Pothole Detection System Using a Black-box Camera.

PubMed

Jo, Youngtae; Ryu, Seungki

2015-11-19

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

Reducing impaired-driving recidivism using advanced vehicle-based alcohol detection systems : a report to Congress

DOT National Transportation Integrated Search

2007-12-01

Vehicle-based alcohol detection systems use technologies designed to detect the presence of alcohol in a driver. Technology suitable for use in all vehicles that will detect an impaired driver faces many challenges including public acceptability, pas...

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

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

PubMed

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

2017-01-01

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

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

PubMed

Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang

2017-10-13

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

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

Aircraft IR/acoustic detection evaluation. Volume 2: Development of a ground-based acoustic sensor system for the detection of subsonic jet-powered aircraft

NASA Technical Reports Server (NTRS)

Kraft, Robert E.

1992-01-01

The design and performance of a ground-based acoustic sensor system for the detection of subsonic jet-powered aircraft is described and specified. The acoustic detection system performance criteria will subsequently be used to determine target detection ranges for the subject contract. Although the defined system has never been built and demonstrated in the field, the design parameters were chosen on the basis of achievable technology and overall system practicality. Areas where additional information is needed to substantiate the design are identified.

Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle

PubMed Central

Chen, Long; Li, Qingquan; Li, Ming; Zhang, Liang; Mao, Qingzhou

2012-01-01

This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. The results of experiments validate the effectiveness of the proposed algorithms and the whole system.

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.

Microcontroller based driver alertness detection systems to detect drowsiness

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

PubMed

Housh, Mashor; Ohar, Ziv

2017-03-01

The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

A stereo vision-based obstacle detection system in vehicles

NASA Astrophysics Data System (ADS)

Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

2008-02-01

Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

Novel vehicle detection system based on stacked DoG kernel and AdaBoost

PubMed Central

Kang, Hyun Ho; Lee, Seo Won; You, Sung Hyun

2018-01-01

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)–based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles—of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions. PMID:29513727

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

An Android malware detection system based on machine learning

NASA Astrophysics Data System (ADS)

Wen, Long; Yu, Haiyang

2017-08-01

The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

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

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

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

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

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

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

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

A Survey on Anomaly Based Host Intrusion Detection System

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

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

Research on a Denial of Service (DoS) Detection System Based on Global Interdependent Behaviors in a Sensor Network Environment

PubMed Central

Song, Jae-gu; Jung, Sungmo; Kim, Jong Hyun; Seo, Dong Il; Kim, Seoksoo

2010-01-01

This research suggests a Denial of Service (DoS) detection method based on the collection of interdependent behavior data in a sensor network environment. In order to collect the interdependent behavior data, we use a base station to analyze traffic and behaviors among nodes and introduce methods of detecting changes in the environment with precursor symptoms. The study presents a DoS Detection System based on Global Interdependent Behaviors and shows the result of detecting a sensor carrying out DoS attacks through the test-bed. PMID:22163475

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

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

PubMed

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

2017-04-01

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

An improved three-dimensional non-scanning laser imaging system based on digital micromirror device

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Lei, Jieyu; Zhai, Yu; Timofeev, Alexander N.

2018-01-01

Nowadays, there are two main methods to realize three-dimensional non-scanning laser imaging detection, which are detection method based on APD and detection method based on Streak Tube. However, the detection method based on APD possesses some disadvantages, such as small number of pixels, big pixel interval and complex supporting circuit. The detection method based on Streak Tube possesses some disadvantages, such as big volume, bad reliability and high cost. In order to resolve the above questions, this paper proposes an improved three-dimensional non-scanning laser imaging system based on Digital Micromirror Device. In this imaging system, accurate control of laser beams and compact design of imaging structure are realized by several quarter-wave plates and a polarizing beam splitter. The remapping fiber optics is used to sample the image plane of receiving optical lens, and transform the image into line light resource, which can realize the non-scanning imaging principle. The Digital Micromirror Device is used to convert laser pulses from temporal domain to spatial domain. The CCD with strong sensitivity is used to detect the final reflected laser pulses. In this paper, we also use an algorithm which is used to simulate this improved laser imaging system. In the last, the simulated imaging experiment demonstrates that this improved laser imaging system can realize three-dimensional non-scanning laser imaging detection.

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

NASA Astrophysics Data System (ADS)

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

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

Real-time DNA Amplification and Detection System Based on a CMOS Image Sensor.

PubMed

Wang, Tiantian; Devadhasan, Jasmine Pramila; Lee, Do Young; Kim, Sanghyo

2016-01-01

In the present study, we developed a polypropylene well-integrated complementary metal oxide semiconductor (CMOS) platform to perform the loop mediated isothermal amplification (LAMP) technique for real-time DNA amplification and detection simultaneously. An amplification-coupled detection system directly measures the photon number changes based on the generation of magnesium pyrophosphate and color changes. The photon number decreases during the amplification process. The CMOS image sensor observes the photons and converts into digital units with the aid of an analog-to-digital converter (ADC). In addition, UV-spectral studies, optical color intensity detection, pH analysis, and electrophoresis detection were carried out to prove the efficiency of the CMOS sensor based the LAMP system. Moreover, Clostridium perfringens was utilized as proof-of-concept detection for the new system. We anticipate that this CMOS image sensor-based LAMP method will enable the creation of cost-effective, label-free, optical, real-time and portable molecular diagnostic devices.

Vision-Based People Detection System for Heavy Machine Applications

PubMed Central

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-01

This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

Vision-Based People Detection System for Heavy Machine Applications.

PubMed

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-20

This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance.

An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

PubMed

He, Jian; Bai, Shuang; Wang, Xiaoyi

2017-06-16

Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

Intensity-based readout of resonant-waveguide grating biosensors: Systems and nanostructures

NASA Astrophysics Data System (ADS)

Paulsen, Moritz; Jahns, Sabrina; Gerken, Martina

2017-09-01

Resonant waveguide gratings (RWG) - also called photonic crystal slabs (PCS) - have been established as reliable optical transducers for label-free biochemical assays as well as for cell-based assays. Current readout systems are based on mechanical scanning and spectrometric measurements with system sizes suitable for laboratory equipment. Here, we review recent progress in compact intensity-based readout systems for point-of-care (POC) applications. We briefly introduce PCSs as sensitive optical transducers and introduce different approaches for intensity-based readout systems. Photometric measurements have been realized with a simple combination of a light source and a photodetector. Recently a 96-channel, intensity-based readout system for both biochemical interaction analyses as well as cellular assays was presented employing the intensity change of a near cut-off mode. As an alternative for multiparametric detection, a camera system for imaging detection has been implemented. A portable, camera-based system of size 13 cm × 4.9 cm × 3.5 cm with six detection areas on an RWG surface area of 11 mm × 7 mm has been demonstrated for the parallel detection of six protein binding kinetics. The signal-to-noise ratio of this system corresponds to a limit of detection of 168 M (24 ng/ml). To further improve the signal-to-noise ratio advanced nanostructure designs are investigated for RWGs. Here, results on multiperiodic and deterministic aperiodic nanostructures are presented. These advanced nanostructures allow for the design of the number and wavelengths of the RWG resonances. In the context of intensity-based readout systems they are particularly interesting for the realization of multi-LED systems. These recent trends suggest that compact point-of-care systems employing disposable test chips with RWG functional areas may reach market in the near future.

A quantification of the effectiveness of EPID dosimetry and software-based plan verification systems in detecting incidents in radiotherapy

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

Bojechko, Casey; Phillps, Mark; Kalet, Alan

Purpose: Complex treatments in radiation therapy require robust verification in order to prevent errors that can adversely affect the patient. For this purpose, the authors estimate the effectiveness of detecting errors with a “defense in depth” system composed of electronic portal imaging device (EPID) based dosimetry and a software-based system composed of rules-based and Bayesian network verifications. Methods: The authors analyzed incidents with a high potential severity score, scored as a 3 or 4 on a 4 point scale, recorded in an in-house voluntary incident reporting system, collected from February 2012 to August 2014. The incidents were categorized into differentmore » failure modes. The detectability, defined as the number of incidents that are detectable divided total number of incidents, was calculated for each failure mode. Results: In total, 343 incidents were used in this study. Of the incidents 67% were related to photon external beam therapy (EBRT). The majority of the EBRT incidents were related to patient positioning and only a small number of these could be detected by EPID dosimetry when performed prior to treatment (6%). A large fraction could be detected by in vivo dosimetry performed during the first fraction (74%). Rules-based and Bayesian network verifications were found to be complimentary to EPID dosimetry, able to detect errors related to patient prescriptions and documentation, and errors unrelated to photon EBRT. Combining all of the verification steps together, 91% of all EBRT incidents could be detected. Conclusions: This study shows that the defense in depth system is potentially able to detect a large majority of incidents. The most effective EPID-based dosimetry verification is in vivo measurements during the first fraction and is complemented by rules-based and Bayesian network plan checking.« less

Monte Carlo simulation of explosive detection system based on a Deuterium-Deuterium (D-D) neutron generator.

PubMed

Bergaoui, K; Reguigui, N; Gary, C K; Brown, C; Cremer, J T; Vainionpaa, J H; Piestrup, M A

2014-12-01

An explosive detection system based on a Deuterium-Deuterium (D-D) neutron generator has been simulated using the Monte Carlo N-Particle Transport Code (MCNP5). Nuclear-based explosive detection methods can detect explosives by identifying their elemental components, especially nitrogen. Thermal neutron capture reactions have been used for detecting prompt gamma emission (10.82MeV) following radiative neutron capture by (14)N nuclei. The explosive detection system was built based on a fully high-voltage-shielded, axial D-D neutron generator with a radio frequency (RF) driven ion source and nominal yield of about 10(10) fast neutrons per second (E=2.5MeV). Polyethylene and paraffin were used as moderators with borated polyethylene and lead as neutron and gamma ray shielding, respectively. The shape and the thickness of the moderators and shields are optimized to produce the highest thermal neutron flux at the position of the explosive and the minimum total dose at the outer surfaces of the explosive detection system walls. In addition, simulation of the response functions of NaI, BGO, and LaBr3-based γ-ray detectors to different explosives is described. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adverse event detection (AED) system for continuously monitoring and evaluating structural health status

NASA Astrophysics Data System (ADS)

Yun, Jinsik; Ha, Dong Sam; Inman, Daniel J.; Owen, Robert B.

2011-03-01

Structural damage for spacecraft is mainly due to impacts such as collision of meteorites or space debris. We present a structural health monitoring (SHM) system for space applications, named Adverse Event Detection (AED), which integrates an acoustic sensor, an impedance-based SHM system, and a Lamb wave SHM system. With these three health-monitoring methods in place, we can determine the presence, location, and severity of damage. An acoustic sensor continuously monitors acoustic events, while the impedance-based and Lamb wave SHM systems are in sleep mode. If an acoustic sensor detects an impact, it activates the impedance-based SHM. The impedance-based system determines if the impact incurred damage. When damage is detected, it activates the Lamb wave SHM system to determine the severity and location of the damage. Further, since an acoustic sensor dissipates much less power than the two SHM systems and the two systems are activated only when there is an acoustic event, our system reduces overall power dissipation significantly. Our prototype system demonstrates the feasibility of the proposed concept.

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.

Video-based real-time on-street parking occupancy detection system

NASA Astrophysics Data System (ADS)

Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

2013-10-01

Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

Design of oil pipeline leak detection and communication system based on optical fiber technology

NASA Astrophysics Data System (ADS)

Tu, Yaqing; Chen, Huabo

1999-08-01

The integrity of oil pipeline is always a major concern of operators. Pipeline leak not only leads to loss of oil, but pollutes environment. A new pipeline leak detection and communication system based on optical fiber technology to ensure the pipeline reliability is presented. Combined direct leak detection method with an indirect one, the system will greatly reduce the rate of false alarm. According, to the practical features of oil pipeline,the pipeline communication system is designed employing the state-of-the-art optic fiber communication technology. The system has such feature as high location accuracy of leak detection, good real-time characteristic, etc. which overcomes the disadvantages of traditional leak detection methods and communication system effectively.

Study on nondestructive detection system based on x-ray for wire ropes conveyer belt

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Wan, Peng; Li, Jie

2008-03-01

A nondestructive detection system based on X-ray for wire ropes conveyer belt is designed by X-ray detection technology. In this paper X-ray detection principle is analyzed, a design scheme of the system is presented; image processing of conveyer belt is researched and image processing algorithms are given; X-ray acquisition receiving board is designed with the use of FPGA and DSP; the software of the system is programmed by C#.NET on WINXP/WIN2000 platform. The experiment indicates the system can implement remote real-time detection of wire ropes conveyer belt images, find faults and give an alarm in time. The system is direct perceived, strong real-time and high accurate. It can be used for fault detection of wire ropes conveyer belts in mines, ports, terminals and other fields.

A computer-aided detection (CAD) system with a 3D algorithm for small acute intracranial hemorrhage

NASA Astrophysics Data System (ADS)

Wang, Ximing; Fernandez, James; Deshpande, Ruchi; Lee, Joon K.; Chan, Tao; Liu, Brent

2012-02-01

Acute Intracranial hemorrhage (AIH) requires urgent diagnosis in the emergency setting to mitigate eventual sequelae. However, experienced radiologists may not always be available to make a timely diagnosis. This is especially true for small AIH, defined as lesion smaller than 10 mm in size. A computer-aided detection (CAD) system for the detection of small AIH would facilitate timely diagnosis. A previously developed 2D algorithm shows high false positive rates in the evaluation based on LAC/USC cases, due to the limitation of setting up correct coordinate system for the knowledge-based classification system. To achieve a higher sensitivity and specificity, a new 3D algorithm is developed. The algorithm utilizes a top-hat transformation and dynamic threshold map to detect small AIH lesions. Several key structures of brain are detected and are used to set up a 3D anatomical coordinate system. A rule-based classification of the lesion detected is applied based on the anatomical coordinate system. For convenient evaluation in clinical environment, the CAD module is integrated with a stand-alone system. The CAD is evaluated by small AIH cases and matched normal collected in LAC/USC. The result of 3D CAD and the previous 2D CAD has been compared.

Detection system of capillary array electrophoresis microchip based on optical fiber

NASA Astrophysics Data System (ADS)

Yang, Xiaobo; Bai, Haiming; Yan, Weiping

2009-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Evaluation of three fully automated immunoassay systems for detection of IgA anti-beta 2-glycoprotein I antibodies.

PubMed

Pérez, D; Martínez-Flores, J A; Serrano, M; Lora, D; Paz-Artal, E; Morales, J M; Serrano, A

2016-10-01

In recent years, we have been witnessing increased clinical interest in the determination of IgA anti-beta 2-glycoprotein I (aB2GPI) antibodies as well as increased demand for this test. Some ELISA-based diagnostic systems for IgA aB2GPI antibodies detection are suboptimal to detect it. The aim of our study was to determine whether the diagnostic yield of modern detection systems based on automatic platforms to measure IgA aB2GPI is equivalent to that of the well-optimized ELISA-based assays. In total, 130 patients were analyzed for IgA aB2GPI by three fully automated immunoassays using an ELISA-based assay as reference. The three systems were also analyzed for IgG aB2GPI with 58 patients. System 1 was able to detect IgA aB2GPI with good sensitivity and kappa index (99% and 0.72, respectively). The other two systems had also poor sensitivity (20% and 15%) and kappa index (0.10 and 0.07), respectively. On the other hand, kappa index for IgG aB2GPI was >0.89 in the three systems. Some analytical methods to detect IgA aB2GPI are suboptimal as well as some ELISA-based diagnostic systems. It is important that the scientific community work to standardize analytical methods to determine IgA aB2GPI antibodies. © 2016 John Wiley & Sons Ltd.

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

PubMed

Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

2018-04-01

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Field programmable gate array based fuzzy neural signal processing system for differential diagnosis of QRS complex tachycardia and tachyarrhythmia in noisy ECG signals.

PubMed

Chowdhury, Shubhajit Roy

2012-04-01

The paper reports of a Field Programmable Gate Array (FPGA) based embedded system for detection of QRS complex in a noisy electrocardiogram (ECG) signal and thereafter differential diagnosis of tachycardia and tachyarrhythmia. The QRS complex has been detected after application of entropy measure of fuzziness to build a detection function of ECG signal, which has been previously filtered to remove power line interference and base line wander. Using the detected QRS complexes, differential diagnosis of tachycardia and tachyarrhythmia has been performed. The entire algorithm has been realized in hardware on an FPGA. Using the standard CSE ECG database, the algorithm performed highly effectively. The performance of the algorithm in respect of QRS detection with sensitivity (Se) of 99.74% and accuracy of 99.5% is achieved when tested using single channel ECG with entropy criteria. The performance of the QRS detection system has been compared and found to be better than most of the QRS detection systems available in literature. Using the system, 200 patients have been diagnosed with an accuracy of 98.5%.

Interference and deception detection technology of satellite navigation based on deep learning

NASA Astrophysics Data System (ADS)

Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

2017-10-01

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

Edge detection based on computational ghost imaging with structured illuminations

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Xiang, Dong; Liu, Xuemei; Zhou, Xin; Bing, Pibin

2018-03-01

Edge detection is one of the most important tools to recognize the features of an object. In this paper, we propose an optical edge detection method based on computational ghost imaging (CGI) with structured illuminations which are generated by an interference system. The structured intensity patterns are designed to make the edge of an object be directly imaged from detected data in CGI. This edge detection method can extract the boundaries for both binary and grayscale objects in any direction at one time. We also numerically test the influence of distance deviations in the interference system on edge extraction, i.e., the tolerance of the optical edge detection system to distance deviation. Hopefully, it may provide a guideline for scholars to build an experimental system.

Automatic identification of alpine mass movements based on seismic and infrasound signals

NASA Astrophysics Data System (ADS)

Schimmel, Andreas; Hübl, Johannes

2017-04-01

The automatic detection and identification of alpine mass movements like debris flows, debris floods or landslides gets increasing importance for mitigation measures in the densely populated and intensively used alpine regions. Since this mass movement processes emits characteristically seismic and acoustic waves in the low frequency range this events can be detected and identified based on this signals. So already several approaches for detection and warning systems based on seismic or infrasound signals has been developed. But a combination of both methods, which can increase detection probability and reduce false alarms is currently used very rarely and can serve as a promising method for developing an automatic detection and identification system. So this work presents an approach for a detection and identification system based on a combination of seismic and infrasound sensors, which can detect sediment related mass movements from a remote location unaffected by the process. The system is based on one infrasound sensor and one geophone which are placed co-located and a microcontroller where a specially designed detection algorithm is executed which can detect mass movements in real time directly at the sensor site. Further this work tries to get out more information from the seismic and infrasound spectrum produced by different sediment related mass movements to identify the process type and estimate the magnitude of the event. The system is currently installed and tested on five test sites in Austria, two in Italy and one in Switzerland as well as one in Germany. This high number of test sites is used to get a large database of very different events which will be the basis for a new identification method for alpine mass movements. These tests shows promising results and so this system provides an easy to install and inexpensive approach for a detection and warning system.

Image processing occupancy sensor

DOEpatents

Brackney, Larry J.

2016-09-27

A system and method of detecting occupants in a building automation system environment using image based occupancy detection and position determinations. In one example, the system includes an image processing occupancy sensor that detects the number and position of occupants within a space that has controllable building elements such as lighting and ventilation diffusers. Based on the position and location of the occupants, the system can finely control the elements to optimize conditions for the occupants, optimize energy usage, among other advantages.

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

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

Enhanced situational awareness in the maritime domain: an agent-based approach for situation management

NASA Astrophysics Data System (ADS)

Brax, Christoffer; Niklasson, Lars

2009-05-01

Maritime Domain Awareness is important for both civilian and military applications. An important part of MDA is detection of unusual vessel activities such as piracy, smuggling, poaching, collisions, etc. Today's interconnected sensorsystems provide us with huge amounts of information over large geographical areas which can make the operators reach their cognitive capacity and start to miss important events. We propose and agent-based situation management system that automatically analyse sensor information to detect unusual activity and anomalies. The system combines knowledge-based detection with data-driven anomaly detection. The system is evaluated using information from both radar and AIS sensors.

A Protocol Specification-Based Intrusion Detection System for VoIP and Its Evaluation

NASA Astrophysics Data System (ADS)

Phit, Thyda; Abe, Kôki

We propose an architecture of Intrusion Detection System (IDS) for VoIP using a protocol specification-based detection method to monitor the network traffics and alert administrator for further analysis of and response to suspicious activities. The protocol behaviors and their interactions are described by state machines. Traffic that behaves differently from the standard specifications are considered to be suspicious. The IDS has been implemented and simulated using OPNET Modeler, and verified to detect attacks. It was found that our system can detect typical attacks within a reasonable amount of delay time.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Fiber-Optic Based Compact Gas Leak Detection System

NASA Technical Reports Server (NTRS)

deGroot, Wim A.

1995-01-01

A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

Parameter Transient Behavior Analysis on Fault Tolerant Control System

NASA Technical Reports Server (NTRS)

Belcastro, Christine (Technical Monitor); Shin, Jong-Yeob

2003-01-01

In a fault tolerant control (FTC) system, a parameter varying FTC law is reconfigured based on fault parameters estimated by fault detection and isolation (FDI) modules. FDI modules require some time to detect fault occurrences in aero-vehicle dynamics. This paper illustrates analysis of a FTC system based on estimated fault parameter transient behavior which may include false fault detections during a short time interval. Using Lyapunov function analysis, the upper bound of an induced-L2 norm of the FTC system performance is calculated as a function of a fault detection time and the exponential decay rate of the Lyapunov function.

A web-based quantitative signal detection system on adverse drug reaction in China.

PubMed

Li, Chanjuan; Xia, Jielai; Deng, Jianxiong; Chen, Wenge; Wang, Suzhen; Jiang, Jing; Chen, Guanquan

2009-07-01

To establish a web-based quantitative signal detection system for adverse drug reactions (ADRs) based on spontaneous reporting to the Guangdong province drug-monitoring database in China. Using Microsoft Visual Basic and Active Server Pages programming languages and SQL Server 2000, a web-based system with three software modules was programmed to perform data preparation and association detection, and to generate reports. Information component (IC), the internationally recognized measure of disproportionality for quantitative signal detection, was integrated into the system, and its capacity for signal detection was tested with ADR reports collected from 1 January 2002 to 30 June 2007 in Guangdong. A total of 2,496 associations including known signals were mined from the test database. Signals (e.g., cefradine-induced hematuria) were found early by using the IC analysis. In addition, 291 drug-ADR associations were alerted for the first time in the second quarter of 2007. The system can be used for the detection of significant associations from the Guangdong drug-monitoring database and could be an extremely useful adjunct to the expert assessment of very large numbers of spontaneously reported ADRs for the first time in China.

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

DOE PAGES

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo; ...

2017-07-14

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

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

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

Attribute and topology based change detection in a constellation of previously detected objects

DOEpatents

Paglieroni, David W.; Beer, Reginald N.

2016-01-19

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

NASA Astrophysics Data System (ADS)

Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

2012-09-01

The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

Biosensor system-on-a-chip including CMOS-based signal processing circuits and 64 carbon nanotube-based sensors for the detection of a neurotransmitter.

PubMed

Lee, Byung Yang; Seo, Sung Min; Lee, Dong Joon; Lee, Minbaek; Lee, Joohyung; Cheon, Jun-Ho; Cho, Eunju; Lee, Hyunjoong; Chung, In-Young; Park, Young June; Kim, Suhwan; Hong, Seunghun

2010-04-07

We developed a carbon nanotube (CNT)-based biosensor system-on-a-chip (SoC) for the detection of a neurotransmitter. Here, 64 CNT-based sensors were integrated with silicon-based signal processing circuits in a single chip, which was made possible by combining several technological breakthroughs such as efficient signal processing, uniform CNT networks, and biocompatible functionalization of CNT-based sensors. The chip was utilized to detect glutamate, a neurotransmitter, where ammonia, a byproduct of the enzymatic reaction of glutamate and glutamate oxidase on CNT-based sensors, modulated the conductance signals to the CNT-based sensors. This is a major technological advancement in the integration of CNT-based sensors with microelectronics, and this chip can be readily integrated with larger scale lab-on-a-chip (LoC) systems for various applications such as LoC systems for neural networks.

Real-Time Model-Based Leak-Through Detection within Cryogenic Flow Systems

NASA Technical Reports Server (NTRS)

Walker, M.; Figueroa, F.

2015-01-01

The timely detection of leaks within cryogenic fuel replenishment systems is of significant importance to operators on account of the safety and economic impacts associated with material loss and operational inefficiencies. Associated loss in control of pressure also effects the stability and ability to control the phase of cryogenic fluids during replenishment operations. Current research dedicated to providing Prognostics and Health Management (PHM) coverage of such cryogenic replenishment systems has focused on the detection of leaks to atmosphere involving relatively simple model-based diagnostic approaches that, while effective, are unable to isolate the fault to specific piping system components. The authors have extended this research to focus on the detection of leaks through closed valves that are intended to isolate sections of the piping system from the flow and pressurization of cryogenic fluids. The described approach employs model-based detection of leak-through conditions based on correlations of pressure changes across isolation valves and attempts to isolate the faults to specific valves. Implementation of this capability is enabled by knowledge and information embedded in the domain model of the system. The approach has been used effectively to detect such leak-through faults during cryogenic operational testing at the Cryogenic Testbed at NASA's Kennedy Space Center.

Highly Portable, Sensor-Based System for Human Fall Monitoring.

PubMed

Mao, Aihua; Ma, Xuedong; He, Yinan; Luo, Jie

2017-09-13

Falls are a very dangerous situation especially among elderly people, because they may lead to fractures, concussion, and other injuries. Without timely rescue, falls may even endanger their lives. The existing optical sensor-based fall monitoring systems have some disadvantages, such as limited monitoring range and inconvenience to carry for users. Furthermore, the fall detection system based only on an accelerometer often mistakenly determines some activities of daily living (ADL) as falls, leading to low accuracy in fall detection. We propose a human fall monitoring system consisting of a highly portable sensor unit including a triaxis accelerometer, a triaxis gyroscope, and a triaxis magnetometer, and a mobile phone. With the data from these sensors, we obtain the acceleration and Euler angle (yaw, pitch, and roll), which represents the orientation of the user's body. Then, a proposed fall detection algorithm was used to detect falls based on the acceleration and Euler angle. With this monitoring system, we design a series of simulated falls and ADL and conduct the experiment by placing the sensors on the shoulder, waist, and foot of the subjects. Through the experiment, we re-identify the threshold of acceleration for accurate fall detection and verify the best body location to place the sensors by comparing the detection performance on different body segments. We also compared this monitoring system with other similar works and found that better fall detection accuracy and portability can be achieved by our system.

Highly Portable, Sensor-Based System for Human Fall Monitoring

PubMed Central

Mao, Aihua; Ma, Xuedong; He, Yinan; Luo, Jie

2017-01-01

Falls are a very dangerous situation especially among elderly people, because they may lead to fractures, concussion, and other injuries. Without timely rescue, falls may even endanger their lives. The existing optical sensor-based fall monitoring systems have some disadvantages, such as limited monitoring range and inconvenience to carry for users. Furthermore, the fall detection system based only on an accelerometer often mistakenly determines some activities of daily living (ADL) as falls, leading to low accuracy in fall detection. We propose a human fall monitoring system consisting of a highly portable sensor unit including a triaxis accelerometer, a triaxis gyroscope, and a triaxis magnetometer, and a mobile phone. With the data from these sensors, we obtain the acceleration and Euler angle (yaw, pitch, and roll), which represents the orientation of the user’s body. Then, a proposed fall detection algorithm was used to detect falls based on the acceleration and Euler angle. With this monitoring system, we design a series of simulated falls and ADL and conduct the experiment by placing the sensors on the shoulder, waist, and foot of the subjects. Through the experiment, we re-identify the threshold of acceleration for accurate fall detection and verify the best body location to place the sensors by comparing the detection performance on different body segments. We also compared this monitoring system with other similar works and found that better fall detection accuracy and portability can be achieved by our system. PMID:28902149

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Implementing and testing a fiber-optic polarization-based intrusion detection system

NASA Astrophysics Data System (ADS)

Hajj, Rasha El; MacDonald, Gregory; Verma, Pramode; Huck, Robert

2015-09-01

We describe a layer-1-based intrusion detection system for fiber-optic-based networks. Layer-1-based intrusion detection represents a significant elevation in security as it prohibits an adversary from obtaining information in the first place (no cryptanalysis is possible). We describe the experimental setup of the intrusion detection system, which is based on monitoring the behavior of certain attributes of light both in unperturbed and perturbed optical fiber links. The system was tested with optical fiber links of various lengths and types, under different environmental conditions, and under changes in fiber geometry similar to what is experienced during tapping activity. Comparison of the results for perturbed and unperturbed links has shown that the state of polarization is more sensitive to intrusion activity than the degree of polarization or power of the received light. The testing was conducted in a simulated telecommunication network environment that included both underground and aerial links. The links were monitored for intrusion activity. Attempts to tap the link were easily detected with no apparent degradation in the visual quality of the real-time surveillance video.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

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

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

2001-09-01

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

Lane Detection on the iPhone

NASA Astrophysics Data System (ADS)

Ren, Feixiang; Huang, Jinsheng; Terauchi, Mutsuhiro; Jiang, Ruyi; Klette, Reinhard

A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

PubMed

Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

2017-03-01

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Video copy protection and detection framework (VPD) for e-learning systems

NASA Astrophysics Data System (ADS)

ZandI, Babak; Doustarmoghaddam, Danial; Pour, Mahsa R.

2013-03-01

This Article reviews and compares the copyright issues related to the digital video files, which can be categorized as contended based and Digital watermarking copy Detection. Then we describe how to protect a digital video by using a special Video data hiding method and algorithm. We also discuss how to detect the copy right of the file, Based on expounding Direction of the technology of the video copy detection, and Combining with the own research results, brings forward a new video protection and copy detection approach in terms of plagiarism and e-learning systems using the video data hiding technology. Finally we introduce a framework for Video protection and detection in e-learning systems (VPD Framework).

Performance Analysis of Iterative Channel Estimation and Multiuser Detection in Multipath DS-CDMA Channels

NASA Astrophysics Data System (ADS)

Li, Husheng; Betz, Sharon M.; Poor, H. Vincent

2007-05-01

This paper examines the performance of decision feedback based iterative channel estimation and multiuser detection in channel coded aperiodic DS-CDMA systems operating over multipath fading channels. First, explicit expressions describing the performance of channel estimation and parallel interference cancellation based multiuser detection are developed. These results are then combined to characterize the evolution of the performance of a system that iterates among channel estimation, multiuser detection and channel decoding. Sufficient conditions for convergence of this system to a unique fixed point are developed.

CO and CO2 dual-gas detection based on mid-infrared wideband absorption spectroscopy

NASA Astrophysics Data System (ADS)

Dong, Ming; Zhong, Guo-qiang; Miao, Shu-zhuo; Zheng, Chuan-tao; Wang, Yi-ding

2018-03-01

A dual-gas sensor system is developed for CO and CO2 detection using a single broadband light source, pyroelectric detectors and time-division multiplexing (TDM) technique. A stepper motor based rotating system and a single-reflection spherical optical mirror are designed and adopted for realizing and enhancing dual-gas detection. Detailed measurements under static detection mode (without rotation) and dynamic mode (with rotation) are performed to study the performance of the sensor system for the two gas samples. The detection period is 7.9 s in one round of detection by scanning the two detectors. Based on an Allan deviation analysis, the 1σ detection limits under static operation are 3.0 parts per million (ppm) in volume and 2.6 ppm for CO and CO2, respectively, and those under dynamic operation are 9.4 ppm and 10.8 ppm for CO and CO2, respectively. The reported sensor has potential applications in various fields requiring CO and CO2 detection such as in the coal mine.

Photon Counting System for High-Sensitivity Detection of Bioluminescence at Optical Fiber End.

PubMed

Iinuma, Masataka; Kadoya, Yutaka; Kuroda, Akio

2016-01-01

The technique of photon counting is widely used for various fields and also applicable to a high-sensitivity detection of luminescence. Thanks to recent development of single photon detectors with avalanche photodiodes (APDs), the photon counting system with an optical fiber has become powerful for a detection of bioluminescence at an optical fiber end, because it allows us to fully use the merits of compactness, simple operation, highly quantum efficiency of the APD detectors. This optical fiber-based system also has a possibility of improving the sensitivity to a local detection of Adenosine triphosphate (ATP) by high-sensitivity detection of the bioluminescence. In this chapter, we are introducing a basic concept of the optical fiber-based system and explaining how to construct and use this system.

Gear-box fault detection using time-frequency based methods

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

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected.more » Two different time-frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen-Loeve basis. Both of them detects the gear-box fault with an acceptable detection delay.« less

QUALITY ASSESSMENT OF CONFOCAL MICROSCOPY SLIDE-BASED SYSTEMS: INSTABLITY

EPA Science Inventory

Background: All slide-based fluorescence cytometry detections systems basically include an excitation light source, intermediate optics, and a detection device (CCD or PMT). Occasionally, this equipment becomes unstable, generating unreliable and inferior data. Methods: A num...

Locomotive track detection for underground

NASA Astrophysics Data System (ADS)

Ma, Zhonglei; Lang, Wenhui; Li, Xiaoming; Wei, Xing

2017-08-01

In order to improve the PC-based track detection system, this paper proposes a method to detect linear track for underground locomotive based on DSP + FPGA. Firstly, the analog signal outputted from the camera is sampled by A / D chip. Then the collected digital signal is preprocessed by FPGA. Secondly, the output signal of FPGA is transmitted to DSP via EMIF port. Subsequently, the adaptive threshold edge detection, polar angle and radius constrain based Hough transform are implemented by DSP. Lastly, the detected track information is transmitted to host computer through Ethernet interface. The experimental results show that the system can not only meet the requirements of real-time detection, but also has good robustness.

A Corpus-Based System of Error Detection and Revision Suggestion for Spanish Learners in Taiwan: A Case Study

ERIC Educational Resources Information Center

Lu, Hui-Chuan; Chu, Yu-Hsin; Chang, Cheng-Yu

2013-01-01

Compared with English learners, Spanish learners have fewer resources for automatic error detection and revision and following the current integrative Computer Assisted Language Learning (CALL), we combined corpus-based approach and CALL to create the System of Error Detection and Revision Suggestion (SEDRS) for learning Spanish. Through…

Detection of melamine in milk powder using MCT-based short-wave infrared hyperspectral imaging system.

