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

PubMed

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

2016-06-18

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

A Sparsity-based Framework for Resolution Enhancement in Optical Fault Analysis of Integrated Circuits

DTIC Science & Technology

2015-01-01

for IC fault detection . This section provides background information on inversion methods. Conventional inversion techniques and their shortcomings are...physical techniques, electron beam imaging/analysis, ion beam techniques, scanning probe techniques. Electrical tests are used to detect faults in 13 an...hand, there is also the second harmonic technique through which duty cycle degradation faults are detected by collecting the magnitude and the phase of

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.

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.

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

NASA Astrophysics Data System (ADS)

Sharma, Anuj; Kumar Panigrahi, Prabin

2012-02-01

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

Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

ERIC Educational Resources Information Center

Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

2017-01-01

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

Compact and cost effective instrument for detecting drug precursors in different environments based on fluorescence polarization

NASA Astrophysics Data System (ADS)

Antolín-Urbaneja, J. C.; Eguizabal, I.; Briz, N.; Dominguez, A.; Estensoro, P.; Secchi, A.; Varriale, A.; Di Giovanni, S.; D'Auria, S.

2013-05-01

Several techniques for detecting chemical drug precursors have been developed in the last decade. Most of them are able to identify molecules at very low concentration under lab conditions. Other commercial devices are able to detect a fixed number and type of target substances based on a single detection technique providing an absence of flexibility with respect to target compounds. The construction of compact and easy to use detection systems providing screening for a large number of compounds being able to discriminate them with low false alarm rate and high probability of detection is still an open concern. Under CUSTOM project, funded by the European Commission within the FP7, a stand-alone portable sensing device based on multiple techniques is being developed. One of these techniques is based on the LED induced fluorescence polarization to detect Ephedrine and Benzyl Methyl Keton (BMK) as a first approach. This technique is highly selective with respect to the target compounds due to the generation of properly engineered fluorescent proteins which are able to bind the target analytes, as it happens in an "immune-type reaction". This paper deals with the advances in the design, construction and validation of the LED induced fluorescence sensor to detect BMK analytes. This sensor includes an analysis module based on high performance LED and PMT detector, a fluidic system to dose suitable quantities of reagents and some printed circuit boards, all of them fixed in a small structure (167mm × 193mm × 228mm) with the capability of working as a stand-alone application.

Laser Based Stand-Off Detection of Biological Agents (detection a distance des agents biologiques a l’aide du laser)

DTIC Science & Technology

2010-02-01

overview of their respective national up-date. Dr. Roy presented a new technique for evaluating the bioaerosol particle size based on a multiple...Field-of-View LIDAR technique . Mr. Levesque from INO gave an overview of their expertise in LIDAR and biophotonics. Dr. Chin from Laval University gave... techniques have the potential to detect particulate aerosols remotely at distances of many kilometres [1]. They can provide spatially resolved

Determination of a Limited Scope Network's Lightning Detection Efficiency

NASA Technical Reports Server (NTRS)

Rompala, John T.; Blakeslee, R.

2008-01-01

This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.

Enhanced automatic artifact detection based on independent component analysis and Renyi's entropy.

PubMed

Mammone, Nadia; Morabito, Francesco Carlo

2008-09-01

Artifacts are disturbances that may occur during signal acquisition and may affect their processing. The aim of this paper is to propose a technique for automatically detecting artifacts from the electroencephalographic (EEG) recordings. In particular, a technique based on both Independent Component Analysis (ICA) to extract artifactual signals and on Renyi's entropy to automatically detect them is presented. This technique is compared to the widely known approach based on ICA and the joint use of kurtosis and Shannon's entropy. The novel processing technique is shown to detect on average 92.6% of the artifactual signals against the average 68.7% of the previous technique on the studied available database. Moreover, Renyi's entropy is shown to be able to detect muscle and very low frequency activity as well as to discriminate them from other kinds of artifacts. In order to achieve an efficient rejection of the artifacts while minimizing the information loss, future efforts will be devoted to the improvement of blind artifact separation from EEG in order to ensure a very efficient isolation of the artifactual activity from any signals deriving from other brain tasks.

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

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.

Vision Based Obstacle Detection in Uav Imaging

NASA Astrophysics Data System (ADS)

Badrloo, S.; Varshosaz, M.

2017-08-01

Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

Comparison of the detection of periodontal pathogens in bacteraemia after tooth brushing by culture and molecular techniques.

PubMed

Marín, M-J; Figuero, E; González, I; O'Connor, A; Diz, P; Álvarez, M; Herrera, D; Sanz, M

2016-05-01

The prevalence and amounts of periodontal pathogens detected in bacteraemia samples after tooth brushing-induced by means of four diagnostic technique, three based on culture and one in a molecular-based technique, have been compared in this study. Blood samples were collected from thirty-six subjects with different periodontal status (17 were healthy, 10 with gingivitis and 9 with periodontitis) at baseline and 2 minutes after tooth brushing. Each sample was analyzed by three culture-based methods [direct anaerobic culturing (DAC), hemo-culture (BACTEC), and lysis-centrifugation (LC)] and one molecular-based technique [quantitative polymerase chain reaction (qPCR)]. With culture any bacterial isolate was detected and quantified, while with qPCR only Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans were detected and quantified. Descriptive analyses, ANOVA and Chi-squared tests, were performed. Neither BACTEC nor qPCR detected any type of bacteria in the blood samples. Only LC (2.7%) and DAC (8.3%) detected bacteraemia, although not in the same patients. Fusobacterium nucleatum was the most frequently detected bacterial species. The disparity in the results when the same samples were analyzed with four different microbiological detection methods highlights the need for a proper validation of the methodology to detect periodontal pathogens in bacteraemia samples, mainly when the presence of periodontal pathogens in blood samples after tooth brushing was very seldom.

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

DTIC Science & Technology

2015-12-14

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

A new method for QRS detection in ECG signals using QRS-preserving filtering techniques.

PubMed

Sharma, Tanushree; Sharma, Kamalesh K

2018-03-28

Detection of QRS complexes in ECG signals is required for various purposes such as determination of heart rate, feature extraction and classification. The problem of automatic QRS detection in ECG signals is complicated by the presence of noise spectrally overlapping with the QRS frequency range. As a solution to this problem, we propose the use of least-squares-optimisation-based smoothing techniques that suppress the noise peaks in the ECG while preserving the QRS complexes. We also propose a novel nonlinear transformation technique that is applied after the smoothing operations, which equalises the QRS amplitudes without boosting the supressed noise peaks. After these preprocessing operations, the R-peaks can finally be detected with high accuracy. The proposed technique has a low computational load and, therefore, it can be used for real-time QRS detection in a wearable device such as a Holter monitor or for fast offline QRS detection. The offline and real-time versions of the proposed technique have been evaluated on the standard MIT-BIH database. The offline implementation is found to perform better than state-of-the-art techniques based on wavelet transforms, empirical mode decomposition, etc. and the real-time implementation also shows improved performance over existing real-time QRS detection techniques.

Progress of new label-free techniques for biosensors: a review.

PubMed

Sang, Shengbo; Wang, Yajun; Feng, Qiliang; Wei, Ye; Ji, Jianlong; Zhang, Wendong

2016-01-01

The detection techniques used in biosensors can be broadly classified into label-based and label-free. Label-based detection relies on the specific properties of labels for detecting a particular target. In contrast, label-free detection is suitable for the target molecules that are not labeled or the screening of analytes which are not easy to tag. Also, more types of label-free biosensors have emerged with developments in biotechnology. The latest developed techniques in label-free biosensors, such as field-effect transistors-based biosensors including carbon nanotube field-effect transistor biosensors, graphene field-effect transistor biosensors and silicon nanowire field-effect transistor biosensors, magnetoelastic biosensors, optical-based biosensors, surface stress-based biosensors and other type of biosensors based on the nanotechnology are discussed. The sensing principles, configurations, sensing performance, applications, advantages and restriction of different label-free based biosensors are considered and discussed in this review. Most concepts included in this survey could certainly be applied to the development of this kind of biosensor in the future.

Field Validity and Feasibility of Four Techniques for the Detection of Trichuris in Simians: A Model for Monitoring Drug Efficacy in Public Health?

PubMed Central

Levecke, Bruno; De Wilde, Nathalie; Vandenhoute, Els; Vercruysse, Jozef

2009-01-01

Background Soil-transmitted helminths, such as Trichuris trichiura, are of major concern in public health. Current efforts to control these helminth infections involve periodic mass treatment in endemic areas. Since these large-scale interventions are likely to intensify, monitoring the drug efficacy will become indispensible. However, studies comparing detection techniques based on sensitivity, fecal egg counts (FEC), feasibility for mass diagnosis and drug efficacy estimates are scarce. Methodology/Principal Findings In the present study, the ether-based concentration, the Parasep Solvent Free (SF), the McMaster and the FLOTAC techniques were compared based on both validity and feasibility for the detection of Trichuris eggs in 100 fecal samples of nonhuman primates. In addition, the drug efficacy estimates of quantitative techniques was examined using a statistical simulation. Trichuris eggs were found in 47% of the samples. FLOTAC was the most sensitive technique (100%), followed by the Parasep SF (83.0% [95% confidence interval (CI): 82.4–83.6%]) and the ether-based concentration technique (76.6% [95% CI: 75.8–77.3%]). McMaster was the least sensitive (61.7% [95% CI: 60.7–62.6%]) and failed to detect low FEC. The quantitative comparison revealed a positive correlation between the four techniques (Rs = 0.85–0.93; p<0.0001). However, the ether-based concentration technique and the Parasep SF detected significantly fewer eggs than both the McMaster and the FLOTAC (p<0.0083). Overall, the McMaster was the most feasible technique (3.9 min/sample for preparing, reading and cleaning of the apparatus), followed by the ether-based concentration technique (7.7 min/sample) and the FLOTAC (9.8 min/sample). Parasep SF was the least feasible (17.7 min/sample). The simulation revealed that the sensitivity is less important for monitoring drug efficacy and that both FLOTAC and McMaster were reliable estimators. Conclusions/Significance The results of this study demonstrated that McMaster is a promising technique when making use of FEC to monitor drug efficacy in Trichuris. PMID:19172171

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

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

Hydroacoustic basis for detection and characterization of eelgrass (Zostera marina)

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

Sabol, B.; McCarthy, E.; Rocha, K.

1997-06-01

Understanding the distribution and density of seagrasses is important for a variety of environmental applications. Physical techniques for detection and characterization are labor and cost intensive and provide little insight into spatial distribution. optical-based techniques are limited by water clarity - frequently resulting in systematic underestimation of the extent of seagrasses. Active hydroacoustic techniques have shown the ability to detect seagrasses but the phenomenology behind detection is poorly understood. Laboratory and in-situ hydroacoustic measurements are presented for eelgrass (Zostera marina), a common seagrass in the United States. Based on these data, hydroacoustic approaches for wide area detection and mapping aremore » discussed and several are demonstrated within areas of established eelgrass beds in Narragansett Bay, Rhode Island.« less

Structural Damage Detection Using Virtual Passive Controllers

NASA Technical Reports Server (NTRS)

Lew, Jiann-Shiun; Juang, Jer-Nan

2001-01-01

This paper presents novel approaches for structural damage detection which uses the virtual passive controllers attached to structures, where passive controllers are energy dissipative devices and thus guarantee the closed-loop stability. The use of the identified parameters of various closed-loop systems can solve the problem that reliable identified parameters, such as natural frequencies of the open-loop system may not provide enough information for damage detection. Only a small number of sensors are required for the proposed approaches. The identified natural frequencies, which are generally much less sensitive to noise and more reliable than the identified natural frequencies, are used for damage detection. Two damage detection techniques are presented. One technique is based on the structures with direct output feedback controllers while the other technique uses the second-order dynamic feedback controllers. A least-squares technique, which is based on the sensitivity of natural frequencies to damage variables, is used for accurately identifying the damage variables.

Nanostructured surfaces for analysis of anticancer drug and cell diagnosis based on electrochemical and SERS tools.

PubMed

El-Said, Waleed A; Yoon, Jinho; Choi, Jeong-Woo

2018-01-01

Discovering new anticancer drugs and screening their efficacy requires a huge amount of resources and time-consuming processes. The development of fast, sensitive, and nondestructive methods for the in vitro and in vivo detection of anticancer drugs' effects and action mechanisms have been done to reduce the time and resources required to discover new anticancer drugs. For the in vitro and in vivo detection of the efficiency, distribution, and action mechanism of anticancer drugs, the applications of electrochemical techniques such as electrochemical cell chips and optical techniques such as surface-enhanced Raman spectroscopy (SERS) have been developed based on the nanostructured surface. Research focused on electrochemical cell chips and the SERS technique have been reviewed here; electrochemical cell chips based on nanostructured surfaces have been developed for the in vitro detection of cell viability and the evaluation of the effects of anticancer drugs, which showed the high capability to evaluate the cytotoxic effects of several chemicals at low concentrations. SERS technique based on the nanostructured surface have been used as label-free, simple, and nondestructive techniques for the in vitro and in vivo monitoring of the distribution, mechanism, and metabolism of different anticancer drugs at the cellular level. The use of electrochemical cell chips and the SERS technique based on the nanostructured surface should be good tools to detect the effects and action mechanisms of anticancer drugs.

Nanostructured surfaces for analysis of anticancer drug and cell diagnosis based on electrochemical and SERS tools

NASA Astrophysics Data System (ADS)

El-Said, Waleed A.; Yoon, Jinho; Choi, Jeong-Woo

2018-04-01

Discovering new anticancer drugs and screening their efficacy requires a huge amount of resources and time-consuming processes. The development of fast, sensitive, and nondestructive methods for the in vitro and in vivo detection of anticancer drugs' effects and action mechanisms have been done to reduce the time and resources required to discover new anticancer drugs. For the in vitro and in vivo detection of the efficiency, distribution, and action mechanism of anticancer drugs, the applications of electrochemical techniques such as electrochemical cell chips and optical techniques such as surface-enhanced Raman spectroscopy (SERS) have been developed based on the nanostructured surface. Research focused on electrochemical cell chips and the SERS technique have been reviewed here; electrochemical cell chips based on nanostructured surfaces have been developed for the in vitro detection of cell viability and the evaluation of the effects of anticancer drugs, which showed the high capability to evaluate the cytotoxic effects of several chemicals at low concentrations. SERS technique based on the nanostructured surface have been used as label-free, simple, and nondestructive techniques for the in vitro and in vivo monitoring of the distribution, mechanism, and metabolism of different anticancer drugs at the cellular level. The use of electrochemical cell chips and the SERS technique based on the nanostructured surface should be good tools to detect the effects and action mechanisms of anticancer drugs.

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.

Caries Detection Methods Based on Changes in Optical Properties between Healthy and Carious Tissue

PubMed Central

Karlsson, Lena

2010-01-01

A conservative, noninvasive or minimally invasive approach to clinical management of dental caries requires diagnostic techniques capable of detecting and quantifying lesions at an early stage, when progression can be arrested or reversed. Objective evidence of initiation of the disease can be detected in the form of distinct changes in the optical properties of the affected tooth structure. Caries detection methods based on changes in a specific optical property are collectively referred to as optically based methods. This paper presents a simple overview of the feasibility of three such technologies for quantitative or semiquantitative assessment of caries lesions. Two of the techniques are well-established: quantitative light-induced fluorescence, which is used primarily in caries research, and laser-induced fluorescence, a commercially available method used in clinical dental practice. The third technique, based on near-infrared transillumination of dental enamel is in the developmental stages. PMID:20454579

Face Detection Technique as Interactive Audio/Video Controller for a Mother-Tongue-Based Instructional Material

NASA Astrophysics Data System (ADS)

Guidang, Excel Philip B.; Llanda, Christopher John R.; Palaoag, Thelma D.

2018-03-01

Face Detection Technique as a strategy in controlling a multimedia instructional material was implemented in this study. Specifically, it achieved the following objectives: 1) developed a face detection application that controls an embedded mother-tongue-based instructional material for face-recognition configuration using Python; 2) determined the perceptions of the students using the Mutt Susan’s student app review rubric. The study concludes that face detection technique is effective in controlling an electronic instructional material. It can be used to change the method of interaction of the student with an instructional material. 90% of the students perceived the application to be a great app and 10% rated the application to be good.

Arduino-based noise robust online heart-rate detection.

PubMed

Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

2017-04-01

This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan W.

2014-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan Walker

2015-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

Adaptive steganography

NASA Astrophysics Data System (ADS)

Chandramouli, Rajarathnam; Li, Grace; Memon, Nasir D.

2002-04-01

Steganalysis techniques attempt to differentiate between stego-objects and cover-objects. In recent work we developed an explicit analytic upper bound for the steganographic capacity of LSB based steganographic techniques for a given false probability of detection. In this paper we look at adaptive steganographic techniques. Adaptive steganographic techniques take explicit steps to escape detection. We explore different techniques that can be used to adapt message embedding to the image content or to a known steganalysis technique. We investigate the advantages of adaptive steganography within an analytical framework. We also give experimental results with a state-of-the-art steganalysis technique demonstrating that adaptive embedding results in a significant number of bits embedded without detection.

Radar fall detection using principal component analysis

NASA Astrophysics Data System (ADS)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Aptamer-based microspheres for highly sensitive protein detection using fluorescently-labeled DNA nanostructures.

PubMed

Han, Daehoon; Hong, Jinkee; Kim, Hyun Cheol; Sung, Jong Hwan; Lee, Jong Bum

2013-11-01

Many highly sensitive protein detection techniques have been developed and have played an important role in the analysis of proteins. Herein, we report a novel technique that can detect proteins sensitively and effectively using aptamer-based DNA nanostructures. Thrombin was used as a target protein and aptamer was used to capture fluorescent dye-labeled DNA nanobarcodes or thrombin on a microsphere. The captured DNA nanobarcodes were replaced by a thrombin and aptamer interaction. The detection ability of this approach was confirmed by flow cytometry with different concentrations of thrombin. Our detection method has great potential for rapid and simple protein detection with a variety of aptamers.

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

USDA-ARS?s Scientific Manuscript database

Nondestructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed in order to detect worms on fresh-cut lettuce. The optimal wavebands for detecting worms on fresh-cut lettuce were investigated using the one-way ANOVA analysis and correlation analysis. The worm detec...

Single-molecule detection: applications to ultrasensitive biochemical analysis

NASA Astrophysics Data System (ADS)

Castro, Alonso; Shera, E. Brooks

1995-06-01

Recent developments in laser-based detection of fluorescent molecules have made possible the implementation of very sensitive techniques for biochemical analysis. We present and discuss our experiments on the applications of our recently developed technique of single-molecule detection to the analysis of molecules of biological interest. These newly developed methods are capable of detecting and identifying biomolecules at the single-molecule level of sensitivity. In one case, identification is based on measuring fluorescence brightness from single molecules. In another, molecules are classified by determining their electrophoretic velocities.

Plasmonic SERS nanochips and nanoprobes for medical diagnostics and bio-energy applications

NASA Astrophysics Data System (ADS)

Ngo, Hoan T.; Wang, Hsin-Neng; Crawford, Bridget M.; Fales, Andrew M.; Vo-Dinh, Tuan

2017-02-01

The development of rapid, easy-to-use, cost-effective, high accuracy, and high sensitive DNA detection methods for molecular diagnostics has been receiving increasing interest. Over the last five years, our laboratory has developed several chip-based DNA detection techniques including the molecular sentinel-on-chip (MSC), the multiplex MSC, and the inverse molecular sentinel-on-chip (iMS-on-Chip). In these techniques, plasmonic surface-enhanced Raman scattering (SERS) Nanowave chips were functionalized with DNA probes for single-step DNA detection. Sensing mechanisms were based on hybridization of target sequences and DNA probes, resulting in a distance change between SERS reporters and the Nanowave chip's gold surface. This distance change resulted in change in SERS intensity, thus indicating the presence and capture of the target sequences. Our techniques were single-step DNA detection techniques. Target sequences were detected by simple delivery of sample solutions onto DNA probe-functionalized Nanowave chips and SERS signals were measured after 1h - 2h incubation. Target sequence labeling or washing to remove unreacted components was not required, making the techniques simple, easy-to-use, and cost effective. The usefulness of the techniques for medical diagnostics was illustrated by the detection of genetic biomarkers for respiratory viral infection and of dengue virus 4 DNA.

Building Change Detection from LIDAR Point Cloud Data Based on Connected Component Analysis

NASA Astrophysics Data System (ADS)

Awrangjeb, M.; Fraser, C. S.; Lu, G.

2015-08-01

Building data are one of the important data types in a topographic database. Building change detection after a period of time is necessary for many applications, such as identification of informal settlements. Based on the detected changes, the database has to be updated to ensure its usefulness. This paper proposes an improved building detection technique, which is a prerequisite for many building change detection techniques. The improved technique examines the gap between neighbouring buildings in the building mask in order to avoid under segmentation errors. Then, a new building change detection technique from LIDAR point cloud data is proposed. Buildings which are totally new or demolished are directly added to the change detection output. However, for demolished or extended building parts, a connected component analysis algorithm is applied and for each connected component its area, width and height are estimated in order to ascertain if it can be considered as a demolished or new building part. Finally, a graphical user interface (GUI) has been developed to update detected changes to the existing building map. Experimental results show that the improved building detection technique can offer not only higher performance in terms of completeness and correctness, but also a lower number of undersegmentation errors as compared to its original counterpart. The proposed change detection technique produces no omission errors and thus it can be exploited for enhanced automated building information updating within a topographic database. Using the developed GUI, the user can quickly examine each suggested change and indicate his/her decision with a minimum number of mouse clicks.

Explosive detection technology

NASA Astrophysics Data System (ADS)

Doremus, Steven; Crownover, Robin

2017-05-01

The continuing proliferation of improvised explosive devices is an omnipresent threat to civilians and members of military and law enforcement around the world. The ability to accurately and quickly detect explosive materials from a distance would be an extremely valuable tool for mitigating the risk posed by these devices. A variety of techniques exist that are capable of accurately identifying explosive compounds, but an effective standoff technique is still yet to be realized. Most of the methods being investigated to fill this gap in capabilities are laser based. Raman spectroscopy is one such technique that has been demonstrated to be effective at a distance. Spatially Offset Raman Spectroscopy (SORS) is a technique capable of identifying chemical compounds inside of containers, which could be used to detect hidden explosive devices. Coherent Anti-Stokes Raman Spectroscopy (CARS) utilized a coherent pair of lasers to excite a sample, greatly increasing the response of sample while decreasing the strength of the lasers being used, which significantly improves the eye safety issue that typically hinders laser-based detection methods. Time-gating techniques are also being developed to improve the data collection from Raman techniques, which are often hindered fluorescence of the test sample in addition to atmospheric, substrate, and contaminant responses. Ultraviolet based techniques have also shown significant promise by greatly improved signal strength from excitation of resonance in many explosive compounds. Raman spectroscopy, which identifies compounds based on their molecular response, can be coupled with Laser Induced Breakdown Spectroscopy (LIBS) capable of characterizing the sample's atomic composition using a single laser.

Invariant domain watermarking using heaviside function of order alpha and fractional Gaussian field.

PubMed

Abbasi, Almas; Woo, Chaw Seng; Ibrahim, Rabha Waell; Islam, Saeed

2015-01-01

Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve this problem, we propose an RST invariant domain watermarking technique based on fractional calculus. We have constructed a domain using Heaviside function of order alpha (HFOA). The HFOA models the signal as a polynomial for watermark embedding. The watermark is embedded in all the coefficients of the image. We have also constructed a fractional variance formula using fractional Gaussian field. A cross correlation method based on the fractional Gaussian field is used for watermark detection. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques. Experimental results confirmed that the proposed technique has a high level of robustness.

Invariant Domain Watermarking Using Heaviside Function of Order Alpha and Fractional Gaussian Field

PubMed Central

Abbasi, Almas; Woo, Chaw Seng; Ibrahim, Rabha Waell; Islam, Saeed

2015-01-01

Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve this problem, we propose an RST invariant domain watermarking technique based on fractional calculus. We have constructed a domain using Heaviside function of order alpha (HFOA). The HFOA models the signal as a polynomial for watermark embedding. The watermark is embedded in all the coefficients of the image. We have also constructed a fractional variance formula using fractional Gaussian field. A cross correlation method based on the fractional Gaussian field is used for watermark detection. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques. Experimental results confirmed that the proposed technique has a high level of robustness. PMID:25884854

A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Sainani, Varsha

The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

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.

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

Signal analysis techniques for incipient failure detection in turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, T.

1985-01-01

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

Experimental Study on Damage Detection in Timber Specimens Based on an Electromechanical Impedance Technique and RMSD-Based Mahalanobis Distance

PubMed Central

Wang, Dansheng; Wang, Qinghua; Wang, Hao; Zhu, Hongping

2016-01-01

In the electromechanical impedance (EMI) method, the PZT patch performs the functions of both sensor and exciter. Due to the high frequency actuation and non-model based characteristics, the EMI method can be utilized to detect incipient structural damage. In recent years EMI techniques have been widely applied to monitor the health status of concrete and steel materials, however, studies on application to timber are limited. This paper will explore the feasibility of using the EMI technique for damage detection in timber specimens. In addition, the conventional damage index, namely root mean square deviation (RMSD) is employed to evaluate the level of damage. On that basis, a new damage index, Mahalanobis distance based on RMSD, is proposed to evaluate the damage severity of timber specimens. Experimental studies are implemented to detect notch and hole damage in the timber specimens. Experimental results verify the availability and robustness of the proposed damage index and its superiority over the RMSD indexes. PMID:27782088

Experimental Study on Damage Detection in Timber Specimens Based on an Electromechanical Impedance Technique and RMSD-Based Mahalanobis Distance.

PubMed

Wang, Dansheng; Wang, Qinghua; Wang, Hao; Zhu, Hongping

2016-10-22

In the electromechanical impedance (EMI) method, the PZT patch performs the functions of both sensor and exciter. Due to the high frequency actuation and non-model based characteristics, the EMI method can be utilized to detect incipient structural damage. In recent years EMI techniques have been widely applied to monitor the health status of concrete and steel materials, however, studies on application to timber are limited. This paper will explore the feasibility of using the EMI technique for damage detection in timber specimens. In addition, the conventional damage index, namely root mean square deviation (RMSD) is employed to evaluate the level of damage. On that basis, a new damage index, Mahalanobis distance based on RMSD, is proposed to evaluate the damage severity of timber specimens. Experimental studies are implemented to detect notch and hole damage in the timber specimens. Experimental results verify the availability and robustness of the proposed damage index and its superiority over the RMSD indexes.

Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels.

PubMed

Sornapudi, Sudhir; Stanley, Ronald Joe; Stoecker, William V; Almubarak, Haidar; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R

2018-01-01

Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods.

A review on creatinine measurement techniques.

PubMed

Mohabbati-Kalejahi, Elham; Azimirad, Vahid; Bahrami, Manouchehr; Ganbari, Ahmad

2012-08-15

This paper reviews the entire recent global tendency for creatinine measurement. Creatinine biosensors involve complex relationships between biology and micro-mechatronics to which the blood is subjected. Comparison between new and old methods shows that new techniques (e.g. Molecular Imprinted Polymers based algorithms) are better than old methods (e.g. Elisa) in terms of stability and linear range. All methods and their details for serum, plasma, urine and blood samples are surveyed. They are categorized into five main algorithms: optical, electrochemical, impedometrical, Ion Selective Field-Effect Transistor (ISFET) based technique and chromatography. Response time, detection limit, linear range and selectivity of reported sensors are discussed. Potentiometric measurement technique has the lowest response time of 4-10 s and the lowest detection limit of 0.28 nmol L(-1) belongs to chromatographic technique. Comparison between various techniques of measurements indicates that the best selectivity belongs to MIP based and chromatographic techniques. Copyright © 2012 Elsevier B.V. All rights reserved.

Cell culture-based biosensing techniques for detecting toxicity in water.

PubMed

Tan, Lu; Schirmer, Kristin

2017-06-01

The significant increase of contaminants entering fresh water bodies calls for the development of rapid and reliable methods to monitor the aquatic environment and to detect water toxicity. Cell culture-based biosensing techniques utilise the overall cytotoxic response to external stimuli, mediated by a transduced signal, to specify the toxicity of aqueous samples. These biosensing techniques can effectively indicate water toxicity for human safety and aquatic organism health. In this review we account for the recent developments of the mainstream cell culture-based biosensing techniques for water quality evaluation, discuss their key features, potentials and limitations, and outline the future prospects of their development. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Raman spectroscopy-based detection of chemical contaminants in food powders

USDA-ARS?s Scientific Manuscript database

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary sp...

Protecting against cyber threats in networked information systems

NASA Astrophysics Data System (ADS)

Ertoz, Levent; Lazarevic, Aleksandar; Eilertson, Eric; Tan, Pang-Ning; Dokas, Paul; Kumar, Vipin; Srivastava, Jaideep

2003-07-01

This paper provides an overview of our efforts in detecting cyber attacks in networked information systems. Traditional signature based techniques for detecting cyber attacks can only detect previously known intrusions and are useless against novel attacks and emerging threats. Our current research at the University of Minnesota is focused on developing data mining techniques to automatically detect attacks against computer networks and systems. This research is being conducted as a part of MINDS (Minnesota Intrusion Detection System) project at the University of Minnesota. Experimental results on live network traffic at the University of Minnesota show that the new techniques show great promise in detecting novel intrusions. In particular, during the past few months our techniques have been successful in automatically identifying several novel intrusions that could not be detected using state-of-the-art tools such as SNORT.

Objective response detection in an electroencephalogram during somatosensory stimulation.

PubMed

Simpson, D M; Tierra-Criollo, C J; Leite, R T; Zayen, E J; Infantosi, A F

2000-06-01

Techniques for objective response detection aim to identify the presence of evoked potentials based purely on statistical principles. They have been shown to be potentially more sensitive than the conventional approach of subjective evaluation by experienced clinicians and could be of great clinical use. Three such techniques to detect changes in an electroencephalogram (EEG) synchronous with the stimuli, namely, magnitude-squared coherence (MSC), the phase-synchrony measure (PSM) and the spectral F test (SFT) were applied to EEG signals of 12 normal subjects under conventional somatosensory pulse stimulation to the tibial nerve. The SFT, which uses only the power spectrum, showed the poorest performance, while the PSM, based only on the phase spectrum, gave results almost as good as those of the MSC, which uses both phase and power spectra. With the latter two techniques, stimulus responses were evident in the frequency range of 20-80 Hz in all subjects after 200 stimuli (5 Hz stimulus frequency), whereas for visual recognition at least 500 stimuli are usually applied. Based on these results and on simulations, the phase-based techniques appear promising for the automated detection and monitoring of somatosensory evoked potentials.

Quantum dot-based western blot for sensitive detection of pig serum antibody to actinobacillus pleuropneumoniae

NASA Astrophysics Data System (ADS)

Cişmileanu, Ana; Sima, Cornelia; Grigoriu, Constantin

2007-08-01

A quantum dot - immunoglobulin conjugate specific for pig IgG, was obtained by carbodiimide chemistry. We used a Western blot technique for detecting specific antibodies against Actinobacillus pleuropneumoniae (A. pp), which cause porcine pleuropneumonia. The antigen used in this technique was Apx haemolysin which is an important virulence factor of A. pp and it induces protective immunity in vaccined pigs. The detection on Western blot membrane was possible at 1/50 dilution of quantum dot conjugate at a dilution of pig serum till 1/6400. The results for pig serum demonstrated a higher sensitivity of QD-based Western blot technique for the presence of antibodies specific for Apx haemolysin in comparison with similar classical techniques (with coloured substrate for enzyme present in secondary antibody conjugate).

Wavelet-based higher-order neural networks for mine detection in thermal IR imagery

NASA Astrophysics Data System (ADS)

Baertlein, Brian A.; Liao, Wen-Jiao

2000-08-01

An image processing technique is described for the detection of miens in RI imagery. The proposed technique is based on a third-order neural network, which processes the output of a wavelet packet transform. The technique is inherently invariant to changes in signature position, rotation and scaling. The well-known memory limitations that arise with higher-order neural networks are addressed by (1) the data compression capabilities of wavelet packets, (2) protections of the image data into a space of similar triangles, and (3) quantization of that 'triangle space'. Using these techniques, image chips of size 28 by 28, which would require 0(109) neural net weights, are processed by a network having 0(102) weights. ROC curves are presented for mine detection in real and simulated imagery.

Advancing Lie Detection by Inducing Cognitive Load on Liars: A Review of Relevant Theories and Techniques Guided by Lessons from Polygraph-Based Approaches

PubMed Central

Walczyk, Jeffrey J.; Igou, Frank P.; Dixon, Alexa P.; Tcholakian, Talar

2013-01-01

This article critically reviews techniques and theories relevant to the emerging field of “lie detection by inducing cognitive load selectively on liars.” To help these techniques benefit from past mistakes, we start with a summary of the polygraph-based Controlled Question Technique (CQT) and the major criticisms of it made by the National Research Council (2003), including that it not based on a validated theory and administration procedures have not been standardized. Lessons from the more successful Guilty Knowledge Test are also considered. The critical review that follows starts with the presentation of models and theories offering insights for cognitive lie detection that can undergird theoretically load-inducing approaches. This is followed by evaluation of specific research-based, load-inducing proposals, especially for their susceptibility to rehearsal and other countermeasures. To help organize these proposals and suggest new direction for innovation and refinement, a theoretical taxonomy is presented based on the type of cognitive load induced in examinees (intrinsic or extraneous) and how open-ended the responses to test items are. Finally, four recommendations are proffered that can help researchers and practitioners to avert the corresponding mistakes with the CQT and yield new, valid cognitive lie detection technologies. PMID:23378840

Comparison of Non-Culture-Based Methods for Detection of Systemic Fungal Infections, with an Emphasis on Invasive Candida Infections

PubMed Central

White, P. Lewis; Archer, Alice E.; Barnes, Rosemary A.

2005-01-01

The accepted limitations associated with classic culture techniques for the diagnosis of invasive fungal infections have lead to the emergence of many non-culture-based methods. With superior sensitivities and quicker turnaround times, non-culture-based methods may aid the diagnosis of invasive fungal infections. In this review of the diagnostic service, we assessed the performances of two antigen detection techniques (enzyme-linked immunosorbent assay [ELISA] and latex agglutination) with a molecular method for the detection of invasive Candida infection and invasive aspergillosis. The specificities for all three assays were high (≥97%), although the Candida PCR method had enhanced sensitivity over both ELISA and latex agglutination with values of 95%, 75%, and 25%, respectively. However, calculating significant sensitivity values for the Aspergillus detection methods was not feasible due to a low number of proven/probable cases. Despite enhanced sensitivity, the PCR method failed to detect nucleic acid in a probable case of invasive Candida infection that was detected by ELISA. In conclusion, both PCR and ELISA techniques should be used in unison to aid the detection of invasive fungal infections. PMID:15872239

A Comparison of Source Code Plagiarism Detection Engines

NASA Astrophysics Data System (ADS)

Lancaster, Thomas; Culwin, Fintan

2004-06-01

Automated techniques for finding plagiarism in student source code submissions have been in use for over 20 years and there are many available engines and services. This paper reviews the literature on the major modern detection engines, providing a comparison of them based upon the metrics and techniques they deploy. Generally the most common and effective techniques are seen to involve tokenising student submissions then searching pairs of submissions for long common substrings, an example of what is defined to be a paired structural metric. Computing academics are recommended to use one of the two Web-based detection engines, MOSS and JPlag. It is shown that whilst detection is well established there are still places where further research would be useful, particularly where visual support of the investigation process is possible.

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

NASA Astrophysics Data System (ADS)

Goel, Amit; Montgomery, Michele

2015-08-01

Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

Sensor data fusion for spectroscopy-based detection of explosives

NASA Astrophysics Data System (ADS)

Shah, Pratik V.; Singh, Abhijeet; Agarwal, Sanjeev; Sedigh, Sahra; Ford, Alan; Waterbury, Robert

2009-05-01

In-situ trace detection of explosive compounds such as RDX, TNT, and ammonium nitrate, is an important problem for the detection of IEDs and IED precursors. Spectroscopic techniques such as LIBS and Raman have shown promise for the detection of residues of explosive compounds on surfaces from standoff distances. Individually, both LIBS and Raman techniques suffer from various limitations, e.g., their robustness and reliability suffers due to variations in peak strengths and locations. However, the orthogonal nature of the spectral and compositional information provided by these techniques makes them suitable candidates for the use of sensor fusion to improve the overall detection performance. In this paper, we utilize peak energies in a region by fitting Lorentzian or Gaussian peaks around the location of interest. The ratios of peak energies are used for discrimination, in order to normalize the effect of changes in overall signal strength. Two data fusion techniques are discussed in this paper. Multi-spot fusion is performed on a set of independent samples from the same region based on the maximum likelihood formulation. Furthermore, the results from LIBS and Raman sensors are fused using linear discriminators. Improved detection performance with significantly reduced false alarm rates is reported using fusion techniques on data collected for sponsor demonstration at Fort Leonard Wood.

Robust myoelectric signal detection based on stochastic resonance using multiple-surface-electrode array made of carbon nanotube composite paper

NASA Astrophysics Data System (ADS)

Shirata, Kento; Inden, Yuki; Kasai, Seiya; Oya, Takahide; Hagiwara, Yosuke; Kaeriyama, Shunichi; Nakamura, Hideyuki

2016-04-01

We investigated the robust detection of surface electromyogram (EMG) signals based on the stochastic resonance (SR) phenomenon, in which the response to weak signals is optimized by adding noise, combined with multiple surface electrodes. Flexible carbon nanotube composite paper (CNT-cp) was applied to the surface electrode, which showed good performance that is comparable to that of conventional Ag/AgCl electrodes. The SR-based EMG signal system integrating an 8-Schmitt-trigger network and the multiple-CNT-cp-electrode array successfully detected weak EMG signals even when the subject’s body is in the motion, which was difficult to achieve using the conventional technique. The feasibility of the SR-based EMG detection technique was confirmed by demonstrating its applicability to robot hand control.

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.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels

PubMed Central

Sornapudi, Sudhir; Stanley, Ronald Joe; Stoecker, William V.; Almubarak, Haidar; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R.

2018-01-01

Background: Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. Methods: In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. Results: The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. Conclusions: The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods. PMID:29619277

Evaluation of culture-based techniques and 454 pyrosequencing for the analysis of fungal diversity in potting media and organic fertilizers.

PubMed

Al-Sadi, A M; Al-Mazroui, S S; Phillips, A J L

2015-08-01

Potting media and organic fertilizers (OFs) are commonly used in agricultural systems. However, there is a lack of studies on the efficiency of culture-based techniques in assessing the level of fungal diversity in these products. A study was conducted to investigate the efficiency of seven culture-based techniques and pyrosequencing for characterizing fungal diversity in potting media and OFs. Fungal diversity was evaluated using serial dilution, direct plating and baiting with carrot slices, potato slices, radish seeds, cucumber seeds and cucumber cotyledons. Identity of all the isolates was confirmed on the basis of the internal transcribed spacer region of the ribosomal RNA (ITS rRNA) sequence data. The direct plating technique was found to be superior over other culture-based techniques in the number of fungal species detected. It was also found to be simple and the least time consuming technique. Comparing the efficiency of direct plating with 454 pyrosequencing revealed that pyrosequencing detected 12 and 15 times more fungal species from potting media and OFs respectively. Analysis revealed that there were differences between potting media and OFs in the dominant phyla, classes, orders, families, genera and species detected. Zygomycota (52%) and Chytridiomycota (60%) were the predominant phyla in potting media and OFs respectively. The superiority of pyrosequencing over cultural methods could be related to the ability to detect obligate fungi, slow growing fungi and fungi that exist at low population densities. The evaluated methods in this study, especially direct plating and pyrosequencing, may be used as tools to help detect and reduce movement of unwanted fungi between countries and regions. © 2015 The Society for Applied Microbiology.

An assessment of ground-based techniques for detecting other planetary systems. Volume 1: An overview. [workshop conclusions

NASA Technical Reports Server (NTRS)

Black, D. C. (Editor); Brunk, W. E. (Editor)

1980-01-01

The feasibility and limitations of ground-based techniques for detecting other planetary systems are discussed as well as the level of accuracy at which these limitations would occur and the extent to which they can be overcome by new technology and instrumenation. Workshop conclusions and recommendations are summarized and a proposed high priority program is considered.

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

PubMed Central

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

2001-01-01

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

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

PubMed

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

2001-12-01

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

Improvement in QEPAS system utilizing a second harmonic based wavelength calibration technique

NASA Astrophysics Data System (ADS)

Zhang, Qinduan; Chang, Jun; Wang, Fupeng; Wang, Zongliang; Xie, Yulei; Gong, Weihua

2018-05-01

A simple laser wavelength calibration technique, based on second harmonic signal, is demonstrated in this paper to improve the performance of quartz enhanced photoacoustic spectroscopy (QEPAS) gas sensing system, e.g. improving the signal to noise ratio (SNR), detection limit and long-term stability. Constant current, corresponding to the gas absorption line, combining f/2 frequency sinusoidal signal are used to drive the laser (constant driving mode), a software based real-time wavelength calibration technique is developed to eliminate the wavelength drift due to ambient fluctuations. Compared to conventional wavelength modulation spectroscopy (WMS), this method allows lower filtering bandwidth and averaging algorithm applied to QEPAS system, improving SNR and detection limit. In addition, the real-time wavelength calibration technique guarantees the laser output is modulated steadily at gas absorption line. Water vapor is chosen as an objective gas to evaluate its performance compared to constant driving mode and conventional WMS system. The water vapor sensor was designed insensitive to the incoherent external acoustic noise by the numerical averaging technique. As a result, the SNR increases 12.87 times in wavelength calibration technique based system compared to conventional WMS system. The new system achieved a better linear response (R2 = 0 . 9995) in concentration range from 300 to 2000 ppmv, and achieved a minimum detection limit (MDL) of 630 ppbv.

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

PubMed

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

2017-09-01

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

Visual Sensor Based Abnormal Event Detection with Moving Shadow Removal in Home Healthcare Applications

PubMed Central

Lee, Young-Sook; Chung, Wan-Young

2012-01-01

Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects more accurately and discriminate between abnormal and normal activities. To improve the accuracy of object detection and tracking, our proposed shadow removal algorithm is employed. Abnormal event detection based on visual sensor by using shape features variation and 3-D trajectory is presented to overcome the low fall detection rate. The experimental results showed that the success rate of detecting abnormal events was 97% with a false positive rate of 2%. Our proposed algorithm can allow distinguishing diverse fall activities such as forward falls, backward falls, and falling asides from normal activities. PMID:22368486

Exploring three faint source detections methods for aperture synthesis radio images

NASA Astrophysics Data System (ADS)

Peracaula, M.; Torrent, A.; Masias, M.; Lladó, X.; Freixenet, J.; Martí, J.; Sánchez-Sutil, J. R.; Muñoz-Arjonilla, A. J.; Paredes, J. M.

2015-04-01

Wide-field radio interferometric images often contain a large population of faint compact sources. Due to their low intensity/noise ratio, these objects can be easily missed by automated detection methods, which have been classically based on thresholding techniques after local noise estimation. The aim of this paper is to present and analyse the performance of several alternative or complementary techniques to thresholding. We compare three different algorithms to increase the detection rate of faint objects. The first technique consists of combining wavelet decomposition with local thresholding. The second technique is based on the structural behaviour of the neighbourhood of each pixel. Finally, the third algorithm uses local features extracted from a bank of filters and a boosting classifier to perform the detections. The methods' performances are evaluated using simulations and radio mosaics from the Giant Metrewave Radio Telescope and the Australia Telescope Compact Array. We show that the new methods perform better than well-known state of the art methods such as SEXTRACTOR, SAD and DUCHAMP at detecting faint sources of radio interferometric images.

New radiological material detection technologies for nuclear forensics: Remote optical imaging and graphene-based sensors.

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

Harrison, Richard Karl; Martin, Jeffrey B.; Wiemann, Dora K.

We developed new detector technologies to identify the presence of radioactive materials for nuclear forensics applications. First, we investigated an optical radiation detection technique based on imaging nitrogen fluorescence excited by ionizing radiation. We demonstrated optical detection in air under indoor and outdoor conditions for alpha particles and gamma radiation at distances up to 75 meters. We also contributed to the development of next generation systems and concepts that could enable remote detection at distances greater than 1 km, and originated a concept that could enable daytime operation of the technique. A second area of research was the development ofmore » room-temperature graphene-based sensors for radiation detection and measurement. In this project, we observed tunable optical and charged particle detection, and developed improved devices. With further development, the advancements described in this report could enable new capabilities for nuclear forensics applications.« less

Obstacle Avoidance On Roadways Using Range Data

NASA Astrophysics Data System (ADS)

Dunlay, R. Terry; Morgenthaler, David G.

1987-02-01

This report describes range data based obstacle avoidance techniques developed for use on an autonomous road-following robot vehicle. The purpose of these techniques is to detect and locate obstacles present in a road environment for navigation of a robot vehicle equipped with an active laser-based range sensor. Techniques are presented for obstacle detection, obstacle location, and coordinate transformations needed in the construction of Scene Models (symbolic structures representing the 3-D obstacle boundaries used by the vehicle's Navigator for path planning). These techniques have been successfully tested on an outdoor robotic vehicle, the Autonomous Land Vehicle (ALV), at speeds up to 3.5 km/hour.

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

NASA Astrophysics Data System (ADS)

Lyu, Jiang-Tao; Zhou, Chen

2017-12-01

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

Acoustic Emission and Echo Signal Compensation Techniques Applied to an Ultrasonic Logging-While-Drilling Caliper.

PubMed

Yao, Yongchao; Ju, Xiaodong; Lu, Junqiang; Men, Baiyong

2017-06-10

A logging-while-drilling (LWD) caliper is a tool used for the real-time measurement of a borehole diameter in oil drilling engineering. This study introduces the mechanical structure and working principle of a new LWD caliper based on ultrasonic distance measurement (UDM). The detection range is a major performance index of a UDM system. This index is determined by the blind zone length and remote reflecting interface detection capability of the system. To reduce the blind zone length and detect near the reflecting interface, a full bridge acoustic emission technique based on bootstrap gate driver (BGD) and metal-oxide-semiconductor field effect transistor (MOSFET) is designed by analyzing the working principle and impedance characteristics of a given piezoelectric transducer. To detect the remote reflecting interface and reduce the dynamic range of the received echo signals, the relationships between the echo amplitude and propagation distance of ultrasonic waves are determined. A signal compensation technique based on time-varying amplification theory, which can automatically change the gain according to the echo arrival time is designed. Lastly, the aforementioned techniques and corresponding circuits are experimentally verified. Results show that the blind zone length in the UDM system of the LWD caliper is significantly reduced and the capability to detect the remote reflecting interface is considerably improved.

Acoustic Emission and Echo Signal Compensation Techniques Applied to an Ultrasonic Logging-While-Drilling Caliper

PubMed Central

Yao, Yongchao; Ju, Xiaodong; Lu, Junqiang; Men, Baiyong

2017-01-01

A logging-while-drilling (LWD) caliper is a tool used for the real-time measurement of a borehole diameter in oil drilling engineering. This study introduces the mechanical structure and working principle of a new LWD caliper based on ultrasonic distance measurement (UDM). The detection range is a major performance index of a UDM system. This index is determined by the blind zone length and remote reflecting interface detection capability of the system. To reduce the blind zone length and detect near the reflecting interface, a full bridge acoustic emission technique based on bootstrap gate driver (BGD) and metal-oxide-semiconductor field effect transistor (MOSFET) is designed by analyzing the working principle and impedance characteristics of a given piezoelectric transducer. To detect the remote reflecting interface and reduce the dynamic range of the received echo signals, the relationships between the echo amplitude and propagation distance of ultrasonic waves are determined. A signal compensation technique based on time-varying amplification theory, which can automatically change the gain according to the echo arrival time is designed. Lastly, the aforementioned techniques and corresponding circuits are experimentally verified. Results show that the blind zone length in the UDM system of the LWD caliper is significantly reduced and the capability to detect the remote reflecting interface is considerably improved. PMID:28604603

Fault detection and isolation in the challenging Tennessee Eastman process by using image processing techniques.

