tinnitus pitch. These findings show that tinnitus in humans has no effect on the ability to detect gaps in auditory stimuli. Thus, the testing procedure in its present form is not suitable for clinical detection of tinnitus in humans.

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

PubMed

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

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.

Sampling little fish in big rivers: Larval fish detection probabilities in two Lake Erie tributaries and implications for sampling effort and abundance indices

USGS Publications Warehouse

Pritt, Jeremy J.; DuFour, Mark R.; Mayer, Christine M.; Roseman, Edward F.; DeBruyne, Robin L.

2014-01-01

Larval fish are frequently sampled in coastal tributaries to determine factors affecting recruitment, evaluate spawning success, and estimate production from spawning habitats. Imperfect detection of larvae is common, because larval fish are small and unevenly distributed in space and time, and coastal tributaries are often large and heterogeneous. We estimated detection probabilities of larval fish from several taxa in the Maumee and Detroit rivers, the two largest tributaries of Lake Erie. We then demonstrated how accounting for imperfect detection influenced (1) the probability of observing taxa as present relative to sampling effort and (2) abundance indices for larval fish of two Detroit River species. We found that detection probabilities ranged from 0.09 to 0.91 but were always less than 1.0, indicating that imperfect detection is common among taxa and between systems. In general, taxa with high fecundities, small larval length at hatching, and no nesting behaviors had the highest detection probabilities. Also, detection probabilities were higher in the Maumee River than in the Detroit River. Accounting for imperfect detection produced up to fourfold increases in abundance indices for Lake Whitefish Coregonus clupeaformis and Gizzard Shad Dorosoma cepedianum. The effect of accounting for imperfect detection in abundance indices was greatest during periods of low abundance for both species. Detection information can be used to determine the appropriate level of sampling effort for larval fishes and may improve management and conservation decisions based on larval fish data.

Combined hostile fire and optics detection

NASA Astrophysics Data System (ADS)

Brännlund, Carl; Tidström, Jonas; Henriksson, Markus; Sjöqvist, Lars

2013-10-01

Snipers and other optically guided weapon systems are serious threats in military operations. We have studied a SWIR (Short Wave Infrared) camera-based system with capability to detect and locate snipers both before and after shot over a large field-of-view. The high frame rate SWIR-camera allows resolution of the temporal profile of muzzle flashes which is the infrared signature associated with the ejection of the bullet from the rifle. The capability to detect and discriminate sniper muzzle flashes with this system has been verified by FOI in earlier studies. In this work we have extended the system by adding a laser channel for optics detection. A laser diode with slit-shaped beam profile is scanned over the camera field-of-view to detect retro reflection from optical sights. The optics detection system has been tested at various distances up to 1.15 km showing the feasibility to detect rifle scopes in full daylight. The high speed camera gives the possibility to discriminate false alarms by analyzing the temporal data. The intensity variation, caused by atmospheric turbulence, enables discrimination of small sights from larger reflectors due to aperture averaging, although the targets only cover a single pixel. It is shown that optics detection can be integrated in combination with muzzle flash detection by adding a scanning rectangular laser slit. The overall optics detection capability by continuous surveillance of a relatively large field-of-view looks promising. This type of multifunctional system may become an important tool to detect snipers before and after shot.

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

PubMed

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

2013-11-01

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

Detection and plant monitoring programs: lessons from an intensive survey of Asclepias meadii with five observers.

PubMed

Alexander, Helen M; Reed, Aaron W; Kettle, W Dean; Slade, Norman A; Bodbyl Roels, Sarah A; Collins, Cathy D; Salisbury, Vaughn

2012-01-01

Monitoring programs, where numbers of individuals are followed through time, are central to conservation. Although incomplete detection is expected with wildlife surveys, this topic is rarely considered with plants. However, if plants are missed in surveys, raw count data can lead to biased estimates of population abundance and vital rates. To illustrate, we had five independent observers survey patches of the rare plant Asclepias meadii at two prairie sites. We analyzed data with two mark-recapture approaches. Using the program CAPTURE, the estimated number of patches equaled the detected number for a burned site, but exceeded detected numbers by 28% for an unburned site. Analyses of detected patches using Huggins models revealed important effects of observer, patch state (flowering/nonflowering), and patch size (number of stems) on probabilities of detection. Although some results were expected (i.e. greater detection of flowering than nonflowering patches), the importance of our approach is the ability to quantify the magnitude of detection problems. We also evaluated the degree to which increased observer numbers improved detection: smaller groups (3-4 observers) generally found 90 - 99% of the patches found by all five people, but pairs of observers or single observers had high error and detection depended on which individuals were involved. We conclude that an intensive study at the start of a long-term monitoring study provides essential information about probabilities of detection and what factors cause plants to be missed. This information can guide development of monitoring programs.

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

DTIC Science & Technology

1995-03-01

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

USING CANINES IN SOURCE DETECTION OF INDOOR AIR POLLUTANTS EPA SCIENCE FORUM

EPA Science Inventory

Scent detection dogs have been used extensively in law enforcement and military applications to detect narcotics and explosives for over thirty years. Controlled laboratory studies have documented accurate detection by dogs of specific compounds associated with explosives and nar...

Urban change detection procedures using Landsat digital data

NASA Technical Reports Server (NTRS)

Jensen, J. R.; Toll, D. L.

1982-01-01

Landsat multispectral scanner data was applied to an urban change detection problem in Denver, CO. A dichotomous key yielding ten stages of residential development at the urban fringe was developed. This heuristic model allowed one to identify certain stages of development which are difficult to detect when performing digital change detection using Landsat data. The stages of development were evaluated in terms of their spectral and derived textural characteristics. Landsat band 5 (0.6-0.7 micron) and texture data produced change detection maps which were approximately 81 percent accurate. Results indicated that the stage of development and the spectral/textural features affect the change in the spectral values used for change detection. These preliminary findings will hopefully prove valuable for improved change detection at the urban fringe.

UV gated Raman spectroscopy for standoff detection of explosives

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2008-07-01

Real-time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called improvised explosive devices (IED). It is recognized that the only method, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We have applied gated Raman spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 m.

The wide window of face detection.

PubMed

Hershler, Orit; Golan, Tal; Bentin, Shlomo; Hochstein, Shaul

2010-08-20

Faces are detected more rapidly than other objects in visual scenes and search arrays, but the cause for this face advantage has been contested. In the present study, we found that under conditions of spatial uncertainty, faces were easier to detect than control targets (dog faces, clocks and cars) even in the absence of surrounding stimuli, making an explanation based only on low-level differences unlikely. This advantage improved with eccentricity in the visual field, enabling face detection in wider visual windows, and pointing to selective sparing of face detection at greater eccentricities. This face advantage might be due to perceptual factors favoring face detection. In addition, the relative face advantage is greater under flanked than non-flanked conditions, suggesting an additional, possibly attention-related benefit enabling face detection in groups of distracters.

Spot restoration for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2014-05-20

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.

Adaptable radiation monitoring system and method

DOEpatents

Archer, Daniel E [Livermore, CA; Beauchamp, Brock R [San Ramon, CA; Mauger, G Joseph [Livermore, CA; Nelson, Karl E [Livermore, CA; Mercer, Michael B [Manteca, CA; Pletcher, David C [Sacramento, CA; Riot, Vincent J [Berkeley, CA; Schek, James L [Tracy, CA; Knapp, David A [Livermore, CA

2006-06-20

A portable radioactive-material detection system capable of detecting radioactive sources moving at high speeds. The system has at least one radiation detector capable of detecting gamma-radiation and coupled to an MCA capable of collecting spectral data in very small time bins of less than about 150 msec. A computer processor is connected to the MCA for determining from the spectral data if a triggering event has occurred. Spectral data is stored on a data storage device, and a power source supplies power to the detection system. Various configurations of the detection system may be adaptably arranged for various radiation detection scenarios. In a preferred embodiment, the computer processor operates as a server which receives spectral data from other networked detection systems, and communicates the collected data to a central data reporting system.

Individual differences in conflict detection during reasoning.

PubMed

Frey, Darren; Johnson, Eric D; De Neys, Wim

2018-05-01

Decades of reasoning and decision-making research have established that human judgment is often biased by intuitive heuristics. Recent "error" or bias detection studies have focused on reasoners' abilities to detect whether their heuristic answer conflicts with logical or probabilistic principles. A key open question is whether there are individual differences in this bias detection efficiency. Here we present three studies in which co-registration of different error detection measures (confidence, response time and confidence response time) allowed us to assess bias detection sensitivity at the individual participant level in a range of reasoning tasks. The results indicate that although most individuals show robust bias detection, as indexed by increased latencies and decreased confidence, there is a subgroup of reasoners who consistently fail to do so. We discuss theoretical and practical implications for the field.

Covariance descriptor fusion for target detection

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

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

Stavis, Samuel M; Edel, Joshua B; Samiee, Kevan T

A nanofluidic channel fabricated in fused silica with an approximately 500 nm square cross section was used to isolate, detect and identify individual quantum dot conjugates. The channel enables the rapid detection of every fluorescent entity in solution. A laser of selected wavelength was used to excite multiple species of quantum dots and organic molecules, and the emission spectra were resolved without significant signal rejection. Quantum dots were then conjugated with organic molecules and detected to demonstrate efficient multicolor detection. PCH was used to analyze coincident detection and to characterize the degree of binding. The use of a small fluidicmore » channel to detect quantum dots as fluorescent labels was shown to be an efficient technique for multiplexed single molecule studies. Detection of single molecule binding events has a variety of applications including high throughput immunoassays.« less

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Rapid detection of human fecal Eubacterium species and related genera by nested PCR method.