PubMed

Lee, Hoonsoo; Kim, Moon S; Lohumi, Santosh; Cho, Byoung-Kwan

2018-06-05

Extensive research has been conducted on non-destructive and rapid detection of melamine in powdered foods in the last decade. While Raman and near-infrared hyperspectral imaging techniques have been successful in terms of non-destructive and rapid measurement, they have limitations with respect to measurement time and detection capability, respectively. Therefore, the objective of this study was to develop a mercury cadmium telluride (MCT)-based short-wave infrared (SWIR) hyperspectral imaging system and algorithm to detect melamine quantitatively in milk powder. The SWIR hyperspectral imaging system consisted of a custom-designed illumination system, a SWIR hyperspectral camera, a data acquisition module and a sample transfer table. SWIR hyperspectral images were obtained for melamine-milk samples with different melamine concentrations, pure melamine and pure milk powder. Analysis of variance and the partial least squares regression method over the 1000-2500 nm wavelength region were used to develop an optimal model for detection. The results showed that a melamine concentration as low as 50 ppm in melamine-milk powder samples could be detected. Thus, the MCT-based SWIR hyperspectral imaging system has the potential for quantitative and qualitative detection of adulterants in powder samples.

Parallel detection experiment of fluorescence confocal microscopy using DMD.

PubMed

Wang, Qingqing; Zheng, Jihong; Wang, Kangni; Gui, Kun; Guo, Hanming; Zhuang, Songlin

2016-05-01

Parallel detection of fluorescence confocal microscopy (PDFCM) system based on Digital Micromirror Device (DMD) is reported in this paper in order to realize simultaneous multi-channel imaging and improve detection speed. DMD is added into PDFCM system, working to take replace of the single traditional pinhole in the confocal system, which divides the laser source into multiple excitation beams. The PDFCM imaging system based on DMD is experimentally set up. The multi-channel image of fluorescence signal of potato cells sample is detected by parallel lateral scanning in order to verify the feasibility of introducing the DMD into fluorescence confocal microscope. In addition, for the purpose of characterizing the microscope, the depth response curve is also acquired. The experimental result shows that in contrast to conventional microscopy, the DMD-based PDFCM system has higher axial resolution and faster detection speed, which may bring some potential benefits in the biology and medicine analysis. SCANNING 38:234-239, 2016. © 2015 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

An integrated knowledge system for the Space Shuttle hazardous gas detection system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Shi, George Z.; Bangasser, Carl; Fensky, Connie; Cegielski, Eric; Overbey, Glenn

1993-01-01

A computer-based integrated Knowledge-Based System, the Intelligent Hypertext Manual (IHM), was developed for the Space Shuttle Hazardous Gas Detection System (HGDS) at NASA Marshall Space Flight Center (MSFC). The IHM stores HGDS related knowledge and presents it in an interactive and intuitive manner. This manual is a combination of hypertext and an expert system which store experts' knowledge and experience in hazardous gas detection and analysis. The IHM's purpose is to provide HGDS personnel with the capabilities of: locating applicable documentation related to procedures, constraints, and previous fault histories; assisting in the training of personnel; enhancing the interpretation of real time data; and recognizing and identifying possible faults in the Space Shuttle sub-systems related to hazardous gas detection.

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

PubMed

Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

PubMed Central

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

PubMed

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Technical Reports Server (NTRS)

Ash, Robert L.; Huang, Jen-Kuang; Ho, Ming-Tsang

1989-01-01

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

Smartphone-based sensing system using ZnO and graphene modified electrodes for VOCs detection.

PubMed

Liu, Lei; Zhang, Diming; Zhang, Qian; Chen, Xing; Xu, Gang; Lu, Yanli; Liu, Qingjun

2017-07-15

Volatile organic compounds (VOCs) detection is in high demand for clinic treatment, environment monitoring, and food quality control. Especially, VOCs from human exhaled breath can serve as significant biomarkers of some diseases, such as lung cancer and diabetes. In this study, a smartphone-based sensing system was developed for real-time VOCs monitoring using alternative current (AC) impedance measurement. The interdigital electrodes modified with zinc oxide (ZnO), graphene, and nitrocellulose were used as sensors to produce impedance responses to VOCs. The responses could be detected by a hand-held device, sent out to a smartphone by Bluetooth, and reported with concentration on an android program of the smartphone. The smartphone-based system was demonstrated to detect acetone at concentrations as low as 1.56ppm, while AC impedance spectroscopy was used to distinguish acetone from other VOCs. Finally, measurements of the exhalations from human being were carried out to obtain the concentration of acetone in exhaled breath before and after exercise. The results proved that the smartphone-based system could be applied on the detection of VOCs in real settings for healthcare diagnosis. Thus, the smartphone-based system for VOCs detection provided a convenient, portable and efficient approach to monitor VOCs in exhaled breath and possibly allowed for early diagnosis of some diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Upconverting nanoparticles for optimizing scintillator based detection systems

DOEpatents

Kross, Brian; McKisson, John E; McKisson, John; Weisenberger, Andrew; Xi, Wenze; Zom, Carl

2013-09-17

An upconverting device for a scintillation detection system is provided. The detection system comprises a scintillator material, a sensor, a light transmission path between the scintillator material and the sensor, and a plurality of upconverting nanoparticles particles positioned in the light transmission path.

A Wireless Sensor Network-Based Portable Vehicle Detector Evaluation System

PubMed Central

Yoo, Seong-eun

2013-01-01

In an upcoming smart transportation environment, performance evaluations of existing Vehicle Detection Systems are crucial to maintain their accuracy. The existing evaluation method for Vehicle Detection Systems is based on a wired Vehicle Detection System reference and a video recorder, which must be operated and analyzed by capable traffic experts. However, this conventional evaluation system has many disadvantages. It is inconvenient to deploy, the evaluation takes a long time, and it lacks scalability and objectivity. To improve the evaluation procedure, this paper proposes a Portable Vehicle Detector Evaluation System based on wireless sensor networks. We describe both the architecture and design of a Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement. With the help of wireless sensor networks and automated analysis, our Vehicle Detector Evaluation System can evaluate a Vehicle Detection System conveniently and objectively. The extensive evaluations of our Vehicle Detector Evaluation System show that it can measure the traffic information such as volume counts and speed with over 98% accuracy. PMID:23344388

A wireless sensor network-based portable vehicle detector evaluation system.

PubMed

Yoo, Seong-eun

2013-01-17

In an upcoming smart transportation environment, performance evaluations of existing Vehicle Detection Systems are crucial to maintain their accuracy. The existing evaluation method for Vehicle Detection Systems is based on a wired Vehicle Detection System reference and a video recorder, which must be operated and analyzed by capable traffic experts. However, this conventional evaluation system has many disadvantages. It is inconvenient to deploy, the evaluation takes a long time, and it lacks scalability and objectivity. To improve the evaluation procedure, this paper proposes a Portable Vehicle Detector Evaluation System based on wireless sensor networks. We describe both the architecture and design of a Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement. With the help of wireless sensor networks and automated analysis, our Vehicle Detector Evaluation System can evaluate a Vehicle Detection System conveniently and objectively. The extensive evaluations of our Vehicle Detector Evaluation System show that it can measure the traffic information such as volume counts and speed with over 98% accuracy.

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

DTIC Science & Technology

2002-04-01

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

Signal detectability in diffusive media using phased arrays in conjunction with detector arrays.

PubMed

Kang, Dongyel; Kupinski, Matthew A

2011-06-20

We investigate Hotelling observer performance (i.e., signal detectability) of a phased array system for tasks of detecting small inhomogeneities and distinguishing adjacent abnormalities in uniform diffusive media. Unlike conventional phased array systems where a single detector is located on the interface between two sources, we consider a detector array, such as a CCD, on a phantom exit surface for calculating the Hotelling observer detectability. The signal detectability for adjacent small abnormalities (2 mm displacement) for the CCD-based phased array is related to the resolution of reconstructed images. Simulations show that acquiring high-dimensional data from a detector array in a phased array system dramatically improves the detectability for both tasks when compared to conventional single detector measurements, especially at low modulation frequencies. It is also observed in all studied cases that there exists the modulation frequency optimizing CCD-based phased array systems, where detectability for both tasks is consistently high. These results imply that the CCD-based phased array has the potential to achieve high resolution and signal detectability in tomographic diffusive imaging while operating at a very low modulation frequency. The effect of other configuration parameters, such as a detector pixel size, on the observer performance is also discussed.

An FPGA-Based Rapid Wheezing Detection System

PubMed Central

Lin, Bor-Shing; Yen, Tian-Shiue

2014-01-01

Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. PMID:24481034

A real-time biomonitoring system to detect arsenic toxicity by valve movement in freshwater clam Corbicula fluminea.

PubMed

Chen, Wei-Yu; Jou, Li-John; Chen, Suz-Hsin; Liao, Chung-Min

2012-05-01

Arsenic (As) is the element of greatest ecotoxicological concern in aquatic environments. Effective monitoring and diagnosis of As pollution via a biological early warning system is a great challenge for As-affected regions. The purpose of this study was to synthesize water chemistry-based bioavailability and valve daily rhythm in Corbicula fluminea to design a biomonitoring system for detecting waterborne As. We integrated valve daily rhythm dynamic patterns and water chemistry-based Hill dose-response model to build into a programmatic mechanism of inductance-based valvometry technique for providing a rapid and cost-effective dynamic detection system. A LabVIEW graphic control program in a personal computer was employed to demonstrate completely the functional presentation of the present dynamic system. We verified the simulated dissolved As concentrations based on the valve daily rhythm behavior with published experimental data. Generally, the performance of this proposed biomonitoring system demonstrates fairly good applicability to detect waterborne As concentrations when the field As concentrations are less than 1 mg L(-1). We also revealed that the detection times were dependent on As exposure concentrations. This biomonitoring system could particularly provide real-time transmitted information on the waterborne As activity under various aquatic environments. This parsimonious C. fluminea valve rhythm behavior-based real-time biomonitoring system presents a valuable effort to promote the automated biomonitoring and offers early warnings on potential ecotoxicological risks in regions with elevated As exposure concentrations.

Train integrity detection risk analysis based on PRISM

NASA Astrophysics Data System (ADS)

Wen, Yuan

2018-04-01

GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

Highly sensitive MicroRNA 146a detection using a gold nanoparticle-based CTG repeat probing system and isothermal amplification.

PubMed

Le, Binh Huy; Seo, Young Jun

2018-01-25

We have developed a gold nanoparticle (AuNP)-based CTG repeat probing system displaying high quenching capability and combined it with isothermal amplification for the detection of miRNA 146a. This method of using a AuNP-based CTG repeat probing system with isothermal amplification allowed the highly sensitive (14 aM) and selective detection of miRNA 146a. A AuNP-based CTG repeat probing system having a hairpin structure and a dT F fluorophore exhibited highly efficient quenching because the CTG repeat-based stable hairpin structure imposed a close distance between the AuNP and the dT F residue. A small amount of miRNA 146a induced multiple copies of the CAG repeat sequence during rolling circle amplification; the AuNP-based CTG repeat probing system then bound to the complementary multiple-copy CAG repeat sequence, thereby inducing a structural change from a hairpin to a linear structure with amplified fluorescence. This AuNP-based CTG probing system combined with isothermal amplification could also discriminate target miRNA 146a from one- and two-base-mismatched miRNAs (ORN 1 and ORN 2, respectively). This simple AuNP-based CTG probing system, combined with isothermal amplification to induce a highly sensitive change in fluorescence, allows the detection of miRNA 146a with high sensitivity (14 aM) and selectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Passarge, M; Fix, M K; Manser, P

Purpose: To create and test an accurate EPID-frame-based VMAT QA metric to detect gross dose errors in real-time and to provide information about the source of error. Methods: A Swiss cheese model was created for an EPID-based real-time QA process. The system compares a treatmentplan- based reference set of EPID images with images acquired over each 2° gantry angle interval. The metric utilizes a sequence of independent consecutively executed error detection Methods: a masking technique that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment to quantify rotation, scaling andmore » translation; standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each test were determined. For algorithm testing, twelve different types of errors were selected to modify the original plan. Corresponding predictions for each test case were generated, which included measurement-based noise. Each test case was run multiple times (with different noise per run) to assess the ability to detect introduced errors. Results: Averaged over five test runs, 99.1% of all plan variations that resulted in patient dose errors were detected within 2° and 100% within 4° (∼1% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 91.5% were detected by the system within 2°. Based on the type of method that detected the error, determination of error sources was achieved. Conclusion: An EPID-based during-treatment error detection system for VMAT deliveries was successfully designed and tested. The system utilizes a sequence of methods to identify and prevent gross treatment delivery errors. The system was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of errors in real-time and indicate the error source. J. V. Siebers receives funding support from Varian Medical Systems.« less

A hierarchical detection method in external communication for self-driving vehicles based on TDMA.

PubMed

Alheeti, Khattab M Ali; Al-Ani, Muzhir Shaban; McDonald-Maier, Klaus

2018-01-01

Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.

Development of yarn breakage detection software system based on machine vision

NASA Astrophysics Data System (ADS)

Wang, Wenyuan; Zhou, Ping; Lin, Xiangyu

2017-10-01

For questions spinning mills and yarn breakage cannot be detected in a timely manner, and save the cost of textile enterprises. This paper presents a software system based on computer vision for real-time detection of yarn breakage. The system and Windows8.1 system Tablet PC, cloud server to complete the yarn breakage detection and management. Running on the Tablet PC software system is designed to collect yarn and location information for analysis and processing. And will be processed after the information through the Wi-Fi and http protocol sent to the cloud server to store in the Microsoft SQL2008 database. In order to follow up on the yarn break information query and management. Finally sent to the local display on time display, and remind the operator to deal with broken yarn. The experimental results show that the system of missed test rate not more than 5%o, and no error detection.

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

NASA Technical Reports Server (NTRS)

Glass, B. J. (Editor)

1992-01-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Thermal Expert System (TEXSYS): Systems automony demonstration project, volume 1. Overview

NASA Technical Reports Server (NTRS)

Glass, B. J. (Editor)

1992-01-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS test bed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

NASA Astrophysics Data System (ADS)

Glass, B. J.

1992-10-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Hardware Evaluation Of Heavy Truck Side And Rear Object Detection Systems

DOT National Transportation Integrated Search

1995-01-01

This paper focuses on two types of electronics-based object detection systems for heavy truck applications: those sensing the presence of objects to the rear of the vehicle (referred to as Rear Object Detection Systems, or RODS) and those sensing the...

Optical fiber strain sensor for application in intelligent intruder detection systems

NASA Astrophysics Data System (ADS)

Stańczyk, Tomasz; Tenderenda, Tadeusz; Szostkiewicz, Lukasz; Bienkowska, Beata; Kunicki, Daniel; Murawski, Michal; Mergo, Pawel; Nasilowski, Tomasz

2017-10-01

Nowadays technology allows to create highly effective Intruder Detection Systems (IDS), that are able to detect the presence of an intruder within a defined area. In such systems the best performance can be achieved by combining different detection techniques in one system. One group of devices that can be applied in an IDS, are devices based on Fiber Optic Sensors (FOS). The FOS benefits from numerous advantages of optical fibers like: small size, light weight or high sensitivity. In this work we present a novel Microstructured Optical Fiber (MOF) characterized by increased strain sensitivity dedicated to distributed acoustic sensing for intelligent intruder detection systems. By designing the MOF with large air holes in close proximity to a fiber core, we increased the effective refractive index sensitivity to longitudinal strain. The presented fiber can be easily integrated in a floor system in order to detect any movement in the investigated area. We believe that sensors, based on the presented MOF, due to its numerous advantages, can find application in intelligent IDS.

Portable point-of-care blood analysis system for global health (Conference Presentation)

NASA Astrophysics Data System (ADS)

Dou, James J.; Aitchison, James Stewart; Chen, Lu; Nayyar, Rakesh

2016-03-01

In this paper we present a portable blood analysis system based on a disposable cartridge and hand-held reader. The platform can perform all the sample preparation, detection and waste collection required to complete a clinical test. In order to demonstrate the utility of this approach a CD4 T cell enumeration was carried out. A handheld, point-of-care CD4 T cell system was developed based on this system. In particular we will describe a pneumatic, active pumping method to control the on-chip fluidic actuation. Reagents for the CD4 T cell counting assay were dried on a reagent plug to eliminate the need for cold chain storage when used in the field. A micromixer based on the active fluidic actuation was designed to complete sample staining with fluorescent dyes that was dried on the reagent plugs. A novel image detection and analysis algorithm was developed to detect and track the flight of target particles and cells during each analysis. The handheld, point-of-care CD4 testing system was benchmarked against clinical cytometer. The experimental results demonstrated experimental results were closely matched with the flow cytometry. The same platform can be further expanded into a bead-array detection system where other types of biomolecules such as proteins can be detected using the same detection system.

Design and Elementary Evaluation of a Highly-Automated Fluorescence-Based Instrument System for On-Site Detection of Food-Borne Pathogens

PubMed Central

Lu, Zhan; Zhang, Jianyi; Xu, Lizhou; Li, Yanbin; Chen, Siyu; Ye, Zunzhong; Wang, Jianping

2017-01-01

A simple, highly-automated instrument system used for on-site detection of foodborne pathogens based on fluorescence was designed, fabricated, and preliminarily tested in this paper. A corresponding method has been proved effective in our previous studies. This system utilizes a light-emitting diode (LED) to excite fluorescent labels and a spectrometer to record the fluorescence signal from samples. A rotation stage for positioning and switching samples was innovatively designed for high-throughput detection, ten at most in one single run. We also developed software based on LabVIEW for data receiving, processing, and the control of the whole system. In the test of using a pure quantum dot (QD) solution as a standard sample, detection results from this home-made system were highly-relevant with that from a well-commercialized product and even slightly better reproducibility was found. And in the test of three typical kinds of food-borne pathogens, fluorescence signals recorded by this system are highly proportional to the variation of the sample concentration, with a satisfied limit of detection (LOD) (nearly 102–103 CFU·mL−1 in food samples). Additionally, this instrument system is low-cost and easy-to-use, showing a promising potential for on-site rapid detection of food-borne pathogens. PMID:28241478

Design and Elementary Evaluation of a Highly-Automated Fluorescence-Based Instrument System for On-Site Detection of Food-Borne Pathogens.

PubMed

Lu, Zhan; Zhang, Jianyi; Xu, Lizhou; Li, Yanbin; Chen, Siyu; Ye, Zunzhong; Wang, Jianping

2017-02-23

A simple, highly-automated instrument system used for on-site detection of foodborne pathogens based on fluorescence was designed, fabricated, and preliminarily tested in this paper. A corresponding method has been proved effective in our previous studies. This system utilizes a light-emitting diode (LED) to excite fluorescent labels and a spectrometer to record the fluorescence signal from samples. A rotation stage for positioning and switching samples was innovatively designed for high-throughput detection, ten at most in one single run. We also developed software based on LabVIEW for data receiving, processing, and the control of the whole system. In the test of using a pure quantum dot (QD) solution as a standard sample, detection results from this home-made system were highly-relevant with that from a well-commercialized product and even slightly better reproducibility was found. And in the test of three typical kinds of food-borne pathogens, fluorescence signals recorded by this system are highly proportional to the variation of the sample concentration, with a satisfied limit of detection (LOD) (nearly 10²-10³ CFU·mL -1 in food samples). Additionally, this instrument system is low-cost and easy-to-use, showing a promising potential for on-site rapid detection of food-borne pathogens.

A comprehensive study of sampling-based optimum signal detection in concentration-encoded molecular communication.

PubMed

Mahfuz, Mohammad U; Makrakis, Dimitrios; Mouftah, Hussein T

2014-09-01

In this paper, a comprehensive analysis of the sampling-based optimum signal detection in ideal (i.e., free) diffusion-based concentration-encoded molecular communication (CEMC) system has been presented. A generalized amplitude-shift keying (ASK)-based CEMC system has been considered in diffusion-based noise and intersymbol interference (ISI) conditions. Information is encoded by modulating the amplitude of the transmission rate of information molecules at the TN. The critical issues involved in the sampling-based receiver thus developed are addressed in detail, and its performance in terms of the number of samples per symbol, communication range, and transmission data rate is evaluated. ISI produced by the residual molecules deteriorates the performance of the CEMC system significantly, which further deteriorates when the communication range and/or the transmission data rate increase(s). In addition, the performance of the optimum receiver depends on the receiver's ability to compute the ISI accurately, thus providing a trade-off between receiver complexity and achievable bit error rate (BER). Exact and approximate detection performances have been derived. Finally, it is found that the sampling-based signal detection scheme thus developed can be applied to both binary and multilevel (M-ary) ASK-based CEMC systems, although M-ary systems suffer more from higher BER.

Evaluating Fluorscence-Based Metrics for Early Detection of ...

EPA Pesticide Factsheets

Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification

A Real-Time System for Lane Detection Based on FPGA and DSP

NASA Astrophysics Data System (ADS)

Xiao, Jing; Li, Shutao; Sun, Bin

2016-12-01

This paper presents a real-time lane detection system including edge detection and improved Hough Transform based lane detection algorithm and its hardware implementation with field programmable gate array (FPGA) and digital signal processor (DSP). Firstly, gradient amplitude and direction information are combined to extract lane edge information. Then, the information is used to determine the region of interest. Finally, the lanes are extracted by using improved Hough Transform. The image processing module of the system consists of FPGA and DSP. Particularly, the algorithms implemented in FPGA are working in pipeline and processing in parallel so that the system can run in real-time. In addition, DSP realizes lane line extraction and display function with an improved Hough Transform. The experimental results show that the proposed system is able to detect lanes under different road situations efficiently and effectively.

Wake Vortex Avoidance System and Method

NASA Technical Reports Server (NTRS)

Shams, Qamar A. (Inventor); Zuckerwar, Allan J. (Inventor); Knight, Howard K. (Inventor)

2017-01-01

A wake vortex avoidance system includes a microphone array configured to detect low frequency sounds. A signal processor determines a geometric mean coherence based on the detected low frequency sounds. A display displays wake vortices based on the determined geometric mean coherence.

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

NASA Astrophysics Data System (ADS)

Chen, Huabo; Tu, Yaqing; Luo, Ting

1998-08-01

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

Achievable Strength-Based Signal Detection in Quantity-Constrained PAM OOK Concentration-Encoded Molecular Communication.

PubMed

Mahfuz, Mohammad Upal

2016-10-01

In this paper, the expressions of achievable strength-based detection probabilities of concentration-encoded molecular communication (CEMC) system have been derived based on finite pulsewidth (FP) pulse-amplitude modulated (PAM) on-off keying (OOK) modulation scheme and strength threshold. An FP-PAM system is characterized by its duty cycle α that indicates the fraction of the entire symbol duration the transmitter remains on and transmits the signal. Results show that the detection performance of an FP-PAM OOK CEMC system significantly depends on the statistical distribution parameters of diffusion-based propagation noise and intersymbol interference (ISI). Analytical detection performance of an FP-PAM OOK CEMC system under ISI scenario has been explained and compared based on receiver operating characteristics (ROC) for impulse (i.e., spike)-modulated (IM) and FP-PAM CEMC schemes. It is shown that the effects of diffusion noise and ISI on ROC can be explained separately based on their communication range-dependent statistics. With full duty cycle, an FP-PAM scheme provides significantly worse performance than an IM scheme. The paper also analyzes the performance of the system when duty cycle, transmission data rate, and quantity of molecules vary.

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

NASA Technical Reports Server (NTRS)

Williams, Martha K.; Lewis, Mark; Szafran, J.; Shelton, C.; Ludwig, L.; Gibson, T.; Lane, J.; Trautwein, T.

2015-01-01

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Leak detection by mass balance effective for Norman Wells line

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

Liou, J.C.P.

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

Structured Light-Based Hazard Detection For Planetary Surface Navigation

NASA Technical Reports Server (NTRS)

Nefian, Ara; Wong, Uland Y.; Dille, Michael; Bouyssounouse, Xavier; Edwards, Laurence; To, Vinh; Deans, Matthew; Fong, Terry

2017-01-01

This paper describes a structured light-based sensor for hazard avoidance in planetary environments. The system presented here can also be used in terrestrial applications constrained by reduced onboard power and computational complexity and low illumination conditions. The sensor is on a calibrated camera and laser dot projector system. The onboard hazard avoidance system determines the position of the projected dots in the image and through a triangulation process detects potential hazards. The paper presents the design parameters for this sensor and describes the image based solution for hazard avoidance. The system presented here was tested extensively in day and night conditions in Lunar analogue environments. The current system achieves over 97 detection rate with 1.7 false alarms over 2000 images.

Imaging, object detection, and change detection with a polarized multistatic GPR array

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

Beer, N. Reginald; Paglieroni, David W.

A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and thenmore » combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.« less

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

Ding, Fei; Jiang, Huaiguang; Tan, Jin

This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observablemore » and detectable.« less

A miniaturised image based fluorescence detection system for point-of-care-testing of cocaine abuse

NASA Astrophysics Data System (ADS)

Walczak, Rafał; Krüger, Jan; Moynihan, Shane

2015-08-01

In this paper, we describe a miniaturised image-based fluorescence detection system and demonstrate its viability as a highly sensitive tool for point-of-care-analysis of drugs of abuse in human sweat with a focus on monitor individuals for drugs of abuse. Investigations of miniaturised and low power optoelectronic configurations and methodologies for real-time image analysis were successfully carried out. The miniaturised fluorescence detection system was validated against a reference detection system under controlled laboratory conditions by analysing spiked sweat samples in dip stick and then strip with sample pad. As a result of the validation studies, a 1 ng mL-1 limit of detection of cocaine in sweat and full agreement of test results with the reference detection system can be reported. Results of the investigations open the way towards a detection system that integrates a hand-held fluorescence reader and a wearable skinpatch, and which can collect and in situ analyse sweat for the presence of cocaine at any point for up to tenths hours.

Portable integrated capillary-electrophoresis system using disposable polymer chips with capacitively coupled contactless conductivity detection for on-site analysis of foodstuff

NASA Astrophysics Data System (ADS)

Gärtner, Claudia; Hoffmann, Werner; Demattio, Horst; Clemens, Thomas; Klotz, Matthias; Klemm, Richard; Becker, Holger

2009-05-01

We present a compact portable chip-based capillary electrophoresis system that employs capacitively coupled contactless conductivity detection (C4D) operating at 4 MHz as an alternative detection method compared to the commonly used optical detection based on laser-induced fluorescence. Emphasis was put on system integration and industrial manufacturing technologies for the system. Therefore, the disposable chip for this system is fabricated out of PMMA using injection molding; the electrodes are screen-printed or thin-film electrodes. The system is designed for the measurement of small ionic species like Li+, Na+, K+, SO42- or NO3- typically present in foods like milk and mineral water as well as acids e.g. in wine.

Design of polarization imaging system based on CIS and FPGA

NASA Astrophysics Data System (ADS)

Zeng, Yan-an; Liu, Li-gang; Yang, Kun-tao; Chang, Da-ding

2008-02-01

As polarization is an important characteristic of light, polarization image detecting is a new image detecting technology of combining polarimetric and image processing technology. Contrasting traditional image detecting in ray radiation, polarization image detecting could acquire a lot of very important information which traditional image detecting couldn't. Polarization image detecting will be widely used in civilian field and military field. As polarization image detecting could resolve some problem which couldn't be resolved by traditional image detecting, it has been researched widely around the world. The paper introduces polarization image detecting in physical theory at first, then especially introduces image collecting and polarization image process based on CIS (CMOS image sensor) and FPGA. There are two parts including hardware and software for polarization imaging system. The part of hardware include drive module of CMOS image sensor, VGA display module, SRAM access module and the real-time image data collecting system based on FPGA. The circuit diagram and PCB was designed. Stokes vector and polarization angle computing method are analyzed in the part of software. The float multiply of Stokes vector is optimized into just shift and addition operation. The result of the experiment shows that real time image collecting system could collect and display image data from CMOS image sensor in real-time.

The Reliability and Effectiveness of a Radar-Based Animal Detection System

DOT National Transportation Integrated Search

2017-09-22

This document contains data on the reliability and effectiveness of an animal detection system along U.S. Hwy 95 near Bonners Ferry, Idaho. The system uses a Doppler radar to detect large mammals (e.g., deer and elk) when they approach the highway. T...

The Reliability and Effectiveness of a Radar-Based Animal Detection System

DOT National Transportation Integrated Search

2017-09-01

This document contains data on the reliability and effectiveness of an animal detection system along U.S. Hwy 95 near Bonners Ferry, Idaho. The system uses a Doppler radar to detect large mammals (e.g., deer and elk) when they approach the highway. T...

Automobile inspection system based on wireless communication

NASA Astrophysics Data System (ADS)

Miao, Changyun; Ye, Chunqing

2010-07-01

This paper aims to research the Automobile Inspection System based on Wireless Communication, and suggests an overall design scheme which uses GPS for speed detection and Bluetooth and GPRS for communication. The communication between PDA and PC was realized by means of GPRS and TCP/IP; and the hardware circuit and software for detection terminal were devised by means of JINOU-3264 Bluetooth Module after analyzing the Bluetooth and its communication protocol. According to the results of debugging test, this system accomplished GPRS based data communication and management as well as the real-time detection on auto safety performance parameters in crash test via PC, whereby the need for mobility and reliability was met and the efficiency and level of detection was improved.

Pedestrian Detection Based on Adaptive Selection of Visible Light or Far-Infrared Light Camera Image by Fuzzy Inference System and Convolutional Neural Network-Based Verification.

PubMed

Kang, Jin Kyu; Hong, Hyung Gil; Park, Kang Ryoung

2017-07-08

A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlusions. In recent times, a growing number of studies have been performed on visible light camera-based pedestrian detection systems using a convolutional neural network (CNN) in order to make the pedestrian detection process more resilient to such conditions. However, visible light cameras still cannot detect pedestrians during nighttime, and are easily affected by shadows and lighting. There are many studies on CNN-based pedestrian detection through the use of far-infrared (FIR) light cameras (i.e., thermal cameras) to address such difficulties. However, when the solar radiation increases and the background temperature reaches the same level as the body temperature, it remains difficult for the FIR light camera to detect pedestrians due to the insignificant difference between the pedestrian and non-pedestrian features within the images. Researchers have been trying to solve this issue by inputting both the visible light and the FIR camera images into the CNN as the input. This, however, takes a longer time to process, and makes the system structure more complex as the CNN needs to process both camera images. This research adaptively selects a more appropriate candidate between two pedestrian images from visible light and FIR cameras based on a fuzzy inference system (FIS), and the selected candidate is verified with a CNN. Three types of databases were tested, taking into account various environmental factors using visible light and FIR cameras. The results showed that the proposed method performs better than the previously reported methods.

Preliminary Assessment of Detection Efficiency for the Geostationary Lightning Mapper Using Intercomparisons with Ground-Based Systems

NASA Technical Reports Server (NTRS)

Bateman, Monte; Mach, Douglas; Blakeslee, Richard J.; Koshak, William

2018-01-01

As part of the calibration/validation (cal/val) effort for the Geostationary Lightning Mapper (GLM) on GOES-16, we need to assess instrument performance (detection efficiency and accuracy). One major effort is to calculate the detection efficiency of GLM by comparing to multiple ground-based systems. These comparisons will be done pair-wise between GLM and each other source. A complication in this process is that the ground-based systems sense different properties of the lightning signal than does GLM (e.g., RF vs. optical). Also, each system has a different time and space resolution and accuracy. Preliminary results indicate that GLM is performing at or above its specification.

Trends in Flow-based Biosensing Systems for Pesticide Assessment

PubMed Central

Prieto-Simón, Beatriz; Campàs, Mònica; Andreescu, Silvana; Marty, Jean-Louis

2006-01-01

This review gives a survey on the state of the art of pesticide detection using flow-based biosensing systems for sample screening. Although immunosensor systems have been proposed as powerful pesticide monitoring tools, this review is mainly focused on enzyme-based biosensors, as they are the most commonly employed when using a flow system. Among the different detection methods able to be integrated into flow-injection analysis (FIA) systems, the electrochemical ones will be treated in more detail, due to their high sensitivity, simple sample pretreatment, easy operational procedures and real-time detection. During the last decade, new trends have been emerging in order to increase the enzyme stability, the sensitivity and selectivity of the measurements, and to lower the detection limits. These approaches are based on (i) the design of novel matrices for enzyme immobilisation, (ii) new manifold configurations of the FIA system, sometimes including miniaturisation or lab-on-chip protocols thanks to micromachining technology, (iii) the use of cholinesterase enzymes either from various commercial sources or genetically modified with the aim of being more sensitive, (iv) the incorporation of other highly specific enzymes, such as organophosphate hydrolase (OPH) or parathion hydrolase (PH) and (v) the combination of different electrochemical methods of detection. This article discusses these novel strategies and their advantages and limitations.

Smartphone-Based Dual-Modality Imaging System for Quantitative Detection of Color or Fluorescent Lateral Flow Immunochromatographic Strips

NASA Astrophysics Data System (ADS)

Hou, Yafei; Wang, Kan; Xiao, Kun; Qin, Weijian; Lu, Wenting; Tao, Wei; Cui, Daxiang

2017-04-01

Nowadays, lateral flow immunochromatographic assays are increasingly popular as a diagnostic tool for point-of-care (POC) test based on their simplicity, specificity, and sensitivity. Hence, quantitative detection and pluralistic popular application are urgently needed in medical examination. In this study, a smartphone-based dual-modality imaging system was developed for quantitative detection of color or fluorescent lateral flow test strips, which can be operated anywhere at any time. In this system, the white and ultra-violet (UV) light of optical device was designed, which was tunable with different strips, and the Sobel operator algorithm was used in the software, which could enhance the identification ability to recognize the test area from the background boundary information. Moreover, this technology based on extraction of the components from RGB format (red, green, and blue) of color strips or only red format of the fluorescent strips can obviously improve the high-signal intensity and sensitivity. Fifty samples were used to evaluate the accuracy of this system, and the ideal detection limit was calculated separately from detection of human chorionic gonadotropin (HCG) and carcinoembryonic antigen (CEA). The results indicated that smartphone-controlled dual-modality imaging system could provide various POC diagnoses, which becomes a potential technology for developing the next-generation of portable system in the near future.

Evaluation of culture- and PCR-based detection methods for Escherichia coli O157:H7 in inoculated ground beeft.