PubMed

Hajihosseini, Payman; Anzehaee, Mohammad Mousavi; Behnam, Behzad

2018-05-22

The early fault detection and isolation in industrial systems is a critical factor in preventing equipment damage. In the proposed method, instead of using the time signals of sensors, the 2D image obtained by placing these signals next to each other in a matrix has been used; and then a novel fault detection and isolation procedure has been carried out based on image processing techniques. Different features including texture, wavelet transform, mean and standard deviation of the image accompanied with MLP and RBF neural networks based classifiers have been used for this purpose. Obtained results indicate the notable efficacy and success of the proposed method in detecting and isolating faults of the Tennessee Eastman benchmark process and its superiority over previous techniques. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A novel input-parasitic compensation technique for a nanopore-based CMOS DNA detection sensor

NASA Astrophysics Data System (ADS)

Kim, Jungsuk

2016-12-01

This paper presents a novel input-parasitic compensation (IPC) technique for a nanopore-based complementary metal-oxide-semiconductor (CMOS) DNA detection sensor. A resistive-feedback transimpedance amplifier is typically adopted as the headstage of a DNA detection sensor to amplify the minute ionic currents generated from a nanopore and convert them to a readable voltage range for digitization. But, parasitic capacitances arising from the headstage input and the nanopore often cause headstage saturation during nanopore sensing, thereby resulting in significant DNA data loss. To compensate for the unwanted saturation, in this work, we propose an area-efficient and automated IPC technique, customized for a low-noise DNA detection sensor, fabricated using a 0.35- μm CMOS process; we demonstrated this prototype in a benchtop test using an α-hemolysin ( α-HL) protein nanopore.

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

Fusion and Gaussian mixture based classifiers for SONAR data

NASA Astrophysics Data System (ADS)

Kotari, Vikas; Chang, KC

2011-06-01

Underwater mines are inexpensive and highly effective weapons. They are difficult to detect and classify. Hence detection and classification of underwater mines is essential for the safety of naval vessels. This necessitates a formulation of highly efficient classifiers and detection techniques. Current techniques primarily focus on signals from one source. Data fusion is known to increase the accuracy of detection and classification. In this paper, we formulated a fusion-based classifier and a Gaussian mixture model (GMM) based classifier for classification of underwater mines. The emphasis has been on sound navigation and ranging (SONAR) signals due to their extensive use in current naval operations. The classifiers have been tested on real SONAR data obtained from University of California Irvine (UCI) repository. The performance of both GMM based classifier and fusion based classifier clearly demonstrate their superior classification accuracy over conventional single source cases and validate our approach.

Investigation of contact acoustic nonlinearities on metal and composite airframe structures via intensity based health monitoring.

PubMed

Romano, P Q; Conlon, S C; Smith, E C

2013-01-01

Nonlinear structural intensity (NSI) and nonlinear structural surface intensity (NSSI) based damage detection techniques were improved and extended to metal and composite airframe structures. In this study, the measurement of NSI maps at sub-harmonic frequencies was completed to provide enhanced understanding of the energy flow characteristics associated with the damage induced contact acoustic nonlinearity mechanism. Important results include NSI source localization visualization at ultra-subharmonic (nf/2) frequencies, and damage detection results utilizing structural surface intensity in the nonlinear domain. A detection metric relying on modulated wave spectroscopy was developed and implemented using the NSSI feature. The data fusion of the intensity formulation provided a distinct advantage, as both the single interrogation frequency NSSI and its modulated wave extension (NSSI-MW) exhibited considerably higher sensitivities to damage than using single-sensor (strain or acceleration) nonlinear detection metrics. The active intensity based techniques were also extended to composite materials, and results show both NSSI and NSSI-MW can be used to detect damage in the bond line of an integrally stiffened composite plate structure with high sensitivity. Initial damage detection measurements made on an OH-58 tailboom (Penn State Applied Research Laboratory, State College, PA) indicate the techniques can be transitioned to complex airframe structures achieving high detection sensitivities with minimal sensors and actuators.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

Detection of lymphocystis disease virus (LCDV) in asymptomatic cultured gilt-head seabream (Sparus aurata, L.) using an immunoblot technique.

PubMed

Cano, I; Alonso, M C; Garcia-Rosado, E; Saint-Jean, S Rodriguez; Castro, D; Borrego, Juan J

2006-03-10

An immunoblot technique for the detection of lymphocystis disease virus (LCDV) in naturally infected gilt-head seabream (Sparus aurata, L.) has been developed. A specific antiserum against a 60 kDa viral protein has been proven to be an appropriate tool for LCDV diagnosis either from inoculated cell cultures or from fish tissues using the immunoblot assay. The sensitivity of this technique varied between 10(-1) and 10(2) TCID50. LCDV has also been detected in fish tissues from both, diseased and asymptomatic gilt-head seabream. For the asymptomatic fish detection, a viral amplification step in cell culture and a subsequent viral concentration using polyethylene glycol (PEG) (600 wt) are required. On the contrary, immunoblot allowed the detection of LCDV antigens directly from tissue homogenates of diseased fish. The method described in this study shows higher sensitivity than classical detection techniques based on cell culture inoculation.

On the performance of energy detection-based CR with SC diversity over IG channel

NASA Astrophysics Data System (ADS)

Verma, Pappu Kumar; Soni, Sanjay Kumar; Jain, Priyanka

2017-12-01

Cognitive radio (CR) is a viable 5G technology to address the scarcity of the spectrum. Energy detection-based sensing is known to be the simplest method as far as hardware complexity is concerned. In this paper, the performance of spectrum sensing-based energy detection technique in CR networks over inverse Gaussian channel for selection combining diversity technique is analysed. More specifically, accurate analytical expressions for the average detection probability under different detection scenarios such as single channel (no diversity) and with diversity reception are derived and evaluated. Further, the detection threshold parameter is optimised by minimising the probability of error over several diversity branches. The results clearly show the significant improvement in the probability of detection when optimised threshold parameter is applied. The impact of shadowing parameters on the performance of energy detector is studied in terms of complimentary receiver operating characteristic curve. To verify the correctness of our analysis, the derived analytical expressions are corroborated via exact result and Monte Carlo simulations.

A novel pre-processing technique for improving image quality in digital breast tomosynthesis.

PubMed

Kim, Hyeongseok; Lee, Taewon; Hong, Joonpyo; Sabir, Sohail; Lee, Jung-Ryun; Choi, Young Wook; Kim, Hak Hee; Chae, Eun Young; Cho, Seungryong

2017-02-01

Nonlinear pre-reconstruction processing of the projection data in computed tomography (CT) where accurate recovery of the CT numbers is important for diagnosis is usually discouraged, for such a processing would violate the physics of image formation in CT. However, one can devise a pre-processing step to enhance detectability of lesions in digital breast tomosynthesis (DBT) where accurate recovery of the CT numbers is fundamentally impossible due to the incompleteness of the scanned data. Since the detection of lesions such as micro-calcifications and mass in breasts is the purpose of using DBT, it is justified that a technique producing higher detectability of lesions is a virtue. A histogram modification technique was developed in the projection data domain. Histogram of raw projection data was first divided into two parts: One for the breast projection data and the other for background. Background pixel values were set to a single value that represents the boundary between breast and background. After that, both histogram parts were shifted by an appropriate amount of offset and the histogram-modified projection data were log-transformed. Filtered-backprojection (FBP) algorithm was used for image reconstruction of DBT. To evaluate performance of the proposed method, we computed the detectability index for the reconstructed images from clinically acquired data. Typical breast border enhancement artifacts were greatly suppressed and the detectability of calcifications and masses was increased by use of the proposed method. Compared to a global threshold-based post-reconstruction processing technique, the proposed method produced images of higher contrast without invoking additional image artifacts. In this work, we report a novel pre-processing technique that improves detectability of lesions in DBT and has potential advantages over the global threshold-based post-reconstruction processing technique. The proposed method not only increased the lesion detectability but also reduced typical image artifacts pronounced in conventional FBP-based DBT. © 2016 American Association of Physicists in Medicine.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Copy-move forgery detection utilizing Fourier-Mellin transform log-polar features

NASA Astrophysics Data System (ADS)

Dixit, Rahul; Naskar, Ruchira

2018-03-01

In this work, we address the problem of region duplication or copy-move forgery detection in digital images, along with detection of geometric transforms (rotation and rescale) and postprocessing-based attacks (noise, blur, and brightness adjustment). Detection of region duplication, following conventional techniques, becomes more challenging when an intelligent adversary brings about such additional transforms on the duplicated regions. In this work, we utilize Fourier-Mellin transform with log-polar mapping and a color-based segmentation technique using K-means clustering, which help us to achieve invariance to all the above forms of attacks in copy-move forgery detection of digital images. Our experimental results prove the efficiency of the proposed method and its superiority to the current state of the art.

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.

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

Damage Detection Based on Power Dissipation Measured with PZT Sensors through the Combination of Electro-Mechanical Impedances and Guided Waves

PubMed Central

Sevillano, Enrique; Sun, Rui; Perera, Ricardo

2016-01-01

The use of piezoelectric ceramic transducers (such as Lead-Zirconate-Titanate—PZT) has become more and more widespread for Structural Health Monitoring (SHM) applications. Among all the techniques that are based on this smart sensing solution, guided waves and electro-mechanical impedance techniques have found wider acceptance, and so more studies and experimental works can be found containing these applications. However, even though these two techniques can be considered as complementary to each other, little work can be found focused on the combination of them in order to define a new and integrated damage detection procedure. In this work, this combination of techniques has been studied by proposing a new integrated damage indicator based on Electro-Mechanical Power Dissipation (EMPD). The applicability of this proposed technique has been tested through different experimental tests, with both lab-scale and real-scale structures. PMID:27164104

Damage Detection Based on Power Dissipation Measured with PZT Sensors through the Combination of Electro-Mechanical Impedances and Guided Waves.

PubMed

Sevillano, Enrique; Sun, Rui; Perera, Ricardo

2016-05-05

The use of piezoelectric ceramic transducers (such as Lead-Zirconate-Titanate-PZT) has become more and more widespread for Structural Health Monitoring (SHM) applications. Among all the techniques that are based on this smart sensing solution, guided waves and electro-mechanical impedance techniques have found wider acceptance, and so more studies and experimental works can be found containing these applications. However, even though these two techniques can be considered as complementary to each other, little work can be found focused on the combination of them in order to define a new and integrated damage detection procedure. In this work, this combination of techniques has been studied by proposing a new integrated damage indicator based on Electro-Mechanical Power Dissipation (EMPD). The applicability of this proposed technique has been tested through different experimental tests, with both lab-scale and real-scale structures.

Ultrasonic non invasive techniques for microbiological instrumentation

NASA Astrophysics Data System (ADS)

Elvira, L.; Sierra, C.; Galán, B.; Resa, P.

2010-01-01

Non invasive techniques based on ultrasounds have advantageous features to study, characterize and monitor microbiological and enzymatic reactions. These processes may change the sound speed, viscosity or particle distribution size of the medium where they take place, which makes possible their analysis using ultrasonic techniques. In this work, two different systems for the analysis of microbiological liquid media based on ultrasounds are presented. In first place, an industrial application based on an ultrasonic monitoring technique for microbiological growth detection in milk is shown. Such a system may improve the quality control strategies in food production factories, being able to decrease the time required to detect possible contaminations in packed products. Secondly, a study about the growing of the Escherichia coli DH5 α in different conditions is presented. It is shown that the use of ultrasonic non invasive characterization techniques in combination with other conventional measurements like optical density provides complementary information about the metabolism of these bacteria.

Catheter-based time-gated near-infrared fluorescence/OCT imaging system

NASA Astrophysics Data System (ADS)

Lu, Yuankang; Abran, Maxime; Cloutier, Guy; Lesage, Frédéric

2018-02-01

We developed a new dual-modality intravascular imaging system based on fast time-gated fluorescence intensity imaging and spectral domain optical coherence tomography (SD-OCT) for the purpose of interventional detection of atherosclerosis. A pulsed supercontinuum laser was used for fluorescence and OCT imaging. A double-clad fiber (DCF)- based side-firing catheter was designed and fabricated to have a 23 μm spot size at a 2.2 mm working distance for OCT imaging. Its single-mode core is used for OCT, while its inner cladding transports fluorescence excitation light and collects fluorescent photons. The combination of OCT and fluorescence imaging was achieved by using a DCF coupler. For fluorescence detection, we used a time-gated technique with a novel single-photon avalanche diode (SPAD) working in an ultra-fast gating mode. A custom-made delay chip was integrated in the system to adjust the delay between the excitation laser pulse and the SPAD gate-ON window. This technique allowed to detect fluorescent photons of interest while rejecting most of the background photons, thus leading to a significantly improved signal to noise ratio (SNR). Experiments were carried out in turbid media mimicking tissue with an indocyanine green (ICG) inclusion (1 mM and 100 μM) to compare the time-gated technique and the conventional continuous detection technique. The gating technique increased twofold depth sensitivity, and tenfold SNR at large distances. The dual-modality imaging capacity of our system was also validated with a silicone-based tissue-mimicking phantom.

Propulsion Health Monitoring for Enhanced Safety

NASA Technical Reports Server (NTRS)

Butz, Mark G.; Rodriguez, Hector M.

2003-01-01

This report presents the results of the NASA contract Propulsion System Health Management for Enhanced Safety performed by General Electric Aircraft Engines (GE AE), General Electric Global Research (GE GR), and Pennsylvania State University Applied Research Laboratory (PSU ARL) under the NASA Aviation Safety Program. This activity supports the overall goal of enhanced civil aviation safety through a reduction in the occurrence of safety-significant propulsion system malfunctions. Specific objectives are to develop and demonstrate vibration diagnostics techniques for the on-line detection of turbine rotor disk cracks, and model-based fault tolerant control techniques for the prevention and mitigation of in-flight engine shutdown, surge/stall, and flameout events. The disk crack detection work was performed by GE GR which focused on a radial-mode vibration monitoring technique, and PSU ARL which focused on a torsional-mode vibration monitoring technique. GE AE performed the Model-Based Fault Tolerant Control work which focused on the development of analytical techniques for detecting, isolating, and accommodating gas-path faults.

Antibody detection tests improve the sensitivity of tuberculosis diagnosis in cattle.

PubMed

Casal, C; Infantes, J A; Risalde, M A; Díez-Guerrier, A; Domínguez, M; Moreno, I; Romero, B; de Juan, L; Sáez, J L; Juste, R; Gortázar, C; Domínguez, L; Bezos, J

2017-06-01

We evaluated the sensitivity (Se) of the single cervical intradermal tuberculin (SIT) test, two interferon-gamma (IFN-γ) assays and three different antibody detection techniques for bovine tuberculosis (bTB) diagnosis in 131 mixed beef breed cattle. The results of the diagnostic techniques performed over the whole herd, and over the animals confirmed as infected based on the presence of lesions compatible with the disease and/or M. bovis isolation were compared to determine apparent prevalence (AP) and Se. The Se of the SIT test (severe interpretation) was 63.7% (95% CI, 54.54-72.00), while the Se of the IFN-γ assays ranged between 60.2% and 92%. The proportion of infected cattle detected by the different antibody detection techniques ranged from 65.5% to 87.6%. Three of the antibody detection techniques yielded a significant higher (p<0.05) Se than that achieved with the official diagnostic techniques. In addition, the interpretation in parallel of cellular and antibody detection techniques reached the highest Se: 98.2% (95% CI, 93.78-99.51) suggesting that the use of diagnostic techniques detecting both cellular and humoral responses could be considered as an alternative in the control of bTB outbreaks in high prevalence settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient dynamic events discrimination technique for fiber distributed Brillouin sensors.

PubMed

Galindez, Carlos A; Madruga, Francisco J; Lopez-Higuera, Jose M

2011-09-26

A technique to detect real time variations of temperature or strain in Brillouin based distributed fiber sensors is proposed and is investigated in this paper. The technique is based on anomaly detection methods such as the RX-algorithm. Detection and isolation of dynamic events from the static ones are demonstrated by a proper processing of the Brillouin gain values obtained by using a standard BOTDA system. Results also suggest that better signal to noise ratio, dynamic range and spatial resolution can be obtained. For a pump pulse of 5 ns the spatial resolution is enhanced, (from 0.541 m obtained by direct gain measurement, to 0.418 m obtained with the technique here exposed) since the analysis is concentrated in the variation of the Brillouin gain and not only on the averaging of the signal along the time. © 2011 Optical Society of America

Effect of background correction on peak detection and quantification in online comprehensive two-dimensional liquid chromatography using diode array detection.

PubMed

Allen, Robert C; John, Mallory G; Rutan, Sarah C; Filgueira, Marcelo R; Carr, Peter W

2012-09-07

A singular value decomposition-based background correction (SVD-BC) technique is proposed for the reduction of background contributions in online comprehensive two-dimensional liquid chromatography (LC×LC) data. The SVD-BC technique was compared to simply subtracting a blank chromatogram from a sample chromatogram and to a previously reported background correction technique for one dimensional chromatography, which uses an asymmetric weighted least squares (AWLS) approach. AWLS was the only background correction technique to completely remove the background artifacts from the samples as evaluated by visual inspection. However, the SVD-BC technique greatly reduced or eliminated the background artifacts as well and preserved the peak intensity better than AWLS. The loss in peak intensity by AWLS resulted in lower peak counts at the detection thresholds established using standards samples. However, the SVD-BC technique was found to introduce noise which led to detection of false peaks at the lower detection thresholds. As a result, the AWLS technique gave more precise peak counts than the SVD-BC technique, particularly at the lower detection thresholds. While the AWLS technique resulted in more consistent percent residual standard deviation values, a statistical improvement in peak quantification after background correction was not found regardless of the background correction technique used. Copyright © 2012 Elsevier B.V. All rights reserved.

A coherent detection technique via optically biased field for broadband terahertz radiation.

PubMed

Du, Hai-Wei; Dong, Jia-Meng; Liu, Yi; Shi, Chang-Cheng; Wu, Jing-Wei; Peng, Xiao-Yu

2017-09-01

We demonstrate theoretically and experimentally a coherent terahertz detection technique based on an optically biased field functioning as a local oscillator and a second harmonic induced by the terahertz electric field in the air sensor working in free space. After optimizing the polarization angle and the energy of the probe pulse, and filling the system with dry nitrogen, the terahertz radiation generated from a two-color-femtosecond-laser-pulses induced plasma filament is measured by this technique with a bandwidth of 0.1-10 THz and a signal-to-noise ratio of 48 dB. Our technique provides an alternative simple method for coherent broadband terahertz detection.

A dual-mode generalized likelihood ratio approach to self-reorganizing digital flight control system design

NASA Technical Reports Server (NTRS)

1976-01-01

Analytic techniques have been developed for detecting and identifying abrupt changes in dynamic systems. The GLR technique monitors the output of the Kalman filter and searches for the time that the failure occured, thus allowing it to be sensitive to new data and consequently increasing the chances for fast system recovery following detection of a failure. All failure detections are based on functional redundancy. Performance tests of the F-8 aircraft flight control system and computerized modelling of the technique are presented.

Intracavity optogalvanic spectroscopy. An analytical technique for 14C analysis with subattomole sensitivity.

PubMed

Murnick, Daniel E; Dogru, Ozgur; Ilkmen, Erhan

2008-07-01

We show a new ultrasensitive laser-based analytical technique, intracavity optogalvanic spectroscopy, allowing extremely high sensitivity for detection of (14)C-labeled carbon dioxide. Capable of replacing large accelerator mass spectrometers, the technique quantifies attomoles of (14)C in submicrogram samples. Based on the specificity of narrow laser resonances coupled with the sensitivity provided by standing waves in an optical cavity and detection via impedance variations, limits of detection near 10(-15) (14)C/(12)C ratios are obtained. Using a 15-W (14)CO2 laser, a linear calibration with samples from 10(-15) to >1.5 x 10(-12) in (14)C/(12)C ratios, as determined by accelerator mass spectrometry, is demonstrated. Possible applications include microdosing studies in drug development, individualized subtherapeutic tests of drug metabolism, carbon dating and real time monitoring of atmospheric radiocarbon. The method can also be applied to detection of other trace entities.

Chemical and biological threat-agent detection using electrophoresis-based lab-on-a-chip devices.

PubMed

Borowsky, Joseph; Collins, Greg E

2007-10-01

The ability to separate complex mixtures of analytes has made capillary electrophoresis (CE) a powerful analytical tool since its modern configuration was first introduced over 25 years ago. The technique found new utility with its application to the microfluidics based lab-on-a-chip platform (i.e., microchip), which resulted in ever smaller footprints, sample volumes, and analysis times. These features, coupled with the technique's potential for portability, have prompted recent interest in the development of novel analyzers for chemical and biological threat agents. This article will comment on three main areas of microchip CE as applied to the separation and detection of threat agents: detection techniques and their corresponding limits of detection, sampling protocol and preparation time, and system portability. These three areas typify the broad utility of lab-on-a-chip for meeting critical, present-day security, in addition to illustrating areas wherein advances are necessary.

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

PubMed

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

2013-07-15

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

Transient Faults in Computer Systems

NASA Technical Reports Server (NTRS)

Masson, Gerald M.

1993-01-01

A powerful technique particularly appropriate for the detection of errors caused by transient faults in computer systems was developed. The technique can be implemented in either software or hardware; the research conducted thus far primarily considered software implementations. The error detection technique developed has the distinct advantage of having provably complete coverage of all errors caused by transient faults that affect the output produced by the execution of a program. In other words, the technique does not have to be tuned to a particular error model to enhance error coverage. Also, the correctness of the technique can be formally verified. The technique uses time and software redundancy. The foundation for an effective, low-overhead, software-based certification trail approach to real-time error detection resulting from transient fault phenomena was developed.

The signature-based radiation-scanning approach to standoff detection of improvised explosive devices.

PubMed

Brewer, R L; Dunn, W L; Heider, S; Matthew, C; Yang, X

2012-07-01

The signature-based radiation-scanning technique for detection of improvised explosive devices is described. The technique seeks to detect nitrogen-rich chemical explosives present in a target. The technology compares a set of "signatures" obtained from a test target to a collection of "templates", sets of signatures for a target that contain an explosive in a specific configuration. Interrogation of nitrogen-rich fertilizer samples, which serve as surrogates for explosives, is shown experimentally to be able to discriminate samples of 3.8L and larger. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

Lin, Jia-Hui; Tseng, Wei-Lung

2015-01-01

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

Feathering effect detection and artifact agglomeration index-based video deinterlacing technique

NASA Astrophysics Data System (ADS)

Martins, André Luis; Rodrigues, Evandro Luis Linhari; de Paiva, Maria Stela Veludo

2018-03-01

Several video deinterlacing techniques have been developed, and each one presents a better performance in certain conditions. Occasionally, even the most modern deinterlacing techniques create frames with worse quality than primitive deinterlacing processes. This paper validates that the final image quality can be improved by combining different types of deinterlacing techniques. The proposed strategy is able to select between two types of deinterlaced frames and, if necessary, make the local correction of the defects. This decision is based on an artifact agglomeration index obtained from a feathering effect detection map. Starting from a deinterlaced frame produced by the "interfield average" method, the defective areas are identified, and, if deemed appropriate, these areas are replaced by pixels generated through the "edge-based line average" method. Test results have proven that the proposed technique is able to produce video frames with higher quality than applying a single deinterlacing technique through getting what is good from intra- and interfield methods.

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.

PubMed

Nguyen, Thanh; Bui, Vy; Lam, Van; Raub, Christopher B; Chang, Lin-Ching; Nehmetallah, George

2017-06-26

We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the background for quantitative measurement. This would be a drawback in real time implementation and for dynamic processes such as cell migration phenomena. A recent automatic aberration compensation approach using principle component analysis (PCA) in DHM avoids human intervention regardless of the cells' motion. However, it corrects spherical/elliptical aberration only and disregards the higher order aberrations. Traditional image segmentation techniques can be employed to spatially detect cell locations. Ideally, automatic image segmentation techniques make real time measurement possible. However, existing automatic unsupervised segmentation techniques have poor performance when applied to DHM phase images because of aberrations and speckle noise. In this paper, we propose a novel method that combines a supervised deep learning technique with convolutional neural network (CNN) and Zernike polynomial fitting (ZPF). The deep learning CNN is implemented to perform automatic background region detection that allows for ZPF to compute the self-conjugated phase to compensate for most aberrations.

Exo-Dye-based assay for rapid, inexpensive, and sensitive detection of DNA-binding proteins.

PubMed

Chen, Zaozao; Ji, Meiju; Hou, Peng; Lu, Zuhong

2006-07-07

We reported herein a rapid, inexpensive, and sensitive technique for detecting sequence-specific DNA-binding proteins. In this technique, the common exonuclease III (ExoIII) footprinting assay is coupled with simple SYBR Green I staining for monitoring the activities of DNA-binding proteins. We named this technique as ExoIII-Dye-based assay. In this assay, a duplex probe was designed to detect DNA-binding protein. One side of the probe contains one protein-binding site, and another side of it contains five protruding bases at 3' end for protection from ExoIII digestion. If a target protein is present, it will bind to binding sites of probe and produce a physical hindrance to ExoIII, which protects the duplex probe from digestion of ExoIII. SYBR Green I will bind to probe, which results in high fluorescence intensity. On the contrary, in the absence of the target protein, the naked duplex probe will be degraded by ExoIII. SYBR Green I will be released, which results in a low fluorescence intensity. In this study, we employed this technique to successfully detect transcription factor NF-kappaB in crude cell extracts. Moreover, it could also be used to evaluate the binding affinity of NF-kappaB. This technique has therefore wide potential application in research, medical diagnosis, and drug discovery.

Bioanalytical Applications of Fluorescence Line-Narrowing and Non-Line-Narrowing Spectroscopy Interfaced with Capillary Electrophoresis and High-Performance Liquid Chromatography

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

Roberts, Kenneth Paul

Capillary electrophoresis (CE) and high-performance liquid chromatography (HPLC) are widely used analytical separation techniques with many applications in chemical, biochemical, and biomedical sciences. Conventional analyte identification in these techniques is based on retention/migration times of standards; requiring a high degree of reproducibility, availability of reliable standards, and absence of coelution. From this, several new information-rich detection methods (also known as hyphenated techniques) are being explored that would be capable of providing unambiguous on-line identification of separating analytes in CE and HPLC. As further discussed, a number of such on-line detection methods have shown considerable success, including Raman, nuclear magnetic resonancemore » (NMR), mass spectrometry (MS), and fluorescence line-narrowing spectroscopy (FLNS). In this thesis, the feasibility and potential of combining the highly sensitive and selective laser-based detection method of FLNS with analytical separation techniques are discussed and presented. A summary of previously demonstrated FLNS detection interfaced with chromatography and electrophoresis is given, and recent results from on-line FLNS detection in CE (CE-FLNS), and the new combination of HPLC-FLNS, are shown.« less

Ground-based deep-space LADAR for satellite detection: A parametric study

NASA Astrophysics Data System (ADS)

Davey, Kevin F.

1989-12-01

The minimum performance requirements are determined of a ground based infrared LADAR designed to detect deep space satellites, and a candidate sensor design is presented based on current technology. The research examines LADAR techniques and detection methods to determine the optimum LADAR configuration, and then assesses the effects of atmospheric transmission, background radiance, and turbulence across the infrared region to find the optimum laser wavelengths. Diffraction theory is then used in a parametric analysis of the transmitted laser beam and received signal, using a Cassegrainian telescope design and heterodyne detection. The effects of beam truncation and obscuration, heterodyne misalignment, off-boresight detection, and image-pixel geometry are also included in the analysis. The derived equations are then used to assess the feasibility of several candidate designs under a wide range of detection conditions including daylight operation through cirrus. The results show that successful detection is theoretically possible under most conditions by transmitting a high power frequency modulated pulse train from an isotopic 13CO2 laser radiating at 11.17 micrometers, and utilizing post-detection integration and pulse compression techniques.

Automated Video-Based Traffic Count Analysis.

DOT National Transportation Integrated Search

2016-01-01

The goal of this effort has been to develop techniques that could be applied to the : detection and tracking of vehicles in overhead footage of intersections. To that end we : have developed and published techniques for vehicle tracking based on dete...

Negative electrospray ionization on porous supporting tips for mass spectrometric analysis: electrostatic charging effect on detection sensitivity and its application to explosive detection.

PubMed

Wong, Melody Yee-Man; Man, Sin-Heng; Che, Chi-Ming; Lau, Kai-Chung; Ng, Kwan-Ming

2014-03-21

The simplicity and easy manipulation of a porous substrate-based ESI-MS technique have been widely applied to the direct analysis of different types of samples in positive ion mode. However, the study and application of this technique in negative ion mode are sparse. A key challenge could be due to the ease of electrical discharge on supporting tips upon the application of negative voltage. The aim of this study is to investigate the effect of supporting materials, including polyester, polyethylene and wood, on the detection sensitivity of a porous substrate-based negative ESI-MS technique. By using nitrobenzene derivatives and nitrophenol derivatives as the target analytes, it was found that the hydrophobic materials (i.e., polyethylene and polyester) with a higher tendency to accumulate negative charge could enhance the detection sensitivity towards nitrobenzene derivatives via electron-capture ionization; whereas, compounds with electron affinities lower than the cut-off value (1.13 eV) were not detected. Nitrophenol derivatives with pKa smaller than 9.0 could be detected in the form of deprotonated ions; whereas polar materials (i.e., wood), which might undergo competitive deprotonation with the analytes, could suppress the detection sensitivity. With the investigation of the material effects on the detection sensitivity, the porous substrate-based negative ESI-MS method was developed and applied to the direct detection of two commonly encountered explosives in complex samples.

Study of fault tolerant software technology for dynamic systems

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Zacharias, G. L.

1985-01-01

The major aim of this study is to investigate the feasibility of using systems-based failure detection isolation and compensation (FDIC) techniques in building fault-tolerant software and extending them, whenever possible, to the domain of software fault tolerance. First, it is shown that systems-based FDIC methods can be extended to develop software error detection techniques by using system models for software modules. In particular, it is demonstrated that systems-based FDIC techniques can yield consistency checks that are easier to implement than acceptance tests based on software specifications. Next, it is shown that systems-based failure compensation techniques can be generalized to the domain of software fault tolerance in developing software error recovery procedures. Finally, the feasibility of using fault-tolerant software in flight software is investigated. In particular, possible system and version instabilities, and functional performance degradation that may occur in N-Version programming applications to flight software are illustrated. Finally, a comparative analysis of N-Version and recovery block techniques in the context of generic blocks in flight software is presented.

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

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

Gibson, Adam; Piquette, Kathryn E.; Bergmann, Uwe

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to providemore » robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. Finally, the tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.« less

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

DOE PAGES

Gibson, Adam; Piquette, Kathryn E.; Bergmann, Uwe; ...

2018-02-26

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to providemore » robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. Finally, the tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.« less

Label and label-free based surface-enhanced Raman scattering for pathogen bacteria detection: A review.

PubMed

Liu, Yu; Zhou, Haibo; Hu, Ziwei; Yu, Guangxia; Yang, Danting; Zhao, Jinshun

2017-08-15

Rapid, accurate detection of pathogen bacteria is a highly topical research area for the sake of food safety and public health. Surface-enhanced Raman scattering (SERS) is being considered as a powerful and attractive technique for pathogen bacteria detection, due to its sensitivity, high speed, comparatively low cost, multiplexing ability and portability. This contribution aims to give a comprehensive overview of SERS as a technique for rapid detection of pathogen bacteria based on label and label-free strategies. A brief tutorial on SERS is given first of all. Then we summarize the recent trends and developments of label and label-free based SERS applied to detection of pathogen bacteria, including the relatively complete interpretation of SERS spectra. In addition, multifunctional SERS platforms for pathogen bacteria in matrix are discussed as well. Furthermore, an outlook of the work done and a perspective on the future directions of SERS as a reliable tool for real-time pathogen bacteria detection are given. Copyright © 2017 Elsevier B.V. All rights reserved.

A three-wavelength multi-channel brain functional imager based on digital lock-in photon-counting technique

NASA Astrophysics Data System (ADS)

Ding, Xuemei; Wang, Bingyuan; Liu, Dongyuan; Zhang, Yao; He, Jie; Zhao, Huijuan; Gao, Feng

2018-02-01

During the past two decades there has been a dramatic rise in the use of functional near-infrared spectroscopy (fNIRS) as a neuroimaging technique in cognitive neuroscience research. Diffuse optical tomography (DOT) and optical topography (OT) can be employed as the optical imaging techniques for brain activity investigation. However, most current imagers with analogue detection are limited by sensitivity and dynamic range. Although photon-counting detection can significantly improve detection sensitivity, the intrinsic nature of sequential excitations reduces temporal resolution. To improve temporal resolution, sensitivity and dynamic range, we develop a multi-channel continuous-wave (CW) system for brain functional imaging based on a novel lock-in photon-counting technique. The system consists of 60 Light-emitting device (LED) sources at three wavelengths of 660nm, 780nm and 830nm, which are modulated by current-stabilized square-wave signals at different frequencies, and 12 photomultiplier tubes (PMT) based on lock-in photon-counting technique. This design combines the ultra-high sensitivity of the photon-counting technique with the parallelism of the digital lock-in technique. We can therefore acquire the diffused light intensity for all the source-detector pairs (SD-pairs) in parallel. The performance assessments of the system are conducted using phantom experiments, and demonstrate its excellent measurement linearity, negligible inter-channel crosstalk, strong noise robustness and high temporal resolution.

Rapid Detection and Identification of Streptococcus Iniae Using a Monoclonal Antibody-Based Indirect Fluorescent Antibody Technique

USDA-ARS?s Scientific Manuscript database

Streptococcus iniae is among the major pathogens of a large number of fish species cultured in fresh and marine recirculating and net pen production systems . The traditional plate culture technique to detect and identify S. iniae is time consuming and may be problematic due to phenotypic variations...

Damage detection methodology under variable load conditions based on strain field pattern recognition using FBGs, nonlinear principal component analysis, and clustering techniques

NASA Astrophysics Data System (ADS)

Sierra-Pérez, Julián; Torres-Arredondo, M.-A.; Alvarez-Montoya, Joham

2018-01-01

Structural health monitoring consists of using sensors integrated within structures together with algorithms to perform load monitoring, damage detection, damage location, damage size and severity, and prognosis. One possibility is to use strain sensors to infer structural integrity by comparing patterns in the strain field between the pristine and damaged conditions. In previous works, the authors have demonstrated that it is possible to detect small defects based on strain field pattern recognition by using robust machine learning techniques. They have focused on methodologies based on principal component analysis (PCA) and on the development of several unfolding and standardization techniques, which allow dealing with multiple load conditions. However, before a real implementation of this approach in engineering structures, changes in the strain field due to conditions different from damage occurrence need to be isolated. Since load conditions may vary in most engineering structures and promote significant changes in the strain field, it is necessary to implement novel techniques for uncoupling such changes from those produced by damage occurrence. A damage detection methodology based on optimal baseline selection (OBS) by means of clustering techniques is presented. The methodology includes the use of hierarchical nonlinear PCA as a nonlinear modeling technique in conjunction with Q and nonlinear-T 2 damage indices. The methodology is experimentally validated using strain measurements obtained by 32 fiber Bragg grating sensors bonded to an aluminum beam under dynamic bending loads and simultaneously submitted to variations in its pitch angle. The results demonstrated the capability of the methodology for clustering data according to 13 different load conditions (pitch angles), performing the OBS and detecting six different damages induced in a cumulative way. The proposed methodology showed a true positive rate of 100% and a false positive rate of 1.28% for a 99% of confidence.

Recombinase polymerase amplification applied to plant virus detection and potential implications.

PubMed

Babu, Binoy; Ochoa-Corona, Francisco M; Paret, Mathews L

2018-04-01

Several isothermal techniques for the detection of plant pathogens have been developed with the advent of molecular techniques. Among them, Recombinase Polymerase Amplification (RPA) is becoming an important technique for the rapid, sensitive and cost-effective detection of plant viruses. The RPA technology has the advantage to be implemented in field-based scenarios because the method requires a minimal sample preparation, and is performed at constant low temperature (37-42 °C). The RPA technique is rapidly becoming a promising tool for use in rapid detection and further diagnostics in plant clinics and monitoring quarantine services. This paper presents a review of studies conducted using RPA for detection/diagnosis of plant viruses with either DNA genomes (Banana bunchy top virus, Bean golden yellow mosaic virus, Tomato mottle virus, Tomato yellow leaf curl virus) or RNA genomes (Little Cherry virus 2, Plum pox virus and Rose rosette virus). Copyright © 2018 Elsevier Inc. All rights reserved.

[Aging explosive detection using terahertz time-domain spectroscopy].

PubMed

Meng, Kun; Li, Ze-ren; Liu, Qiao

2011-05-01

Detecting the aging situation of stock explosive is essentially meaningful to the research on the capability, security and stability of explosive. Existing aging explosive detection techniques, such as scan microscope technique, Fourier transfer infrared spectrum technique, gas chromatogram mass spectrum technique and so on, are either not able to differentiate whether the explosive is aging or not, or not able to image the structure change of the molecule. In the present paper, using the density functional theory (DFT), the absorb spectrum changes after the explosive aging were calculated, from which we can clearly find the difference of spectrum between explosive molecule and aging ones in the terahertz band. The terahertz time-domain spectrum (THz-TDS) system as well as its frequency spectrum resolution and measured range are analyzed. Combined with the existing experimental results and the essential characters of the terahertz wave, the application of THz-TDS technique to the detection of aging explosive was demonstrated from the aspects of feasibility, veracity and practicability. On the base of that, the authors advance the new method of aging explosive detection using the terahertz time-domain spectrum technique.

Combination of process and vibration data for improved condition monitoring of industrial systems working under variable operating conditions

NASA Astrophysics Data System (ADS)

Ruiz-Cárcel, C.; Jaramillo, V. H.; Mba, D.; Ottewill, J. R.; Cao, Y.

2016-01-01

The detection and diagnosis of faults in industrial processes is a very active field of research due to the reduction in maintenance costs achieved by the implementation of process monitoring algorithms such as Principal Component Analysis, Partial Least Squares or more recently Canonical Variate Analysis (CVA). Typically the condition of rotating machinery is monitored separately using vibration analysis or other specific techniques. Conventional vibration-based condition monitoring techniques are based on the tracking of key features observed in the measured signal. Typically steady-state loading conditions are required to ensure consistency between measurements. In this paper, a technique based on merging process and vibration data is proposed with the objective of improving the detection of mechanical faults in industrial systems working under variable operating conditions. The capabilities of CVA for detection and diagnosis of faults were tested using experimental data acquired from a compressor test rig where different process faults were introduced. Results suggest that the combination of process and vibration data can effectively improve the detectability of mechanical faults in systems working under variable operating conditions.

A hybrid approach for efficient anomaly detection using metaheuristic methods

PubMed Central

Ghanem, Tamer F.; Elkilani, Wail S.; Abdul-kader, Hatem M.

2014-01-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms. PMID:26199752

A hybrid approach for efficient anomaly detection using metaheuristic methods.

PubMed

Ghanem, Tamer F; Elkilani, Wail S; Abdul-Kader, Hatem M

2015-07-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

Photoacoustic Techniques for Trace Gas Sensing Based on Semiconductor Laser Sources

PubMed Central

Elia, Angela; Lugarà, Pietro Mario; Di Franco, Cinzia; Spagnolo, Vincenzo

2009-01-01

The paper provides an overview on the use of photoacoustic sensors based on semiconductor laser sources for the detection of trace gases. We review the results obtained using standard, differential and quartz enhanced photoacoustic techniques. PMID:22303143

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

An Approach to V&V of Embedded Adaptive Systems

NASA Technical Reports Server (NTRS)

Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth

2004-01-01

Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

Multiscale corner detection and classification using local properties and semantic patterns

NASA Astrophysics Data System (ADS)

Gallo, Giovanni; Giuoco, Alessandro L.

2002-05-01

A new technique to detect, localize and classify corners in digital closed curves is proposed. The technique is based on correct estimation of support regions for each point. We compute multiscale curvature to detect and to localize corners. As a further step, with the aid of some local features, it's possible to classify corners into seven distinct types. Classification is performed using a set of rules, which describe corners according to preset semantic patterns. Compared with existing techniques, the proposed approach inscribes itself into the family of algorithms that try to explain the curve, instead of simple labeling. Moreover, our technique works in manner similar to what is believed are typical mechanisms of human perception.

Comparison of conditional sampling and averaging techniques in a turbulent boundary layer

NASA Astrophysics Data System (ADS)

Subramanian, C. S.; Rajagopalan, S.; Antonia, R. A.; Chambers, A. J.

1982-10-01

A rake of cold wires was used in a slightly heated boundary layer to identify coherent temperature fronts. An X-wire/cold-wire arrangement was used simultaneously with the rake to provide measurements of the longitudinal and normal velocity fluctuations and temperature fluctuations. Conditional averages of these parameters and their products were obtained by application of conditional techniques (VITA, HOLE, BT, RA1, and RA3) based on the detection of temperature fronts using information obtained at only one point in space. It is found that none of the one-point detection techniques is in good quantitative agreement with the rake detection technique, the largest correspondence being 51%. Despite the relatively poor correspondence between the conditional techniques, these techniques, with the exception of HOLE, produce conditional averages that are in reasonable qualitative agreement with those deduced using the rake.

Distributed Transforms for Efficient Data Gathering in Sensor Networks

NASA Technical Reports Server (NTRS)

Ortega, Antonio (Inventor); Shen, Godwin (Inventor); Narang, Sunil K. (Inventor); Perez-Trufero, Javier (Inventor)

2014-01-01

Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.

[Application of isothermal amplification technology for pathogen detection in parasitic and other diseases].

PubMed

Ting, Li; Kun, Yang

2018-04-16

The in vitro nucleic acid amplification technique based on polymerase chain reaction (PCR) has been successfully applied to scientific researches. In recent years, the emergence of isothermal amplification technology is increasingly applied in the molecular diagnosis and disease detection because of its advantages of constant temperature, high efficiency, short time-consuming, and less reliance on equipment and instruments. The principle, characteristics and application of the partial isothermal amplification technique in the pathogen detection in parasitic and other diseases are reviewed in this paper, and the prospects of the wide development of the technique are also discussed.

Min-max hyperellipsoidal clustering for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A

2006-08-01

A novel hyperellipsoidal clustering technique is presented for an intrusion-detection system in network security. Hyperellipsoidal clusters toward maximum intracluster similarity and minimum intercluster similarity are generated from training data sets. The novelty of the technique lies in the fact that the parameters needed to construct higher order data models in general multivariate Gaussian functions are incrementally derived from the data sets using accretive processes. The technique is implemented in a feedforward neural network that uses a Gaussian radial basis function as the model generator. An evaluation based on the inclusiveness and exclusiveness of samples with respect to specific criteria is applied to accretively learn the output clusters of the neural network. One significant advantage of this is its ability to detect individual anomaly types that are hard to detect with other anomaly-detection schemes. Applying this technique, several feature subsets of the tcptrace network-connection records that give above 95% detection at false-positive rates below 5% were identified.

Investigation of a Moire Based Crack Detection Technique for Propulsion Health Monitoring

NASA Technical Reports Server (NTRS)

Woike, Mark R.; Abudl-Aziz, Ali; Fralick, Gustave C.; Wrbanek, John D.

2012-01-01

The development of techniques for the health monitoring of the rotating components in gas turbine engines is of major interest to NASA s Aviation Safety Program. As part of this on-going effort several experiments utilizing a novel optical Moir based concept along with external blade tip clearance and shaft displacement instrumentation were conducted on a simulated turbine engine disk as a means of demonstrating a potential optical crack detection technique. A Moir pattern results from the overlap of two repetitive patterns with slightly different periods. With this technique, it is possible to detect very small differences in spacing and hence radial growth in a rotating disk due to a flaw such as a crack. The experiment involved etching a circular reference pattern on a subscale engine disk that had a 50.8 mm (2 in.) long notch machined into it to simulate a crack. The disk was operated at speeds up to 12 000 rpm and the Moir pattern due to the shift with respect to the reference pattern was monitored as a means of detecting the radial growth of the disk due to the defect. In addition, blade displacement data were acquired using external blade tip clearance and shaft displacement sensors as a means of confirming the data obtained from the optical technique. The results of the crack detection experiments and its associated analysis are presented in this paper.

Activity Detection and Retrieval for Image and Video Data with Limited Training

DTIC Science & Technology

2015-06-10

applications. Here we propose two techniques for image segmentation. The first involves an automata based multiple threshold selection scheme, where a... automata . For our second approach to segmentation, we employ a region based segmentation technique that is capable of handling intensity inhomogeneity...techniques for image segmentation. The first involves an automata based multiple threshold selection scheme, where a mixture of Gaussian is fitted to the

Detection of pathogenic organisms in food, water, and body fluids

NASA Astrophysics Data System (ADS)

Wallace, William H.; Henley, Michael V.; Sayler, Gary S.

2002-06-01

The construction of specific bioluminescent bacteriophage for detection of pathogenic organism can be developed to overcome interferences in complex matrices such as food, water and body fluids. Detection and identification of bacteria often require several days and frequently weeks by standard methods of isolation, growth and biochemical test. Immunoassay detection often requires the expression of the bacterial toxin, which can lead to non-detection of cells that may express the toxin under conditions different from testing protocols. Immunoassays require production of a specific antibody to the agent for detection and interference by contaminants frequently affects results. PCR based detection may be inhibited by substances in complex matrices. Modified methods of the PCR technique, such as magnetic capture-hybridization PCR (MCH-PCR), appear to improve the technique by removing the DNA products away from the inhibitors. However, the techniques required for PCR-based detection are slow and the procedures require skilled personnel working with labile reagents. Our approach is based on transferring bioluminescence (lux) genes into a selected bacteriophage. Bacteriophages are bacterial viruses that are widespread in nature and often are genus and species specific. This specificity eliminates or reduces false positives in a bacteriophage assay. The phage recognizes a specific receptor molecule on the surface of a susceptible bacterium, attaches and then injects the viral nucleic acid into the cell. The injected viral genome is expressed and then replicated, generating numerous exact copies of the viral genetic material including the lux genes, often resulting in an increase in bioluminescence by several hundred fold.

Benford's Law based detection of latent fingerprint forgeries on the example of artificial sweat printed fingerprints captured by confocal laser scanning microscopes

NASA Astrophysics Data System (ADS)

Hildebrandt, Mario; Dittmann, Jana

2015-03-01

The possibility of forging latent fingerprints at crime scenes is known for a long time. Ever since it has been stated that an expert is capable of recognizing the presence of multiple identical latent prints as an indicator towards forgeries. With the possibility of printing fingerprint patterns to arbitrary surfaces using affordable ink- jet printers equipped with artificial sweat, it is rather simple to create a multitude of fingerprints with slight variations to avoid raising any suspicion. Such artificially printed fingerprints are often hard to detect during the analysis procedure. Moreover, the visibility of particular detection properties might be decreased depending on the utilized enhancement and acquisition technique. In previous work primarily such detection properties are used in combination with non-destructive high resolution sensory and pattern recognition techniques to detect fingerprint forgeries. In this paper we apply Benford's Law in the spatial domain to differentiate between real latent fingerprints and printed fingerprints. This technique has been successfully applied in media forensics to detect image manipulations. We use the differences between Benford's Law and the distribution of the most significant digit of the intensity and topography data from a confocal laser scanning microscope as features for a pattern recognition based detection of printed fingerprints. Our evaluation based on 3000 printed and 3000 latent print samples shows a very good detection performance of up to 98.85% using WEKA's Bagging classifier in a 10-fold stratified cross-validation.

Long fiber Bragg grating sensor interrogation using discrete-time microwave photonic filtering techniques.

PubMed

Ricchiuti, Amelia Lavinia; Barrera, David; Sales, Salvador; Thevenaz, Luc; Capmany, José

2013-11-18

A novel technique for interrogating photonic sensors based on long fiber Bragg gratings (FBGs) is presented and experimentally demonstrated, dedicated to detect the presence and the precise location of several spot events. The principle of operation is based on a technique used to analyze microwave photonics (MWP) filters. The long FBGs are used as quasi-distributed sensors. Several hot-spots can be detected along the FBG with a spatial accuracy under 0.5 mm using a modulator and a photo-detector (PD) with a modest bandwidth of less than 1 GHz. The proposed interrogation system is intrinsically robust against environmental changes.

Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique.

PubMed

Chen, Wen; Chowdhury, Fahmida N; Djuric, Ana; Yeh, Chih-Ping

2014-09-01

This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Detecting transitions in protein dynamics using a recurrence quantification analysis based bootstrap method.