PubMed

Kageyama, A; Benno, Y

2001-01-01

PCR procedures based on 16S rDNA gene sequence specific for seven Eubacterium spp. and Eggerthella lenta that predominate in the human intestinal tract were developed, and used for direct detection of these species in seven human feces samples. Three species of Eggerthella lenta, Eubacterium rectale, and Eubacterium eligens were detected from seven fecal samples. Eubacterium biforme was detected from six samples. It was reported that E. rectale, E. eligens, and E. biforme were difficult to detect by traditional culture method, but the nested PCR method is available for the detection of these species. This result shows that the nested PCR method utilizing a universal primer pair, followed by amplification with species-specific primers, would allow rapid detection of Eubacterium species in human feces.

Abnormal global and local event detection in compressive sensing domain

NASA Astrophysics Data System (ADS)

Wang, Tian; Qiao, Meina; Chen, Jie; Wang, Chuanyun; Zhang, Wenjia; Snoussi, Hichem

2018-05-01

Abnormal event detection, also known as anomaly detection, is one challenging task in security video surveillance. It is important to develop effective and robust movement representation models for global and local abnormal event detection to fight against factors such as occlusion and illumination change. In this paper, a new algorithm is proposed. It can locate the abnormal events on one frame, and detect the global abnormal frame. The proposed algorithm employs a sparse measurement matrix designed to represent the movement feature based on optical flow efficiently. Then, the abnormal detection mission is constructed as a one-class classification task via merely learning from the training normal samples. Experiments demonstrate that our algorithm performs well on the benchmark abnormal detection datasets against state-of-the-art methods.

An immunity-based anomaly detection system with sensor agents.

PubMed

Okamoto, Takeshi; Ishida, Yoshiteru

2009-01-01

This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems.

Method of noncontacting ultrasonic process monitoring

DOEpatents

Garcia, Gabriel V.; Walter, John B.; Telschow, Kenneth L.

1992-01-01

A method of monitoring a material during processing comprising the steps of (a) shining a detection light on the surface of a material; (b) generating ultrasonic waves at the surface of the material to cause a change in frequency of the detection light; (c) detecting a change in the frequency of the detection light at the surface of the material; (d) detecting said ultrasonic waves at the surface point of detection of the material; (e) measuring a change in the time elapsed from generating the ultrasonic waves at the surface of the material and return to the surface point of detection of the material, to determine the transit time; and (f) comparing the transit time to predetermined values to determine properties such as, density and the elastic quality of the material.

Detecting impossible changes in infancy: a three-system account

PubMed Central

Wang, Su-hua; Baillargeon, Renée

2012-01-01

Can infants detect that an object has magically disappeared, broken apart or changed color while briefly hidden? Recent research suggests that infants detect some but not other ‘impossible’ changes; and that various contextual manipulations can induce infants to detect changes they would not otherwise detect. We present an account that includes three systems: a physical-reasoning, an object-tracking, and an object-representation system. What impossible changes infants detect depends on what object information is included in the physical-reasoning system; this information becomes subject to a principle of persistence, which states that objects can undergo no spontaneous or uncaused change. What contextual manipulations induce infants to detect impossible changes depends on complex interplays between the physical-reasoning system and the object-tracking and object-representation systems. PMID:18078778

Detection of Salmonella enteritidis Using a Miniature Optical Surface Plasmon Resonance Biosensor

NASA Astrophysics Data System (ADS)

Son, J. R.; Kim, G.; Kothapalli, A.; Morgan, M. T.; Ess, D.

2007-04-01

The frequent outbreaks of foodborne illness demand rapid detection of foodborne pathogens. Unfortunately, conventional methods for pathogen detection and identification are labor-intensive and take days to complete. Biosensors have shown great potential for the rapid detection of foodborne pathogens. Surface plasmon resonance (SPR) sensors have been widely adapted as an analysis tool for the study of various biological binding reactions. SPR biosensors could detect antibody-antigen bindings on the sensor surface by measuring either a resonance angle or refractive index value. In this study, the feasibility of a miniature SPR sensor (Spreeta, TI, USA) for detection of Salmonella enteritidis has been evaluated. Anti-Salmonella antibodies were immobilized on the gold sensor surface by using neutravidin. Salmonella could be detected by the Spreeta biosensor at concentrations down to 105 cfu/ml.

Finding intonational boundaries using acoustic cues related to the voice source

NASA Astrophysics Data System (ADS)

Choi, Jeung-Yoon; Hasegawa-Johnson, Mark; Cole, Jennifer

2005-10-01

Acoustic cues related to the voice source, including harmonic structure and spectral tilt, were examined for relevance to prosodic boundary detection. The measurements considered here comprise five categories: duration, pitch, harmonic structure, spectral tilt, and amplitude. Distributions of the measurements and statistical analysis show that the measurements may be used to differentiate between prosodic categories. Detection experiments on the Boston University Radio Speech Corpus show equal error detection rates around 70% for accent and boundary detection, using only the acoustic measurements described, without any lexical or syntactic information. Further investigation of the detection results shows that duration and amplitude measurements, and, to a lesser degree, pitch measurements, are useful for detecting accents, while all voice source measurements except pitch measurements are useful for boundary detection.

Feasibility Study of Radiometry for Airborne Detection of Aviation Hazards

NASA Technical Reports Server (NTRS)

Gimmestad, Gary G.; Papanicolopoulos, Chris D.; Richards, Mark A.; Sherman, Donald L.; West, Leanne L.; Johnson, James W. (Technical Monitor)

2001-01-01

Radiometric sensors for aviation hazards have the potential for widespread and inexpensive deployment on aircraft. This report contains discussions of three aviation hazards - icing, turbulence, and volcanic ash - as well as candidate radiometric detection techniques for each hazard. Dual-polarization microwave radiometry is the only viable radiometric technique for detection of icing conditions, but more research will be required to assess its usefulness to the aviation community. Passive infrared techniques are being developed for detection of turbulence and volcanic ash by researchers in this country and also in Australia. Further investigation of the infrared airborne radiometric hazard detection approaches will also be required in order to develop reliable detection/discrimination techniques. This report includes a description of a commercial hyperspectral imager for investigating the infrared detection techniques for turbulence and volcanic ash.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Clinical experience with a computer-aided diagnosis system for automatic detection of pulmonary nodules at spiral CT of the chest

NASA Astrophysics Data System (ADS)

Wormanns, Dag; Fiebich, Martin; Saidi, Mustafa; Diederich, Stefan; Heindel, Walter

2001-05-01

The purpose of the study was to evaluate a computer aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Two radiologists in consensus reported 88 consecutive spiral CT examinations. All examinations were reviewed using a UNIX-based CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm was designed to detect nodules with at least 5 mm diameter. The results of automatic nodule detection were compared to the consensus reporting of two radiologists as gold standard. Additional CAD findings were regarded as nodules initially missed by the radiologists or as false positive results. A total of 153 nodules were detected with all modalities (diameter: 85 nodules <5mm, 63 nodules 5-9 mm, 5 nodules >= 10 mm). Reasons for failure of automatic nodule detection were assessed. Sensitivity of radiologists for nodules >=5 mm was 85%, sensitivity of CAD was 38%. For nodules >=5 mm without pleural contact sensitivity was 84% for radiologists at 45% for CAD. CAD detected 15 (10%) nodules not mentioned in the radiologist's report but representing real nodules, among them 10 (15%) nodules with a diameter $GREW5 mm. Reasons for nodules missed by CAD include: exclusion because of morphological features during region analysis (33%), nodule density below the detection threshold (26%), pleural contact (33%), segmentation errors (5%) and other reasons (2%). CAD improves detection of pulmonary nodules at spiral CT significantly and is a valuable second opinion in a clinical setting for lung cancer screening. Optimization of region analysis and an appropriate density threshold have a potential for further improvement of automatic nodule detection.

[The clinical value of sentinel lymph node detection in laryngeal and hypopharyngeal carcinoma patients with clinically negative neck by methylene blue method and radiolabeled tracer method].

PubMed

Zhao, Xin; Xiao, Dajiang; Ni, Jianming; Zhu, Guochen; Yuan, Yuan; Xu, Ting; Zhang, Yongsheng

2014-11-01

To investigate the clinical value of sentinel lymph node (SLN) detection in laryngeal and hypopharyngeal carcinoma patients with clinically negative neck (cN0) by methylene blue method, radiolabeled tracer method and combination of these two methods. Thirty-three patients with cN0 laryngeal carcinoma and six patients with cN0 hypopharyngeal carcinoma underwent SLN detection using both of methylene blue and radiolabeled tracer method. All these patients were accepted received the injection of radioactive isotope 99 Tc(m)-sulfur colloid (SC) and methylene blue into the carcinoma before surgery, then all these patients underwent intraopertive lymphatic mapping with a handheld gamma-detecting probe and blue-dyed SLN. After the mapping of SLN, selected neck dissections and tumor resections were peformed. The results of SLN detection by radiolabeled tracer, dye and combination of both methods were compared. The detection rate of SLN by radiolabeled tracer, methylene blue and combined method were 89.7%, 79.5%, 92.3% respectively. The number of detected SLN was significantly different between radiolabeled tracer method and combined method, and also between methylene blue method and combined method. The detection rate of methylene blue and radiolabeled tracer method were significantly different from combined method (P < 0.05). Nine patients were found to have lymph node metastasis by final pathological examination. The accuracy and negative rate of SLN detection of the combined method were 97.2% and 11.1%. The combined method using radiolabeled tracer and methylene blue can improve the detection rate and accuracy of sentinel lymph node detection. Furthermore, sentinel lymph node detection can accurately represent the cervical lymph node status in cN0 laryngeal and hypopharyngeal carcinoma.

Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation

USGS Publications Warehouse

Walker, Donald M.; Leys, Jacob E.; Dunham, Kelly E.; Oliver, Joshua C.; Schiller, Emily E.; Stephenson, Kelsey S.; Kimrey, John T.; Wooten, Jessica; Rogers, Mark W.

2017-01-01

Environmental DNA (eDNA) can be used as an assessment tool to detect populations of threatened species and provide fine-scale data required to make management decisions. The objectives of this project were to use quantitative PCR (qPCR) to: (i) detect spiked salamander DNA in soil, (ii) quantify eDNA degradation over time, (iii) determine detectability of salamander eDNA in a terrestrial environment using soil, faeces, and skin swabs, (iv) detect salamander eDNA in a mesocosm experiment. Salamander eDNA was positively detected in 100% of skin swabs and 66% of faecal samples and concentrations did not differ between the two sources. However, eDNA was not detected in soil samples collected from directly underneath wild-caught living salamanders. Salamander genomic DNA (gDNA) was detected in all qPCR reactions when spiked into soil at 10.0, 5.0, and 1.0 ng/g soil and spike concentration had a significant effect on detected concentrations. Only 33% of samples showed recoverable eDNA when spiked with 0.25 ng/g soil, which was the low end of eDNA detection. To determine the rate of eDNA degradation, gDNA (1 ng/g soil) was spiked into soil and quantified over seven days. Salamander eDNA concentrations decreased across days, but eDNA was still amplifiable at day 7. Salamander eDNA was detected in two of 182 mesocosm soil samples over 12 weeks (n = 52 control samples; n = 65 presence samples; n = 65 eviction samples). The discrepancy in detection success between experiments indicates the potential challenges for this method to be used as a monitoring technique for small-bodied wild terrestrial salamander populations.

Label-Free Direct Detection of miRNAs with Poly-Silicon Nanowire Biosensors

PubMed Central

Gong, Changguo; Qi, Jiming; Xiao, Han; Jiang, Bin; Zhao, Yulan

2015-01-01

Background The diagnostic and prognostic value of microRNAs (miRNAs) in a variety of diseases is promising. The novel silicon nanowire (SiNW) biosensors have advantages in molecular detection because of their high sensitivity and fast response. In this study, poly-crystalline silicon nanowire field-effect transistor (poly-SiNW FET) device was developed to achieve specific and ultrasensitive detection of miRNAs without labeling and amplification. Methods The poly-SiNW FET was fabricated by a top–down Complementary Metal Oxide Semiconductor (CMOS) wafer fabrication based technique. Single strand DNA (ssDNA) probe was bind to the surface of the poly-SiNW device which was silanated and aldehyde-modified. By comparing the difference of resistance value before and after ssDNA and miRNA hybridization, poly-SiNW device can be used to detect standard and real miRNA samples. Results Poly-SiNW device with different structures (different line width and different pitch) was applied to detect standard Let-7b sample with a detection limitation of 1 fM. One-base mismatched sequence could be distinguished meanwhile. Furthermore, these poly-SiNW arrays can detect snRNA U6 in total RNA samples extracted from HepG2 cells with a detection limitation of 0.2 μg/mL. In general, structures with pitch showed better results than those without pitch in detection of both Let-7b and snRNA U6. Moreover, structures with smaller pitch showed better detection efficacy. Conclusion Our findings suggest that poly-SiNW arrays could detect standard and real miRNA sample without labeling or amplification. Poly-SiNW biosensor device is promising for miRNA detection. PMID:26709827

Survival of patients with symptom- and screening-detected colorectal cancer.

PubMed

Brenner, Hermann; Jansen, Lina; Ulrich, Alexis; Chang-Claude, Jenny; Hoffmeister, Michael

2016-07-12

An increasing proportion of colorectal cancer (CRC) patients are diagnosed by screening rather than symptoms. We aimed to assess and compare prognosis of patients with screen-detected CRC and symptom-detected CRC. Overall and CRC specific mortality over a median follow-up of 4.8 years was assessed according to mode of diagnosis (symptoms, screening colonoscopy, fecal occult blood test [FOBT], other) in a multi-center cohort of 2,450 CRC patients aged 50-79 years recruited in Germany in 2003-2010. 68%, 11% and 10% were detected by symptoms, screening colonoscopy and FOBT, respectively. The screen-detected cancers had a more favorable stage distribution than the symptom-detected cancers (68% versus 50% in stage I or II). Age- and sex adjusted hazard ratios (HRs) of total mortality with 95% confidence intervals (95% CIs) compared to symptom-detected cancers were 0.35 (0.24-0.50) and 0.36 (0.25-0.53) for screening colonoscopy and FOBT detected CRCs, respectively. HRs were only slightly attenuated and remained highly significant after adjustment for stage and multiple other covariates (0.50 (0.34-0.73) and 0.54 (0.37-0.80), respectively). Even stronger associations were seen for CRC specific mortality. Patients with screen-detected stage III CRC had as good CRC specific survival as patients with symptom-detected stage I or II CRC. Patients with screen-detected CRC have a very good prognosis far beyond the level explained by their more favorable stage distribution. Mode of detection is an important, easy-to-obtain proxy indicator for favorable diagnosis beyond earlier stage at diagnosis and as such may be useful for risk stratification in treatment decisions.

Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation.

PubMed

Walker, Donald M; Leys, Jacob E; Dunham, Kelly E; Oliver, Joshua C; Schiller, Emily E; Stephenson, Kelsey S; Kimrey, John T; Wooten, Jessica; Rogers, Mark W

2017-11-01

Environmental DNA (eDNA) can be used as an assessment tool to detect populations of threatened species and provide fine-scale data required to make management decisions. The objectives of this project were to use quantitative PCR (qPCR) to: (i) detect spiked salamander DNA in soil, (ii) quantify eDNA degradation over time, (iii) determine detectability of salamander eDNA in a terrestrial environment using soil, faeces, and skin swabs, (iv) detect salamander eDNA in a mesocosm experiment. Salamander eDNA was positively detected in 100% of skin swabs and 66% of faecal samples and concentrations did not differ between the two sources. However, eDNA was not detected in soil samples collected from directly underneath wild-caught living salamanders. Salamander genomic DNA (gDNA) was detected in all qPCR reactions when spiked into soil at 10.0, 5.0, and 1.0 ng/g soil and spike concentration had a significant effect on detected concentrations. Only 33% of samples showed recoverable eDNA when spiked with 0.25 ng/g soil, which was the low end of eDNA detection. To determine the rate of eDNA degradation, gDNA (1 ng/g soil) was spiked into soil and quantified over seven days. Salamander eDNA concentrations decreased across days, but eDNA was still amplifiable at day 7. Salamander eDNA was detected in two of 182 mesocosm soil samples over 12 weeks (n = 52 control samples; n = 65 presence samples; n = 65 eviction samples). The discrepancy in detection success between experiments indicates the potential challenges for this method to be used as a monitoring technique for small-bodied wild terrestrial salamander populations. © 2017 John Wiley & Sons Ltd.

Detection rates of the MODIS active fire product in the United States

USGS Publications Warehouse

Hawbaker, T.J.; Radeloff, V.C.; Syphard, A.D.; Zhu, Z.; Stewart, S.I.

2008-01-01

MODIS active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render satellite-derived fire statistics difficult to interpret. We evaluated the MODIS 1??km daily active fire product to quantify detection rates for both Terra and Aqua MODIS sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. MODIS active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one MODIS active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both Aqua and Terra were combined, 82% of all reference fires were found, but detection rates were less for Aqua and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the Aqua data were considered exclusively. MODIS detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining Aqua and Terra (195??ha for Aqua and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The MODIS active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the MODIS active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.

Long term monitoring of jaguars in the Cockscomb Basin Wildlife Sanctuary, Belize; Implications for camera trap studies of carnivores.

PubMed

Harmsen, Bart J; Foster, Rebecca J; Sanchez, Emma; Gutierrez-González, Carmina E; Silver, Scott C; Ostro, Linde E T; Kelly, Marcella J; Kay, Elma; Quigley, Howard

2017-01-01

In this study, we estimate life history parameters and abundance for a protected jaguar population using camera-trap data from a 14-year monitoring program (2002-2015) in Belize, Central America. We investigated the dynamics of this jaguar population using 3,075 detection events of 105 individual adult jaguars. Using robust design open population models, we estimated apparent survival and temporary emigration and investigated individual heterogeneity in detection rates across years. Survival probability was high and constant among the years for both sexes (φ = 0.78), and the maximum (conservative) age recorded was 14 years. Temporary emigration rate for the population was random, but constant through time at 0.20 per year. Detection probability varied between sexes, and among years and individuals. Heterogeneity in detection took the form of a dichotomy for males: those with consistently high detection rates, and those with low, sporadic detection rates, suggesting a relatively stable population of 'residents' consistently present and a fluctuating layer of 'transients'. Female detection was always low and sporadic. On average, twice as many males than females were detected per survey, and individual detection rates were significantly higher for males. We attribute sex-based differences in detection to biases resulting from social variation in trail-walking behaviour. The number of individual females detected increased when the survey period was extended from 3 months to a full year. Due to the low detection rates of females and the variable 'transient' male subpopulation, annual abundance estimates based on 3-month surveys had low precision. To estimate survival and monitor population changes in elusive, wide-ranging, low-density species, we recommend repeated surveys over multiple years; and suggest that continuous monitoring over multiple years yields even further insight into population dynamics of elusive predator populations.

Improved Automatic Detection of New T2 Lesions in Multiple Sclerosis Using Deformation Fields.