PubMed

Arthur, Terrance M; Bosilevac, Joseph M; Nou, Xiangwu; Koohmaraie, Mohammad

2005-08-01

Currently, several beef processors employ test-and-hold systems for increased quality control of ground beef. In such programs, each lot of product must be tested and found negative for Escherichia coli O157:H7 prior to release of the product into commerce. Optimization of three testing attributes (detection time, specificity, and sensitivity) is critical to the success of such strategies. Because ground beef is a highly perishable product, the testing methodology used must be as rapid as possible. The test also must have a low false-positive result rate so product is not needlessly discarded. False-negative results cannot be tolerated because they would allow contaminated product to be released and potentially cause disease. In this study, two culture-based and three PCR-based methods for detecting E. coli O157:H7 in ground beef were compared for their abilities to meet the above criteria. Ground beef samples were individually spiked with five genetically distinct strains of E. coli O157: H7 at concentrations of 17 and 1.7 CFU/65 g and then subjected to the various testing methodologies. There was no difference (P > 0.05) in the abilities of the PCR-based methods to detect E. coli O157:H7 inoculated in ground beef at 1.7 CFU/65 g. The culture-based systems detected more positive samples than did the PCR-based systems, but the detection times (21 to 48 h) were at least 9 h longer than those for the PCR-based methods (7.5 to 12 h). Ground beef samples were also spiked with potentially cross-reactive strains. The PCR-based systems that employed an immunomagnetic separation step prior to detection produced fewer false-positive results.

Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis

PubMed Central

Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq

2015-01-01

Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim’ based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks. PMID:26222882

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

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

Zhang, Fengli; Li, Qinghua

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Networkmore » and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.« less

Human visual system-based smoking event detection

NASA Astrophysics Data System (ADS)

Odetallah, Amjad D.; Agaian, Sos S.

2012-06-01

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

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.

Collaborative Point Paper on Border Surveillance Technology

DTIC Science & Technology

2007-06-01

Systems PLC LORHIS (Long Range Hyperspectral Imaging System ) can be configured for either manned or unmanned aircraft to automatically detect and...Airships, and/or Aerostats, (RF, Electro-Optical, Infrared, Video) • Land- based Sensor Systems (Attended/Mobile and Unattended: e.g., CCD, Motion, Acoustic...electronic surveillance technologies for intrusion detection and warning. These ground- based systems are primarily short-range, up to around 500 meters

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.

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

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

Fusion of a FBG-based health monitoring system for wind turbines with a fiber-optic lightning detection system

NASA Astrophysics Data System (ADS)

Krämer, Sebastian G. M.; Wiesent, Benjamin; Müller, Mathias S.; Puente León, Fernando; Méndez Hernández, Yarú

2008-04-01

Wind turbine blades are made of composite materials and reach a length of more than 42 meters. Developments for modern offshore turbines are working on about 60 meters long blades. Hence, with the increasing height of the turbines and the remote locations of the structures, health monitoring systems are becoming more and more important. Therefore, fiber-optic sensor systems are well-suited, as they are lightweight, immune against electromagnetic interference (EMI), and as they can be multiplexed. Based on two separately existing concepts for strain measurements and lightning detection on wind turbines, a fused system is presented. The strain measurement system is based on a reflective fiber-Bragg-grating (FBG) network embedded in the composite structure of the blade. For lightning detection, transmissive &fiber-optic magnetic field sensors based on the Faraday effect are used to register the lightning parameters and estimate the impact point. Hence, an existing lightning detection system will be augmented, due to the fusion, by the capability to measure strain, temperature and vibration. Load, strain, temperature and impact detection information can be incorporated into the turbine's monitoring or SCADA system and remote controlled by operators. Data analysis techniques allow dynamic maintenance scheduling to become a reality, what is of special interest for the cost-effective maintenance of large offshore or badly attainable onshore wind parks. To prove the feasibility of this sensor fusion on one optical fiber, interferences between both sensor systems are investigated and evaluated.

Driver fatigue alarm based on eye detection and gaze estimation

NASA Astrophysics Data System (ADS)

Sun, Xinghua; Xu, Lu; Yang, Jingyu

2007-11-01

The driver assistant system has attracted much attention as an essential component of intelligent transportation systems. One task of driver assistant system is to prevent the drivers from fatigue. For the fatigue detection it is natural that the information about eyes should be utilized. The driver fatigue can be divided into two types, one is the sleep with eyes close and another is the sleep with eyes open. Considering that the fatigue detection is related with the prior knowledge and probabilistic statistics, the dynamic Bayesian network is used as the analysis tool to perform the reasoning of fatigue. Two kinds of experiments are performed to verify the system effectiveness, one is based on the video got from the laboratory and another is based on the video got from the real driving situation. Ten persons participate in the test and the experimental result is that, in the laboratory all the fatigue events can be detected, and in the practical vehicle the detection ratio is about 85%. Experiments show that in most of situations the proposed system works and the corresponding performance is satisfying.

An FPGA-Based People Detection System

NASA Astrophysics Data System (ADS)

Nair, Vinod; Laprise, Pierre-Olivier; Clark, James J.

2005-12-01

This paper presents an FPGA-based system for detecting people from video. The system is designed to use JPEG-compressed frames from a network camera. Unlike previous approaches that use techniques such as background subtraction and motion detection, we use a machine-learning-based approach to train an accurate detector. We address the hardware design challenges involved in implementing such a detector, along with JPEG decompression, on an FPGA. We also present an algorithm that efficiently combines JPEG decompression with the detection process. This algorithm carries out the inverse DCT step of JPEG decompression only partially. Therefore, it is computationally more efficient and simpler to implement, and it takes up less space on the chip than the full inverse DCT algorithm. The system is demonstrated on an automated video surveillance application and the performance of both hardware and software implementations is analyzed. The results show that the system can detect people accurately at a rate of about[InlineEquation not available: see fulltext.] frames per second on a Virtex-II 2V1000 using a MicroBlaze processor running at[InlineEquation not available: see fulltext.], communicating with dedicated hardware over FSL links.

Hydrogel Based Biosensors for In Vitro Diagnostics of Biochemicals, Proteins, and Genes.

PubMed

Jung, Il Young; Kim, Ji Su; Choi, Bo Ram; Lee, Kyuri; Lee, Hyukjin

2017-06-01

Hydrogel-based biosensors have drawn considerable attention due to their various advantages over conventional detection systems. Recent studies have shown that hydrogel biosensors can be excellent alternative systems to detect a wide range of biomolecules, including small biochemicals, pathogenic proteins, and disease specific genes. Due to the excellent physical properties of hydrogels such as the high water content and stimuli-responsive behavior of cross-linked network structures, this system can offer substantial improvement for the design of novel detection systems for various diagnostic applications. The other main advantage of hydrogels is the role of biomimetic three-dimensional (3D) matrix immobilizing enzymes and aptamers within the detection systems, which enhances their stability. This provides ideal reaction conditions for enzymes and aptamers to interact with substrates within the aqueous environment of the hydrogel. In this review, we have highlighted various novel detection approaches utilizing the outstanding properties of the hydrogel. This review summarizes the recent progress of hydrogel-based biosensors and discusses their future perspectives and clinical limitations to overcome. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2012-08-21

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

A hierarchical detection method in external communication for self-driving vehicles based on TDMA

PubMed Central

Al-ani, Muzhir Shaban; McDonald-Maier, Klaus

2018-01-01

Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms. PMID:29315302

Advances in developing rapid, reliable and portable detection systems for alcohol.

PubMed

Thungon, Phurpa Dema; Kakoti, Ankana; Ngashangva, Lightson; Goswami, Pranab

2017-11-15

Development of portable, reliable, sensitive, simple, and inexpensive detection system for alcohol has been an instinctive demand not only in traditional brewing, pharmaceutical, food and clinical industries but also in rapidly growing alcohol based fuel industries. Highly sensitive, selective, and reliable alcohol detections are currently amenable typically through the sophisticated instrument based analyses confined mostly to the state-of-art analytical laboratory facilities. With the growing demand of rapid and reliable alcohol detection systems, an all-round attempt has been made over the past decade encompassing various disciplines from basic and engineering sciences. Of late, the research for developing small-scale portable alcohol detection system has been accelerated with the advent of emerging miniaturization techniques, advanced materials and sensing platforms such as lab-on-chip, lab-on-CD, lab-on-paper etc. With these new inter-disciplinary approaches along with the support from the parallel knowledge growth on rapid detection systems being pursued for various targets, the progress on translating the proof-of-concepts to commercially viable and environment friendly portable alcohol detection systems is gaining pace. Here, we summarize the progress made over the years on the alcohol detection systems, with a focus on recent advancement towards developing portable, simple and efficient alcohol sensors. Copyright © 2017 Elsevier B.V. All rights reserved.

An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening

NASA Astrophysics Data System (ADS)

Wang, Weiya; Jia, Mengyu; Gao, Feng; Yang, Lihong; Qu, Pengpeng; Zou, Changping; Liu, Pengxi; Zhao, Huijuan

2015-02-01

The cervical cancer screening at a pre-cancer stage is beneficial to reduce the mortality of women. An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening is introduced in this paper. In this system, three electrodes alternately discharge to the cervical tissue and three light emitting diodes in different wavelengths alternately irradiate the cervical tissue. Then the relative optical reflectance and electrical voltage attenuation curve are obtained by optical and electrical detection, respectively. The system is based on DSP to attain the portable and cheap instrument. By adopting the relative reflectance and the voltage attenuation constant, the classification algorithm based on Support Vector Machine (SVM) discriminates abnormal cervical tissue from normal. We use particle swarm optimization to optimize the two key parameters of SVM, i.e. nuclear factor and cost factor. The clinical data were collected on 313 patients to build a clinical database of tissue responses under optical and electrical stimulations with the histopathologic examination as the gold standard. The classification result shows that the opto-electronic joint detection has higher total coincidence rate than separate optical detection or separate electrical detection. The sensitivity, specificity, and total coincidence rate increase with the increasing of sample numbers in the training set. The average total coincidence rate of the system can reach 85.1% compared with the histopathologic examination.

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.

Microfluidic lab-on-a-foil for nucleic acid analysis based on isothermal recombinase polymerase amplification (RPA).

PubMed

Lutz, Sascha; Weber, Patrick; Focke, Max; Faltin, Bernd; Hoffmann, Jochen; Müller, Claas; Mark, Daniel; Roth, Günter; Munday, Peter; Armes, Niall; Piepenburg, Olaf; Zengerle, Roland; von Stetten, Felix

2010-04-07

For the first time we demonstrate a self-sufficient lab-on-a-foil system for the fully automated analysis of nucleic acids which is based on the recently available isothermal recombinase polymerase amplification (RPA). The system consists of a novel, foil-based centrifugal microfluidic cartridge including prestored liquid and dry reagents, and a commercially available centrifugal analyzer for incubation at 37 degrees C and real-time fluorescence detection. The system was characterized with an assay for the detection of the antibiotic resistance gene mecA of Staphylococcus aureus. The limit of detection was <10 copies and time-to-result was <20 min. Microfluidic unit operations comprise storage and release of liquid reagents, reconstitution of lyophilized reagents, aliquoting the sample into < or = 30 independent reaction cavities, and mixing of reagents with the DNA samples. The foil-based cartridge was produced by blow-molding and sealed with a self-adhesive tape. The demonstrated system excels existing PCR based lab-on-a-chip platforms in terms of energy efficiency and time-to-result. Applications are suggested in the field of mobile point-of-care analysis, B-detection, or in combination with continuous monitoring 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 ZigBee-Based Location-Aware Fall Detection System for Improving Elderly Telecare

PubMed Central

Huang, Chih-Ning; Chan, Chia-Tai

2014-01-01

Falls are the primary cause of accidents among the elderly and frequently cause fatal and non-fatal injuries associated with a large amount of medical costs. Fall detection using wearable wireless sensor nodes has the potential of improving elderly telecare. This investigation proposes a ZigBee-based location-aware fall detection system for elderly telecare that provides an unobstructed communication between the elderly and caregivers when falls happen. The system is based on ZigBee-based sensor networks, and the sensor node consists of a motherboard with a tri-axial accelerometer and a ZigBee module. A wireless sensor node worn on the waist continuously detects fall events and starts an indoor positioning engine as soon as a fall happens. In the fall detection scheme, this study proposes a three-phase threshold-based fall detection algorithm to detect critical and normal falls. The fall alarm can be canceled by pressing and holding the emergency fall button only when a normal fall is detected. On the other hand, there are three phases in the indoor positioning engine: path loss survey phase, Received Signal Strength Indicator (RSSI) collection phase and location calculation phase. Finally, the location of the faller will be calculated by a k-nearest neighbor algorithm with weighted RSSI. The experimental results demonstrate that the fall detection algorithm achieves 95.63% sensitivity, 73.5% specificity, 88.62% accuracy and 88.6% precision. Furthermore, the average error distance for indoor positioning is 1.15 ± 0.54 m. The proposed system successfully delivers critical information to remote telecare providers who can then immediately help a fallen person. PMID:24743841

Rubber hose surface defect detection system based on machine vision

NASA Astrophysics Data System (ADS)

Meng, Fanwu; Ren, Jingrui; Wang, Qi; Zhang, Teng

2018-01-01

As an important part of connecting engine, air filter, engine, cooling system and automobile air-conditioning system, automotive hose is widely used in automobile. Therefore, the determination of the surface quality of the hose is particularly important. This research is based on machine vision technology, using HALCON algorithm for the processing of the hose image, and identifying the surface defects of the hose. In order to improve the detection accuracy of visual system, this paper proposes a method to classify the defects to reduce misjudegment. The experimental results show that the method can detect surface defects accurately.

Optically Based Flame Detection in the NASA Langley 8-ft High- Temperature Wind Tunnel

NASA Technical Reports Server (NTRS)

Borg, Stephen E.

2005-01-01

Two optically based flame-detection systems have been developed for use in NASA Langley's 8-Foot High-Temperature Tunnel (8-ft HTT). These systems are used to detect the presence and stability of the main-burner and pilot-level flames during facility operation. System design considerations will be discussed, and a detailed description of the system components and circuit diagrams will be provided in the Appendices of this report. A more detailed description of the manufacturing process used in the fabrication of the fiber-optic probes is covered in NASA TM-2001-211233.

Fast neutron counting in a mobile, trailer-based search platform

NASA Astrophysics Data System (ADS)

Hayward, Jason P.; Sparger, John; Fabris, Lorenzo; Newby, Robert J.

2017-12-01

Trailer-based search platforms for detection of radiological and nuclear threats are often based upon coded aperture gamma-ray imaging, because this method can be rendered insensitive to local variations in gamma background while still localizing the source well. Since gamma source emissions are rather easily shielded, in this work we consider the addition of fast neutron counting to a mobile platform for detection of sources containing Pu. A proof-of-concept system capable of combined gamma and neutron coded-aperture imaging was built inside of a trailer and used to detect a 252Cf source while driving along a roadway. Neutron detector types employed included EJ-309 in a detector plane and EJ-299-33 in a front mask plane. While the 252Cf gamma emissions were not readily detectable while driving by at 16.9 m standoff, the neutron emissions can be detected while moving. Mobile detection performance for this system and a scaled-up system design are presented, along with implications for threat sensing.

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

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

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

A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

PubMed Central

Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

2013-01-01

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors. PMID:23529146

A distributed signature detection method for detecting intrusions in sensor systems.

PubMed

Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

2013-03-25

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu-Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors.

On-road vehicle detection: a review.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-05-01

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.

Event detection in an assisted living environment.

PubMed

Stroiescu, Florin; Daly, Kieran; Kuris, Benjamin

2011-01-01

This paper presents the design of a wireless event detection and in building location awareness system. The systems architecture is based on using a body worn sensor to detect events such as falls where they occur in an assisted living environment. This process involves developing event detection algorithms and transmitting such events wirelessly to an in house network based on the 802.15.4 protocol. The network would then generate alerts both in the assisted living facility and remotely to an offsite monitoring facility. The focus of this paper is on the design of the system architecture and the compliance challenges in applying this technology.

Design of an infrared camera based aircraft detection system for laser guide star installations

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

Friedman, H.; Macintosh, B.

1996-03-05

There have been incidents in which the irradiance resulting from laser guide stars have temporarily blinded pilots or passengers of aircraft. An aircraft detection system based on passive near infrared cameras (instead of active radar) is described in this report.

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

PubMed Central

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

2015-01-01

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

State-Based Network Intrusion Detection Systems for SCADA Protocols: A Proof of Concept

NASA Astrophysics Data System (ADS)

Carcano, Andrea; Fovino, Igor Nai; Masera, Marcelo; Trombetta, Alberto

We present a novel Intrusion Detection System able to detect complex attacks to SCADA systems. By complex attack, we mean a set of commands (carried in Modbus packets) that, while licit when considered in isolation on a single-packet basis, interfere with the correct behavior of the system. The proposed IDS detects such attacks thanks to an internal representation of the controlled SCADA system and a corresponding rule language, powerful enough to express the system's critical states. Furthermore, we detail the implementation and provide experimental comparative results.

Detection of Structural Abnormalities Using Neural Nets

NASA Technical Reports Server (NTRS)

Zak, M.; Maccalla, A.; Daggumati, V.; Gulati, S.; Toomarian, N.

1996-01-01

This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

Research on IPv6 intrusion detection system Snort-based

NASA Astrophysics Data System (ADS)

Shen, Zihao; Wang, Hui

2010-07-01

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

Free-radical sensing by using naphthalimide based mesoporous silica (MCM-41) nanoparticles: A combined fluorescence and cellular imaging study

NASA Astrophysics Data System (ADS)

Jha, Gaurav; Roy, Subhasis; Sahu, Prabhat Kumar; Banerjee, Somnath; Anoop, N.; Rahaman, Abdur; Sarkar, Moloy

2018-01-01

Keeping in mind the advantages of material-based systems over simple molecule-based systems, we have designed and developed three inorganic-organic hybrid systems by anchoring 1,8-naphthalimide derivatives to mesoporous silica nanoparticles for detection of free radicals. Prior to photophysical study, systems are characterized by spectroscopic, microscopic and thermo-gravimetric techniques. Steady state and time-resolved fluorescence studies demonstrate that the hydrazine based system is senstive towards detection of various free radicals. Cellular imaging study reveals cell permeability and toxicity study demonstrates the non-toxic nature of the material. These studies have suggested that present system has the potential to be used in various biological applications.

Model-based approach for cyber-physical attack detection in water distribution systems.

PubMed

Housh, Mashor; Ohar, Ziv

2018-08-01

Modern Water Distribution Systems (WDSs) are often controlled by Supervisory Control and Data Acquisition (SCADA) systems and Programmable Logic Controllers (PLCs) which manage their operation and maintain a reliable water supply. As such, and with the cyber layer becoming a central component of WDS operations, these systems are at a greater risk of being subjected to cyberattacks. This paper offers a model-based methodology based on a detailed hydraulic understanding of WDSs combined with an anomaly detection algorithm for the identification of complex cyberattacks that cannot be fully identified by hydraulically based rules alone. The results show that the proposed algorithm is capable of achieving the best-known performance when tested on the data published in the BATtle of the Attack Detection ALgorithms (BATADAL) competition (http://www.batadal.net). Copyright © 2018. Published by Elsevier Ltd.

Is comprehension necessary for error detection? A conflict-based account of monitoring in speech production

PubMed Central

Nozari, Nazbanou; Dell, Gary S.; Schwartz, Myrna F.

2011-01-01

Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the double dissociation between comprehension and error-detection ability observed in the aphasic patients. We propose a new theory of speech-error detection which is instead based on the production process itself. The theory borrows from studies of forced-choice-response tasks the notion that error detection is accomplished by monitoring response conflict via a frontal brain structure, such as the anterior cingulate cortex. We adapt this idea to the two-step model of word production, and test the model-derived predictions on a sample of aphasic patients. Our results show a strong correlation between patients’ error-detection ability and the model’s characterization of their production skills, and no significant correlation between error detection and comprehension measures, thus supporting a production-based monitor, generally, and the implemented conflict-based monitor in particular. The successful application of the conflict-based theory to error-detection in linguistic, as well as non-linguistic domains points to a domain-general monitoring system. PMID:21652015

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

PubMed

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

2010-01-01

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

Determination of total sulfur content via sulfur-specific chemiluminescence detection

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

Kubala, S.W.; Campbell, D.N.; DiSanzo, F.P.

A specially designed system, based upon sulfur-specific chemiluminescence detection (SSCD), was developed to permit the determination of total sulfur content in a variety of samples. This type of detection system possesses several advantages such as excellent linearity and selectivity, low minimum detectable levels, and an equimolar response to various sulfur compounds. This paper will focus on the design and application of a sulfur-specific chemiluminescence detection system for use in determining total sulfur content in gasoline.

Monocular precrash vehicle detection: features and classifiers.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-07-01

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

TOXICITY-BASED CHEMICAL AGENT DETECTION SYSTEMS: CONTINUOUS MONITOR AND EXPOSURE HISTORY

EPA Science Inventory

This project will develop and characterize chemical agent detection systems that will provide broad toxicological screening information to first responders and building decontamination personnel. The primary goal for this technology is to detect the presence of airborne chemic...

Hierarchical structural health monitoring system combining a fiber optic spinal cord network and distributed nerve cell devices

NASA Astrophysics Data System (ADS)

Minakuchi, Shu; Tsukamoto, Haruka; Takeda, Nobuo

2009-03-01

This study proposes novel hierarchical sensing concept for detecting damages in composite structures. In the hierarchical system, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with the optical fiber network through transducing mechanisms. The distributed "sensory nerve cell" devices detect the damage, and the fiber optic "spinal cord" network gathers damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of the hierarchical sensing system thorough comparison with existing fiber optic based systems and nerve systems in the animal kingdom. Then, in order to validate the proposed sensing concept, impact damage detection system for the composite structure was proposed. The sensor devices were developed based on Comparative Vacuum Monitoring (CVM) system and the Brillouin based distributed strain sensing was utilized to gather the damage signals from the distributed devices. Finally a verification test was conducted using prototype devices. Occurrence of barely visible impact damage was successfully detected and it was clearly indicated that the hierarchical system has better repairability, higher robustness, and wider monitorable area compared to existing systems utilizing embedded optical fiber sensors.

Design of Cyber Attack Precursor Symptom Detection Algorithm through System Base Behavior Analysis and Memory Monitoring

NASA Astrophysics Data System (ADS)

Jung, Sungmo; Kim, Jong Hyun; Cagalaban, Giovanni; Lim, Ji-Hoon; Kim, Seoksoo

More recently, botnet-based cyber attacks, including a spam mail or a DDos attack, have sharply increased, which poses a fatal threat to Internet services. At present, antivirus businesses make it top priority to detect malicious code in the shortest time possible (Lv.2), based on the graph showing a relation between spread of malicious code and time, which allows them to detect after malicious code occurs. Despite early detection, however, it is not possible to prevent malicious code from occurring. Thus, we have developed an algorithm that can detect precursor symptoms at Lv.1 to prevent a cyber attack using an evasion method of 'an executing environment aware attack' by analyzing system behaviors and monitoring memory.

Coherent receiver design based on digital signal processing in optical high-speed intersatellite links with M-phase-shift keying

NASA Astrophysics Data System (ADS)

Schaefer, Semjon; Gregory, Mark; Rosenkranz, Werner

2016-11-01

We present simulative and experimental investigations of different coherent receiver designs for high-speed optical intersatellite links. We focus on frequency offset (FO) compensation in homodyne and intradyne detection systems. The considered laser communication terminal uses an optical phase-locked loop (OPLL), which ensures stable homodyne detection. However, the hardware complexity increases with the modulation order. Therefore, we show that software-based intradyne detection is an attractive alternative for OPLL-based homodyne systems. Our approach is based on digital FO and phase noise compensation, in order to achieve a more flexible coherent detection scheme. Analytic results will further show the theoretical impact of the different detection schemes on the receiver sensitivity. Finally, we compare the schemes in terms of bit error ratio measurements and optimal receiver design.

Driver fatigue detection based on eye state.

PubMed

Lin, Lizong; Huang, Chao; Ni, Xiaopeng; Wang, Jiawen; Zhang, Hao; Li, Xiao; Qian, Zhiqin

2015-01-01

Nowadays, more and more traffic accidents occur because of driver fatigue. In order to reduce and prevent it, in this study, a calculation method using PERCLOS (percentage of eye closure time) parameter characteristics based on machine vision was developed. It determined whether a driver's eyes were in a fatigue state according to the PERCLOS value. The overall workflow solutions included face detection and tracking, detection and location of the human eye, human eye tracking, eye state recognition, and driver fatigue testing. The key aspects of the detection system incorporated the detection and location of human eyes and driver fatigue testing. The simplified method of measuring the PERCLOS value of the driver was to calculate the ratio of the eyes being open and closed with the total number of frames for a given period. If the eyes were closed more than the set threshold in the total number of frames, the system would alert the driver. Through many experiments, it was shown that besides the simple detection algorithm, the rapid computing speed, and the high detection and recognition accuracies of the system, the system was demonstrated to be in accord with the real-time requirements of a driver fatigue detection system.

Communication protocol in chassis detecting wireless transmission system based on WiFi

USDA-ARS?s Scientific Manuscript database

In chassis detecting wireless transmission system, the wireless network communication protocol plays a key role in the information exchange and synchronization between the host and chassis PDA. This paper presents a wireless network transmission protocol based on TCP/IP which makes the rules of info...

A K(+)-mediated G-quadruplex formation enhancement fluorescence polarization system based on quantum dots for detection of Hg2+ and biothiols.

PubMed

Zhang, Juanni; Tian, Jianniao; He, Yanlong; Zhao, Yanchun; Zhao, Shulin

2014-02-25

A fluorescence polarization homogenous system based on CdTe/CdS QDs that employed a K(+)-mediated G-quadruplex as an enhancer was identified for sensitive and selective detection of Hg(2+) and biothiols in complex samples.

Smartphone-based cyclic voltammetry system with graphene modified screen printed electrodes for glucose detection.

PubMed

Ji, Daizong; Liu, Lei; Li, Shuang; Chen, Chen; Lu, Yanli; Wu, Jiajia; Liu, Qingjun

2017-12-15

Smartphone-based electrochemical devices have such advantages as the low price, miniaturization, and obtaining the real-time data. As a popular electrochemical method, cyclic voltammetry (CV) has shown its great practicability for quantitative detection and electrodes modification. In this study, a smartphone-based CV system with a simple method of electrode modification was constructed to perform electrochemical detections. The system was composed of these main portions: modified electrodes, portable electrochemical detector and smartphone. Among them, the detector was comprised of an energy transformation module applying the stimuli signals, and a low-cost potentiostat module for CV measurements with a Bluetooth module for transmitting data and commands. With an Application (App), the smartphone was used as the controller and displayer of the system. Through controlling of different scan rates, the smartphone-based system could perform CV detections for redox couples with test errors less than 3.8% compared to that of commercial electrochemical workstation. Also, the reduced graphene oxide (rGO) and sensitive substance could be modified by the system on the screen printed electrodes for detections. As a demonstration, 3-amino phenylboronic acid (APBA) was used as the sensitive substance to fabricate a glucose sensor. Finally, the experimental data of the system were shown the linear, sensitive, and specific responses to glucose at different doses, even in blood serum as low as about 0.026mM with 3δ/slope calculation. Thus, the system could show great potentials of detection and modification of electrodes in various fields, such as public health, water monitoring, and food quality. Copyright © 2017 Elsevier B.V. All rights reserved.

The Assessment of Liver Reserve Function by Spectrophotometry based on Determination of Phenacetin and Paracetamol.

PubMed

Ren, Rui; Ma, Yongmei; Ma, Wanshan; Lu, Sumei

2015-01-01

To establish a technical system for assessing liver reserve function based on spectrophotometry by detection of phenacetin and paracetamol in blood samples. Taking detected contents of phenacetin and paracetamol by high performance liquid chromatography (HPLC) as standard, which was proved to be able to detect drug concentrations with high resolution and accuracy, we established a technical system based on the spectrophotometric technique to assay phenacetin and paracetamol, including the color system, the maximum absorption wavelength, the influence factors of color system, and the optimal conditions for hydrolysis. Then we verified our established system compared with that under HPLC by recovery test. This study established a technical system to detect phenacetin and paracetamol in blood samples using spectrophotometry. Mainly, 3 mol/L hydrochloric acid (HCl) was added to samples for hydrolysis for 30 minutes, then, adding 0.02% 1,2-naphthoquinone-4-sulfonate (NQS), 1% cetyltrimethyl ammonium bromide (CTA) and 2% sodium hydroxide (or 3% sodium carbonate) (ratio of 1:6:1:2 or 3), and the absorbance was measured at 500 nm and 570 nm to calculate their concentrations. Using an established spectrophotometric system to detect phenacetin and paracetamol in blood samples could assess liver reserve function, which was proved comparable with HPLC in resolution and repeatability.

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

Multi-modal intelligent seizure acquisition (MISA) system--a new approach towards seizure detection based on full body motion measures.

PubMed

Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Terney, Daniella; Sams, Thomas; Sorensen, Helge B D

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG) and audio and video recording. The results showed that a non-subject specific MISA system developed on data from the modalities: accelerometer (ACM), gyroscope and EMG is able to detect 98% of the simulated seizures and at the same time mistakes only 4 of the normal movements for seizures. If the system is individualized (subject specific) it is able to detect all simulated seizures with a maximum of 1 false positive. Based on the results from the simulated seizures and normal movements the MISA system seems to be a promising approach to seizure detection.

Using State Estimation Residuals to Detect Abnormal SCADA Data

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

Ma, Jian; Chen, Yousu; Huang, Zhenyu

2010-04-30

Detection of abnormal supervisory control and data acquisition (SCADA) data is critically important for safe and secure operation of modern power systems. In this paper, a methodology of abnormal SCADA data detection based on state estimation residuals is presented. Preceded with a brief overview of outlier detection methods and bad SCADA data detection for state estimation, the framework of the proposed methodology is described. Instead of using original SCADA measurements as the bad data sources, the residuals calculated based on the results of the state estimator are used as the input for the outlier detection algorithm. The BACON algorithm ismore » applied to the outlier detection task. The IEEE 118-bus system is used as a test base to evaluate the effectiveness of the proposed methodology. The accuracy of the BACON method is compared with that of the 3-σ method for the simulated SCADA measurements and residuals.« less

Cold-Rolled Strip Steel Stress Detection Technology Based on a Magnetoresistance Sensor and the Magnetoelastic Effect

PubMed Central

Guan, Ben; Zang, Yong; Han, Xiaohui; Zheng, Kailun

2018-01-01

Driven by the demands for contactless stress detection, technologies are being used for shape control when producing cold-rolled strips. This paper presents a novel contactless stress detection technology based on a magnetoresistance sensor and the magnetoelastic effect, enabling the detection of internal stress in manufactured cold-rolled strips. An experimental device was designed and produced. Characteristics of this detection technology were investigated through experiments assisted by theoretical analysis. Theoretically, a linear correlation exists between the internal stress of strip steel and the voltage output of a magneto-resistive sensor. Therefore, for this stress detection system, the sensitivity of the stress detection was adjusted by adjusting the supply voltage of the magnetoresistance sensor, detection distance, and other relevant parameters. The stress detection experimental results showed that this detection system has good repeatability and linearity. The detection error was controlled within 1.5%. Moreover, the intrinsic factors of the detected strip steel, including thickness, carbon percentage, and crystal orientation, also affected the sensitivity of the detection system. The detection technology proposed in this research enables online contactless detection and meets the requirements for cold-rolled steel strips. PMID:29883387

Cold-Rolled Strip Steel Stress Detection Technology Based on a Magnetoresistance Sensor and the Magnetoelastic Effect.

PubMed

Guan, Ben; Zang, Yong; Han, Xiaohui; Zheng, Kailun

2018-05-21

Driven by the demands for contactless stress detection, technologies are being used for shape control when producing cold-rolled strips. This paper presents a novel contactless stress detection technology based on a magnetoresistance sensor and the magnetoelastic effect, enabling the detection of internal stress in manufactured cold-rolled strips. An experimental device was designed and produced. Characteristics of this detection technology were investigated through experiments assisted by theoretical analysis. Theoretically, a linear correlation exists between the internal stress of strip steel and the voltage output of a magneto-resistive sensor. Therefore, for this stress detection system, the sensitivity of the stress detection was adjusted by adjusting the supply voltage of the magnetoresistance sensor, detection distance, and other relevant parameters. The stress detection experimental results showed that this detection system has good repeatability and linearity. The detection error was controlled within 1.5%. Moreover, the intrinsic factors of the detected strip steel, including thickness, carbon percentage, and crystal orientation, also affected the sensitivity of the detection system. The detection technology proposed in this research enables online contactless detection and meets the requirements for cold-rolled steel strips.

A posture recognition based fall detection system for monitoring an elderly person in a smart home environment.

PubMed

Yu, Miao; Rhuma, Adel; Naqvi, Syed Mohsen; Wang, Liang; Chambers, Jonathon

2012-11-01

We propose a novel computer vision based fall detection system for monitoring an elderly person in a home care application. Background subtraction is applied to extract the foreground human body and the result is improved by using certain post-processing. Information from ellipse fitting and a projection histogram along the axes of the ellipse are used as the features for distinguishing different postures of the human. These features are then fed into a directed acyclic graph support vector machine (DAGSVM) for posture classification, the result of which is then combined with derived floor information to detect a fall. From a dataset of 15 people, we show that our fall detection system can achieve a high fall detection rate (97.08%) and a very low false detection rate (0.8%) in a simulated home environment.

Development of gas chromatographic methods for the analyses of organic carbonate-based electrolytes

NASA Astrophysics Data System (ADS)

Terborg, Lydia; Weber, Sascha; Passerini, Stefano; Winter, Martin; Karst, Uwe; Nowak, Sascha

2014-01-01

In this work, novel methods based on gas chromatography (GC) for the investigation of common organic carbonate-based electrolyte systems are presented, which are used in lithium ion batteries. The methods were developed for flame ionization detection (FID), mass spectrometric detection (MS). Further, headspace (HS) sampling for the investigation of solid samples like electrodes is reported. Limits of detection are reported for FID. Finally, the developed methods were applied to the electrolyte system of commercially available lithium ion batteries as well as on in-house assembled cells.

Automatic on-line detection system design research on internal defects of metal materials based on optical fiber F-P sensing technology

NASA Astrophysics Data System (ADS)

Xia, Liu; Shan, Ning; Chao, Ban; Caoshan, Wang

2016-10-01

Metal materials have been used in aerospace and other industrial fields widely because of its excellent characteristics, so its internal defects detection is very important. Ultrasound technology is used widely in the fields of nondestructive detection because of its excellent characteristic. But the conventional detection instrument for ultrasound, which has shortcomings such as low intelligent level and long development cycles, limits its development. In this paper, the theory of ultrasound detection is analyzed. A computational method of the defects distributional position is given. The non-contact type optical fiber F-P interference cavity structure is designed and the length of origin cavity is given. The real-time on-line ultrasound detecting experiment devices for internal defects of metal materials is established based on the optical fiber F-P sensing system. The virtual instrument of automation ultrasound detection internal defects is developed based on LabVIEW software and the experimental study is carried out. The results show that this system can be used in internal defect real-time on-line locating of engineering structures effectively. This system has higher measurement precision. Relative error is 6.7%. It can be met the requirement of engineering practice. The system is characterized by simple operation, easy realization. The software has a friendly interface, good expansibility, and high intelligent level.