PubMed

Karain, Wael I

2017-11-28

Proteins undergo conformational transitions over different time scales. These transitions are closely intertwined with the protein's function. Numerous standard techniques such as principal component analysis are used to detect these transitions in molecular dynamics simulations. In this work, we add a new method that has the ability to detect transitions in dynamics based on the recurrences in the dynamical system. It combines bootstrapping and recurrence quantification analysis. We start from the assumption that a protein has a "baseline" recurrence structure over a given period of time. Any statistically significant deviation from this recurrence structure, as inferred from complexity measures provided by recurrence quantification analysis, is considered a transition in the dynamics of the protein. We apply this technique to a 132 ns long molecular dynamics simulation of the β-Lactamase Inhibitory Protein BLIP. We are able to detect conformational transitions in the nanosecond range in the recurrence dynamics of the BLIP protein during the simulation. The results compare favorably to those extracted using the principal component analysis technique. The recurrence quantification analysis based bootstrap technique is able to detect transitions between different dynamics states for a protein over different time scales. It is not limited to linear dynamics regimes, and can be generalized to any time scale. It also has the potential to be used to cluster frames in molecular dynamics trajectories according to the nature of their recurrence dynamics. One shortcoming for this method is the need to have large enough time windows to insure good statistical quality for the recurrence complexity measures needed to detect the transitions.

Direct Detection Doppler Lidar for Spaceborne Wind Measurement

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Flesia, Cristina

1999-01-01

Aerosol and molecular based versions of the double-edge technique can be used for direct detection Doppler lidar spaceborne wind measurement. The edge technique utilizes the edge of a high spectral resolution filter for high accuracy wind measurement using direct detection lidar. The signal is split between an edge filter channel and a broadband energy monitor channel. The energy monitor channel is used for signal normalization. The edge measurement is made as a differential frequency measurement between the outgoing laser signal and the atmospheric backscattered return for each pulse. As a result the measurement is insensitive to laser and edge filter frequency jitter and drift at a level less than a few parts in 10(exp 10). We have developed double edge versions of the edge technique for aerosol and molecular-based lidar measurement of the wind. Aerosol-based wind measurements have been made at Goddard Space Flight Center and molecular-based wind measurements at the University of Geneva. We have demonstrated atmospheric measurements using these techniques for altitudes from 1 to more than 10 km. Measurement accuracies of better than 1.25 m/s have been obtained with integration times from 5 to 30 seconds. The measurements can be scaled to space and agree, within a factor of two, with satellite-based simulations of performance based on Poisson statistics. The theory of the double edge aerosol technique is described by a generalized formulation which substantially extends the capabilities of the edge technique. It uses two edges with opposite slopes located about the laser frequency at approximately the half-width of each edge filter. This doubles the signal change for a given Doppler shift and yields a factor of 1.6 improvement in the measurement accuracy compared to the single edge technique. The use of two high resolution edge filters substantially reduces the effects of Rayleigh scattering on the measurement, as much as order of magnitude, and allows the signal to noise ratio to be substantially improved in areas of low aerosol backscatter. We describe a method that allows the Rayleigh and aerosol components of the signal to be independently determined using the two edge channels and an energy monitor channel. The effects of Rayleigh scattering may then subtracted from the measurement and we show that the correction process does not significantly increase the measurement noise for Rayleigh to aerosol ratios up to 10. We show that for small Doppler shifts a measurement accuracy of 0.4 m/s can be obtained for 5000 detected photon, 1.2 m/s for 1000 detected photons, and 3.7 m/s for 50 detected photons for a Rayleigh to aerosol ratio of 5. Methods for increasing the dynamic range of the aerosol-based system to more than +/- 100 m/s are given.

The application of compressive sampling in rapid ultrasonic computerized tomography (UCT) technique of steel tube slab (STS).

PubMed

Jiang, Baofeng; Jia, Pengjiao; Zhao, Wen; Wang, Wentao

2018-01-01

This paper explores a new method for rapid structural damage inspection of steel tube slab (STS) structures along randomly measured paths based on a combination of compressive sampling (CS) and ultrasonic computerized tomography (UCT). In the measurement stage, using fewer randomly selected paths rather than the whole measurement net is proposed to detect the underlying damage of a concrete-filled steel tube. In the imaging stage, the ℓ1-minimization algorithm is employed to recover the information of the microstructures based on the measurement data related to the internal situation of the STS structure. A numerical concrete tube model, with the various level of damage, was studied to demonstrate the performance of the rapid UCT technique. Real-world concrete-filled steel tubes in the Shenyang Metro stations were detected using the proposed UCT technique in a CS framework. Both the numerical and experimental results show the rapid UCT technique has the capability of damage detection in an STS structure with a high level of accuracy and with fewer required measurements, which is more convenient and efficient than the traditional UCT technique.

Biosensing Using Magnetic Particle Detection Techniques

PubMed Central

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

2017-01-01

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

Development and testing of incident detection algorithms. Vol. 2, research methodology and detailed results.

DOT National Transportation Integrated Search

1976-04-01

The development and testing of incident detection algorithms was based on Los Angeles and Minneapolis freeway surveillance data. Algorithms considered were based on times series and pattern recognition techniques. Attention was given to the effects o...

Resonant fiber optic gyro based on a sinusoidal wave modulation and square wave demodulation technique.

PubMed

Wang, Linglan; Yan, Yuchao; Ma, Huilian; Jin, Zhonghe

2016-04-20

New developments are made in the resonant fiber optic gyro (RFOG), which is an optical sensor for the measurement of rotation rate. The digital signal processing system based on the phase modulation technique is capable of detecting the weak frequency difference induced by the Sagnac effect and suppressing the reciprocal noise in the circuit, which determines the detection sensitivity of the RFOG. A new technique based on the sinusoidal wave modulation and square wave demodulation is implemented, and the demodulation curve of the system is simulated and measured. Compared with the past technique using sinusoidal modulation and demodulation, it increases the slope of the demodulation curve by a factor of 1.56, improves the spectrum efficiency of the modulated signal, and reduces the occupancy of the field-programmable gate array resource. On the basis of this new phase modulation technique, the loop is successfully locked and achieves a short-term bias stability of 1.08°/h, which is improved by a factor of 1.47.

Novel concept of washing for microfluidic paper-based analytical devices based on capillary force of paper substrates.

PubMed

Mohammadi, Saeed; Busa, Lori Shayne Alamo; Maeki, Masatoshi; Mohamadi, Reza M; Ishida, Akihiko; Tani, Hirofumi; Tokeshi, Manabu

2016-11-01

A novel washing technique for microfluidic paper-based analytical devices (μPADs) that is based on the spontaneous capillary action of paper and eliminates unbound antigen and antibody in a sandwich immunoassay is reported. Liquids can flow through a porous medium (such as paper) in the absence of external pressure as a result of capillary action. Uniform results were achieved when washing a paper substrate in a PDMS holder which was integrated with a cartridge absorber acting as a porous medium. Our study demonstrated that applying this washing technique would allow μPADs to become the least expensive microfluidic device platform with high reproducibility and sensitivity. In a model μPAD assay that utilized this novel washing technique, C-reactive protein (CRP) was detected with a limit of detection (LOD) of 5 μg mL -1 . Graphical Abstract A novel washing technique for microfluidic paper-based analytical devices (μPADs) that is based on the spontaneous capillary action of paper and eliminates unbound antigen and antibody in a sandwich immunoassay is reported.

Keypoint Density-Based Region Proposal for Fine-Grained Object Detection and Classification Using Regions with Convolutional Neural Network Features

DTIC Science & Technology

2015-12-15

Keypoint Density-based Region Proposal for Fine-Grained Object Detection and Classification using Regions with Convolutional Neural Network ... Convolutional Neural Networks (CNNs) enable them to outperform conventional techniques on standard object detection and classification tasks, their...detection accuracy and speed on the fine-grained Caltech UCSD bird dataset (Wah et al., 2011). Recently, Convolutional Neural Networks (CNNs), a deep

Estimating propagation velocity through a surface acoustic wave sensor

DOEpatents

Xu, Wenyuan; Huizinga, John S.

2010-03-16

Techniques are described for estimating the propagation velocity through a surface acoustic wave sensor. In particular, techniques which measure and exploit a proper segment of phase frequency response of the surface acoustic wave sensor are described for use as a basis of bacterial detection by the sensor. As described, use of velocity estimation based on a proper segment of phase frequency response has advantages over conventional techniques that use phase shift as the basis for detection.

Signal Detection and Monitoring Based on Longitudinal Healthcare Data

PubMed Central

Suling, Marc; Pigeot, Iris

2012-01-01

Post-marketing detection and surveillance of potential safety hazards are crucial tasks in pharmacovigilance. To uncover such safety risks, a wide set of techniques has been developed for spontaneous reporting data and, more recently, for longitudinal data. This paper gives a broad overview of the signal detection process and introduces some types of data sources typically used. The most commonly applied signal detection algorithms are presented, covering simple frequentistic methods like the proportional reporting rate or the reporting odds ratio, more advanced Bayesian techniques for spontaneous and longitudinal data, e.g., the Bayesian Confidence Propagation Neural Network or the Multi-item Gamma-Poisson Shrinker and methods developed for longitudinal data only, like the IC temporal pattern detection. Additionally, the problem of adjustment for underlying confounding is discussed and the most common strategies to automatically identify false-positive signals are addressed. A drug monitoring technique based on Wald’s sequential probability ratio test is presented. For each method, a real-life application is given, and a wide set of literature for further reading is referenced. PMID:24300373

Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

PubMed

Hussain, Lal; Ahmed, Adeel; Saeed, Sharjil; Rathore, Saima; Awan, Imtiaz Ahmed; Shah, Saeed Arif; Majid, Abdul; Idris, Adnan; Awan, Anees Ahmed

2018-02-06

Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and multiresolution of MRIs from prostate cancer require a proper diagnostic systems and tools. In the past researchers developed Computer aided diagnosis (CAD) systems that help the radiologist to detect the abnormalities. In this research paper, we have employed novel Machine learning techniques such as Bayesian approach, Support vector machine (SVM) kernels: polynomial, radial base function (RBF) and Gaussian and Decision Tree for detecting prostate cancer. Moreover, different features extracting strategies are proposed to improve the detection performance. The features extracting strategies are based on texture, morphological, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) features. The performance was evaluated based on single as well as combination of features using Machine Learning Classification techniques. The Cross validation (Jack-knife k-fold) was performed and performance was evaluated in term of receiver operating curve (ROC) and specificity, sensitivity, Positive predictive value (PPV), negative predictive value (NPV), false positive rate (FPR). Based on single features extracting strategies, SVM Gaussian Kernel gives the highest accuracy of 98.34% with AUC of 0.999. While, using combination of features extracting strategies, SVM Gaussian kernel with texture + morphological, and EFDs + morphological features give the highest accuracy of 99.71% and AUC of 1.00.

Contributed review: quantum cascade laser based photoacoustic detection of explosives.

PubMed

Li, J S; Yu, B; Fischer, H; Chen, W; Yalin, A P

2015-03-01

Detecting trace explosives and explosive-related compounds has recently become a topic of utmost importance for increasing public security around the world. A wide variety of detection methods and an even wider range of physical chemistry issues are involved in this very challenging area. Optical sensing methods, in particular mid-infrared spectrometry techniques, have a great potential to become a more desirable tools for the detection of explosives. The small size, simplicity, high output power, long-term reliability make external cavity quantum cascade lasers (EC-QCLs) the promising spectroscopic sources for developing analytical instrumentation. This work reviews the current technical progress in EC-QCL-based photoacoustic spectroscopy for explosives detection. The potential for both close-contact and standoff configurations using this technique is completely presented over the course of approximately the last one decade.

Contributed Review: Quantum cascade laser based photoacoustic detection of explosives

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

Li, J. S., E-mail: jingsong-li@ahu.edu.cn; Yu, B.; Fischer, H.

2015-03-15

Detecting trace explosives and explosive-related compounds has recently become a topic of utmost importance for increasing public security around the world. A wide variety of detection methods and an even wider range of physical chemistry issues are involved in this very challenging area. Optical sensing methods, in particular mid-infrared spectrometry techniques, have a great potential to become a more desirable tools for the detection of explosives. The small size, simplicity, high output power, long-term reliability make external cavity quantum cascade lasers (EC-QCLs) the promising spectroscopic sources for developing analytical instrumentation. This work reviews the current technical progress in EC-QCL-based photoacousticmore » spectroscopy for explosives detection. The potential for both close-contact and standoff configurations using this technique is completely presented over the course of approximately the last one decade.« less

Evaluation of a new serological technique for detecting rabies virus antibodies following vaccination.

PubMed

Ma, Xiaoyue; Niezgoda, Michael; Blanton, Jesse D; Recuenco, Sergio; Rupprecht, Charles E

2012-08-03

Two major techniques are currently used to estimate rabies virus antibody values: neutralization assays, such as the rapid fluorescent focus inhibition test (RFFIT), and enzyme-linked immunosorbent assays (ELISAs). The RFFIT is considered the gold standard assay and has been used to assess the titer of rabies virus neutralizing antibodies for more than three decades. In the late 1970s, ELISA began to be used to estimate the level of rabies virus antibody and has recently been used by some laboratories as an alternate screening test for animal sera. Although the ELISA appears simpler, safer and more efficient, the assay is less sensitive in detecting low values of rabies virus neutralizing antibodies than neutralization tests. This study was designed to evaluate a new ELISA-based method for detecting rabies virus binding antibody. This new technique uses electro-chemi-luminescence labels and carbon electrode plates to detect binding events. In this comparative study, the RFFIT and the new ELISA-based technique were used to evaluate the level of rabies virus antibodies in human and animal serum samples. By using a conservative approximation of 0.15 IU/ml as a cutoff point, the new ELISA-based technique demonstrated a sensitivity of 100% and a specificity of 95% for human samples and for experimental animal samples. The sensitivity and specificity for field animal samples was 96% and 95%, respectively. The preliminary results from this study appear promising and demonstrate a higher sensitivity than traditional ELISA methods. Published by Elsevier Ltd.

Visualization of ultrasound induced cavitation bubbles using the synchrotron x-ray Analyzer Based Imaging technique.

PubMed

Izadifar, Zahra; Belev, George; Izadifar, Mohammad; Izadifar, Zohreh; Chapman, Dean

2014-12-07

Observing cavitation bubbles deep within tissue is very difficult. The development of a method for probing cavitation, irrespective of its location in tissues, would improve the efficiency and application of ultrasound in the clinic. A synchrotron x-ray imaging technique, which is capable of detecting cavitation bubbles induced in water by a sonochemistry system, is reported here; this could possibly be extended to the study of therapeutic ultrasound in tissues. The two different x-ray imaging techniques of Analyzer Based Imaging (ABI) and phase contrast imaging (PCI) were examined in order to detect ultrasound induced cavitation bubbles. Cavitation was not observed by PCI, however it was detectable with ABI. Acoustic cavitation was imaged at six different acoustic power levels and six different locations through the acoustic beam in water at a fixed power level. The results indicate the potential utility of this technique for cavitation studies in tissues, but it is time consuming. This may be improved by optimizing the imaging method.

Pterin detection using surface-enhanced Raman spectroscopy incorporating a straightforward silver colloid-based synthesis technique

NASA Astrophysics Data System (ADS)

Smyth, Ciarán A.; Mehigan, Sam; Rakovich, Yury P.; Bell, Steven E. J.; McCabe, Eithne M.

2011-07-01

Optical techniques toward the realization of sensitive and selective biosensing platforms have received considerable attention in recent times. Techniques based on interferometry, surface plasmon resonance, and waveguides have all proved popular, while spectroscopy in particular offers much potential. Raman spectroscopy is an information-rich technique in which the vibrational frequencies reveal much about the structure of a compound, but it is a weak process and offers poor sensitivity. In response to this problem, surface-enhanced Raman scattering (SERS) has received much attention, due to significant increases in sensitivity instigated by bringing the sample into contact with an enhancing substrate. Here we discuss a facile and rapid technique for the detection of pterins using SERS-active colloidal silver suspensions. Pterins are a family of biological compounds that are employed in nature in color pigmentation and as facilitators in metabolic pathways. In this work, small volumes of xanthopterin, isoxanthopterin, and 7,8-dihydrobiopterin have been examined while adsorbed to silver colloids. Limits of detection have been examined for both xanthopterin and isoxanthopterin using a 10-s exposure to a 12 mW 532 nm laser, which, while showing a trade-off between scan time and signal intensity, still provides the opportunity for the investigation of simultaneous detection of both pterins in solution.

Flag-based detection of weak gas signatures in long-wave infrared hyperspectral image sequences

NASA Astrophysics Data System (ADS)

Marrinan, Timothy; Beveridge, J. Ross; Draper, Bruce; Kirby, Michael; Peterson, Chris

2016-05-01

We present a flag manifold based method for detecting chemical plumes in long-wave infrared hyperspectral movies. The method encodes temporal and spatial information related to a hyperspectral pixel into a flag, or nested sequence of linear subspaces. The technique used to create the flags pushes information about the background clutter, ambient conditions, and potential chemical agents into the leading elements of the flags. Exploiting this temporal information allows for a detection algorithm that is sensitive to the presence of weak signals. This method is compared to existing techniques qualitatively on real data and quantitatively on synthetic data to show that the flag-based algorithm consistently performs better on data when the SINRdB is low, and beats the ACE and MF algorithms in probability of detection for low probabilities of false alarm even when the SINRdB is high.

Shot boundary detection and label propagation for spatio-temporal video segmentation

NASA Astrophysics Data System (ADS)

Piramanayagam, Sankaranaryanan; Saber, Eli; Cahill, Nathan D.; Messinger, David

2015-02-01

This paper proposes a two stage algorithm for streaming video segmentation. In the first stage, shot boundaries are detected within a window of frames by comparing dissimilarity between 2-D segmentations of each frame. In the second stage, the 2-D segments are propagated across the window of frames in both spatial and temporal direction. The window is moved across the video to find all shot transitions and obtain spatio-temporal segments simultaneously. As opposed to techniques that operate on entire video, the proposed approach consumes significantly less memory and enables segmentation of lengthy videos. We tested our segmentation based shot detection method on the TRECVID 2007 video dataset and compared it with block-based technique. Cut detection results on the TRECVID 2007 dataset indicate that our algorithm has comparable results to the best of the block-based methods. The streaming video segmentation routine also achieves promising results on a challenging video segmentation benchmark database.

Label-free genotyping of cytochrome P450 2D6*10 using ligation-mediated strand displacement amplification with DNAzyme-based chemiluminescence detection.

PubMed

Wang, Hong-Qi; Wu, Zhan; Zhang, Yan; Tang, Li-Juan; Yu, Ru-Qin; Jiang, Jian-Hui

2012-01-13

Genotyping of cytochrome P450 monooxygenase 2D6*10 (CYP2D6*10) plays an important role in pharmacogenomics, especially in clinical drug therapy of Asian populations. This work reported a novel label-free technique for genotyping of CYP2D6*10 based on ligation-mediated strand displacement amplification (SDA) with DNAzyme-based chemiluminescence detection. Discrimination of single-base mismatch is firstly accomplished using DNA ligase to generate a ligation product. The ligated product then initiates a SDA reaction to produce aptamer sequences against hemin, which can be probed by chemiluminescence detection. The proposed strategy is used for the assay of CYP2D6*10 target and the genomic DNA. The results reveal that the proposed technique displays chemiluminescence responses in linear correlation to the concentrations of DNA target within the range from 1 pM to 1 nM. A detection limit of 0.1 pM and a signal-to-background ratio of 57 are achieved. Besides such high sensitivity, the proposed CYP2D6*10 genotyping strategy also offers superb selectivity, great robustness, low cost and simplified operations due to its label-free, homogeneous, and chemiluminescence-based detection format. These advantages suggest this technique may hold considerable potential for clinical CYP2D6*10 genotyping and association studies. Copyright © 2011 Elsevier B.V. All rights reserved.

Eco-friendly plasmonic sensors: using the photothermal effect to prepare metal nanoparticle-containing test papers for highly sensitive colorimetric detection.

PubMed

Tseng, Shao-Chin; Yu, Chen-Chieh; Wan, Dehui; Chen, Hsuen-Li; Wang, Lon Alex; Wu, Ming-Chung; Su, Wei-Fang; Han, Hsieh-Cheng; Chen, Li-Chyong

2012-06-05

Convenient, rapid, and accurate detection of chemical and biomolecules would be a great benefit to medical, pharmaceutical, and environmental sciences. Many chemical and biosensors based on metal nanoparticles (NPs) have been developed. However, as a result of the inconvenience and complexity of most of the current preparation techniques, surface plasmon-based test papers are not as common as, for example, litmus paper, which finds daily use. In this paper, we propose a convenient and practical technique, based on the photothermal effect, to fabricate the plasmonic test paper. This technique is superior to other reported methods for its rapid fabrication time (a few seconds), large-area throughput, selectivity in the positioning of the NPs, and the capability of preparing NP arrays in high density on various paper substrates. In addition to their low cost, portability, flexibility, and biodegradability, plasmonic test paper can be burned after detecting contagious biomolecules, making them safe and eco-friendly.

An Enzyme-Free Signal Amplification Technique for Ultrasensitive Colorimetric Assay of Disease Biomarkers

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

Ye, Haihang; Yang, Kuikun; Tao, Jing

Enzyme-based colorimetric assays have been widely used in research labs and clinical diagnosis for decades. Nevertheless, as constrained by the performance of enzymes, their detection sensitivity has not been substantially improved in recent years, which inhibits many critical applications such as early detection of cancers. In this work, we demonstrate an enzyme-free signal amplification technique, based on gold vesicles encapsulated with Pd-Ir nanoparticles as peroxidase mimics, for colorimetric assay of disease biomarkers with significantly enhanced sensitivity. This technique overcomes the intrinsic limitations of enzymes, thanks to the superior catalytic efficiency of peroxidase mimics and the efficient loading and release ofmore » these mimics. Using human prostate surface antigen as a model biomarker, we demonstrated that the enzyme-free assay could reach a limit of detection at the femtogram/mL level, which is over 10 3-fold lower than that of conventional enzyme-based assay when the same antibodies and similar procedure were used.« less

An Enzyme-Free Signal Amplification Technique for Ultrasensitive Colorimetric Assay of Disease Biomarkers

DOE PAGES

Ye, Haihang; Yang, Kuikun; Tao, Jing; ...

2017-01-30

Enzyme-based colorimetric assays have been widely used in research labs and clinical diagnosis for decades. Nevertheless, as constrained by the performance of enzymes, their detection sensitivity has not been substantially improved in recent years, which inhibits many critical applications such as early detection of cancers. In this work, we demonstrate an enzyme-free signal amplification technique, based on gold vesicles encapsulated with Pd-Ir nanoparticles as peroxidase mimics, for colorimetric assay of disease biomarkers with significantly enhanced sensitivity. This technique overcomes the intrinsic limitations of enzymes, thanks to the superior catalytic efficiency of peroxidase mimics and the efficient loading and release ofmore » these mimics. Using human prostate surface antigen as a model biomarker, we demonstrated that the enzyme-free assay could reach a limit of detection at the femtogram/mL level, which is over 10 3-fold lower than that of conventional enzyme-based assay when the same antibodies and similar procedure were used.« less

Impedance biosensor for the rapid detection of Listeria spp. based on aptamer functionalized Pt-interdigitated microelectrodes array

NASA Astrophysics Data System (ADS)

Sidhu, R.; Rong, Y.; Vanegas, D. C.; Claussen, J.; McLamore, E. S.; Gomes, C.

2016-05-01

Listeria monocytogenes is one of the most common causes of food illness deaths worldwide, with multiple outbreaks in the United States alone. Current methods to detect foodborne pathogens are laborious and can take several hours to days to produce results. Thus, faster techniques are needed to detect bacteria within the same reliability level as traditional techniques. This study reports on a rapid, accurate, and sensitive aptamer biosensor device for Listeria spp. detection based on platinum interdigitated array microelectrodes (Pt-IDEs). Pt-IDEs with different geometric electrode gaps were fabricated by lithographic techniques and characterized by cyclic voltammetric (CV), electrochemical impedance spectroscopy (EIS), and potential amperometry (DCPA) measurements of reversible redox species. Based on these results, 50 μm Pt-IDE was chosen to further functionalize with a Listeria monocytogenes DNA aptamer selective to the cell surface protein internalin A, via metal-thiol self-assembly at the 5' end of the 47-mer's. EIS analysis was used to detect Listeria spp. without the need for label amplification and pre-concentration steps. The optimized aptamer concentration of 800 nM was selected to capture the bacteria through internalin A binding and the aptamer hairpin structure near the 3' end. The aptasensor was capable of detecting a wide range of bacteria concentration from 10 to 106 CFU/mL at lower detection limit of 5.39 +/- 0.21 CFU/mL with sensitivity of 268.1 +/- 25.40 (Ohms/log [CFU/mL]) in 17 min. The aptamer based biosensor offers a portable, rapid and sensitive alternative for food safety applications with one of the lowest detection limits reported to date.

Motion-based video monitoring for early detection of livestock diseases: The case of African swine fever

PubMed Central

Martínez-Avilés, Marta; Ivorra, Benjamin; Martínez-López, Beatriz; Ramos, Ángel Manuel; Sánchez-Vizcaíno, José Manuel

2017-01-01

Early detection of infectious diseases can substantially reduce the health and economic impacts on livestock production. Here we describe a system for monitoring animal activity based on video and data processing techniques, in order to detect slowdown and weakening due to infection with African swine fever (ASF), one of the most significant threats to the pig industry. The system classifies and quantifies motion-based animal behaviour and daily activity in video sequences, allowing automated and non-intrusive surveillance in real-time. The aim of this system is to evaluate significant changes in animals’ motion after being experimentally infected with ASF virus. Indeed, pig mobility declined progressively and fell significantly below pre-infection levels starting at four days after infection at a confidence level of 95%. Furthermore, daily motion decreased in infected animals by approximately 10% before the detection of the disease by clinical signs. These results show the promise of video processing techniques for real-time early detection of livestock infectious diseases. PMID:28877181

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

The methods of formaldehyde emission testing of engine: A review

NASA Astrophysics Data System (ADS)

Zhang, Chunhui; Geng, Peng; Cao, Erming; Wei, Lijiang

2015-12-01

A number of measurements have been provided to detect formaldehyde in the atmosphere, but there are no clear unified standards in engine exhaust. Nowadays, formaldehyde, an unregulated emission from methanol engine, has been attracting increasing attention by researchers. This paper presents the detection techniques for formaldehyde emitted from the engines applied in recent market, introducing the approaches in terms of unregulated emission tests of formaldehyde, which involved gas chromatography, liquid chromatography, chromatography-mass spectrometry, chromatography-spectrum, Fourier infrared spectroscopy and spectrophotometry. The author also introduces the comparison regarding to the advantages of the existing detection techniques based on the principle, to compare with engine exhaust sampling method, the treatment in advance of detection, obtaining approaches accessing to the qualitative and quantitative analysis of chromatograms or spectra. The accuratest result obtained was chromatography though it cannot be used continuously. It also can be utilized to develop high requirements of emissions and other regulations. Fourier infrared spectroscopy has the advantage of continuous detection for a variety of unregulated emissions and can be applied to the bench in variable condition. However, its accuracy is not as good as chromatography. As the conclusion, a detection technique is chosen based on different requirements.

Mesoscale, Radiometrically Referenced, Multi-Temporal Hyperspectral Data for Co2 Leak Detection by Locating Spatial Variation of Biophysically Relevant Parameters

NASA Astrophysics Data System (ADS)

McCann, Cooper Patrick

Low-cost flight-based hyperspectral imaging systems have the potential to provide valuable information for ecosystem and environmental studies as well as aide in land management and land health monitoring. This thesis describes (1) a bootstrap method of producing mesoscale, radiometrically-referenced hyperspectral data using the Landsat surface reflectance (LaSRC) data product as a reference target, (2) biophysically relevant basis functions to model the reflectance spectra, (3) an unsupervised classification technique based on natural histogram splitting of these biophysically relevant parameters, and (4) local and multi-temporal anomaly detection. The bootstrap method extends standard processing techniques to remove uneven illumination conditions between flight passes, allowing the creation of radiometrically self-consistent data. Through selective spectral and spatial resampling, LaSRC data is used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from a flight on 06/02/2016 is compared with concurrently collected ground based reflectance spectra as a means of validation achieving an average error of 2.74%. Fitting reflectance spectra using basis functions, based on biophysically relevant spectral features, allows both noise and data reductions while shifting information from spectral bands to biophysical features. Histogram splitting is used to determine a clustering based on natural splittings of these fit parameters. The Indian Pines reference data enabled comparisons of the efficacy of this technique to established techniques. The splitting technique is shown to be an improvement over the ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. This improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA. Three hyperspectral flights over the Kevin Dome area, covering 1843 ha, acquired 06/21/2014, 06/24/2015 and 06/26/2016 are examined with different methods of anomaly detection. Detection of anomalies within a single data set is examined to determine, on a local scale, areas that are significantly different from the surrounding area. Additionally, the detection and identification of persistent anomalies and non-persistent anomalies was investigated across multiple data sets.

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

PubMed

Meegan, Daniel V

2008-01-01

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

Rear-end vision-based collision detection system for motorcyclists

NASA Astrophysics Data System (ADS)

Muzammel, Muhammad; Yusoff, Mohd Zuki; Meriaudeau, Fabrice

2017-05-01

In many countries, the motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. To increase the safety of motorcyclists and minimize their road fatalities, this paper introduces a vision-based rear-end collision detection system. The binary road detection scheme contributes significantly to reduce the negative false detections and helps to achieve reliable results even though shadows and different lane markers are present on the road. The methodology is based on Harris corner detection and Hough transform. To validate this methodology, two types of dataset are used: (1) self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and (2) online datasets (recorded by placing a camera at the front of a car). This method achieved 95.1% accuracy for the self-recorded dataset and gives reliable results for the rear-end vehicle detections under different road scenarios. This technique also performs better for the online car datasets. The proposed technique's high detection accuracy using a monocular vision camera coupled with its low computational complexity makes it a suitable candidate for a motorbike rear-end collision detection system.

Laser based in-situ and standoff detection of chemical warfare agents and explosives

NASA Astrophysics Data System (ADS)

Patel, C. Kumar N.

2009-09-01

Laser based detection of gaseous, liquid and solid residues and trace amounts has been developed ever since lasers were invented. However, the lack of availability of reasonably high power tunable lasers in the spectral regions where the relevant targets can be interrogated as well as appropriate techniques for high sensitivity, high selectivity detection has hampered the practical exploitation of techniques for the detection of targets important for homeland security and defense applications. Furthermore, emphasis has been on selectivity without particular attention being paid to the impact of interfering species on the quality of detection. Having high sensitivity is necessary but not a sufficient condition. High sensitivity assures a high probability of detection of the target species. However, it is only recently that the sensor community has come to recognize that any measure of probability of detection must be associated with a probability of false alarm, if it is to have any value as a measure of performance. This is especially true when one attempts to compare performance characteristics of different sensors based on different physical principles. In this paper, I will provide a methodology for characterizing the performance of sensors utilizing optical absorption measurement techniques. However, the underlying principles are equally application to all other sensors. While most of the current progress in high sensitivity, high selectivity detection of CWAs, TICs and explosives involve identifying and quantifying the target species in-situ, there is an urgent need for standoff detection of explosives from safe distances. I will describe our results on CO2 and quantum cascade laser (QCL) based photoacoustic sensors for the detection of CWAs, TICs and explosives as well the very new results on stand-off detection of explosives at distances up to 150 meters. The latter results are critically important for assuring safety of military personnel in battlefield environment, especially from improvised explosive devices (IEDs), and of civilian personnel from terrorist attacks in metropolitan areas.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores.

PubMed

Ghosh, Sourav K; Ostanin, Victor P; Johnson, Christian L; Lowe, Christopher R; Seshia, Ashwin A

2011-11-15

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks. Copyright © 2011 Elsevier B.V. All rights reserved.

a Uav Based 3-D Positioning Framework for Detecting Locations of Buried Persons in Collapsed Disaster Area

NASA Astrophysics Data System (ADS)

Moon, H.; Kim, C.; Lee, W.

2016-06-01

Regarding spatial location positioning, indoor location positioning theories based on wireless communication techniques such as Wi-Fi, beacon, UWB and Bluetooth has widely been developing across the world. These techniques are mainly focusing on spatial location detection of customers using fixed wireless APs and unique Tags in the indoor environment. Besides, since existing detection equipment and techniques using ultrasound or sound etc. to detect buried persons and identify survival status for them cause 2nd damages on the collapsed debris for rescuers. In addition, it might take time to check the buried persons. However, the collapsed disaster sites should consider both outdoor and indoor environments because empty spaces under collapsed debris exists. In order to detect buried persons from the empty spaces, we should collect wireless signals with Wi-Fi from their mobile phone. Basically, the Wi-Fi signal measure 2-D location. However, since the buried persons have Z value with burial depth, we also should collect barometer sensor data from their mobile phones in order to measure Z values according to weather conditions. Specially, for quick accessibility to the disaster area, a drone (UAV; Unmanned Arial Vehicle) system, which is equipped with a wireless detection module, was introduced. Using these framework, this study aims to provide the rescuers with effective rescue information by calculating 3-D location for buried persons based on the wireless and barometer sensor fusion.

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.

On the spot damage detection methodology for highway bridges during natural crises : tech transfer summary.

DOT National Transportation Integrated Search

2010-07-01

The objective of this work was to develop a : low-cost portable damage detection tool to : assess and predict damage areas in highway : bridges. : The proposed tool was based on standard : vibration-based damage identification (VBDI) : techniques but...

Light Scattering based detection of food pathogens

USDA-ARS?s Scientific Manuscript database

The current methods for detecting foodborne pathogens are mostly destructive (i.e., samples need to be pretreated), and require time, personnel, and laboratories for analyses. Optical methods including light scattering based techniques have gained a lot of attention recently due to its their rapid a...

Multiple excitation nano-spot generation and confocal detection for far-field microscopy.

PubMed

Mondal, Partha Pratim

2010-03-01

An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.

Multiple excitation nano-spot generation and confocal detection for far-field microscopy

NASA Astrophysics Data System (ADS)

Mondal, Partha Pratim

2010-03-01

An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.

Remote sensing based on hyperspectral data analysis

NASA Astrophysics Data System (ADS)

Sharifahmadian, Ershad

In remote sensing, accurate identification of far objects, especially concealed objects is difficult. In this study, to improve object detection from a distance, the hyperspecral imaging and wideband technology are employed with the emphasis on wideband radar. As the wideband data includes a broad range of frequencies, it can reveal information about both the surface of the object and its content. Two main contributions are made in this study: 1) Developing concept of return loss for target detection: Unlike typical radar detection methods which uses radar cross section to detect an object, it is possible to enhance the process of detection and identification of concealed targets using the wideband radar based on the electromagnetic characteristics --conductivity, permeability, permittivity, and return loss-- of materials. During the identification process, collected wideband data is evaluated with information from wideband signature library which has already been built. In fact, several classes (e.g. metal, wood, etc.) and subclasses (ex. metals with high conductivity) have been defined based on their electromagnetic characteristics. Materials in a scene are then classified based on these classes. As an example, materials with high electrical conductivity can be conveniently detected. In fact, increasing relative conductivity leads to a reduction in the return loss. Therefore, metals with high conductivity (ex. copper) shows stronger radar reflections compared with metals with low conductivity (ex. stainless steel). Thus, it is possible to appropriately discriminate copper from stainless steel. 2) Target recognition techniques: To detect and identify targets, several techniques have been proposed, in particular the Multi-Spectral Wideband Radar Image (MSWRI) which is able to localize and identify concealed targets. The MSWRI is based on the theory of robust capon beamformer. During identification process, information from wideband signature library is utilized. The WB signature library includes such parameters as conductivity, permeability, permittivity, and return loss at different frequencies for possible materials related to a target. In the MSWRI approach, identification procedure is performed by calculating the RLs at different selected frequencies. Based on similarity of the calculated RLs and RL from WB signature library, targets are detected and identified. Based on the simulation and experimental results, it is concluded that the MSWRI technique is a promising approach for standoff target detection.

Breath Analysis Using Laser Spectroscopic Techniques: Breath Biomarkers, Spectral Fingerprints, and Detection Limits

PubMed Central

Wang, Chuji; Sahay, Peeyush

2009-01-01

Breath analysis, a promising new field of medicine and medical instrumentation, potentially offers noninvasive, real-time, and point-of-care (POC) disease diagnostics and metabolic status monitoring. Numerous breath biomarkers have been detected and quantified so far by using the GC-MS technique. Recent advances in laser spectroscopic techniques and laser sources have driven breath analysis to new heights, moving from laboratory research to commercial reality. Laser spectroscopic detection techniques not only have high-sensitivity and high-selectivity, as equivalently offered by the MS-based techniques, but also have the advantageous features of near real-time response, low instrument costs, and POC function. Of the approximately 35 established breath biomarkers, such as acetone, ammonia, carbon dioxide, ethane, methane, and nitric oxide, 14 species in exhaled human breath have been analyzed by high-sensitivity laser spectroscopic techniques, namely, tunable diode laser absorption spectroscopy (TDLAS), cavity ringdown spectroscopy (CRDS), integrated cavity output spectroscopy (ICOS), cavity enhanced absorption spectroscopy (CEAS), cavity leak-out spectroscopy (CALOS), photoacoustic spectroscopy (PAS), quartz-enhanced photoacoustic spectroscopy (QEPAS), and optical frequency comb cavity-enhanced absorption spectroscopy (OFC-CEAS). Spectral fingerprints of the measured biomarkers span from the UV to the mid-IR spectral regions and the detection limits achieved by the laser techniques range from parts per million to parts per billion levels. Sensors using the laser spectroscopic techniques for a few breath biomarkers, e.g., carbon dioxide, nitric oxide, etc. are commercially available. This review presents an update on the latest developments in laser-based breath analysis. PMID:22408503

Detecting and classifying method based on similarity matching of Android malware behavior with profile.

PubMed

Jang, Jae-Wook; Yun, Jaesung; Mohaisen, Aziz; Woo, Jiyoung; Kim, Huy Kang

2016-01-01

Mass-market mobile security threats have increased recently due to the growth of mobile technologies and the popularity of mobile devices. Accordingly, techniques have been introduced for identifying, classifying, and defending against mobile threats utilizing static, dynamic, on-device, and off-device techniques. Static techniques are easy to evade, while dynamic techniques are expensive. On-device techniques are evasion, while off-device techniques need being always online. To address some of those shortcomings, we introduce Andro-profiler, a hybrid behavior based analysis and classification system for mobile malware. Andro-profiler main goals are efficiency, scalability, and accuracy. For that, Andro-profiler classifies malware by exploiting the behavior profiling extracted from the integrated system logs including system calls. Andro-profiler executes a malicious application on an emulator in order to generate the integrated system logs, and creates human-readable behavior profiles by analyzing the integrated system logs. By comparing the behavior profile of malicious application with representative behavior profile for each malware family using a weighted similarity matching technique, Andro-profiler detects and classifies it into malware families. The experiment results demonstrate that Andro-profiler is scalable, performs well in detecting and classifying malware with accuracy greater than 98 %, outperforms the existing state-of-the-art work, and is capable of identifying 0-day mobile malware samples.

Advances in the in-field detection of microorganisms in ice.

PubMed

Barnett, Megan J; Pearce, David A; Cullen, David C

2012-01-01

The historic view of ice-bound ecosystems has been one of a predominantly lifeless environment, where microorganisms certainly exist but are assumed to be either completely inactive or in a state of long-term dormancy. However, this standpoint has been progressively overturned in the past 20years as studies have started to reveal the importance of microbial life in the functioning of these environments. Our present knowledge of the distribution, taxonomy, and metabolic activity of such microbial life has been derived primarily from laboratory-based analyses of collected field samples. To date, only a restricted range of life detection and characterization techniques have been applied in the field. Specific examples include direct observation and DNA-based techniques (microscopy, specific stains, and community profiling based on PCR amplification), the detection of biomarkers (such as adenosine triphosphate), and measurements of metabolism [through the uptake and incorporation of radiolabeled isotopes or chemical alteration of fluorescent substrates (umbelliferones are also useful here)]. On-going improvements in technology mean that smaller and more robust life detection and characterization systems are continually being designed, manufactured, and adapted for in-field use. Adapting technology designed for other applications is the main source of new methodology, and the range of techniques is currently increasing rapidly. Here we review the current use of technology and techniques to detect and characterize microbial life within icy environments and specifically its deployment to in-field situations. We discuss the necessary considerations, limitations, and adaptations, review emerging technologies, and highlight the future potential. Successful application of these new techniques to in-field studies will certainly generate new insights into the way ice bound ecosystems function. Copyright © 2012 Elsevier Inc. All rights reserved.

Nanoplatforms for Detection, Remediation and Protection Against Chem-Bio Warfare

NASA Astrophysics Data System (ADS)

Denkbaş, E. B.; Bayram, C.; Kavaz, D.; Çirak, T.; Demirbilek, M.

Chemical and biological substances have been used as warfare agents by terrorists by varying degree of sophistication. It is critical that these agents be detected in real-time with high level of sensitively, specificity, and accuracy. Many different types of techniques and systems have been developed to detect these agents. But there are some limitations in these conventional techniques and systems. Limitations include the collection, handling and sampling procedures, detection limits, sample transfer, expensive equipment, personnel training, and detection materials. Due to the unique properties such as quantum effect, very high surface/volume ratio, enhanced surface reactivity, conductivity, electrical and magnetic properties of the nanomaterials offer great opportunity to develop very fast, sensitive, accurate and cost effective detection techniques and systems to detect chemical and biological (chem.-bio) warfare agents. Furthermore, surface modification of the materials is very easy and effective way to get functional or smart surfaces to be used as nano-biosensor platform. In that respect many different types of nanomaterials have been developed and used for the detection, remediation and protection, such as gold and silver nanoparticles, quantum dots, Nano chips and arrays, fluorescent polymeric and magnetic nanoparticles, fiber optic and cantilever based nanobiosensors, nanofibrillar nanostructures etc. This study summarizes preparation and characterization of nanotechnology based approaches for the detection of and remediation and protection against chem.-bio warfare agents.

Laser desorption with corona discharge ion mobility spectrometry for direct surface detection of explosives.

PubMed

Sabo, M; Malásková, M; Matejčík, S

2014-10-21

We present a new highly sensitive technique for the detection of explosives directly from the surface using laser desorption-corona discharge-ion mobility spectrometry (LD-CD-IMS). We have developed LD based on laser diode modules (LDM) and the technique was tested using three different LDM (445, 532 and 665 nm). The explosives were detected directly from the surface without any further preparation. We discuss the mechanism of the LD and the limitations of this technique such as desorption time, transport time and desorption area. After the evaluation of experimental data, we estimated the potential limits of detection of this method to be 0.6 pg for TNT, 2.8 pg for RDX and 8.4 pg for PETN.

Contrast-enhanced spectral mammography based on a photon-counting detector: quantitative accuracy and radiation dose

NASA Astrophysics Data System (ADS)

Lee, Seungwan; Kang, Sooncheol; Eom, Jisoo

2017-03-01

Contrast-enhanced mammography has been used to demonstrate functional information about a breast tumor by injecting contrast agents. However, a conventional technique with a single exposure degrades the efficiency of tumor detection due to structure overlapping. Dual-energy techniques with energy-integrating detectors (EIDs) also cause an increase of radiation dose and an inaccuracy of material decomposition due to the limitations of EIDs. On the other hands, spectral mammography with photon-counting detectors (PCDs) is able to resolve the issues induced by the conventional technique and EIDs using their energy-discrimination capabilities. In this study, the contrast-enhanced spectral mammography based on a PCD was implemented by using a polychromatic dual-energy model, and the proposed technique was compared with the dual-energy technique with an EID in terms of quantitative accuracy and radiation dose. The results showed that the proposed technique improved the quantitative accuracy as well as reduced radiation dose comparing to the dual-energy technique with an EID. The quantitative accuracy of the contrast-enhanced spectral mammography based on a PCD was slightly improved as a function of radiation dose. Therefore, the contrast-enhanced spectral mammography based on a PCD is able to provide useful information for detecting breast tumors and improving diagnostic accuracy.

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.

Streak Imaging Flow Cytometer for Rare Cell Analysis.

PubMed

Balsam, Joshua; Bruck, Hugh Alan; Ossandon, Miguel; Prickril, Ben; Rasooly, Avraham

2017-01-01

There is a need for simple and affordable techniques for cytology for clinical applications, especially for point-of-care (POC) medical diagnostics in resource-poor settings. However, this often requires adapting expensive and complex laboratory-based techniques that often require significant power and are too massive to transport easily. One such technique is flow cytometry, which has great potential for modification due to the simplicity of the principle of optical tracking of cells. However, it is limited in that regard due to the flow focusing technique used to isolate cells for optical detection. This technique inherently reduces the flow rate and is therefore unsuitable for rapid detection of rare cells which require large volume for analysis.To address these limitations, we developed a low-cost, mobile flow cytometer based on streak imaging. In our new configuration we utilize a simple webcam for optical detection over a large area associated with a wide-field flow cell. The new flow cell is capable of larger volume and higher throughput fluorescence detection of rare cells than the flow cells with hydrodynamic focusing used in conventional flow cytometry. The webcam is an inexpensive, commercially available system, and for fluorescence analysis we use a 1 W 450 nm blue laser to excite Syto-9 stained cells with emission at 535 nm. We were able to detect low concentrations of stained cells at high flow rates of 10 mL/min, which is suitable for rapidly analyzing larger specimen volumes to detect rare cells at appropriate concentration levels. The new rapid detection capabilities, combined with the simplicity and low cost of this device, suggest a potential for clinical POC flow cytometry in resource-poor settings associated with global health.

Molecular sensing with magnetic nanoparticles using magnetic spectroscopy of nanoparticle Brownian motion.

PubMed

Zhang, Xiaojuan; Reeves, Daniel B; Perreard, Irina M; Kett, Warren C; Griswold, Karl E; Gimi, Barjor; Weaver, John B

2013-12-15

Functionalized magnetic nanoparticles (mNPs) have shown promise in biosensing and other biomedical applications. Here we use functionalized mNPs to develop a highly sensitive, versatile sensing strategy required in practical biological assays and potentially in vivo analysis. We demonstrate a new sensing scheme based on magnetic spectroscopy of nanoparticle Brownian motion (MSB) to quantitatively detect molecular targets. MSB uses the harmonics of oscillating mNPs as a metric for the freedom of rotational motion, thus reflecting the bound state of the mNP. The harmonics can be detected in vivo from nanogram quantities of iron within 5s. Using a streptavidin-biotin binding system, we show that the detection limit of the current MSB technique is lower than 150 pM (0.075 pmole), which is much more sensitive than previously reported techniques based on mNP detection. Using mNPs conjugated with two anti-thrombin DNA aptamers, we show that thrombin can be detected with high sensitivity (4 nM or 2 pmole). A DNA-DNA interaction was also investigated. The results demonstrated that sequence selective DNA detection can be achieved with 100 pM (0.05 pmole) sensitivity. The results of using MSB to sense these interactions, show that the MSB based sensing technique can achieve rapid measurement (within 10s), and is suitable for detecting and quantifying a wide range of biomarkers or analytes. It has the potential to be applied in variety of biomedical applications or diagnostic analyses. © 2013 Elsevier B.V. All rights reserved.

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

PubMed

Ang, Li Minn; Seng, Kah Phooi; Ge, Feng Lu

2017-05-23

This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively.

Determination of multi-walled carbon nanotube bioaccumulation in earthworms measured by a microwave-based detection technique

EPA Science Inventory

Reliable quantification techniques for carbon nanotubes (CNTs) are limited. In this study, a new procedure was developed for quantifying multi-walled carbon nanotubes (MWNTs) in earthworms (Eisenia fetida) based on freeze drying and microwave-induced heating. Specifically, earthw...

A Monte Carlo technique for signal level detection in implanted intracranial pressure monitoring.

PubMed

Avent, R K; Charlton, J D; Nagle, H T; Johnson, R N

1987-01-01

Statistical monitoring techniques like CUSUM, Trigg's tracking signal and EMP filtering have a major advantage over more recent techniques, such as Kalman filtering, because of their inherent simplicity. In many biomedical applications, such as electronic implantable devices, these simpler techniques have greater utility because of the reduced requirements on power, logic complexity and sampling speed. The determination of signal means using some of the earlier techniques are reviewed in this paper, and a new Monte Carlo based method with greater capability to sparsely sample a waveform and obtain an accurate mean value is presented. This technique may find widespread use as a trend detection method when reduced power consumption is a requirement.

Studies of MRI relaxivities of gadolinium-labeled dendrons

NASA Astrophysics Data System (ADS)

Pan, Hongmu; Daniel, Marie-Christine

2011-05-01

In cancer detection, imaging techniques have a great importance in early diagnosis. The more sensitive the imaging technique and the earlier the tumor can be detected. Contrast agents have the capability to increase the sensitivity in imaging techniques such as magnetic resonance imaging (MRI). Until now, gadolinium-based contrast agents are mainly used for MRI, and show good enhancement. But improvement is needed for detection of smaller tumors at the earliest stage possible. The dendrons complexed with Gd(DOTA) were synthesized and evaluated as a new MRI contrast agent. The longitudinal and transverse relaxation effects were tested and compared with commercial drug Magnevist, Gd(DTPA).