PubMed

Cabezas, M; Corral, J F; Oliver, A; Díez, Y; Tintoré, M; Auger, C; Montalban, X; Lladó, M; Pareto, D; Rovira, À

2016-06-09

Detection of disease activity, defined as new/enlarging T2 lesions on brain MR imaging, has been proposed as a biomarker in MS. However, detection of new/enlarging T2 lesions can be hindered by several factors that can be overcome with image subtraction. The purpose of this study was to improve automated detection of new T2 lesions and reduce user interaction to eliminate inter- and intraobserver variability. Multiparametric brain MR imaging was performed at 2 time points in 36 patients with new T2 lesions. Images were registered by using an affine transformation and the Demons algorithm to obtain a deformation field. After affine registration, images were subtracted and a threshold was applied to obtain a lesion mask, which was then refined by using the deformation field, intensity, and local information. This pipeline was compared with only applying a threshold, and with a state-of-the-art approach relying only on image intensities. To assess improvements, we compared the results of the different pipelines with the expert visual detection. The multichannel pipeline based on the deformation field obtained a detection Dice similarity coefficient close to 0.70, with a false-positive detection of 17.8% and a true-positive detection of 70.9%. A statistically significant correlation (r = 0.81, P value = 2.2688e-09) was found between visual detection and automated detection by using our approach. The deformation field-based approach proposed in this study for detecting new/enlarging T2 lesions resulted in significantly fewer false-positives while maintaining most true-positives and showed a good correlation with visual detection annotations. This approach could reduce user interaction and inter- and intraobserver variability. © 2016 American Society of Neuroradiology.

Power to detect trends in abundance of secretive marsh birds: effects of species traits and sampling effort

USGS Publications Warehouse

Steidl, Robert J.; Conway, Courtney J.; Litt, Andrea R.

2013-01-01

Standardized protocols for surveying secretive marsh birds have been implemented across North America, but the efficacy of surveys to detect population trends has not been evaluated. We used survey data collected from populations of marsh birds across North America and simulations to explore how characteristics of bird populations (proportion of survey stations occupied, abundance at occupied stations, and detection probability) and aspects of sampling effort (numbers of survey routes, stations/route, and surveys/station/year) affect statistical power to detect trends in abundance of marsh bird populations. In general, the proportion of survey stations along a route occupied by a species had a greater relative effect on power to detect trends than did the number of birds detected per survey at occupied stations. Uncertainty introduced by imperfect detection during surveys reduced power to detect trends considerably, but across the range of detection probabilities for most species of marsh birds, variation in detection probability had only a minor influence on power. For species that occupy a relatively high proportion of survey stations (0.20), have relatively high abundances at occupied stations (2.0 birds/station), and have high detection probability (0.50), ≥40 routes with 10 survey stations per route surveyed 3 times per year would provide an 80% chance of detecting a 3% annual decrease in abundance after 20 years of surveys. Under the same assumptions but for species that are less common, ≥100 routes would be needed to achieve the same power. Our results can help inform the design of programs to monitor trends in abundance of marsh bird populations, especially with regards to the amount of sampling effort necessary to meet programmatic goals.

Patterns and Correlates of PrEP Drug Detection among MSM and Transgender Women in the Global iPrEx Study

PubMed Central

Liu, Albert; Glidden, David V.; Anderson, Peter L.; Amico, K.R.; McMahan, Vanessa; Mehrotra, Megha; Lama, Javier R.; MacRae, John; Hinojosa, Juan Carlos; Montoya, Orlando; Veloso, Valdilea G.; Schechter, Mauro; Kallas, Esper G.; Chariyalerstak, Suwat; Bekker, Linda-Gail; Mayer, Kenneth; Buchbinder, Susan; Grant, Robert

2014-01-01

Background Adherence to pre-exposure prophylaxis (PrEP) is critical for efficacy. Antiretroviral concentrations are an objective measure of PrEP use and correlate with efficacy. Understanding patterns and correlates of drug detection can identify populations at risk for non-adherence and inform design of PrEP adherence interventions. Methods Blood antiretroviral concentrations were assessed among active-arm participants in iPrEx, a randomized, placebo-controlled trial of emtricitabine/tenofovir in men who have sex with men (MSM) and transgender women in 6 countries. We evaluated rates and correlates of drug detection among a random sample of 470 participants at week 8 and a longitudinal cohort of 303 participants through 72 weeks of follow-up. Results Overall, 55% (95% CI 49–60%) of participants tested at week 8 had drug detected. Drug detection was associated with older age and varied by study site. In longitudinal analysis, 31% never had drug detected, 30% always had drug detected, and 39% had an inconsistent pattern. Overall detection rates declined over time. Drug detection at some or all visits was associated with older age; indices of sexual risk, including condomless receptive anal sex; and responding "don't know" to a question about belief of PrEP efficacy (0–10 scale). Conclusions Distinct patterns of study-product use were identified, with a significant proportion demonstrating no drug detection at any visit. Research literacy may explain greater drug detection among populations having greater research experience, such as older MSM in the US. Greater drug detection among those reporting highest-risk sexual practices is expected to increase the impact and cost-effectiveness of PrEP. PMID:25230290

Detection of bacterial pathogens in Mongolia meningitis surveillance with a new real-time PCR assay to detect Haemophilus influenzae.

PubMed

Wang, Xin; Mair, Raydel; Hatcher, Cynthia; Theodore, M Jordan; Edmond, Karen; Wu, Henry M; Harcourt, Brian H; Carvalho, Maria da Gloria S; Pimenta, Fabiana; Nymadawa, Pagbajab; Altantsetseg, Dorjpurev; Kirsch, Mariah; Satola, Sarah W; Cohn, Amanda; Messonnier, Nancy E; Mayer, Leonard W

2011-04-01

Since the implementation of Haemophilus influenzae (Hi) serotype b vaccine, other serotypes and non-typeable strains have taken on greater importance as a cause of Hi diseases. A rapid and accurate method is needed to detect all Hi regardless of the encapsulation status. We developed 2 real-time PCR (rt-PCR) assays to detect specific regions of the protein D gene (hpd). Both hpd assays are very specific and sensitive for detection of Hi. Of the 63 non-Hi isolates representing 21 bacterial species, none was detected by the hpd #1 assay, and only one of 2 H. aphrophilus isolates was detected by the hpd #3 assay. The hpd #1 and #3 assays detected 97% (229/237) and 99% (234/237) of Hi isolates, respectively, and were superior for detection of both typeable and non-typeable Hi isolates, as compared to previously developed rt-PCR targeting ompP2 or bexA. The diagnostic sensitivity and specificity of these rt-PCR assays were assessed on cerebrospinal fluid specimens collected as part of meningitis surveillance in Ulaanbaatar, Mongolia. The etiology (Neisseria meningitidis, Hi, and Streptococcus pneumoniae) of 111 suspected meningitis cases was determined by conventional methods (culture and latex agglutination), previously developed rt-PCR assays, and the new hpd assays. The rt-PCR assays were more sensitive for detection of meningitis pathogens than other classical methods and improved detection from 50% (56/111) to 75% (83/111). The hpd #3 assay identified a non-b Hi that was missed by the bexA assay and other methods. A sensitive rt-PCR assay to detect both typeable and non-typeable Hi is a useful tool for improving Hi disease surveillance especially after Hib vaccine introduction. Published by Elsevier GmbH.

Evaluation of three read-depth based CNV detection tools using whole-exome sequencing data.

PubMed

Yao, Ruen; Zhang, Cheng; Yu, Tingting; Li, Niu; Hu, Xuyun; Wang, Xiumin; Wang, Jian; Shen, Yiping

2017-01-01

Whole exome sequencing (WES) has been widely accepted as a robust and cost-effective approach for clinical genetic testing of small sequence variants. Detection of copy number variants (CNV) within WES data have become possible through the development of various algorithms and software programs that utilize read-depth as the main information. The aim of this study was to evaluate three commonly used, WES read-depth based CNV detection programs using high-resolution chromosomal microarray analysis (CMA) as a standard. Paired CMA and WES data were acquired for 45 samples. A total of 219 CNVs (size ranged from 2.3 kb - 35 mb) identified on three CMA platforms (Affymetrix, Agilent and Illumina) were used as standards. CNVs were called from WES data using XHMM, CoNIFER, and CNVnator with modified settings. All three software packages detected an elevated proportion of small variants (< 20 kb) compared to CMA. XHMM and CoNIFER had poor detection sensitivity (22.2 and 14.6%), which correlated with the number of capturing probes involved. CNVnator detected most variants and had better sensitivity (87.7%); however, suffered from an overwhelming detection of small CNVs below 20 kb, which required further confirmation. Size estimation of variants was exaggerated by CNVnator and understated by XHMM and CoNIFER. Low concordances of CNV, detected by three different read-depth based programs, indicate the immature status of WES-based CNV detection. Low sensitivity and uncertain specificity of WES-based CNV detection in comparison with CMA based CNV detection suggests that CMA will continue to play an important role in detecting clinical grade CNV in the NGS era, which is largely based on WES.

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2002-01-01

Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.

Systematic Evaluation of In Vitro and In Vivo Adventitious Virus Assays for the Detection of Viral Contamination of Cell Banks and Biological Products1

PubMed Central

Gombold, James; Karakasidis, Stephen; Niksa, Paula; Podczasy, John; Neumann, Kitti; Richardson, James; Sane, Nandini; Johnson-Leva, Renita; Randolph, Valerie; Sadoff, Jerald; Minor, Phillip; Schmidt, Alexander; Duncan, Paul; Sheets, Rebecca L.