A Two-Stage Composition Method for Danger-Aware Services Based on Context Similarity

NASA Astrophysics Data System (ADS)

Wang, Junbo; Cheng, Zixue; Jing, Lei; Ota, Kaoru; Kansen, Mizuo

Context-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Danger-aware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

Design and characterization of a dead-time regime enhanced early photon projection imaging system

NASA Astrophysics Data System (ADS)

Sinha, L.; Fogarty, M.; Zhou, W.; Giudice, A.; Brankov, J. G.; Tichauer, K. M.

2018-04-01

Scattering of visible and near-infrared light in biological tissue reduces spatial resolution for imaging of tissues thicker than 100 μm. In this study, an optical projection imaging system is presented and characterized that exploits the dead-time characteristics typical of photon counting modules based on single photon avalanche diodes (SPADs). With this system, it is possible to attenuate the detection of more scattered late-arriving photons, such that detection of less scattered early-arriving photons can be enhanced with increased light intensity, without being impeded by the maximum count rate of the SPADs. The system has the potential to provide transmittance-based anatomical information or fluorescence-based functional information (with slight modification in the instrumentation) of biological samples with improved resolution in the mesoscopic domain (0.1-2 cm). The system design, calibration, stability, and performance were evaluated using simulation and experimental phantom studies. The proposed system allows for the detection of very-rare early-photons at a higher frequency and with a better signal-to-noise ratio. The experimental results demonstrated over a 3.4-fold improvement in the spatial resolution using early photon detection vs. conventional detection, and a 1000-fold improvement in imaging time using enhanced early detection vs. conventional early photon detection in a 4-mm thick phantom with a tissue-equivalent absorption coefficient of μa = 0.05 mm-1 and a reduced scattering coefficient of μs' = 5 mm-1.

Anomaly Detection for Next-Generation Space Launch Ground Operations

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Iverson, David L.; Hall, David R.; Taylor, William M.; Patterson-Hine, Ann; Brown, Barbara; Ferrell, Bob A.; Waterman, Robert D.

2010-01-01

NASA is developing new capabilities that will enable future human exploration missions while reducing mission risk and cost. The Fault Detection, Isolation, and Recovery (FDIR) project aims to demonstrate the utility of integrated vehicle health management (IVHM) tools in the domain of ground support equipment (GSE) to be used for the next generation launch vehicles. In addition to demonstrating the utility of IVHM tools for GSE, FDIR aims to mature promising tools for use on future missions and document the level of effort - and hence cost - required to implement an application with each selected tool. One of the FDIR capabilities is anomaly detection, i.e., detecting off-nominal behavior. The tool we selected for this task uses a data-driven approach. Unlike rule-based and model-based systems that require manual extraction of system knowledge, data-driven systems take a radically different approach to reasoning. At the basic level, they start with data that represent nominal functioning of the system and automatically learn expected system behavior. The behavior is encoded in a knowledge base that represents "in-family" system operations. During real-time system monitoring or during post-flight analysis, incoming data is compared to that nominal system operating behavior knowledge base; a distance representing deviation from nominal is computed, providing a measure of how far "out of family" current behavior is. We describe the selected tool for FDIR anomaly detection - Inductive Monitoring System (IMS), how it fits into the FDIR architecture, the operations concept for the GSE anomaly monitoring, and some preliminary results of applying IMS to a Space Shuttle GSE anomaly.

Disposable pen-shaped capillary gel electrophoresis cartridge for fluorescence detection of bio-molecules

NASA Astrophysics Data System (ADS)

Amirkhanian, Varoujan; Tsai, Shou-Kuan

2014-03-01

We introduce a novel and cost-effective capillary gel electrophoresis (CGE) system utilizing disposable pen-shaped gelcartridges for highly efficient, high speed, high throughput fluorescence detection of bio-molecules. The CGE system has been integrated with dual excitation and emission optical-fibers with micro-ball end design for fluorescence detection of bio-molecules separated and detected in a disposable pen-shaped capillary gel electrophoresis cartridge. The high-performance capillary gel electrophoresis (CGE) analyzer has been optimized for glycoprotein analysis type applications. Using commercially available labeling agent such as ANTS (8-aminonapthalene-1,3,6- trisulfonate) as an indicator, the capillary gel electrophoresis-based glycan analyzer provides high detection sensitivity and high resolving power in 2-5 minutes of separations. The system can hold total of 96 samples, which can be automatically analyzed within 4-5 hours. This affordable fiber optic based fluorescence detection system provides fast run times (4 minutes vs. 20 minutes with other CE systems), provides improved peak resolution, good linear dynamic range and reproducible migration times, that can be used in laboratories for high speed glycan (N-glycan) profiling applications. The CGE-based glycan analyzer will significantly increase the pace at which glycoprotein research is performed in the labs, saving hours of preparation time and assuring accurate, consistent and economical results.

Development of an adaptive failure detection and identification system for detecting aircraft control element failures

NASA Technical Reports Server (NTRS)

Bundick, W. Thomas

1990-01-01

A methodology for designing a failure detection and identification (FDI) system to detect and isolate control element failures in aircraft control systems is reviewed. An FDI system design for a modified B-737 aircraft resulting from this methodology is also reviewed, and the results of evaluating this system via simulation are presented. The FDI system performed well in a no-turbulence environment, but it experienced an unacceptable number of false alarms in atmospheric turbulence. An adaptive FDI system, which adjusts thresholds and other system parameters based on the estimated turbulence level, was developed and evaluated. The adaptive system performed well over all turbulence levels simulated, reliably detecting all but the smallest magnitude partially-missing-surface failures.

Cassette bacteria detection system. [for monitoring the sterility of regenerated water in spacecraft

NASA Technical Reports Server (NTRS)

1974-01-01

The design, fabrication, and testing of an automatic bacteria detection system, with a zero-g capability, based on the filter-capable approach, and intended for monitoring the sterility of regenerated water in spacecraft is discussed. The principle of detection is based on measuring the increase in chemiluminescence produced by the action of bacterial porphyrins on a luminol-hydrogen peroxide mixture. Viable organisms are detected by comparing the signal of an incubated water sample with an unincubated control. High signals for the incubated water sample indicate the presence of viable organisms.

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.

Initial Evaluation of Signal-Based Bayesian Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Russell, S.

2016-12-01

We present SIGVISA (Signal-based Vertically Integrated Seismic Analysis), a next-generation system for global seismic monitoring through Bayesian inference on seismic signals. Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a network of stations. We report results from an evaluation of SIGVISA monitoring the western United States for a two-week period following the magnitude 6.0 event in Wells, NV in February 2008. During this period, SIGVISA detects more than twice as many events as NETVISA, and three times as many as SEL3, while operating at the same precision; at lower precisions it detects up to five times as many events as SEL3. At the same time, signal-based monitoring reduces mean location errors by a factor of four relative to detection-based systems. We provide evidence that, given only IMS data, SIGVISA detects events that are missed by regional monitoring networks, indicating that our evaluations may even underestimate its performance. Finally, SIGVISA matches or exceeds the detection rates of existing systems for de novo events - events with no nearby historical seismicity - and detects through automated processing a number of such events missed even by the human analysts generating the LEB.

A multi-data source surveillance system to detect a bioterrorism attack during the G8 Summit in Scotland.

PubMed

Meyer, N; McMenamin, J; Robertson, C; Donaghy, M; Allardice, G; Cooper, D

2008-07-01

In 18 weeks, Health Protection Scotland (HPS) deployed a syndromic surveillance system to early-detect natural or intentional disease outbreaks during the G8 Summit 2005 at Gleneagles, Scotland. The system integrated clinical and non-clinical datasets. Clinical datasets included Accident & Emergency (A&E) syndromes, and General Practice (GPs) codes grouped into syndromes. Non-clinical data included telephone calls to a nurse helpline, laboratory test orders, and hotel staff absenteeism. A cumulative sum-based detection algorithm and a log-linear regression model identified signals in the data. The system had a fax-based track for real-time identification of unusual presentations. Ninety-five signals were triggered by the detection algorithms and four forms were faxed to HPS. Thirteen signals were investigated. The system successfully complemented a traditional surveillance system in identifying a small cluster of gastroenteritis among the police force and triggered interventions to prevent further cases.

Object detection with a multistatic array using singular value decomposition

DOEpatents

Hallquist, Aaron T.; Chambers, David H.

2014-07-01

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

A Novel Fiber Optic Based Surveillance System for Prevention of Pipeline Integrity Threats.

PubMed

Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F; Piote, Daniel; Pastor-Graells, Juan; Martin-Lopez, Sonia; Corredera, Pedro; Gonzalez-Herraez, Miguel

2017-02-12

This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Micro-Detection System for Determination of the Biotic or Abiotic Origin of Amino Acids

NASA Technical Reports Server (NTRS)

Bada, Jeffrey L.; Betts, Bruce (Technical Monitor)

2002-01-01

The research involved the development of a breadboard version of a spacecraft based system for the detection of amino acid chirality (handedness) on solar system bodies. The design concept has three distinct components: a sublimation chamber for the release of amino acids from an acquired sample; a microchip based capillary electrophoresis (CE) chip for the separation of amino acids and their enantiomers; and a fluorescent based detection system. In addition, we have investigated the use of a microfluidics system for the extraction of amino acids in samples in which sublimation has proven to be problematic. This is a joint project carried out at the Scripps Institution of Oceanography (SIO), University of California at San Diego; the Jet Propulsion Laboratory (JPL), Pasadena; and the Department of Chemistry, University of California, Berkeley.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

'Known Secure Sensor Measurements' for Critical Infrastructure Systems: Detecting Falsification of System State

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

Miles McQueen; Annarita Giani

2011-09-01

This paper describes a first investigation on a low cost and low false alarm, reliable mechanism for detecting manipulation of critical physical processes and falsification of system state. We call this novel mechanism Known Secure Sensor Measurements (KSSM). The method moves beyond analysis of network traffic and host based state information, in fact it uses physical measurements of the process being controlled to detect falsification of state. KSSM is intended to be incorporated into the design of new, resilient, cost effective critical infrastructure control systems. It can also be included in incremental upgrades of already in- stalled systems for enhancedmore » resilience. KSSM is based on known secure physical measurements for assessing the likelihood of an attack and will demonstrate a practical approach to creating, transmitting, and using the known secure measurements for detection.« less

The architecture of a network level intrusion detection system

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

Heady, R.; Luger, G.; Maccabe, A.

1990-08-15

This paper presents the preliminary architecture of a network level intrusion detection system. The proposed system will monitor base level information in network packets (source, destination, packet size, and time), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model.

PubMed

Hsieh, Chia-Yeh; Liu, Kai-Chun; Huang, Chih-Ning; Chu, Woei-Chyn; Chan, Chia-Tai

2017-02-08

Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides an alarm that can decrease injuries or death caused by the lack of rescue. The automatic fall detection system has opportunities to provide real-time emergency alarms for improving the safety and quality of home healthcare services. Two common technical challenges are also tackled in order to provide a reliable fall detection algorithm, including variability and ambiguity. We propose a novel hierarchical fall detection algorithm involving threshold-based and knowledge-based approaches to detect a fall event. The threshold-based approach efficiently supports the detection and identification of fall events from continuous sensor data. A multiphase fall model is utilized, including free fall, impact, and rest phases for the knowledge-based approach, which identifies fall events and has the potential to deal with the aforementioned technical challenges of a fall detection system. Seven kinds of falls and seven types of daily activities arranged in an experiment are used to explore the performance of the proposed fall detection algorithm. The overall performances of the sensitivity, specificity, precision, and accuracy using a knowledge-based algorithm are 99.79%, 98.74%, 99.05% and 99.33%, respectively. The results show that the proposed novel hierarchical fall detection algorithm can cope with the variability and ambiguity of the technical challenges and fulfill the reliability, adaptability, and flexibility requirements of an automatic fall detection system with respect to the individual differences.

Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model

PubMed Central

Hsieh, Chia-Yeh; Liu, Kai-Chun; Huang, Chih-Ning; Chu, Woei-Chyn; Chan, Chia-Tai

2017-01-01

Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides an alarm that can decrease injuries or death caused by the lack of rescue. The automatic fall detection system has opportunities to provide real-time emergency alarms for improving the safety and quality of home healthcare services. Two common technical challenges are also tackled in order to provide a reliable fall detection algorithm, including variability and ambiguity. We propose a novel hierarchical fall detection algorithm involving threshold-based and knowledge-based approaches to detect a fall event. The threshold-based approach efficiently supports the detection and identification of fall events from continuous sensor data. A multiphase fall model is utilized, including free fall, impact, and rest phases for the knowledge-based approach, which identifies fall events and has the potential to deal with the aforementioned technical challenges of a fall detection system. Seven kinds of falls and seven types of daily activities arranged in an experiment are used to explore the performance of the proposed fall detection algorithm. The overall performances of the sensitivity, specificity, precision, and accuracy using a knowledge-based algorithm are 99.79%, 98.74%, 99.05% and 99.33%, respectively. The results show that the proposed novel hierarchical fall detection algorithm can cope with the variability and ambiguity of the technical challenges and fulfill the reliability, adaptability, and flexibility requirements of an automatic fall detection system with respect to the individual differences. PMID:28208694

Could home sexually transmitted infection specimen collection with e-prescription be a cost-effective strategy for clinical trials and clinical care?

PubMed

Blake, Diane R; Spielberg, Freya; Levy, Vivian; Lensing, Shelly; Wolff, Peter A; Venkatasubramanian, Lalitha; Acevedo, Nincoshka; Padian, Nancy; Chattopadhyay, Ishita; Gaydos, Charlotte A

2015-01-01

Results of a recent demonstration project evaluating feasibility, acceptability, and cost of a Web-based sexually transmitted infection (STI) testing and e-prescription treatment program (eSTI) suggest that this approach could be a feasible alternative to clinic-based testing and treatment, but the results need to be confirmed by a randomized comparative effectiveness trial. We modeled a decision tree comparing (1) cost of eSTI screening using a home collection kit and an e-prescription for uncomplicated treatment versus (2) hypothetical costs derived from the literature for referral to standard clinic-based STI screening and treatment. Primary outcome was number of STIs detected. Analyses were conducted from the clinical trial perspective and the health care system perspective. The eSTI strategy detected 75 infections, and the clinic referral strategy detected 45 infections. Total cost of eSTI was $94,938 ($1266/STI detected) from the clinical trial perspective and $96,088 ($1281/STI detected) from the health care system perspective. Total cost of clinic referral was $87,367 ($1941/STI detected) from the clinical trial perspective and $71,668 ($1593/STI detected) from the health care system perspective. Results indicate that eSTI will likely be more cost-effective (lower cost/STI detected) than clinic-based STI screening, both in the context of clinical trials and in routine clinical care. Although our results are promising, they are based on a demonstration project and estimates from other small studies. A comparative effectiveness research trial is needed to determine actual cost and impact of the eSTI system on identification and treatment of new infections and prevention of their sequelae.

Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata.

PubMed

Ghanizadeh, Afshin; Abarghouei, Amir Atapour; Sinaie, Saman; Saad, Puteh; Shamsuddin, Siti Mariyam

2011-07-01

Iris-based biometric systems identify individuals based on the characteristics of their iris, since they are proven to remain unique for a long time. An iris recognition system includes four phases, the most important of which is preprocessing in which the iris segmentation is performed. The accuracy of an iris biometric system critically depends on the segmentation system. In this paper, an iris segmentation system using edge detection techniques and Hough transforms is presented. The newly proposed edge detection system enhances the performance of the segmentation in a way that it performs much more efficiently than the other conventional iris segmentation methods.

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

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

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

An intelligent control system for failure detection and controller reconfiguration

NASA Technical Reports Server (NTRS)

Biswas, Saroj K.

1994-01-01

We present an architecture of an intelligent restructurable control system to automatically detect failure of system components, assess its impact on system performance and safety, and reconfigure the controller for performance recovery. Fault detection is based on neural network associative memories and pattern classifiers, and is implemented using a multilayer feedforward network. Details of the fault detection network along with simulation results on health monitoring of a dc motor have been presented. Conceptual developments for fault assessment using an expert system and controller reconfiguration using a neural network are outlined.

Optimal Detection Range of RFID Tag for RFID-based Positioning System Using the k-NN Algorithm.

PubMed

Han, Soohee; Kim, Junghwan; Park, Choung-Hwan; Yoon, Hee-Cheon; Heo, Joon

2009-01-01

Positioning technology to track a moving object is an important and essential component of ubiquitous computing environments and applications. An RFID-based positioning system using the k-nearest neighbor (k-NN) algorithm can determine the position of a moving reader from observed reference data. In this study, the optimal detection range of an RFID-based positioning system was determined on the principle that tag spacing can be derived from the detection range. It was assumed that reference tags without signal strength information are regularly distributed in 1-, 2- and 3-dimensional spaces. The optimal detection range was determined, through analytical and numerical approaches, to be 125% of the tag-spacing distance in 1-dimensional space. Through numerical approaches, the range was 134% in 2-dimensional space, 143% in 3-dimensional space.

[System design of open-path natural gas leakage detection based on Fresnel lens].

PubMed

Xia, Hui; Liu, Wen-Qing; Zhang, Yu-Jun; Kan, Rui-Feng; Cui, Yi-Ben; Wang, Min; He, Ying; Cui, Xiao-Juan; Ruan, Jun; Geng, Hui

2009-03-01

Based on the technology of tunable diode laser absorption spectroscopy (TDLAS) in conjunction with second harmonic wave detection, a long open-path TDLAS system using a 1.65 microm InGaAsP distributed feedback laser was developed, which is used for detecting pipeline leakage. In this system, a high cost performance Fresnel lens is used as the receiving optical system, which receives the laser-beam reflected by a solid corner cube reflector, and focuses the receiving laser-beam to the InGaAs detector. At the same time, the influences of the concentration to the fluctuation of light intensity were taken into account in the process of measurement, and were eliminated by the method of normalized light intensity. As a result, the measurement error caused by the fluctuation of light intensity was made less than 1%. The experiment of natural gas leakage detection was simulated, and the detection sensitivity is 0.1 x 10(-6) (ratio by volume) with a total path of 320 m. According to the receiving light efficiency of the optical system and the detectable minimum light intensity of the detector, the detectable maximal optical path of the system was counted to be 2 000 m. The results of experiment show that it is a feasible design to use the Fresnel lens as the receiving optical system and can satisfy the demand of the leakage detection of natural gas.

Development of Laser Based Remote Sensing System for Inner-Concrete Defects

NASA Astrophysics Data System (ADS)

Shimada, Yoshinori; Kotyaev, Oleg

Laser-based remote sensing using a vibration detection system has been developed using a photorefractive crystal to reduce the effect of concrete surface-roughness. An electric field was applied to the crystal and the reference beam was phase shifted to increase the detection efficiency (DE). The DE increased by factor of 8.5 times compared to that when no voltage and no phase shifting were applied. Vibration from concrete defects can be detected at a distance of 5 m from the system. A vibration-canceling system has also developed that appears to be promising for canceling vibrations between the laser system and the concrete. Finally, we have constructed a prototype system that can be transported in a small truck.

A real-time standard parts inspection based on deep learning

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Cephalometric landmark detection in dental x-ray images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Lee, Hansang; Park, Minseok; Kim, Junmo

2017-03-01

In dental X-ray images, an accurate detection of cephalometric landmarks plays an important role in clinical diagnosis, treatment and surgical decisions for dental problems. In this work, we propose an end-to-end deep learning system for cephalometric landmark detection in dental X-ray images, using convolutional neural networks (CNN). For detecting 19 cephalometric landmarks in dental X-ray images, we develop a detection system using CNN-based coordinate-wise regression systems. By viewing x- and y-coordinates of all landmarks as 38 independent variables, multiple CNN-based regression systems are constructed to predict the coordinate variables from input X-ray images. First, each coordinate variable is normalized by the length of either height or width of an image. For each normalized coordinate variable, a CNN-based regression system is trained on training images and corresponding coordinate variable, which is a variable to be regressed. We train 38 regression systems with the same CNN structure on coordinate variables, respectively. Finally, we compute 38 coordinate variables with these trained systems from unseen images and extract 19 landmarks by pairing the regressed coordinates. In experiments, the public database from the Grand Challenges in Dental X-ray Image Analysis in ISBI 2015 was used and the proposed system showed promising performance by successfully locating the cephalometric landmarks within considerable margins from the ground truths.

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.

Establishment of novel detection system for embryonic stem cell-derived hepatocyte-like cells based on nongenetic manipulation with indocyanine green.

PubMed

Yoshie, Susumu; Ito, Jun; Shirasawa, Sakiko; Yokoyama, Tadayuki; Fujimura, Yuu; Takeda, Kazuo; Mizuguchi, Masahiro; Matsumoto, Ken; Tomotsune, Daihachiro; Sasaki, Katsunori

2012-01-01

Hepatocytes derived from embryonic stem cells (ESCs) are expected to be useful for basic research and clinical applications. However, in several studies, genetic methods used to detect and obtain them are difficult and pose major safety problems. Therefore, in this study, we established a novel detection system for hepatocytes by using indocyanine green (ICG), which is selectively taken up by hepatocytes, based on nongenetic manipulation. ICG has maximum light absorption near 780 nm, and it fluoresces between 800 and 900 nm. Making use of these properties, we developed flow cytometry equipped with an excitation lazer of 785 nm and specific bandpass filters and successfully detected ESC-derived ICG-positive cells that were periodic acid-Schiff positive and expressed hepatocyte phenotypic mRNAs. These results demonstrate that this detection system based on nongenetic manipulation with ICG will lead to isolate hepatocytes generated from ESCs and provide the appropriate levels of stability, quality, and safety required for cell source for cell-based therapy and pharmaceutical studies such as toxicology.

Vision-based object detection and recognition system for intelligent vehicles

NASA Astrophysics Data System (ADS)

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

1999-01-01

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

Nondestructive and rapid detection of potato black heart based on machine vision technology

NASA Astrophysics Data System (ADS)

Tian, Fang; Peng, Yankun; Wei, Wensong

2016-05-01

Potatoes are one of the major food crops in the world. Potato black heart is a kind of defect that the surface is intact while the tissues in skin become black. This kind of potato has lost the edibleness, but it's difficult to be detected with conventional methods. A nondestructive detection system based on the machine vision technology was proposed in this study to distinguish the normal and black heart of potatoes according to the different transmittance of them. The detection system was equipped with a monochrome CCD camera, LED light sources for transmitted illumination and a computer. Firstly, the transmission images of normal and black heart potatoes were taken by the detection system. Then the images were processed by algorithm written with VC++. As the transmitted light intensity was influenced by the radial dimension of the potato samples, the relationship between the grayscale value and the potato radial dimension was acquired by analyzing the grayscale value changing rule of the transmission image. Then proper judging condition was confirmed to distinguish the normal and black heart of potatoes after image preprocessing. The results showed that the nondestructive system built coupled with the processing methods was accessible for the detection of potato black heart at a considerable accuracy rate. The transmission detection technique based on machine vision is nondestructive and feasible to realize the detection of potato black heart.

A matched filter method for ground-based sub-noise detection of terrestrial extrasolar planets in eclipsing binaries: application to CM Draconis.

PubMed

Jenkins, J M; Doyle, L R; Cullers, D K

1996-02-01

The photometric detection of extrasolar planets by transits in eclipsing binary systems can be significantly improved by cross-correlating the observational light curves with synthetic models of possible planetary transit features, essentially a matched filter approach. We demonstrate the utility and application of this transit detection algorithm for ground-based detections of terrestrial-sized (Earth-to-Neptune radii) extrasolar planets in the dwarf M-star eclipsing binary system CM Draconis. Preliminary photometric observational data of this system demonstrate that the observational noise is well characterized as white and Gaussian at the observational time steps required for precision photometric measurements. Depending on planet formation scenarios, terrestrial-sized planets may form quite close to this low-luminosity system. We demonstrate, for example, that planets as small as 1.4 Earth radii with periods on the order of a few months in the CM Draconis system could be detected at the 99.9% confidence level in less than a year using 1-m class telescopes from the ground. This result contradicts commonly held assumptions limiting present ground-based efforts to, at best, detections of gas giant planets after several years of observation. This method can be readily extended to a number of other larger star systems with the utilization of larger telescopes and longer observing times. Its extension to spacecraft observations should also allow the determination of the presence of terrestrial-sized planets in nearly 100 other known eclipsing binary systems.

A matched filter method for ground-based sub-noise detection of terrestrial extrasolar planets in eclipsing binaries: application to CM Draconis

NASA Technical Reports Server (NTRS)

Jenkins, J. M.; Doyle, L. R.; Cullers, D. K.

1996-01-01

The photometric detection of extrasolar planets by transits in eclipsing binary systems can be significantly improved by cross-correlating the observational light curves with synthetic models of possible planetary transit features, essentially a matched filter approach. We demonstrate the utility and application of this transit detection algorithm for ground-based detections of terrestrial-sized (Earth-to-Neptune radii) extrasolar planets in the dwarf M-star eclipsing binary system CM Draconis. Preliminary photometric observational data of this system demonstrate that the observational noise is well characterized as white and Gaussian at the observational time steps required for precision photometric measurements. Depending on planet formation scenarios, terrestrial-sized planets may form quite close to this low-luminosity system. We demonstrate, for example, that planets as small as 1.4 Earth radii with periods on the order of a few months in the CM Draconis system could be detected at the 99.9% confidence level in less than a year using 1-m class telescopes from the ground. This result contradicts commonly held assumptions limiting present ground-based efforts to, at best, detections of gas giant planets after several years of observation. This method can be readily extended to a number of other larger star systems with the utilization of larger telescopes and longer observing times. Its extension to spacecraft observations should also allow the determination of the presence of terrestrial-sized planets in nearly 100 other known eclipsing binary systems.

Evanescent field Sensors Based on Tantalum Pentoxide Waveguides – A Review

PubMed Central

Schmitt, Katrin; Oehse, Kerstin; Sulz, Gerd; Hoffmann, Christian

2008-01-01

Evanescent field sensors based on waveguide surfaces play an important role where high sensitivity is required. Particularly tantalum pentoxide (Ta2O5) is a suitable material for thin-film waveguides due to its high refractive index and low attenuation. Many label-free biosensor systems such as grating couplers and interferometric sensors as well as fluorescence-based systems benefit from this waveguide material leading to extremely high sensitivity. Some biosensor systems based on Ta2O5 waveguides already took the step into commercialization. This report reviews the various detection systems in terms of limit of detection, the applications, and the suitable surface chemistry. PMID:27879731

Real-Time N2O Gas Detection System for Agricultural Production Using a 4.6-μm-Band Laser Source Based on a Periodically Poled LiNbO3 Ridge Waveguide

PubMed Central

Tokura, Akio; Asobe, Masaki; Enbutsu, Koji; Yoshihara, Toshihiro; Hashida, Shin-nosuke; Takenouchi, Hirokazu

2013-01-01

This article describes a gas monitoring system for detecting nitrous oxide (N2O) gas using a compact mid-infrared laser source based on difference-frequency generation in a quasi-phase-matched LiNbO3 waveguide. We obtained a stable output power of 0.62 mW from a 4.6-μm-band continuous-wave laser source operating at room temperature. This laser source enabled us to detect atmospheric N2O gas at a concentration as low as 35 parts per billion. Using this laser source, we constructed a new real-time in-situ monitoring system for detecting N2O gas emitted from potted plants. A few weeks of monitoring with the developed detection system revealed a strong relationship between nitrogen fertilization and N2O emission. This system is promising for the in-situ long-term monitoring of N2O in agricultural production, and it is also applicable to the detection of other greenhouse gases. PMID:23921829

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.

Real-time N2O gas detection system for agricultural production using a 4.6-µm-band laser source based on a periodically poled LiNbO3 ridge waveguide.

PubMed

Tokura, Akio; Asobe, Masaki; Enbutsu, Koji; Yoshihara, Toshihiro; Hashida, Shin-nosuke; Takenouchi, Hirokazu

2013-08-05

This article describes a gas monitoring system for detecting nitrous oxide (N2O) gas using a compact mid-infrared laser source based on difference-frequency generation in a quasi-phase-matched LiNbO3 waveguide. We obtained a stable output power of 0.62 mW from a 4.6-μm-band continuous-wave laser source operating at room temperature. This laser source enabled us to detect atmospheric N2O gas at a concentration as low as 35 parts per billion. Using this laser source, we constructed a new real-time in-situ monitoring system for detecting N2O gas emitted from potted plants. A few weeks of monitoring with the developed detection system revealed a strong relationship between nitrogen fertilization and N2O emission. This system is promising for the in-situ long-term monitoring of N2O in agricultural production, and it is also applicable to the detection of other greenhouse gases.

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

DTIC Science & Technology

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

Note: An improved 3D imaging system for electron-electron coincidence measurements

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

Lin, Yun Fei; Lee, Suk Kyoung; Adhikari, Pradip

We demonstrate an improved imaging system that can achieve highly efficient 3D detection of two electrons in coincidence. The imaging system is based on a fast frame complementary metal-oxide semiconductor camera and a high-speed waveform digitizer. We have shown previously that this detection system is capable of 3D detection of ions and electrons with good temporal and spatial resolution. Here, we show that with a new timing analysis algorithm, this system can achieve an unprecedented dead-time (<0.7 ns) and dead-space (<1 mm) when detecting two electrons. A true zero dead-time detection is also demonstrated.

Note: An improved 3D imaging system for electron-electron coincidence measurements

NASA Astrophysics Data System (ADS)

Lin, Yun Fei; Lee, Suk Kyoung; Adhikari, Pradip; Herath, Thushani; Lingenfelter, Steven; Winney, Alexander H.; Li, Wen

2015-09-01

We demonstrate an improved imaging system that can achieve highly efficient 3D detection of two electrons in coincidence. The imaging system is based on a fast frame complementary metal-oxide semiconductor camera and a high-speed waveform digitizer. We have shown previously that this detection system is capable of 3D detection of ions and electrons with good temporal and spatial resolution. Here, we show that with a new timing analysis algorithm, this system can achieve an unprecedented dead-time (<0.7 ns) and dead-space (<1 mm) when detecting two electrons. A true zero dead-time detection is also demonstrated.

Comparing the detection of iron-based pottery pigment on a carbon-coated sherd by SEM-EDS and by Micro-XRF-SEM.

PubMed

Pendleton, Michael W; Washburn, Dorothy K; Ellis, E Ann; Pendleton, Bonnie B

2014-03-01

The same sherd was analyzed using a scanning electron microscope with energy dispersive spectroscopy (SEM-EDS) and a micro X-ray fluorescence tube attached to a scanning electron microscope (Micro-XRF-SEM) to compare the effectiveness of elemental detection of iron-based pigment. To enhance SEM-EDS mapping, the sherd was carbon coated. The carbon coating was not required to produce Micro-XRF-SEM maps but was applied to maintain an unbiased comparison between the systems. The Micro-XRF-SEM analysis was capable of lower limits of detection than that of the SEM-EDS system, and therefore the Micro-XRF-SEM system could produce elemental maps of elements not easily detected by SEM-EDS mapping systems. Because SEM-EDS and Micro-XRF-SEM have been used for imaging and chemical analysis of biological samples, this comparison of the detection systems should be useful to biologists, especially those involved in bone or tooth (hard tissue) analysis.

Comparing the Detection of Iron-Based Pottery Pigment on a Carbon-Coated Sherd by SEM-EDS and by Micro-XRF-SEM

PubMed Central

Pendleton, Michael W.; Washburn, Dorothy K.; Ellis, E. Ann; Pendleton, Bonnie B.

2014-01-01

The same sherd was analyzed using a scanning electron microscope with energy dispersive spectroscopy (SEM-EDS) and a micro X-ray fluorescence tube attached to a scanning electron microscope (Micro-XRF-SEM) to compare the effectiveness of elemental detection of iron-based pigment. To enhance SEM-EDS mapping, the sherd was carbon coated. The carbon coating was not required to produce Micro-XRF-SEM maps but was applied to maintain an unbiased comparison between the systems. The Micro-XRF-SEM analysis was capable of lower limits of detection than that of the SEM-EDS system, and therefore the Micro-XRF-SEM system could produce elemental maps of elements not easily detected by SEM-EDS mapping systems. Because SEM-EDS and Micro-XRF-SEM have been used for imaging and chemical analysis of biological samples, this comparison of the detection systems should be useful to biologists, especially those involved in bone or tooth (hard tissue) analysis. PMID:24600333

Application of nanomaterials in the bioanalytical detection of disease-related genes.

PubMed

Zhu, Xiaoqian; Li, Jiao; He, Hanping; Huang, Min; Zhang, Xiuhua; Wang, Shengfu

2015-12-15

In the diagnosis of genetic diseases and disorders, nanomaterials-based gene detection systems have significant advantages over conventional diagnostic systems in terms of simplicity, sensitivity, specificity, and portability. In this review, we describe the application of nanomaterials for disease-related genes detection in different methods excluding PCR-related method, such as colorimetry, fluorescence-based methods, electrochemistry, microarray methods, surface-enhanced Raman spectroscopy (SERS), quartz crystal microbalance (QCM) methods, and dynamic light scattering (DLS). The most commonly used nanomaterials are gold, silver, carbon and semiconducting nanoparticles. Various nanomaterials-based gene detection methods are introduced, their respective advantages are discussed, and selected examples are provided to illustrate the properties of these nanomaterials and their emerging applications for the detection of specific nucleic acid sequences. Copyright © 2015. Published by Elsevier B.V.

A portable liquid crystal-based polarized light system for the detection of organophosphorus nerve gas.

PubMed

He, Feng Jie; Liu, Hui Long; Chen, Long Cong; Xiong, Xing Liang

2018-03-01

Liquid crystal (LC)-based sensors have the advantageous properties of being fast, sensitive, and label-free, the results of which can be accessed directly only through the naked eye. However, the inherent disadvantages possessed by LC sensors, such as relying heavily on polarizing microscopes and the difficulty to quantify, have limited the possibility of field applications. Herein, we have addressed these issues by constructing a portable polarized detection system with constant temperature control. This system is mainly composed of four parts: the LC cell, the optics unit, the automatic temperature control unit, and the image processing unit. The LC cell was based on the ordering transitions of LCs in the presence of analytes. The optics unit based on the imaging principle of LCs was designed to substitute the polarizing microscope for the real-time observation. The image processing unit is expected to quantify the concentration of analytes. The results have shown that the presented system can detect dimethyl methyl phosphonate (a stimulant for organophosphorus nerve gas) within 25 s, and the limit of detection is about 10 ppb. In all, our portable system has potential in field applications.