DETECTION OF PATHOGENS IN DRINKING WATER (SEER 2)

EPA Science Inventory

Project investigators developed a polymerase chain reaction (PCR)-based technique to detect E. coli 0157:H7 cells in environmental samples using previously reported PCR primers for the specific detection of genes involved in biosynthesis of 0157 polysacchari...

The Population of Small Comets: Optimum Techniques for Detection

NASA Technical Reports Server (NTRS)

Brandt, John C.

1997-01-01

The goals of this project were: (1) to present evidence to the scientific community for the importance of the small comet population and (2) to develop techniques for optimum detection in order to characterize the population. Our work on techniques has been to develop algorithms for searching images for SCs based on the distinctive properties of comets; (1) motion with respect to background stars; (2) extended source with most light coming from the coma rather than the nucleus; and characteristic spectral signature.

Statistical techniques for the characterization of partially observed epidemics.

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

Safta, Cosmin; Ray, Jaideep; Crary, David

Techniques appear promising to construct and integrate automated detect-and-characterize technique for epidemics - Working off biosurveillance data, and provides information on the particular/ongoing outbreak. Potential use - in crisis management and planning, resource allocation - Parameter estimation capability ideal for providing the input parameters into an agent-based model, Index Cases, Time of Infection, infection rate. Non-communicable diseases are easier than communicable ones - Small anthrax can be characterized well with 7-10 days of data, post-detection; plague takes longer, Large attacks are very easy.

On Modeling of Adversary Behavior and Defense for Survivability of Military MANET Applications

DTIC Science & Technology

2015-01-01

anomaly detection technique. b) A system-level majority-voting based intrusion detection system with m being the number of verifiers used to perform...pp. 1254 - 1263. [5] R. Mitchell, and I.R. Chen, “Adaptive Intrusion Detection for Unmanned Aircraft Systems based on Behavior Rule Specification...and adaptively trigger the best attack strategies while avoiding detection and eviction. The second step is to model defense behavior of defenders

Confabulation Based Real-time Anomaly Detection for Wide-area Surveillance Using Heterogeneous High Performance Computing Architecture

DTIC Science & Technology

2015-06-01

system accuracy. The AnRAD system was also generalized for the additional application of network intrusion detection . A self-structuring technique...to Host- based Intrusion Detection Systems using Contiguous and Discontiguous System Call Patterns,” IEEE Transactions on Computer, 63(4), pp. 807...square kilometer areas. The anomaly recognition and detection (AnRAD) system was built as a cogent confabulation network . It represented road

Small threat and contraband detection with TNA-based systems.

PubMed

Shaw, T J; Brown, D; D'Arcy, J; Liu, F; Shea, P; Sivakumar, M; Gozani, T

2005-01-01

The detection of small threats, such as explosives, drugs, and chemical weapons, concealed or encased in surrounding material, is a major concern in areas from security checkpoints to UneXploded Ordnance (UXO) clearance. Techniques such as X-ray and trace detection are often ineffectual in these applications. Thermal neutron analysis (TNA) provides an effective method for detecting concealed threats. This paper shows the effectiveness of Ancore's SPEDS, based on TNA, in detecting concealed liquid threats and differentiating live from inert mortar shells.

A Real-Time Earthquake Precursor Detection Technique Using TEC from a GPS Network

NASA Astrophysics Data System (ADS)

Alp Akyol, Ali; Arikan, Feza; Arikan, Orhan

2016-07-01

Anomalies have been observed in the ionospheric electron density distribution prior to strong earthquakes. However, most of the reported results are obtained by earthquake analysis. Therefore, their implementation in practice is highly problematic. Recently, a novel earthquake precursor detection technique based on spatio-temporal analysis of Total Electron Content (TEC) data obtained from Turkish National Permanent GPS Network (TNPGN) is developed by IONOLAB group (www.ionolab.org). In the present study, the developed detection technique is implemented in a causal setup over the available data set in test phase that enables the real time implementation. The performance of the developed earthquake prediction technique is evaluated by using 10 fold cross validation over the data obtained in 2011. Among the 23 earthquakes that have magnitudes higher than 5, the developed technique can detect precursors of 14 earthquakes while producing 8 false alarms. This study is supported by TUBITAK 115E915 and Joint TUBITAK 114E092 and AS CR 14/001 projects.

On effectiveness of network sensor-based defense framework

NASA Astrophysics Data System (ADS)

Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

2012-06-01

Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

Current status and prospects of nuclear physics research based on tracking techniques

NASA Astrophysics Data System (ADS)

Alekseev, V. A.; Alexandrov, A. B.; Bagulya, A. V.; Chernyavskiy, M. M.; Goncharova, L. A.; Gorbunov, S. A.; Kalinina, G. V.; Konovalova, N. S.; Okatyeva, N. M.; Pavlova, T. A.; Polukhina, N. G.; Shchedrina, T. V.; Starkov, N. I.; Tioukov, V. E.; Vladymirov, M. S.; Volkov, A. E.

2017-01-01

Results of nuclear physics research made using track detectors are briefly reviewed. Advantages and prospects of the track detection technique in particle physics, neutrino physics, astrophysics and other fields are discussed on the example of the results of the search for direct origination of tau neutrino in a muon neutrino beam within the framework of the international experiment OPERA (Oscillation Project with Emulsion-tRacking Apparatus) and works on search for superheavy nuclei in nature on base of their tracks in meteoritic olivine crystals. The spectra of superheavy elements in galactic cosmic rays are presented. Prospects of using the track detection technique in fundamental and applied research are reported.

A lightweight network anomaly detection technique

DOE PAGES

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

2017-03-13

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

A lightweight network anomaly detection technique

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

Kim, Jinoh; Yoo, Wucherl; Sim, Alex

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

Updating Landsat-derived land-cover maps using change detection and masking techniques

NASA Technical Reports Server (NTRS)

Likens, W.; Maw, K.

1982-01-01

The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

Biosensors and their applications in detection of organophosphorus pesticides in the environment.

PubMed

Hassani, Shokoufeh; Momtaz, Saeideh; Vakhshiteh, Faezeh; Maghsoudi, Armin Salek; Ganjali, Mohammad Reza; Norouzi, Parviz; Abdollahi, Mohammad

2017-01-01

This review discusses the past and recent advancements of biosensors focusing on detection of organophosphorus pesticides (OPs) due to their exceptional use during the last decades. Apart from agricultural benefits, OPs also impose adverse toxicological effects on animal and human population. Conventional approaches such as chromatographic techniques used for pesticide detection are associated with several limitations. A biosensor technology is unique due to the detection sensitivity, selectivity, remarkable performance capabilities, simplicity and on-site operation, fabrication and incorporation with nanomaterials. This study also provided specifications of the most OPs biosensors reported until today based on their transducer system. In addition, we highlighted the application of advanced complementary materials and analysis techniques in OPs detection systems. The availability of these new materials associated with new sensing techniques has led to introduction of easy-to-use analytical tools of high sensitivity and specificity in the design and construction of OPs biosensors. In this review, we elaborated the achievements in sensing systems concerning innovative nanomaterials and analytical techniques with emphasis on OPs.

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

NASA Astrophysics Data System (ADS)

Pal, S. K.; Majumdar, T. J.; Bhattacharya, Amit K.

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.

Discrimination of the glucose and the white sugar based on the pulsed laser-induced photoacoustic technique

NASA Astrophysics Data System (ADS)

Ren, Zhong; Liu, Guodong

2017-08-01

In this study, to discriminate the glucose and the white sugar gradient in the food, a noninvasive optical detection system based on pulsed laser-induced photoacoustic technique was developed. Meanwhile, the Nd: YAG 532nm pumped OPO pulsed laser was used as the excitation light source to generate of the photoacoustic signals of the glucose and white sugar. The focused ultrasonic transducer with central detection frequency of 1MHz was used to capture the photoacoustic signals. In experiments, the real-time photoacoustic signals of the glucose and the white sugar aqueous solutions were gotten and compared with each other. In addition, to discriminate the difference of the characteristic photoacoustic signals between both of them, the difference spectrum and the first order derivative technique between the peak-to-peak photoacoustic signals of the water and that of the glucose and white sugar were employed. The difference characteristic photoacoustic wavelengths between the glucose and the white sugar were found based on the established photoacoustic detection system. This study provides the potential possibility for the discrimination of the glucose and the white sugar by using the photoacoustic detection method.

Counterflow Dielectrophoresis for Trypanosome Enrichment and Detection in Blood

NASA Astrophysics Data System (ADS)

Menachery, Anoop; Kremer, Clemens; Wong, Pui E.; Carlsson, Allan; Neale, Steven L.; Barrett, Michael P.; Cooper, Jonathan M.

2012-10-01

Human African trypanosomiasis or sleeping sickness is a deadly disease endemic in sub-Saharan Africa, caused by single-celled protozoan parasites. Although it has been targeted for elimination by 2020, this will only be realized if diagnosis can be improved to enable identification and treatment of afflicted patients. Existing techniques of detection are restricted by their limited field-applicability, sensitivity and capacity for automation. Microfluidic-based technologies offer the potential for highly sensitive automated devices that could achieve detection at the lowest levels of parasitemia and consequently help in the elimination programme. In this work we implement an electrokinetic technique for the separation of trypanosomes from both mouse and human blood. This technique utilises differences in polarisability between the blood cells and trypanosomes to achieve separation through opposed bi-directional movement (cell counterflow). We combine this enrichment technique with an automated image analysis detection algorithm, negating the need for a human operator.

Computerized mass detection in whole breast ultrasound images: reduction of false positives using bilateral subtraction technique

NASA Astrophysics Data System (ADS)

Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako

2007-03-01

The comparison of left and right mammograms is a common technique used by radiologists for the detection and diagnosis of masses. In mammography, computer-aided detection (CAD) schemes using bilateral subtraction technique have been reported. However, in breast ultrasonography, there are no reports on CAD schemes using comparison of left and right breasts. In this study, we propose a scheme of false positive reduction based on bilateral subtraction technique in whole breast ultrasound images. Mass candidate regions are detected by using the information of edge directions. Bilateral breast images are registered with reference to the nipple positions and skin lines. A false positive region is detected based on a comparison of the average gray values of a mass candidate region and a region with the same position and same size as the candidate region in the contralateral breast. In evaluating the effectiveness of the false positive reduction method, three normal and three abnormal bilateral pairs of whole breast images were employed. These abnormal breasts included six masses larger than 5 mm in diameter. The sensitivity was 83% (5/6) with 13.8 (165/12) false positives per breast before applying the proposed reduction method. By applying the method, false positives were reduced to 4.5 (54/12) per breast without removing a true positive region. This preliminary study indicates that the bilateral subtraction technique is effective for improving the performance of a CAD scheme in whole breast ultrasound images.

Rope-based oral fluid sampling for early detection of classical swine fever in domestic pigs at group level.

PubMed

Dietze, Klaas; Tucakov, Anna; Engel, Tatjana; Wirtz, Sabine; Depner, Klaus; Globig, Anja; Kammerer, Robert; Mouchantat, Susan

2017-01-05

Non-invasive sampling techniques based on the analysis of oral fluid specimen have gained substantial importance in the field of swine herd management. Methodological advances have a focus on endemic viral diseases in commercial pig production. More recently, these approaches have been adapted to non-invasive sampling of wild boar for transboundary animal disease detection for which these effective population level sampling methods have not been available. In this study, a rope-in-a-bait based oral fluid sampling technique was tested to detect classical swine fever virus nucleic acid shedding from experimentally infected domestic pigs. Separated in two groups treated identically, the course of the infection was slightly differing in terms of onset of the clinical signs and levels of viral ribonucleic acid detection in the blood and oral fluid. The technique was capable of detecting classical swine fever virus nucleic acid as of day 7 post infection coinciding with the first detection in conventional oropharyngeal swab samples from some individual animals. Except for day 7 post infection in the "slower onset group", the chances of classical swine fever virus nucleic acid detection in ropes were identical or higher as compared to the individual sampling. With the provided evidence, non-invasive oral fluid sampling at group level can be considered as additional cost-effective detection tool in classical swine fever prevention and control strategies. The proposed methodology is of particular use in production systems with reduced access to veterinary services such as backyard or scavenging pig production where it can be integrated in feeding or baiting practices.

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.

Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

In many Asian countries, motorcyclists have a higher fatality rate as compared to other vehicles. Among many other factors, rear end collisions are also contributing for these fatalities. Collision detection systems can be useful to minimize these accidents. However, the designing of efficient and cost effective collision detection system for motorcyclist is still a major challenge. In this paper, an acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications. The proposed technique uses the Short time Fourier Transform (STFT) to extract the features from the audio signal and Principal component analysis (PCA) has been used to reduce the feature vector length. The reduction of feature length, further increases the performance of this technique. The proposed technique has been tested on self recorded dataset and gives accuracy of 97.87%. We believe that this method can help to reduce a significant number of motorcycle accidents.

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Raman scattering spectroscopy for explosives identification

NASA Astrophysics Data System (ADS)

Nagli, L.; Gaft, M.

2007-04-01

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 technique, 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. We applied gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. Raman system was developed and tested by LDS for field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Detection of swine-origin influenza A (H1N1) viruses using a paired surface plasma waves biosensor

NASA Astrophysics Data System (ADS)

Su, Li-Chen; Chang, Ying-Feng; Li, Ying-Chang; Hsieh, Jo-Ping; Lee, Cheng-Chung; Chou, Chien

2010-08-01

In order to enhance the sensitivity of conventional rapid test technique for the detection of swine-origin influenza A (H1N1) viruses (S-OIVs), we used a paired surface plasma waves biosensor (PSPWB) based on SPR in conjunction with an optical heterodyne technique. Experimentally, PSPWB showed a 125-fold improvement at least in the S-OIV detection as compared to conventional enzyme linked immunosorbent assay. Moreover, the detection limit of the PSPWB for the S-OIV detection was enhanced 250-fold in buffer at least in comparison with that of conventional rapid influenza diagnostic test.

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1980-01-01

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

Damage of composite structures: Detection technique, dynamic response and residual strength

NASA Astrophysics Data System (ADS)

Lestari, Wahyu

2001-10-01

Reliable and accurate health monitoring techniques can prevent catastrophic failures of structures. Conventional damage detection methods are based on visual or localized experimental methods and very often require prior information concerning the vicinity of the damage or defect. The structure must also be readily accessible for inspections. The techniques are also labor intensive. In comparison to these methods, health-monitoring techniques that are based on the structural dynamic response offers unique information on failure of structures. However, systematic relations between the experimental data and the defect are not available and frequently, the number of vibration modes needed for an accurate identification of defects is much higher than the number of modes that can be readily identified in the experiment. These motivated us to develop an experimental data based detection method with systematic relationships between the experimentally identified information and the analytical or mathematical model representing the defective structures. The developed technique use changes in vibrational curvature modes and natural frequencies. To avoid misinterpretation of the identified information, we also need to understand the effects of defects on the structural dynamic response prior to developing health-monitoring techniques. In this thesis work we focus on two type of defects in composite structures, namely delamination and edge notch like defect. Effects of nonlinearity due to the presence of defect and due to the axial stretching are studied for beams with delamination. Once defects are detected in a structure, next concern is determining the effects of the defects on the strength of the structure and its residual stiffness under dynamic loading. In this thesis, energy release rate due to dynamic loading in a delaminated structure is studied, which will be a foundation toward determining the residual strength of the structure.

Functional requirements for an intelligent RPC. [remote power controller for spaceborne electrical distribution system

NASA Technical Reports Server (NTRS)

Aucoin, B. M.; Heller, R. P.

1990-01-01

An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

Depth-Based Detection of Standing-Pigs in Moving Noise Environments.

PubMed

Kim, Jinseong; Chung, Yeonwoo; Choi, Younchang; Sa, Jaewon; Kim, Heegon; Chung, Yongwha; Park, Daihee; Kim, Hakjae

2017-11-29

In a surveillance camera environment, the detection of standing-pigs in real-time is an important issue towards the final goal of 24-h tracking of individual pigs. In this study, we focus on depth-based detection of standing-pigs with "moving noises", which appear every night in a commercial pig farm, but have not been reported yet. We first apply a spatiotemporal interpolation technique to remove the moving noises occurring in the depth images. Then, we detect the standing-pigs by utilizing the undefined depth values around them. Our experimental results show that this method is effective for detecting standing-pigs at night, in terms of both cost-effectiveness (using a low-cost Kinect depth sensor) and accuracy (i.e., 94.47%), even with severe moving noises occluding up to half of an input depth image. Furthermore, without any time-consuming technique, the proposed method can be executed in real-time.

Hidden explosives detector employing pulsed neutron and x-ray interrogation

DOEpatents

Schultz, F.J.; Caldwell, J.T.

1993-04-06

Methods and systems for the detection of small amounts of modern, highly-explosive nitrogen-based explosives, such as plastic explosives, hidden in airline baggage. Several techniques are employed either individually or combined in a hybrid system. One technique employed in combination is X-ray imaging. Another technique is interrogation with a pulsed neutron source in a two-phase mode of operation to image both nitrogen and oxygen densities. Another technique employed in combination is neutron interrogation to form a hydrogen density image or three-dimensional map. In addition, deliberately-placed neutron-absorbing materials can be detected.

Hidden explosives detector employing pulsed neutron and x-ray interrogation

DOEpatents

Schultz, Frederick J.; Caldwell, John T.

1993-01-01

Methods and systems for the detection of small amounts of modern, highly-explosive nitrogen-based explosives, such as plastic explosives, hidden in airline baggage. Several techniques are employed either individually or combined in a hybrid system. One technique employed in combination is X-ray imaging. Another technique is interrogation with a pulsed neutron source in a two-phase mode of operation to image both nitrogen and oxygen densities. Another technique employed in combination is neutron interrogation to form a hydrogen density image or three-dimensional map. In addition, deliberately-placed neutron-absorbing materials can be detected.

Ultrasonic Array for Obstacle Detection Based on CDMA with Kasami Codes

PubMed Central

Diego, Cristina; Hernández, Álvaro; Jiménez, Ana; Álvarez, Fernando J.; Sanz, Rebeca; Aparicio, Joaquín

2011-01-01

This paper raises the design of an ultrasonic array for obstacle detection based on Phased Array (PA) techniques, which steers the acoustic beam through the environment by electronics rather than mechanical means. The transmission of every element in the array has been encoded, according to Code Division for Multiple Access (CDMA), which allows multiple beams to be transmitted simultaneously. All these features together enable a parallel scanning system which does not only improve the image rate but also achieves longer inspection distances in comparison with conventional PA techniques. PMID:22247675

Review of neutron-based technologies for the inspection of cargo containers

NASA Astrophysics Data System (ADS)

Khan, Siraj M.

1994-10-01

Three techniques (API, PFNA and PFTNA) are described and compared in this brief review of neutron based technologies for the detection of contraband in cargo containers. It appears that the role that these techniques can play in the detection of contraband in Customs, airline security and physical security applications remains to be demonstrated. However, their utilization in the fields of non-proliferation, arms control and disarmament, radwaste remediation and pollution control seems more straight forward since the issues of thruput and radiation safety are not so critical.

Vision based techniques for rotorcraft low altitude flight

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Suorsa, Ray; Smith, Philip

1991-01-01

An overview of research in obstacle detection at NASA Ames Research Center is presented. The research applies techniques from computer vision to automation of rotorcraft navigation. The development of a methodology for detecting the range to obstacles based on the maximum utilization of passive sensors is emphasized. The development of a flight and image data base for verification of vision-based algorithms, and a passive ranging methodology tailored to the needs of helicopter flight are discussed. Preliminary results indicate that it is possible to obtain adequate range estimates except at regions close to the FOE. Closer to the FOE, the error in range increases since the magnitude of the disparity gets smaller, resulting in a low SNR.

Development of a noninvasive technique for the measurement of intracranial pressure

NASA Technical Reports Server (NTRS)

Ueno, T.; Shuer, L. M.; Yost, W. T.; Hargens, A. R.

1998-01-01

Intracranial pressure (ICP) dynamics are important for understanding adjustments to altered gravity. Previous flight observations document significant facial edema during exposure to microgravity, which suggests that ICP is elevated during microgravity. However, there are no experimental results obtained during space flight, primarily due to the invasiveness of currently available techniques. We have developed and refined a noninvasive technique to measure intracranial pressure noninvasively. The technique is based upon detecting skull movements of a few micrometers in association with altered intracranial pressure. We reported that the PPLL technique has enough sensitivity to detect changes in cranial distance associated with the pulsation of ICP in cadavera. In normal operations, however, we place a transducer on the scalp. Thus, we cannot rule out the possibility that the PPLL technique picks up cutaneous pulsation. The purpose of the present study was therefore to show that the PPLL technique has enough sensitivity to detect changes in cranial distance associated with cardiac cycles in vivo.

Plant Ethylene Detection Using Laser-Based Photo-Acoustic Spectroscopy.

PubMed

Van de Poel, Bram; Van Der Straeten, Dominique

2017-01-01

Analytical detection of the plant hormone ethylene is an important prerequisite in physiological studies. Real-time and super sensitive detection of trace amounts of ethylene gas is possible using laser-based photo-acoustic spectroscopy. This Chapter will provide some background on the technique, compare it with conventional gas chromatography, and provide a detailed user-friendly hand-out on how to operate the machine and the software. In addition, this Chapter provides some tips and tricks for designing and performing physiological experiments suited for ethylene detection with laser-based photo-acoustic spectroscopy.

Radiation and Electromagnetic Induction Data Fusion for Detection of Buried Radioactive Metal Waste - 12282

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

Long, Zhiling; Wei, Wei; Turlapaty, Anish

2012-07-01

At the United States Army's test sites, fired penetrators made of Depleted Uranium (DU) have been buried under ground and become hazardous waste. Previously, we developed techniques for detecting buried radioactive targets. We also developed approaches for locating buried paramagnetic metal objects by utilizing the electromagnetic induction (EMI) sensor data. In this paper, we apply data fusion techniques to combine results from both the radiation detection and the EMI detection, so that we can further distinguish among DU penetrators, DU oxide, and non- DU metal debris. We develop a two-step fusion approach for the task, and test it with surveymore » data collected on simulation targets. In this work, we explored radiation and EMI data fusion for detecting DU, oxides, and non-DU metals. We developed a two-step fusion approach based on majority voting and a set of decision rules. With this approach, we fuse results from radiation detection based on the RX algorithm and EMI detection based on a 3-step analysis. Our fusion approach has been tested successfully with data collected on simulation targets. In the future, we will need to further verify the effectiveness of this fusion approach with field data. (authors)« less

Molecular Methods for the Detection of Mycoplasma and Ureaplasma Infections in Humans

PubMed Central

Waites, Ken B.; Xiao, Li; Paralanov, Vanya; Viscardi, Rose M.; Glass, John I.

2012-01-01

Mycoplasma and Ureaplasma species are well-known human pathogens responsible for a broad array of inflammatory conditions involving the respiratory and urogenital tracts of neonates, children, and adults. Greater attention is being given to these organisms in diagnostic microbiology, largely as a result of improved methods for their laboratory detection, made possible by powerful molecular-based techniques that can be used for primary detection in clinical specimens. For slow-growing species, such as Mycoplasma pneumoniae and Mycoplasma genitalium, molecular-based detection is the only practical means for rapid microbiological diagnosis. Most molecular-based methods used for detection and characterization of conventional bacteria have been applied to these organisms. A complete genome sequence is available for one or more strains of all of the important human pathogens in the Mycoplasma and Ureaplasma genera. Information gained from genome analyses and improvements in efficiency of DNA sequencing are expected to significantly advance the field of molecular detection and genotyping during the next few years. This review provides a summary and critical review of methods suitable for detection and characterization of mycoplasmas and ureaplasmas of humans, with emphasis on molecular genotypic techniques. PMID:22819362

Biosensor for detection of dissolved chromium in potable water: A review.

PubMed

Biswas, Puja; Karn, Abhinav Kumar; Balasubramanian, P; Kale, Paresh G

2017-08-15

The unprecedented deterioration rate of the environmental quality due to rapid urbanization and industrialization causes a severe global health concern to both ecosystem and humanity. Heavy metals are ubiquitous in nature and being used extensively in industrial processes, the exposure to excessive levels could alter the biochemical cycles of living systems. Hence the environmental monitoring through rapid and specific detection of heavy metal contamination in potable water is of paramount importance. Various standard analytical techniques and sensors are used for the detection of heavy metals include spectroscopy and chromatographic methods along with electrochemical, optical waveguide and polymer based sensors. However, the mentioned techniques lack the point of care application as it demands huge capital cost as well as the attention of expert personnel for sample preparation and operation. Recent advancements in the synergetic interaction among biotechnology and microelectronics have advocated the biosensor technology for a wide array of applications due to its characteristic features of sensitivity and selectivity. This review paper has outlined the overview of chromium toxicity, conventional analytical techniques along with a particular emphasis on electrochemical based biosensors for chromium detection in potable water. This article emphasized porous silicon as a host material for enzyme immobilization and elaborated the working principle, mechanism, kinetics of an enzyme-based biosensor for chromium detection. The significant characteristics such as pore size, thickness, and porosity make the porous silicon suitable for enzyme entrapment. Further, several schemes on porous silicon-based immobilized enzyme biosensors for the detection of chromium in potable water are proposed. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling And Detecting Anomalies In Scada Systems

NASA Astrophysics Data System (ADS)

Svendsen, Nils; Wolthusen, Stephen

The detection of attacks and intrusions based on anomalies is hampered by the limits of specificity underlying the detection techniques. However, in the case of many critical infrastructure systems, domain-specific knowledge and models can impose constraints that potentially reduce error rates. At the same time, attackers can use their knowledge of system behavior to mask their manipulations, causing adverse effects to observed only after a significant period of time. This paper describes elementary statistical techniques that can be applied to detect anomalies in critical infrastructure networks. A SCADA system employed in liquefied natural gas (LNG) production is used as a case study.

Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

PubMed

Mirzaei, Golrokh; Adeli, Anahita; Adeli, Hojjat

2016-12-01

Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection techniques have been defined to be the key to an accurate diagnosis. This paper presents a state-of-the-art review of the research performed on the diagnosis of AD based on imaging and machine learning techniques. Different segmentation and machine learning techniques used for the diagnosis of AD are reviewed including thresholding, supervised and unsupervised learning, probabilistic techniques, Atlas-based approaches, and fusion of different image modalities. More recent and powerful classification techniques such as the enhanced probabilistic neural network of Ahmadlou and Adeli should be investigated with the goal of improving the diagnosis accuracy. A combination of different image modalities can help improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal biomarkers.

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.

Heterogeneity and frequency of BRAF mutations in primary melanoma: Comparison between molecular methods and immunohistochemistry

PubMed Central

Bruno, William; Martinuzzi, Claudia; Andreotti, Virginia; Pastorino, Lorenza; Spagnolo, Francesco; Dalmasso, Bruna; Cabiddu, Francesco; Gualco, Marina; Ballestrero, Alberto; Bianchi-Scarrà, Giovanna; Queirolo, Paola

2017-01-01

Finding the best technique to identify BRAF mutations with a high sensitivity and specificity is mandatory for accurate patient selection for target therapy. BRAF mutation frequency ranges from 40 to 60% depending on melanoma clinical characteristics and detection technique used. Intertumoral heterogeneity could lead to misinterpretation of BRAF mutational status; this is especially important if testing is performed on primary specimens, when metastatic lesions are unavailable. Aim of this study was to identify the best combination of methods for detecting BRAF mutations (among peptide nucleic acid – PNA-clamping real-time PCR, immunohistochemistry and capillary sequencing) and investigate BRAF mutation heterogeneity in a series of 100 primary melanomas and a subset of 25 matched metastatic samples. Overall, we obtained a BRAF mutation frequency of 62%, based on the combination of at least two techniques. Concordance between mutation status in primary and metastatic tumor was good but not complete (67%), when agreement of at least two techniques were considered. Next generation sequencing was used to quantify the threshold of detected mutant alleles in discordant samples. Combining different methods excludes that the observed heterogeneity is technique-based. We propose an algorithm for BRAF mutation testing based on agreement between immunohistochemistry and PNA; a third molecular method could be added in case of discordance of the results. Testing the primary tumor when the metastatic sample is unavailable is a good option if at least two methods of detection are used, however the presence of intertumoral heterogeneity or the occurrence of additional primaries should be carefully considered. PMID:28039443

[Development of the automatic dental X-ray film processor].

PubMed

Bai, J; Chen, H

1999-07-01

This paper introduces a multiple-point detecting technique of the density of dental X-ray films. With the infrared ray multiple-point detecting technique, a single-chip microcomputer control system is used to analyze the effectiveness of the film-developing in real time in order to achieve a good image. Based on the new technology, We designed the intelligent automatic dental X-ray film processing.

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.

Imaging free radicals in organelles, cells, tissue, and in vivo with immuno-spin trapping.

PubMed

Mason, Ronald Paul

2016-08-01

The accurate and sensitive detection of biological free radicals in a reliable manner is required to define the mechanistic roles of such species in biochemistry, medicine and toxicology. Most of the techniques currently available are either not appropriate to detect free radicals in cells and tissues due to sensitivity limitations (electron spin resonance, ESR) or subject to artifacts that make the validity of the results questionable (fluorescent probe-based analysis). The development of the immuno-spin trapping technique overcomes all these difficulties. This technique is based on the reaction of amino acid- and DNA base-derived radicals with the spin trap 5, 5-dimethyl-1-pyrroline N-oxide (DMPO) to form protein- and DNA-DMPO nitroxide radical adducts, respectively. These adducts have limited stability and decay to produce the very stable macromolecule-DMPO-nitrone product. This stable product can be detected by mass spectrometry, NMR or immunochemistry by the use of anti-DMPO nitrone antibodies. The formation of macromolecule-DMPO-nitrone adducts is based on the selective reaction of free radical addition to the spin trap and is thus not subject to artifacts frequently encountered with other methods for free radical detection. The selectivity of spin trapping for free radicals in biological systems has been proven by ESR. Immuno-spin trapping is proving to be a potent, sensitive (a million times higher sensitivity than ESR), and easy (not quantum mechanical) method to detect low levels of macromolecule-derived radicals produced in vitro and in vivo. Anti-DMPO antibodies have been used to determine the distribution of free radicals in cells and tissues and even in living animals. In summary, the invention of the immuno-spin trapping technique has had a major impact on the ability to accurately and sensitively detect biological free radicals and, subsequently, on our understanding of the role of free radicals in biochemistry, medicine and toxicology. Published by Elsevier B.V.

The application of compressive sampling in rapid ultrasonic computerized tomography (UCT) technique of steel tube slab (STS)

PubMed Central

Jiang, Baofeng; Jia, Pengjiao; Zhao, Wen; Wang, Wentao

2018-01-01

This paper explores a new method for rapid structural damage inspection of steel tube slab (STS) structures along randomly measured paths based on a combination of compressive sampling (CS) and ultrasonic computerized tomography (UCT). In the measurement stage, using fewer randomly selected paths rather than the whole measurement net is proposed to detect the underlying damage of a concrete-filled steel tube. In the imaging stage, the ℓ1-minimization algorithm is employed to recover the information of the microstructures based on the measurement data related to the internal situation of the STS structure. A numerical concrete tube model, with the various level of damage, was studied to demonstrate the performance of the rapid UCT technique. Real-world concrete-filled steel tubes in the Shenyang Metro stations were detected using the proposed UCT technique in a CS framework. Both the numerical and experimental results show the rapid UCT technique has the capability of damage detection in an STS structure with a high level of accuracy and with fewer required measurements, which is more convenient and efficient than the traditional UCT technique. PMID:29293593

Sensor failure detection system. [for the F100 turbofan engine

NASA Technical Reports Server (NTRS)

Beattie, E. C.; Laprad, R. F.; Mcglone, M. E.; Rock, S. M.; Akhter, M. M.

1981-01-01

Advanced concepts for detecting, isolating, and accommodating sensor failures were studied to determine their applicability to the gas turbine control problem. Five concepts were formulated based upon such techniques as Kalman filters and a screening process led to the selection of one advanced concept for further evaluation. The selected advanced concept uses a Kalman filter to generate residuals, a weighted sum square residuals technique to detect soft failures, likelihood ratio testing of a bank of Kalman filters for isolation, and reconfiguring of the normal mode Kalman filter by eliminating the failed input to accommodate the failure. The advanced concept was compared to a baseline parameter synthesis technique. The advanced concept was shown to be a viable concept for detecting, isolating, and accommodating sensor failures for the gas turbine applications.

Magnetic Imaging: a New Tool for UK National Nuclear Security

NASA Astrophysics Data System (ADS)

Darrer, Brendan J.; Watson, Joe C.; Bartlett, Paul; Renzoni, Ferruccio

2015-01-01

Combating illicit trafficking of Special Nuclear Material may require the ability to image through electromagnetic shields. This is the case when the trafficking involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. The present study considers techniques that employ an electromagnetic based principle of detection. It is generally assumed that a ferromagnetic metallic enclosure will effectively act as a Faraday cage to electromagnetic radiation and therefore screen any form of interrogating electromagnetic radiation from penetrating, thus denying the detection of any eventual hidden material. In contrast, we demonstrate that it is actually possible to capture magnetic images of a conductive object through a set of metallic ferromagnetic enclosures. This validates electromagnetic interrogation techniques as a potential detection tool for National Nuclear Security applications.

Magnetic Imaging: a New Tool for UK National Nuclear Security

PubMed Central

Darrer, Brendan J.; Watson, Joe C.; Bartlett, Paul; Renzoni, Ferruccio

2015-01-01

Combating illicit trafficking of Special Nuclear Material may require the ability to image through electromagnetic shields. This is the case when the trafficking involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. The present study considers techniques that employ an electromagnetic based principle of detection. It is generally assumed that a ferromagnetic metallic enclosure will effectively act as a Faraday cage to electromagnetic radiation and therefore screen any form of interrogating electromagnetic radiation from penetrating, thus denying the detection of any eventual hidden material. In contrast, we demonstrate that it is actually possible to capture magnetic images of a conductive object through a set of metallic ferromagnetic enclosures. This validates electromagnetic interrogation techniques as a potential detection tool for National Nuclear Security applications. PMID:25608957

Magnetic imaging: a new tool for UK national nuclear security.

PubMed

Darrer, Brendan J; Watson, Joe C; Bartlett, Paul; Renzoni, Ferruccio

2015-01-22

Combating illicit trafficking of Special Nuclear Material may require the ability to image through electromagnetic shields. This is the case when the trafficking involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. The present study considers techniques that employ an electromagnetic based principle of detection. It is generally assumed that a ferromagnetic metallic enclosure will effectively act as a Faraday cage to electromagnetic radiation and therefore screen any form of interrogating electromagnetic radiation from penetrating, thus denying the detection of any eventual hidden material. In contrast, we demonstrate that it is actually possible to capture magnetic images of a conductive object through a set of metallic ferromagnetic enclosures. This validates electromagnetic interrogation techniques as a potential detection tool for National Nuclear Security applications.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

NASA Astrophysics Data System (ADS)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

Laser ultrasonic techniques for assessment of tooth structure

NASA Astrophysics Data System (ADS)

Blodgett, David W.; Baldwin, Kevin C.

2000-06-01

Dental health care and research workers require a means of imaging the structures within teeth in vivo. For example, there is a need to image the margins of a restoration for the detection of poor bonding or voids between the restorative material and the dentin. With conventional x-ray techniques, it is difficult to detect cracks and to visualize interfaces between hard media. This due to the x-ray providing only a 2 dimensional projection of the internal structure (i.e. a silhouette). In addition, a high resolution imaging modality is needed to detect tooth decay in its early stages. If decay can be detected early enough, the process can be monitored and interventional procedures, such as fluoride washes and controlled diet, can be initiated which can help the tooth to re-mineralize itself. Currently employed x-ray imaging is incapable of detecting decay at a stage early enough to avoid invasive cavity preparation followed by a restoration with a synthetic material. Other clinical applications include the visualization of periodontal defects, the localization of intraosseous lesions, and determining the degree of osseointegration between a dental implant and the surrounding bone. A means of assessing the internal structure of the tooth based upon use of high frequency, highly localized ultrasound (acoustic waves) generated by a laser pulse is discussed. Optical interferometric detection of ultrasound provides a complementary technique with a very small detection footprint. Initial results using laser-based ultrasound for assessment of dental structures are presented. Discussion will center on the adaptability of this technique to clinical applications.

Single molecule transistor based nanopore for the detection of nicotine

NASA Astrophysics Data System (ADS)

Ray, S. J.

2014-12-01

A nanopore based detection methodology was proposed and investigated for the detection of Nicotine. This technique uses a Single Molecular Transistor working as a nanopore operational in the Coulomb Blockade regime. When the Nicotine molecule is pulled through the nanopore area surrounded by the Source(S), Drain (D), and Gate electrodes, the charge stability diagram can detect the presence of the molecule and is unique for a specific molecular structure. Due to the weak coupling between the different electrodes which is set by the nanopore size, the molecular energy states stay almost unaffected by the electrostatic environment that can be realised from the charge stability diagram. Identification of different orientation and position of the Nicotine molecule within the nanopore area can be made from specific regions of overlap between different charge states on the stability diagram that could be used as an electronic fingerprint for detection. This method could be advantageous and useful to detect the presence of Nicotine in smoke which is usually performed using chemical chromatography techniques.

The Detection Method of Escherichia coli in Water Resources: A Review

NASA Astrophysics Data System (ADS)

Nurliyana, M. R.; Sahdan, M. Z.; Wibowo, K. M.; Muslihati, A.; Saim, H.; Ahmad, S. A.; Sari, Y.; Mansor, Z.

2018-04-01

This article reviews several approaches for Escherichia coli (E. coli) bacteria detection from conventional methods, emerging method and goes to biosensor-based techniques. Detection and enumeration of E. coli bacteria usually required long duration of time in obtaining the result since laboratory-based approach is normally used in its assessment. It requires 24 hours to 72 hours after sampling to process the culturing samples before results are available. Although faster technique for detecting E. coli in water such as Polymerase Chain Reaction (PCR) and Enzyme-Linked Immunosorbent Assay (ELISA) have been developed, it still required transporting the samples from water resources to the laboratory, high-cost, complicated equipment usage, complex procedures, as well as the requirement of skilled specialist to cope with the complexity which limit their wide spread practice in water quality detection. Recently, development of biosensor device that is easy to perform, portable, highly sensitive and selective becomes indispensable in detecting extremely lower consolidation of pathogenic E. coli bacteria in water samples.

Nonlinear ultrasonic fatigue crack detection using a single piezoelectric transducer

NASA Astrophysics Data System (ADS)

An, Yun-Kyu; Lee, Dong Jun

2016-04-01

This paper proposes a new nonlinear ultrasonic technique for fatigue crack detection using a single piezoelectric transducer (PZT). The proposed technique identifies a fatigue crack using linear (α) and nonlinear (β) parameters obtained from only a single PZT mounted on a target structure. Based on the different physical characteristics of α and β, a fatigue crack-induced feature is able to be effectively isolated from the inherent nonlinearity of a target structure and data acquisition system. The proposed technique requires much simpler test setup and less processing costs than the existing nonlinear ultrasonic techniques, but fast and powerful. To validate the proposed technique, a real fatigue crack is created in an aluminum plate, and then false positive and negative tests are carried out under varying temperature conditions. The experimental results reveal that the fatigue crack is successfully detected, and no positive false alarm is indicated.

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

Optimal electrode selection for multi-channel electroencephalogram based detection of auditory steady-state responses.

PubMed

Van Dun, Bram; Wouters, Jan; Moonen, Marc

2009-07-01

Auditory steady-state responses (ASSRs) are used for hearing threshold estimation at audiometric frequencies. Hearing impaired newborns, in particular, benefit from this technique as it allows for a more precise diagnosis than traditional techniques, and a hearing aid can be better fitted at an early age. However, measurement duration of current single-channel techniques is still too long for clinical widespread use. This paper evaluates the practical performance of a multi-channel electroencephalogram (EEG) processing strategy based on a detection theory approach. A minimum electrode set is determined for ASSRs with frequencies between 80 and 110 Hz using eight-channel EEG measurements of ten normal-hearing adults. This set provides a near-optimal hearing threshold estimate for all subjects and improves response detection significantly for EEG data with numerous artifacts. Multi-channel processing does not significantly improve response detection for EEG data with few artifacts. In this case, best response detection is obtained when noise-weighted averaging is applied on single-channel data. The same test setup (eight channels, ten normal-hearing subjects) is also used to determine a minimum electrode setup for 10-Hz ASSRs. This configuration allows to record near-optimal signal-to-noise ratios for 80% of subjects.

X-ray Scatter Imaging of Hepatocellular Carcinoma in a Mouse Model Using Nanoparticle Contrast Agents

NASA Astrophysics Data System (ADS)

Rand, Danielle; Derdak, Zoltan; Carlson, Rolf; Wands, Jack R.; Rose-Petruck, Christoph

2015-10-01

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and is almost uniformly fatal. Current methods of detection include ultrasound examination and imaging by CT scan or MRI; however, these techniques are problematic in terms of sensitivity and specificity, and the detection of early tumors (<1 cm diameter) has proven elusive. Better, more specific, and more sensitive detection methods are therefore urgently needed. Here we discuss the application of a newly developed x-ray imaging technique called Spatial Frequency Heterodyne Imaging (SFHI) for the early detection of HCC. SFHI uses x-rays scattered by an object to form an image and is more sensitive than conventional absorption-based x-radiography. We show that tissues labeled in vivo with gold nanoparticle contrast agents can be detected using SFHI. We also demonstrate that directed targeting and SFHI of HCC tumors in a mouse model is possible through the use of HCC-specific antibodies. The enhanced sensitivity of SFHI relative to currently available techniques enables the x-ray imaging of tumors that are just a few millimeters in diameter and substantially reduces the amount of nanoparticle contrast agent required for intravenous injection relative to absorption-based x-ray imaging.

ECG-based gating in ultra high field cardiovascular magnetic resonance using an independent component analysis approach.

PubMed

Krug, Johannes W; Rose, Georg; Clifford, Gari D; Oster, Julien

2013-11-19

In Cardiovascular Magnetic Resonance (CMR), the synchronization of image acquisition with heart motion is performed in clinical practice by processing the electrocardiogram (ECG). The ECG-based synchronization is well established for MR scanners with magnetic fields up to 3 T. However, this technique is prone to errors in ultra high field environments, e.g. in 7 T MR scanners as used in research applications. The high magnetic fields cause severe magnetohydrodynamic (MHD) effects which disturb the ECG signal. Image synchronization is thus less reliable and yields artefacts in CMR images. A strategy based on Independent Component Analysis (ICA) was pursued in this work to enhance the ECG contribution and attenuate the MHD effect. ICA was applied to 12-lead ECG signals recorded inside a 7 T MR scanner. An automatic source identification procedure was proposed to identify an independent component (IC) dominated by the ECG signal. The identified IC was then used for detecting the R-peaks. The presented ICA-based method was compared to other R-peak detection methods using 1) the raw ECG signal, 2) the raw vectorcardiogram (VCG), 3) the state-of-the-art gating technique based on the VCG, 4) an updated version of the VCG-based approach and 5) the ICA of the VCG. ECG signals from eight volunteers were recorded inside the MR scanner. Recordings with an overall length of 87 min accounting for 5457 QRS complexes were available for the analysis. The records were divided into a training and a test dataset. In terms of R-peak detection within the test dataset, the proposed ICA-based algorithm achieved a detection performance with an average sensitivity (Se) of 99.2%, a positive predictive value (+P) of 99.1%, with an average trigger delay and jitter of 5.8 ms and 5.0 ms, respectively. Long term stability of the demixing matrix was shown based on two measurements of the same subject, each being separated by one year, whereas an averaged detection performance of Se = 99.4% and +P = 99.7% was achieved.Compared to the state-of-the-art VCG-based gating technique at 7 T, the proposed method increased the sensitivity and positive predictive value within the test dataset by 27.1% and 42.7%, respectively. The presented ICA-based method allows the estimation and identification of an IC dominated by the ECG signal. R-peak detection based on this IC outperforms the state-of-the-art VCG-based technique in a 7 T MR scanner environment.

Monitoring of pipelines in nuclear power plants by measuring laser-based mechanical impedance

NASA Astrophysics Data System (ADS)

Lee, Hyeonseok; Sohn, Hoon; Yang, Suyoung; Yang, Jinyeol

2014-06-01

Using laser-based mechanical impedance (LMI) measurement, this study proposes a damage detection technique that enables structural health monitoring of pipelines under the high temperature and radioactive environments of nuclear power plants (NPPs). The applications of conventional electromechanical impedance (EMI) based techniques to NPPs have been limited, mainly due to the contact nature of piezoelectric transducers, which cannot survive under the high temperature and high radiation environments of NPPs. The proposed LMI measurement technique aims to tackle the limitations of the EMI techniques by utilizing noncontact laser beams for both ultrasound generation and sensing. An Nd:Yag pulse laser is used for ultrasound generation, and a laser Doppler vibrometer is employed for the measurement of the corresponding ultrasound responses. For the monitoring of pipes covered by insulation layers, this study utilizes optical fibers to guide the laser beams to specific target locations. Then, an outlier analysis is adopted for autonomous damage diagnosis. Validation of the proposed LMI technique is carried out on a carbon steel pipe elbow under varying temperatures. A corrosion defect chemically engraved in the specimen is successfully detected.

Pulsed quantum cascade laser-based cavity ring-down spectroscopy for ammonia detection in breath.

PubMed

Manne, Jagadeeshwari; Sukhorukov, Oleksandr; Jäger, Wolfgang; Tulip, John

2006-12-20

Breath analysis can be a valuable, noninvasive tool for the clinical diagnosis of a number of pathological conditions. The detection of ammonia in exhaled breath is of particular interest for it has been linked to kidney malfunction and peptic ulcers. Pulsed cavity ringdown spectroscopy in the mid-IR region has developed into a sensitive analytical technique for trace gas analysis. A gas analyzer based on a pulsed mid-IR quantum cascade laser operating near 970 cm(-1) has been developed for the detection of ammonia levels in breath. We report a sensitivity of approximately 50 parts per billion with a 20 s time resolution for ammonia detection in breath with this system. The challenges and possible solutions for the quantification of ammonia in human breath by the described technique are discussed.

Electrochemical impedimetric sensor based on molecularly imprinted polymers/sol-gel chemistry for methidathion organophosphorous insecticide recognition.

PubMed

Bakas, Idriss; Hayat, Akhtar; Piletsky, Sergey; Piletska, Elena; Chehimi, Mohamed M; Noguer, Thierry; Rouillon, Régis

2014-12-01

We report here a novel method to detect methidathion organophosphorous insecticides. The sensing platform was architected by the combination of molecularly imprinted polymers and sol-gel technique on inexpensive, portable and disposable screen printed carbon electrodes. Electrochemical impedimetric detection technique was employed to perform the label free detection of the target analyte on the designed MIP/sol-gel integrated platform. The selection of the target specific monomer by electrochemical impedimetric methods was consistent with the results obtained by the computational modelling method. The prepared electrochemical MIP/sol-gel based sensor exhibited a high recognition capability toward methidathion, as well as a broad linear range and a low detection limit under the optimized conditions. Satisfactory results were also obtained for the methidathion determination in waste water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Change-based threat detection in urban environments with a forward-looking camera

NASA Astrophysics Data System (ADS)

Morton, Kenneth, Jr.; Ratto, Christopher; Malof, Jordan; Gunter, Michael; Collins, Leslie; Torrione, Peter

2012-06-01

Roadside explosive threats continue to pose a significant risk to soldiers and civilians in conflict areas around the world. These objects are easy to manufacture and procure, but due to their ad hoc nature, they are difficult to reliably detect using standard sensing technologies. Although large roadside explosive hazards may be difficult to conceal in rural environments, urban settings provide a much more complicated background where seemingly innocuous objects (e.g., piles of trash, roadside debris) may be used to obscure threats. Since direct detection of all innocuous objects would flag too many objects to be of use, techniques must be employed to reduce the number of alarms generated and highlight only a limited subset of possibly threatening regions for the user. In this work, change detection techniques are used to reduce false alarm rates and increase detection capabilities for possible threat identification in urban environments. The proposed model leverages data from multiple video streams collected over the same regions by first applying video aligning and then using various distance metrics to detect changes based on image keypoints in the video streams. Data collected at an urban warfare simulation range at an Eastern US test site was used to evaluate the proposed approach, and significant reductions in false alarm rates compared to simpler techniques are illustrated.