2015-01-01

Viral vaccines and the cell substrates used to manufacture them are subjected to tests for adventitious agents, including viruses, which might contaminant them. Some of the compendial methods (in vivo and in vitro in cell culture) were established in the mid-20th century. These methods have not been subjected to current assay validation, as new methods would need to be. This study was undertaken to provide insight into the breadth (selectivity) and sensitivity (limit of detection) of the routine methods, two such validation parameters. Sixteen viral stocks were prepared and characterized. These stocks were tested in serial dilutions by the routine methods to establish which viruses were detected by which methods and above what limit of detection. Sixteen out of sixteen viruses were detected in vitro, though one (bovine viral diarrhea virus) required special conditions to detect and another (rubella virus) was detected with low sensitivity. Many were detected at levels below 1 TCID50 or PFU (titers were established on the production cell line in most cases). In contrast, in vivo, only 6/11 viruses were detected, and 4 of these were detected only at amounts one or more logs above 1 TCID50 or PFU. Only influenza virus and vesicular stomatitis virus were detected at lower amounts in vivo than in vitro. Given the call to reduce, refine, or replace (3 R's) the use of animals in product safety testing and the emergence of new technologies for the detection of viruses, a re-examination of the current adventitious virus testing strategies seems warranted. Suggested pathways forward are offered. PMID:24681273

Occurrence and concentrations of pharmaceutical compounds in deep groundwater used for public drinking-water supply in California

USGS Publications Warehouse

Fram, Miranda S.; Belitz, Kenneth

2011-01-01

Pharmaceutical compounds were detected at low concentrations in 2.3% of 1231 samples of groundwater (median depth to top of screened interval in wells = 61 m) used for public drinking-water supply in California. Samples were collected statewide for the California State Water Resources Control Board's Groundwater Ambient Monitoring and Assessment (GAMA) Program. Of 14 pharmaceutical compounds analyzed, 7 were detected at concentrations greater than or equal to method detection limits: acetaminophen (used as an analgesic, detection frequency 0.32%, maximum concentration 1.89 μg/L), caffeine (stimulant, 0.24%, 0.29 μg/L), carbamazepine (mood stabilizer, 1.5%, 0.42 μg/L), codeine (opioid analgesic, 0.16%, 0.214 μg/L), p-xanthine (caffeine metabolite, 0.08%, 0.12 μg/L), sulfamethoxazole (antibiotic, 0.41%, 0.17 μg/L), and trimethoprim (antibiotic, 0.08%, 0.018 μg/L). Detection frequencies of pesticides (33%), volatile organic compounds not including trihalomethanes (23%), and trihalomethanes (28%) in the same 1231 samples were significantly higher. Median detected concentration of pharmaceutical compounds was similar to those of volatile organic compounds, and higher than that of pesticides. Pharmaceutical compounds were detected in 3.3% of the 855 samples containing modern groundwater (tritium activity > 0.2 TU). Pharmaceutical detections were significantly positively correlated with detections of urban-use herbicides and insecticides, detections of volatile organic compounds, and percentage of urban land use around wells. Groundwater from the Los Angeles metropolitan area had higher detection frequencies of pharmaceuticals and other anthropogenic compounds than groundwater from other areas of the state with similar proportions of urban land use. The higher detection frequencies may reflect that groundwater flow systems in Los Angeles area basins are dominated by engineered recharge and intensive groundwater pumping.

COMPARISON BETWEEN COMPUTED TOMOGRAPHIC ARTHROGRAPHY, RADIOGRAPHY, ULTRASONOGRAPHY, AND ARTHROSCOPY FOR THE DIAGNOSIS OF FEMOROTIBIAL JOINT DISEASE IN WESTERN PERFORMANCE HORSES.

PubMed

Nelson, Brad B; Kawcak, Chris E; Goodrich, Laurie R; Werpy, Natasha M; Valdés-Martínez, Alejandro; McIlwraith, C Wayne

2016-07-01

The femorotibial joints are a common source of lameness in Western performance horses. The objective of this prospective study was to compare the radiography, ultrasonography, computed tomographic arthrography (CTA), and arthroscopy findings in horses with lameness localized to the femorotibial joints. Twenty-five stifles in 24 horses were included and were evaluated with all four of these diagnostic methods. Defects detected in femorotibial joint structures were compared between diagnostic methods using a McNemar's test to evaluate for disagreement. Cranial medial meniscotibial desmopathy was most detected on arthroscopy (in 14/25 cases) and was only detected on ultrasonography in three out of 11 (27.3%) arthroscopically observed cases, but was detected on CTA in nine out of 12 (75%) arthroscopically observed cases. Medial meniscal injury located on the craniolateral border was most detected on arthroscopy (n = 9) and was detected on CTA in five cases, but on ultrasonography in 0 cases. Detection of articular cartilage defects on the medial femoral condyle was most detected with arthroscopy (24/25, 96% cases) and was also detected on CTA in 12/20 (60%) cases with a significant disagreement identified between modalities (P = 0.02). Cranial and caudal cruciate ligament defects were detected on CTA in 6/22 (27.3%) and 7/19 (36.8%) cases, respectively, and with arthroscopy in 3/25 (12%) and 2/25 (8%) cases, respectively. The use of CTA detected more defects in the cruciate ligaments, proximal tibia, and ligament entheses than the other diagnostic methods, but was not reliable for detection of articular cartilage damage on the medial femoral condyle. © 2016 American College of Veterinary Radiology.

A Study of Dim Object Detection for the Space Surveillance Telescope

DTIC Science & Technology

2013-03-21

ENG-13-M-32 Abstract Current methods of dim object detection for space surveillance make use of a Gaussian log-likelihood-ratio-test-based...quantitatively comparing the efficacy of two methods for dim object detection , termed in this paper the point detector and the correlator, both of which rely... applications . It is used in national defense for detecting satellites. It is used to detecting space debris, which threatens both civilian and

A preliminary evaluation of a failure detection filter for detecting and identifying control element failures in a transport aircraft

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1985-01-01

The application of the failure detection filter to the detection and identification of aircraft control element failures was evaluated in a linear digital simulation of the longitudinal dynamics of a B-737 Aircraft. Simulation results show that with a simple correlator and threshold detector used to process the filter residuals, the failure detection performance is seriously degraded by the effects of turbulence.

Ricin detection: tracking active toxin.

PubMed

Bozza, William P; Tolleson, William H; Rivera Rosado, Leslie A; Zhang, Baolin

2015-01-01

Ricin is a plant toxin with high bioterrorism potential due to its natural abundance and potency in inducing cell death. Early detection of the active toxin is essential for developing appropriate countermeasures. Here we review concepts for designing ricin detection methods, including mechanism of action of the toxin, advantages and disadvantages of current detection assays, and perspectives on the future development of rapid and reliable methods for detecting ricin in environmental samples. Published by Elsevier Inc.

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

DTIC Science & Technology

2010-01-01

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

Procedure for flaw detection in cast stainless steel

DOEpatents

Kupperman, David S.

1988-01-01

A method of ultrasonic flaw detection in cast stainless steel components incorporating the steps of determining the nature of the microstructure of the cast stainless steel at the site of the flaw detection measurements by ultrasonic elements independent of the component thickness at the site; choosing from a plurality of flaw detection techniques, one such technique appropriate to the nature of the microstructure as determined and detecting flaws by use of the chosen technique.

Assessment of soil-gas contamination at three former fuel-dispensing sites, Fort Gordon, Georgia, 2010—2011

USGS Publications Warehouse

Caldwell, Andral W.; Falls, W. Fred; Guimaraes, Wladmir B.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2012-01-01

Soil gas was assessed for contaminants at three former fuel-dispensing sites at Fort Gordon, Georgia, from October 2010 to September 2011. The assessment included delineation of organic contaminants using soil-gas samplers collected from the former fuel-dispensing sites at 8th Street, Chamberlain Avenue, and 12th Street. This assessment was conducted to provide environmental contamination data to Fort Gordon personnel pursuant to requirements for the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Soil-gas samplers installed and retrieved during June and August 2011 at the 8th Street site had detections above the method detection level (MDL) for the mass of total petroleum hydrocarbons (TPH), benzene, toluene, ortho-xylene, undecane, tridecane, pentadecane, and chloroform. Total petroleum hydrocarbons soil-gas mass exceeded the MDL of 0.02 microgram in 54 of the 55 soil-gas samplers. The highest detection of TPH soil-gas mass was 146.10 micrograms, located in the central part of the site. Benzene mass exceeded the MDL of 0.01 microgram in 23 soil-gas samplers, whereas toluene was detected in only 10 soil-gas samplers. Ortho-xylene was detected above the MDL in only one soil-gas sampler. The highest soil-gas mass detected for undecane, tridecane, and pentadecane was located in the northeastern corner of the 8th Street site. Chloroform mass greater than the MDL of 0.01 microgram was detected in less than one-third of the soil-gas samplers. Soil-gas masses above the MDL were identified for TPH, gasoline-related compounds, diesel-range alkanes, trimethylbenzenes, naphthalene, 2-methyl-napthalene, octane, and tetrachloroethylene for the July 2011 soil-gas survey at the Chamberlain Avenue site. All 30 of the soil-gas samplers contained TPH mass above the MDL. The highest detection of TPH mass, 426.36 micrograms, was for a soil-gas sampler located near the northern boundary of the site. Gasoline-related compounds and diesel-range alkanes were detected in multiple soil-gas samplers, and the highest detections of these compounds were located near the central part of the site near existing, nonoperational, fuel-dispensing pumps. Trimethylbenzenes were detected in less than half of the soil-gas samplers. Naphthalene soil-gas mass was detected above the MDL in 10 soil-gas samplers, whereas 2-methyl-napthalene was detected above the MDL in half of the soil-gas samplers. Octane mass was detected above the MDL in one soil-gas sampler located near the central part of the site. Tetrachloroethylene soil-gas mass was detected above the MDL in more than half of the soil-gas samplers, and the highest tetrachloroethylene soil-gas mass of 0.90 microgram was located in the northeastern part of the site. Soil-gas samplers collected at the 12th Street site during July 2011 contained soil-gas mass above the MDL for TPH, toluene, undecane, tridecane, and pentadecane (diesel-range alkanes), trichloroethylene, 1,4-dichlorobenzene, chloroform, and 1,2,4-trimethylbenzene. The highest detected TPH mass was 24.37 micrograms in a soil-gas sampler located in the northern part of the site. The highest detection of toluene soil-gas mass was from a soil-gas sampler located near the southern boundary of the site. The diesel-range alkanes were detected above the MDL in five soil-gas samplers; the highest detection of soil-gas diesel mass, 0.65 microgram, was located in the southern part of the site. Trichloroethylene and 1,4-dichlorobenzene were detected above the MDL in the northern part of the site in one soil-gas sampler that also had one of the highest detections of TPH. Chloroform was detected above the MDL in three soil-gas samplers, whereas 1,2,4-trimethylbenzene soil-gas mass was detected above the MDL in two soil-gas samplers.