A portable liquid crystal-based polarized light system for the detection of organophosphorus nerve gas

NASA Astrophysics Data System (ADS)

He, Feng Jie; Liu, Hui Long; Chen, Long Cong; Xiong, Xing Liang

2018-03-01

Liquid crystal (LC)-based sensors have the advantageous properties of being fast, sensitive, and label-free, the results of which can be accessed directly only through the naked eye. However, the inherent disadvantages possessed by LC sensors, such as relying heavily on polarizing microscopes and the difficulty to quantify, have limited the possibility of field applications. Herein, we have addressed these issues by constructing a portable polarized detection system with constant temperature control. This system is mainly composed of four parts: the LC cell, the optics unit, the automatic temperature control unit, and the image processing unit. The LC cell was based on the ordering transitions of LCs in the presence of analytes. The optics unit based on the imaging principle of LCs was designed to substitute the polarizing microscope for the real-time observation. The image processing unit is expected to quantify the concentration of analytes. The results have shown that the presented system can detect dimethyl methyl phosphonate (a stimulant for organophosphorus nerve gas) within 25 s, and the limit of detection is about 10 ppb. In all, our portable system has potential in field applications.

A SQUID-based metal detector—comparison to coil and x-ray systems

NASA Astrophysics Data System (ADS)

Bick, M.; Sullivan, P.; Tilbrook, D. L.; Du, J.; Gnanarajan, S.; Leslie, K. E.; Foley, C. P.

2005-03-01

The presence of foreign metal bodies and fragments in foodstuff and pharmaceutical products is of major concern to producers. Further, hidden metal objects can pose threats to security. In particular, stainless steel is difficult to detect by conventional coil metal detectors due to its low conductivity. We have employed an HTS SQUID magnetometer for the detection of stainless steel particles which is based on the measurement of the remanent magnetization of the particle. Our aim was to determine the detection limits of HTS SQUID-based remote magnetometry, especially for food inspection purposes, and to make a comparison of this technique to commonly used eddy current coil and x-ray inspection systems. We show that the SQUID system's sensitivity to stainless steel fragments is significantly higher than that of coil systems if the samples are magnetized in a 100 mT magnetic field prior to detection. Further, it has a higher sensitivity than x-ray systems, depending on the density distribution of the product under inspection. A 0.6 mg piece of grade-316 stainless steel (a fragment of a hypodermic needle 0.5 mm long and 0.65 mm diameter) represents the detection limit of our system with a 150 × 150 mm2 inspection orifice.

75 FR 5009 - Proximity Detection Systems for Underground Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-01

... electromagnetic field based systems. After reviewing the different types of systems, MSHA determined that the electromagnetic field based system offers the greatest potential for reducing pinning, crushing, and striking... near RCCMs. An electromagnetic field based system consists of a combination of electromagnetic field...

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

PubMed

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

2016-05-28

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

Integrity Verification for SCADA Devices Using Bloom Filters and Deep Packet Inspection

DTIC Science & Technology

2014-03-27

prevent intrusions in smart grids [PK12]. Parthasarathy proposed an anomaly detection based IDS that takes into account system state. In his implementation...Security, 25(7):498–506, 10 2006. [LMV12] O. Linda, M. Manic, and T. Vollmer. Improving cyber-security of smart grid systems via anomaly detection and...6 2012. 114 [PK12] S. Parthasarathy and D. Kundur. Bloom filter based intrusion detection for smart grid SCADA. In Electrical & Computer Engineering

Improved Sensor Fault Detection, Isolation, and Mitigation Using Multiple Observers Approach

PubMed Central

Wang, Zheng; Anand, D. M.; Moyne, J.; Tilbury, D. M.

2017-01-01

Traditional Fault Detection and Isolation (FDI) methods analyze a residual signal to detect and isolate sensor faults. The residual signal is the difference between the sensor measurements and the estimated outputs of the system based on an observer. The traditional residual-based FDI methods, however, have some limitations. First, they require that the observer has reached its steady state. In addition, residual-based methods may not detect some sensor faults, such as faults on critical sensors that result in an unobservable system. Furthermore, the system may be in jeopardy if actions required for mitigating the impact of the faulty sensors are not taken before the faulty sensors are identified. The contribution of this paper is to propose three new methods to address these limitations. Faults that occur during the observers' transient state can be detected by analyzing the convergence rate of the estimation error. Open-loop observers, which do not rely on sensor information, are used to detect faults on critical sensors. By switching among different observers, we can potentially mitigate the impact of the faulty sensor during the FDI process. These three methods are systematically integrated with a previously developed residual-based method to provide an improved FDI and mitigation capability framework. The overall approach is validated mathematically, and the effectiveness of the overall approach is demonstrated through simulation on a 5-state suspension system. PMID:28924303

Motion-Based Immunological Detection of Zika Virus Using Pt-Nanomotors and a Cellphone.

PubMed

Draz, Mohamed Shehata; Lakshminaraasimulu, Nivethitha Kota; Krishnakumar, Sanchana; Battalapalli, Dheerendranath; Vasan, Anish; Kanakasabapathy, Manoj Kumar; Sreeram, Aparna; Kallakuri, Shantanu; Thirumalaraju, Prudhvi; Li, Yudong; Hua, Stephane; Yu, Xu G; Kuritzkes, Daniel R; Shafiee, Hadi

2018-05-16

Zika virus (ZIKV) infection is an emerging pandemic threat to humans that can be fatal in newborns. Advances in digital health systems and nanoparticles can facilitate the development of sensitive and portable detection technologies for timely management of emerging viral infections. Here we report a nanomotor-based bead-motion cellphone (NBC) system for the immunological detection of ZIKV. The presence of virus in a testing sample results in the accumulation of platinum (Pt)-nanomotors on the surface of beads, causing their motion in H 2 O 2 solution. Then the virus concentration is detected in correlation with the change in beads motion. The developed NBC system was capable of detecting ZIKV in samples with virus concentrations as low as 1 particle/μL. The NBC system allowed a highly specific detection of ZIKV in the presence of the closely related dengue virus and other neurotropic viruses, such as herpes simplex virus type 1 and human cytomegalovirus. The NBC platform technology has the potential to be used in the development of point-of-care diagnostics for pathogen detection and disease management in developed and developing countries.

A deep-learning based automatic pulmonary nodule detection system

NASA Astrophysics Data System (ADS)

Zhao, Yiyuan; Zhao, Liang; Yan, Zhennan; Wolf, Matthias; Zhan, Yiqiang

2018-02-01

Lung cancer is the deadliest cancer worldwide. Early detection of lung cancer is a promising way to lower the risk of dying. Accurate pulmonary nodule detection in computed tomography (CT) images is crucial for early diagnosis of lung cancer. The development of computer-aided detection (CAD) system of pulmonary nodules contributes to making the CT analysis more accurate and with more efficiency. Recent studies from other groups have been focusing on lung cancer diagnosis CAD system by detecting medium to large nodules. However, to fully investigate the relevance between nodule features and cancer diagnosis, a CAD that is capable of detecting nodules with all sizes is needed. In this paper, we present a deep-learning based automatic all size pulmonary nodule detection system by cascading two artificial neural networks. We firstly use a U-net like 3D network to generate nodule candidates from CT images. Then, we use another 3D neural network to refine the locations of the nodule candidates generated from the previous subsystem. With the second sub-system, we bring the nodule candidates closer to the center of the ground truth nodule locations. We evaluate our system on a public CT dataset provided by the Lung Nodule Analysis (LUNA) 2016 grand challenge. The performance on the testing dataset shows that our system achieves 90% sensitivity with an average of 4 false positives per scan. This indicates that our system can be an aid for automatic nodule detection, which is beneficial for lung cancer diagnosis.

Building Intrusion Detection with a Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Wälchli, Markus; Braun, Torsten

This paper addresses the detection and reporting of abnormal building access with a wireless sensor network. A common office room, offering space for two working persons, has been monitored with ten sensor nodes and a base station. The task of the system is to report suspicious office occupation such as office searching by thieves. On the other hand, normal office occupation should not throw alarms. In order to save energy for communication, the system provides all nodes with some adaptive short-term memory. Thus, a set of sensor activation patterns can be temporarily learned. The local memory is implemented as an Adaptive Resonance Theory (ART) neural network. Unknown event patterns detected on sensor node level are reported to the base station, where the system-wide anomaly detection is performed. The anomaly detector is lightweight and completely self-learning. The system can be run autonomously or it could be used as a triggering system to turn on an additional high-resolution system on demand. Our building monitoring system has proven to work reliably in different evaluated scenarios. Communication costs of up to 90% could be saved compared to a threshold-based approach without local memory.

Real Time Coincidence Detection Engine for High Count Rate Timestamp Based PET

NASA Astrophysics Data System (ADS)

Tetrault, M.-A.; Oliver, J. F.; Bergeron, M.; Lecomte, R.; Fontaine, R.

2010-02-01

Coincidence engines follow two main implementation flows: timestamp based systems and AND-gate based systems. The latter have been more widespread in recent years because of its lower cost and high efficiency. However, they are highly dependent on the selected electronic components, they have limited flexibility once assembled and they are customized to fit a specific scanner's geometry. Timestamp based systems are gathering more attention lately, especially with high channel count fully digital systems. These new systems must however cope with important singles count rates. One option is to record every detected event and postpone coincidence detection offline. For daily use systems, a real time engine is preferable because it dramatically reduces data volume and hence image preprocessing time and raw data management. This paper presents the timestamp based coincidence engine for the LabPET¿, a small animal PET scanner with up to 4608 individual readout avalanche photodiode channels. The engine can handle up to 100 million single events per second and has extensive flexibility because it resides in programmable logic devices. It can be adapted for any detector geometry or channel count, can be ported to newer, faster programmable devices and can have extra modules added to take advantage of scanner-specific features. Finally, the user can select between full processing mode for imaging protocols and minimum processing mode to study different approaches for coincidence detection with offline software.

Highly sensitive and selective lateral flow immunoassay based on magnetic nanoparticles for quantitative detection of carcinoembryonic antigen.

PubMed

Liu, Fangming; Zhang, Honglian; Wu, Zhenhua; Dong, Haidao; Zhou, Lin; Yang, Dawei; Ge, Yuqing; Jia, Chunping; Liu, Huiying; Jin, Qinghui; Zhao, Jianlong; Zhang, Qiqing; Mao, Hongju

2016-12-01

Carcinoembryonic antigen (CEA) is an important biomarker in cancer diagnosis. Here, we present an efficient, selective lateral-flow immunoassay (LFIA) based on magnetic nanoparticles (MNPs) for in situ sensitive and accurate point-of-care detection of CEA. Signal amplification mechanism involved linking of detection MNPs with signal MNPs through biotin-modified single-stranded DNA (ssDNA) and streptavidin. To verify the effectiveness of this modified LFIA system, the sensitivity and specificity were evaluated. Sensitivity evaluation showed a broad detection range of 0.25-1000ng/ml for CEA protein by the modified LFIA, and the limit of detection (LOD) of the modified LFIA was 0.25ng/ml, thus producing significant increase in detection threshold compared with the traditional LFIA. The modified LFIA could selectively recognize CEA in presence of several interfering proteins. In addition, this newly developed assay was applied for quantitative detection of CEA in human serum specimens collected from 10 randomly selected patients. The modified LFIA system detected minimum 0.27ng/ml of CEA concentration in serum samples. The results were consistent with the clinical data obtained using commercial electrochemiluminescence immunoassay (ECLIA) (p<0.01). In conclusion, the MNPs based LFIA system not only demonstrated enhanced signal to noise ratio, it also detected CEA with higher sensitivity and selectivity, and thus has great potential to be commercially applied as a sensitive tumor marker filtration system. Copyright © 2016 Elsevier B.V. All rights reserved.

Smartphone-based portable biosensing system using impedance measurement with printed electrodes for 2,4,6-trinitrotoluene (TNT) detection.

PubMed

Zhang, Diming; Jiang, Jing; Chen, Junye; Zhang, Qian; Lu, Yanli; Yao, Yao; Li, Shuang; Logan Liu, Gang; Liu, Qingjun

2015-08-15

Rapid, sensitive, selective and portable detection of 2,4,6-trinitrotoluene (TNT) is in high demand for public safety and environmental monitoring. In this study, we reported a smartphone-based system using impedance monitoring for TNT detection. The screen-printed electrodes modified with TNT-specific peptides were used as disposable a biosensor to produce impedance responses to TNT. The responses could be monitored by a hand-held device and send out to smartphone through Bluetooth. Then, the smartphone was used to display TNT responses in real time and report concentration finally. In the measurement, the system was demonstrated to detect TNT at concentration as low as 10(-6) M and distinguish TNT versus different chemicals in high specificity. Thus, the smartphone-based biosensing platform provided a convenient and efficient approach to design portable instruments for chemical detections such as TNT recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Intelligent Power Swing Detection Scheme to Prevent False Relay Tripping Using S-Transform

NASA Astrophysics Data System (ADS)

Mohamad, Nor Z.; Abidin, Ahmad F.; Musirin, Ismail

2014-06-01

Distance relay design is equipped with out-of-step tripping scheme to ensure correct distance relay operation during power swing. The out-of-step condition is a consequence result from unstable power swing. It requires proper detection of power swing to initiate a tripping signal followed by separation of unstable part from the entire power system. The distinguishing process of unstable swing from stable swing poses a challenging task. This paper presents an intelligent approach to detect power swing based on S-Transform signal processing tool. The proposed scheme is based on the use of S-Transform feature of active power at the distance relay measurement point. It is demonstrated that the proposed scheme is able to detect and discriminate the unstable swing from stable swing occurring in the system. To ascertain validity of the proposed scheme, simulations were carried out with the IEEE 39 bus system and its performance has been compared with the wavelet transform-based power swing detection scheme.

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

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

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

a Mini Multi-Gas Detection System Based on Infrared Principle

NASA Astrophysics Data System (ADS)

Zhijian, Xie; Qiulin, Tan

2006-12-01

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

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.

Compact electrochemical sensor system and method for field testing for metals in saliva or other fluids

DOEpatents

Lin, Yuehe; Bennett, Wendy D.; Timchalk, Charles; Thrall, Karla D.

2004-03-02

Microanalytical systems based on a microfluidics/electrochemical detection scheme are described. Individual modules, such as microfabricated piezoelectrically actuated pumps and a microelectrochemical cell were integrated onto portable platforms. This allowed rapid change-out and repair of individual components by incorporating "plug and play" concepts now standard in PC's. Different integration schemes were used for construction of the microanalytical systems based on microfluidics/electrochemical detection. In one scheme, all individual modules were integrated in the surface of the standard microfluidic platform based on a plug-and-play design. Microelectrochemical flow cell which integrated three electrodes based on a wall-jet design was fabricated on polymer substrate. The microelectrochemical flow cell was then plugged directly into the microfluidic platform. Another integration scheme was based on a multilayer lamination method utilizing stacking modules with different functionality to achieve a compact microanalytical device. Application of the microanalytical system for detection of lead in, for example, river water and saliva samples using stripping voltammetry is described.

Fly Ear Inspired Miniature Acoustic Sensors for Detection and Localization

DTIC Science & Technology

2011-07-31

Micro-Opto-Electro-Mechnical-System ( MOEMS ) sensor platform that is capable of integrating multiplexed Fabry-Perot (FP) interferometer based sensors. A...on a single MOEMS chip is shown in Figure 8. Light from a low coherence light source with a coherence length Lc is first sent to the reference...towards developing a low coherence interferometer based MOEMS detection system. An optical Micro-Electro-Mechanical-System (MEMS) sensor platform was

VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

PubMed

Feng, Lichen; Li, Zunchao; Wang, Yuanfa

2018-02-01

Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG.

PubMed

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-03-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver's brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety.

Design on wireless auto-measurement system for lead rail straightness measurement based on PSD

NASA Astrophysics Data System (ADS)

Yan, Xiugang; Zhang, Shuqin; Dong, Dengfeng; Cheng, Zhi; Wu, Guanghua; Wang, Jie; Zhou, Weihu

2016-10-01

Straightness detection is not only one of the key technologies for the product quality and installation accuracy of all types of lead rail, but also an important dimensional measurement technology. The straightness measuring devices now available have disadvantages of low automation level, limiting by measuring environment, and low measurement efficiency. In this paper, a wireless measurement system for straightness detection based on position sensitive detector (PSD) is proposed. The system has some advantage of high automation-level, convenient, high measurement efficiency, easy to transplanting and expanding, and can detect straightness of lead rail in real-time.

Magnetic Enzymatic Platform for Organophosphate Pesticide Detection Using Boron-doped Diamond Electrodes.

PubMed

Pino, Flavio; Ivandini, Tribidasari A; Nakata, Kazuya; Fujishima, Akira; Merkoçi, Arben; Einaga, Yasuaki

2015-01-01

A simple and reliable enzymatic system for organophosporus pesticide detection was successfully developed, by exploiting the synergy between the magnetic beads collection capacity and the outstanding electrochemistry property of boron-doped diamond electrodes. The determination of an organophosphate pesticide, chlorpyrifos (CPF), was performed based on the inhibition system of the enzyme acetylcholinesterase bonded to magnetic beads through a biotin-streptavidin complex system. A better sensitivity was found for a system with magnetic beads in the concentration range of 10(-9) to 10(-5) M. The estimated limits of detection based on IC10 (10% acetylcholinesterase (AChE) inhibition) have been detected and optimized to be 5.7 × 10(-10) M CPF. Spiked samples of water of Yokohama (Japan) have been measured to validate the efficiency of the enzymatic system. The results suggested that the use of magnetic beads to immobilize biomolecules or biosensing agents is suitable to maintain the superiority of BDD electrodes.

Counter sniper: a localization system based on dual thermal imager

NASA Astrophysics Data System (ADS)

He, Yuqing; Liu, Feihu; Wu, Zheng; Jin, Weiqi; Du, Benfang

2010-11-01

Sniper tactics is widely used in modern warfare, which puts forward the urgent requirement of counter sniper detection devices. This paper proposed the anti-sniper detection system based on a dual-thermal imaging system. Combining the infrared characteristics of the muzzle flash and bullet trajectory of binocular infrared images obtained by the dual-infrared imaging system, the exact location of the sniper was analyzed and calculated. This paper mainly focuses on the system design method, which includes the structure and parameter selection. It also analyzes the exact location calculation method based on the binocular stereo vision and image analysis, and give the fusion result as the sniper's position.

Analysis of Android Device-Based Solutions for Fall Detection

PubMed Central

Casilari, Eduardo; Luque, Rafael; Morón, María-José

2015-01-01

Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions. PMID:26213928

Analysis of Android Device-Based Solutions for Fall Detection.

PubMed

Casilari, Eduardo; Luque, Rafael; Morón, María-José

2015-07-23

Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

Shilling attack detection for recommender systems based on credibility of group users and rating time series.

PubMed

Zhou, Wei; Wen, Junhao; Qu, Qiang; Zeng, Jun; Cheng, Tian

2018-01-01

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user's credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method.

Shilling attack detection for recommender systems based on credibility of group users and rating time series

PubMed Central

Wen, Junhao; Qu, Qiang; Zeng, Jun; Cheng, Tian

2018-01-01

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user’s credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method. PMID:29742134

Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations. Chapter 8

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2010-01-01

This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed. The other two types of algorithms being deployed include a "nile-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rule-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions), a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," can be found in. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to an aggregation of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).

On the reliable use of satellite-derived surface water products for global flood monitoring

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

2015-12-01

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

Continuous-flow, microfluidic, qRT-PCR system for RNA virus detection.

PubMed

Fernández-Carballo, B Leticia; McBeth, Christine; McGuiness, Ian; Kalashnikov, Maxim; Baum, Christoph; Borrós, Salvador; Sharon, Andre; Sauer-Budge, Alexis F

2018-01-01

One of the main challenges in the diagnosis of infectious diseases is the need for rapid and accurate detection of the causative pathogen in any setting. Rapid diagnosis is key to avoiding the spread of the disease, to allow proper clinical decisions to be made in terms of patient treatment, and to mitigate the rise of drug-resistant pathogens. In the last decade, significant interest has been devoted to the development of point-of-care reverse transcription polymerase chain reaction (PCR) platforms for the detection of RNA-based viral pathogens. We present the development of a microfluidic, real-time, fluorescence-based, continuous-flow reverse transcription PCR system. The system incorporates a disposable microfluidic chip designed to be produced industrially with cost-effective roll-to-roll embossing methods. The chip has a long microfluidic channel that directs the PCR solution through areas heated to different temperatures. The solution first travels through a reverse transcription zone where RNA is converted to complementary DNA, which is later amplified and detected in real time as it travels through the thermal cycling area. As a proof of concept, the system was tested for Ebola virus detection. Two different master mixes were tested, and the limit of detection of the system was determined, as was the maximum speed at which amplification occurred. Our results and the versatility of our system suggest its promise for the detection of other RNA-based viruses such as Zika virus or chikungunya virus, which constitute global health threats worldwide. Graphical abstract Photograph of the RT-PCR thermoplastic chip.

Artificial-neural-network-based failure detection and isolation

NASA Astrophysics Data System (ADS)

Sadok, Mokhtar; Gharsalli, Imed; Alouani, Ali T.

1998-03-01

This paper presents the design of a systematic failure detection and isolation system that uses the concept of failure sensitive variables (FSV) and artificial neural networks (ANN). The proposed approach was applied to tube leak detection in a utility boiler system. Results of the experimental testing are presented in the paper.

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

PubMed

N Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

Cost analysis of the Mercedes-Benz occupant detection system for air bag shut-off

DOT National Transportation Integrated Search

1997-04-01

The objective of this project is to develop the variable manufacturing costs and lead time estimates of an "occupant detection system for air bag shut off". The Mercedes-Benz system was used as a base for developing this data. The system consists of ...

Indoor air quality inspection and analysis system based on gas sensor array

NASA Astrophysics Data System (ADS)

Gao, Xiang; Wang, Mingjiang; Fan, Binwen

2017-08-01

A detection and analysis system capable of measuring the concentration of four major gases in indoor air is designed. It uses four gas sensors constitute a gas sensor array, to achieve four indoor gas concentration detection, while the detection of data for further processing to reduce the cross-sensitivity between the gas sensor to improve the accuracy of detection.

Application of local binary pattern and human visual Fibonacci texture features for classification different medical images

NASA Astrophysics Data System (ADS)

Sanghavi, Foram; Agaian, Sos

2017-05-01

The goal of this paper is to (a) test the nuclei based Computer Aided Cancer Detection system using Human Visual based system on the histopathology images and (b) Compare the results of the proposed system with the Local Binary Pattern and modified Fibonacci -p pattern systems. The system performance is evaluated using different parameters such as accuracy, specificity, sensitivity, positive predictive value, and negative predictive value on 251 prostate histopathology images. The accuracy of 96.69% was observed for cancer detection using the proposed human visual based system compared to 87.42% and 94.70% observed for Local Binary patterns and the modified Fibonacci p patterns.

Automatic background updating for video-based vehicle detection

NASA Astrophysics Data System (ADS)

Hu, Chunhai; Li, Dongmei; Liu, Jichuan

2008-03-01

Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.

A prototype implementation of a network-level intrusion detection system. Technical report number CS91-11

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

Heady, R.; Luger, G.F.; Maccabe, A.B.

1991-05-15

This paper presents the implementation of a prototype network level intrusion detection system. The prototype system monitors base level information in network packets (source, destination, packet size, time, and network protocol), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

A Sensor System for Detection of Hull Surface Defects

PubMed Central

Navarro, Pedro; Iborra, Andrés; Fernández, Carlos; Sánchez, Pedro; Suardíaz, Juan

2010-01-01

This paper presents a sensor system for detecting defects in ship hull surfaces. The sensor was developed to enable a robotic system to perform grit blasting operations on ship hulls. To achieve this, the proposed sensor system captures images with the help of a camera and processes them in real time using a new defect detection method based on thresholding techniques. What makes this method different is its efficiency in the automatic detection of defects from images recorded in variable lighting conditions. The sensor system was tested under real conditions at a Spanish shipyard, with excellent results. PMID:22163590

Automated Inattention and Fatigue Detection System in Distance Education for Elementary School Students

ERIC Educational Resources Information Center

Hwang, Kuo-An; Yang, Chia-Hao

2009-01-01

Most courses based on distance learning focus on the cognitive domain of learning. Because students are sometimes inattentive or tired, they may neglect the attention goal of learning. This study proposes an auto-detection and reinforcement mechanism for the distance-education system based on the reinforcement teaching strategy. If a student is…

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.

A Low-Cost Liquid-Chromatography System Using a Spectronic 20-Based Detector.

ERIC Educational Resources Information Center

Jezorek, John R.; And Others

1986-01-01

Describes the design and evaluation of a Spectronic 20-based detector as well as a simple system for postcolumn derivatization useful for metal-ion chromatographic detection. Both detection and derivatization can be performed in the ultra-violet (UV) mode using a low-cost UV-visible spectrophotometer and UV-region derivatization reagents. (JN)

Systems and methods of detecting force and stress using tetrapod nanocrystal

DOEpatents

Choi, Charina L.; Koski, Kristie J.; Sivasankar, Sanjeevi; Alivisatos, A. Paul

2013-08-20

Systems and methods of detecting force on the nanoscale including methods for detecting force using a tetrapod nanocrystal by exposing the tetrapod nanocrystal to light, which produces a luminescent response by the tetrapod nanocrystal. The method continues with detecting a difference in the luminescent response by the tetrapod nanocrystal relative to a base luminescent response that indicates a force between a first and second medium or stresses or strains experienced within a material. Such systems and methods find use with biological systems to measure forces in biological events or interactions.

Eddy Current System for Detection of Cracking Beneath Braiding in Corrugated Metal Hose

NASA Astrophysics Data System (ADS)

Wincheski, Buzz; Simpson, John; Hall, George

2009-03-01

In this paper an eddy current system for the detection of partially-through-the-thickness cracks in corrugated metal hose is presented. Design criteria based upon the geometry and conductivity of the part are developed and applied to the fabrication of a prototype inspection system. Experimental data are used to highlight the capabilities of the system and an image processing technique is presented to improve flaw detection capabilities. A case study for detection of cracking damage in a space shuttle radiator retract flex hoses is also presented.

Eddy Current System for Detection of Cracking Beneath Braiding in Corrugated Metal Hose

NASA Technical Reports Server (NTRS)

Wincheski, Buzz; Simpson, John; Hall, George

2008-01-01

In this paper an eddy current system for the detection of partially-through-the-thickness cracks in corrugated metal hose is presented. Design criteria based upon the geometry and conductivity of the part are developed and applied to the fabrication of a prototype inspection system. Experimental data are used to highlight the capabilities of the system and an image processing technique is presented to improve flaw detection capabilities. A case study for detection of cracking damage in a space shuttle radiator retract flex hoses is also presented.

Recent advances and developments on integrating nanotechnology with chemiluminescence assays.

PubMed

Tiwari, Ashish; Dhoble, S J

2018-04-01

Chemiluminescence (CL) techniques are extensively utilized for detection of analytes due to their high sensitivity, rapidity and selectivity. With the advent of nanotechnology and incorporation of the nanoparticles in the CL system has revolutionized the assays due to their unique optical and mechanical properties. Several CL-based reactions have been developed where these nanoparticle based CL sensors have evolved as excellent prospects for sensing in various analytical applications. This review article addresses the nanoparticles based CL detection system that are recently developed, the mechanisms has been summarized and the role of luminophors have been discussed. This article critically analyzes the optimal conditions for the CL detection along with quantitative assessment of the analytes. We have included the use of semiconductor nanoparticles, metal nanoparticles, graphene based nanostructures, mesoporous nanospheres, layered double hydroxides, clays for CL detection. The scope and application of these nanoscale material based CL system in various branches of science and technology including chemistry, biomedical applications, pharmaceutics, food, environmental and toxicological applications has been critically summarized. Copyright © 2017 Elsevier B.V. All rights reserved.

A Novel Pretreatment-Free Duplex Chamber Digital PCR Detection System for the Absolute Quantitation of GMO Samples.

PubMed

Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Luo, Yunbo; Xu, Wentao

2016-03-18

Digital polymerase chain reaction (PCR) has developed rapidly since it was first reported in the 1990s. However, pretreatments are often required during preparation for digital PCR, which can increase operation error. The single-plex amplification of both the target and reference genes may cause uncertainties due to the different reaction volumes and the matrix effect. In the current study, a quantitative detection system based on the pretreatment-free duplex chamber digital PCR was developed. The dynamic range, limit of quantitation (LOQ), sensitivity and specificity were evaluated taking the GA21 event as the experimental object. Moreover, to determine the factors that may influence the stability of the duplex system, we evaluated whether the pretreatments, the primary and secondary structures of the probes and the SNP effect influence the detection. The results showed that the LOQ was 0.5% and the sensitivity was 0.1%. We also found that genome digestion and single nucleotide polymorphism (SNP) sites affect the detection results, whereas the unspecific hybridization within different probes had little side effect. This indicated that the detection system was suited for both chamber-based and droplet-based digital PCR. In conclusion, we have provided a simple and flexible way of achieving absolute quantitation for genetically modified organism (GMO) genome samples using commercial digital PCR detection systems.

A Novel Pretreatment-Free Duplex Chamber Digital PCR Detection System for the Absolute Quantitation of GMO Samples

PubMed Central

Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Luo, Yunbo; Xu, Wentao

2016-01-01

Digital polymerase chain reaction (PCR) has developed rapidly since it was first reported in the 1990s. However, pretreatments are often required during preparation for digital PCR, which can increase operation error. The single-plex amplification of both the target and reference genes may cause uncertainties due to the different reaction volumes and the matrix effect. In the current study, a quantitative detection system based on the pretreatment-free duplex chamber digital PCR was developed. The dynamic range, limit of quantitation (LOQ), sensitivity and specificity were evaluated taking the GA21 event as the experimental object. Moreover, to determine the factors that may influence the stability of the duplex system, we evaluated whether the pretreatments, the primary and secondary structures of the probes and the SNP effect influence the detection. The results showed that the LOQ was 0.5% and the sensitivity was 0.1%. We also found that genome digestion and single nucleotide polymorphism (SNP) sites affect the detection results, whereas the unspecific hybridization within different probes had little side effect. This indicated that the detection system was suited for both chamber-based and droplet-based digital PCR. In conclusion, we have provided a simple and flexible way of achieving absolute quantitation for genetically modified organism (GMO) genome samples using commercial digital PCR detection systems. PMID:26999129

Factors influencing performance of internet-based biosurveillance systems used in epidemic intelligence for early detection of infectious diseases outbreaks.

PubMed

Barboza, Philippe; Vaillant, Laetitia; Le Strat, Yann; Hartley, David M; Nelson, Noele P; Mawudeku, Abla; Madoff, Lawrence C; Linge, Jens P; Collier, Nigel; Brownstein, John S; Astagneau, Pascal

2014-01-01

Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems' performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p=0001) whereas other indicators were similar (C-DR: p=020; C-Se, p=013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Although differences could result from a biosurveillance system's conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p=00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance.

A Systematic Review of Wearable Systems for Cancer Detection: Current State and Challenges.

PubMed

Ray, Partha Pratim; Dash, Dinesh; De, Debashis

2017-10-02

Rapid growth of sensor and computing platforms have introduced the wearable systems. In recent years, wearable systems have led to new applications across all medical fields. The aim of this review is to present current state-of-the-art approach in the field of wearable system based cancer detection and identify key challenges that resist it from clinical adoption. A total of 472 records were screened and 11 were finally included in this study. Two types of records were studied in this context that includes 45% research articles and 55% manufactured products. The review was performed per PRISMA guidelines where considerations was given to records that were published or reported between 2009 and 2017. The identified records included 4 cancer detecting wearable systems such as breast cancer (36.3%), skin cancer (36.3%), prostate cancer (18.1%), and multi-type cancer (9%). Most works involved sensor based smart systems comprising of microcontroller, Bluetooth module, and smart phone. Few demonstrated Ultra-Wide Band (i.e. UWB) antenna based wearable systems. Skin cancer detecting wearable systems were most comprehensible ones. The current works are gradually progressing with seamless integration of sensory units along with smart networking. However, they lack in cloud computing and long-range communication paradigms. Artificial intelligence and machine learning are key ports that need to be attached with current wearable systems. Further, clinical inertia, lack of awareness, and high cost are altogether pulling back the actual growth of such system. It is well comprehended that upon sincere orientation of all identified challenges, wearable systems would emerge as vital alternative to futuristic cancer detection.

Radioactive threat detection using scintillant-based detectors

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2004-09-01

An update to the performance of AS&E's Radioactive Threat Detection sensor technology. A model is presented detailing the components of the scintillant-based RTD system employed in AS&E products aimed at detecting radiological WMD. An overview of recent improvements in the sensors, electrical subsystems and software algorithms are presented. The resulting improvements in performance are described and sample results shown from existing systems. Advanced and future capabilities are described with an assessment of their feasibility and their application to Homeland Defense.

Photonuclear-based, nuclear material detection system for cargo containers

NASA Astrophysics Data System (ADS)

Jones, J. L.; Yoon, W. Y.; Norman, D. R.; Haskell, K. J.; Zabriskie, J. M.; Watson, S. M.; Sterbentz, J. W.

2005-12-01

The Idaho National Laboratory (INL) has been developing electron accelerator-based, photonuclear inspection technologies for over a decade. A current need, having important national implications, has been with the detection of smuggled nuclear material within air- and, especially, sea-cargo transportation containers. This paper describes the latest pulsed, photonuclear inspection system for nuclear material detection and identification in cargo configurations, the numerical responses of 5 kg of a nuclear material placed within selected cargo configurations, and the technology's potential role in addressing future inspection needs.

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

NASA Astrophysics Data System (ADS)

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

2008-07-01

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

An Adaptive Failure Detector Based on Quality of Service in Peer-to-Peer Networks

PubMed Central

Dong, Jian; Ren, Xiao; Zuo, Decheng; Liu, Hongwei

2014-01-01

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen's classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen's model. Moreover, B-AFD has better adaptability to P2P network. PMID:25198005

ROS-based ground stereo vision detection: implementation and experiments.

PubMed

Hu, Tianjiang; Zhao, Boxin; Tang, Dengqing; Zhang, Daibing; Kong, Weiwei; Shen, Lincheng

This article concentrates on open-source implementation on flying object detection in cluttered scenes. It is of significance for ground stereo-aided autonomous landing of unmanned aerial vehicles. The ground stereo vision guidance system is presented with details on system architecture and workflow. The Chan-Vese detection algorithm is further considered and implemented in the robot operating systems (ROS) environment. A data-driven interactive scheme is developed to collect datasets for parameter tuning and performance evaluating. The flying vehicle outdoor experiments capture the stereo sequential images dataset and record the simultaneous data from pan-and-tilt unit, onboard sensors and differential GPS. Experimental results by using the collected dataset validate the effectiveness of the published ROS-based detection algorithm.