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

PubMed

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

2015-05-01

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

Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

NASA Astrophysics Data System (ADS)

Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

2016-03-01

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

Multivariate image analysis of laser-induced photothermal imaging used for detection of caries tooth

NASA Astrophysics Data System (ADS)

El-Sherif, Ashraf F.; Abdel Aziz, Wessam M.; El-Sharkawy, Yasser H.

2010-08-01

Time-resolved photothermal imaging has been investigated to characterize tooth for the purpose of discriminating between normal and caries areas of the hard tissue using thermal camera. Ultrasonic thermoelastic waves were generated in hard tissue by the absorption of fiber-coupled Q-switched Nd:YAG laser pulses operating at 1064 nm in conjunction with a laser-induced photothermal technique used to detect the thermal radiation waves for diagnosis of human tooth. The concepts behind the use of photo-thermal techniques for off-line detection of caries tooth features were presented by our group in earlier work. This paper illustrates the application of multivariate image analysis (MIA) techniques to detect the presence of caries tooth. MIA is used to rapidly detect the presence and quantity of common caries tooth features as they scanned by the high resolution color (RGB) thermal cameras. Multivariate principal component analysis is used to decompose the acquired three-channel tooth images into a two dimensional principal components (PC) space. Masking score point clusters in the score space and highlighting corresponding pixels in the image space of the two dominant PCs enables isolation of caries defect pixels based on contrast and color information. The technique provides a qualitative result that can be used for early stage caries tooth detection. The proposed technique can potentially be used on-line or real-time resolved to prescreen the existence of caries through vision based systems like real-time thermal camera. Experimental results on the large number of extracted teeth as well as one of the thermal image panoramas of the human teeth voltanteer are investigated and presented.

Early Oscillation Detection for Hybrid DC/DC Converter Fault Diagnosis

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2011-01-01

This paper describes a novel fault detection technique for hybrid DC/DC converter oscillation diagnosis. The technique is based on principles of feedback control loop oscillation and RF signal modulations, and Is realized by using signal spectral analysis. Real-circuit simulation and analytical study reveal critical factors of the oscillation and indicate significant correlations between the spectral analysis method and the gain/phase margin method. A stability diagnosis index (SDI) is developed as a quantitative measure to accurately assign a degree of stability to the DC/DC converter. This technique Is capable of detecting oscillation at an early stage without interfering with DC/DC converter's normal operation and without limitations of probing to the converter.

Visualization of delamination in composite materials utilizing advanced X-ray imaging techniques

NASA Astrophysics Data System (ADS)

Vavrik, D.; Jakubek, J.; Jandejsek, I.; Krejci, F.; Kumpova, I.; Zemlicka, J.

2015-04-01

This work is focused on the development of instrumental radiographic methods for detection of delaminations in layered carbon fibre reinforced plastic composites used in the aerospace industry. The main limitation of current visualisation techniques is a very limited possibility to image so-called closed delaminations in which delaminated layers are in contact practically with no physical gap. In this contribution we report the development of innovative methods for closed delamination detection using an X-ray phase contrast technique for which the distance between delamination surfaces is not relevant. The approach is based on the energetic sensitivity of phase-enhanced radiography. Based on the applied methodology, we can distinguish both closed and open delamination. Further we have demonstrated the possibility to visualise open delaminations characterised by a physical gap between delaminated layers. This delamination type was successfully identified and visualized utilizing a high resolution and computed tomography table-top technique based on proper beam-hardening effect correction.

Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation.

PubMed

Iliya, Sunday; Neri, Ferrante

2016-09-01

This paper presents a neural system-based technique for segmenting short impaired speech utterances into silent, unvoiced, and voiced sections. Moreover, the proposed technique identifies those points of the (voiced) speech where the spectrum becomes steady. The resulting technique thus aims at detecting that limited section of the speech which contains the information about the potential impairment of the speech. This section is of interest to the speech therapist as it corresponds to the possibly incorrect movements of speech organs (lower lip and tongue with respect to the vocal tract). Two segmentation models to detect and identify the various sections of the disordered (impaired) speech signals have been developed and compared. The first makes use of a combination of four artificial neural networks. The second is based on a support vector machine (SVM). The SVM has been trained by means of an ad hoc nested algorithm whose outer layer is a metaheuristic while the inner layer is a convex optimization algorithm. Several metaheuristics have been tested and compared leading to the conclusion that some variants of the compact differential evolution (CDE) algorithm appears to be well-suited to address this problem. Numerical results show that the SVM model with a radial basis function is capable of effective detection of the portion of speech that is of interest to a therapist. The best performance has been achieved when the system is trained by the nested algorithm whose outer layer is hybrid-population-based/CDE. A population-based approach displays the best performance for the isolation of silence/noise sections, and the detection of unvoiced sections. On the other hand, a compact approach appears to be clearly well-suited to detect the beginning of the steady state of the voiced signal. Both the proposed segmentation models display outperformed two modern segmentation techniques based on Gaussian mixture model and deep learning.

Measurement of gadolinium retention: current status and review from an applied radiation physics perspective.

PubMed

Gräfe, James L; McNeill, Fiona E

2018-06-28

This article briefly reviews the main measurement techniques for the non-invasive detection of residual gadolinium (Gd) in those exposed to gadolinium-based contrast agents (GBCAs). Approach and Main results: The current status of in vivo Gd measurement is discussed and is put into the context of concerns within the radiology community. The main techniques are based on applied atomic/nuclear medicine utilizing the characteristic atomic and nuclear spectroscopic signature of Gd. The main emission energies are in the 40-200 keV region and require spectroscopic detectors with good energy resolution. The two main techniques, prompt gamma neutron activation analysis and x-ray fluorescence, provide adequate detection limits for in vivo measurement, whilst delivering a low effective radiation dose on the order of a few µSv. Gadolinium is being detected in measureable quantities in people with healthy renal function who have received FDA approved GBCAs. The applied atomic/nuclear medicine techniques discussed in this review will be useful in determining the significance of this retention, and will help on advising future administration protocols.

Reconstructing the Sky Location of Gravitational-Wave Detected Compact Binary Systems: Methodology for Testing and Comparison

NASA Technical Reports Server (NTRS)

Sidney, T.; Aylott, B.; Christensen, N.; Farr, B.; Farr, W.; Feroz, F.; Gair, J.; Grover, K.; Graff, P.; Hanna, C.;

Reconstructing the sky location of gravitational-wave detected compact binary systems: Methodology for testing and comparison

NASA Astrophysics Data System (ADS)

Sidery, T.; Aylott, B.; Christensen, N.; Farr, B.; Farr, W.; Feroz, F.; Gair, J.; Grover, K.; Graff, P.; Hanna, C.; Kalogera, V.; Mandel, I.; O'Shaughnessy, R.; Pitkin, M.; Price, L.; Raymond, V.; Röver, C.; Singer, L.; van der Sluys, M.; Smith, R. J. E.; Vecchio, A.; Veitch, J.; Vitale, S.

2014-04-01

The problem of reconstructing the sky position of compact binary coalescences detected via gravitational waves is a central one for future observations with the ground-based network of gravitational-wave laser interferometers, such as Advanced LIGO and Advanced Virgo. Different techniques for sky localization have been independently developed. They can be divided in two broad categories: fully coherent Bayesian techniques, which are high latency and aimed at in-depth studies of all the parameters of a source, including sky position, and "triangulation-based" techniques, which exploit the data products from the search stage of the analysis to provide an almost real-time approximation of the posterior probability density function of the sky location of a detection candidate. These techniques have previously been applied to data collected during the last science runs of gravitational-wave detectors operating in the so-called initial configuration. Here, we develop and analyze methods for assessing the self consistency of parameter estimation methods and carrying out fair comparisons between different algorithms, addressing issues of efficiency and optimality. These methods are general, and can be applied to parameter estimation problems other than sky localization. We apply these methods to two existing sky localization techniques representing the two above-mentioned categories, using a set of simulated inspiral-only signals from compact binary systems with a total mass of ≤20M⊙ and nonspinning components. We compare the relative advantages and costs of the two techniques and show that sky location uncertainties are on average a factor ≈20 smaller for fully coherent techniques than for the specific variant of the triangulation-based technique used during the last science runs, at the expense of a factor ≈1000 longer processing time.

Ultra-sensitive high performance liquid chromatography-laser-induced fluorescence based proteomics for clinical applications.

PubMed

Patil, Ajeetkumar; Bhat, Sujatha; Pai, Keerthilatha M; Rai, Lavanya; Kartha, V B; Chidangil, Santhosh

2015-09-08

An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper. In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

Ultrasonic sensor based defect detection and characterisation of ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh; Zhang, Tonzhua; Crouch, Ian

2014-01-01

Ceramic tiles, used in body armour systems, are currently inspected visually offline using an X-ray technique that is both time consuming and very expensive. The aim of this research is to develop a methodology to detect, locate and classify various manufacturing defects in Reaction Sintered Silicon Carbide (RSSC) ceramic tiles, using an ultrasonic sensing technique. Defects such as free silicon, un-sintered silicon carbide material and conventional porosity are often difficult to detect using conventional X-radiography. An alternative inspection system was developed to detect defects in ceramic components using an Artificial Neural Network (ANN) based signal processing technique. The inspection methodology proposed focuses on pre-processing of signals, de-noising, wavelet decomposition, feature extraction and post-processing of the signals for classification purposes. This research contributes to developing an on-line inspection system that would be far more cost effective than present methods and, moreover, assist manufacturers in checking the location of high density areas, defects and enable real time quality control, including the implementation of accept/reject criteria. Copyright © 2013 Elsevier B.V. All rights reserved.

Application of the modified transient plane source technique for early detection of liquid explosives

NASA Astrophysics Data System (ADS)

Bateman, Robert; Harris, Adam; Lee, Linda; Howle, Christopher R.; Ackermann, Sarah L. G.

2016-05-01

The paper will review the feasibility of adapting the Modified Transient Plane Source (MTPS) method as a screening tool for early-detection of explosives and hazardous materials. Materials can be distinguished from others based on their inherent thermal properties (e.g. thermal effusivity) in testing through different types of barrier materials. A complimentary advantage to this technique relative to other traditional detection technologies is that it can penetrate reflective barrier materials, such as aluminum, easily. A strong proof-of-principle is presented on application of the MTPS transient thermal property measuring in the early-screening of liquid explosives. The work demonstrates a significant sensitivity to distinguishing a wide range of fluids based on their thermal properties through a barrier material. The work covers various complicating factors to the longer-term adoption of such a method including the impact of carbonization and viscosity. While some technical challenges remain, the technique offers significant advantages in complimenting existing detection methods in being able to penetrate reflective metal containers (e.g. aluminum soft drinkscans) with ease.

Detection of stiff nanoparticles within cellular structures by contact resonance atomic force microscopy subsurface nanomechanical imaging.

PubMed

Reggente, Melania; Passeri, Daniele; Angeloni, Livia; Scaramuzzo, Francesca Anna; Barteri, Mario; De Angelis, Francesca; Persiconi, Irene; De Stefano, Maria Egle; Rossi, Marco

2017-05-04

Detecting stiff nanoparticles buried in soft biological matrices by atomic force microscopy (AFM) based techniques represents a new frontier in the field of scanning probe microscopies, originally developed as surface characterization methods. Here we report the detection of stiff (magnetic) nanoparticles (NPs) internalized in cells by using contact resonance AFM (CR-AFM) employed as a potentially non-destructive subsurface characterization tool. Magnetite (Fe 3 O 4 ) NPs were internalized in microglial cells from cerebral cortices of mouse embryos of 18 days by phagocytosis. Nanomechanical imaging of cells was performed by detecting the contact resonance frequencies (CRFs) of an AFM cantilever held in contact with the sample. Agglomerates of NPs internalized in cells were visualized on the basis of the local increase in the contact stiffness with respect to the surrounding biological matrix. A second AFM-based technique for nanomechanical imaging, i.e., HarmoniX™, as well as magnetic force microscopy and light microscopy were used to confirm the CR-AFM results. Thus, CR-AFM was demonstrated as a promising technique for subsurface imaging of nanomaterials in biological samples.

Baseline-free damage detection in composite plates based on the reciprocity principle

NASA Astrophysics Data System (ADS)

Huang, Liping; Zeng, Liang; Lin, Jing

2018-01-01

Lamb wave based damage detection techniques have been widely used in composite structures. In particular, these techniques usually rely on reference signals, which are significantly influenced by the operational and environmental conditions. To solve this issue, this paper presents a baseline-free damage inspection method based on the reciprocity principle. If a localized nonlinear scatterer exists along the wave path, the reciprocity breaks down. Through estimating the loss of reciprocity, the delamination could be detected. A reciprocity index (RI), which compares the discrepancy between the signal received in transducer B when emitting from transducer A and the signal received in A when the same source is located in B, is established to quantitatively analyze the reciprocity. Experimental results show that the RI value of a damaged path is much higher than that of a healthy path. In addition, the effects of the parameters of excitation signal (i.e., central frequency and bandwidth) and the position of delamination on the RI value are discussed. Furthermore, a RI based probabilistic imaging algorithm is proposed for detecting delamination damage of composite plates without reference signals. Finally, the effectiveness of this baseline-free damage detection method is validated by an experimental example.

Damage Detection in Rotorcraft Composite Structures Using Thermography and Laser-Based Ultrasound

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Zalameda, Joseph N.; Madaras, Eric I.

2004-01-01

New rotorcraft structural composite designs incorporate lower structural weight, reduced manufacturing complexity, and improved threat protection. These new structural concepts require nondestructive evaluation inspection technologies that can potentially be field-portable and able to inspect complex geometries for damage or structural defects. Two candidate technologies were considered: Thermography and Laser-Based Ultrasound (Laser UT). Thermography and Laser UT have the advantage of being non-contact inspection methods, with Thermography being a full-field imaging method and Laser UT a point scanning technique. These techniques were used to inspect composite samples that contained both embedded flaws and impact damage of various size and shape. Results showed that the inspection techniques were able to detect both embedded and impact damage with varying degrees of success.

Vision-based obstacle recognition system for automated lawn mower robot development

NASA Astrophysics Data System (ADS)

Mohd Zin, Zalhan; Ibrahim, Ratnawati

2011-06-01

Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

A search for methane in the atmosphere of Mars using ground-based mid infrared heterodyne spectroscopy

NASA Astrophysics Data System (ADS)

Sonnabend, G.; Stupar, D.; Sornig, M.; Stangier, T.; Kostiuk, T.; Livengood, T. A.

2013-09-01

We report our search for methane in the atmosphere of Mars using high-spectral resolution heterodyne spectroscopy in the 7.8 μm wavelength region. Resolving power and frequency precision of >106 of the technique enable identification and full resolution of a targeted spectral line in the terrestrial-Mars spectrum observed from the ground. Observations were carried out on two occasions, in April 2010 and May 2012 at the McMath-Pierce Solar Telescope and the NASA Infrared Telescope Facility, respectively. A single line in the ν4 band of methane at 1282.62448 cm-1 was targeted in both cases. No absorption due to methane was detected and only upper limits of ∼100 ppb for the martian atmospheric methane concentration were retrieved. Lack of observing time (due to weather) and telluric opacity greater than anticipated led to reduced signal-to-noise ratios (SNR). Based on current measurements and calculations, under proper viewing conditions, we estimate an achievable detection limit of ∼10 ppb using the infrared heterodyne technique - adequate for confirming reported detections of methane based on other techniques.

Step-gate polysilicon nanowires field effect transistor compatible with CMOS technology for label-free DNA biosensor.

PubMed

Wenga, G; Jacques, E; Salaün, A-C; Rogel, R; Pichon, L; Geneste, F

2013-02-15

Currently, detection of DNA hybridization using fluorescence-based detection technique requires expensive optical systems and complex bioinformatics tools. Hence, the development of new low cost devices that enable direct and highly sensitive detection stimulates a lot of research efforts. Particularly, devices based on silicon nanowires are emerging as ultrasensitive electrical sensors for the direct detection of biological species thanks to their high surface to volume ratio. In this study, we propose innovative devices using step-gate polycrystalline silicon nanowire FET (poly-Si NW FETs), achieved with simple and low cost fabrication process, and used as ultrasensitive electronic sensor for DNA hybridization. The poly-SiNWs are synthesized using the sidewall spacer formation technique. The detailed fabrication procedure for a step-gate NWFET sensor is described in this paper. No-complementary and complementary DNA sequences were clearly discriminated and detection limit to 1 fM range is observed. This first result using this nano-device is promising for the development of low cost and ultrasensitive polysilicon nanowires based DNA sensors compatible with the CMOS technology. Copyright © 2012 Elsevier B.V. All rights reserved.

Detection of neurotransmitters by a light scattering technique based on seed-mediated growth of gold nanoparticles

NASA Astrophysics Data System (ADS)

Shang, Li; Dong, Shaojun

2008-03-01

A simple light scattering detection method for neurotransmitters has been developed, based on the growth of gold nanoparticles. Neurotransmitters (dopamine, L-dopa, noradrenaline and adrenaline) can effectively function as active reducing agents for generating gold nanoparticles, which result in enhanced light scattering signals. The strong light scattering of gold nanoparticles then allows the quantitative detection of the neurotransmitters simply by using a common spectrofluorometer. In particular, Au-nanoparticle seeds were added to facilitate the growth of nanoparticles, which was found to enhance the sensing performance greatly. Using this light scattering technique based on the seed-mediated growth of gold nanoparticles, detection limits of 4.4 × 10-7 M, 3.5 × 10-7 M, 4.1 × 10-7 M, and 7.7 × 10-7 M were achieved for dopamine, L-dopa, noradrenaline and adrenaline, respectively. The present strategy can be extended to detect other biologically important molecules in a very fast, simple and sensitive way, and may have potential applications in a wide range of fields.

Detection of Glaucoma Using Image Processing Techniques: A Critique.

PubMed

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

2018-01-01

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

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique.

PubMed

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-03-15

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system's lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system's ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection.

Shot noise limited detection of OH using the technique of laser induced fluorescence

NASA Technical Reports Server (NTRS)

Bakalyar, D. M.; Davis, L. I., Jr.; Guo, C.; James, J. V.; Kakos, S.; Morris, P. T.; Wang, C. C.

1984-01-01

Nearly shot-noise limited detection of OH using the technique of laser-induced fluorescence is reported. A LIDAR configuration is used to excite fluorescence in a large volume and a narrow-bandwidth interference filter provides spectral discrimination. This arrangement alleviates the effect of ozone interference and facilitates image processing at relatively close distances. The detection limit is determined mainly by the shot-noise of the solar background. Ground-based measurements in Dearborn indicate a detection limit of better than 1 x 10 to the 6th power OH/cubic cm over a forty-minute acquisition period. Under favorable conditions, a comparable detection limit was also observed for airborne measurements.

Shot noise limited detection of OH using the technique of laser-induced fluorescence

NASA Technical Reports Server (NTRS)

Bakalyar, D. M.; Davis, L. I., Jr.; Guo, C.; James, J. V.; Wang, C. C.; Kakos, S.; Morris, P. T.

1984-01-01

Nearly shot-noise limited detection of OH using the technique of laser-induced fluorescence is reported. A LIDAR configuration is used to excite fluoresence in a large volume and a narrow-bandwidth interference filter provides spectral discrimination. This arrangement alleviates the effect of ozone interference and facilitates image processing at relatively close distances. The detection limit is determined mainly by the short-noise of the solar background. Ground-based measurements in Dearborn indicate a detection limit of better than 1 x 10 to the 6th power OH/cubic cm over a forty-minute acquisition period. Under favorable conditions, a comparable detection limit was also observed for airborne measurements.

Technique for ship/wake detection

DOEpatents

Roskovensky, John K [Albuquerque, NM

2012-05-01

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

A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition

PubMed Central

Paul, R R; Mukherjee, A; Dutta, P K; Banerjee, S; Pal, M; Chatterjee, J; Chaudhuri, K; Mukkerjee, K

2005-01-01

Aim: To describe a novel neural network based oral precancer (oral submucous fibrosis; OSF) stage detection method. Method: The wavelet coefficients of transmission electron microscopy images of collagen fibres from normal oral submucosa and OSF tissues were used to choose the feature vector which, in turn, was used to train the artificial neural network. Results: The trained network was able to classify normal and oral precancer stages (less advanced and advanced) after obtaining the image as an input. Conclusions: The results obtained from this proposed technique were promising and suggest that with further optimisation this method could be used to detect and stage OSF, and could be adapted for other conditions. PMID:16126873

Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

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

Su, Hui

2001-01-01

Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitablymore » designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm 2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection.« less

Improving membrane based multiplex immunoassays for semi-quantitative detection of multiple cytokines in a single sample

PubMed Central

2014-01-01

Background Inflammatory mediators can serve as biomarkers for the monitoring of the disease progression or prognosis in many conditions. In the present study we introduce an adaptation of a membrane-based technique in which the level of up to 40 cytokines and chemokines can be determined in both human and rodent blood in a semi-quantitative way. The planar assay was modified using the LI-COR (R) detection system (fluorescence based) rather than chemiluminescence and semi-quantitative outcomes were achieved by normalizing the outcomes using the automated exposure settings of the Odyssey readout device. The results were compared to the gold standard assay, namely ELISA. Results The improved planar assay allowed the detection of a considerably higher number of analytes (n = 30 and n = 5 for fluorescent and chemiluminescent detection, respectively). The improved planar method showed high sensitivity up to 17 pg/ml and a linear correlation of the normalized fluorescence intensity with the results from the ELISA (r = 0.91). Conclusions The results show that the membrane-based technique is a semi-quantitative assay that correlates satisfactorily to the gold standard when enhanced by the use of fluorescence and subsequent semi-quantitative analysis. This promising technique can be used to investigate inflammatory profiles in multiple conditions, particularly in studies with constraints in sample sizes and/or budget. PMID:25022797

Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples.

PubMed

Alasaad, Noor; Alzubi, Hussein; Kader, Ahmad Abdul

2016-06-01

Food and feed samples were randomly collected from different sources, including local and imported materials from the Syrian local market. These included maize, barley, soybean, fresh food samples and raw material. GMO detection was conducted by PCR and nested PCR-based techniques using specific primers for the most used foreign DNA commonly used in genetic transformation procedures, i.e., 35S promoter, T-nos, epsps, cryIA(b) gene and nptII gene. The results revealed for the first time in Syria the presence of GM foods and feeds with glyphosate-resistant trait of P35S promoter and NOS terminator in the imported soybean samples with high frequency (5 out of the 6 imported soybean samples). While, tests showed negative results for the local samples. Also, tests revealed existence of GMOs in two imported maize samples detecting the presence of 35S promoter and nos terminator. Nested PCR results using two sets of primers confirmed our data. The methods applied in the brief data are based on DNA analysis by Polymerase Chain Reaction (PCR). This technique is specific, practical, reproducible and sensitive enough to detect up to 0.1% GMO in food and/or feedstuffs. Furthermore, all of the techniques mentioned are economic and can be applied in Syria and other developing countries. For all these reasons, the DNA-based analysis methods were chosen and preferred over protein-based analysis.

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.

Polydiacetylene-Based Liposomes: An "Optical Tongue" for Bacteria Detection and Identification

ERIC Educational Resources Information Center

West, Matthew R.; Hanks, Timothy W.; Watson, Rhett T.

2009-01-01

Food- and water-borne bacteria are a major health concern worldwide. Current detection methods are time-consuming and require sophisticated equipment that is not always readily available. However, new techniques based on nanotechnology are under development that will result in a new generation of sensors. In this experiment, liposomes are…

Laser-Induced Breakdown Spectroscopy: A Review of Applied Explosive Detection

DTIC Science & Technology

2013-09-01

Based Techniques ..........................................................................................7 2.5 Ion Mobility and Mass Spectrometry...proximal trace detection. We show that the algorithms for material identification could be improved by including the critical signatures (e.g., C2...IMS), desorption electrospray ionization (DESI), laser electrospray mass spectrometry (LEMS), emerging efforts like antibody/antigen-based efforts

DC-to-AC inverter ratio failure detector

NASA Technical Reports Server (NTRS)

Ebersole, T. J.; Andrews, R. E.

1975-01-01

Failure detection technique is based upon input-output ratios, which is independent of inverter loading. Since inverter has fixed relationship between V-in/V-out and I-in/I-out, failure detection criteria are based on this ratio, which is simply inverter transformer turns ratio, K, equal to primary turns divided by secondary turns.

Community Detection for Correlation Matrices

NASA Astrophysics Data System (ADS)

MacMahon, Mel; Garlaschelli, Diego

2015-04-01

A challenging problem in the study of complex systems is that of resolving, without prior information, the emergent, mesoscopic organization determined by groups of units whose dynamical activity is more strongly correlated internally than with the rest of the system. The existing techniques to filter correlations are not explicitly oriented towards identifying such modules and can suffer from an unavoidable information loss. A promising alternative is that of employing community detection techniques developed in network theory. Unfortunately, this approach has focused predominantly on replacing network data with correlation matrices, a procedure that we show to be intrinsically biased because of its inconsistency with the null hypotheses underlying the existing algorithms. Here, we introduce, via a consistent redefinition of null models based on random matrix theory, the appropriate correlation-based counterparts of the most popular community detection techniques. Our methods can filter out both unit-specific noise and system-wide dependencies, and the resulting communities are internally correlated and mutually anticorrelated. We also implement multiresolution and multifrequency approaches revealing hierarchically nested subcommunities with "hard" cores and "soft" peripheries. We apply our techniques to several financial time series and identify mesoscopic groups of stocks which are irreducible to a standard, sectorial taxonomy; detect "soft stocks" that alternate between communities; and discuss implications for portfolio optimization and risk management.

Computer-Aided Diagnostic (CAD) Scheme by Use of Contralateral Subtraction Technique

NASA Astrophysics Data System (ADS)

Nagashima, Hiroyuki; Harakawa, Tetsumi

We developed a computer-aided diagnostic (CAD) scheme for detection of subtle image findings of acute cerebral infarction in brain computed tomography (CT) by using a contralateral subtraction technique. In our computerized scheme, the lateral inclination of image was first corrected automatically by rotating and shifting. The contralateral subtraction image was then derived by subtraction of reversed image from original image. Initial candidates for acute cerebral infarctions were identified using the multiple-thresholding and image filtering techniques. As the 1st step for removing false positive candidates, fourteen image features were extracted in each of the initial candidates. Halfway candidates were detected by applying the rule-based test with these image features. At the 2nd step, five image features were extracted using the overlapping scale with halfway candidates in interest slice and upper/lower slice image. Finally, acute cerebral infarction candidates were detected by applying the rule-based test with five image features. The sensitivity in the detection for 74 training cases was 97.4% with 3.7 false positives per image. The performance of CAD scheme for 44 testing cases had an approximate result to training cases. Our CAD scheme using the contralateral subtraction technique can reveal suspected image findings of acute cerebral infarctions in CT images.

Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads

DOE PAGES

Rosen, Gail L.; Polikar, Robi; Caseiro, Diamantino A.; ...

2011-01-01

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments (“reads”) from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted. We develop a detection technique that can discriminate between “known” and “unknown” taxa, which can be used with composition-based methods, as well as a hybrid method. Unlike previous studies, we rigorously evaluate all algorithms for theirmore » ability to detect novel taxa. First, we show that the integration of a detector with a composition-based method performs significantly better than homology-based methods for the detection of novel species and genera, with best performance at finer taxonomic resolutions. Most importantly, we evaluate all the algorithms by introducing an “unknown” class and show that the modified version of PhymmBL has similar or better overall classification performance than the other modified algorithms, especially for the species-level and ultrashort reads. Finally, we evaluate theperformance of several algorithms on a real acid mine drainage dataset.« less

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

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah

2016-05-01

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

The combined use of the RST-FIRES algorithm and geostationary satellite data to timely detect fires

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2017-04-01

Timely detection of fires may enable a rapid contrast action before they become uncontrolled and wipe out entire forests. Remote sensing, especially based on geostationary satellite data, can be successfully used to this aim. Differently from sensors onboard polar orbiting platforms, instruments on geostationary satellites guarantee a very high temporal resolution (from 30 to 2,5 minutes) which may be usefully employed to carry out a "continuous" monitoring over large areas as well as to timely detect fires at their early stages. Together with adequate satellite data, an appropriate fire detection algorithm should be used. Over the last years, many fire detection algorithms have been just adapted from polar to geostationary sensors and, consequently, the very high temporal resolution of geostationary sensors is not exploited at all in tests for fire identification. In addition, even when specifically designed for geostationary satellite sensors, fire detection algorithms are frequently based on fixed thresholds tests which are generally set up in the most conservative way to avoid false alarm proliferation. The result is a low algorithm sensitivity which generally means that only large and/or extremely intense events are detected. This work describes the Robust Satellite Techniques for FIRES detection and monitoring (RST-FIRES) which is a multi-temporal change-detection technique trying to overcome the above mentioned issues. Its performance in terms of reliability and sensitivity was verified using data acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG) geostationary platform. More than 20,000 SEVIRI images, collected during a four-year-collaboration with the Regional Civil Protection Departments and Local Authorities of two Italian regions, were used. About 950 near real-time ground and aerial checks of the RST-FIRES detections were performed. This study also demonstrates the added value of the RST-FIRES technique to detect starting/small fires and its sensitivity from 3 to 70 times higher than any other similar SEVIRI-based products.

Existing and emerging detection technologies for DNA (Deoxyribonucleic Acid) finger printing, sequencing, bio- and analytical chips: a multidisciplinary development unifying molecular biology, chemical and electronics engineering.

PubMed

Kumar Khanna, Vinod

2007-01-01

The current status and research trends of detection techniques for DNA-based analysis such as DNA finger printing, sequencing, biochips and allied fields are examined. An overview of main detectors is presented vis-à-vis these DNA operations. The biochip method is explained, the role of micro- and nanoelectronic technologies in biochip realization is highlighted, various optical and electrical detection principles employed in biochips are indicated, and the operational mechanisms of these detection devices are described. Although a diversity of biochips for diagnostic and therapeutic applications has been demonstrated in research laboratories worldwide, only some of these chips have entered the clinical market, and more chips are awaiting commercialization. The necessity of tagging is eliminated in refractive-index change based devices, but the basic flaw of indirect nature of most detection methodologies can only be overcome by generic and/or reagentless DNA sensors such as the conductance-based approach and the DNA-single electron transistor (DNA-SET) structure. Devices of the electrical detection-based category are expected to pave the pathway for the next-generation DNA chips. The review provides a comprehensive coverage of the detection technologies for DNA finger printing, sequencing and related techniques, encompassing a variety of methods from the primitive art to the state-of-the-art scenario as well as promising methods for the future.

Nanomaterials-Based Optical Techniques for the Detection of Acetylcholinesterase and Pesticides

PubMed Central

Xia, Ning; Wang, Qinglong; Liu, Lin

2015-01-01

The large amount of pesticide residues in the environment is a threat to global health by inhibition of acetylcholinesterase (AChE). Biosensors for inhibition of AChE have been thus developed for the detection of pesticides. In line with the rapid development of nanotechnology, nanomaterials have attracted great attention and have been intensively studied in biological analysis due to their unique chemical, physical and size properties. The aim of this review is to provide insight into nanomaterial-based optical techniques for the determination of AChE and pesticides, including colorimetric and fluorescent assays and surface plasmon resonance. PMID:25558991

Comparison of remote sensing image processing techniques to identify tornado damage areas from Landsat TM data

USGS Publications Warehouse

Myint, S.W.; Yuan, M.; Cerveny, R.S.; Giri, C.P.

2008-01-01

Remote sensing techniques have been shown effective for large-scale damage surveys after a hazardous event in both near real-time or post-event analyses. The paper aims to compare accuracy of common imaging processing techniques to detect tornado damage tracks from Landsat TM data. We employed the direct change detection approach using two sets of images acquired before and after the tornado event to produce a principal component composite images and a set of image difference bands. Techniques in the comparison include supervised classification, unsupervised classification, and objectoriented classification approach with a nearest neighbor classifier. Accuracy assessment is based on Kappa coefficient calculated from error matrices which cross tabulate correctly identified cells on the TM image and commission and omission errors in the result. Overall, the Object-oriented Approach exhibits the highest degree of accuracy in tornado damage detection. PCA and Image Differencing methods show comparable outcomes. While selected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approach performs significantly better with 15-20% higher accuracy than the other two techniques. ?? 2008 by MDPI.

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

PubMed Central

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

2008-01-01

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

[Recombinase Polymerase Amplification and its Applications in Parasite Detection].

PubMed

ZHENG, Wen-bin; WU, Yao-dong; MA, Jian-gang; ZHU, Xing-quan; ZHOU, Dong-hui

2015-10-01

Recombinase polymerase amplification (RPA) is a recently -developed isothermal nucleic-acid-amplification technology that is based on the nucleic acid replication mechanism in T4 bacteriophage. With this technique, nucleic-acid templates can be amplified to measurable levels within 20 min at 37-42 °C. The. RPA process has high sensitivity and specificity, and is simple to operate, thus nucleic acids can be detected rapidly in non-laboratory conditions. Since its development in 2006, the RPA technique has been applied in agriculture, food safety, medicine, transgene detection, etc. In this review, we will give an overview on the research progress of RPA and its application in parasite detection.

A technique for simultaneous detection of individual vortex states of Laguerre-Gaussian beams transmitted through an aqueous suspension of microparticles

NASA Astrophysics Data System (ADS)

Khonina, S. N.; Karpeev, S. V.; Paranin, V. D.

2018-06-01

A technique for simultaneous detection of individual vortex states of the beams propagating in a randomly inhomogeneous medium is proposed. The developed optical system relies on the correlation method that is invariant to the beam wandering. The intensity distribution formed at the optical system output does not require digital processing. The proposed technique based on a multi-order phase diffractive optical element (DOE) is studied numerically and experimentally. The developed detection technique is used for the analysis of Laguerre-Gaussian vortex beams propagating under conditions of intense absorption, reflection, and scattering in transparent and opaque microparticles in aqueous suspensions. The performed experimental studies confirm the relevance of the vortex phase dependence of a laser beam under conditions of significant absorption, reflection, and scattering of the light.

Automated Network Anomaly Detection with Learning, Control and Mitigation

ERIC Educational Resources Information Center

Ippoliti, Dennis

2014-01-01

Anomaly detection is a challenging problem that has been researched within a variety of application domains. In network intrusion detection, anomaly based techniques are particularly attractive because of their ability to identify previously unknown attacks without the need to be programmed with the specific signatures of every possible attack.…

Local Measurement of Tropospheric HO(x)

NASA Technical Reports Server (NTRS)

Crosley, David R.

1994-01-01

In March of 1992 a workshop sponsored by NASA and NSF was held at SRI International to assess the current ability to measure atmospheric OH and HO2. The measurement techniques reviewed during the workshop for detection of OH included five laser-induced fluorescence schemes, five laser-based adsorption techniques, and four non-laser methods. Six instruments or instrument concepts for HO2 detection, including chemical amplification, conversion to OH with subsequent OH detection, or direct spectroscopic detection of the HO2 were also discussed. The conclusions from the workshop identify several measurement techniques for OH and HO2 that are ready for field tests. These have the ability to measure the radicals with sufficient sensitivity and accuracy to form meaningful comparison with atmospheric model predictions. The workshop conclusions also include recommendations for informal and formal intercomparison protocols.

QRS classification and spatial combination for robust heart rate detection in low-quality fetal ECG recordings.

PubMed

Warmerdam, G; Vullings, R; Van Pul, C; Andriessen, P; Oei, S G; Wijn, P

2013-01-01

Non-invasive fetal electrocardiography (ECG) can be used for prolonged monitoring of the fetal heart rate (FHR). However, the signal-to-noise-ratio (SNR) of non-invasive ECG recordings is often insufficient for reliable detection of the FHR. To overcome this problem, source separation techniques can be used to enhance the fetal ECG. This study uses a physiology-based source separation (PBSS) technique that has already been demonstrated to outperform widely used blind source separation techniques. Despite the relatively good performance of PBSS in enhancing the fetal ECG, PBSS is still susceptible to artifacts. In this study an augmented PBSS technique is developed to reduce the influence of artifacts. The performance of the developed method is compared to PBSS on multi-channel non-invasive fetal ECG recordings. Based on this comparison, the developed method is shown to outperform PBSS for the enhancement of the fetal ECG.

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

SERS-based inverse molecular sentinel (iMS) nanoprobes for multiplexed detection of microRNA cancer biomarkers in biological samples

NASA Astrophysics Data System (ADS)

Crawford, Bridget M.; Wang, Hsin-Neng; Fales, Andrew M.; Bowie, Michelle L.; Seewaldt, Victoria L.; Vo-Dinh, Tuan

2017-02-01

The development of sensitive and selective biosensing techniques is of great interest for clinical diagnostics. Here, we describe the development and application of a surface enhanced Raman scattering (SERS) sensing technology, referred to as "inverse Molecular Sentinel (iMS)" nanoprobes, for the detection of nucleic acid biomarkers in biological samples. This iMS nanoprobe involves the use of plasmonic-active nanostars as the sensing platform for a homogenous assay for multiplexed detection of nucleic acid biomarkers, including DNA, RNA and microRNA (miRNA). The "OFF-to-ON" signal switch is based on a non-enzymatic strand-displacement process and the conformational change of stem-loop (hairpin) oligonucleotide probes upon target binding. Here, we demonstrate the development of iMS nanoprobes for the detection of DNA sequences as well as a modified design of the nanoprobe for the detection of short (22-nt) microRNA sequences. The application of iMS nanoprobes to detect miRNAs in real biological samples was performed with total small RNA extracted from breast cancer cell lines. The multiplex capability of the iMS technique was demonstrated using a mixture of the two differently labeled nanoprobes to detect miR-21 and miR-34a miRNA biomarkers for breast cancer. The results of this study demonstrate the feasibility of applying the iMS technique for multiplexed detection of nucleic acid biomarkers, including short miRNAs molecules.

Density-based parallel skin lesion border detection with webCL

PubMed Central

2015-01-01

Background Dermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate borders through a hand drawn representation based upon visual inspection. Due to the subjective nature of this technique, intra- and inter-observer variations are common. Because of this, the automated assessment of lesion borders in dermoscopic images has become an important area of study. Methods Fast density based skin lesion border detection method has been implemented in parallel with a new parallel technology called WebCL. WebCL utilizes client side computing capabilities to use available hardware resources such as multi cores and GPUs. Developed WebCL-parallel density based skin lesion border detection method runs efficiently from internet browsers. Results Previous research indicates that one of the highest accuracy rates can be achieved using density based clustering techniques for skin lesion border detection. While these algorithms do have unfavorable time complexities, this effect could be mitigated when implemented in parallel. In this study, density based clustering technique for skin lesion border detection is parallelized and redesigned to run very efficiently on the heterogeneous platforms (e.g. tablets, SmartPhones, multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units) by transforming the technique into a series of independent concurrent operations. Heterogeneous computing is adopted to support accessibility, portability and multi-device use in the clinical settings. For this, we used WebCL, an emerging technology that enables a HTML5 Web browser to execute code in parallel for heterogeneous platforms. We depicted WebCL and our parallel algorithm design. In addition, we tested parallel code on 100 dermoscopy images and showed the execution speedups with respect to the serial version. Results indicate that parallel (WebCL) version and serial version of density based lesion border detection methods generate the same accuracy rates for 100 dermoscopy images, in which mean of border error is 6.94%, mean of recall is 76.66%, and mean of precision is 99.29% respectively. Moreover, WebCL version's speedup factor for 100 dermoscopy images' lesion border detection averages around ~491.2. Conclusions When large amount of high resolution dermoscopy images considered in a usual clinical setting along with the critical importance of early detection and diagnosis of melanoma before metastasis, the importance of fast processing dermoscopy images become obvious. In this paper, we introduce WebCL and the use of it for biomedical image processing applications. WebCL is a javascript binding of OpenCL, which takes advantage of GPU computing from a web browser. Therefore, WebCL parallel version of density based skin lesion border detection introduced in this study can supplement expert dermatologist, and aid them in early diagnosis of skin lesions. While WebCL is currently an emerging technology, a full adoption of WebCL into the HTML5 standard would allow for this implementation to run on a very large set of hardware and software systems. WebCL takes full advantage of parallel computational resources including multi-cores and GPUs on a local machine, and allows for compiled code to run directly from the Web Browser. PMID:26423836

Density-based parallel skin lesion border detection with webCL.

PubMed

Lemon, James; Kockara, Sinan; Halic, Tansel; Mete, Mutlu

2015-01-01

Dermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate borders through a hand drawn representation based upon visual inspection. Due to the subjective nature of this technique, intra- and inter-observer variations are common. Because of this, the automated assessment of lesion borders in dermoscopic images has become an important area of study. Fast density based skin lesion border detection method has been implemented in parallel with a new parallel technology called WebCL. WebCL utilizes client side computing capabilities to use available hardware resources such as multi cores and GPUs. Developed WebCL-parallel density based skin lesion border detection method runs efficiently from internet browsers. Previous research indicates that one of the highest accuracy rates can be achieved using density based clustering techniques for skin lesion border detection. While these algorithms do have unfavorable time complexities, this effect could be mitigated when implemented in parallel. In this study, density based clustering technique for skin lesion border detection is parallelized and redesigned to run very efficiently on the heterogeneous platforms (e.g. tablets, SmartPhones, multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units) by transforming the technique into a series of independent concurrent operations. Heterogeneous computing is adopted to support accessibility, portability and multi-device use in the clinical settings. For this, we used WebCL, an emerging technology that enables a HTML5 Web browser to execute code in parallel for heterogeneous platforms. We depicted WebCL and our parallel algorithm design. In addition, we tested parallel code on 100 dermoscopy images and showed the execution speedups with respect to the serial version. Results indicate that parallel (WebCL) version and serial version of density based lesion border detection methods generate the same accuracy rates for 100 dermoscopy images, in which mean of border error is 6.94%, mean of recall is 76.66%, and mean of precision is 99.29% respectively. Moreover, WebCL version's speedup factor for 100 dermoscopy images' lesion border detection averages around ~491.2. When large amount of high resolution dermoscopy images considered in a usual clinical setting along with the critical importance of early detection and diagnosis of melanoma before metastasis, the importance of fast processing dermoscopy images become obvious. In this paper, we introduce WebCL and the use of it for biomedical image processing applications. WebCL is a javascript binding of OpenCL, which takes advantage of GPU computing from a web browser. Therefore, WebCL parallel version of density based skin lesion border detection introduced in this study can supplement expert dermatologist, and aid them in early diagnosis of skin lesions. While WebCL is currently an emerging technology, a full adoption of WebCL into the HTML5 standard would allow for this implementation to run on a very large set of hardware and software systems. WebCL takes full advantage of parallel computational resources including multi-cores and GPUs on a local machine, and allows for compiled code to run directly from the Web Browser.

Detection and Monitoring of Toxic Chemical at Ultra Trace Level by Utilizing Doped Nanomaterial

PubMed Central

Khan, Sher Bahadar; Rahman, Mohammed M.; Akhtar, Kalsoom; Asiri, Abdullah M.

2014-01-01

Composite nanoparticles were synthesized by eco-friendly hydrothermal process and characterized by different spectroscopic techniques. All the spectroscopic techniques suggested the synthesis of well crystalline optically active composite nanoparticles with average diameter of ∼30 nm. The synthesized nanoparticles were applied for the development of chemical sensor which was fabricated by coating the nanoparticles on silver electrode for the recognition of phthalimide using simple I–V technique. The developed sensor exhibited high sensitivity (1.7361 µA.mM−1.cm−2), lower detection limit (8.0 µM) and long range of detection (77.0 µM to 0.38 M). Further the resistances of composite nanoparticles based sensor was found to be 2.7 MΩ which change from 2.7 to 1.7 with change in phthalimide concentration. The major advantages of the designed sensor over existing sensors are its simple technique, low cost, lower detection limit, high sensitivity and long range of detection. It can detect phthalimide even at trace level and sense over wide range of concentrations. Therefore the composite nanoparticals would be a better choice for the fabrication of phthalimide chemical sensor and would be time and cost substituted implement for environmental safety. PMID:25329666

Enzyme-based electrochemical biosensors for determination of organophosphorus and carbamate pesticides

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

Everett, W.R.; Rechnitz, G.A.

1999-01-01

A mini review of enzyme-based electrochemical biosensors for inhibition analysis of organophosphorus and carbamate pesticides is presented. Discussion includes the most recent literature to present advances in detection limits, selectivity and real sample analysis. Recent reviews on the monitoring of pesticides and their residues suggest that the classical analytical techniques of gas and liquid chromatography are the most widely used methods of detection. These techniques, although very accurate in their determinations, can be quite time consuming and expensive and usually require extensive sample clean up and pro-concentration. For these and many other reasons, the classical techniques are very difficult tomore » adapt for field use. Numerous researchers, in the past decade, have developed and made improvements on biosensors for use in pesticide analysis. This mini review will focus on recent advances made in enzyme-based electrochemical biosensors for the determinations of organophosphorus and carbamate pesticides.« less

Ground-based mm-wave emission spectroscopy for the detection and monitoring of stratospheric ozone

NASA Technical Reports Server (NTRS)

Parrish, A.; Dezafra, R.; Solomon, P.

1981-01-01

The molecular rotational spectrum of ozone is quite rich in the mm-wave region from 50 to 300 GHz. An apparatus, which was developed primarily for detection and measurement of stratospheric ClO and other trace molecules, is found to be well suited also for the observation of ozone lines. The collecting antenna of the apparatus is a simple mm-waveguide feedhorn. The detector is a superheterodyne mixer using a special high frequency Schottky diode and a klystron local oscillator. The spectrometer is a 256 channel filter bank with 1 MHz resolution per channel. The apparatus is believed to be the first ground-based mm-wave instrument having the capability of obtaining data of sufficient quality to make use of the inversion technique. The ground based radio technique is most sensitive to changes in vertical distribution in the region above 25 km, a region which is difficult to sample by other techniques.

Restoration of out-of-focus images based on circle of confusion estimate

NASA Astrophysics Data System (ADS)

Vivirito, Paolo; Battiato, Sebastiano; Curti, Salvatore; La Cascia, M.; Pirrone, Roberto

2002-11-01

In this paper a new method for a fast out-of-focus blur estimation and restoration is proposed. It is suitable for CFA (Color Filter Array) images acquired by typical CCD/CMOS sensor. The method is based on the analysis of a single image and consists of two steps: 1) out-of-focus blur estimation via Bayer pattern analysis; 2) image restoration. Blur estimation is based on a block-wise edge detection technique. This edge detection is carried out on the green pixels of the CFA sensor image also called Bayer pattern. Once the blur level has been estimated the image is restored through the application of a new inverse filtering technique. This algorithm gives sharp images reducing ringing and crisping artifact, involving wider region of frequency. Experimental results show the effectiveness of the method, both in subjective and numerical way, by comparison with other techniques found in literature.

Chemiluminescent optical fiber immunosensor for the detection of anti-West Nile virus IgG.

PubMed

Herrmann, Sebastien; Leshem, Boaz; Landes, Shimi; Rager-Zisman, Bracha; Marks, Robert S

2005-03-31

An ELISA-based optical fiber methodology developed for the detection of anti-West Nile virus IgG antibodies in serum was compared to standard colorimetric and chemiluminescent ELISA based on microtiter plates. Colorimetric ELISA was the least sensitive, especially at high titer dilutions. The fiber-optic immunosensor based on the same ELISA immunological rationale was the most sensitive technique.

Multiplexed Paper Analytical Device for Quantification of Metals using Distance-Based Detection

PubMed Central

Cate, David M.; Noblitt, Scott D.; Volckens, John; Henry, Charles S.

2015-01-01

Exposure to metal-containing aerosols has been linked with adverse health outcomes for almost every organ in the human body. Commercially available techniques for quantifying particulate metals are time-intensive, laborious, and expensive; often sample analysis exceeds $100. We report a simple technique, based upon a distance-based detection motif, for quantifying metal concentrations of Ni, Cu, and Fe in airborne particulate matter using microfluidic paper-based analytical devices. Paper substrates are used to create sensors that are self-contained, self-timing, and require only a drop of sample for operation. Unlike other colorimetric approaches in paper microfluidics that rely on optical instrumentation for analysis, with distance-based detection, analyte is quantified visually based on the distance of a colorimetric reaction, similar to reading temperature on a thermometer. To demonstrate the effectiveness of this approach, Ni, Cu, and Fe were measured individually in single-channel devices; detection limits as low as 0.1, 0.1, and 0.05 µg were reported for Ni, Cu, and Fe. Multiplexed analysis of all three metals was achieved with detection limits of 1, 5, and 1 µg for Ni, Cu, and Fe. We also extended the dynamic range for multi-analyte detection by printing concentration gradients of colorimetric reagents using an off the shelf inkjet printer. Analyte selectivity was demonstrated for common interferences. To demonstrate utility of the method, Ni, Cu, and Fe were measured from samples of certified welding fume; levels measured with paper sensors matched known values determined gravimetrically. PMID:26009988

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

A novel, multiplex, real-time PCR-based approach for the detection of the commonly occurring pathogenic fungi and bacteria.