Automated methods for multiplexed pathogen detection.

PubMed

Straub, Timothy M; Dockendorff, Brian P; Quiñonez-Díaz, Maria D; Valdez, Catherine O; Shutthanandan, Janani I; Tarasevich, Barbara J; Grate, Jay W; Bruckner-Lea, Cynthia J

2005-09-01

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cycler where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides "live vs. dead" capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.

Detection of atrial fibrillation and flutter by a dual-chamber implantable cardioverter-defibrillator. For the Worldwide Jewel AF Investigators.

PubMed

Swerdlow, C D; Schsls, W; Dijkman, B; Jung, W; Sheth, N V; Olson, W H; Gunderson, B D

2000-02-29

To distinguish prolonged episodes of atrial fibrillation (AF) that require cardioversion from self-terminating episodes that do not, an atrial implantable cardioverter-defibrillator (ICD) must be able to detect AF continuously for extended periods. The ICD should discriminate between atrial tachycardia/flutter (AT), which may be terminated by antitachycardia pacing, and AF, which requires cardioversion. We studied 80 patients with AT/AF and ventricular arrhythmias who were treated with a new atrial/dual-chamber ICD. During a follow-up period lasting 6+/-2 months, we validated spontaneous, device-defined AT/AF episodes by stored electrograms in all patients. In 58 patients, we performed 80 Holter recordings with telemetered atrial electrograms, both to validate the continuous detection of AT/AF and to determine the sensitivity of the detection of AT/AF. Detection was appropriate in 98% of 132 AF episodes and 88% of 190 AT episodes (98% of 128 AT episodes with an atrial cycle length <300 ms). Intermittent sensing of far-field R waves during sinus tachycardia caused 27 inappropriate AT/AF detections; these detections lasted 2.6+/-2.0 minutes. AT/AF was detected continuously in 27 of 28 patients who had spontaneous episodes of AT/AF (96%). The device memory recorded 90 appropriate AT/AF episodes lasting >1 hour, for a total of 2697 hours of continuous detection of AT/AF. During Holter monitoring, the sensitivity of the detection of AT/AF (116 hours) was 100%; the specificity of the detection of non-AT/AF rhythms (1290 hours) was 99.99%. Of 166 appropriate episodes detected as AT, 45% were terminated by antitachycardia pacing. A new ICD detects AT/AF accurately and continuously. Therapy may be programmed for long-duration AT/AF, with a low risk of underdetection. Discrimination of AT from AF permits successful pacing therapy for a significant fraction of AT.

Assessing environmental DNA detection in controlled lentic systems.

PubMed

Moyer, Gregory R; Díaz-Ferguson, Edgardo; Hill, Jeffrey E; Shea, Colin

2014-01-01

Little consideration has been given to environmental DNA (eDNA) sampling strategies for rare species. The certainty of species detection relies on understanding false positive and false negative error rates. We used artificial ponds together with logistic regression models to assess the detection of African jewelfish eDNA at varying fish densities (0, 0.32, 1.75, and 5.25 fish/m3). Our objectives were to determine the most effective water stratum for eDNA detection, estimate true and false positive eDNA detection rates, and assess the number of water samples necessary to minimize the risk of false negatives. There were 28 eDNA detections in 324, 1-L, water samples collected from four experimental ponds. The best-approximating model indicated that the per-L-sample probability of eDNA detection was 4.86 times more likely for every 2.53 fish/m3 (1 SD) increase in fish density and 1.67 times less likely for every 1.02 C (1 SD) increase in water temperature. The best section of the water column to detect eDNA was the surface and to a lesser extent the bottom. Although no false positives were detected, the estimated likely number of false positives in samples from ponds that contained fish averaged 3.62. At high densities of African jewelfish, 3-5 L of water provided a >95% probability for the presence/absence of its eDNA. Conversely, at moderate and low densities, the number of water samples necessary to achieve a >95% probability of eDNA detection approximated 42-73 and >100 L, respectively. Potential biases associated with incomplete detection of eDNA could be alleviated via formal estimation of eDNA detection probabilities under an occupancy modeling framework; alternatively, the filtration of hundreds of liters of water may be required to achieve a high (e.g., 95%) level of certainty that African jewelfish eDNA will be detected at low densities (i.e., <0.32 fish/m3 or 1.75 g/m3).

Environmental DNA (eDNA) Sampling Improves Occurrence and Detection Estimates of Invasive Burmese Pythons

PubMed Central

Hunter, Margaret E.; Oyler-McCance, Sara J.; Dorazio, Robert M.; Fike, Jennifer A.; Smith, Brian J.; Hunter, Charles T.; Reed, Robert N.; Hart, Kristen M.

2015-01-01

Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models. PMID:25874630

Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys.

PubMed

Murn, Campbell; Holloway, Graham J

2016-10-01

Species occurring at low density can be difficult to detect and if not properly accounted for, imperfect detection will lead to inaccurate estimates of occupancy. Understanding sources of variation in detection probability and how they can be managed is a key part of monitoring. We used sightings data of a low-density and elusive raptor (white-headed vulture Trigonoceps occipitalis ) in areas of known occupancy (breeding territories) in a likelihood-based modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model occupancy parameter to 1.0 and focused on identifying sources of variation in detection probability. Using detection histories from 359 territory visits, we assessed nine covariates in 29 candidate models. The model with the highest support indicated that observer speed during a survey, combined with temporal covariates such as time of year and length of time within a territory, had the highest influence on the detection probability. Averaged detection probability was 0.207 (s.e. 0.033) and based on this the mean number of visits required to determine within 95% confidence that white-headed vultures are absent from a breeding area is 13 (95% CI: 9-20). Topographical and habitat covariates contributed little to the best models and had little effect on detection probability. We highlight that low detection probabilities of some species means that emphasizing habitat covariates could lead to spurious results in occupancy models that do not also incorporate temporal components. While variation in detection probability is complex and influenced by effects at both temporal and spatial scales, temporal covariates can and should be controlled as part of robust survey methods. Our results emphasize the importance of accounting for detection probability in occupancy studies, particularly during presence/absence studies for species such as raptors that are widespread and occur at low densities.

Hepatocellular Carcinoma Screening Associated with Early Tumor Detection and Improved Survival Among Patients with Cirrhosis in the US.

PubMed

Singal, Amit G; Mittal, Sahil; Yerokun, Olutola A; Ahn, Chul; Marrero, Jorge A; Yopp, Adam C; Parikh, Neehar D; Scaglione, Steve J

2017-09-01

Professional societies recommend hepatocellular carcinoma screening in patients with cirrhosis, but high-quality data evaluating its effectiveness to improve early tumor detection and survival in "real world" clinical practice are needed. We aim to characterize the association between hepatocellular carcinoma screening and early tumor detection, curative treatment, and overall survival among patients with cirrhosis. We performed a retrospective cohort study of patients diagnosed with hepatocellular carcinoma between June 2012 and May 2013 at 4 health systems in the US. Patients were categorized in the screening group if hepatocellular carcinoma was detected by imaging performed for screening purposes. Generalized linear models and multivariate Cox regression with frailty adjustment were used to compare early detection, curative treatment, and survival between screen-detected and non-screen-detected patients. Among 374 hepatocellular carcinoma patients, 42% (n = 157) were detected by screening. Screen-detected patients had a significantly higher proportion of early tumors (Barcelona Clinic Liver Cancer stage A 63.1% vs 36.4%, P <.001) and were more likely to undergo curative treatment (31% vs 13%, P = .02). Hepatocellular carcinoma screening was significantly associated with improved survival in multivariate analysis (hazards ratio 0.41; 95% confidence interval, 0.26-0.65) after adjusting for patient demographics, Child-Pugh class, and performance status. Median survival of screen-detected patients was 14.6 months, compared with 6.0 months for non-screen-detected patients, with the difference remaining significant after adjusting for lead-time bias (hazards ratio 0.59, 95% confidence interval, 0.37-0.93). Hepatocellular carcinoma screening is associated with increased early tumor detection and improved survival; however, a minority of hepatocellular carcinoma patients are detected by screening. Interventions to increase screening use in patients with cirrhosis may help curb hepatocellular carcinoma mortality rates. Copyright © 2017 Elsevier Inc. All rights reserved.

Algorithms for Autonomous Plume Detection on Outer Planet Satellites

NASA Astrophysics Data System (ADS)

Lin, Y.; Bunte, M. K.; Saripalli, S.; Greeley, R.