Piezoresistive microcantilever based lab-on-a-chip system for detection of macronutrients in the soil

NASA Astrophysics Data System (ADS)

Patkar, Rajul S.; Ashwin, Mamta; Rao, V. Ramgopal

2017-12-01

Monitoring of soil nutrients is very important in precision agriculture. In this paper, we have demonstrated a micro electro mechanical system based lab-on-a-chip system for detection of various soil macronutrients which are available in ionic form K+, NO3-, and H2PO4-. These sensors are highly sensitive piezoresistive silicon microcantilevers coated with a polymer matrix containing methyltridodecylammonium nitrate ionophore/ nitrate ionophore VI for nitrate sensing, 18-crown-6 ether for potassium sensing and Tributyltin chloride for phosphate detection. A complete lab-on-a-chip system integrating a highly sensitive current excited Wheatstone's bridge based portable electronic setup along with arrays of microcantilever devices mounted on a printed circuit board with a liquid flow cell for on the site experimentation for soil test has been demonstrated.

36 CFR Appendix B to Part 1234 - Alternative Certified Fire-Safety Detection and Suppression System(s)

Code of Federal Regulations, 2012 CFR

2012-07-01

... the system at the base of the main sprinkler riser. l. Fire hydrants must be located within 250 feet... Suppression System(s) 1. General. This Appendix B contains information on the Fire-safety Detection and Suppression System(s) tested by NARA through independent live fire testing that are certified to meet the...

36 CFR Appendix B to Part 1234 - Alternative Certified Fire-Safety Detection and Suppression System(s)

Code of Federal Regulations, 2014 CFR

2014-07-01

... the system at the base of the main sprinkler riser. l. Fire hydrants must be located within 250 feet... Suppression System(s) 1. General. This Appendix B contains information on the Fire-safety Detection and Suppression System(s) tested by NARA through independent live fire testing that are certified to meet the...

36 CFR Appendix B to Part 1234 - Alternative Certified Fire-Safety Detection and Suppression System(s)

Code of Federal Regulations, 2013 CFR

2013-07-01

... the system at the base of the main sprinkler riser. l. Fire hydrants must be located within 250 feet... Suppression System(s) 1. General. This Appendix B contains information on the Fire-safety Detection and Suppression System(s) tested by NARA through independent live fire testing that are certified to meet the...

A Bevel Gear Quality Inspection System Based on Multi-Camera Vision Technology.

PubMed

Liu, Ruiling; Zhong, Dexing; Lyu, Hongqiang; Han, Jiuqiang

2016-08-25

Surface defect detection and dimension measurement of automotive bevel gears by manual inspection are costly, inefficient, low speed and low accuracy. In order to solve these problems, a synthetic bevel gear quality inspection system based on multi-camera vision technology is developed. The system can detect surface defects and measure gear dimensions simultaneously. Three efficient algorithms named Neighborhood Average Difference (NAD), Circle Approximation Method (CAM) and Fast Rotation-Position (FRP) are proposed. The system can detect knock damage, cracks, scratches, dents, gibbosity or repeated cutting of the spline, etc. The smallest detectable defect is 0.4 mm × 0.4 mm and the precision of dimension measurement is about 40-50 μm. One inspection process takes no more than 1.3 s. Both precision and speed meet the requirements of real-time online inspection in bevel gear production.

Design optimization of Cassegrain telescope for remote explosive trace detection

NASA Astrophysics Data System (ADS)

Bhavsar, Kaushalkumar; Eseller, K. E.; Prabhu, Radhakrishna

2017-10-01

The past three years have seen a global increase in explosive-based terror attacks. The widespread use of improvised explosives and anti-personnel landmines have caused thousands of civilian casualties across the world. Current scenario of globalized civilization threat from terror drives the need to improve the performance and capabilities of standoff explosive trace detection devices to be able to anticipate the threat from a safe distance to prevent explosions and save human lives. In recent years, laser-induced breakdown spectroscopy (LIBS) is an emerging approach for material or elemental investigations. All the principle elements on the surface are detectable in a single measurement using LIBS and hence, a standoff LIBS based method has been used to remotely detect explosive traces from several to tens of metres distance. The most important component of LIBS based standoff explosive trace detection system is the telescope which enables remote identification of chemical constituents of the explosives. However, in a compact LIBS system where Cassegrain telescope serves the purpose of laser beam delivery and light collection, need a design optimization of the telescope system. This paper reports design optimization of a Cassegrain telescope to detect explosives remotely for LIBS system. A design optimization of Schmidt corrector plate was carried out for Nd:YAG laser. Effect of different design parameters was investigated to eliminate spherical aberration in the system. Effect of different laser wavelengths on the Schmidt corrector design was also investigated for the standoff LIBS system.

Analysis and design of algorithm-based fault-tolerant systems

NASA Technical Reports Server (NTRS)

Nair, V. S. Sukumaran

1990-01-01

An important consideration in the design of high performance multiprocessor systems is to ensure the correctness of the results computed in the presence of transient and intermittent failures. Concurrent error detection and correction have been applied to such systems in order to achieve reliability. Algorithm Based Fault Tolerance (ABFT) was suggested as a cost-effective concurrent error detection scheme. The research was motivated by the complexity involved in the analysis and design of ABFT systems. To that end, a matrix-based model was developed and, based on that, algorithms for both the design and analysis of ABFT systems are formulated. These algorithms are less complex than the existing ones. In order to reduce the complexity further, a hierarchical approach is developed for the analysis of large systems.

Convolutional Neural Network-Based Shadow Detection in Images Using Visible Light Camera Sensor.

PubMed

Kim, Dong Seop; Arsalan, Muhammad; Park, Kang Ryoung

2018-03-23

Recent developments in intelligence surveillance camera systems have enabled more research on the detection, tracking, and recognition of humans. Such systems typically use visible light cameras and images, in which shadows make it difficult to detect and recognize the exact human area. Near-infrared (NIR) light cameras and thermal cameras are used to mitigate this problem. However, such instruments require a separate NIR illuminator, or are prohibitively expensive. Existing research on shadow detection in images captured by visible light cameras have utilized object and shadow color features for detection. Unfortunately, various environmental factors such as illumination change and brightness of background cause detection to be a difficult task. To overcome this problem, we propose a convolutional neural network-based shadow detection method. Experimental results with a database built from various outdoor surveillance camera environments, and from the context-aware vision using image-based active recognition (CAVIAR) open database, show that our method outperforms previous works.

Convolutional Neural Network-Based Shadow Detection in Images Using Visible Light Camera Sensor

PubMed Central

Kim, Dong Seop; Arsalan, Muhammad; Park, Kang Ryoung

2018-01-01

Recent developments in intelligence surveillance camera systems have enabled more research on the detection, tracking, and recognition of humans. Such systems typically use visible light cameras and images, in which shadows make it difficult to detect and recognize the exact human area. Near-infrared (NIR) light cameras and thermal cameras are used to mitigate this problem. However, such instruments require a separate NIR illuminator, or are prohibitively expensive. Existing research on shadow detection in images captured by visible light cameras have utilized object and shadow color features for detection. Unfortunately, various environmental factors such as illumination change and brightness of background cause detection to be a difficult task. To overcome this problem, we propose a convolutional neural network-based shadow detection method. Experimental results with a database built from various outdoor surveillance camera environments, and from the context-aware vision using image-based active recognition (CAVIAR) open database, show that our method outperforms previous works. PMID:29570690

A dynamic bead-based microarray for parallel DNA detection

NASA Astrophysics Data System (ADS)

Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

2011-05-01

A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

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. ,

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

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%.

Interference and differentiation of the neighboring surface microcracks in distributed sensing with PPP-BOTDA.

PubMed

Meng, Dewei; Ansari, Farhad

2016-12-01

Detection of cracks while at their early stages of evolution is important in health monitoring of civil structures. Review of technical literature reveals that single or sparsely distributed multiple cracks can be detected by Brillouin-scattering-based optical fiber sensor systems. In a recent study, a pre-pump-pulse Brillouin optical time-domain analysis (PPP-BOTDA) system was employed for detection of a single microcrack. Specific characteristics of the Brillouin gain spectrum, such as Brillouin frequency shift, and Brillouin gain spectrum width, were utilized in order to detect the formation and growth of microcracks with crack opening displacements as small as 25 μm. In most situations, formations of neighboring microcracks are not detected due to inherent limitations of Brillouin-based systems. In the study reported here, the capability of PPP-BOTDA for detection of two neighboring microcracks was investigated in terms of the proximity of the microcracks with respect to each other, i.e., crack spacing distance, crack opening displacement, and the spatial resolution of the PPP-BOTDA. The extent of the study pertained both to theoretical as well as experimental investigations. The concept of shape index is introduced in order to establish an analytical method for gauging the influence of the neighboring microcracks in detection and microcrack differentiation capabilities of Brillouin-based optical fiber sensor systems.

An explosives detection system for airline security using coherent x-ray scattering technology

NASA Astrophysics Data System (ADS)

Madden, Robert W.; Mahdavieh, Jacob; Smith, Richard C.; Subramanian, Ravi

2008-08-01

L-3 Communications Security and Detection Systems (SDS) has developed a new system for automated alarm resolution in airline baggage Explosive Detection Systems (EDS) based on coherent x-ray scattering spectroscopy. The capabilities of the system were demonstrated in tests with concealed explosives at the Transportation Security Laboratory and airline passenger baggage at Orlando International Airport. The system uses x-ray image information to identify suspicious objects and performs targeted diffraction measurements to classify them. This extra layer of detection capability affords a significant reduction in the rate of false alarm objects that must presently be resolved by opening passenger bags for hand inspection.

Rail inspection system based on iGPS

NASA Astrophysics Data System (ADS)

Fu, Xiaoyan; Wang, Mulan; Wen, Xiuping

2018-05-01

Track parameters include gauge, super elevation, cross level and so on, which could be calculated through the three-dimensional coordinates of the track. The rail inspection system based on iGPS (indoor/infrared GPS) was composed of base station, receiver, rail inspection frame, wireless communication unit, display and control unit and data processing unit. With the continuous movement of the inspection frame, the system could accurately inspect the coordinates of rail; realize the intelligent detection and precision measurement. According to principle of angle intersection measurement, the inspection model was structured, and detection process was given.

Detection of multiple chemicals based on external cavity quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Sun, Juan; Ding, Junya; Liu, Ningwu; Yang, Guangxiang; Li, Jingsong

2018-02-01

A laser spectroscopy system based on a broadband tunable external cavity quantum cascade laser (ECQCL) and a mini quartz crystal tuning fork (QCTF) detector was developed for standoff detection of volatile organic compounds (VOCs). The self-established spectral analysis model based on multiple algorithms for quantitative and qualitative analysis of VOC components (i.e. ethanol and acetone) was detailedly investigated in both closed cell and open path configurations. A good agreement was obtained between the experimentally observed spectra and the standard reference spectra. For open path detection of VOCs, the sensor system was demonstrated at a distance of 30 m. The preliminary laboratory results show that standoff detection of VOCs at a distance of over 100 m is very promising.

Optofluidic platforms based on surface-enhanced Raman scattering.

PubMed

Lim, Chaesung; Hong, Jongin; Chung, Bong Geun; deMello, Andrew J; Choo, Jaebum

2010-05-01

We report recent progress in the development of surface-enhanced Raman scattering (SERS)-based optofluidic platforms for the fast and sensitive detection of chemical and biological analytes. In the current context, a SERS-based optofluidic platform is defined as an integrated analytical device composed of a microfluidic element and a sensitive Raman spectrometer. Optofluidic devices for SERS detection normally involve nanocolloid-based microfluidic systems or metal nanostructure-embedded microfluidic systems. In the current review, recent advances in both approaches are surveyed and assessed. Additionally, integrated real-time sensing systems that combine portable Raman spectrometers with microfluidic devices are also reviewed. Such real-time sensing systems have significant utility in environmental monitoring, forensic science and homeland defense applications.

Using Unix system auditing for detecting network intrusions

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

Christensen, M.J.

1993-03-01

Intrusion Detection Systems (IDSs) are designed to detect actions of individuals who use computer resources without authorization as well as legitimate users who exceed their privileges. This paper describes a novel approach to IDS research, namely a decision aiding approach to intrusion detection. The introduction of a decision tree represents the logical steps necessary to distinguish and identify different types of attacks. This tool, the Intrusion Decision Aiding Tool (IDAT), utilizes IDS-based attack models and standard Unix audit data. Since attacks have certain characteristics and are based on already developed signature attack models, experienced and knowledgeable Unix system administrators knowmore » what to look for in system audit logs to determine if a system has been attacked. Others, however, are usually less able to recognize common signatures of unauthorized access. Users can traverse the tree using available audit data displayed by IDAT and general knowledge they possess to reach a conclusion regarding suspicious activity. IDAT is an easy-to-use window based application that gathers, analyzes, and displays pertinent system data according to Unix attack characteristics. IDAT offers a more practical approach and allows the user to make an informed decision regarding suspicious activity.« less

Technologies for autonomous integrated lab-on-chip systems for space missions

NASA Astrophysics Data System (ADS)

Nascetti, A.; Caputo, D.; Scipinotti, R.; de Cesare, G.

2016-11-01

Lab-on-chip devices are ideal candidates for use in space missions where experiment automation, system compactness, limited weight and low sample and reagent consumption are required. Currently, however, most microfluidic systems require external desktop instrumentation to operate and interrogate the chip, thus strongly limiting their use as stand-alone systems. In order to overcome the above-mentioned limitations our research group is currently working on the design and fabrication of "true" lab-on-chip systems that integrate in a single device all the analytical steps from the sample preparation to the detection without the need for bulky external components such as pumps, syringes, radiation sources or optical detection systems. Three critical points can be identified to achieve 'true' lab-on-chip devices: sample handling, analytical detection and signal transduction. For each critical point, feasible solutions are presented and evaluated. Proposed microfluidic actuation and control is based on electrowetting on dielectrics, autonomous capillary networks and active valves. Analytical detection based on highly specific chemiluminescent reactions is used to avoid external radiation sources. Finally, the integration on the same chip of thin film sensors based on hydrogenated amorphous silicon is discussed showing practical results achieved in different sensing tasks.

A Fuzzy Aproach For Facial Emotion Recognition

NASA Astrophysics Data System (ADS)

Gîlcă, Gheorghe; Bîzdoacă, Nicu-George

2015-09-01

This article deals with an emotion recognition system based on the fuzzy sets. Human faces are detected in images with the Viola - Jones algorithm and for its tracking in video sequences we used the Camshift algorithm. The detected human faces are transferred to the decisional fuzzy system, which is based on the variable fuzzyfication measurements of the face: eyebrow, eyelid and mouth. The system can easily determine the emotional state of a person.

Proof of Concept in Disrupted Tactical Networking

DTIC Science & Technology

2017-09-01

because of the risk of detection. In this study , we design projectile-based mesh networking prototypes as one potential type of short-living network...to communicate because of the risk of detection. In this study , we design projectile-based mesh networking prototypes as one potential type of short...reader with a background in systems-theory. This study is designed using systems theory and uses systems theory as a lens through which to observe

Theory and experiments in model-based space system anomaly management

NASA Astrophysics Data System (ADS)

Kitts, Christopher Adam

This research program consists of an experimental study of model-based reasoning methods for detecting, diagnosing and resolving anomalies that occur when operating a comprehensive space system. Using a first principles approach, several extensions were made to the existing field of model-based fault detection and diagnosis in order to develop a general theory of model-based anomaly management. Based on this theory, a suite of algorithms were developed and computationally implemented in order to detect, diagnose and identify resolutions for anomalous conditions occurring within an engineering system. The theory and software suite were experimentally verified and validated in the context of a simple but comprehensive, student-developed, end-to-end space system, which was developed specifically to support such demonstrations. This space system consisted of the Sapphire microsatellite which was launched in 2001, several geographically distributed and Internet-enabled communication ground stations, and a centralized mission control complex located in the Space Technology Center in the NASA Ames Research Park. Results of both ground-based and on-board experiments demonstrate the speed, accuracy, and value of the algorithms compared to human operators, and they highlight future improvements required to mature this technology.

Immunity-Based Aircraft Fault Detection System

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks

PubMed Central

Barboza, Philippe; Vaillant, Laetitia; Le Strat, Yann; Hartley, David M.; Nelson, Noele P.; Mawudeku, Abla; Madoff, Lawrence C.; Linge, Jens P.; Collier, Nigel; Brownstein, John S.; Astagneau, Pascal

2014-01-01

Background Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se, p = 013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Conclusion Although differences could result from a biosurveillance system's conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p = 00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance. PMID:24599062

Detecting nuclear materials smuggling: performance evaluation of container inspection policies.

PubMed

Gaukler, Gary M; Li, Chenhua; Ding, Yu; Chirayath, Sunil S

2012-03-01

In recent years, the United States, along with many other countries, has significantly increased its detection and defense mechanisms against terrorist attacks. A potential attack with a nuclear weapon, using nuclear materials smuggled into the country, has been identified as a particularly grave threat. The system for detecting illicit nuclear materials that is currently in place at U.S. ports of entry relies heavily on passive radiation detectors and a risk-scoring approach using the automated targeting system (ATS). In this article we analyze this existing inspection system and demonstrate its performance for several smuggling scenarios. We provide evidence that the current inspection system is inherently incapable of reliably detecting sophisticated smuggling attempts that use small quantities of well-shielded nuclear material. To counter the weaknesses of the current ATS-based inspection system, we propose two new inspection systems: the hardness control system (HCS) and the hybrid inspection system (HYB). The HCS uses radiography information to classify incoming containers based on their cargo content into "hard" or "soft" containers, which then go through different inspection treatment. The HYB combines the radiography information with the intelligence information from the ATS. We compare and contrast the relative performance of these two new inspection systems with the existing ATS-based system. Our studies indicate that the HCS and HYB policies outperform the ATS-based policy for a wide range of realistic smuggling scenarios. We also examine the impact of changes in adversary behavior on the new inspection systems and find that they effectively preclude strategic gaming behavior of the adversary. © 2011 Society for Risk Analysis.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

The parameterization of microchannel-plate-based detection systems

NASA Astrophysics Data System (ADS)

Gershman, Daniel J.; Gliese, Ulrik; Dorelli, John C.; Avanov, Levon A.; Barrie, Alexander C.; Chornay, Dennis J.; MacDonald, Elizabeth A.; Holland, Matthew P.; Giles, Barbara L.; Pollock, Craig J.

2016-10-01

The most common instrument for low-energy plasmas consists of a top-hat electrostatic analyzer (ESA) geometry coupled with a microchannel-plate-based (MCP-based) detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Here we develop a comprehensive mathematical description of particle detection systems. As a function of instrument azimuthal angle, we parameterize (1) particle scattering within the ESA and at the surface of the MCP, (2) the probability distribution of MCP gain for an incident particle, (3) electron charge cloud spreading between the MCP and anode board, and (4) capacitive coupling between adjacent discrete anodes. Using the Dual Electron Spectrometers on the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission as an example, we demonstrate a method for extracting these fundamental detection system parameters from laboratory calibration. We further show that parameters that will evolve in flight, namely, MCP gain, can be determined through application of this model to specifically tailored in-flight calibration activities. This methodology provides a robust characterization of sensor suite performance throughout mission lifetime. The model developed in this work is not only applicable to existing sensors but also can be used as an analytical design tool for future particle instrumentation.

End-to-end system of license plate localization and recognition

NASA Astrophysics Data System (ADS)

Zhu, Siyu; Dianat, Sohail; Mestha, Lalit K.

2015-03-01

An end-to-end license plate recognition system is proposed. It is composed of preprocessing, detection, segmentation, and character recognition to find and recognize plates from camera-based still images. The system utilizes connected component (CC) properties to quickly extract the license plate region. A two-stage CC filtering is utilized to address both shape and spatial relationship information to produce high precision and to recall values for detection. Floating peak and valleys of projection profiles are used to cut the license plates into individual characters. A turning function-based method is proposed to quickly and accurately recognize each character. It is further accelerated using curvature histogram-based support vector machine. The INFTY dataset is used to train the recognition system, and MediaLab license plate dataset is used for testing. The proposed system achieved 89.45% F-measure for detection and 87.33% accuracy for overall recognition rate which is comparable to current state-of-the-art systems.

Completing fishing monitoring with spaceborne Vessel Detection System (VDS) and Automatic Identification System (AIS) to assess illegal fishing in Indonesia.

PubMed

Longépé, Nicolas; Hajduch, Guillaume; Ardianto, Romy; Joux, Romain de; Nhunfat, Béatrice; Marzuki, Marza I; Fablet, Ronan; Hermawan, Indra; Germain, Olivier; Subki, Berny A; Farhan, Riza; Muttaqin, Ahmad Deni; Gaspar, Philippe

2017-10-26

The Indonesian fisheries management system is now equipped with the state-of-the-art technologies to deter and combat Illegal, Unreported and Unregulated (IUU) fishing. Since October 2014, non-cooperative fishing vessels can be detected from spaceborne Vessel Detection System (VDS) based on high resolution radar imagery, which directly benefits to coordinated patrol vessels in operation context. This study attempts to monitor the amount of illegal fishing in the Arafura Sea based on this new source of information. It is analyzed together with Vessel Monitoring System (VMS) and satellite-based Automatic Identification System (Sat-AIS) data, taking into account their own particularities. From October 2014 to March 2015, i.e. just after the establishment of a new moratorium by the Indonesian authorities, the estimated share of fishing vessels not carrying VMS, thus being illegal, ranges from 42 to 47%. One year later in January 2016, this proportion decreases and ranges from 32 to 42%. Copyright © 2017 Elsevier Ltd. All rights reserved.

Damage identification via asymmetric active magnetic bearing acceleration feedback control

NASA Astrophysics Data System (ADS)

Zhao, Jie; DeSmidt, Hans; Yao, Wei

2015-04-01

A Floquet-based damage detection methodology for cracked rotor systems is developed and demonstrated on a shaft-disk system. This approach utilizes measured changes in the system natural frequencies to estimate the severity and location of shaft structural cracks during operation. The damage detection algorithms are developed with the initial guess solved by least square method and iterative damage parameter vector by updating the eigenvector updating. Active Magnetic Bearing is introduced to break the symmetric structure of rotor system and the tuning range of proper stiffness/virtual mass gains is studied. The system model is built based on energy method and the equations of motion are derived by applying assumed modes method and Lagrange Principle. In addition, the crack model is based on the Strain Energy Release Rate (SERR) concept in fracture mechanics. Finally, the method is synthesized via harmonic balance and numerical examples for a shaft/disk system demonstrate the effectiveness in detecting both location and severity of the structural damage.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera.

PubMed

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-10-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN-based methods and other previous handcrafted methods.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera

PubMed Central

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-01-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN-based methods and other previous handcrafted methods. PMID:28974031

Fault detection and isolation

NASA Technical Reports Server (NTRS)

Bernath, Greg

1994-01-01

In order for a current satellite-based navigation system (such as the Global Positioning System, GPS) to meet integrity requirements, there must be a way of detecting erroneous measurements, without help from outside the system. This process is called Fault Detection and Isolation (FDI). Fault detection requires at least one redundant measurement, and can be done with a parity space algorithm. The best way around the fault isolation problem is not necessarily isolating the bad measurement, but finding a new combination of measurements which excludes it.

Development of Measurement Methods for Detection of Special Nuclear Materials using D-D Pulsed Neutron Source

NASA Astrophysics Data System (ADS)

Misawa, Tsuyoshi; Takahashi, Yoshiyuki; Yagi, Takahiro; Pyeon, Cheol Ho; Kimura, Masaharu; Masuda, Kai; Ohgaki, Hideaki

2015-10-01

For detection of hidden special nuclear materials (SNMs), we have developed an active neutron-based interrogation system combined with a D-D fusion pulsed neutron source and a neutron detection system. In the detection scheme, we have adopted new measurement techniques simultaneously; neutron noise analysis and neutron energy spectrum analysis. The validity of neutron noise analysis method has been experimentally studied in the Kyoto University Critical Assembly (KUCA), and was applied to a cargo container inspection system by simulation.

Quantum cascade laser-based multipass absorption system for hydrogen peroxide detection

NASA Astrophysics Data System (ADS)

Cao, Yingchun; Sanchez, Nancy P.; Jiang, Wenzhe; Ren, Wei; Lewicki, Rafal; Jiang, Dongfang; Griffin, Robert J.; Tittel, Frank K.

2015-01-01

Hydrogen peroxide (H2O2) is a relevant molecular trace gas species, that is related to the oxidative capacity of the atmosphere, the production of radical species such as OH, the generation of sulfate aerosol via oxidation of S(IV) to S(VI), and the formation of acid rain. The detection of atmospheric H2O2 involves specific challenges due to its high reactivity and low concentration (ppbv to sub-ppbv level). Traditional methods for measuring atmospheric H2O2 concentration are often based on wet-chemistry methods that require a transfer from the gas- to liquid-phase for a subsequent determination by techniques such as fluorescence spectroscopy, which can lead to problems such as sampling artifacts and interference by other atmospheric constituents. A quartz-enhanced photoacoustic spectroscopy-based system for the measurement of atmospheric H2O2 with a detection limit of 75 ppb for 1-s integration time was previously reported. In this paper, an updated H2O2 detection system based on long-optical-path-length absorption spectroscopy by using a distributed feedback quantum cascade laser (DFB-QCL) will be described. A 7.73-μm CW-DFB-QCL and a thermoelectrically cooled infrared detector, optimized for a wavelength of 8 μm, are employed for theH2O2 sensor system. A commercial astigmatic Herriott multi-pass cell with an effective optical path-length of 76 m is utilized for the reported QCL multipass absorption system. Wavelength modulation spectroscopy (WMS) with second harmonic detection is used for enhancing the signal-to-noise-ratio. A minimum detection limit of 13.4 ppb is achieved with a 2 s sampling time. Based on an Allan-Werle deviation analysis the minimum detection limit can be improved to 1.5 ppb when using an averaging time of 300 s.

APDS: the autonomous pathogen detection system.

PubMed

Hindson, Benjamin J; Makarewicz, Anthony J; Setlur, Ujwal S; Henderer, Bruce D; McBride, Mary T; Dzenitis, John M

2005-04-15

We have developed and tested a fully autonomous pathogen detection system (APDS) capable of continuously monitoring the environment for airborne biological threat agents. The system was developed to provide early warning to civilians in the event of a bioterrorism incident and can be used at high profile events for short-term, intensive monitoring or in major public buildings or transportation nodes for long-term monitoring. The APDS is completely automated, offering continuous aerosol sampling, in-line sample preparation fluidics, multiplexed detection and identification immunoassays, and nucleic acid-based polymerase chain reaction (PCR) amplification and detection. Highly multiplexed antibody-based and duplex nucleic acid-based assays are combined to reduce false positives to a very low level, lower reagent costs, and significantly expand the detection capabilities of this biosensor. This article provides an overview of the current design and operation of the APDS. Certain sub-components of the ADPS are described in detail, including the aerosol collector, the automated sample preparation module that performs multiplexed immunoassays with confirmatory PCR, and the data monitoring and communications system. Data obtained from an APDS that operated continuously for 7 days in a major U.S. transportation hub is reported.

A Portable Smart-Phone Readout Device for the Detection of Mercury Contamination Based on an Aptamer-Assay Nanosensor.

PubMed

Xiao, Wei; Xiao, Meng; Fu, Qiangqiang; Yu, Shiting; Shen, Haicong; Bian, Hongfen; Tang, Yong

2016-11-08

The detection of environmental mercury (Hg) contamination requires complex and expensive instruments and professional technicians. We present a simple, sensitive, and portable Hg 2+ detection system based on a smartphone and colorimetric aptamer nanosensor. A smartphone equipped with a light meter app was used to detect, record, and process signals from a smartphone-based microwell reader (MR S-phone), which is composed of a simple light source and a miniaturized assay platform. The colorimetric readout of the aptamer nanosensor is based on a specific interaction between the selected aptamer and Hg 2+ , which leads to a color change in the reaction solution due to an aggregation of gold nanoparticles (AuNPs). The MR S-phone-based AuNPs-aptamer colorimetric sensor system could reliably detect Hg 2+ in both tap water and Pearl River water samples and produced a linear colorimetric readout of Hg 2+ concentration in the range of 1 ng/mL-32 ng/mL with a correlation of 0.991, and a limit of detection (LOD) of 0.28 ng/mL for Hg 2+ . The detection could be quickly completed in only 20 min. Our novel mercury detection assay is simple, rapid, and sensitive, and it provides new strategies for the on-site detection of mercury contamination in any environment.

A Portable Smart-Phone Readout Device for the Detection of Mercury Contamination Based on an Aptamer-Assay Nanosensor

PubMed Central

Xiao, Wei; Xiao, Meng; Fu, Qiangqiang; Yu, Shiting; Shen, Haicong; Bian, Hongfen; Tang, Yong

2016-01-01

The detection of environmental mercury (Hg) contamination requires complex and expensive instruments and professional technicians. We present a simple, sensitive, and portable Hg2+ detection system based on a smartphone and colorimetric aptamer nanosensor. A smartphone equipped with a light meter app was used to detect, record, and process signals from a smartphone-based microwell reader (MR S-phone), which is composed of a simple light source and a miniaturized assay platform. The colorimetric readout of the aptamer nanosensor is based on a specific interaction between the selected aptamer and Hg2+, which leads to a color change in the reaction solution due to an aggregation of gold nanoparticles (AuNPs). The MR S-phone-based AuNPs-aptamer colorimetric sensor system could reliably detect Hg2+ in both tap water and Pearl River water samples and produced a linear colorimetric readout of Hg2+ concentration in the range of 1 ng/mL–32 ng/mL with a correlation of 0.991, and a limit of detection (LOD) of 0.28 ng/mL for Hg2+. The detection could be quickly completed in only 20 min. Our novel mercury detection assay is simple, rapid, and sensitive, and it provides new strategies for the on-site detection of mercury contamination in any environment. PMID:27834794

A Testbed for Data Fusion for Engine Diagnostics and Prognostics1

DTIC Science & Technology

2002-03-01

detected ; too late to be useful for prognostics development. Table 1. Table of acronyms ACRONYM MEANING AD Anomaly detector...strictly defined points. Determining where we are on the engine health curve is the first step in prognostics . Fault detection / diagnostic reasoning... Detection As described above the ability of the monitoring system to detect an anomaly is especially important for knowledge-based systems, i.e.,

Bionic Vision-Based Intelligent Power Line Inspection System

PubMed Central

Ma, Yunpeng; He, Feijia; Xu, Jinxin

2017-01-01

Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism in this intelligent inspection system is used to detect and track power lines in image sequences according to the shape information of power lines, and the binocular visual model is used to calculate the 3D coordinate information of obstacles and power lines. In order to improve the real time and accuracy of the system, we propose a new matching strategy based on the traditional SURF algorithm. The experimental results show that the system is able to accurately locate the position of the obstacles around power lines automatically, and the designed power line inspection system is effective in complex backgrounds, and there are no missing detection instances under different conditions. PMID:28203269

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System

NASA Astrophysics Data System (ADS)

Gu, Yanlei; Panahpour Tehrani, Mehrdad; Yendo, Tomohiro; Fujii, Toshiaki; Tanimoto, Masayuki

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

Power System Transient Diagnostics Based on Novel Traveling Wave Detection

NASA Astrophysics Data System (ADS)

Hamidi, Reza Jalilzadeh

Modern electrical power systems demand novel diagnostic approaches to enhancing the system resiliency by improving the state-of-the-art algorithms. The proliferation of high-voltage optical transducers and high time-resolution measurements provide opportunities to develop novel diagnostic methods of very fast transients in power systems. At the same time, emerging complex configuration, such as multi-terminal hybrid transmission systems, limits the applications of the traditional diagnostic methods, especially in fault location and health monitoring. The impedance-based fault-location methods are inefficient for cross-bounded cables, which are widely used for connection of offshore wind farms to the main grid. Thus, this dissertation first presents a novel traveling wave-based fault-location method for hybrid multi-terminal transmission systems. The proposed method utilizes time-synchronized high-sampling voltage measurements. The traveling wave arrival times (ATs) are detected by observation of the squares of wavelet transformation coefficients. Using the ATs, an over-determined set of linear equations are developed for noise reduction, and consequently, the faulty segment is determined based on the characteristics of the provided equation set. Then, the fault location is estimated. The accuracy and capabilities of the proposed fault location method are evaluated and also compared to the existing traveling-wave-based method for a wide range of fault parameters. In order to improve power systems stability, auto-reclosing (AR), single-phase auto-reclosing (SPAR), and adaptive single-phase auto-reclosing (ASPAR) methods have been developed with the final objectives of distinguishing between the transient and permanent faults to clear the transient faults without de-energization of the solid phases. However, the features of the electrical arcs (transient faults) are severely influenced by a number of random parameters, including the convection of the air and plasma, wind speed, air pressure, and humidity. Therefore, the dead-time (the de-energization duration of the faulty phase) is unpredictable. Accordingly, conservatively long dead-times are usually considered by protection engineers. However, if the exact arc distinction time is determined, the power system stability and quality will enhance. Therefore, a new method for detection of arc extinction times leading to a new ASPAR method utilizing power line carrier (PLC) signals is presented. The efficiency of the proposed ASPAR method is verified through simulations and compared with the existing ASPAR methods. High-sampling measurements are prone to be skewed by the environmental noises and analog-to-digital (A/D) converters quantization errors. Therefore noise-contaminated measurements are the major source of uncertainties and errors in the outcomes of traveling wave-based diagnostic applications. The existing AT-detection methods do not provide enough sensitivity and selectivity at the same time. Therefore, a new AT-detection method based on short-time matrix pencil (STMPM) is developed to accurately detect ATs of the traveling waves with low signal-to-noise (SNR) ratios. As STMPM is based on matrix algebra, it is a challenging to implement this new technique in microprocessor-based fault locators. Hence, a fully recursive and computationally efficient method based on adaptive discrete Kalman filter (ADKF) is introduced for AT-detection, which is proper for microprocessors and able to accomplish accurate AT-detection for online applications such as ultra-high-speed protection. Both proposed AT-detection methods are evaluated based on extensive simulation studies, and the superior outcomes are compared to the existing methods.

Chemical Sensor Systems and Associated Algorithms for Fire Detection: A Review.

PubMed

Fonollosa, Jordi; Solórzano, Ana; Marco, Santiago

2018-02-11

Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative.

Chemical Sensor Systems and Associated Algorithms for Fire Detection: A Review

PubMed Central

Fonollosa, Jordi

2018-01-01

Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative. PMID:29439490

Development of a multispectral structured-illumination reflectance imaging (SIRI) system and its application to bruise detection of apples

USDA-ARS?s Scientific Manuscript database

Structured-illumination reflectance imaging (SIRI) is a new, promising imaging modality for enhancing quality detection of food. A liquid-crystal tunable filter (LCTF)-based multispectral SIRI system was developed and used for selecting optimal wavebands to detect bruising in apples. Immediately aft...