PubMed

Horváth, Ádám; Pető, Zoltán; Urbán, Edit; Vágvölgyi, Csaba; Somogyvári, Ferenc

2013-12-23

Polymerase chain reaction (PCR)-based techniques are widely used to identify fungal and bacterial infections. There have been numerous reports of different, new, real-time PCR-based pathogen identification methods although the clinical practicability of such techniques is not yet fully clarified.The present study focuses on a novel, multiplex, real-time PCR-based pathogen identification system developed for rapid differentiation of the commonly occurring bacterial and fungal causative pathogens of bloodstream infections. A multiplex, real-time PCR approach is introduced for the detection and differentiation of fungi, Gram-positive (G+) and Gram-negative (G-) bacteria. The Gram classification is performed with the specific fluorescence resonance energy transfer (FRET) probes recommended for LightCycler capillary real-time PCR. The novelty of our system is the use of a non-specific SYBR Green dye instead of labelled anchor probes or primers, to excite the acceptor dyes on the FRET probes. In conjunction with this, the use of an intercalating dye allows the detection of fungal amplicons.With the novel pathogen detection system, fungi, G + and G- bacteria in the same reaction tube can be differentiated within an hour after the DNA preparation via the melting temperatures of the amplicons and probes in the same tube. This modified FRET technique is specific and more rapid than the gold-standard culture-based methods. The fact that fungi, G + and G- bacteria were successfully identified in the same tube within an hour after the DNA preparation permits rapid and early evidence-based management of bloodstream infections in clinical practice.

Ultrasound elastography: principles, techniques, and clinical applications.

PubMed

Dewall, Ryan J

2013-01-01

Ultrasound elastography is an emerging set of imaging modalities used to image tissue elasticity and are often referred to as virtual palpation. These techniques have proven effective in detecting and assessing many different pathologies, because tissue mechanical changes often correlate with tissue pathological changes. This article reviews the principles of ultrasound elastography, many of the ultrasound-based techniques, and popular clinical applications. Originally, elastography was a technique that imaged tissue strain by comparing pre- and postcompression ultrasound images. However, new techniques have been developed that use different excitation methods such as external vibration or acoustic radiation force. Some techniques track transient phenomena such as shear waves to quantitatively measure tissue elasticity. Clinical use of elastography is increasing, with applications including lesion detection and classification, fibrosis staging, treatment monitoring, vascular imaging, and musculoskeletal applications.

Electrochemical impedance spectroscopy based MEMS sensors for phthalates detection in water and juices

NASA Astrophysics Data System (ADS)

Zia, Asif I.; Mohd Syaifudin, A. R.; Mukhopadhyay, S. C.; Yu, P. L.; Al-Bahadly, I. H.; Gooneratne, Chinthaka P.; Kosel, Jǘrgen; Liao, Tai-Shan

2013-06-01

Phthalate esters are ubiquitous environmental and food pollutants well known as endocrine disrupting compounds (EDCs). These developmental and reproductive toxicants pose a grave risk to the human health due to their unlimited use in consumer plastic industry. Detection of phthalates is strictly laboratory based time consuming and expensive process and requires expertise of highly qualified and skilled professionals. We present a real time, non-invasive, label free rapid detection technique to quantify phthalates' presence in deionized water and fruit juices. Electrochemical impedance spectroscopy (EIS) technique applied to a novel planar inter-digital (ID) capacitive sensor plays a vital role to explore the presence of phthalate esters in bulk fluid media. The ID sensor with multiple sensing gold electrodes was fabricated on silicon substrate using micro-electromechanical system (MEMS) device fabrication technology. A thin film of parylene C polymer was coated as a passivation layer to enhance the capacitive sensing capabilities of the sensor and to reduce the magnitude of Faradic current flowing through the sensor. Various concentrations, 0.002ppm through to 2ppm of di (2-ethylhexyl) phthalate (DEHP) in deionized water, were exposed to the sensing system by dip testing method. Impedance spectra obtained was analysed to determine sample conductance which led to consequent evaluation of its dielectric properties. Electro-chemical impedance spectrum analyser algorithm was employed to model the experimentally obtained impedance spectra. Curve fitting technique was applied to deduce constant phase element (CPE) equivalent circuit based on Randle's equivalent circuit model. The sensing system was tested to detect different concentrations of DEHP in orange juice as a real world application. The result analysis indicated that our rapid testing technique is able to detect the presence of DEHP in all test samples distinctively.

Computer assisted diagnostic system in tumor radiography.

PubMed

Faisal, Ahmed; Parveen, Sharmin; Badsha, Shahriar; Sarwar, Hasan; Reza, Ahmed Wasif

2013-06-01

An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

Method of Identifying a Base in a Nucleic Acid

DOEpatents

Fodor, Stephen P. A.; Lipshutz, Robert J.; Huang, Xiaohua

1999-01-01

Devices and techniques for hybridization of nucleic acids and for determining the sequence of nucleic acids. Arrays of nucleic acids are formed by techniques, preferably high resolution, light-directed techniques. Positions of hybridization of a target nucleic acid are determined by, e.g., epifluorescence microscopy. Devices and techniques are proposed to determine the sequence of a target nucleic acid more efficiently and more quickly through such synthesis and detection techniques.

Identifying a base in a nucleic acid

DOEpatents

Fodor, Stephen P. A.; Lipshutz, Robert J.; Huang, Xiaohua

2005-02-08

Devices and techniques for hybridization of nucleic acids and for determining the sequence of nucleic acids. Arrays of nucleic acids are formed by techniques, preferably high resolution, light-directed techniques. Positions of hybridization of a target nucleic acid are determined by, e.g., epifluorescence microscopy. Devices and techniques are proposed to determine the sequence of a target nucleic acid more efficiently and more quickly through such synthesis and detection techniques.

A comparison of line enhancement techniques: applications to guide-wire detection and respiratory motion tracking

NASA Astrophysics Data System (ADS)

Bismuth, Vincent; Vancamberg, Laurence; Gorges, Sébastien

2009-02-01

During interventional radiology procedures, guide-wires are usually inserted into the patients vascular tree for diagnosis or healing purpose. These procedures are monitored with an Xray interventional system providing images of the interventional devices navigating through the patient's body. The automatic detection of such tools by image processing means has gained maturity over the past years and enables applications ranging from image enhancement to multimodal image fusion. Sophisticated detection methods are emerging, which rely on a variety of device enhancement techniques. In this article we reviewed and classified these techniques into three families. We chose a state of the art approach in each of them and built a rigorous framework to compare their detection capability and their computational complexity. Through simulations and the intensive use of ROC curves we demonstrated that the Hessian based methods are the most robust to strong curvature of the devices and that the family of rotated filters technique is the most suited for detecting low CNR and low curvature devices. The steerable filter approach demonstrated less interesting detection capabilities and appears to be the most expensive one to compute. Finally we demonstrated the interest of automatic guide-wire detection on a clinical topic: the compensation of respiratory motion in multimodal image fusion.

Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

PubMed

Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

2016-04-07

Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity. Copyright © 2016 Elsevier B.V. All rights reserved.

Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases.

PubMed

Ahmed, Towfiq; Haraldsen, Jason T; Rehr, John J; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V

2014-03-28

Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new 'multi-point cross-correlation' technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.

Detection of abrupt changes in dynamic systems

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1984-01-01

Some of the basic ideas associated with the detection of abrupt changes in dynamic systems are presented. Multiple filter-based techniques and residual-based method and the multiple model and generalized likelihood ratio methods are considered. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.

Laser desorption mass spectrometry for molecular diagnosis

NASA Astrophysics Data System (ADS)

Chen, C. H. Winston; Taranenko, N. I.; Zhu, Y. F.; Allman, S. L.; Tang, K.; Matteson, K. J.; Chang, L. Y.; Chung, C. N.; Martin, Steve; Haff, Lawrence

1996-04-01

Laser desorption mass spectrometry has been used for molecular diagnosis of cystic fibrosis. Both 3-base deletion and single-base point mutation have been successfully detected by clinical samples. This new detection method can possibly speed up the diagnosis by one order of magnitude in the future. It may become a new biotechnology technique for population screening of genetic disease.

Assessing the Effectiveness of Statistical Classification Techniques in Predicting Future Employment of Participants in the Temporary Assistance for Needy Families Program

ERIC Educational Resources Information Center

Montoya, Isaac D.

2008-01-01

Three classification techniques (Chi-square Automatic Interaction Detection [CHAID], Classification and Regression Tree [CART], and discriminant analysis) were tested to determine their accuracy in predicting Temporary Assistance for Needy Families program recipients' future employment. Technique evaluation was based on proportion of correctly…

Recent technological advancements in tuberculosis diagnostics - A review.

PubMed

Gupta, Shagun; Kakkar, Vipan

2018-09-15

Early diagnosis and on-time effective treatment are indispensable for Tuberculosis (TB) control - a life threatening infectious communicable disease. The conventional techniques for diagnosing TB normally take two to three weeks. This delay in diagnosis and further increase in detection complexity due to the emerging risks of XDR-TB (Extensively drug Resistant-TB) and MDR-TB (Multidrug Resistant-TB) are evoking interest of researchers in the field of developing rapid TB detection techniques such as biosensing and other point-of-care (POC) techniques. Biosensing technologies along with the collaboration with nanotechnology have enormous potential to boost the MTB detection and for overall management in clinical diagnosis. A diverse range of portable, sensitive and rapid biosensors based on different signal transducer principles and with different biomarkers detection capabilities have been developed for TB detection in the early stages. Further, a lot of progress has been achieved over the years in developing various point-of-care diagnostic tools including non-molecular methods and molecular techniques. The objective of this study is to present a succinct review of the available TB detection techniques that are either in use or under development. The focus of this review is on the current developments occurred in nano-biosensing technologies. A synopsis of ameliorations in different non-molecular diagnostic tools and progress in the field of molecular techniques along with the role of emerging Lab-on-Chip technology for diagnosing and mitigating the TB consequences have also been presented. Copyright © 2018 Elsevier B.V. All rights reserved.

Hydrogeology from 10,000 ft below: lessons learned in applying pulse testing for leakage detection in a carbon sequestration formation

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Lu, J.; Hovorka, S. D.; Freifeld, B. M.; Islam, A.

2015-12-01

Monitoring techniques capable of deep subsurface detection are desirable for early warning and leakage pathway identification in geologic carbon storage formations. This work investigates the feasibility of a leakage detection technique based on pulse testing, which is a traditional hydrogeological characterization tool. In pulse testing, the monitoring reservoir is stimulated at a fixed frequency and the acquired pressure perturbation signals are analyzed in the frequency domain to detect potential deviations in the reservoir's frequency domain response function. Unlike traditional time-domain analyses, the frequency-domain analysis aims to minimize the interference of reservoir noise by imposing coded injection patterns such that the reservoir responses to injection can be uniquely determined. We have established the theoretical basis of the approach in previous work. Recently, field validation of this pressure-based, leakage detection technique was conducted at a CO2-EOR site located in Mississippi, USA. During the demonstration, two sets of experiments were performed using 90-min and 150-min pulsing periods, for both with and without leak scenarios. Because of the lack of pre-existing leakage pathways, artificial leakage CO2 was simulated by rate-controlled venting from one of the monitoring wells. Our results show that leakage events caused a significant deviation in the amplitude of the frequency response function, indicating that pulse testing may be used as a cost-effective monitoring technique with a strong potential for automation.

Innovative smart micro sensors for Army weaponry applications

NASA Astrophysics Data System (ADS)

Ruffin, Paul B.; Brantley, Christina; Edwards, Eugene

2008-03-01

Micro sensors offer the potential solution to cost, size, and weight issues associated with smart networked sensor systems designed for environmental/missile health monitoring and rocket out-gassing/fuel leak detection, as well as situational awareness on the battlefield. In collaboration with the University of Arkansas (Fayetteville), University of Alabama (Tuscaloosa and Birmingham), Alabama A&M University (Normal), and Streamline Automation (Huntsville, AL), scientists and engineers at the Army Aviation & Missile Research, Development, and Engineering Center (AMRDEC) are investigating several nano-based technologies to solve the problem of sensing extremely small levels of toxic gases associated with both chemical warfare agents (in air and liquids) and potential rocket motor leaks. Innovative techniques are being devised to adapt voltammetry, which is a well established technique for the detection and quantification of substances dissolved in liquids, to low-cost micro sensors for detecting airborne chemical agents and potential missile propellant leakages. In addition, a surface enhanced Raman scattering (SERS) technique, which enhances Raman scattered light by excitation of surface plasmons on nanoporous metal surfaces (nanospheres), is being investigated to develop novel smart sensors for the detection of chemical agents (including rocket motor out-gassing) and potential detection of home-made explosive devices. In this paper, results are delineated that are associated with experimental studies, which are conducted for the aforementioned cases and for several other nano-based technology approaches. The design challenges of each micro sensor technology approach are discussed. Finally, a comparative analysis of the various innovative micro-sensor techniques is provided.

Consistent detection and identification of individuals in a large camera network

NASA Astrophysics Data System (ADS)

Colombo, Alberto; Leung, Valerie; Orwell, James; Velastin, Sergio A.

2007-10-01

In the wake of an increasing number of terrorist attacks, counter-terrorism measures are now a main focus of many research programmes. An important issue for the police is the ability to track individuals and groups reliably through underground stations, and in the case of post-event analysis, to be able to ascertain whether specific individuals have been at the station previously. While there exist many motion detection and tracking algorithms, the reliable deployment of them in a large network is still ongoing research. Specifically, to track individuals through multiple views, on multiple levels and between levels, consistent detection and labelling of individuals is crucial. In view of these issues, we have developed a change detection algorithm to work reliably in the presence of periodic movements, e.g. escalators and scrolling advertisements, as well as a content-based retrieval technique for identification. The change detection technique automatically extracts periodically varying elements in the scene using Fourier analysis, and constructs a Markov model for the process. Training is performed online, and no manual intervention is required, making this system suitable for deployment in large networks. Experiments on real data shows significant improvement over existing techniques. The content-based retrieval technique uses MPEG-7 descriptors to identify individuals. Given the environment under which the system operates, i.e. at relatively low resolution, this approach is suitable for short timescales. For longer timescales, other forms of identification such as gait, or if the resolution allows, face recognition, will be required.

Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation

PubMed Central

Alacid, Beatriz

2018-01-01

This work presents a method for oil-spill detection on Spanish coasts using aerial Side-Looking Airborne Radar (SLAR) images, which are captured using a Terma sensor. The proposed method uses grayscale image processing techniques to identify the dark spots that represent oil slicks on the sea. The approach is based on two steps. First, the noise regions caused by aircraft movements are detected and labeled in order to avoid the detection of false-positives. Second, a segmentation process guided by a map saliency technique is used to detect image regions that represent oil slicks. The results show that the proposed method is an improvement on the previous approaches for this task when employing SLAR images. PMID:29316716

Fast iterative censoring CFAR algorithm for ship detection from SAR images

NASA Astrophysics Data System (ADS)

Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

2017-11-01

Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

Francisella tularensis detection using magnetic labels and a magnetic biosensor based on frequency mixing

NASA Astrophysics Data System (ADS)

Meyer, Martin H. F.; Krause, Hans-Joachim; Hartmann, Markus; Miethe, Peter; Oster, Jürgen; Keusgen, Michael

2007-04-01

A biosensor that uses resonant coils with a special frequency-mixing technique and magnetic beads as detectable labels has been established for the detection of Francisella tularensis, the causative agent for tularemia. The detection principle is based on a sandwich immunoassay using an anti-Ft antibody for immunofiltration immobilized to ABICAP ® polyethylene filters, and biotinylated with streptavidin-coated magnetic beads as labels. The linear detection range of this biosensor was found to be 10 4-10 6 cfu F. tularensis lipopolysaccharide (LPS) per ml. Tested sample matrices were physiological PBS buffer and rabbit serum.

Instrumentation development for drug detection on the breath

DOT National Transportation Integrated Search

1972-09-01

Based on a survey of candidate analytical methods, mass spectrometry was identified as a promising technique for drug detection on the breath. To demonstrate its capabilities, an existing laboratory mass spectrometer was modified by the addition of a...

Detecting Weak Spectral Lines in Interferometric Data through Matched Filtering

NASA Astrophysics Data System (ADS)

Loomis, Ryan A.; Öberg, Karin I.; Andrews, Sean M.; Walsh, Catherine; Czekala, Ian; Huang, Jane; Rosenfeld, Katherine A.

2018-04-01

Modern radio interferometers enable observations of spectral lines with unprecedented spatial resolution and sensitivity. In spite of these technical advances, many lines of interest are still at best weakly detected and therefore necessitate detection and analysis techniques specialized for the low signal-to-noise ratio (S/N) regime. Matched filters can leverage knowledge of the source structure and kinematics to increase sensitivity of spectral line observations. Application of the filter in the native Fourier domain improves S/N while simultaneously avoiding the computational cost and ambiguities associated with imaging, making matched filtering a fast and robust method for weak spectral line detection. We demonstrate how an approximate matched filter can be constructed from a previously observed line or from a model of the source, and we show how this filter can be used to robustly infer a detection significance for weak spectral lines. When applied to ALMA Cycle 2 observations of CH3OH in the protoplanetary disk around TW Hya, the technique yields a ≈53% S/N boost over aperture-based spectral extraction methods, and we show that an even higher boost will be achieved for observations at higher spatial resolution. A Python-based open-source implementation of this technique is available under the MIT license at http://github.com/AstroChem/VISIBLE.

Investigation on the thermographic detection of corrosion in RC structures

NASA Astrophysics Data System (ADS)

Tantele, Elia A.; Votsis, Renos A.; Kyriakides, Nicholas; Georgiou, Panagiota G.; Ioannou, Fotia G.

2017-09-01

Corrosion of the steel reinforcement is the main problem of reinforced concrete (RC) structures. Over the past decades, several methods have been developed aiming to detect the corrosion process early in order to minimise the structural damage and consequently the repairing costs. Emphasis was given in developing methods and techniques of non-destructive nature providing fast on-the-spot detection and covering large areas rather that concentrating on single locations. This study, investigates a non-destructive corrosion detection technique for reinforced concrete, which is based on infrared thermography and the difference in thermal characteristics of corroded and non-corroded steel rebars. The technique is based on the principle that corrosion products have poor heat conductivity, and they inhibit the diffusion of heat that is generated in the reinforcing bar due to heating. For the investigation RC specimens, have been constructed in the laboratory using embedded steel bars of different corrosion states. Afterward, one surface of the specimens was heated using an electric device while thermal images were captured at predefined time instants on the opposite surface with an IR camera. The test results showed a clear difference between the thermal characteristics of the corroded and the non-corroded samples, which demonstrates the potential of using thermography in corrosion detection in RC structures.

X-ray scatter imaging of hepatocellular carcinoma in a mouse model using nanoparticle contrast agents

DOE PAGES

Rand, Danielle; Derdak, Zoltan; Carlson, Rolf; ...

2015-10-29

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and is almost uniformly fatal. Current methods of detection include ultrasound examination and imaging by CT scan or MRI; however, these techniques are problematic in terms of sensitivity and specificity, and the detection of early tumors (<1 cm diameter) has proven elusive. Better, more specific, and more sensitive detection methods are therefore urgently needed. Here we discuss the application of a newly developed x-ray imaging technique called Spatial Frequency Heterodyne Imaging (SFHI) for the early detection of HCC. SFHI uses x-rays scattered by an object to form anmore » image and is more sensitive than conventional absorption-based x-radiography. We show that tissues labeled in vivo with gold nanoparticle contrast agents can be detected using SFHI. We also demonstrate that directed targeting and SFHI of HCC tumors in a mouse model is possible through the use of HCC-specific antibodies. As a result, the enhanced sensitivity of SFHI relative to currently available techniques enables the x-ray imaging of tumors that are just a few millimeters in diameter and substantially reduces the amount of nanoparticle contrast agent required for intravenous injection relative to absorption-based x-ray imaging.« less

Automated Detection of Clouds in Satellite Imagery

NASA Technical Reports Server (NTRS)

Jedlovec, Gary

2010-01-01

Many different approaches have been used to automatically detect clouds in satellite imagery. Most approaches are deterministic and provide a binary cloud - no cloud product used in a variety of applications. Some of these applications require the identification of cloudy pixels for cloud parameter retrieval, while others require only an ability to mask out clouds for the retrieval of surface or atmospheric parameters in the absence of clouds. A few approaches estimate a probability of the presence of a cloud at each point in an image. These probabilities allow a user to select cloud information based on the tolerance of the application to uncertainty in the estimate. Many automated cloud detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of clouds in both day and night imagery. Visible channels are quite effective in detecting clouds during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. Cloud detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night cloud detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each cloud test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle.

Detrecting and Locating Partial Discharges in Transformers

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

Shourbaji, A.; Richards, R.; Kisner, R. A.

A collaborative research between the Oak Ridge National Laboratory (ORNL), the American Electric Power (AEP), the Tennessee Valley Authority (TVA), and the State of Ohio Energy Office (OEO) has been formed to conduct a feasibility study to detect and locate partial discharges (PDs) inside large transformers. The success of early detection of the PDs is necessary to avoid costly catastrophic failures that can occur if the process of PD is ignored. The detection method under this research is based on an innovative technology developed by ORNL researchers using optical methods to sense the acoustical energy produced by the PDs. ORNLmore » researchers conducted experimental studies to detect PD using an optical fiber as an acoustic sensor capable of detecting acoustical disturbances at any point along its length. This technical approach also has the potential to locate the point at which the PD was sensed within the transformer. Several optical approaches were experimentally investigated, including interferometric detection of acoustical disturbances along the sensing fiber, light detection and ranging (LIDAR) techniques using frequency modulation continuous wave (FMCW), frequency modulated (FM) laser with a multimode fiber, FM laser with a single mode fiber, and amplitude modulated (AM) laser with a multimode fiber. The implementation of the optical fiber-based acoustic measurement technique would include installing a fiber inside a transformer allowing real-time detection of PDs and determining their locations. The fibers are nonconductive and very small (core plus cladding are diameters of 125 μm for single-mode fibers and 230 μm for multimode fibers). The research identified the capabilities and limitations of using optical technology to detect and locate sources of acoustical disturbances such as in PDs in large transformers. Amplitude modulation techniques showed the most promising results and deserve further research to better quantify the technique’s sensitivity and its ability to characterize a PD event. Other sensing techniques have been also identified, such as the wavelength shifting fiber optics and custom fabricated fibers with special coatings.« less

Methods for automatic detection of artifacts in microelectrode recordings.

PubMed

Bakštein, Eduard; Sieger, Tomáš; Wild, Jiří; Novák, Daniel; Schneider, Jakub; Vostatek, Pavel; Urgošík, Dušan; Jech, Robert

2017-10-01

Extracellular microelectrode recording (MER) is a prominent technique for studies of extracellular single-unit neuronal activity. In order to achieve robust results in more complex analysis pipelines, it is necessary to have high quality input data with a low amount of artifacts. We show that noise (mainly electromagnetic interference and motion artifacts) may affect more than 25% of the recording length in a clinical MER database. We present several methods for automatic detection of noise in MER signals, based on (i) unsupervised detection of stationary segments, (ii) large peaks in the power spectral density, and (iii) a classifier based on multiple time- and frequency-domain features. We evaluate the proposed methods on a manually annotated database of 5735 ten-second MER signals from 58 Parkinson's disease patients. The existing methods for artifact detection in single-channel MER that have been rigorously tested, are based on unsupervised change-point detection. We show on an extensive real MER database that the presented techniques are better suited for the task of artifact identification and achieve much better results. The best-performing classifiers (bagging and decision tree) achieved artifact classification accuracy of up to 89% on an unseen test set and outperformed the unsupervised techniques by 5-10%. This was close to the level of agreement among raters using manual annotation (93.5%). We conclude that the proposed methods are suitable for automatic MER denoising and may help in the efficient elimination of undesirable signal artifacts. Copyright © 2017 Elsevier B.V. All rights reserved.

Acoustic Emission Beamforming for Detection and Localization of Damage

NASA Astrophysics Data System (ADS)

Rivey, Joshua Callen

The aerospace industry is a constantly evolving field with corporate manufacturers continually utilizing innovative processes and materials. These materials include advanced metallics and composite systems. The exploration and implementation of new materials and structures has prompted the development of numerous structural health monitoring and nondestructive evaluation techniques for quality assurance purposes and pre- and in-service damage detection. Exploitation of acoustic emission sensors coupled with a beamforming technique provides the potential for creating an effective non-contact and non-invasive monitoring capability for assessing structural integrity. This investigation used an acoustic emission detection device that employs helical arrays of MEMS-based microphones around a high-definition optical camera to provide real-time non-contact monitoring of inspection specimens during testing. The study assessed the feasibility of the sound camera for use in structural health monitoring of composite specimens during tensile testing for detecting onset of damage in addition to nondestructive evaluation of aluminum inspection plates for visualizing stress wave propagation in structures. During composite material monitoring, the sound camera was able to accurately identify the onset and location of damage resulting from large amplitude acoustic feedback mechanisms such as fiber breakage. Damage resulting from smaller acoustic feedback events such as matrix failure was detected but not localized to the degree of accuracy of larger feedback events. Findings suggest that beamforming technology can provide effective non-contact and non-invasive inspection of composite materials, characterizing the onset and the location of damage in an efficient manner. With regards to the nondestructive evaluation of metallic plates, this remote sensing system allows us to record wave propagation events in situ via a single-shot measurement. This is a significant improvement over the conventional wave propagation tracking technique based on laser doppler vibrometry that requires synchronization of data acquired from numerous excitations and measurements. The proposed technique can be used to characterize and localize damage by detecting the scattering, attenuation, and reflections of stress waves resulting from damage and defects. These studies lend credence to the potential development of new SHM/NDE techniques based on acoustic emission beamforming for characterizing a wide spectrum of damage modes in next-generation materials and structures without the need for mounted contact sensors.

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

PubMed

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

2010-06-01

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

A parameter selection for Raman spectroscopy-based detection of chemical contaminants in food powders

USDA-ARS?s Scientific Manuscript database

Raman spectroscopy technique has proven to be a reliable method for detection of chemical contaminants in food ingredients and products. To detect each contaminant particle in a food sample, it is important to determine the effective depth of penetration of laser through the food sample and the corr...

Multi-Sectional Views Textural Based SVM for MS Lesion Segmentation in Multi-Channels MRIs

PubMed Central

Abdullah, Bassem A; Younis, Akmal A; John, Nigel M

2012-01-01

In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classification is done on each of the axial, sagittal and coronal sectional brain view independently and the resultant segmentations are aggregated to provide more accurate output segmentation. The main contribution of the proposed technique described in this paper is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional view segmentation to produce verified segmentation. The proposed textural-based SVM technique was evaluated using three simulated datasets and more than fifty real MRI datasets. The results were compared with state of the art methods. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI. PMID:22741026

Nanotechnology: a promising method for oral cancer detection and diagnosis.

PubMed

Chen, Xiao-Jie; Zhang, Xue-Qiong; Liu, Qi; Zhang, Jing; Zhou, Gang

2018-06-11

Oral cancer is a common and aggressive cancer with high morbidity, mortality, and recurrence rate globally. Early detection is of utmost importance for cancer prevention and disease management. Currently, tissue biopsy remains the gold standard for oral cancer diagnosis, but it is invasive, which may cause patient discomfort. The application of traditional noninvasive methods-such as vital staining, exfoliative cytology, and molecular imaging-is limited by insufficient sensitivity and specificity. Thus, there is an urgent need for exploring noninvasive, highly sensitive, and specific diagnostic techniques. Nano detection systems are known as new emerging noninvasive strategies that bring the detection sensitivity of biomarkers to nano-scale. Moreover, compared to current imaging contrast agents, nanoparticles are more biocompatible, easier to synthesize, and able to target specific surface molecules. Nanoparticles generate localized surface plasmon resonances at near-infrared wavelengths, providing higher image contrast and resolution. Therefore, using nano-based techniques can help clinicians to detect and better monitor diseases during different phases of oral malignancy. Here, we review the progress of nanotechnology-based methods in oral cancer detection and diagnosis.

Door detection in images based on learning by components

NASA Astrophysics Data System (ADS)

Cicirelli, Grazia; D'Orazio, Tiziana; Ancona, Nicola

2001-10-01

In this paper we present a vision-based technique for detecting targets of the environment which has to be reached by an autonomous mobile robot during its navigational task. The targets the robot has to reach are the doors of our office building. Color and shape information are used as identifying features for detecting principal components of the door. In fact in images the door can appear of different dimensions depending on the attitude of the robot with respect to the door, therefore detection of the door is performed by detecting its most significant components in the image. Positive and negative examples, in form of image patterns, are manually selected from real images for training two neural classifiers in order to recognize the single components. Each classifier has been realized by a feed-forward neural network with one hidden layer and sigmoid activation function. Moreover for selecting negative examples, relevant for the problem at hand, a bootstrap technique has been used during the training process. Finally the detecting system has been applied to several test real images for evaluating its performance.

Single molecule transistor based nanopore for the detection of nicotine

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

Ray, S. J., E-mail: ray.sjr@gmail.com

A nanopore based detection methodology was proposed and investigated for the detection of Nicotine. This technique uses a Single Molecular Transistor working as a nanopore operational in the Coulomb Blockade regime. When the Nicotine molecule is pulled through the nanopore area surrounded by the Source(S), Drain (D), and Gate electrodes, the charge stability diagram can detect the presence of the molecule and is unique for a specific molecular structure. Due to the weak coupling between the different electrodes which is set by the nanopore size, the molecular energy states stay almost unaffected by the electrostatic environment that can be realisedmore » from the charge stability diagram. Identification of different orientation and position of the Nicotine molecule within the nanopore area can be made from specific regions of overlap between different charge states on the stability diagram that could be used as an electronic fingerprint for detection. This method could be advantageous and useful to detect the presence of Nicotine in smoke which is usually performed using chemical chromatography techniques.« less

Independent component analysis (ICA) and self-organizing map (SOM) approach to multidetection system for network intruders

NASA Astrophysics Data System (ADS)

Abdi, Abdi M.; Szu, Harold H.

2003-04-01

With the growing rate of interconnection among computer systems, network security is becoming a real challenge. Intrusion Detection System (IDS) is designed to protect the availability, confidentiality and integrity of critical network information systems. Today"s approach to network intrusion detection involves the use of rule-based expert systems to identify an indication of known attack or anomalies. However, these techniques are less successful in identifying today"s attacks. Hackers are perpetually inventing new and previously unanticipated techniques to compromise information infrastructure. This paper proposes a dynamic way of detecting network intruders on time serious data. The proposed approach consists of a two-step process. Firstly, obtaining an efficient multi-user detection method, employing the recently introduced complexity minimization approach as a generalization of a standard ICA. Secondly, we identified unsupervised learning neural network architecture based on Kohonen"s Self-Organizing Map for potential functional clustering. These two steps working together adaptively will provide a pseudo-real time novelty detection attribute to supplement the current intrusion detection statistical methodology.

New Researches and Application Progress of Commonly Used Optical Molecular Imaging Technology

PubMed Central

Chen, Zhi-Yi; Yang, Feng; Lin, Yan; Zhou, Qiu-Lan; Liao, Yang-Ying

2014-01-01

Optical molecular imaging, a new medical imaging technique, is developed based on genomics, proteomics and modern optical imaging technique, characterized by non-invasiveness, non-radiativity, high cost-effectiveness, high resolution, high sensitivity and simple operation in comparison with conventional imaging modalities. Currently, it has become one of the most widely used molecular imaging techniques and has been applied in gene expression regulation and activity detection, biological development and cytological detection, drug research and development, pathogenesis research, pharmaceutical effect evaluation and therapeutic effect evaluation, and so forth, This paper will review the latest researches and application progresses of commonly used optical molecular imaging techniques such as bioluminescence imaging and fluorescence molecular imaging. PMID:24696850

Food Safety Evaluation Based on Near Infrared Spectroscopy and Imaging: A Review.

PubMed

Fu, Xiaping; Ying, Yibin

2016-08-17

In recent years, due to the increasing consciousness of food safety and human health, much progress has been made in developing rapid and nondestructive techniques for the evaluation of food hazards, food authentication, and traceability. Near infrared (NIR) spectroscopy and imaging techniques have gained wide acceptance in many fields because of their advantages over other analytical techniques. Following a brief introduction of NIR spectroscopy and imaging basics, this review mainly focuses on recent NIR spectroscopy and imaging applications for food safety evaluation, including (1) chemical hazards detection; (2) microbiological hazards detection; (3) physical hazards detection; (4) new technology-induced food safety concerns; and (5) food traceability. The review shows NIR spectroscopy and imaging to be effective tools that will play indispensable roles for food safety evaluation. In addition, on-line/real-time applications of these techniques promise to be a huge growth field in the near future.

Spectroelectrochemical detection of microRNA-155 based on functional RNA immobilization onto ITO/GNP nanopattern.

PubMed

Mohammadniaei, Mohsen; Yoon, Jinho; Lee, Taek; Choi, Jeong-Woo

2018-05-20

We fabricated a microRNA biosensor using the combination of surface enhanced Raman spectroscopy (SERS) and electrochemical (EC) techniques. For the first time, the weaknesses of each techniques for microRNA detection was compensated by the other ones to give rise to the specific and wide-range detection of miR-155. A single stranded 3' methylene blue (MB) and 5' thiol-modified RNA (MB-ssRNA-SH) was designed to detect the target miR-155 and immobilized onto the gold nanoparticle-modified ITO (ITO/GNP). Upon the invasion of target strand, the double-stranded RNA transformed rapidly to an upright structure resulting in a notable decrease in SERS and redox signals of the MB. For the first time, by combination of SERS and EC techniques in a single platform we extended the dynamic range of both techniques from 10 pM to 450 nM (SERS: 10 pM-5 nM and EC: 5 nM-450 nM). As well, the SERS technique improved the detection limit of the EC method from 100 pM to 100 fM, while the EC method covered single-mismatch detection which was the SERS deficiency. The fabricated single-step biosensor possessing a good capability of miRNA detection in human serum, could be employed throughout the broad ranges of biomedical and bioelectronics applications. Copyright © 2018 Elsevier B.V. All rights reserved.

An automated cross-correlation based event detection technique and its application to surface passive data set

USGS Publications Warehouse

Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

2013-01-01

In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

Directional analysis and filtering for dust storm detection in NOAA-AVHRR imagery

NASA Astrophysics Data System (ADS)

Janugani, S.; Jayaram, V.; Cabrera, S. D.; Rosiles, J. G.; Gill, T. E.; Rivera Rivera, N.

2009-05-01

In this paper, we propose spatio-spectral processing techniques for the detection of dust storms and automatically finding its transport direction in 5-band NOAA-AVHRR imagery. Previous methods that use simple band math analysis have produced promising results but have drawbacks in producing consistent results when low signal to noise ratio (SNR) images are used. Moreover, in seeking to automate the dust storm detection, the presence of clouds in the vicinity of the dust storm creates a challenge in being able to distinguish these two types of image texture. This paper not only addresses the detection of the dust storm in the imagery, it also attempts to find the transport direction and the location of the sources of the dust storm. We propose a spatio-spectral processing approach with two components: visualization and automation. Both approaches are based on digital image processing techniques including directional analysis and filtering. The visualization technique is intended to enhance the image in order to locate the dust sources. The automation technique is proposed to detect the transport direction of the dust storm. These techniques can be used in a system to provide timely warnings of dust storms or hazard assessments for transportation, aviation, environmental safety, and public health.

Applications of hyperspectral imaging in chicken meat safety and quality detection and evaluation: a review.

PubMed

Xiong, Zhenjie; Xie, Anguo; Sun, Da-Wen; Zeng, Xin-An; Liu, Dan

2015-01-01

Currently, the issue of food safety and quality is a great public concern. In order to satisfy the demands of consumers and obtain superior food qualities, non-destructive and fast methods are required for quality evaluation. As one of these methods, hyperspectral imaging (HSI) technique has emerged as a smart and promising analytical tool for quality evaluation purposes and has attracted much interest in non-destructive analysis of different food products. With the main advantage of combining both spectroscopy technique and imaging technique, HSI technique shows a convinced attitude to detect and evaluate chicken meat quality objectively. Moreover, developing a quality evaluation system based on HSI technology would bring economic benefits to the chicken meat industry. Therefore, in recent years, many studies have been conducted on using HSI technology for the safety and quality detection and evaluation of chicken meat. The aim of this review is thus to give a detailed overview about HSI and focus on the recently developed methods exerted in HSI technology developed for microbiological spoilage detection and quality classification of chicken meat. Moreover, the usefulness of HSI technique for detecting fecal contamination and bone fragments of chicken carcasses are presented. Finally, some viewpoints on its future research and applicability in the modern poultry industry are proposed.

Field ion spectrometry: a new technology for cocaine and heroin detection

NASA Astrophysics Data System (ADS)

Carnahan, Byron L.; Day, Stephen; Kouznetsov, Viktor; Tarassov, Alexandre

1997-02-01

Field ion spectrometry, also known as transverse field compensation ion mobility spectrometry, is a new technique for trace gas analysis that can be applied to the detection of cocaine and heroin. Its principle is based on filtering ion species according to the functional dependence of their mobilities with electric field strength. Field ion spectrometry eliminates the gating electrodes needed in conventional IMS to pulse ions into the spectrometer; instead, ions are injected in to the spectrometer and reach the detector continuously, resulting in improved sensitivity. The technique enables analyses that are difficult with conventional constant field strength ion mobility spectrometers. We have shown that a filed ion spectrometer can selectively detect the vapors from cocaine and heroin emitted from both their base and hydrochloride forms. The estimated volumetric limits of detection are in the low pptv range, based on testing with standardized drug vapor generation systems. The spectrometer can detect cocaine base in the vapor phase, at concentrations well below its estimated 100 pptv vapor pressure equivalent at 20 degrees C. This paper describes the underlying principles of field ion spectrometry in relation to narcotic drug detection, and recent results obtained for cocaine and heroin. The work has been sponsored in part by the United States Advanced Research Projects Agency under contract DAAB10-95C-0004, for the DOD Counterdrug Technology Development Program.

Loop-mediated isothermal amplification (LAMP) as an alternative to PCR: A rapid on-site detection of gene doping.

PubMed

Salamin, Olivier; Kuuranne, Tiia; Saugy, Martial; Leuenberger, Nicolas

2017-11-01

Innovation in medical research has been diverted at multiple occasions to enhance human performance. The predicted great progress in gene therapy has raised some concerns regarding its misuse in the world of sports (gene doping) for several years now. Even though there is no evidence that gene doping has ever been used in sports, the continuous improvement of gene therapy techniques increases the likelihood of abuse. Therefore, since 2004, efforts have been invested by the anti-doping community and WADA for the development of detection methods. Several nested PCR and qPCR-based strategies exploiting the absence of introns in the transgenic DNA have been proposed for the long-term detection of transgene in blood. Despite their great sensitivity, those protocols are hampered by limitations of the techniques that can be cumbersome and costly. The purpose of this perspective is to describe a new approach based on loop-mediated isothermal amplification (LAMP) for the detection of gene doping. This protocol enables a rapid and simple method to amplify nucleic acids with a high sensitivity and specificity and with a simple visual detection of the results. LAMP is already being used in clinical application for the detection of viruses or mutations. Therefore, this technique has the potential to be further developed for the detection of foreign genetic material in elite athletes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Air Coupled Acoustic Thermography (ACAT) Inspection Technique

NASA Technical Reports Server (NTRS)

Zalameda, Joseph; Winfree, William P.; Yost, William T.

2007-01-01

The scope of this effort is to determine the viability of a new heating technique using a noncontact acoustic excitation source. Because of low coupling between air and the structure, a synchronous detection method is employed. Any reduction in the out of plane stiffness improves the acoustic coupling efficiency and as a result, defective areas have an increase in temperature relative to the surrounding area. Hence a new measurement system, based on air-coupled acoustic energy and synchronous detection is presented. An analytical model of a clamped circular plate is given, experimentally tested, and verified. Repeatability confirms the technique with a measurement uncertainty of plus or minus 6.2 percent. The range of frequencies used was 800-2,000 Hertz. Acoustic excitation and consequent thermal detection of flaws in a helicopter blade is examined and results indicate that air coupled acoustic excitation enables the detection of core damage in sandwich honeycomb structures.

Imitation-tumor targeting based on continuous-wave near-infrared tomography.

PubMed

Liu, Dan; Liu, Xin; Zhang, Yan; Wang, Qisong; Lu, Jingyang; Sun, Jinwei

2017-12-01

Continuous-wave Near-Infrared (NIR) optical spectroscopy has shown great diagnostic capability in the early tumor detection with advantages of low-cost, portable, non-invasive, and non-radiative. In this paper, Modified Lambert-Beer Theory is deployed to address the low-resolution issues of the NIR technique and to design the tumor detecting and imaging system. Considering that tumor tissues have features such as high blood flow and hypoxia, the proposed technique can detect the location, size, and other information of the tumor tissues by comparing the absorbance between pathological and normal tissues. Finally, the tumor tissues can be imaged through tomographic method. The simulation experiments prove that the proposed technique and designed system can efficiently detect the tumor tissues, achieving imaging precision within 1 mm. The work of the paper has shown great potential in the diagnosis of tumor close to body surface.

Historical Techniques of Lie Detection

PubMed Central

Vicianova, Martina

2015-01-01

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

Multirobot autonomous landmine detection using distributed multisensor information aggregation

NASA Astrophysics Data System (ADS)

Jumadinova, Janyl; Dasgupta, Prithviraj

2012-06-01

We consider the problem of distributed sensor information fusion by multiple autonomous robots within the context of landmine detection. We assume that different landmines can be composed of different types of material and robots are equipped with different types of sensors, while each robot has only one type of landmine detection sensor on it. We introduce a novel technique that uses a market-based information aggregation mechanism called a prediction market. Each robot is provided with a software agent that uses sensory input of the robot and performs calculations of the prediction market technique. The result of the agent's calculations is a 'belief' representing the confidence of the agent in identifying the object as a landmine. The beliefs from different robots are aggregated by the market mechanism and passed on to a decision maker agent. The decision maker agent uses this aggregate belief information about a potential landmine and makes decisions about which other robots should be deployed to its location, so that the landmine can be confirmed rapidly and accurately. Our experimental results show that, for identical data distributions and settings, using our prediction market-based information aggregation technique increases the accuracy of object classification favorably as compared to two other commonly used techniques.

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

Post-processing for improving hyperspectral anomaly detection accuracy

NASA Astrophysics Data System (ADS)

Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

2015-10-01

Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

Microwave magnetic field detection based on Cs vapor cell in free space

NASA Astrophysics Data System (ADS)

Liu, Xiaochi; Jiang, Zhiyuan; Qu, Jifeng; Hou, Dong; Huang, Xianhe; Sun, Fuyu

2018-06-01

In this study, we demonstrate the direct measurement of a microwave (MW) magnetic field through the detection of atomic Rabi resonances with Cs vapor cells in a free-space low-Q cavity. The line shape (amplitude and linewidth) of detected Rabi resonances is investigated versus several experimental parameters such as the laser intensity, cell buffer gas pressure, and cell length. The specially designed low-Q cavity creates a suitable MW environment allowing easy testing of different vapor cells with distinct properties. Obtained results are analyzed to optimize the performances of a MW magnetic field sensor based on the present atom-based detection technique.

Failure detection and fault management techniques for flush airdata sensing systems

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

1992-01-01

Methods based on chi-squared analysis are presented for detecting system and individual-port failures in the high-angle-of-attack flush airdata sensing system on the NASA F-18 High Alpha Research Vehicle. The HI-FADS hardware is introduced, and the aerodynamic model describes measured pressure in terms of dynamic pressure, angle of attack, angle of sideslip, and static pressure. Chi-squared analysis is described in the presentation of the concept for failure detection and fault management which includes nominal, iteration, and fault-management modes. A matrix of pressure orifices arranged in concentric circles on the nose of the aircraft indicate the parameters which are applied to the regression algorithms. The sensing techniques are applied to the F-18 flight data, and two examples are given of the computed angle-of-attack time histories. The failure-detection and fault-management techniques permit the matrix to be multiply redundant, and the chi-squared analysis is shown to be useful in the detection of failures.

Detection and Length Estimation of Linear Scratch on Solid Surfaces Using an Angle Constrained Ant Colony Technique

NASA Astrophysics Data System (ADS)

Pal, Siddharth; Basak, Aniruddha; Das, Swagatam

In many manufacturing areas the detection of surface defects is one of the most important processes in quality control. Currently in order to detect small scratches on solid surfaces most of the industries working on material manufacturing rely on visual inspection primarily. In this article we propose a hybrid computational intelligence technique to automatically detect a linear scratch from a solid surface and estimate its length (in pixel unit) simultaneously. The approach is based on a swarm intelligence algorithm called Ant Colony Optimization (ACO) and image preprocessing with Wiener and Sobel filters as well as the Canny edge detector. The ACO algorithm is mostly used to compensate for the broken parts of the scratch. Our experimental results confirm that the proposed technique can be used for detecting scratches from noisy and degraded images, even when it is very difficult for conventional image processing to distinguish the scratch area from its background.

Behavior Knowledge Space-Based Fusion for Copy-Move Forgery Detection.

PubMed

Ferreira, Anselmo; Felipussi, Siovani C; Alfaro, Carlos; Fonseca, Pablo; Vargas-Munoz, John E; Dos Santos, Jefersson A; Rocha, Anderson

2016-07-20

The detection of copy-move image tampering is of paramount importance nowadays, mainly due to its potential use for misleading the opinion forming process of the general public. In this paper, we go beyond traditional forgery detectors and aim at combining different properties of copy-move detection approaches by modeling the problem on a multiscale behavior knowledge space, which encodes the output combinations of different techniques as a priori probabilities considering multiple scales of the training data. Afterwards, the conditional probabilities missing entries are properly estimated through generative models applied on the existing training data. Finally, we propose different techniques that exploit the multi-directionality of the data to generate the final outcome detection map in a machine learning decision-making fashion. Experimental results on complex datasets, comparing the proposed techniques with a gamut of copy-move detection approaches and other fusion methodologies in the literature show the effectiveness of the proposed method and its suitability for real-world applications.

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

NASA Astrophysics Data System (ADS)

Ghanbari, Teymoor; Samet, Haidar

2017-11-01

Monitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

Four-Wave-Mixing Approach to In Situ Detection of Nanoparticles

NASA Astrophysics Data System (ADS)

Gerakis, Alexandros; Yeh, Yao-Wen; Shneider, Mikhail N.; Mitrani, James M.; Stratton, Brentley C.; Raitses, Yevgeny

2018-01-01

We report on the development and experimental validation of a laser-based technique which uses coherent Rayleigh-Brillouin scattering (CRBS) to detect nanoparticles with characteristic sizes ranging from the atomic scale to tens of nanometers. This technique is aimed (nonexclusively) at the detection of nanoparticles produced by volumetric nanoparticle synthesis methods. Using CRBS, carbon nanoparticles of dimensions less than 10 nm and concentrations of 1010 cm-3 are detected in situ in a carbon arc discharge with graphite electrodes. This four-wave-mixing approach should enable advances in the understanding of nanoparticle growth that could potentially lead to improved modeling of the growth mechanisms, and thus to improve synthesis selectivity of nanoparticles and yield.

NQR: From imaging to explosives and drugs detection

NASA Astrophysics Data System (ADS)

Osán, Tristán M.; Cerioni, Lucas M. C.; Forguez, José; Ollé, Juan M.; Pusiol, Daniel J.

2007-02-01

The main aim of this work is to present an overview of the nuclear quadrupole resonance (NQR) spectroscopy capabilities for solid state imaging and detection of illegal substances, such as explosives and drugs. We briefly discuss the evolution of different NQR imaging techniques, in particular those involving spatial encoding which permit conservation of spectroscopic information. It has been shown that plastic explosives and other forbidden substances cannot be easily detected by means of conventional inspection techniques, such as those based on conventional X-ray technology. For this kind of applications, the experimental results show that the information inferred from NQR spectroscopy provides excellent means to perform volumetric and surface detection of dangerous explosive and drug compounds.