2011-12-01

We investigate techniques for automated detection of geophysical events (i.e., volcanic plumes) from spacecraft images. The algorithms presented here have not been previously applied to detection of transient events on outer planet satellites. We apply Scale Invariant Feature Transform (SIFT) to raw images of Io and Enceladus from the Voyager, Galileo, Cassini, and New Horizons missions. SIFT produces distinct interest points in every image; feature descriptors are reasonably invariant to changes in illumination, image noise, rotation, scaling, and small changes in viewpoint. We classified these descriptors as plumes using the k-nearest neighbor (KNN) algorithm. In KNN, an object is classified by its similarity to examples in a training set of images based on user defined thresholds. Using the complete database of Io images and a selection of Enceladus images where 1-3 plumes were manually detected in each image, we successfully detected 74% of plumes in Galileo and New Horizons images, 95% in Voyager images, and 93% in Cassini images. Preliminary tests yielded some false positive detections; further iterations will improve performance. In images where detections fail, plumes are less than 9 pixels in size or are lost in image glare. We compared the appearance of plumes and illuminated mountain slopes to determine the potential for feature classification. We successfully differentiated features. An advantage over other methods is the ability to detect plumes in non-limb views where they appear in the shadowed part of the surface; improvements will enable detection against the illuminated background surface where gradient changes would otherwise preclude detection. This detection method has potential applications to future outer planet missions for sustained plume monitoring campaigns and onboard automated prioritization of all spacecraft data. The complementary nature of this method is such that it could be used in conjunction with edge detection algorithms to increase effectiveness. We have demonstrated an ability to detect transient events above the planetary limb and on the surface and to distinguish feature classes in spacecraft images.

Moving human full body and body parts detection, tracking, and applications on human activity estimation, walking pattern and face recognition

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2016-05-01

We have developed a new way for detection and tracking of human full-body and body-parts with color (intensity) patch morphological segmentation and adaptive thresholding for security surveillance cameras. An adaptive threshold scheme has been developed for dealing with body size changes, illumination condition changes, and cross camera parameter changes. Tests with the PETS 2009 and 2014 datasets show that we can obtain high probability of detection and low probability of false alarm for full-body. Test results indicate that our human full-body detection method can considerably outperform the current state-of-the-art methods in both detection performance and computational complexity. Furthermore, in this paper, we have developed several methods using color features for detection and tracking of human body-parts (arms, legs, torso, and head, etc.). For example, we have developed a human skin color sub-patch segmentation algorithm by first conducting a RGB to YIQ transformation and then applying a Subtractive I/Q image Fusion with morphological operations. With this method, we can reliably detect and track human skin color related body-parts such as face, neck, arms, and legs. Reliable body-parts (e.g. head) detection allows us to continuously track the individual person even in the case that multiple closely spaced persons are merged. Accordingly, we have developed a new algorithm to split a merged detection blob back to individual detections based on the detected head positions. Detected body-parts also allow us to extract important local constellation features of the body-parts positions and angles related to the full-body. These features are useful for human walking gait pattern recognition and human pose (e.g. standing or falling down) estimation for potential abnormal behavior and accidental event detection, as evidenced with our experimental tests. Furthermore, based on the reliable head (face) tacking, we have applied a super-resolution algorithm to enhance the face resolution for improved human face recognition performance.

Serrated and adenomatous polyp detection increases with longer withdrawal time: results from the New Hampshire Colonoscopy Registry.

PubMed

Butterly, Lynn; Robinson, Christina M; Anderson, Joseph C; Weiss, Julia E; Goodrich, Martha; Onega, Tracy L; Amos, Christopher I; Beach, Michael L

2014-03-01

Detection and removal of adenomas and clinically significant serrated polyps (CSSPs) is critical to the effectiveness of colonoscopy in preventing colorectal cancer. Although longer withdrawal time has been found to increase polyp detection, this association and the use of withdrawal time as a quality indicator remains controversial. Few studies have reported on withdrawal time and serrated polyp detection. Using data from the New Hampshire Colonoscopy Registry, we examined how an endoscopist's withdrawal time in normal colonoscopies affects adenoma and serrated polyp detection. We analyzed 7,996 colonoscopies performed in 7,972 patients between 2009 and 2011 by 42 endoscopists at 14 hospitals, ambulatory surgery centers, and community practices. CSSPs were defined as sessile serrated polyps and hyperplastic polyps proximal to the sigmoid. Adenoma and CSSP detection rates were calculated based on median endoscopist withdrawal time in normal exams. Regression models were used to estimate the association of increased normal withdrawal time and polyp, adenoma, and CSSP detection. Polyp and adenoma detection rates were highest among endoscopists with 9 min median normal withdrawal time, and detection of CSSPs reached its highest levels at 8-9 min. Incident rate ratios for adenoma and CSSP detection increased with each minute of normal withdrawal time above 6 min, with maximum benefit at 9 min for adenomas (1.50, 95% confidence interval (CI) (1.21, 1.85)) and CSSPs (1.77, 95% CI (1.15, 2.72)). When modeling was used to set the minimum withdrawal time at 9 min, we predicted that adenomas and CSSPs would be detected in 302 (3.8%) and 191 (2.4%) more patients. The increase in detection was most striking for the CSSPs, with nearly a 30% relative increase. A withdrawal time of 9 min resulted in a statistically significant increase in adenoma and serrated polyp detection. Colonoscopy quality may improve with a median normal withdrawal time benchmark of 9 min.

An ultrasensitive alloyed near-infrared quinternary quantum dot-molecular beacon nanodiagnostic bioprobe for influenza virus RNA.

PubMed

Adegoke, Oluwasesan; Kato, Tatsuya; Park, Enoch Y

2016-06-15

Conventional techniques used to diagnose influenza virus face several challenges, such as low sensitivity, slow detection, false positive results and misinterpreted data. Hence, diagnostic probes that can offer robust detection qualities, such as high sensitivity, rapid detection, elimination of false positive data, and specificity for influenza virus, are urgently needed. The near-infrared (NIR) range is an attractive spectral window due to low photon absorption by biological tissues, hence well-constructed fluorescent biosensors that emit within the NIR window can offer an improved limit of detection (LOD). Here, we demonstrate the use of a newly synthesized NIR quinternary alloyed CdZnSeTeS quantum dots (QDs) as an ultrasensitive fluorescence reporter in a conjugated molecular beacon (MB) assay to detect extremely low concentrations of influenza virus H1N1 RNA. Under optimum conditions, two different strains of influenza virus H1N1 RNA were detected based on fluorescence enhancement signal transduction. We successfully discriminated between two different strains of influenza virus H1N1 RNA based on the number of complementary nucleotide base pairs of the MB to the target RNA sequence. The merits of our bioprobe system are rapid detection, high sensitivity (detects H1N1 viral RNA down to 2 copies/mL), specificity and versatility (detects H1N1 viral RNA in human serum). For comparison, a conventional CdSe/ZnS-MB probe could not detect the extremely low concentrations of H1N1 viral RNA detected by our NIR alloyed CdZnSeTeS-MB probe. Our bioprobe detection system produced a LOD as low as ~1 copy/mL and is more sensitive than conventional molecular tests and rapid influenza detection tests (RIDTS) probes. Copyright © 2016 Elsevier B.V. All rights reserved.

Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive Burmese pythons

USGS Publications Warehouse

Hunter, Margaret E.; Oyler-McCance, Sara J.; Dorazio, Robert M.; Fike, Jennifer A.; Smith, Brian J.; Hunter, Charles T.; Reed, Robert N.; Hart, Kristen M.

2015-01-01

Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models.

VIRAL LOAD AND SHORT-TERM NATURAL HISTORY OF TYPE-SPECIFIC ONCOGENIC HUMAN PAPILLOMAVIRUS INFECTIONS IN A HIGH-RISK COHORT OF MID-ADULT WOMEN

PubMed Central

Winer, Rachel L.; Xi, Long Fu; Shen, Zhenping; Stern, Joshua E.; Newman, Laura; Feng, Qinghua; Hughes, James P.; Koutsky, Laura A.

2013-01-01

Oncogenic human papillomavirus (HPV) viral load may inform the origin of newly detected infections and characterize oncogenic HPV natural history in mid-adult women. From 2007–2011, we enrolled 521 25–65 year old female online daters and followed them triannually with mailed health and sexual behavior questionnaires and kits for self-sampling for PCR-based HPV DNA testing. Samples from oncogenic HPV positive women were selected for type-specific DNA load testing by real-time PCR with adjustment for cellularity. Linear or logistic regression models were used to evaluate relationships between viral levels, health and sexual behavior, and longitudinal oncogenic HPV detection. Type-specific viral levels were borderline significantly higher in oncogenic HPV infections that were prevalent versus newly detected (p=0.092), but levels in newly detected infections were higher than in infections re-detected after intercurrent negativity (p<.001). Recent sex partners were not significantly associated with viral levels. Compared to prevalent infections detected intermittently, the likelihood of persistent (OR=4.31,95%CI:2.20–8.45) or single-time (OR=1.32,95%CI:1.03–1.71) detection increased per 1-unit increase in baseline log10 viral load. Viral load differences between re-detected and newly detected infections suggest a portion of new detections were due to new acquisition, although report of recent new sex partners (a potential marker of new infection) was not predictive of viral load; oncogenic HPV infections in mid-adult women with new partners likely represent a mix of new acquisition and reactivation or intermittent detection of previous infection. Intermittent detection was characterized by low viral levels, suggesting that intermittent detection of persisting oncogenic HPV infection may be of limited clinical significance PMID:24136492

A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings

NASA Astrophysics Data System (ADS)

Liang, Sheng-Fu; Chen, Yi-Chun; Wang, Yu-Lin; Chen, Pin-Tzu; Yang, Chia-Hsiang; Chiueh, Herming

2013-08-01

Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short detection latency, and (4) energy-efficient design for hardware implementation.

First Results of Using a UVTron Flame Sensor to Detect Alpha-Induced Air Fluorescence in the UVC Wavelength Range.