Defect detection performance of the UCSD non-contact air-coupled ultrasonic guided wave inspection of rails prototype

NASA Astrophysics Data System (ADS)

Mariani, Stefano; Nguyen, Thompson V.; Sternini, Simone; Lanza di Scalea, Francesco; Fateh, Mahmood; Wilson, Robert

2016-04-01

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system's operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. The prototype based on this technology was tested in October 2014 at the Transportation Technology Center (TTC) in Pueblo, Colorado, and again in November 2015 after incorporating changes based on lessons learned. Results from the 2015 field test are discussed in this paper.

Optical coherence tomography-based decision making in exudative age-related macular degeneration: comparison of time- vs spectral-domain devices.

PubMed

Cukras, C; Wang, Y D; Meyerle, C B; Forooghian, F; Chew, E Y; Wong, W T

2010-05-01

To determine whether optical coherence tomography (OCT) device-type influences clinical grading of OCT imaging in the context of exudative age-related macular degeneration (AMD). Ninety-six paired OCT scans from 49 patients with active exudative AMD were obtained on both the time-domain Stratus OCT system and the spectral-domain Cirrus OCT system at the same visit. Three independent graders judged each scan for the presence of intraretinal fluid (IRF) or subretinal fluid (SRF). The degree of grader consensus was evaluated and the ability of the systems to detect the presence of disease activity was analysed. Cirrus OCT generated a higher degree of inter-grader consensus than Stratus OCT with higher intraclass correlation coefficients for all parameters analysed. A pair-wise comparison of Cirrus OCT with Stratus OCT systems revealed that Cirrus-based gradings more frequently reported the presence of SRF and IRF and detected overall neovascular activity at a higher rate (P<0.05) compared with Stratus-based gradings. The choice of time-domain (Stratus) vs spectra-domain (Cirrus) OCT systems has a measurable impact on clinical decision making in exudative AMD. Spectral-domain OCT systems may be able to generate more consensus in clinical interpretation and, in particular cases, detect disease activity not detected by time-domain systems. Clinical trials using OCT-based clinical evaluations of exudative AMD may need to account for these inter-system differences in planning and analysis.

Optical Coherence Tomography-Based Decision Making in Exudative Age-related Macular Degeneration: Comparison of Time- versus Spectral-Domain Devices

PubMed Central

Cukras, Catherine; Wang, Yunqing D.; Meyerle, Catherine B.; Forooghian, Farzin; Chew, Emily Y.; Wong, Wai T.

2010-01-01

Purpose To determine if optical coherence tomography (OCT) device-type influences clinical grading of OCT imaging in the context of exudative age-related macular degeneration (AMD). Methods Ninety-six paired OCT scans from 49 patients with active exudative AMD were obtained on both the time-domain Stratus™ OCT system and the spectral-domain Cirrus™ OCT system at the same visit. Three independent graders judged each scan for the presence of intraretinal fluid (IRF) or subretinal fluid (SRF). The degree of grader consensus was evaluated and the ability of the systems to detect the presence of disease activity was analyzed. Results Cirrus™ OCT generated a higher degree of inter-grader consensus than Stratus OCT with higher intraclass correlation coefficients (ICC) for all parameters analyzed. A pair-wise comparison of Cirrus™ OCT to Stratus™ OCT systems revealed that Cirrus™-based gradings more frequently reported the presence of SRF and IRF and detected overall neovascular activity at a higher rate (p<0.05) compared to Stratus™-based gradings Conclusions The choice of time-domain (Stratus™) versus spectra-domain (Cirrus™) OCT systems has a measurable impact on clinical decision making in exudative AMD. Spectral-domain OCT systems may be able to generate more consensus in clinical interpretation and, in particular cases, detect disease activity not detected by time-domain systems. Clinical trials employing OCT-based clinical evaluations of exudative AMD may need to account for these inter-system differences in planning and analysis. PMID:19696804

Fibre optic portable rail vehicle detector

NASA Astrophysics Data System (ADS)

Kepak, Stanislav; Cubik, Jakub; Zavodny, Petr; Hejduk, Stanislav; Nedoma, Jan; Davidson, Alan; Vasinek, Vladimir

2016-12-01

During track maintenance operations, the early detection of oncoming rail vehicles is critical for the safety of maintenance personnel. In addition, the detection system should be simple to install at the trackside by minimally qualified personnel. Fibre optic based sensor systems have the inherent advantages of being passive, unaffected by radio frequency interference (RFI) and suffering very low signal attenuation. Such a system therefore represents a good alternative to conventional approaches such as ultrasonic based sensor systems. The proposed system consists of one or more passive fibre trackside sensors and an x86 processing unit located at the work site. The solid fibre connection between sensors and processing unit eliminates the risk of RFI. In addition, the detection system sensors are easy to install with no requirement for electrical power at the sensor site. The system was tested on a tram line in Ostrava with the results obtained indicating the successful detection of all the trams in the monitoring windows using a single sensor. However, the platform allows flexibility in configuring multiple sensors where required by system users.

The design of high precision temperature control system for InGaAs short-wave infrared detector

NASA Astrophysics Data System (ADS)

Wang, Zheng-yun; Hu, Yadong; Ni, Chen; Huang, Lin; Zhang, Aiwen; Sun, Xiao-bing; Hong, Jin

2018-02-01

The InGaAs Short-wave infrared detector is a temperature-sensitive device. Accurate temperature control can effectively reduce the background signal and improve detection accuracy, detection sensitivity, and the SNR of the detection system. Firstly, the relationship between temperature and detection background, NEP is analyzed, the principle of TEC and formula between cooling power, cooling current and hot-cold interface temperature difference are introduced. Then, the high precision constant current drive circuit based on triode voltage control current, and an incremental algorithm model based on deviation tracking compensation and PID control are proposed, which effectively suppresses the temperature overshoot, overcomes the temperature inertia, and has strong robustness. Finally, the detector and temperature control system are tested. Results show that: the lower of detector temperature, the smaller the temperature fluctuation, the higher the detection accuracy and the detection sensitivity. The temperature control system achieves the high temperature control with the temperature control rate is 7 8°C/min and the temperature fluctuation is better than +/-0. 04°C.

Computer-aided detection of breast lesions in DCE-MRI using region growing based on fuzzy C-means clustering and vesselness filter

NASA Astrophysics Data System (ADS)

B. Shokouhi, Shahriar; Fooladivanda, Aida; Ahmadinejad, Nasrin

2017-12-01

A computer-aided detection (CAD) system is introduced in this paper for detection of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The proposed CAD system firstly compensates motion artifacts and segments the breast region. Then, the potential lesion voxels are detected and used as the initial seed points for the seeded region-growing algorithm. A new and robust region-growing algorithm incorporating with Fuzzy C-means (FCM) clustering and vesselness filter is proposed to segment any potential lesion regions. Subsequently, the false positive detections are reduced by applying a discrimination step. This is based on 3D morphological characteristics of the potential lesion regions and kinetic features which are fed to the support vector machine (SVM) classifier. The performance of the proposed CAD system is evaluated using the free-response operating characteristic (FROC) curve. We introduce our collected dataset that includes 76 DCE-MRI studies, 63 malignant and 107 benign lesions. The prepared dataset has been used to verify the accuracy of the proposed CAD system. At 5.29 false positives per case, the CAD system accurately detects 94% of the breast lesions.

Progress in Arc Safety System Based on Harmonics Detection for ICRH Antennae

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

Berger-By, G.; Beaumont, B.; Lombard, G.

2007-09-28

The arc detection systems based on harmonics detection have been tested n USA (TFTR, DIII, Alcator C-mod) and Germany (Asdex). These systems have some advantages in comparison with traditonal securities which use a threshold on the Vr/Vf (Reflected to Forward voltage ratio) calculation and are ITER relevant. On Tore Supra (TS) 3 systems have been built using this principle with some improvements and new features to increase the protection of the 3 ICRH generators and antennae. On JET 2 arc safety systems based on the TS principle wil also be used to mprove the JET ITER-like antenna safety. In ordermore » to have the maximum security level on the TS ICRH system, the 3 antennae are used with these systems during all plasma shots n redundancy with the other systems. This TS RF principle and ts electronic interactions with the VME control of the generator are described. The results on the TS ICRH transmitter feeding the 3 antennae are summarized and some typical signals are given.« less

Epileptic seizure onset detection based on EEG and ECG data fusion.

PubMed

Qaraqe, Marwa; Ismail, Muhammad; Serpedin, Erchin; Zulfi, Haneef

2016-05-01

This paper presents a novel method for seizure onset detection using fused information extracted from multichannel electroencephalogram (EEG) and single-channel electrocardiogram (ECG). In existing seizure detectors, the analysis of the nonlinear and nonstationary ECG signal is limited to the time-domain or frequency-domain. In this work, heart rate variability (HRV) extracted from ECG is analyzed using a Matching-Pursuit (MP) and Wigner-Ville Distribution (WVD) algorithm in order to effectively extract meaningful HRV features representative of seizure and nonseizure states. The EEG analysis relies on a common spatial pattern (CSP) based feature enhancement stage that enables better discrimination between seizure and nonseizure features. The EEG-based detector uses logical operators to pool SVM seizure onset detections made independently across different EEG spectral bands. Two fusion systems are adopted. In the first system, EEG-based and ECG-based decisions are directly fused to obtain a final decision. The second fusion system adopts an override option that allows for the EEG-based decision to override the fusion-based decision in the event that the detector observes a string of EEG-based seizure decisions. The proposed detectors exhibit an improved performance, with respect to sensitivity and detection latency, compared with the state-of-the-art detectors. Experimental results demonstrate that the second detector achieves a sensitivity of 100%, detection latency of 2.6s, and a specificity of 99.91% for the MAJ fusion case. Copyright © 2016 Elsevier Inc. All rights reserved.

Determining root correspondence between previously and newly detected objects

DOEpatents

Paglieroni, David W.; Beer, N Reginald

2014-06-17

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

Dose and detectability for a cone-beam C-arm CT system revisited

PubMed Central

Ganguly, Arundhuti; Yoon, Sungwon; Fahrig, Rebecca

2010-01-01

Purpose: The authors had previously published measurements of the detectability of disk-shaped contrast objects in images obtained from a C-arm CT system. A simple approach based on Rose’s criterion was used to scale the date, assuming the threshold for the smallest diameter detected should be inversely proportional to (dose)1∕2. A more detailed analysis based on recent theoretical modeling of C-arm CT images is presented in this work. Methods: The signal and noise propagations in a C-arm based CT system have been formulated by other authors using cascaded systems analysis. They established a relationship between detectability and the noise equivalent quanta. Based on this model, the authors obtained a relation between x-ray dose and the diameter of the smallest disks detected. A closed form solution was established by assuming no rebinning and no resampling of data, with low additive noise and using a ramp filter. For the case when no such assumptions were made, a numerically calculated solution using previously reported imaging and reconstruction parameters was obtained. The detection probabilities for a range of dose and kVp values had been measured previously. These probabilities were normalized to a single dose of 56.6 mGy using the Rose-criteria-based relation to obtain a universal curve. Normalizations based on the new numerically calculated relationship were compared to the measured results. Results: The theoretical and numerical calculations have similar results and predict the detected diameter size to be inversely proportional to (dose)1∕3 and (dose)1∕2.8, respectively. The normalized experimental curves and the associated universal plot using the new relation were not significantly different from those obtained using the Rose-criterion-based normalization. Conclusions: From numerical simulations, the authors found that the diameter of detected disks depends inversely on the cube root of the dose. For observer studies for disks larger than 4 mm, the cube root as well as square root relations appear to give similar results when used for normalization. PMID:20527560

A Method of Detections' Fusion for GNSS Anti-Spoofing.

PubMed

Tao, Huiqi; Li, Hong; Lu, Mingquan

2016-12-19

The spoofing attack is one of the security threats of systems depending on the Global Navigation Satellite System (GNSS). There have been many GNSS spoofing detection methods, and each of them focuses on a characteristic of the GNSS signal or a measurement that the receiver has obtained. The method based on a single detector is insufficient against spoofing attacks in some scenarios. How to fuse multiple detections together is a problem that concerns the performance of GNSS anti-spoofing. Scholars have put forward a model to fuse different detection results based on the Dempster-Shafer theory (DST) of evidence combination. However, there are some problems in the application. The main challenge is the valuation of the belief function, which is a key issue in DST. This paper proposes a practical method of detections' fusion based on an approach to assign the belief function for spoofing detections. The frame of discernment is simplified, and the hard decision of hypothesis testing is replaced by the soft decision; then, the belief functions for some detections can be evaluated. The method is discussed in detail, and a performance evaluation is provided, as well. Detections' fusion reduces false alarms of detection and makes the result more reliable. Experimental results based on public test datasets demonstrate the performance of the proposed method.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.

1992-01-01

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

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

PubMed

Johnson, Mitchell E; Landers, James P

2004-11-01

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

Electrical breakdown detection system for dielectric elastomer actuators

NASA Astrophysics Data System (ADS)

Ghilardi, Michele; Busfield, James J. C.; Carpi, Federico

2017-04-01

Electrical breakdown of dielectric elastomer actuators (DEAs) is an issue that has to be carefully addressed when designing systems based on this novel technology. Indeed, in some systems electrical breakdown might have serious consequences, not only in terms of interruption of the desired function but also in terms of safety of the overall system (e.g. overheating and even burning). The risk for electrical breakdown often cannot be completely avoided by simply reducing the driving voltages, either because completely safe voltages might not generate sufficient actuation or because internal or external factors might change some properties of the actuator whilst in operation (for example the aging or fatigue of the material, or an externally imposed deformation decreasing the distance between the compliant electrodes). So, there is the clear need for reliable, simple and cost-effective detection systems that are able to acknowledge the occurrence of a breakdown event, making DEA-based devices able to monitor their status and become safer and "selfaware". Here a simple solution for a portable detection system is reported that is based on a voltage-divider configuration that detects the voltage drop at the DEA terminals and assesses the occurrence of breakdown via a microcontroller (Beaglebone Black single-board computer) combined with a real-time, ultra-low-latency processing unit (Bela cape an open-source embedded platform developed at Queen Mary University of London). The system was used to both generate the control signal that drives the actuator and constantly monitor the functionality of the actuator, detecting any breakdown event and discontinuing the supplied voltage accordingly, so as to obtain a safer controlled actuation. This paper presents preliminary tests of the detection system in different scenarios in order to assess its reliability.

Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator

NASA Astrophysics Data System (ADS)

Hou, Jian; Yan, Xiao-peng; Li, Ping; Hao, Xin-hong

2018-03-01

The conventional Duffing oscillator weak signal detection method, which is based on a strong reference signal, has inherent deficiencies. To address these issues, the characteristics of the Duffing oscillatorʼs phase trajectory in a small-scale periodic state are analyzed by introducing the theory of stopping oscillation system. Based on this approach, a novel Duffing oscillator weak wide-band signal detection method is proposed. In this novel method, the reference signal is discarded, and the to-be-detected signal is directly used as a driving force. By calculating the cosine function of a phase space angle, a single Duffing oscillator can be used for weak wide-band signal detection instead of an array of uncoupled Duffing oscillators. Simulation results indicate that, compared with the conventional Duffing oscillator detection method, this approach performs better in frequency detection intervals, and reduces the signal-to-noise ratio detection threshold, while improving the real-time performance of the system. Project supported by the National Natural Science Foundation of China (Grant No. 61673066).

Motion-compensated optical coherence tomography using envelope-based surface detection and Kalman-based prediction

NASA Astrophysics Data System (ADS)

Irsch, Kristina; Lee, Soohyun; Bose, Sanjukta N.; Kang, Jin U.

2018-02-01

We present an optical coherence tomography (OCT) imaging system that effectively compensates unwanted axial motion with micron-scale accuracy. The OCT system is based on a swept-source (SS) engine (1060-nm center wavelength, 100-nm full-width sweeping bandwidth, and 100-kHz repetition rate), with axial and lateral resolutions of about 4.5 and 8.5 microns respectively. The SS-OCT system incorporates a distance sensing method utilizing an envelope-based surface detection algorithm. The algorithm locates the target surface from the B-scans, taking into account not just the first or highest peak but the entire signature of sequential A-scans. Subsequently, a Kalman filter is applied as predictor to make up for system latencies, before sending the calculated position information to control a linear motor, adjusting and maintaining a fixed system-target distance. To test system performance, the motioncorrection algorithm was compared to earlier, more basic peak-based surface detection methods and to performing no motion compensation. Results demonstrate increased robustness and reproducibility, particularly noticeable in multilayered tissues, while utilizing the novel technique. Implementing such motion compensation into clinical OCT systems may thus improve the reliability of objective and quantitative information that can be extracted from OCT measurements.

A Feasibility Analysis of Land-Based SINS/GNSS Gravimetry for Groundwater Resource Detection in Taiwan

PubMed Central

Chiang, Kai-Wei; Lin, Cheng-An; Kuo, Chung-Yen

2015-01-01

The integration of the Strapdown Inertial Navigation System and Global Navigation Satellite System (SINS/GNSS) has been implemented for land-based gravimetry and has been proven to perform well in estimating gravity. Based on the mGal-level gravimetry results, this research aims to construct and develop a land-based SINS/GNSS gravimetry device containing a navigation-grade Inertial Measurement Unit. This research also presents a feasibility analysis for groundwater resource detection. A preliminary comparison of the kinematic velocities and accelerations using multi-combination of GNSS data including Global Positioning System, Global Navigation Satellite System, and BeiDou Navigation Satellite System, indicates that three-system observations performed better than two-system data in the computation. A comparison of gravity derived from SINS/GNSS and measured using a relative gravimeter also shows that both agree reasonably well with a mean difference of 2.30 mGal. The mean difference between repeat measurements of gravity disturbance using SINS/GNSS is 2.46 mGal with a standard deviation of 1.32 mGal. The gravity variation because of the groundwater at Pingtung Plain, Taiwan could reach 2.72 mGal. Hence, the developed land-based SINS/GNSS gravimetry can sufficiently and effectively detect groundwater resources. PMID:26426019

A Feasibility Analysis of Land-Based SINS/GNSS Gravimetry for Groundwater Resource Detection in Taiwan.

PubMed

Chiang, Kai-Wei; Lin, Cheng-An; Kuo, Chung-Yen

2015-09-29

The integration of the Strapdown Inertial Navigation System and Global Navigation Satellite System (SINS/GNSS) has been implemented for land-based gravimetry and has been proven to perform well in estimating gravity. Based on the mGal-level gravimetry results, this research aims to construct and develop a land-based SINS/GNSS gravimetry device containing a navigation-grade Inertial Measurement Unit. This research also presents a feasibility analysis for groundwater resource detection. A preliminary comparison of the kinematic velocities and accelerations using multi-combination of GNSS data including Global Positioning System, Global Navigation Satellite System, and BeiDou Navigation Satellite System, indicates that three-system observations performed better than two-system data in the computation. A comparison of gravity derived from SINS/GNSS and measured using a relative gravimeter also shows that both agree reasonably well with a mean difference of 2.30 mGal. The mean difference between repeat measurements of gravity disturbance using SINS/GNSS is 2.46 mGal with a standard deviation of 1.32 mGal. The gravity variation because of the groundwater at Pingtung Plain, Taiwan could reach 2.72 mGal. Hence, the developed land-based SINS/GNSS gravimetry can sufficiently and effectively detect groundwater resources.

Research on the attitude detection technology of the tetrahedron robot

NASA Astrophysics Data System (ADS)

Gong, Hao; Chen, Keshan; Ren, Wenqiang; Cai, Xin

2017-10-01

The traditional attitude detection technology can't tackle the problem of attitude detection of the polyhedral robot. Thus we propose a novel algorithm of multi-sensor data fusion which is based on Kalman filter. In the algorithm a tetrahedron robot is investigated. We devise an attitude detection system for the polyhedral robot and conduct the verification of data fusion algorithm. It turns out that the minimal attitude detection system we devise could capture attitudes of the tetrahedral robot in different working conditions. Thus the Kinematics model we establish for the tetrahedron robot is correct and the feasibility of the attitude detection system is proven.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Capability of long distance 100  GHz FMCW using a single GDD lamp sensor.

PubMed

Levanon, Assaf; Rozban, Daniel; Aharon Akram, Avihai; Kopeika, Natan S; Yitzhaky, Yitzhak; Abramovich, Amir

2014-12-20

Millimeter wave (MMW)-based imaging systems are required for applications in medicine, homeland security, concealed weapon detection, and space technology. The lack of inexpensive room temperature imaging sensors makes it difficult to provide a suitable MMW system for many of the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The radar system requires that the millimeter wave detector will be able to operate as a heterodyne detector. Since the source of radiation is a frequency modulated continuous wave (FMCW), the detected signal as a result of heterodyne detection gives the object's depth information according to value of difference frequency, in addition to the reflectance of the 2D image. New experiments show the capability of long distance FMCW detection by using a large scale Cassegrain projection system, described first (to our knowledge) in this paper. The system presents the capability to employ a long distance of at least 20 m with a low-cost plasma-based glow discharge detector (GDD) focal plane array (FPA). Each point on the object corresponds to a point in the image and includes the distance information. This will enable relatively inexpensive 3D MMW imaging.

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.

Automatic Fall Detection System Based on the Combined Use of a Smartphone and a Smartwatch.

PubMed

Casilari, Eduardo; Oviedo-Jiménez, Miguel A

2015-01-01

Due to their widespread popularity, decreasing costs, built-in sensors, computing power and communication capabilities, Android-based personal devices are being seen as an appealing technology for the deployment of wearable fall detection systems. In contrast with previous solutions in the existing literature, which are based on the performance of a single element (a smartphone), this paper proposes and evaluates a fall detection system that benefits from the detection performed by two popular personal devices: a smartphone and a smartwatch (both provided with an embedded accelerometer and a gyroscope). In the proposed architecture, a specific application in each component permanently tracks and analyses the patient's movements. Diverse fall detection algorithms (commonly employed in the literature) were implemented in the developed Android apps to discriminate falls from the conventional activities of daily living of the patient. As a novelty, a fall is only assumed to have occurred if it is simultaneously and independently detected by the two Android devices (which can interact via Bluetooth communication). The system was systematically evaluated in an experimental testbed with actual test subjects simulating a set of falls and conventional movements associated with activities of daily living. The tests were repeated by varying the detection algorithm as well as the pre-defined mobility patterns executed by the subjects (i.e., the typology of the falls and non-fall movements). The proposed system was compared with the cases where only one device (the smartphone or the smartwatch) is considered to recognize and discriminate the falls. The obtained results show that the joint use of the two detection devices clearly increases the system's capability to avoid false alarms or 'false positives' (those conventional movements misidentified as falls) while maintaining the effectiveness of the detection decisions (that is to say, without increasing the ratio of 'false negatives' or actual falls that remain undetected).

Fault detection of Tennessee Eastman process based on topological features and SVM

NASA Astrophysics Data System (ADS)

Zhao, Huiyang; Hu, Yanzhu; Ai, Xinbo; Hu, Yu; Meng, Zhen

2018-03-01

Fault detection in industrial process is a popular research topic. Although the distributed control system(DCS) has been introduced to monitor the state of industrial process, it still cannot satisfy all the requirements for fault detection of all the industrial systems. In this paper, we proposed a novel method based on topological features and support vector machine(SVM), for fault detection of industrial process. The proposed method takes global information of measured variables into account by complex network model and predicts whether a system has generated some faults or not by SVM. The proposed method can be divided into four steps, i.e. network construction, network analysis, model training and model testing respectively. Finally, we apply the model to Tennessee Eastman process(TEP). The results show that this method works well and can be a useful supplement for fault detection of industrial process.

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.

Three-gas detection system with IR optical sensor based on NDIR technology

NASA Astrophysics Data System (ADS)

Tan, Qiulin; Tang, Licheng; Yang, Mingliang; Xue, Chenyang; Zhang, Wendong; Liu, Jun; Xiong, Jijun

2015-11-01

In this paper, a three-gas detection system with a environmental parameter compensation method is proposed based on Non-dispersive infra-red (NDIR) technique, which can be applied to detect multi-gas (methane, carbon dioxide and carbon monoxide). In this system, an IR source and four single-channel pyroelectric sensors are integrated in the miniature optical gas chamber successfully. Inner wall of the chamber coated with Au film is designed as paraboloids. The infrared light is reflected twice before reaching to detectors, thus increasing optical path. Besides, a compensation method is presented to overcome the influence in variation of environment (ambient temperature, humidity and pressure), thus leading to improve the accuracy in gas detection. Experimental results demonstrated that detection ranges are 0-50,000 ppm for CH4, 0-44,500 ppm for CO, 0-48,000 ppm for CO2 and the accuracy is ±0.05%.

The research of adaptive-exposure on spot-detecting camera in ATP system

NASA Astrophysics Data System (ADS)

Qian, Feng; Jia, Jian-jun; Zhang, Liang; Wang, Jian-Yu

2013-08-01

High precision acquisition, tracking, pointing (ATP) system is one of the key techniques of laser communication. The spot-detecting camera is used to detect the direction of beacon in laser communication link, so that it can get the position information of communication terminal for ATP system. The positioning accuracy of camera decides the capability of laser communication system directly. So the spot-detecting camera in satellite-to-earth laser communication ATP systems needs high precision on target detection. The positioning accuracy of cameras should be better than +/-1μ rad . The spot-detecting cameras usually adopt centroid algorithm to get the position information of light spot on detectors. When the intensity of beacon is moderate, calculation results of centroid algorithm will be precise. But the intensity of beacon changes greatly during communication for distance, atmospheric scintillation, weather etc. The output signal of detector will be insufficient when the camera underexposes to beacon because of low light intensity. On the other hand, the output signal of detector will be saturated when the camera overexposes to beacon because of high light intensity. The calculation accuracy of centroid algorithm becomes worse if the spot-detecting camera underexposes or overexposes, and then the positioning accuracy of camera will be reduced obviously. In order to improve the accuracy, space-based cameras should regulate exposure time in real time according to light intensity. The algorithm of adaptive-exposure technique for spot-detecting camera based on metal-oxide-semiconductor (CMOS) detector is analyzed. According to analytic results, a CMOS camera in space-based laser communication system is described, which utilizes the algorithm of adaptive-exposure to adapting exposure time. Test results from imaging experiment system formed verify the design. Experimental results prove that this design can restrain the reduction of positioning accuracy for the change of light intensity. So the camera can keep stable and high positioning accuracy during communication.

A Web-Based, Hospital-Wide Health Care-Associated Bloodstream Infection Surveillance and Classification System: Development and Evaluation.

PubMed

Tseng, Yi-Ju; Wu, Jung-Hsuan; Lin, Hui-Chi; Chen, Ming-Yuan; Ping, Xiao-Ou; Sun, Chun-Chuan; Shang, Rung-Ji; Sheng, Wang-Huei; Chen, Yee-Chun; Lai, Feipei; Chang, Shan-Chwen

2015-09-21

Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20; r=.999 P<.001) and by time (n=14; r=.941; P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system.

Is Comprehension Necessary for Error Detection? A Conflict-Based Account of Monitoring in Speech Production

ERIC Educational Resources Information Center

Nozari, Nazbanou; Dell, Gary S.; Schwartz, Myrna F.

2011-01-01

Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the…

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

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

PubMed

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

2016-09-29

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

Automatic Emboli Detection System for the Artificial Heart

NASA Astrophysics Data System (ADS)

Steifer, T.; Lewandowski, M.; Karwat, P.; Gawlikowski, M.

In spite of the progress in material engineering and ventricular assist devices construction, thromboembolism remains the most crucial problem in mechanical heart supporting systems. Therefore, the ability to monitor the patient's blood for clot formation should be considered an important factor in development of heart supporting systems. The well-known methods for automatic embolus detection are based on the monitoring of the ultrasound Doppler signal. A working system utilizing ultrasound Doppler is being developed for the purpose of flow estimation and emboli detection in the clinical artificial heart ReligaHeart EXT. Thesystem will be based on the existing dual channel multi-gate Doppler device with RF digital processing. A specially developed clamp-on cannula probe, equipped with 2 - 4 MHz piezoceramic transducers, enables easy system setup. We present the issuesrelated to the development of automatic emboli detection via Doppler measurements. We consider several algorithms for the flow estimation and emboli detection. We discuss their efficiency and confront them with the requirements of our experimental setup. Theoretical considerations are then met with preliminary experimental findings from a) flow studies with blood mimicking fluid and b) in-vitro flow studies with animal blood. Finally, we discuss some more methodological issues - we consider several possible approaches to the problem of verification of the accuracy of the detection system.

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG

PubMed Central

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-01-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety. PMID:28257073

System for critical infrastructure security based on multispectral observation-detection module

NASA Astrophysics Data System (ADS)

Trzaskawka, Piotr; Kastek, Mariusz; Życzkowski, Marek; Dulski, Rafał; Szustakowski, Mieczysław; Ciurapiński, Wiesław; Bareła, Jarosław

2013-10-01

Recent terrorist attacks and possibilities of such actions in future have forced to develop security systems for critical infrastructures that embrace sensors technologies and technical organization of systems. The used till now perimeter protection of stationary objects, based on construction of a ring with two-zone fencing, visual cameras with illumination are efficiently displaced by the systems of the multisensor technology that consists of: visible technology - day/night cameras registering optical contrast of a scene, thermal technology - cheap bolometric cameras recording thermal contrast of a scene and active ground radars - microwave and millimetre wavelengths that record and detect reflected radiation. Merging of these three different technologies into one system requires methodology for selection of technical conditions of installation and parameters of sensors. This procedure enables us to construct a system with correlated range, resolution, field of view and object identification. Important technical problem connected with the multispectral system is its software, which helps couple the radar with the cameras. This software can be used for automatic focusing of cameras, automatic guiding cameras to an object detected by the radar, tracking of the object and localization of the object on the digital map as well as target identification and alerting. Based on "plug and play" architecture, this system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provide high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering. The paper presents a structure and some elements of critical infrastructure protection solution which is based on a modular multisensor security system. System description is focused mainly on methodology of selection of sensors parameters. The results of the tests in real conditions are also presented.

Microfluidic acoustophoretic force based low-concentration oil separation and detection from the environment.

PubMed

Wang, Han; Liu, Zhongzheng; Kim, Sungman; Koo, Chiwan; Cho, Younghak; Jang, Dong-Young; Kim, Yong-Joe; Han, Arum

2014-03-07

Detecting and quantifying extremely low concentrations of oil from the environment have broad applications in oil spill monitoring in ocean and coastal areas as well as in oil leakage monitoring on land. Currently available methods for low-concentration oil detection are bulky or costly with limited sensitivities. Thus they are difficult to be used as portable and field-deployable detectors in the case of oil spills or for monitoring the long-term effects of dispersed oil on marine and coastal ecosystems. Here, we present a low-concentration oil droplet trapping and detection microfluidic system based on the acoustophoresis phenomenon where oil droplets in water having a negative acoustic contrast factor move towards acoustic pressure anti-nodes. By trapping oil droplets from water samples flowing through a microfluidic channel, even very low concentrations of oil droplets can be concentrated to a detectable level for further analyses, which is a significant improvement over currently available oil detection systems. Oil droplets in water were successfully trapped and accumulated in a circular acoustophoretic trapping chamber of the microfluidic device and detected using a custom-built compact fluorescent detector based on the natural fluorescence of the trapped crude oil droplets. After the on-line detection, crude oil droplets released from the trapping chamber were successfully separated into a collection outlet by acoustophoretic force for further off-chip analyses. The developed microfluidic system provides a new way of trapping, detecting, and separating low-concentration crude oil from environmental water samples and holds promise as a low-cost field-deployable oil detector with extremely high sensitivity. The microfluidic system and operation principle are expected to be utilized in a wide range of applications where separating, concentrating, and detecting small particles having a negative acoustic contrast factor are required.

Forest fire autonomous decision system based on fuzzy logic

NASA Astrophysics Data System (ADS)

Lei, Z.; Lu, Jianhua

2010-11-01

The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.

Developments on a SEM-based X-ray tomography system: Stabilization scheme and performance evaluation

NASA Astrophysics Data System (ADS)

Gomes Perini, L. A.; Bleuet, P.; Filevich, J.; Parker, W.; Buijsse, B.; Kwakman, L. F. Tz.

2017-06-01

Recent improvements in a SEM-based X-ray tomography system are described. In this type of equipment, X-rays are generated through the interaction between a highly focused electron-beam and a geometrically confined anode target. Unwanted long-term drifts of the e-beam can lead to loss of X-ray flux or decrease of spatial resolution in images. To circumvent this issue, a closed-loop control using FFT-based image correlation is integrated to the acquisition routine, in order to provide an in-line drift correction. The X-ray detection system consists of a state-of-the-art scientific CMOS camera (indirect detection), featuring high quantum efficiency (˜60%) and low read-out noise (˜1.2 electrons). The system performance is evaluated in terms of resolution, detectability, and scanning times for applications covering three different scientific fields: microelectronics, technical textile, and material science.

Staircase-scene-based nonuniformity correction in aerial point target detection systems.

PubMed

Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

2016-09-01

Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections.

A Bevel Gear Quality Inspection System Based on Multi-Camera Vision Technology

PubMed Central

Liu, Ruiling; Zhong, Dexing; Lyu, Hongqiang; Han, Jiuqiang

2016-01-01

Surface defect detection and dimension measurement of automotive bevel gears by manual inspection are costly, inefficient, low speed and low accuracy. In order to solve these problems, a synthetic bevel gear quality inspection system based on multi-camera vision technology is developed. The system can detect surface defects and measure gear dimensions simultaneously. Three efficient algorithms named Neighborhood Average Difference (NAD), Circle Approximation Method (CAM) and Fast Rotation-Position (FRP) are proposed. The system can detect knock damage, cracks, scratches, dents, gibbosity or repeated cutting of the spline, etc. The smallest detectable defect is 0.4 mm × 0.4 mm and the precision of dimension measurement is about 40–50 μm. One inspection process takes no more than 1.3 s. Both precision and speed meet the requirements of real-time online inspection in bevel gear production. PMID:27571078

Optical biosensor system with integrated microfluidic sample preparation and TIRF based detection

NASA Astrophysics Data System (ADS)

Gilli, Eduard; Scheicher, Sylvia R.; Suppan, Michael; Pichler, Heinz; Rumpler, Markus; Satzinger, Valentin; Palfinger, Christian; Reil, Frank; Hajnsek, Martin; Köstler, Stefan

2013-05-01

There is a steadily growing demand for miniaturized bioanalytical devices allowing for on-site or point-of-care detection of biomolecules or pathogens in applications like diagnostics, food testing, or environmental monitoring. These, so called labs-on-a-chip or micro-total analysis systems (μ-TAS) should ideally enable convenient sample-in - result-out type operation. Therefore, the entire process from sample preparation, metering, reagent incubation, etc. to detection should be performed on a single disposable device (on-chip). In the early days such devices were mainly fabricated using glass or silicon substrates and adapting established fabrication technologies from the electronics and semiconductor industry. More recently, the development focuses on the use of thermoplastic polymers as they allow for low-cost high volume fabrication of disposables. One of the most promising materials for the development of plastic based lab-on-achip systems are cyclic olefin polymers and copolymers (COP/COC) due to their excellent optical properties (high transparency and low autofluorescence) and ease of processing. We present a bioanalytical system for whole blood samples comprising a disposable plastic chip based on TIRF (total internal reflection fluorescence) optical detection. The chips were fabricated by compression moulding of COP and microfluidic channels were structured by hot embossing. These microfluidic structures integrate several sample pretreatment steps. These are the separation of erythrocytes, metering of sample volume using passive valves, and reagent incubation for competitive bioassays. The surface of the following optical detection zone is functionalized with specific capture probes in an array format. The plastic chips comprise dedicated structures for simple and effective coupling of excitation light from low-cost laser diodes. This enables TIRF excitation of fluorescently labeled probes selectively bound to detection spots at the microchannel surface. The fluorescence of these detection arrays is imaged using a simple set-up based on a digital consumer camera. Image processing for spot detection and intensity calculation is accomplished using customized software. Using this combined TIRF excitation and imaging based detection approach allowes for effective suppression of background fluorescence from the sample, multiplexed detection in an array format, as well as internal calibration and background correction.