Quinone-based stable isotope probing for assessment of 13C substrate-utilizing bacteria

NASA Astrophysics Data System (ADS)

Kunihiro, Tadao; Katayama, Arata; Demachi, Toyoko; Veuger, Bart; Boschker, Henricus T. S.; van Oevelen, Dick

2015-04-01

In this study, we attempted to establish quinone-stable-isotope probing (SIP) technique to link substrate-utilizing bacterial group to chemotaxonomic group in bacterial community. To identify metabolically active bacterial group in various environments, SIP techniques combined with biomarkers have been widely utilized as an attractive method for environmental study. Quantitative approaches of the SIP technique have unique advantage to assess substrate-incorporation into bacteria. As a most major quantitative approach, SIP technique based on phospholipid-derived fatty acids (PLFA) have been applied to simultaneously assess substrate-incorporation rate into bacteria and microbial community structure. This approach is powerful to estimate the incorporation rate because of the high sensitivity due to the detection by a gas chromatograph-combustion interface-isotope ratio mass spectrometer (GC-c-IRMS). However, its phylogenetic resolution is limited by specificity of a compound-specific marker. We focused on respiratory quinone as a biomarker. Our previous study found a good correlation between concentrations of bacteria-specific PLFAs and quinones over several orders of magnitude in various marine sediments, and the quinone method has a higher resolution (bacterial phylum level) for resolving differences in bacterial community composition more than that of bacterial PLFA. Therefore, respiratory quinones are potentially good biomarkers for quantitative approaches of the SIP technique. The LC-APCI-MS method as molecular-mass based detection method for quinone was developed and provides useful structural information for identifying quinone molecular species in environmental samples. LC-MS/MS on hybrid triple quadrupole/linear ion trap, which enables to simultaneously identify and quantify compounds in a single analysis, can detect high molecular compounds with their isotope ions. Use of LC-MS/MS allows us to develop quinone-SIP based on molecular mass differences due to 13C abundance in the quinone. In this study, we verified carbon stable isotope of quinone compared with bulk carbon stable isotope of bacterial culture. Results indicated a good correlation between carbon stable isotope of quinone compared with bulk carbon stable isotope. However, our measurement conditions for detection of quinone isotope-ions incurred underestimation of 13C abundance in the quinone. The quinone-SIP technique needs further optimization for measurement conditions of LC-MS/MS.

Pattern-histogram-based temporal change detection using personal chest radiographs

NASA Astrophysics Data System (ADS)

Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

1999-05-01

An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

Compressed Sensing Techniques Applied to Ultrasonic Imaging of Cargo Containers.

PubMed

López, Yuri Álvarez; Lorenzo, José Ángel Martínez

2017-01-15

One of the key issues in the fight against the smuggling of goods has been the development of scanners for cargo inspection. X-ray-based radiographic system scanners are the most developed sensing modality. However, they are costly and use bulky sources that emit hazardous, ionizing radiation. Aiming to improve the probability of threat detection, an ultrasonic-based technique, capable of detecting the footprint of metallic containers or compartments concealed within the metallic structure of the inspected cargo, has been proposed. The system consists of an array of acoustic transceivers that is attached to the metallic structure-under-inspection, creating a guided acoustic Lamb wave. Reflections due to discontinuities are detected in the images, provided by an imaging algorithm. Taking into consideration that the majority of those images are sparse, this contribution analyzes the application of Compressed Sensing (CS) techniques in order to reduce the amount of measurements needed, thus achieving faster scanning, without compromising the detection capabilities of the system. A parametric study of the image quality, as a function of the samples needed in spatial and frequency domains, is presented, as well as the dependence on the sampling pattern. For this purpose, realistic cargo inspection scenarios have been simulated.

Compressed Sensing Techniques Applied to Ultrasonic Imaging of Cargo Containers

PubMed Central

Álvarez López, Yuri; Martínez Lorenzo, José Ángel

2017-01-01

One of the key issues in the fight against the smuggling of goods has been the development of scanners for cargo inspection. X-ray-based radiographic system scanners are the most developed sensing modality. However, they are costly and use bulky sources that emit hazardous, ionizing radiation. Aiming to improve the probability of threat detection, an ultrasonic-based technique, capable of detecting the footprint of metallic containers or compartments concealed within the metallic structure of the inspected cargo, has been proposed. The system consists of an array of acoustic transceivers that is attached to the metallic structure-under-inspection, creating a guided acoustic Lamb wave. Reflections due to discontinuities are detected in the images, provided by an imaging algorithm. Taking into consideration that the majority of those images are sparse, this contribution analyzes the application of Compressed Sensing (CS) techniques in order to reduce the amount of measurements needed, thus achieving faster scanning, without compromising the detection capabilities of the system. A parametric study of the image quality, as a function of the samples needed in spatial and frequency domains, is presented, as well as the dependence on the sampling pattern. For this purpose, realistic cargo inspection scenarios have been simulated. PMID:28098841

NBIT Program Phase I (2007-2010). Part 1, Chapters 1 Through 4

DTIC Science & Technology

2009-08-27

2 schematically shows the sample prepared before hydrothermal synthesis . The thin layer of Zn was convered to ZnO nanowires during hydrothermal ... Nanoparticle -Based Magnetically Amplified Surface Plasmon Resonance (Mag-SPR) Techniques; Jinwoo Cheon (Yonsei University, Korea) and A. Paul...Ion; Chapter 3 ? Ultra-Sensitive Biological Detection via Nanoparticle -Based Magnetically Amplified Surface Plasmon Resonance (Mag-SPR) Techniques

Steganalysis for Audio Data

DTIC Science & Technology

2006-03-31

from existing image steganography and steganalysis techniques, the overall objective of Task (b) is to design and implement audio steganography in...general design of the VoIP steganography algorithm is based on known LSB hiding techniques (used for example in StegHide (http...system. Nasir Memon et. al. described a steganalyzer based on image quality metrics [AMS03]. Basically, the main idea to detect steganography by

Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

PubMed

Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

2017-09-01

In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to combine the advantages brought forward by the proposed EWMA-GLRT fault detection chart with the KPCA model. Thus, it is used to enhance fault detection of the Cad System in E. coli model through monitoring some of the key variables involved in this model such as enzymes, transport proteins, regulatory proteins, lysine, and cadaverine. The results demonstrate the effectiveness of the proposed KPCA-based EWMA-GLRT method over Q , GLRT, EWMA, Shewhart, and moving window-GLRT methods. The detection performance is assessed and evaluated in terms of FAR, missed detection rates, and average run length (ARL 1 ) values.

Optical remote sensing and correlation of office equipment functional state and stress levels via power quality disturbances inefficiencies

NASA Astrophysics Data System (ADS)

Sternberg, Oren; Bednarski, Valerie R.; Perez, Israel; Wheeland, Sara; Rockway, John D.

2016-09-01

Non-invasive optical techniques pertaining to the remote sensing of power quality disturbances (PQD) are part of an emerging technology field typically dominated by radio frequency (RF) and invasive-based techniques. Algorithms and methods to analyze and address PQD such as probabilistic neural networks and fully informed particle swarms have been explored in industry and academia. Such methods are tuned to work with RF equipment and electronics in existing power grids. As both commercial and defense assets are heavily power-dependent, understanding electrical transients and failure events using non-invasive detection techniques is crucial. In this paper we correlate power quality empirical models to the observed optical response. We also empirically demonstrate a first-order approach to map household, office and commercial equipment PQD to user functions and stress levels. We employ a physics-based image and signal processing approach, which demonstrates measured non-invasive (remote sensing) techniques to detect and map the base frequency associated with the power source to the various PQD on a calibrated source.

Detection of adulteration in diesel and petrol by kerosene using SPR based fiber optic technique

NASA Astrophysics Data System (ADS)

Verma, Rajneesh K.; Suwalka, Payal; Yadav, Jatin

2018-07-01

In this paper we focused on the experimental investigations for fabricating a surface plasmon resonance (SPR) based fiber optic sensor for the detection of the extent of adulteration in petrochemicals: petrol and diesel by kerosene. Primarily it is observed that the refractive index of the petrol and diesel changes if we mix kerosene in it. The variation in refractive index is linear in nature. Utilizing the phenomenon of surface plasmon resonance in Krestchmann configuration on optical fiber, the percentage of adulteration in petrol and diesel is detected. The detection level of adulteration is quantified systematically for both the petrol and diesel. The study carried out here explores the possibility of utilizing SPR technique for the detection of the level of adulteration in petrochemicals. The suitability of the optical fiber for remote sensing and its immunity towards electromagnetic interaction makes this probe very useful for such endeavor. High sensitivity, easy construction and its portability, makes this study important in the development of SPR based optical fiber sensors for petrochemical industries. Apart from this various aspects of environment polluting hazardous/toxic gases as an emission product of automobile fuels has also been discussed.

Hybridization and sequencing of nucleic acids using base pair mismatches

DOEpatents

Fodor, Stephen P. A.; Lipshutz, Robert J.; Huang, Xiaohua

2001-01-01

Devices and techniques for hybridization of nucleic acids and for determining the sequence of nucleic acids. Arrays of nucleic acids are formed by techniques, preferably high resolution, light-directed techniques. Positions of hybridization of a target nucleic acid are determined by, e.g., epifluorescence microscopy. Devices and techniques are proposed to determine the sequence of a target nucleic acid more efficiently and more quickly through such synthesis and detection techniques.

Probe kit for identifying a base in a nucleic acid

DOEpatents

Fodor, Stephen P. A.; Lipshutz, Robert J.; Huang, Xiaohua

2001-01-01

Devices and techniques for hybridization of nucleic acids and for determining the sequence of nucleic acids. Arrays of nucleic acids are formed by techniques, preferably high resolution, light-directed techniques. Positions of hybridization of a target nucleic acid are determined by, e.g., epifluorescence microscopy. Devices and techniques are proposed to determine the sequence of a target nucleic acid more efficiently and more quickly through such synthesis and detection techniques.

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.

Confocal laser feedback tomography for skin cancer detection

PubMed Central

Mowla, Alireza; Du, Benjamin Wensheng; Taimre, Thomas; Bertling, Karl; Wilson, Stephen; Soyer, H. Peter; Rakić, Aleksandar D.

2017-01-01

Tomographic imaging of soft tissue such as skin has a potential role in cancer detection. The penetration of infrared wavelengths makes a confocal approach based on laser feedback interferometry feasible. We present a compact system using a semiconductor laser as both transmitter and receiver. Numerical and physical models based on the known optical properties of keratinocyte cancers were developed. We validated the technique on three phantoms containing macro-structural changes in optical properties. Experimental results were in agreement with numerical simulations and structural changes were evident which would permit discrimination of healthy tissue and tumour. Furthermore, cancer type discrimination was also able to be visualized using this imaging technique. PMID:28966845

Confocal laser feedback tomography for skin cancer detection.

PubMed

Mowla, Alireza; Du, Benjamin Wensheng; Taimre, Thomas; Bertling, Karl; Wilson, Stephen; Soyer, H Peter; Rakić, Aleksandar D

2017-09-01

Tomographic imaging of soft tissue such as skin has a potential role in cancer detection. The penetration of infrared wavelengths makes a confocal approach based on laser feedback interferometry feasible. We present a compact system using a semiconductor laser as both transmitter and receiver. Numerical and physical models based on the known optical properties of keratinocyte cancers were developed. We validated the technique on three phantoms containing macro-structural changes in optical properties. Experimental results were in agreement with numerical simulations and structural changes were evident which would permit discrimination of healthy tissue and tumour. Furthermore, cancer type discrimination was also able to be visualized using this imaging technique.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

NASA Astrophysics Data System (ADS)

Wang, Pan-Pan; Yu, Qiang; Hu, Yong-Jun; Miao, Chang-Xin

2017-11-01

Current research in broken rotor bar (BRB) fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estimation cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the frequencies of the fundamental and fault characteristic components with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

NASA Technical Reports Server (NTRS)

Smith, Phillip N.

1990-01-01

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements.

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique

PubMed Central

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-01-01

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system’s lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system’s ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection. PMID:29543733

Expanded Processing Techniques for EMI Systems

DTIC Science & Technology

2012-07-01

possible to perform better target detection using physics-based algorithms and the entire data set, rather than simulating a simpler data set and mapping...possible to perform better target detection using physics-based algorithms and the entire data set, rather than simulating a simpler data set and...54! Figure 4.25: Plots of simulated MetalMapper data for two oblate spheroidal targets

Rapid and sensitive phenotypic marker detection on breast cancer cells using surface-enhanced Raman scattering (SERS) imaging.

PubMed

Lee, Sangyeop; Chon, Hyangah; Lee, Jiyoung; Ko, Juhui; Chung, Bong Hyun; Lim, Dong Woo; Choo, Jaebum

2014-01-15

We report a surface-enhanced Raman scattering (SERS)-based cellular imaging technique to detect and quantify breast cancer phenotypic markers expressed on cell surfaces. This technique involves the synthesis of SERS nano tags consisting of silica-encapsulated hollow gold nanospheres (SEHGNs) conjugated with specific antibodies. Hollow gold nanospheres (HGNs) enhance SERS signal intensity of individual particles by localizing surface electromagnetic fields through pinholes in the hollow particle structures. This capacity to enhance imaging at the level of single molecules permits the use of HGNs to detect specific biological markers expressed in living cancer cells. In addition, silica encapsulation greatly enhances the stability of nanoparticles. Here we applied a SERS-based imaging technique using SEHGNs in the multiplex imaging of three breast cancer cell phenotypes. Expression of epidermal growth factor (EGF), ErbB2, and insulin-like growth factor-1 (IGF-1) receptors were assessed in the MDA-MB-468, KPL4 and SK-BR-3 human breast cancer cell lines. SERS imaging technology described here can be used to test the phenotype of a cancer cell and quantify proteins expressed on the cell surface simultaneously. Based on results, this technique may enable an earlier diagnosis of breast cancer than is currently possible and offer guidance in treatment. © 2013 Elsevier B.V. All rights reserved.

A system identification technique based on the random decrement signatures. Part 2: Experimental results

NASA Technical Reports Server (NTRS)

Bedewi, Nabih E.; Yang, Jackson C. S.

1987-01-01

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The results of an experiment conducted on an offshore platform scale model to verify the validity of the technique and to demonstrate its application in damage detection are presented.

An overview of landmine detection with emphasis on electromagnetic approaches

NASA Astrophysics Data System (ADS)

Das, Yogadhish

2003-04-01

Human suffering caused by antipersonnel landmines left over from previous conflicts has only recently received significant public exposure. However, considerable amount of research on how to detect and deal with buried landmines has been carried out at least since the second world war. The research has encompassed a wide range of technologies and large sums of money have been spent. Despite these efforts there is still no operationally satisfactory solution, especially to the detection problem. This lack of success is attributable to the difficulty of the problem and the high degree of effectiveness demanded of any proposed solution. The many landmine detection approaches can be divided into two broad categories: (1)approaches primarily aimed at detecting the casing of the landmine (physical properties of its explosive content may also have some influence) and (2)approaches aimed at directly detecting the explosive contents. Examples of techniques belonging to the first group are electromagnetic induction, ground probing radar and other high frequency electromagnetic techniques, acoustics and other mechanical techniques, and infrared. Trace explosive vapour detection, thermalneutron activation and nuclear quadrupole resonance are examples of the second group. Following a brief introduction to nature of the landmine problem and the many technologies that have been explored to solve it, the presentation will focus on some of the detection approaches based on electromagnetic techniques. In particular, the state of the art in electromagnetic induction detection will be reviewed and required future research and development in this area will be presented.

A robust indicator based on singular value decomposition for flaw feature detection from noisy ultrasonic signals

NASA Astrophysics Data System (ADS)

Cui, Ximing; Wang, Zhe; Kang, Yihua; Pu, Haiming; Deng, Zhiyang

2018-05-01

Singular value decomposition (SVD) has been proven to be an effective de-noising tool for flaw echo signal feature detection in ultrasonic non-destructive evaluation (NDE). However, the uncertainty in the arbitrary manner of the selection of an effective singular value weakens the robustness of this technique. Improper selection of effective singular values will lead to bad performance of SVD de-noising. What is more, the computational complexity of SVD is too large for it to be applied in real-time applications. In this paper, to eliminate the uncertainty in SVD de-noising, a novel flaw indicator, named the maximum singular value indicator (MSI), based on short-time SVD (STSVD), is proposed for flaw feature detection from a measured signal in ultrasonic NDE. In this technique, the measured signal is first truncated into overlapping short-time data segments to put feature information of a transient flaw echo signal in local field, and then the MSI can be obtained from the SVD of each short-time data segment. Research shows that this indicator can clearly indicate the location of ultrasonic flaw signals, and the computational complexity of this STSVD-based indicator is significantly reduced with the algorithm proposed in this paper. Both simulation and experiments show that this technique is very efficient for real-time application in flaw detection from noisy data.

GyneScan

PubMed Central

Acharya, U. Rajendra; Sree, S. Vinitha; Kulshreshtha, Sanjeev; Molinari, Filippo; Koh, Joel En Wei; Saba, Luca; Suri, Jasjit S.

2014-01-01

Ovarian cancer is the fifth highest cause of cancer in women and the leading cause of death from gynecological cancers. Accurate diagnosis of ovarian cancer from acquired images is dependent on the expertise and experience of ultrasonographers or physicians, and is therefore, associated with inter observer variabilities. Computer Aided Diagnostic (CAD) techniques use a number of different data mining techniques to automatically predict the presence or absence of cancer, and therefore, are more reliable and accurate. A review of published literature in the field of CAD based ovarian cancer detection indicates that many studies use ultrasound images as the base for analysis. The key objective of this work is to propose an effective adjunct CAD technique called GyneScan for ovarian tumor detection in ultrasound images. In our proposed data mining framework, we extract several texture features based on first order statistics, Gray Level Co-occurrence Matrix and run length matrix. The significant features selected using t-test are then used to train and test several supervised learning based classifiers such as Probabilistic Neural Networks (PNN), Support Vector Machine (SVM), Decision Tree (DT), k-Nearest Neighbor (KNN), and Naïve Bayes (NB). We evaluated the developed framework using 1300 benign and 1300 malignant images. Using 11 significant features in KNN/PNN classifiers, we were able to achieve 100% classification accuracy, sensitivity, specificity, and positive predictive value in detecting ovarian tumor. Even though more validation using larger databases would better establish the robustness of our technique, the preliminary results are promising. This technique could be used as a reliable adjunct method to existing imaging modalities to provide a more confident second opinion on the presence/absence of ovarian tumor. PMID:24325128

Multivariate evoked response detection based on the spectral F-test.

PubMed

Rocha, Paulo Fábio F; Felix, Leonardo B; Miranda de Sá, Antonio Mauricio F L; Mendes, Eduardo M A M

2016-05-01

Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed. The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector. The multivariate method showed detection rates consistently higher than those ones when only one signal was used. It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used. Copyright © 2016 Elsevier B.V. All rights reserved.

Lip boundary detection techniques using color and depth information

NASA Astrophysics Data System (ADS)

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

2002-01-01

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

Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

Robust Hidden Markov Model based intelligent blood vessel detection of fundus images.

PubMed

Hassan, Mehdi; Amin, Muhammad; Murtza, Iqbal; Khan, Asifullah; Chaudhry, Asmatullah

2017-11-01

In this paper, we consider the challenging problem of detecting retinal vessel networks. Precise detection of retinal vessel networks is vital for accurate eye disease diagnosis. Most of the blood vessel tracking techniques may not properly track vessels in presence of vessels' occlusion. Owing to problem in sensor resolution or acquisition of fundus images, it is possible that some part of vessel may occlude. In this scenario, it becomes a challenging task to accurately trace these vital vessels. For this purpose, we have proposed a new robust and intelligent retinal vessel detection technique on Hidden Markov Model. The proposed model is able to successfully track vessels in the presence of occlusion. The effectiveness of the proposed technique is evaluated on publically available standard DRIVE dataset of the fundus images. The experiments show that the proposed technique not only outperforms the other state of the art methodologies of retinal blood vessels segmentation, but it is also capable of accurate occlusion handling in retinal vessel networks. The proposed technique offers better average classification accuracy, sensitivity, specificity, and area under the curve (AUC) of 95.7%, 81.0%, 97.0%, and 90.0% respectively, which shows the usefulness of the proposed technique. Copyright © 2017 Elsevier B.V. All rights reserved.

A novel shape similarity based elastography system for prostate cancer assessment

NASA Astrophysics Data System (ADS)

Wang, Haisu; Mousavi, Seyed Reza; Samani, Abbas

2012-03-01

Prostate cancer is the second common cancer among men worldwide and remains the second leading cancer-related cause of death in mature men. The disease can be cured if it is detected at early stage. This implies that prostate cancer detection at early stage is very critical for desirable treatment outcome. Conventional techniques of prostate cancer screening and detection, such as Digital Rectal Examination (DRE), Prostate-Specific Antigen (PSA) and Trans Rectal Ultra-Sonography (TRUS), are known to have low sensitivity and specificity. Elastography is an imaging technique that uses tissue stiffness as contrast mechanism. As the association between the degree of prostate tissue stiffness alteration and its pathology is well established, elastography can potentially detect prostate cancer with a high degree of sensitivity and specificity. In this paper, we present a novel elastography technique which, unlike other elastography techniques, does not require displacement data acquisition system. This technique requires the prostate's pre-compression and postcompression transrectal ultrasound images. The conceptual foundation of reconstructing the prostate's normal and pathological tissues elastic moduli is to determine these moduli such that the similarity between calculated and observed shape features of the post compression prostate image is maximized. Results indicate that this technique is highly accurate and robust.

Evaluation of Anomaly Detection Method Based on Pattern Recognition

NASA Astrophysics Data System (ADS)

Fontugne, Romain; Himura, Yosuke; Fukuda, Kensuke

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Toward detection of marine vehicles on horizon from buoy camera

NASA Astrophysics Data System (ADS)

Fefilatyev, Sergiy; Goldgof, Dmitry B.; Langebrake, Lawrence

2007-10-01

This paper presents a new technique for automatic detection of marine vehicles in open sea from a buoy camera system using computer vision approach. Users of such system include border guards, military, port safety and flow management, sanctuary protection personnel. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them on the subject of presence of marine vehicles. The goal of the system is to detect an approximate window around the ship and prepare the small image for transmission and human evaluation. The proposed computer vision-based algorithm combines horizon detection method with edge detection and post-processing. The dataset of 100 images is used to evaluate the performance of proposed technique. We discuss promising results of ship detection and suggest necessary improvements for achieving better performance.

Comments on "Failures in detecting volcanic ash from a satellite-based technique"

USGS Publications Warehouse

Prata, F.; Bluth, G.; Rose, B.; Schneider, D.; Tupper, A.

2001-01-01

The recent paper by Simpson et al. [Remote Sens. Environ. 72 (2000) 191.] on failures to detect volcanic ash using the 'reverse' absorption technique provides a timely reminder of the danger that volcanic ash presents to aviation and the urgent need for some form of effective remote detection. The paper unfortunately suffers from a fundamental flaw in its methodology and numerous errors of fact and interpretation. For the moment, the 'reverse' absorption technique provides the best means for discriminating volcanic ash clouds from meteorological clouds. The purpose of our comment is not to defend any particular algorithm; rather, we point out some problems with Simpson et al.'s analysis and re-state the conditions under which the 'reverse' absorption algorithm is likely to succeed. ?? 2001 Elsevier Science Inc. All rights reserved.

Evaluation of eddy current and magnetic techniques for inspecting rebars in bridge barrier rails

NASA Astrophysics Data System (ADS)

Lo, C. C. H.; Nakagawa, N.

2013-01-01

This paper reports on a feasibility study of using eddy current (EC) and magnetic flux leakage (MFL) methods to detect corrosion damage in rebars that anchor concrete barrier rails to the road deck of bridge structures. EC and MFL measurements were carried out on standalone rebars with and without artificial defects of 25% and 50% material loss, using a commercial EC-based rebar locator and a MFL system that was developed using giant magnetoresistance sensors to detect leakage fluxes from the defects. Both techniques can readily detect the defects at a distance of 2.5″ (63.5 mm). The amplitudes of the EC and MFL signals vary monotonically with the amount of material loss, indicating the potential of using the techniques to quantify material loss of standalone rebars.

Search for Superconductivity in Micrometeorites

PubMed Central

Guénon, S.; Ramírez, J. G.; Basaran, Ali C.; Wampler, J.; Thiemens, M.; Taylor, S.; Schuller, Ivan K.

2014-01-01

We have developed a very sensitive, highly selective, non-destructive technique for screening inhomogeneous materials for the presence of superconductivity. This technique, based on phase sensitive detection of microwave absorption is capable of detecting 10−12 cc of a superconductor embedded in a non-superconducting, non-magnetic matrix. For the first time, we apply this technique to the search for superconductivity in extraterrestrial samples. We tested approximately 65 micrometeorites collected from the water well at the Amundsen-Scott South pole station and compared their spectra with those of eight reference materials. None of these micrometeorites contained superconducting compounds, but we saw the Verwey transition of magnetite in our microwave system. This demonstrates that we are able to detect electro-magnetic phase transitions in extraterrestrial materials at cryogenic temperatures. PMID:25476841

Construction and Potential Applications of Biosensors for Proteins in Clinical Laboratory Diagnosis

PubMed Central

Liu, Xuan

2017-01-01

Biosensors for proteins have shown attractive advantages compared to traditional techniques in clinical laboratory diagnosis. In virtue of modern fabrication modes and detection techniques, various immunosensing platforms have been reported on basis of the specific recognition between antigen-antibody pairs. In addition to profit from the development of nanotechnology and molecular biology, diverse fabrication and signal amplification strategies have been designed for detection of protein antigens, which has led to great achievements in fast quantitative and simultaneous testing with extremely high sensitivity and specificity. Besides antigens, determination of antibodies also possesses great significance for clinical laboratory diagnosis. In this review, we will categorize recent immunosensors for proteins by different detection techniques. The basic conception of detection techniques, sensing mechanisms, and the relevant signal amplification strategies are introduced. Since antibodies and antigens have an equal position to each other in immunosensing, all biosensing strategies for antigens can be extended to antibodies under appropriate optimizations. Biosensors for antibodies are summarized, focusing on potential applications in clinical laboratory diagnosis, such as a series of biomarkers for infectious diseases and autoimmune diseases, and an evaluation of vaccine immunity. The excellent performances of these biosensors provide a prospective space for future antibody-detection-based disease serodiagnosis. PMID:29207528

Construction and Potential Applications of Biosensors for Proteins in Clinical Laboratory Diagnosis.

PubMed

Liu, Xuan; Jiang, Hui

2017-12-04

Biosensors for proteins have shown attractive advantages compared to traditional techniques in clinical laboratory diagnosis. In virtue of modern fabrication modes and detection techniques, various immunosensing platforms have been reported on basis of the specific recognition between antigen-antibody pairs. In addition to profit from the development of nanotechnology and molecular biology, diverse fabrication and signal amplification strategies have been designed for detection of protein antigens, which has led to great achievements in fast quantitative and simultaneous testing with extremely high sensitivity and specificity. Besides antigens, determination of antibodies also possesses great significance for clinical laboratory diagnosis. In this review, we will categorize recent immunosensors for proteins by different detection techniques. The basic conception of detection techniques, sensing mechanisms, and the relevant signal amplification strategies are introduced. Since antibodies and antigens have an equal position to each other in immunosensing, all biosensing strategies for antigens can be extended to antibodies under appropriate optimizations. Biosensors for antibodies are summarized, focusing on potential applications in clinical laboratory diagnosis, such as a series of biomarkers for infectious diseases and autoimmune diseases, and an evaluation of vaccine immunity. The excellent performances of these biosensors provide a prospective space for future antibody-detection-based disease serodiagnosis.

Diagnosis of 25 genotypes of human papillomaviruses for their physical statuses in cervical precancerous/cancerous lesions: a comparison of E2/E6E7 ratio-based vs. multiple E1-L1/E6E7 ratio-based detection techniques.

PubMed

Zhang, Rong; He, Yi-feng; Chen, Mo; Chen, Chun-mei; Zhu, Qiu-jing; Lu, Huan; Wei, Zhen-hong; Li, Fang; Zhang, Xiao-xin; Xu, Cong-jian; Yu, Long

2014-10-02

Cervical lesions caused by integrated human papillomavirus (HPV) infection are highly dangerous because they can quickly develop into invasive cancers. However, clinicians are currently hampered by the lack of a quick, convenient and precise technique to detect integrated/mixed infections of various genotypes of HPVs in the cervix. This study aimed to develop a practical tool to determine the physical status of different HPVs and evaluate its clinical significance. The target population comprised 1162 women with an HPV infection history of > six months and an abnormal cervical cytological finding. The multiple E1-L1/E6E7 ratio analysis, a novel technique, was developed based on determining the ratios of E1/E6E7, E2/E6E7, E4E5/E6E7, L2/E6E7 and L1/E6E7 within the viral genome. Any imbalanced ratios indicate integration. Its diagnostic and predictive performances were compared with those of E2/E6E7 ratio analysis. The detection accuracy of both techniques was evaluated using the gold-standard technique "detection of integrated papillomavirus sequences" (DIPS). To realize a multigenotypic detection goal, a primer and probe library was established. The integration rate of a particular genotype of HPV was correlated with its tumorigenic potential and women with higher lesion grades often carried lower viral loads. The E1-L1/E6E7 ratio analysis achieved 92.7% sensitivity and 99.0% specificity in detecting HPV integration, while the E2/E6E7 ratio analysis showed a much lower sensitivity (75.6%) and a similar specificity (99.3%). Interference due to episomal copies was observed in both techniques, leading to false-negative results. However, some positive results of E1-L1/E6E7 ratio analysis were missed by DIPS due to its stochastic detection nature. The E1-L1/E6E7 ratio analysis is more efficient than E2/E6E7 ratio analysis and DIPS in predicting precancerous/cancerous lesions, in which both positive predictive values (36.7%-82.3%) and negative predictive values (75.9%-100%) were highest (based on the results of three rounds of biopsies). The multiple E1-L1/E6E7 ratio analysis is more sensitive and predictive than E2/E6E7 ratio analysis as a triage test for detecting HPV integration. It can effectively narrow the range of candidates for colposcopic examination and cervical biopsy, thereby lowering the expense of cervical cancer prevention.

Underwater Turbulence Detection Using Gated Wavefront Sensing Technique

PubMed Central

Bi, Ying; Xu, Xiping; Chow, Eddy Mun Tik

2018-01-01

Laser sensing has been applied in various underwater applications, ranging from underwater detection to laser underwater communications. However, there are several great challenges when profiling underwater turbulence effects. Underwater detection is greatly affected by the turbulence effect, where the acquired image suffers excessive noise, blurring, and deformation. In this paper, we propose a novel underwater turbulence detection method based on a gated wavefront sensing technique. First, we elaborate on the operating principle of gated wavefront sensing and wavefront reconstruction. We then setup an experimental system in order to validate the feasibility of our proposed method. The effect of underwater turbulence on detection is examined at different distances, and under different turbulence levels. The experimental results obtained from our gated wavefront sensing system indicate that underwater turbulence can be detected and analyzed. The proposed gated wavefront sensing system has the advantage of a simple structure and high detection efficiency for underwater environments. PMID:29518889

Assessing and validating RST-FIRES on MSG-SEVIRI data by means a Total Validation Approach (TVA).

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, %Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2015-04-01

Several fire detection methods have been developed through the years for detecting forest fires from space. These algorithms (which may be grouped in single channel, multichannel and contextual algorithms) are generally based on the use of fixed thresholds that, being intrinsically exposed to false alarm proliferation, are often used in a conservative way. As a consequence, most of satellite-based algorithms for fire detection show low sensitivity resulting not suitable in operational contexts. In this work, the RST-FIRES algorithm, which is based on an original multi-temporal scheme of satellite data analysis (RST-Robust Satellite Techniques), is presented. The implementation of RST-FIRES on data provided by Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG) that, offering the best revisit time (i.e. 15 minutes), can be successfully used for detecting fires at early stage, is described here. Moreover, results of a Total Validation Approach (TVA) experimented both in Northern and Southern Italy, in collaboration with local and regional civil protection agencies, are also reported. In particular, TVA allowed us to assess RST-FIRES detections by means of ground check and aerial surveys, demonstrating the good performances offered by RST-FIRES using MSG-SEVIRI data. Indeed, this algorithm was capable of detecting several fires that for their features (e.g., small size, short time duration) would not have appeared in the official reports, highlighting a significant improvement in terms of sensitivity in comparison with other established satellite-based fire detection techniques still preserving a high confidence level of detection.

An advanced dual labeled gold nanoparticles probe to detect Cryptosporidium parvum using rapid immuno-dot blot assay.

PubMed

Thiruppathiraja, Chinnasamy; Kamatchiammal, Senthilkumar; Adaikkappan, Periyakaruppan; Alagar, Muthukaruppan

2011-07-15

The zoonotic protozoan parasite Cryptosporidium parvum poses a significant risk to public health. Due to the low infectious dose of C. parvum, remarkably sensitive detection methods are required for water and food industries analysis. However PCR affirmed sensing method of the causative nucleic acid has numerous advantages, still criterion demands for simple techniques and expertise understanding to extinguish its routine use. In contrast, protein based immuno detecting techniques are simpler to perform by a commoner, but lack of sensitivity due to inadequate signal amplification. In this paper, we focused on the development of a mere sensitive immuno detection method by coupling anti-cyst antibody and alkaline phosphatase on gold nanoparticle for C. parvum is described. Outcome of the sensitivity in an immuno-dot blot assay detection is enhanced by 500 fold (using conventional method) and visually be able to detect up to 10 oocysts/mL with minimal processing period. Techniques reported in this paper substantiate the convenience of immuno-dot blot assay for the routine screening of C. parvum in water/environmental examines and most importantly, demonstrates the potential of a prototype development of simple and inexpensive diagnostic technique. Copyright © 2011 Elsevier B.V. All rights reserved.

Microwave-based medical diagnosis using particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Modiri, Arezoo

This dissertation proposes and investigates a novel architecture intended for microwave-based medical diagnosis (MBMD). Furthermore, this investigation proposes novel modifications of particle swarm optimization algorithm for achieving enhanced convergence performance. MBMD has been investigated through a variety of innovative techniques in the literature since the 1990's and has shown significant promise in early detection of some specific health threats. In comparison to the X-ray- and gamma-ray-based diagnostic tools, MBMD does not expose patients to ionizing radiation; and due to the maturity of microwave technology, it lends itself to miniaturization of the supporting systems. This modality has been shown to be effective in detecting breast malignancy, and hence, this study focuses on the same modality. A novel radiator device and detection technique is proposed and investigated in this dissertation. As expected, hardware design and implementation are of paramount importance in such a study, and a good deal of research, analysis, and evaluation has been done in this regard which will be reported in ensuing chapters of this dissertation. It is noteworthy that an important element of any detection system is the algorithm used for extracting signatures. Herein, the strong intrinsic potential of the swarm-intelligence-based algorithms in solving complicated electromagnetic problems is brought to bear. This task is accomplished through addressing both mathematical and electromagnetic problems. These problems are called benchmark problems throughout this dissertation, since they have known answers. After evaluating the performance of the algorithm for the chosen benchmark problems, the algorithm is applied to MBMD tumor detection problem. The chosen benchmark problems have already been tackled by solution techniques other than particle swarm optimization (PSO) algorithm, the results of which can be found in the literature. However, due to the relatively high level of complexity and randomness inherent to the selection of electromagnetic benchmark problems, a trend to resort to oversimplification in order to arrive at reasonable solutions has been taken in literature when utilizing analytical techniques. Here, an attempt has been made to avoid oversimplification when using the proposed swarm-based optimization algorithms.

Detection of HLA Antibodies in Organ Transplant Recipients – Triumphs and Challenges of the Solid Phase Bead Assay

PubMed Central

Tait, Brian D.

2016-01-01

This review outlines the development of human leukocyte antigen (HLA) antibody detection assays and their use in organ transplantation in both antibody screening and crossmatching. The development of sensitive solid phase assays such as the enzyme-linked immunosorbent assay technique, and in particular the bead-based technology has revolutionized this field over the last 10–15 years. This revolution however has created a new paradigm in clinical decision making with respect to the detection of low level pretransplant HLA sensitization and its clinical relevance. The relative sensitivities of the assays used are discussed and the relevance of conflicting inter-assay results. Each assay has its advantages and disadvantages and these are discussed. Over the last decade, the bead-based assay utilizing the Luminex® fluorocytometer instrument has become established as the “gold standard” for HLA antibody testing. However, there are still unresolved issues surrounding this technique, such as the presence of denatured HLA molecules on the beads which reveal cryptic epitopes and the issue of appropriate fluorescence cut off values for positivity. The assay has been modified to detect complement binding (CB) in addition to non-complement binding (NCB) HLA antibodies although the clinical relevance of the CB and NCB IgG isotypes is not fully resolved. The increase sensitivity of the Luminex® bead assay over the complement-dependent cytotoxicity crossmatch has permitted the concept of the “virtual crossmatch” whereby the crossmatch is predicted to a high degree of accuracy based on the HLA antibody specificities detected by the solid phase assay. Dialog between clinicians and laboratory staff on an individual patient basis is essential for correct clinical decision making based on HLA antibody results obtained by the various techniques. PMID:28018342

Machine vision extracted plant movement for early detection of plant water stress.

PubMed

Kacira, M; Ling, P P; Short, T H

2002-01-01

A methodology was established for early, non-contact, and quantitative detection of plant water stress with machine vision extracted plant features. Top-projected canopy area (TPCA) of the plants was extracted from plant images using image-processing techniques. Water stress induced plant movement was decoupled from plant diurnal movement and plant growth using coefficient of relative variation of TPCA (CRV[TPCA)] and was found to be an effective marker for water stress detection. Threshold value of CRV(TPCA) as an indicator of water stress was determined by a parametric approach. The effectiveness of the sensing technique was evaluated against the timing of stress detection by an operator. Results of this study suggested that plant water stress detection using projected canopy area based features of the plants was feasible.

Glider-based Passive Acoustic Monitoring Techniques in the Southern California Region & West Coast Naval Training Range Demonstration of Glider-based Passive Acoustic Monitoring

DTIC Science & Technology

2012-09-30

generalized power-law detection algorithm for humpback whale vocalizations. J. Acous. Soc. Am. 131(4), 2682-2699. Roch, M. A., H. Klinck, S...Heaney (2012b). Site specific probability of passive acoustic detection of humpback whale calls from single fixed hydrophones. J. Acous. Soc. Am...monitoring: Correcting humpback call detections for site-specific and time-dependent environmental characteristics . JASA Express Letters, submitted October, 2012, 5 pgs plus 3 figs.

Nondestructive detection of infested chestnuts based on NIR spectroscopy

USDA-ARS?s Scientific Manuscript database

Insect feeding is a significant postharvest problem for processors of Chestnuts (Castanea sativa, Miller). In most cases, damage from insects is 'hidden', i.e. not visually detectable on the fruit surface. Consequently, traditional sorting techniques, including manual sorting, are generally inadequa...

Quantifying palpation techniques in relation to performance in a clinical prostate exam.

PubMed

Wang, Ninghuan; Gerling, Gregory J; Childress, Reba Moyer; Martin, Marcus L

2010-07-01

This paper seeks to quantify finger palpation techniques in the prostate clinical exam, determine their relationship with performance in detecting abnormalities, and differentiate the tendencies of nurse practitioner students and resident physicians. One issue with the digital rectal examination (DRE) is that performance in detecting abnormalities varies greatly and agreement between examiners is low. The utilization of particular palpation techniques may be one way to improve clinician ability. Based on past qualitative instruction, this paper algorithmically defines a set of palpation techniques for the DRE, i.e., global finger movement (GFM), local finger movement (LFM), and average intentional finger pressure, and utilizes a custom-built simulator to analyze finger movements in an experiment with two groups: 18 nurse practitioner students and 16 resident physicians. Although technique utilization varied, some elements clearly impacted performance. For example, those utilizing the LFM of vibration were significantly better at detecting abnormalities. Also, the V GFM led to greater success, but finger pressure played a lesser role. Interestingly, while the residents were clearly the superior performers, their techniques differed only subtly from the students. In summary, the quantified palpation techniques appear to account for examination ability at some level, but not entirely for differences between groups.

Flexible digital signal processing architecture for narrowband and spread-spectrum lock-in detection in multiphoton microscopy and time-resolved spectroscopy

PubMed Central

Wilson, Jesse W.; Park, Jong Kang; Warren, Warren S.

2015-01-01

The lock-in amplifier is a critical component in many different types of experiments, because of its ability to reduce spurious or environmental noise components by restricting detection to a single frequency and phase. One example application is pump-probe microscopy, a multiphoton technique that leverages excited-state dynamics for imaging contrast. With this application in mind, we present here the design and implementation of a high-speed lock-in amplifier on the field-programmable gate array (FPGA) coprocessor of a data acquisition board. The most important advantage is the inherent ability to filter signals based on more complex modulation patterns. As an example, we use the flexibility of the FPGA approach to enable a novel pump-probe detection scheme based on spread-spectrum communications techniques. PMID:25832238

Flexible digital signal processing architecture for narrowband and spread-spectrum lock-in detection in multiphoton microscopy and time-resolved spectroscopy.

PubMed

Wilson, Jesse W; Park, Jong Kang; Warren, Warren S; Fischer, Martin C

2015-03-01

The lock-in amplifier is a critical component in many different types of experiments, because of its ability to reduce spurious or environmental noise components by restricting detection to a single frequency and phase. One example application is pump-probe microscopy, a multiphoton technique that leverages excited-state dynamics for imaging contrast. With this application in mind, we present here the design and implementation of a high-speed lock-in amplifier on the field-programmable gate array (FPGA) coprocessor of a data acquisition board. The most important advantage is the inherent ability to filter signals based on more complex modulation patterns. As an example, we use the flexibility of the FPGA approach to enable a novel pump-probe detection scheme based on spread-spectrum communications techniques.

Spectroscopic detection of biological NO with a quantum cascade laser

NASA Technical Reports Server (NTRS)

Menzel, L.; Kosterev, A. A.; Curl, R. F.; Tittel, F. K.; Gmachl, C.; Capasso, F.; Sivco, D. L.; Baillargeon, J. N.; Hutchinson, A. L.; Cho, A. Y.;

Principles and status of neutron-based inspection technologies

NASA Astrophysics Data System (ADS)

Gozani, Tsahi

2011-06-01

Nuclear based explosive inspection techniques can detect a wide range of substances of importance for a wide range of objectives. For national and international security it is mainly the detection of nuclear materials, explosives and narcotic threats. For Customs Services it is also cargo characterization for shipment control and customs duties. For the military and other law enforcement agencies it could be the detection and/or validation of the presence of explosive mines, improvised explosive devices (IED) and unexploded ordnances (UXO). The inspection is generally based on the nuclear interactions of the neutrons (or high energy photons) with the various nuclides present and the detection of resultant characteristic emissions. These can be discrete gamma lines resulting from the thermal neutron capture process (n,γ) or inelastic neutron scattering (n,n'γ) occurring with fast neutrons. The two types of reactions are generally complementary. The capture process provides energetic and highly penetrating gamma rays in most inorganic substances and in hydrogen, while fast neutron inelastic scattering provides relatively strong gamma-ray signatures in light elements such as carbon and oxygen. In some specific important cases unique signatures are provided by the neutron capture process in light elements such as nitrogen, where unusually high-energy gamma ray is produced. This forms the basis for key explosive detection techniques. In some cases the elastically scattered source (of mono-energetic) neutrons may provide information on the atomic weight of the scattering elements. The detection of nuclear materials, both fissionable (e.g., 238U) and fissile (e.g., 235U), are generally based on the fissions induced by the probing neutrons (or photons) and detecting one or more of the unique signatures of the fission process. These include prompt and delayed neutrons and gamma rays. These signatures are not discrete in energy (typically they are continua) but temporally and energetically significantly different from the background, thus making them readily distinguishable. The penetrability of neutrons as probes and signatures as well as the gamma ray signatures make neutron interrogation applicable to the inspection of large conveyances such as cars, trucks, marine containers and also smaller objects like explosive mines concealed in the ground. The application of nuclear interrogation techniques greatly depends on operational requirements. For example explosive mines and IED detection clearly require one-sided inspection, which excludes transmission based inspection (e.g., transmission radiography) and greatly limits others. The technologies developed over the last decades are now being implemented with good results. Further advances have been made over the last several years that increase the sensitivity, applicability and robustness of these systems. The principle, applications and status of neutron-based inspection techniques will be reviewed.

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.

New sensors and techniques for the structural health monitoring of propulsion systems.

PubMed

Woike, Mark; Abdul-Aziz, Ali; Oza, Nikunj; Matthews, Bryan

2013-01-01

The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA), through the Aviation Safety Program (AVSP), has taken a lead role in the development of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. This paper presents a summary of key results and findings obtained from three different structural health monitoring approaches that have been investigated. This includes evaluating the performance of a novel microwave blade tip clearance sensor; a vibration based crack detection technique using an externally mounted capacitive blade tip clearance sensor; and lastly the results of using data driven anomaly detection algorithms for detecting cracks in a rotating disk.

New Sensors and Techniques for the Structural Health Monitoring of Propulsion Systems

PubMed Central

2013-01-01

The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA), through the Aviation Safety Program (AVSP), has taken a lead role in the development of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. This paper presents a summary of key results and findings obtained from three different structural health monitoring approaches that have been investigated. This includes evaluating the performance of a novel microwave blade tip clearance sensor; a vibration based crack detection technique using an externally mounted capacitive blade tip clearance sensor; and lastly the results of using data driven anomaly detection algorithms for detecting cracks in a rotating disk. PMID:23935425

Circulating tumor cell detection: A direct comparison between negative and unbiased enrichment in lung cancer.

PubMed

Xu, Yan; Liu, Biao; Ding, Fengan; Zhou, Xiaodie; Tu, Pin; Yu, Bo; He, Yan; Huang, Peilin

2017-06-01

Circulating tumor cells (CTCs), isolated as a 'liquid biopsy', may provide important diagnostic and prognostic information. Therefore, rapid, reliable and unbiased detection of CTCs are required for routine clinical analyses. It was demonstrated that negative enrichment, an epithelial marker-independent technique for isolating CTCs, exhibits a better efficiency in the detection of CTCs compared with positive enrichment techniques that only use specific anti-epithelial cell adhesion molecules. However, negative enrichment techniques incur significant cell loss during the isolation procedure, and as it is a method that uses only one type of antibody, it is inherently biased. The detection procedure and identification of cell types also relies on skilled and experienced technicians. In the present study, the detection sensitivity of using negative enrichment and a previously described unbiased detection method was compared. The results revealed that unbiased detection methods may efficiently detect >90% of cancer cells in blood samples containing CTCs. By contrast, only 40-60% of CTCs were detected by negative enrichment. Additionally, CTCs were identified in >65% of patients with stage I/II lung cancer. This simple yet efficient approach may achieve a high level of sensitivity. It demonstrates a potential for the large-scale clinical implementation of CTC-based diagnostic and prognostic strategies.

Integration of FTTH and GI-POF in-house networks based on injection locking and direct-detection techniques.

PubMed

Peng, Hsiao-Chun; Lu, Hai-Han; Li, Chung-Yi; Su, Heng-Sheng; Hsu, Chin-Tai

2011-03-28

An integration of fiber-to-the-home (FTTH) and graded-index plastic optical fiber (GI-POF) in-house networks based on injection-locked vertical cavity surface emitting lasers (VCSELs) and direct-detection technique is proposed and experimentally demonstrated. Sufficient low bit error rate (BER) values were obtained over a combination of 20-km single-mode fiber (SMF) and 50-m GI-POF links. Signal qualities satisfy the worldwide interoperability for microwave access (WiMAX) requirement with data signals of 20 Mbps/5.8 GHz and 70 Mbps/10 GHz, respectively. Since our proposed network does not use sophisticated and expensive RF devices in premises, it reveals a prominent one with simpler and more economic advantages. Our proposed architecture is suitable for the SMF-based primary and GI-POF-based in-house networks.

Flow-based analysis using microfluidics-chemiluminescence systems.

PubMed

Al Lawati, Haider A J

2013-01-01

This review will discuss various approaches and techniques in which analysis using microfluidics-chemiluminescence systems (MF-CL) has been reported. A variety of applications is examined, including environmental, pharmaceutical, biological, food and herbal analysis. Reported uses of CL reagents, sample introduction techniques, sample pretreatment methods, CL signal enhancement and detection systems are discussed. A hydrodynamic pumping system is predominately used for these applications. However, several reports are available in which electro-osmotic (EO) pumping has been implemented. Various sample pretreatment methods have been used, including liquid-liquid extraction, solid-phase extraction and molecularly imprinted polymers. A wide range of innovative techniques has been reported for CL signal enhancement. Most of these techniques are based on enhancement of the mixing process in the microfluidics channels, which leads to enhancement of the CL signal. However, other techniques are also reported, such as mirror reaction, liquid core waveguide, on-line pre-derivatization and the use of an opaque white chip with a thin transparent seal. Photodetectors are the most commonly used detectors; however, other detection systems have also been used, including integrated electrochemiluminescence (ECL) and organic photodiodes (OPDs). Copyright © 2012 John Wiley & Sons, Ltd.