PubMed

Crompton, Anita J; Gamage, Kelum A A; Bell, Steven; Wilson, Andrew P; Jenkins, Alex; Trivedi, Divyesh

2017-11-29

In this work, a robust stand-off alpha detection method using the secondary effects of alpha radiation has been sought. Alpha particles ionise the surrounding atmosphere as they travel. Fluorescence photons produced as a consequence of this can be used to detect the source of the alpha emissions. This paper details experiments carried out to detect this fluorescence, with the focus on photons in the ultraviolet C (UVC) wavelength range (180-280 nm). A detector, UVTron R9533 (Hamamatsu, 325-6, Sunayama-cho, Naka-ku, Hamamatsu City, Shizuoka Pref., 430-8587, Japan), designed to detect the UVC emissions from flames for fire alarm purposes, was tested in various gas atmospheres with a 210 Po alpha source to determine if this could provide an avenue for stand-off alpha detection. The results of the experiments show that this detector is capable of detecting alpha-induced air fluorescence in normal indoor lighting conditions, as the interference from daylight and artificial lighting is less influential on this detection system which operates below the UVA and UVB wavelength ranges (280-315 nm and 315-380 nm respectively). Assuming a standard 1 r 2 drop off in signal, the limit of detection in this configuration can be calculated to be approximately 240 mm, well beyond the range of alpha-particles in air, which indicates that this approach could have potential for stand-off alpha detection. The gas atmospheres tested produced an increase in the detector count, with xenon having the greatest effect with a measured 52% increase in the detector response in comparison to the detector response in an air atmosphere. This type of alpha detection system could be operated at a distance, where it would potentially provide a more cost effective, safer, and faster solution in comparison with traditional alpha detection methods to detect and characterise alpha contamination in nuclear decommissioning and security applications.

Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive burmese pythons.

PubMed

Hunter, Margaret E; Oyler-McCance, Sara J; Dorazio, Robert M; Fike, Jennifer A; Smith, Brian J; Hunter, Charles T; Reed, Robert N; Hart, Kristen M

2015-01-01

Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models.

First Results of Using a UVTron Flame Sensor to Detect Alpha-Induced Air Fluorescence in the UVC Wavelength Range

PubMed Central

Crompton, Anita J.; Wilson, Andrew P.; Jenkins, Alex; Trivedi, Divyesh

2017-01-01

In this work, a robust stand-off alpha detection method using the secondary effects of alpha radiation has been sought. Alpha particles ionise the surrounding atmosphere as they travel. Fluorescence photons produced as a consequence of this can be used to detect the source of the alpha emissions. This paper details experiments carried out to detect this fluorescence, with the focus on photons in the ultraviolet C (UVC) wavelength range (180–280 nm). A detector, UVTron R9533 (Hamamatsu, 325-6, Sunayama-cho, Naka-ku, Hamamatsu City, Shizuoka Pref., 430-8587, Japan), designed to detect the UVC emissions from flames for fire alarm purposes, was tested in various gas atmospheres with a 210Po alpha source to determine if this could provide an avenue for stand-off alpha detection. The results of the experiments show that this detector is capable of detecting alpha-induced air fluorescence in normal indoor lighting conditions, as the interference from daylight and artificial lighting is less influential on this detection system which operates below the UVA and UVB wavelength ranges (280–315 nm and 315–380 nm respectively). Assuming a standard 1r2 drop off in signal, the limit of detection in this configuration can be calculated to be approximately 240 mm, well beyond the range of alpha-particles in air, which indicates that this approach could have potential for stand-off alpha detection. The gas atmospheres tested produced an increase in the detector count, with xenon having the greatest effect with a measured 52% increase in the detector response in comparison to the detector response in an air atmosphere. This type of alpha detection system could be operated at a distance, where it would potentially provide a more cost effective, safer, and faster solution in comparison with traditional alpha detection methods to detect and characterise alpha contamination in nuclear decommissioning and security applications. PMID:29186051

TU-G-BRD-01: Quantifying the Effectiveness of the Physics Pre-Treatment Plan Review for Detecting Errors in Radiation Therapy

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

Gopan, O; Novak, A; Zeng, J

Purpose: Physics pre-treatment plan review is crucial to safe radiation oncology treatments. Studies show that most errors originate in treatment planning, which underscores the importance of physics plan review. As a QA measure the physics review is of fundamental importance and is central to the profession of medical physics. However, little is known about its effectiveness. More hard data are needed. The purpose of this study was to quantify the effectiveness of physics review with the goal of improving it. Methods: This study analyzed 315 “potentially serious” near-miss incidents within an institutional incident learning system collected over a two-year period.more » 139 of these originated prior to physics review and were found at the review or after. Incidents were classified as events that: 1)were detected by physics review, 2)could have been detected (but were not), and 3)could not have been detected. Category 1 and 2 events were classified by which specific check (within physics review) detected or could have detected the event. Results: Of the 139 analyzed events, 73/139 (53%) were detected or could have been detected by the physics review; although, 42/73 (58%) were not actually detected. 45/73 (62%) errors originated in treatment planning, making physics review the first step in the workflow that could detect the error. Two specific physics checks were particularly effective (combined effectiveness of >20%): verifying DRRs (8/73) and verifying isocenter (7/73). Software-based plan checking systems were evaluated and found to have potential effectiveness of 40%. Given current data structures, software implementations of some tests such as isocenter verification check would be challenging. Conclusion: Physics plan review is a key safety measure and can detect majority of reported events. However, a majority of events that potentially could have been detected were NOT detected in this study, indicating the need to improve the performance of physics review.« less

Automated Methods for Multiplexed Pathogen Detection

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

Straub, Tim M.; Dockendorff, Brian P.; Quinonez-Diaz, Maria D.

2005-09-01

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cyclermore » where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides ''live vs. dead'' capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.« less

49 CFR 195.444 - CPM leak detection.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 3 2010-10-01 2010-10-01 false CPM leak detection. 195.444 Section 195.444... PIPELINE Operation and Maintenance § 195.444 CPM leak detection. Each computational pipeline monitoring (CPM) leak detection system installed on a hazardous liquid pipeline transporting liquid in single...

Reducing impaired-driving recidivism using advanced vehicle-based alcohol detection systems : a report to Congress

DOT National Transportation Integrated Search

2007-12-01

Vehicle-based alcohol detection systems use technologies designed to detect the presence of alcohol in a driver. Technology suitable for use in all vehicles that will detect an impaired driver faces many challenges including public acceptability, pas...

77 FR 39498 - Guidances for Industry and Food and Drug Administration Staff: Computer-Assisted Detection...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-03

...] Guidances for Industry and Food and Drug Administration Staff: Computer-Assisted Detection Devices Applied... Clinical Performance Assessment: Considerations for Computer-Assisted Detection Devices Applied to... guidance, entitled ``Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device...

Bed bug detection: Current technologies and future directions

USDA-ARS?s Scientific Manuscript database

This study evaluates current technologies used to detect bed bug infestations, and presents new information regarding the underlying chemical basis of canines scent detection. The manuscript also reports new and future devices that may play a part in bed bug detection in the future....

Detection of entrapped moisture in honeycomb sandwich structures

NASA Technical Reports Server (NTRS)

Hallmark, W. B.

1967-01-01

Thermal neutron moisture detection system detects entrapped moisture in intercellular areas of bonded honeycomb sandwich structures. A radium/beryllium fast neutron source bombards a specimen. The emitted thermal neutrons from the target nucleus are detected and counted by a boron trifluoride thermal neutron detector.

Active Detection for Exposing Intelligent Attacks in Control Systems

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

Weerakkody, Sean; Ozel, Omur; Griffioen, Paul

In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detectmore » the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.« less

Automated seizure detection systems and their effectiveness for each type of seizure.

PubMed

Ulate-Campos, A; Coughlin, F; Gaínza-Lein, M; Fernández, I Sánchez; Pearl, P L; Loddenkemper, T

2016-08-01

Epilepsy affects almost 1% of the population and most of the approximately 20-30% of patients with refractory epilepsy have one or more seizures per month. Seizure detection devices allow an objective assessment of seizure frequency and a treatment tailored to the individual patient. A rapid recognition and treatment of seizures through closed-loop systems could potentially decrease morbidity and mortality in epilepsy. However, no single detection device can detect all seizure types. Therefore, the choice of a seizure detection device should consider the patient-specific seizure semiologies. This review of the literature evaluates seizure detection devices and their effectiveness for different seizure types. Our aim is to summarize current evidence, offer suggestions on how to select the most suitable seizure detection device for each patient and provide guidance to physicians, families and researchers when choosing or designing seizure detection devices. Further, this review will guide future prospective validation studies. Copyright © 2016. Published by Elsevier Ltd.

CO and CO2 dual-gas detection based on mid-infrared wideband absorption spectroscopy

NASA Astrophysics Data System (ADS)

Dong, Ming; Zhong, Guo-qiang; Miao, Shu-zhuo; Zheng, Chuan-tao; Wang, Yi-ding

2018-03-01

A dual-gas sensor system is developed for CO and CO2 detection using a single broadband light source, pyroelectric detectors and time-division multiplexing (TDM) technique. A stepper motor based rotating system and a single-reflection spherical optical mirror are designed and adopted for realizing and enhancing dual-gas detection. Detailed measurements under static detection mode (without rotation) and dynamic mode (with rotation) are performed to study the performance of the sensor system for the two gas samples. The detection period is 7.9 s in one round of detection by scanning the two detectors. Based on an Allan deviation analysis, the 1σ detection limits under static operation are 3.0 parts per million (ppm) in volume and 2.6 ppm for CO and CO2, respectively, and those under dynamic operation are 9.4 ppm and 10.8 ppm for CO and CO2, respectively. The reported sensor has potential applications in various fields requiring CO and CO2 detection such as in the coal mine.