Recent Electrochemical and Optical Sensors in Flow-Based Analysis

PubMed Central

Chailapakul, Orawon; Ngamukot, Passapol; Yoosamran, Alongkorn; Siangproh, Weena; Wangfuengkanagul, Nattakarn

2006-01-01

Some recent analytical sensors based on electrochemical and optical detection coupled with different flow techniques have been chosen in this overview. A brief description of fundamental concepts and applications of each flow technique, such as flow injection analysis (FIA), sequential injection analysis (SIA), all injection analysis (AIA), batch injection analysis (BIA), multicommutated FIA (MCFIA), multisyringe FIA (MSFIA), and multipumped FIA (MPFIA) were reviewed.

Detection of thermal-induced prompt fission neutrons of highly-enriched uranium: A position sensitive technique

NASA Astrophysics Data System (ADS)

Tartaglione, A.; Di Lorenzo, F.; Mayer, R. E.

2009-07-01

Cargo interrogation in search for special nuclear materials like highly-enriched uranium or 239Pu is a first priority issue of international borders security. In this work we present a thermal-pulsed neutron-based approach to a technique which combines the time-of-flight method and demonstrates a capability to detect small quantities of highly-enriched uranium shielded with high or low Z materials providing, in addition, a manner to know the approximate position of the searched material.

The Fibrin slide assay for detecting urokinase activity in human fetal kidney cells

NASA Technical Reports Server (NTRS)

Sedor, K.

1985-01-01

The Fibrin Slide Technique of Hau C. Kwaan and Tage Astrup is discussed. This relatively simple assay involves two steps: the formation of an artificial clot and then the addition of an enzyme (UKOKINASE) to dissolve the clot. The actual dissolving away of the clot is detected by the appearance of holes (lysis zones) in the stained clot. The procedure of Kwaan and Astrup is repeated, along with modifications and suggestions for improvements based on experience with the technique.

Influence of detector noise and background noise on detection-system

NASA Astrophysics Data System (ADS)

Song, Yiheng; Wang, Zhiyong

2018-02-01

Study the noise by detectors and background light ,we find that the influence of background noise on the detection is more than that of itself. Therefore, base on the fiber coupled beam splitting technique, the small area detector is used to replace the large area detector. It can achieve high signal-to-noise ratio (SNR) and reduce the speckle interference of the background light. This technique is expected to solve the bottleneck of large field of view and high sensitivity.

Analysis of Ergot Alkaloids

PubMed Central

Crews, Colin

2015-01-01

The principles and application of established and newer methods for the quantitative and semi-quantitative determination of ergot alkaloids in food, feed, plant materials and animal tissues are reviewed. The techniques of sampling, extraction, clean-up, detection, quantification and validation are described. The major procedures for ergot alkaloid analysis comprise liquid chromatography with tandem mass spectrometry (LC-MS/MS) and liquid chromatography with fluorescence detection (LC-FLD). Other methods based on immunoassays are under development and variations of these and minor techniques are available for specific purposes. PMID:26046699

Microseismic techniques for avoiding induced seismicity during fluid injection

DOE PAGES

Matzel, Eric; White, Joshua; Templeton, Dennise; ...

2014-01-01

The goal of this research is to develop a fundamentally better approach to geological site characterization and early hazard detection. We combine innovative techniques for analyzing microseismic data with a physics-based inversion model to forecast microseismic cloud evolution. The key challenge is that faults at risk of slipping are often too small to detect during the site characterization phase. Our objective is to devise fast-running methodologies that will allow field operators to respond quickly to changing subsurface conditions.

MALDI-TOF for the rapid detection of carbapenemase-producing Enterobacteriaceae: comparison of the commercialized MBT STAR®-Carba IVD Kit with two in-house MALDI-TOF techniques and the RAPIDEC® CARBA NP.

PubMed

Dortet, Laurent; Tandé, Didier; de Briel, Dominique; Bernabeu, Sandrine; Lasserre, Camille; Gregorowicz, Guillaume; Jousset, Agnès B; Naas, Thierry

2018-06-11

There is an urgent need for accurate and fast diagnostic tests to identify carbapenemase-producing bacteria. Here, we have evaluated three MALDI-TOF-based techniques to detect carbapenemase-producing Enterobacteriaceae (CPE) from cultured colonies. The performance of three MALDI-TOF-based techniques, including the commercialized MBT STAR®-Carba IVD Kit (Bruker Daltonics) and two in-house protocols performed on the Microflex LT Biotyper (Bruker Daltonics) and the VITEK® MS Plus (bioMérieux), were compared with those of the RAPIDEC® CARBA NP (bioMérieux). A collection of 175 isolates including 120 carbapenemase producers and 55 non-carbapenemase producers was tested. Samples were tested blind in the three participating centres. The repeatability of the MBT STAR®-Carba IVD Kit was also evaluated. The three MALDI-TOF techniques possess sensitivities ranging from 95% to 100% and specificities from 98.2% to 100% compared with 99.2% and 100%, respectively, for the RAPIDEC® CARBA NP. The MBT STAR®-Carba IVD Kit gave highly reproducible results and is the only technique able to provide a concomitant identification of the bacterial isolate. The three MALDI-TOF techniques possess a fast turnaround time (less than 1.5 h). Overall, MALDI-TOF is a reliable technique for the rapid detection of CPE from cultured colonies. MBT STAR®-Carba IVD Kit, the only commercially available assay, could easily be implemented in a clinical microbiology laboratory if it is already equipped with a Microflex LT Biotyper mass spectrometer.

Image steganalysis using Artificial Bee Colony algorithm

NASA Astrophysics Data System (ADS)

Sajedi, Hedieh

2017-09-01

Steganography is the science of secure communication where the presence of the communication cannot be detected while steganalysis is the art of discovering the existence of the secret communication. Processing a huge amount of information takes extensive execution time and computational sources most of the time. As a result, it is needed to employ a phase of preprocessing, which can moderate the execution time and computational sources. In this paper, we propose a new feature-based blind steganalysis method for detecting stego images from the cover (clean) images with JPEG format. In this regard, we present a feature selection technique based on an improved Artificial Bee Colony (ABC). ABC algorithm is inspired by honeybees' social behaviour in their search for perfect food sources. In the proposed method, classifier performance and the dimension of the selected feature vector depend on using wrapper-based methods. The experiments are performed using two large data-sets of JPEG images. Experimental results demonstrate the effectiveness of the proposed steganalysis technique compared to the other existing techniques.

Discrete Wavelet Transform for Fault Locations in Underground Distribution System

NASA Astrophysics Data System (ADS)

Apisit, C.; Ngaopitakkul, A.

2010-10-01

In this paper, a technique for detecting faults in underground distribution system is presented. Discrete Wavelet Transform (DWT) based on traveling wave is employed in order to detect the high frequency components and to identify fault locations in the underground distribution system. The first peak time obtained from the faulty bus is employed for calculating the distance of fault from sending end. The validity of the proposed technique is tested with various fault inception angles, fault locations and faulty phases. The result is found that the proposed technique provides satisfactory result and will be very useful in the development of power systems protection scheme.

Non-destructive scanning for applied stress by the continuous magnetic Barkhausen noise method

NASA Astrophysics Data System (ADS)

Franco Grijalba, Freddy A.; Padovese, L. R.

2018-01-01

This paper reports the use of a non-destructive continuous magnetic Barkhausen noise technique to detect applied stress on steel surfaces. The stress profile generated in a sample of 1070 steel subjected to a three-point bending test is analyzed. The influence of different parameters such as pickup coil type, scanner speed, applied magnetic field and frequency band analyzed on the effectiveness of the technique is investigated. A moving smoothing window based on a second-order statistical moment is used to analyze the time signal. The findings show that the technique can be used to detect applied stress profiles.

Polyaniline nanowires-gold nanoparticles hybrid network based chemiresistive hydrogen sulfide sensor

NASA Astrophysics Data System (ADS)

Shirsat, Mahendra D.; Bangar, Mangesh A.; Deshusses, Marc A.; Myung, Nosang V.; Mulchandani, Ashok

2009-02-01

We report a sensitive, selective, and fast responding room temperature chemiresistive sensor for hydrogen sulfide detection and quantification using polyaniline nanowires-gold nanoparticles hybrid network. The sensor was fabricated by facile electrochemical technique. Initially, polyaniline nanowires with a diameter of 250-320 nm bridging the gap between a pair of microfabricated gold electrodes were synthesized using templateless electrochemical polymerization using a two step galvanostatic technique. Polyaniline nanowires were then electrochemically functionalized with gold nanoparticles using cyclic voltammetry technique. These chemiresistive sensors show an excellent limit of detection (0.1 ppb), wide dynamic range (0.1-100 ppb), and very good selectivity and reproducibility.

Development and evaluation of a technique for in vivo monitoring of 60Co in human lungs

NASA Astrophysics Data System (ADS)

de Mello, J. Q.; Lucena, E. A.; Dantas, A. L. A.; Dantas, B. M.

2016-07-01

60Co is a fission product of 235U and represents a risk of internal exposure of workers in nuclear power plants, especially those involved in the maintenance of potentially contaminated parts and equipment. The control of 60Co intake by inhalation can be performed through in vivo monitoring. This work describes the evaluation of a technique through the minimum detectable activity and the corresponding minimum detectable effective doses, based on biokinetic and dosimetric models of 60Co in the human body. The results allow to state that the technique is suitable either for monitoring of occupational exposures or evaluation of accidental intake.

Fibre optic system for biochemical and microbiological sensing

NASA Astrophysics Data System (ADS)

Penwill, L. A.; Slater, J. H.; Hayes, N. W.; Tremlett, C. J.

2007-07-01

This poster will discuss state-of-the-art fibre optic sensors based on evanescent wave technology emphasising chemophotonic sensors for biochemical reactions and microbe detection. Devices based on antibody specificity and unique DNA sequences will be described. The development of simple sensor devices with disposable single use sensor probes will be illustrated with a view to providing cost effective field based or point of care analysis of major themes such as hospital acquired infections or bioterrorism events. This presentation will discuss the nature and detection thresholds required, the optical detection techniques investigated, results of sensor trials and the potential for wider commercial application.

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

Investigation of piezoelectric impedance-based health monitoring of structure interface debonding

NASA Astrophysics Data System (ADS)

Xiao, Li; Chen, Guofeng; Chen, Xiaoming; Qu, Wenzhong

2016-04-01

Various damages might occur during the solid rocket motor (SRM) manufacturing/operational phase, and the debonding of propellant/insulator/composite case interfaces is one of damage types which determine the life of a motor. The detection of such interface debonding damage will be beneficial for developing techniques for reliable nondestructive evaluation (NDE) and structural health monitoring (SHM). Piezoelectric sensors are widely used for structural health monitoring technique. In particular, electromechanical impedance (EMI) techniques give simple and low-cost solutions for detecting damage in various structures. In this work, piezoelectric EMI structural health monitoring technique is applied to identify the debonding condition of propellant/insulator interface structure using finite element method and experimental investigation. A three-dimensional coupled field finite element model is developed using the software ANSYS and the harmonic analysis is conducted for high-frequency impedance analysis procedure. In the experimental study, the impedance signals were measured from PZT and MFC sensors outside attached to composite case monitoring the different debonding conditions between the propellant and insulator. Root mean square deviation (RMSD) based damage index is conducted to quantify the changes i n impedance for different de bonding conditions and frequency range. Simulation and experimental results confirmed that the EMI technique can be used effectively for detecting the debonding damage in SRM and is expected to be useful for future application of real SRM's SHM.

Standoff detection: classification of biological aerosols using laser induced fluorescence (LIF) technique

NASA Astrophysics Data System (ADS)

Hausmann, Anita; Duschek, Frank; Fischbach, Thomas; Pargmann, Carsten; Aleksejev, Valeri; Poryvkina, Larisa; Sobolev, Innokenti; Babichenko, Sergey; Handke, Jürgen

2014-05-01

The challenges of detecting hazardous biological materials are manifold: Such material has to be discriminated from other substances in various natural surroundings. The detection sensitivity should be extremely high. As living material may reproduce itself, already one single bacterium may represent a high risk. Of course, identification should be quite fast with a low false alarm rate. Up to now, there is no single technique to solve this problem. Point sensors may collect material and identify it, but the problems of fast identification and especially of appropriate positioning of local collectors are sophisticated. On the other hand, laser based standoff detection may instantaneously provide the information of some accidental spillage of material by detecting the generated thin cloud. LIF technique may classify but hardly identify the substance. A solution can be the use of LIF technique in a first step to collect primary data and - if necessary- followed by utilizing these data for an optimized positioning of point sensors. We perform studies on an open air laser test range at distances between 20 and 135 m applying LIF technique to detect and classify aerosols. In order to employ LIF capability, we use a laser source emitting two wavelengths alternatively, 280 and 355 nm, respectively. Moreover, the time dependence of fluorescence spectra is recorded by a gated intensified CCD camera. Signal processing is performed by dedicated software for spectral pattern recognition. The direct comparison of all results leads to a basic classification of the various compounds.

Comparison of dual and single exposure techniques in dual-energy chest radiography.

PubMed

Ho, J T; Kruger, R A; Sorenson, J A

1989-01-01

Conventional chest radiography is the most effective tool for lung cancer detection and diagnosis; nevertheless, a high percentage of lung cancer tumors are missed because of the overlap of lung nodule image contrast with bone image contrast in a chest radiograph. Two different energy subtraction strategies, dual exposure and single exposure techniques, were studied for decomposing a radiograph into bone-free and soft tissue-free images to address this problem. For comparing the efficiency of these two techniques in lung nodule detection, the performances of the techniques were evaluated on the basis of residual tissue contrast, energy separation, and signal-to-noise ratio. The evaluation was based on both computer simulation and experimental verification. The dual exposure technique was found to be better than the single exposure technique because of its higher signal-to-noise ratio and greater residual tissue contrast. However, x-ray tube loading and patient motion are problems.

In vivo flow cytometry for blood cell analysis using differential epi-detection of forward scattered light

NASA Astrophysics Data System (ADS)

Paudel, Hari P.; Jung, Yookyung; Raphael, Anthony; Alt, Clemens; Wu, Juwell; Runnels, Judith; Lin, Charles P.

2018-02-01

The present standard of blood cell analysis is an invasive procedure requiring the extraction of patient's blood, followed by ex-vivo analysis using a flow cytometer or a hemocytometer. We are developing a noninvasive optical technique that alleviates the need for blood extraction. For in-vivo blood analysis we need a high speed, high resolution and high contrast label-free imaging technique. In this proceeding report, we reported a label-free method based on differential epi-detection of forward scattered light, a method inspired by Jerome Mertz's oblique back-illumination microscopy (OBM) (Ford et al, Nat. Meth. 9(12) 2012). The differential epi-detection of forward light gives phase contrast image at diffraction-limited resolution. Unlike reflection confocal microscopy (RCM), which detects only sharp refractive index variation and suffers from speckle noise, this technique is suitable for detection of subtle variation of refractive index in biological tissue and it provides the shape and the size of cells. A custom built high speed electronic detection circuit board produces a real-time differential signal which yields image contrast based on phase gradient in the sample. We recorded blood flow in-vivo at 17.2k lines per second in line scan mode, or 30 frames per second (full frame), or 120 frame per second (quarter frame) in frame scan mode. The image contrast and speed of line scan data recording show the potential of the system for noninvasive blood cell analysis.

Trace detection of perchlorate in industrial-grade emulsion explosive with portable surface-enhanced Raman spectroscopy.

PubMed

Nuntawong, N; Eiamchai, P; Limwichean, S; Wong-ek, B; Horprathum, M; Patthanasettakul, V; Leelapojanaporn, A; Nakngoenthong, S; Chindaudom, P

2013-12-10

Recent analyses by ion-exchange chromatography (IC) showed that, beside nitrate, the majority of the industrial-grade emulsion explosives, extensively used by most separatists in the southern Thailand insurgency, contained small traces of perchlorate anions. In demand for the faster, reliable, and simple detection methods, the portable detection of nitrate and perchlorate became the great interest for the forensic and field-investigators. This work proposed a unique method to detect the trace amount of perchlorate in seven industrial-grade emulsion explosives under the field tests. We utilized the combination of the portable Raman spectroscope, the developed surfaced-enhanced Raman substrates, and the sample preparation procedures. The portable Raman spectroscope with a laser diode of 785 nm for excitation and a thermoelectric-cooled CCD spectrometer for detection was commercially available. The SERS substrates, with uniformly distributed nanostructured silver nanorods, were fabricated by the DC magnetron sputtering system, based on the oblique-angle deposition technique. The sample preparation procedures were proposed based on (1) pentane extraction technique and (2) combustion technique, prior to being dissolved in the purified water. In comparison to the ion chromatography and the conventional Raman measurements, our proposed methods successfully demonstrated the highly sensitive detectability of the minimal trace amount of perchlorate from five of the explosives with minimal operating time. This work was therefore highly practical to the development for the forensic analyses of the post-blast explosive residues under the field-investigations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A benzothiazole-based fluorescent probe for hypochlorous acid detection and imaging in living cells

NASA Astrophysics Data System (ADS)

Nguyen, Khac Hong; Hao, Yuanqiang; Zeng, Ke; Fan, Shengnan; Li, Fen; Yuan, Suke; Ding, Xuejing; Xu, Maotian; Liu, You-Nian

2018-06-01

A benzothiazole-based turn-on fluorescent probe with a large Stokes shift (190 nm) has been developed for hypochlorous acid detection. The probe displays prompt fluorescence response for HClO with excellent selectivity over other reactive oxygen species as well as a low detection limit of 0.08 μM. The sensing mechanism involves the HClO-induced specific oxidation of oxime moiety of the probe to nitrile oxide, which was confirmed by HPLC-MS technique. Furthermore, imaging studies demonstrated that the probe is cell permeable and can be applied to detect HClO in living cells.

Silica nanoparticle based techniques for extraction, detection, and degradation of pesticides.

PubMed

Bapat, Gandhali; Labade, Chaitali; Chaudhari, Amol; Zinjarde, Smita

2016-11-01

Silica nanoparticles (SiNPs) find applications in the fields of drug delivery, catalysis, immobilization and sensing. Their synthesis can be mediated in a facile manner and they display broad range compatibility and stability. Their existence in the form of spheres, wires and sheets renders them suitable for varied purposes. This review summarizes the use of silica nanostructures in developing techniques for extraction, detection and degradation of pesticides. Silica nanostructures on account of their sorbent properties, porous nature and increased surface area allow effective extraction of pesticides. They can be modified (with ionic liquids, silanes or amines), coated with molecularly imprinted polymers or magnetized to improve the extraction of pesticides. Moreover, they can be altered to increase their sensitivity and stability. In addition to the analysis of pesticides by sophisticated techniques such as High Performance Liquid Chromatography or Gas chromatography, silica nanoparticles related simple detection methods are also proving to be effective. Electrochemical and optical detection based on enzymes (acetylcholinesterase and organophosphate hydrolase) or antibodies have been developed. Pesticide sensors dependent on fluorescence, chemiluminescence or Surface Enhanced Raman Spectroscopic responses are also SiNP based. Moreover, degradative enzymes (organophosphate hydrolases, carboxyesterases and laccases) and bacterial cells that produce recombinant enzymes have been immobilized on SiNPs for mediating pesticide degradation. After immobilization, these systems show increased stability and improved degradation. SiNP are significant in developing systems for effective extraction, detection and degradation of pesticides. SiNPs on account of their chemically inert nature and amenability to surface modifications makes them popular tools for fabricating devices for 'on-site' applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Polymerase chain reaction in the detection of tumor cells: new approaches in diagnosis and follow-up of patients with thyroid cancer.

PubMed

Bojunga, Jörg; Kusterer, Klaus; Schumm-Draeger, Petra-Maria; Usadel, Klaus-Henning

2002-12-01

Thyroid cancers are the most common endocrine malignancies and are being diagnosed with increasing frequency. In addition to other measures, diagnosis is based on fine-needle aspiration cytology examination. Recently, new assays using reverse transcription-polymerase chain reaction (PCR) are being tested to improve sensitivity and specificity of primary diagnosis and detection of recurrent thyroid cancer. In the preoperative diagnosis of thyroid cancer, several tissue- and/or tumor-specific mRNA have been described and in several cases, a higher sensitivity and specificity could be achieved using molecular techniques compared to conventional methods. In the postoperative follow-up of patients with thyroid cancer, conflicting data have been published and the use of PCR techniques revealed several problems of the molecular approach, which are based on some technical as well as biologic limitations. Despite these problems, which are discussed in detail in this review, molecular techniques may nevertheless improve the sensitivity and accuracy of fine-needle aspiration of thyroid nodules, fine-needle aspiration of metastases, and detection of recurrent disease in peripheral blood samples.

Sensor failure detection for jet engines using analytical redundance

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1984-01-01

Analytical redundant sensor failure detection, isolation and accommodation techniques for gas turbine engines are surveyed. Both the theoretical technology base and demonstrated concepts are discussed. Also included is a discussion of current technology needs and ongoing Government sponsored programs to meet those needs.

Shack-Hartmann wavefront sensing based on binary-aberration-mode filtering.

PubMed

Wang, Shuai; Yang, Ping; Xu, Bing; Dong, Lizhi; Ao, Mingwu

2015-02-23

Spot centroid detection is required by Shack-Hartmann wavefront sensing since the technique was first proposed. For a Shack-Hartmann wavefront sensor, the standard structure is to place a camera behind a lenslet array to record the image of spots. We proposed a new Shack-Hartmann wavefront sensing technique without using spot centroid detection. Based on the principle of binary-aberration-mode filtering, for each subaperture, only one light-detecting unit is used to measure the local wavefront slopes. It is possible to adopt single detectors in Shack-Hartmann wavefront sensor. Thereby, the method is able to gain noise benefits from using singe detectors behind each subaperture when used for sensing rapid varying wavefront in weak light. Moreover, due to non-discrete pixel imaging, this method is a potential solution for high measurement precision with fewer detecting units. Our simulations demonstrate the validity of the theoretical model. In addition, the results also indicate the advantage in measurement accuracy.

Coherent Structure Detection using Persistent Homology and other Topological Tools

NASA Astrophysics Data System (ADS)

Smith, Spencer; Roberts, Eric; Sindi, Suzanne; Mitchell, Kevin

2017-11-01

For non-autonomous, aperiodic fluid flows, coherent structures help organize the dynamics, much as invariant manifolds and periodic orbits do for autonomous or periodic systems. The prevalence of such flows in nature and industry has motivated many successful techniques for defining and detecting coherent structures. However, often these approaches require very fine trajectory data to reconstruct velocity fields and compute Cauchy-Green-tensor-related quantities. We use topological techniques to help detect coherent trajectory sets in relatively sparse 2D advection problems. More specifically, we have developed a homotopy-based algorithm, the ensemble-based topological entropy calculation (E-tec), which assigns to each edge in an initial triangulation of advected points a topologically forced lower bound on its future stretching rate. The triangulation and its weighted edges allow us to analyze flows using persistent homology. This topological data analysis tool detects clusters and loops in the triangulation that are robust in the presence of noise and in this case correspond to coherent trajectory sets.

Online Detection of Functional Groups in SEC via Quantum Cascade Laser IR Spectroscopy.

PubMed

Morlock, Sascha; Kübel, Jennifer M; Beskers, Timo F; Lendl, Bernhard; Wilhelm, Manfred

2018-01-01

The development of coupled techniques based on chemically sensitive detectors, such as FTIR or NMR spectrometers, for size exclusion chromatography (SEC) provides sophisticated methods for determining the molecular-weight-dependent chemical composition in polymers. However, the detection of rare functionalities such as end groups or branching points presents a challenge, especially for online coupled SEC detection, which is based on low-concentration chromatography. To address this issue, for the first time, an external cavity quantum cascade laser (EC-QCL) infrared spectrometer is coupled to an SEC. The system is evaluated using polystyrene/poly(methyl methacrylate) (PS/PMMA) blends. The current limit of detection for the carbonyl (PMMA) stretch vibration at 1730 cm -1 with this technique is 3.5 µg PMMA on a semipreparative column (typical load of 2.5 mg polymer in total). That equals 0.15 mol% of PMMA in the PS/PMMA blend and corresponds to one carbonyl group per 70 kg mol -1 polymer. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An industrial information integration approach to in-orbit spacecraft

NASA Astrophysics Data System (ADS)

Du, Xiaoning; Wang, Hong; Du, Yuhao; Xu, Li Da; Chaudhry, Sohail; Bi, Zhuming; Guo, Rong; Huang, Yongxuan; Li, Jisheng

2017-01-01

To operate an in-orbit spacecraft, the spacecraft status has to be monitored autonomously by collecting and analysing real-time data, and then detecting abnormities and malfunctions of system components. To develop an information system for spacecraft state detection, we investigate the feasibility of using ontology-based artificial intelligence in the system development. We propose a new modelling technique based on the semantic web, agent, scenarios and ontologies model. In modelling, the subjects of astronautics fields are classified, corresponding agents and scenarios are defined, and they are connected by the semantic web to analyse data and detect failures. We introduce the modelling methodologies and the resulted framework of the status detection information system in this paper. We discuss system components as well as their interactions in details. The system has been prototyped and tested to illustrate its feasibility and effectiveness. The proposed modelling technique is generic which can be extended and applied to the system development of other large-scale and complex information systems.

Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy.

PubMed

Ortiz-Aguayo, Dionisia; Del Valle, Manel

2018-01-26

This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)₆] 3- /[Fe(CN)₆] 4- as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µM for lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM -1 in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis.

Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy

PubMed Central

2018-01-01

This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)6]3−/[Fe(CN)6]4− as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µM for lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM−1 in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis. PMID:29373502

Phase editing as a signal pre-processing step for automated bearing fault detection

NASA Astrophysics Data System (ADS)

Barbini, L.; Ompusunggu, A. P.; Hillis, A. J.; du Bois, J. L.; Bartic, A.

2017-07-01

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance. However automation of the detection process is difficult due to the complexity of vibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator. This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally-efficient full-band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state-of-the-art processing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates compared to the state-of-the-art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.

Object tracking via background subtraction for monitoring illegal activity in crossroad

NASA Astrophysics Data System (ADS)

Ghimire, Deepak; Jeong, Sunghwan; Park, Sang Hyun; Lee, Joonwhoan

2016-07-01

In the field of intelligent transportation system a great number of vision-based techniques have been proposed to prevent pedestrians from being hit by vehicles. This paper presents a system that can perform pedestrian and vehicle detection and monitoring of illegal activity in zebra crossings. In zebra crossing, according to the traffic light status, to fully avoid a collision, a driver or pedestrian should be warned earlier if they possess any illegal moves. In this research, at first, we detect the traffic light status of pedestrian and monitor the crossroad for vehicle pedestrian moves. The background subtraction based object detection and tracking is performed to detect pedestrian and vehicles in crossroads. Shadow removal, blob segmentation, trajectory analysis etc. are used to improve the object detection and classification performance. We demonstrate the experiment in several video sequences which are recorded in different time and environment such as day time and night time, sunny and raining environment. Our experimental results show that such simple and efficient technique can be used successfully as a traffic surveillance system to prevent accidents in zebra crossings.

Four-Wave-Mixing Approach to In Situ Detection of Nanoparticles

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

Gerakis, Alexandros; Yeh, Yao -Wen; Shneider, Mikhail N.

Here, we report on the development and experimental validation of a laser-based technique which uses coherent Rayleigh-Brillouin scattering (CRBS) to detect nanoparticles with characteristic sizes ranging from the atomic scale to tens of nanometers. This technique is aimed (nonexclusively) at the detection of nanoparticles produced by volumetric nanoparticle synthesis methods. Using CRBS, carbon nanoparticles of dimensions less than 10 nm and concentrations of 10 10 cm –3 are detected in situ in a carbon arc discharge with graphite electrodes. This four-wave-mixing approach should enable advances in the understanding of nanoparticle growth that could potentially lead to improved modeling of themore » growth mechanisms, and thus to improve synthesis selectivity of nanoparticles and yield.« less

Noninvasive detection of macular pigments in the human eye.

PubMed

Gellermann, Werner; Bernstein, Paul S

2004-01-01

There is currently strong interest in developing noninvasive technologies for the detection of macular carotenoid pigments in the human eye. These pigments, consisting of lutein and zeaxanthin, are taken up from the diet and are thought to play an important role in the prevention of age-related macular degeneration, the leading cause of blindness in the elderly in the Western world. It may be possible to prevent or delay the onset of this debilitating disease with suitable dietary intervention strategies. We review the most commonly used detection techniques based on heterochromatic flicker photometry, fundus reflectometry, and autofluorescense techniques and put them in perspective with recently developed more molecule-specific Raman detection methods. (c) 2004 Society of Photo-Optical Instrumentation Engineers.

Oxygen detection using the laser diode absorption technique

NASA Technical Reports Server (NTRS)

Disimile, P. J.; Fox, C. W.

1991-01-01

Accurate measurement of the concentration and flow rate of gaseous oxygen is becoming of greater importance. The detection technique presented is based on the principal of light absorption by the Oxygen A-Band. Oxygen molecules have characteristics which attenuate radiation in the 759-770 nm wavelength range. With an ability to measure changes in the relative light transmission to less than 0.01 percent, a sensitive optical gas detection system was configured. This system is smaller in size and light in weight, has low energy requirements and has a rapid response time. In this research program, the application of temperature tuning laser diodes and their ability to be wavelength shifted to a selected absorption spectral peak has allowed concentrations as low as 1300 ppm to be detected.

The increasing application of multiplex nucleic acid detection tests to the diagnosis of syndromic infections.

PubMed

Gray, J; Coupland, L J

2014-01-01

On 14 January 2013, the US Food and Drug Administration (FDA) announced permission for a multiplex nucleic acid test, the xTAG® Gastrointestinal Pathogen Panel (GPP) (Luminex Corporation, USA), which simultaneously detects 11 common viral, bacterial and parasitic causes of infectious gastroenteritis, to be marketed in the USA. This announcement reflects the current move towards the development and commercialization of detection technologies based on nucleic acid amplification techniques for diagnosis of syndromic infections. We discuss the limitations and advantages of nucleic acid amplification techniques and the recent advances in Conformité Européene - in-vitro diagnostic (CE-IVD)-approved multiplex real-time PCR kits for the simultaneous detection of multiple targets within the clinical diagnostics market.

Four-Wave-Mixing Approach to In Situ Detection of Nanoparticles

DOE PAGES

Gerakis, Alexandros; Yeh, Yao -Wen; Shneider, Mikhail N.; ...

2018-01-29

Here, we report on the development and experimental validation of a laser-based technique which uses coherent Rayleigh-Brillouin scattering (CRBS) to detect nanoparticles with characteristic sizes ranging from the atomic scale to tens of nanometers. This technique is aimed (nonexclusively) at the detection of nanoparticles produced by volumetric nanoparticle synthesis methods. Using CRBS, carbon nanoparticles of dimensions less than 10 nm and concentrations of 10 10 cm –3 are detected in situ in a carbon arc discharge with graphite electrodes. This four-wave-mixing approach should enable advances in the understanding of nanoparticle growth that could potentially lead to improved modeling of themore » growth mechanisms, and thus to improve synthesis selectivity of nanoparticles and yield.« less

Comparison of ELISA and RT-PCR for the detection of Prunus necrotic ring spot virus and prune dwarf virus in almond (Prunus dulcis).

PubMed

Mekuria, Genet; Ramesh, Sunita A; Alberts, Evita; Bertozzi, Terry; Wirthensohn, Michelle; Collins, Graham; Sedgley, Margaret

2003-12-01

A technique based on the reverse transcriptase-polymerase chain reaction (RT-PCR) has been developed to detect the presence of Prunus necrotic ringspot virus (PNRSV) and prune dwarf virus (PDV) simultaneously in almond. This paper presents the results of a 3-year study comparing both enzyme-linked immunosorbent assay (ELISA) and RT-PCR for the detection of PNRSV and PDV using 175 almond leaf samples. Multiplex RT-PCR was found to be more sensitive than ELISA, especially when followed by nested PCR for the detection of PDV. The RT-PCR technique has the added advantage that plant material can be tested at any time throughout the growing season.

Fire detection behind a wall by using microwave techniques

NASA Astrophysics Data System (ADS)

Alkurt, Fatih Özkan; Baǧmancı, Mehmet; Karaaslan, Muharrem; Bakır, Mehmet; Altıntaş, Olcay; Karadaǧ, Faruk; Akgöl, Oǧuzhan; Ünal, Emin

2018-02-01

In this work, detection of the fire location behind a wall by using microwave techniques is illustrated. According to Planck's Law, Blackbody emits electromagnetic radiation in the microwave region of the electromagnetic spectrum. This emitted waves penetrates all materials except that metals. These radiated waves can be detected by using directional and high gain antennas. The proposed antenna consists of a simple microstrip patch antenna and a 2×2 microstrip patch antenna array. FIT based simulation results show that 2×2 array antenna can absorb emitted power from a fire source which is located behind a wall. This contribution can be inspirational for further works.

Inspection applications with higher electron beam energies

NASA Astrophysics Data System (ADS)

Norman, D. R.; Jones, J. L.; Yoon, W. Y.; Haskell, K. J.; Sterbentz, J. W.; Zabriskie, J. M.; Hunt, A. W.; Harmon, F.; Kinlaw, M. T.

2005-12-01

The Idaho National Laboratory has developed prototype shielded nuclear material detection systems based on pulsed photonuclear assessment (PPA) techniques for the inspection of cargo containers. During this work, increased nuclear material detection capabilities have been demonstrated at higher electron beam energies than those allowed by federal regulations for cargo inspection. This paper gives a general overview of a nuclear material detection system, the PPA technique and discusses the benefits of using these higher energies. This paper also includes a summary of the numerical and test results from LINAC operations up to 24 MeV and discusses some of the federal energy limitations associated with cargo inspection.

Resolution-improved in situ DNA hybridization detection based on microwave photonic interrogation.

PubMed

Cao, Yuan; Guo, Tuan; Wang, Xudong; Sun, Dandan; Ran, Yang; Feng, Xinhuan; Guan, Bai-ou

2015-10-19

In situ bio-sensing system based on microwave photonics filter (MPF) interrogation method with improved resolution is proposed and experimentally demonstrated. A microfiber Bragg grating (mFBG) is used as sensing probe for DNA hybridization detection. Different from the traditional wavelength monitoring technique, we use the frequency interrogation scheme for resolution-improved bio-sensing detection. Experimental results show that the frequency shift of MPF notch presents a linear response to the surrounding refractive index (SRI) change over the range of 1.33 to 1.38, with a SRI resolution up to 2.6 × 10(-5) RIU, which has been increased for almost two orders of magnitude compared with the traditional fundamental mode monitoring technique (~3.6 × 10(-3) RIU). Due to the high Q value (about 27), the whole process of DNA hybridization can be in situ monitored. The proposed MPF-based bio-sensing system provides a new interrogation method over the frequency domain with improved sensing resolution and rapid interrogation rate for biochemical and environmental measurement.

Measuring Time-of-Flight in an Ultrasonic LPS System Using Generalized Cross-Correlation

PubMed Central

Villladangos, José Manuel; Ureña, Jesús; García, Juan Jesús; Mazo, Manuel; Hernández, Álvaro; Jiménez, Ana; Ruíz, Daniel; De Marziani, Carlos

2011-01-01

In this article, a time-of-flight detection technique in the frequency domain is described for an ultrasonic Local Positioning System (LPS) based on encoded beacons. Beacon transmissions have been synchronized and become simultaneous by means of the DS-CDMA (Direct-Sequence Code Division Multiple Access) technique. Every beacon has been associated to a 255-bit Kasami code. The detection of signal arrival instant at the receiver, from which the distance to each beacon can be obtained, is based on the application of the Generalized Cross-Correlation (GCC), by using the cross-spectral density between the received signal and the sequence to be detected. Prior filtering to enhance the frequency components around the carrier frequency (40 kHz) has improved estimations when obtaining the correlation function maximum, which implies an improvement in distance measurement precision. Positioning has been achieved by using hyperbolic trilateration, based on the Time Differences of Arrival (TDOA) between a reference beacon and the others. PMID:22346645

Measuring time-of-flight in an ultrasonic LPS system using generalized cross-correlation.

PubMed

Villladangos, José Manuel; Ureña, Jesús; García, Juan Jesús; Mazo, Manuel; Hernández, Alvaro; Jiménez, Ana; Ruíz, Daniel; De Marziani, Carlos

2011-01-01

In this article, a time-of-flight detection technique in the frequency domain is described for an ultrasonic local positioning system (LPS) based on encoded beacons. Beacon transmissions have been synchronized and become simultaneous by means of the DS-CDMA (direct-sequence code Division multiple access) technique. Every beacon has been associated to a 255-bit Kasami code. The detection of signal arrival instant at the receiver, from which the distance to each beacon can be obtained, is based on the application of the generalized cross-correlation (GCC), by using the cross-spectral density between the received signal and the sequence to be detected. Prior filtering to enhance the frequency components around the carrier frequency (40 kHz) has improved estimations when obtaining the correlation function maximum, which implies an improvement in distance measurement precision. Positioning has been achieved by using hyperbolic trilateration, based on the time differences of arrival (TDOA) between a reference beacon and the others.

In field application of differential Die-Away time technique for detecting gram quantities of fissile materials

NASA Astrophysics Data System (ADS)

Remetti, Romolo; Gandolfo, Giada; Lepore, Luigi; Cherubini, Nadia

2017-10-01

In the frame of Chemical, Biological, Radiological, and Nuclear defense European activities, the ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development, is proposing the Neutron Active Interrogation system (NAI), a device designed to find transuranic-based Radioactive Dispersal Devices hidden inside suspected packages. It is based on Differential Die-Away time Analysis, an active neutron technique targeted in revealing the presence of fissile material through detection of induced fission neutrons. Several Monte Carlo simulations, carried out by MCNPX code, and the development of ad-hoc design methods, have led to the realization of a first prototype based on a 14 MeV d-t neutron generator coupled with a tailored moderating structure, and an array of helium-3 neutron detectors. The complete system is characterized by easy transportability, light weight, and real-time response. First results have shown device's capability to detect gram quantities of fissile materials.

One-Class Classification-Based Real-Time Activity Error Detection in Smart Homes.

PubMed

Das, Barnan; Cook, Diane J; Krishnan, Narayanan C; Schmitter-Edgecombe, Maureen

2016-08-01

Caring for individuals with dementia is frequently associated with extreme physical and emotional stress, which often leads to depression. Smart home technology and advances in machine learning techniques can provide innovative solutions to reduce caregiver burden. One key service that caregivers provide is prompting individuals with memory limitations to initiate and complete daily activities. We hypothesize that sensor technologies combined with machine learning techniques can automate the process of providing reminder-based interventions. The first step towards automated interventions is to detect when an individual faces difficulty with activities. We propose machine learning approaches based on one-class classification that learn normal activity patterns. When we apply these classifiers to activity patterns that were not seen before, the classifiers are able to detect activity errors, which represent potential prompt situations. We validate our approaches on smart home sensor data obtained from older adult participants, some of whom faced difficulties performing routine activities and thus committed errors.

Fiber-ring laser-based intracavity photoacoustic spectroscopy for trace gas sensing.

PubMed

Wang, Qiang; Wang, Zhen; Chang, Jun; Ren, Wei

2017-06-01

We demonstrated a novel trace gas sensing method based on fiber-ring laser intracavity photoacoustic spectroscopy. This spectroscopic technique is a merging of photoacoustic spectroscopy (PAS) with a fiber-ring cavity for sensitive and all-fiber gas detection. A transmission-type PAS gas cell (resonant frequency f₀=2.68  kHz) was placed inside the fiber-ring laser to fully utilize the intracavity laser power. The PAS signal was excited by modulating the laser wavelength at f₀/2 using a custom-made fiber Bragg grating-based modulator. We used this spectroscopic technique to detect acetylene (C₂H₂) at 1531.6 nm as a proof of principle. With a low Q-factor (4.9) of the PAS cell, our sensor achieved a good linear response (R²=0.996) to C₂H₂ concentration and a minimum detection limit of 390 ppbv at 2-s response time.

Mass spectrometry for fragment screening.

PubMed

Chan, Daniel Shiu-Hin; Whitehouse, Andrew J; Coyne, Anthony G; Abell, Chris

2017-11-08

Fragment-based approaches in chemical biology and drug discovery have been widely adopted worldwide in both academia and industry. Fragment hits tend to interact weakly with their targets, necessitating the use of sensitive biophysical techniques to detect their binding. Common fragment screening techniques include differential scanning fluorimetry (DSF) and ligand-observed NMR. Validation and characterization of hits is usually performed using a combination of protein-observed NMR, isothermal titration calorimetry (ITC) and X-ray crystallography. In this context, MS is a relatively underutilized technique in fragment screening for drug discovery. MS-based techniques have the advantage of high sensitivity, low sample consumption and being label-free. This review highlights recent examples of the emerging use of MS-based techniques in fragment screening. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Convolution neural-network-based detection of lung structures

NASA Astrophysics Data System (ADS)

Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.

1994-05-01

Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

NASA Astrophysics Data System (ADS)

Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

2017-02-01

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

A Novel Rules Based Approach for Estimating Software Birthmark

PubMed Central

Binti Alias, Norma; Anwar, Sajid

2015-01-01

Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363

Aircraft propeller induced structure-borne noise

NASA Technical Reports Server (NTRS)

Unruh, James F.

1989-01-01

A laboratory-based test apparatus employing components typical of aircraft construction was developed that would allow the study of structure-borne noise transmission due to propeller induced wake/vortex excitation of in-wake structural appendages. The test apparatus was employed to evaluate several aircraft installation effects (power plant placement, engine/nacelle mass loading, and wing/fuselage attachment methods) and several structural response modifications for structure-borne noise control (the use of wing blocking mass/fuel, wing damping treaments, and tuned mechanical dampers). Most important was the development of in-flight structure-borne noise transmission detection techniques using a combination of ground-based frequency response function testing and in-flight structural response measurement. Propeller wake/vortex excitation simulation techniques for improved ground-based testing were also developed to support the in-flight structure-borne noise transmission detection development.

Microaneurysm detection with radon transform-based classification on retina images.

PubMed

Giancardo, L; Meriaudeau, F; Karnowski, T P; Li, Y; Tobin, K W; Chaum, E

2011-01-01

The creation of an automatic diabetic retinopathy screening system using retina cameras is currently receiving considerable interest in the medical imaging community. The detection of microaneurysms is a key element in this effort. In this work, we propose a new microaneurysms segmentation technique based on a novel application of the radon transform, which is able to identify these lesions without any previous knowledge of the retina morphological features and with minimal image preprocessing. The algorithm has been evaluated on the Retinopathy Online Challenge public dataset, and its performance compares with the best current techniques. The performance is particularly good at low false positive ratios, which makes it an ideal candidate for diabetic retinopathy screening systems.

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.

Fungal Diversity in Tomato Rhizosphere Soil under Conventional and Desert Farming Systems

PubMed Central

Kazerooni, Elham A.; Maharachchikumbura, Sajeewa S. N.; Rethinasamy, Velazhahan; Al-Mahrouqi, Hamed; Al-Sadi, Abdullah M.

2017-01-01

This study examined fungal diversity and composition in conventional (CM) and desert farming (DE) systems in Oman. Fungal diversity in the rhizosphere of tomato was assessed using 454-pyrosequencing and culture-based techniques. Both techniques produced variable results in terms of fungal diversity, with 25% of the fungal classes shared between the two techniques. In addition, pyrosequencing recovered more taxa compared to direct plating. These findings could be attributed to the ability of pyrosequencing to recover taxa that cannot grow or are slow growing on culture media. Both techniques showed that fungal diversity in the conventional farm was comparable to that in the desert farm. However, the composition of fungal classes and taxa in the two farming systems were different. Pyrosequencing revealed that Microsporidetes and Dothideomycetes are the two most common fungal classes in CM and DE, respectively. However, the culture-based technique revealed that Eurotiomycetes was the most abundant class in both farming systems and some classes, such as Microsporidetes, were not detected by the culture-based technique. Although some plant pathogens (e.g., Pythium or Fusarium) were detected in the rhizosphere of tomato, the majority of fungal species in the rhizosphere of tomato were saprophytes. Our study shows that the cultivation system may have an impact on fungal diversity. The factors which affected fungal diversity in both farms are discussed. PMID:28824590

DETECTION OF DNA DAMAGE USING MELTING ANALYSIS TECHNIQUES

EPA Science Inventory

A rapid and simple fluorescence screening assay for UV radiation-, chemical-, and enzyme-induced DNA damage is reported. This assay is based on a melting/annealing analysis technique and has been used with both calf thymus DNA and plasmid DNA (puc 19 plasmid from E. coli). DN...

Nonlinear multi-photon laser wave-mixing optical detection in microarrays and microchips for ultrasensitive detection and separation of biomarkers for cancer and neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Iwabuchi, Manna; Hetu, Marcel; Maxwell, Eric; Pradel, Jean S.; Ramos, Sashary; Tong, William G.

2015-09-01

Multi-photon degenerate four-wave mixing is demonstrated as an ultrasensitive absorption-based optical method for detection, separation and identification of biomarker proteins in the development of early diagnostic methods for HIV- 1, cancer and neurodegenerative diseases using compact, portable microarrays and capillary- or microchip-based chemical separation systems that offer high chemical specificity levels. The wave-mixing signal has a quadratic dependence on concentration, and hence, it allows more reliable monitoring of smaller changes in analyte properties. Our wave-mixing detection sensitivity is comparable or better than those of current methods including enzyme-linked immunoassay for clinical diagnostic and screening. Detection sensitivity is excellent since the wave-mixing signal is a coherent laser-like beam that can be collected with virtually 100% collection efficiency with high S/N. Our analysis time is short (1-15 minutes) for molecular weight-based protein separation as compared to that of a conventional separation technique, e.g., sodium dodecyl sulfate-polyacrylamide gel electrophoresis. When ultrasensitive wavemixing detection is paired with high-resolution capillary- or microchip-based separation systems, biomarkers can be separated and identified at the zepto- and yocto-mole levels for a wide range of analytes. Specific analytes can be captured in a microchannel through the use of antibody-antigen interactions that provide better chemical specificity as compared to size-based separation alone. The technique can also be combined with immune-precipitation and a multichannel capillary array for high-throughput analysis of more complex protein samples. Wave mixing allows the use of chromophores and absorption-modifying tags, in addition to conventional fluorophores, for online detection of immunecomplexes related to cancer.

Visual detection technique for efficient screening and isolation of Salmonella based on a novel enrichment assay using chromatography membrane.

PubMed

Tang, F; Xiong, Y; Zhang, H; Wu, K; Xiang, Y; Shao, J-B; Ai, H-W; Xiang, Y-P; Zheng, X-L; Lv, J-R; Sun, H; Bao, L-S; Zhang, Z; Hu, H-B; Zhang, J-Y; Chen, L; Lu, J; Liu, W-Y; Mei, H; Ma, Y; Xu, C-F; Fang, A-Y; Gu, M; Xu, C-Y; Chen, Y; Chen, Z; Sun, Z-Y

2016-03-01

To detect Salmonella more efficiently and isolate strains more easily, a novel and simple detection method that uses an enrichment assay and two chromogenic reactions on a chromatography membrane was developed. Grade 3 chromatography paper is used as functionalized solid phase support (SPS), which contains specially optimized medium. One reaction for screening is based on the sulfate-reducing capacity of Salmonella. Hydrogen sulfide (H2S) generated by Salmonella reacts with ammonium ferric citrate to produce black colored ferrous sulfide. Another reaction is based on Salmonella C8 esterase that is unique for Enterobacteriaceae except Serratia and interacts with 4-methylumbelliferyl caprylate (MUCAP) to produce fluorescent umbelliferone, which is visible under ultraviolet light. A very low detection limit (10(1) CFU ml(-1)) for Salmonella was achieved on the background of 10(5) CFU ml(-1) Escherichia coli. More importantly, testing with more than 1,000 anal samples indicated that our method has a high positive detection rate and is relatively low cost, compared with the traditional culture-based method. It took only 1 day for the preliminary screening and 2 days to efficiently isolate the Salmonella cells, indicating that the new assay is specific, rapid, and simple for Salmonella detection. In contrast to the traditional culture-based method, this method can be easily used to screen and isolate targeted strains with the naked eye. The results of quantitative and comparative experiments showed that the visual detection technique is an efficient alternative method for the screening of Salmonella spp. in many applications of large-sized samples related to public health surveillance.