Sensor and methods of detecting target materials and situations in closed systems

DOEpatents

Mee, David K.; Ripley, Edward B.; Nienstedt, Zachary C.; Nienstedt, Alex W.; Howell, Jr., Layton N.

2018-03-13

Disclosed is a passive, in-situ pressure sensor. The sensor includes a sensing element having a ferromagnetic metal and a tension inducing mechanism coupled to the ferromagnetic metal. The tension inducing mechanism is operable to change a tensile stress upon the ferromagnetic metal based on a change in pressure in the sensing element. Changes in pressure are detected based on changes in the magnetic switching characteristics of the ferromagnetic metal when subjected to an alternating magnetic field caused by the change in the tensile stress. The sensing element is embeddable in a closed system for detecting pressure changes without the need for any penetrations of the system for power or data acquisition by detecting changes in the magnetic switching characteristics of the ferromagnetic metal caused by the tensile stress.

Automatic Detection and Estimation of Unannounced Meals for Multivariable Artificial Pancreas System.

PubMed

Samadi, Sediqeh; Rashid, Mudassir; Turksoy, Kamuran; Feng, Jianyuan; Hajizadeh, Iman; Hobbs, Nicole; Lazaro, Caterina; Sevil, Mert; Littlejohn, Elizabeth; Cinar, Ali

2018-03-01

Automatically attenuating the postprandial rise in the blood glucose concentration without manual meal announcement is a significant challenge for artificial pancreas (AP) systems. In this study, a meal module is proposed to detect the consumption of a meal and to estimate the amount of carbohydrate (CHO) intake. The meals are detected based on qualitative variables describing variation of continuous glucose monitoring (CGM) readings. The CHO content of the meals/snacks is estimated by a fuzzy system using CGM and subcutaneous insulin delivery data. The meal bolus amount is computed according to the patient's insulin to CHO ratio. Integration of the meal module into a multivariable AP system allows revision of estimated CHO based on knowledge about physical activity, sleep, and the risk of hypoglycemia before the final decision for a meal bolus is made. The algorithm is evaluated by using 117 meals/snacks in retrospective data from 11 subjects with type 1 diabetes. Sensitivity, defined as the percentage of correctly detected meals and snacks, is 93.5% for meals and 68.0% for snacks. The percentage of false positives, defined as the proportion of false detections relative to the total number of detected meals and snacks, is 20.8%. Integration of a meal detection module in an AP system is a further step toward an automated AP without manual entries. Detection of a consumed meal/snack and infusion of insulin boluses using an estimate of CHO enables the AP system to automatically prevent postprandial hyperglycemia.

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET

PubMed Central

N. Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks. PMID:27285146

Source detection at 100 meter standoff with a time-encoded imaging system

NASA Astrophysics Data System (ADS)

Brennan, J.; Brubaker, E.; Gerling, M.; Marleau, P.; Monterial, M.; Nowack, A.; Schuster, P.; Sturm, B.; Sweany, M.

2018-01-01

We present the design, characterization, and testing of a laboratory prototype radiological search and localization system. The system, based on time-encoded imaging, uses the attenuation signature of neutrons in time, induced by the geometrical layout and motion of the system. We have demonstrated the ability to detect a ∼ 1mCi252Cf radiological source at 100m standoff with 90% detection efficiency and 10% false positives against background in 12min. This same detection efficiency is met at 15s for a 40m standoff, and 1 . 2s for a 20m standoff.

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.

Automatic quadrature control and measuring system. [using optical coupling circuitry

NASA Technical Reports Server (NTRS)

Hamlet, J. F. (Inventor)

1974-01-01

A quadrature component cancellation and measuring system comprising a detection system for detecting the quadrature component from a primary signal, including reference circuitry to define the phase of the quadrature component for detection is described. A Raysistor optical coupling control device connects an output from the detection system to a circuit driven by a signal based upon the primary signal. Combining circuitry connects the primary signal and the circuit controlled by the Raysistor device to subtract quadrature components. A known current through the optically sensitive element produces a signal defining the magnitude of the quadrature component.

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.

Impact of fiber ring laser configuration on detection capabilities in FBG based sensor systems

NASA Astrophysics Data System (ADS)

Osuch, Tomasz; Kossek, Tomasz; Markowski, Konrad

2014-11-01

In this paper fiber ring lasers (FRL) as interrogation units for distributed fiber Bragg grating (FBG) based sensor networks are studied. In particular, two configurations of the fiber laser with erbium-doped fiber amplifier (EDFA) and semiconductor optical amplifier (SOA) as gain medium were analyzed. In the case of EDFA-based fiber interrogation systems, CW as well as active-mode locking operation were taken into account. The influence of spectral overlapping of FBGs spectra on detection capabilities of examined FRLs are presented. Experimental results show that the SOA-based fiber laser interrogation unit can operate as a multi-parametric sensing system. In turn, using an actively mode-locked fiber ring laser with an EDFA, an electronically switchable FBG based sensing system can be realized.

Microfluidic approaches to malaria detection

PubMed Central

Gascoyne, Peter; Satayavivad, Jutamaad; Ruchirawat, Mathuros

2009-01-01

Microfluidic systems are under development to address a variety of medical problems. Key advantages of micrototal analysis systems based on microfluidic technology are the promise of small size and the integration of sample handling and measurement functions within a single, automated device having low mass-production costs. Here, we review the spectrum of methods currently used to detect malaria, consider their advantages and disadvantages, and discuss their adaptability towards integration into small, automated micro total analysis systems. Molecular amplification methods emerge as leading candidates for chip-based systems because they offer extremely high sensitivity, the ability to recognize malaria species and strain, and they will be adaptable to the detection of new genotypic signatures that will emerge from current genomic-based research of the disease. Current approaches to the development of chip-based molecular amplification are considered with special emphasis on flow-through PCR, and we present for the first time the method of malaria specimen preparation by dielectrophoretic field-flow-fractionation. Although many challenges must be addressed to realize a micrototal analysis system for malaria diagnosis, it is concluded that the potential benefits of the approach are well worth pursuing. PMID:14744562

Detection, discrimination, and real-time tracking of cracks in rotating disks

NASA Astrophysics Data System (ADS)

Haase, Wayne C.; Drumm, Michael J.

2002-06-01

The purpose of this effort was to develop a system* to detect, discriminate and track fatigue cracks in rotating disks. Aimed primarily at jet engines in flight applications, the system also has value for detecting cracks in a spin pit during low cycle fatigue testing, and for monitoring the health of steam turbines and land-based gas turbine engines for maintenance purposes. The results of this effort produced: a physics-based model that describes the change in the center of mass of a rotating disk using damping ratio, initial unbalance and crack size as parameters; the development of a data acquisition and analysis system that can detect and discriminate a crack using a single cycle of data; and initial validation of the model through testing in a spin pit. The development of the physics-based model also pointed to the most likely regimes for crack detection; identified specific powers of (omega) search for in specific regimes; dictated a particular type of data acquisition for crack discrimination; and demonstrated a need for a higher signal-to-noise ratio in the measurement of the basic vibration signal.

A reagent-assisted method in SERS detection of methyl salicylate

NASA Astrophysics Data System (ADS)

Li, Yali; Li, Qianwen; Wang, Yanan; Oh, Joohee; Jin, Sila; Park, Yeonju; Zhou, Tieli; Zhao, Bing; Ruan, Weidong; Jung, Young Mee

2018-04-01

With the explosive application of methyl salicylate (MS) molecules in food and cosmetics, the further detection of MS molecules becomes particularly important. Here we investigated the detection of MS molecules based on surface-enhanced Raman scattering (SERS) in a novel molecule/assistant/metal system constructed with MS, 4,4‧-(hexafluoroisopropylidene) bis (benzoic acid) and Ag nanoparticles (AgNPs). The minimum detection concentration is 10-4 M. To explore the function of assisted reagent, we also referred another system without assistant molecules. The result demonstrates that SERS signals were not acquired, which proves that the assistant molecules are critical for the capture of MS molecules. Two possible mechanisms of MS/assistant/AgNPs system were speculated through two patterns of hydrogen bonds. The linker molecules acted as the role of the bridge between metallic substrates and target molecules through the molecular recognition. This strategy is very beneficial to the expanding of MS detection techniques and other hydrogen bond based coupling detections with SERS.

Development of a computer-aided detection system for lung cancer diagnosis

NASA Astrophysics Data System (ADS)

Suzuki, Hideo; Inaoka, Noriko; Takabatake, Hirotsugu; Mori, Masaki; Sasaoka, Soichi; Natori, Hiroshi; Suzuki, Akira

1992-06-01

This paper describes a modified system for automatic detection of lung nodules by means of chest x ray image processing techniques. The objective of the system is to help radiologists to improve their accuracy in cancer detection. It is known from retrospective studies of chest x- ray images that radiologists fail to detect about 30 percent of lung cancer cases. A computerized method for detecting lung nodules would be very useful for decreasing the proportion of such oversights. Our proposed system consists of five sub-systems, for image input, lung region determination, nodule detection, rule-based false-positive elimination, and statistical false-positive elimination. In an experiment with the modified system, using 30 lung cancer cases and 78 normal control cases, we obtained figures of 73.3 percent and 89.7 percent for the sensitivity and specificity of the system, respectively. The system has been developed to run on the IBM* PS/55* and IBM RISC System/6000* (RS/6000), and we give the processing time for each platform.

Development of systems for detection, early warning, and control of pipeline leakage in drinking water distribution: a case study.

PubMed

Li, Weifeng; Ling, Wencui; Liu, Suoxiang; Zhao, Jing; Liu, Ruiping; Chen, Qiuwen; Qiang, Zhimin; Qu, Jiuhui

2011-01-01

Water leakage in drinking water distribution systems is a serious problem for many cities and a huge challenge for water utilities. An integrated system for the detection, early warning, and control of pipeline leakage has been developed and successfully used to manage the pipeline networks in selected areas of Beijing. A method based on the geographic information system has been proposed to quickly and automatically optimize the layout of the instruments which detect leaks. Methods are also proposed to estimate the probability of each pipe segment leaking (on the basis of historic leakage data), and to assist in locating the leakage points (based on leakage signals). The district metering area (DMA) strategy is used. Guidelines and a flowchart for establishing a DMA to manage the large-scale looped networks in Beijing are proposed. These different functions have been implemented into a central software system to simplify the day-to-day use of the system. In 2007 the system detected 102 non-obvious leakages (i.e., 14.2% of the total detected in Beijing) in the selected areas, which was estimated to save a total volume of 2,385,000 m3 of water. These results indicate the feasibility, efficiency and wider applicability of this system.

Forest Fire Advanced System Technology (FFAST): A Conceptual Design for Detection and Mapping

Treesearch

J. David Nichols; John R. Warren

1987-01-01

The Forest Fire Advanced System Technology (FFAST) project is developing a data system to provide near-real-time forest fire information to fire management at the fire Incident Command Post (ICP). The completed conceptual design defined an integrated forest fire detection and mapping system that is based upon technology available in the 1990's. System component...

Automated high-grade prostate cancer detection and ranking on whole slide images

NASA Astrophysics Data System (ADS)

Huang, Chao-Hui; Racoceanu, Daniel

2017-03-01

Recently, digital pathology (DP) has been largely improved due to the development of computer vision and machine learning. Automated detection of high-grade prostate carcinoma (HG-PCa) is an impactful medical use-case showing the paradigm of collaboration between DP and computer science: given a field of view (FOV) from a whole slide image (WSI), the computer-aided system is able to determine the grade by classifying the FOV. Various approaches have been reported based on this approach. However, there are two reasons supporting us to conduct this work: first, there is still room for improvement in terms of detection accuracy of HG-PCa; second, a clinical practice is more complex than the operation of simple image classification. FOV ranking is also an essential step. E.g., in clinical practice, a pathologist usually evaluates a case based on a few FOVs from the given WSI. Then, makes decision based on the most severe FOV. This important ranking scenario is not yet being well discussed. In this work, we introduce an automated detection and ranking system for PCa based on Gleason pattern discrimination. Our experiments suggested that the proposed system is able to perform high-accuracy detection ( 95:57% +/- 2:1%) and excellent performance of ranking. Hence, the proposed system has a great potential to support the daily tasks in the medical routine of clinical pathology.

Hardware accelerator design for change detection in smart camera

NASA Astrophysics Data System (ADS)

Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Chaudhury, Santanu; Vohra, Anil

2011-10-01

Smart Cameras are important components in Human Computer Interaction. In any remote surveillance scenario, smart cameras have to take intelligent decisions to select frames of significant changes to minimize communication and processing overhead. Among many of the algorithms for change detection, one based on clustering based scheme was proposed for smart camera systems. However, such an algorithm could achieve low frame rate far from real-time requirements on a general purpose processors (like PowerPC) available on FPGAs. This paper proposes the hardware accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board. Resulted frame rate is 30 frames per second for QVGA resolution in gray scale.

Damage Detection Sensor System for Aerospace and Multiple Applications

NASA Technical Reports Server (NTRS)

Williams, M.; Lewis, M.; Gibson, T.; Medelius, P.; Lane, J.

2017-01-01

The damage detection sensory system is an intelligent damage detection ‘skin’ that can be embedded into rigid or flexible structures, providing a lightweight capability for in-situ health monitoring for applications such as spacecraft, expandable or inflatable structures, extravehicular activities (EVA) suits, smart wearables, and other applications where diagnostic impact damage monitoring might be critical. The sensor systems can be customized for detecting location, damage size, and depth, with velocity options and can be designed for particular environments for monitoring of impact or physical damage to a structure. The operation of the sensor detection system is currently based on the use of parallel conductive traces placed on a firm or flexible surface. Several detection layers can be implemented, where alternate layers are arranged in orthogonal direction with respect to the adjacent layers allowing for location and depth calculations. Increased flexibility of the damage detection sensor system designs will also be introduced.

Toward detecting deception in intelligent systems

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Johnson, Gregory, Jr.

2004-08-01

Contemporary decision makers often must choose a course of action using knowledge from several sources. Knowledge may be provided from many diverse sources including electronic sources such as knowledge-based diagnostic or decision support systems or through data mining techniques. As the decision maker becomes more dependent on these electronic information sources, detecting deceptive information from these sources becomes vital to making a correct, or at least more informed, decision. This applies to unintentional disinformation as well as intentional misinformation. Our ongoing research focuses on employing models of deception and deception detection from the fields of psychology and cognitive science to these systems as well as implementing deception detection algorithms for probabilistic intelligent systems. The deception detection algorithms are used to detect, classify and correct attempts at deception. Algorithms for detecting unexpected information rely upon a prediction algorithm from the collaborative filtering domain to predict agent responses in a multi-agent system.

A Wavelet-based Fast Discrimination of Transformer Magnetizing Inrush Current

NASA Astrophysics Data System (ADS)

Kitayama, Masashi

Recently customers who need electricity of higher quality have been installing co-generation facilities. They can avoid voltage sags and other distribution system related disturbances by supplying electricity to important load from their generators. For another example, FRIENDS, highly reliable distribution system using semiconductor switches or storage devices based on power electronics technology, is proposed. These examples illustrates that the request for high reliability in distribution system is increasing. In order to realize these systems, fast relaying algorithms are indispensable. The author proposes a new method of detecting magnetizing inrush current using discrete wavelet transform (DWT). DWT provides the function of detecting discontinuity of current waveform. Inrush current occurs when transformer core becomes saturated. The proposed method detects spikes of DWT components derived from the discontinuity of the current waveform at both the beginning and the end of inrush current. Wavelet thresholding, one of the wavelet-based statistical modeling, was applied to detect the DWT component spikes. The proposed method is verified using experimental data using single-phase transformer and the proposed method is proved to be effective.

Real-time detection of transients in OGLE-IV with application of machine learning

NASA Astrophysics Data System (ADS)

Klencki, Jakub; Wyrzykowski, Łukasz

2016-06-01

The current bottleneck of transient detection in most surveys is the problem of rejecting numerous artifacts from detected candidates. We present a triple-stage hierarchical machine learning system for automated artifact filtering in difference imaging, based on self-organizing maps. The classifier, when tested on the OGLE-IV Transient Detection System, accepts 97% of real transients while removing up to 97.5% of artifacts.

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

PubMed

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

2017-09-27

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

Real Time Corner Detection for Miniaturized Electro-Optical Sensors Onboard Small Unmanned Aerial Systems

PubMed Central

Forlenza, Lidia; Carton, Patrick; Accardo, Domenico; Fasano, Giancarmine; Moccia, Antonio

2012-01-01

This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d’Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed. PMID:22368499

Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions.

PubMed

Li, Zuojin; Li, Shengbo Eben; Li, Renjie; Cheng, Bo; Shi, Jinliang

2017-03-02

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn)featuresfromfixedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: "wake" and "drowsy". The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the "awake" state, and 15.15% false detections of the "drowsy" state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue.

Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions

PubMed Central

Li, Zuojin; Li, Shengbo Eben; Li, Renjie; Cheng, Bo; Shi, Jinliang

2017-01-01

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn) features from fixed sliding windows on real-time steering wheel angles time series. After that, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: “wake” and “drowsy”. The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the “awake” state, and 15.15% false detections of the “drowsy” state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue. PMID:28257094

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

PubMed Central

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-01-01

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

PubMed

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-08-24

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

Lidar-based door and stair detection from a mobile robot

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

Can we estimate the cellular phone RF peak output power with a simple experiment?

NASA Astrophysics Data System (ADS)

Fioreze, Maycon; dos Santos Junior, Sauli; Goncalves Hönnicke, Marcelo

2016-07-01

Cellular phones are becoming increasingly useful tools for students. Since cell phones operate in the microwave bandwidth, they can be used to motivate students to demonstrate and better understand the properties of electromagnetic waves. However, since these waves operate at higher frequencies (L-band, from 800 MHz to 2 GHz) it is not simple to detect them. Usually, expensive real-time high frequency oscilloscopes are required. Indirect measurements are also possible through heat-based and diode-detector-based radio-frequency (RF) power sensors. Another didactic and intuitive way is to explore a simple and inexpensive detection system, based on the interference effect caused in the electronic circuit of TV and PC soundspeakers, and to try to investigate different properties of the cell phones’ RF electromagnetic waves, such as its power and modulated frequency. This manuscript proposes a trial to quantify these measurements, based on a simple Friis equation model and the time constant of the circuit used in the detection system, in order to show it didactically to the students and even allow them also to explore such a simple detection system at home.

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

PubMed

Van Hertem, T; Bahr, C; Schlageter Tello, A; Viazzi, S; Steensels, M; Romanini, C E B; Lokhorst, C; Maltz, E; Halachmi, I; Berckmans, D

2016-09-01

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Characterization of System Status Signals for Multivariate Time Series Discretization Based on Frequency and Amplitude Variation

PubMed Central

2018-01-01

Many fault detection methods have been proposed for monitoring the health of various industrial systems. Characterizing the monitored signals is a prerequisite for selecting an appropriate detection method. However, fault detection methods tend to be decided with user’s subjective knowledge or their familiarity with the method, rather than following a predefined selection rule. This study investigates the performance sensitivity of two detection methods, with respect to status signal characteristics of given systems: abrupt variance, characteristic indicator, discernable frequency, and discernable index. Relation between key characteristics indicators from four different real-world systems and the performance of two fault detection methods using pattern recognition are evaluated. PMID:29316731

[Development of operation patient security detection system].

PubMed

Geng, Shu-Qin; Tao, Ren-Hai; Zhao, Chao; Wei, Qun

2008-11-01

This paper describes a patient security detection system developed with two dimensional bar codes, wireless communication and removal storage technique. Based on the system, nurses and correlative personnel check code wait operation patient to prevent the defaults. The tests show the system is effective. Its objectivity and currency are more scientific and sophisticated than current traditional method in domestic hospital.

An intelligent detecting system for permeability prediction of MBR.

PubMed

Han, Honggui; Zhang, Shuo; Qiao, Junfei; Wang, Xiaoshuang

2018-01-01

The membrane bioreactor (MBR) has been widely used to purify wastewater in wastewater treatment plants. However, a critical difficulty of the MBR is membrane fouling. To reduce membrane fouling, in this work, an intelligent detecting system is developed to evaluate the performance of MBR by predicting the membrane permeability. This intelligent detecting system consists of two main parts. First, a soft computing method, based on the partial least squares method and the recurrent fuzzy neural network, is designed to find the nonlinear relations between the membrane permeability and the other variables. Second, a complete new platform connecting the sensors and the software is built, in order to enable the intelligent detecting system to handle complex algorithms. Finally, the simulation and experimental results demonstrate the reliability and effectiveness of the proposed intelligent detecting system, underlying the potential of this system for the online membrane permeability for detecting membrane fouling of MBR.

Model-Based Anomaly Detection for a Transparent Optical Transmission System

NASA Astrophysics Data System (ADS)

Bengtsson, Thomas; Salamon, Todd; Ho, Tin Kam; White, Christopher A.

In this chapter, we present an approach for anomaly detection at the physical layer of networks where detailed knowledge about the devices and their operations is available. The approach combines physics-based process models with observational data models to characterize the uncertainties and derive the alarm decision rules. We formulate and apply three different methods based on this approach for a well-defined problem in optical network monitoring that features many typical challenges for this methodology. Specifically, we address the problem of monitoring optically transparent transmission systems that use dynamically controlled Raman amplification systems. We use models of amplifier physics together with statistical estimation to derive alarm decision rules and use these rules to automatically discriminate between measurement errors, anomalous losses, and pump failures. Our approach has led to an efficient tool for systematically detecting anomalies in the system behavior of a deployed network, where pro-active measures to address such anomalies are key to preventing unnecessary disturbances to the system's continuous operation.

A Microfluidics-HPLC/Differential Mobility Spectrometer Macromolecular Detection System for Human and Robotic Missions

NASA Technical Reports Server (NTRS)

Coy, S. L.; Killeen, K.; Han, J.; Eiceman, G. A.; Kanik, I.; Kidd, R. D.

2011-01-01

Our goal is to develop a unique, miniaturized, solute analyzer based on microfluidics technology. The analyzer consists of an integrated microfluidics High Performance Liquid Chromatographic chip / Differential Mobility Spectrometer (?HPLCchip/ DMS) detection system

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.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Driver Distraction Using Visual-Based Sensors and Algorithms.

PubMed

Fernández, Alberto; Usamentiaga, Rubén; Carús, Juan Luis; Casado, Rubén

2016-10-28

Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed.

Driver Distraction Using Visual-Based Sensors and Algorithms

PubMed Central

Fernández, Alberto; Usamentiaga, Rubén; Carús, Juan Luis; Casado, Rubén

2016-01-01

Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed. PMID:27801822

Fall Detection System for the Elderly Based on the Classification of Shimmer Sensor Prototype Data

PubMed Central

Ahmed, Moiz; Mehmood, Nadeem; Mehmood, Amir; Rizwan, Kashif

2017-01-01

Objectives Falling in the elderly is considered a major cause of death. In recent years, ambient and wireless sensor platforms have been extensively used in developed countries for the detection of falls in the elderly. However, we believe extra efforts are required to address this issue in developing countries, such as Pakistan, where most deaths due to falls are not even reported. Considering this, in this paper, we propose a fall detection system prototype that s based on the classification on real time shimmer sensor data. Methods We first developed a data set, ‘SMotion’ of certain postures that could lead to falls in the elderly by using a body area network of Shimmer sensors and categorized the items in this data set into age and weight groups. We developed a feature selection and classification system using three classifiers, namely, support vector machine (SVM), K-nearest neighbor (KNN), and neural network (NN). Finally, a prototype was fabricated to generate alerts to caregivers, health experts, or emergency services in case of fall. Results To evaluate the proposed system, SVM, KNN, and NN were used. The results of this study identified KNN as the most accurate classifier with maximum accuracy of 96% for age groups and 93% for weight groups. Conclusions In this paper, a classification-based fall detection system is proposed. For this purpose, the SMotion data set was developed and categorized into two groups (age and weight groups). The proposed fall detection system for the elderly is implemented through a body area sensor network using third-generation sensors. The evaluation results demonstrate the reasonable performance of the proposed fall detection prototype system in the tested scenarios. PMID:28875049

Biosensors for plant pathogen detection.

PubMed

Khater, Mohga; de la Escosura-Muñiz, Alfredo; Merkoçi, Arben

2017-07-15

Infectious plant diseases are caused by pathogenic microorganisms such as fungi, bacteria, viruses, viroids, phytoplasma and nematodes. Worldwide, plant pathogen infections are among main factors limiting crop productivity and increasing economic losses. Plant pathogen detection is important as first step to manage a plant disease in greenhouses, field conditions and at the country boarders. Current immunological techniques used to detect pathogens in plant include enzyme-linked immunosorbent assays (ELISA) and direct tissue blot immunoassays (DTBIA). DNA-based techniques such as polymerase chain reaction (PCR), real time PCR (RT-PCR) and dot blot hybridization have also been proposed for pathogen identification and detection. However these methodologies are time-consuming and require complex instruments, being not suitable for in-situ analysis. Consequently, there is strong interest for developing new biosensing systems for early detection of plant diseases with high sensitivity and specificity at the point-of-care. In this context, we revise here the recent advancement in the development of advantageous biosensing systems for plant pathogen detection based on both antibody and DNA receptors. The use of different nanomaterials such as nanochannels and metallic nanoparticles for the development of innovative and sensitive biosensing systems for the detection of pathogens (i.e. bacteria and viruses) at the point-of-care is also shown. Plastic and paper-based platforms have been used for this purpose, offering cheap and easy-to-use really integrated sensing systems for rapid on-site detection. Beside devices developed at research and development level a brief revision of commercially available kits is also included in this review. Copyright © 2016 Elsevier B.V. All rights reserved.

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

PubMed

Levman, Jacob E D; Gallego-Ortiz, Cristina; Warner, Ellen; Causer, Petrina; Martel, Anne L

2016-02-01

Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.

Development of a β-Lactoglobulin Sensor Based on SPR for Milk Allergens Detection.

PubMed

Ashley, Jon; D'Aurelio, Roberta; Piekarska, Monika; Temblay, Jeff; Pleasants, Mike; Trinh, Linda; Rodgers, Thomas L; Tothill, Ibtisam E

2018-03-27

A sensitive and label-free surface plasmon resonance (SPR) based sensor was developed in this work for the detection of milk allergens. β-lactoglobulin (BLG) protein was used as the biomarker for cow milk detection. This is to be used directly in final rinse samples of cleaning in-place (CIP) systems of food manufacturers. The affinity assay was optimised and characterised before a standard curve was performed in pure buffer conditions, giving a detection limit of 0.164 µg mL -1 as a direct binding assay. The detection limit can be further enhanced through the use of a sandwich assay and amplification with nanomaterials. However, this was not required here, as the detection limit achieved exceeded the required allergen detection levels of 2 µg mL -1 for β-lactoglobulin. The binding affinities of the polyclonal antibody for BLG, expressed by the dissociation constant (K D ), were equal to 2.59 × 10 -9 M. The developed SPR-based sensor offers several advantages in terms of label-free detection, real-time measurements, potential on-line system and superior sensitivity when compared to ELISA-based techniques. The method is novel for this application and could be applied to wider food allergen risk management decision(s) in food manufacturing.

Target Acquisition Performance of a Satellite Based Multiple Access Surveillance System

DOT National Transportation Integrated Search

1975-03-01

A quantitative description of the detection performance of a satellite-based surveillance system is presented. This system is one which has been proposed for CONUS coverage in an advanced air traffic control system. In addition, the computer program ...

Design of indoor temperature and humidity detection system based on single chip microcomputer

NASA Astrophysics Data System (ADS)

Fu, Xiuwei; Fu, Li; Ma, Tianhui

2018-03-01

The indoor temperature and humidity detection system based on STC15F2K60S2 is designed in this paper. The temperature and humidity sensor DHT22 to monitor the indoor temperature and humidity are used, and the temperature and humidity data to the user's handheld device are wirelessly transmitted, when the temperature reaches or exceeds the user set the temperature alarm value, and the system sound and light alarm, to remind the user.

RF signal detection by a tunable optoelectronic oscillator based on a PS-FBG.

PubMed

Shao, Yuchen; Han, Xiuyou; Li, Ming; Zhao, Mingshan

2018-03-15

Low-power radio frequency (RF) signal detection is highly desirable for many applications, ranging from wireless communication to radar systems. A tunable optoelectronic oscillator (OEO) based on a phase-shifted fiber Bragg grating for detecting low-power RF signals is proposed and experimentally demonstrated. When the frequency of the input RF signal is matched with the potential oscillation mode of the OEO, it is detected and amplified. The frequency of the RF signal under detection can be estimated simultaneously by scanning the wavelength of the laser source. The RF signals from 1.5 to 5 GHz as low as -91  dBm are detected with a gain of about 10 dB, and the frequency is estimated with an error of ±100  MHz. The performance of the OEO system for detecting an RF signal with different modulation rates is also investigated.

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.

Development of a Sensitive Luciferase-Based Sandwich ELISA System for the Detection of Human Extracellular Matrix 1 Protein.

PubMed

Li, Ya; Li, Yanqing; Zhao, Junli; Zheng, Xiaojing; Mao, Qinwen; Xia, Haibin

2016-12-01

Enzyme-linked immunosorbent assay (ELISA) has been one of the main methods for detecting an antigen in an aqueous sample for more than four decades. Nowadays, one of the biggest concerns for ELISA is still how to improve the sensitivity of the assay, and the luciferase-luciferin reaction system has been noticed as a new detection method with high sensitivity. In this study, a luciferin-luciferase reaction system was used as the detection method for a sandwich ELISA system. It was shown that this new system led to an increase in the detection sensitivity of at least two times when compared with the traditional horseradish peroxidase (HRP) detection method. Lastly, the serum levels of the human extracellular matrix 1 protein of breast cancer patients were determined by the new system, which were overall similar to the HRP chemiluminescent system. Furthermore, this new luciferase reporter can be implemented into other ELISA systems for the purpose of increasing the assay sensitivity.

A compact and low-cost laser induced fluorescence detector with silicon based photodetector assembly for capillary flow systems.

PubMed

Geng, Xuhui; Shi, Meng; Ning, Haijing; Feng, Chunbo; Guan, Yafeng

2018-05-15

A compact and low-cost laser induced fluorescence (LIF) detector based on confocal structure for capillary flow systems was developed and applied for analysis of Her2 protein on single Hela cells. A low-power and low-cost 450 nm laser diode (LD) instead of a high quality laser was used as excitation light source. A compact optical design together with shortened optical path length improved the optical efficiency and detection sensitivity. A superior silicon based photodetector assembly was used for fluorescence detection instead of a photomultiplier (PMT). The limit of detection (LOD) for fluorescein sodium was 3 × 10 -12 M or 165 fluorescein molecules in detection volume measured on a homemade capillary electroosmotic driven (EOD)-LIF system, which was similar to commercial LIFs. Compared to commercial LIFs, the whole volume of our LIF was reduced to 1/2-1/3, and the cost was less than 1/3 of them. Copyright © 2018 Elsevier B.V. All rights reserved.

A study on new method of noninvasive esophageal venous pressure measurement based on the airflow and laser detection technology.

PubMed

Hu, Chenghuan; Huang, Feizhou; Zhang, Rui; Zhu, Shaihong; Nie, Wanpin; Liu, Xunyang; Liu, Yinglong; Li, Peng

2015-01-01

Using optics combined with automatic control and computer real-time image detection technology, a novel noninvasive method of noncontact pressure manometry was developed based on the airflow and laser detection technology in this study. The new esophageal venous pressure measurement system was tested in-vitro experiments. A stable and adjustable pulse stream was produced from a self-developed pump and a laser emitting apparatus could generate optical signals which can be captured by image acquisition and analysis system program. A synchronization system simultaneous measured the changes of air pressure and the deformation of the vein wall to capture the vascular deformation while simultaneously record the current pressure value. The results of this study indicated that the pressure values tested by the new method have good correlation with the actual pressure value in animal experiments. The new method of noninvasive pressure measurement based on the airflow and laser detection technology is accurate, feasible, repeatable and has a good application prospects.

Continuous, Real-Time Monitoring of Cocaine in Undiluted Blood Serum via a Microfluidic, Electrochemical Aptamer-Based Sensor

PubMed Central

Swensen, James S.; Xiao, Yi; Ferguson, Brian S.; Lubin, Arica A.; Lai, Rebecca Y.; Heeger, Alan J.; Plaxco, Kevin W.; Soh, H. Tom.

2009-01-01

The development of a biosensor system capable of continuous, real-time measurement of small-molecule analytes directly in complex, unprocessed aqueous samples has been a significant challenge, and successful implementation has been achieved for only a limited number of targets. Towards a general solution to this problem, we report here the Microfluidic Electrochemical Aptamer-based Sensor (MECAS) chip wherein we integrate target-specific DNA aptamers that fold, and thus generate an electrochemical signal, in response to the analyte with a microfluidic detection system. As a model, we demonstrate the continuous, real-time (~1 minute time resolution) detection of the small molecule drug cocaine at near physiological, low micromolar concentrations directly in undiluted, otherwise unmodified blood serum. We believe our approach of integrating folding-based electrochemical sensors with miniaturized detection systems may lay the ground work for the real-time, point-of-care detection of a wide variety of molecular targets. PMID:19271708

Detection of Kaposi's Sarcoma Associated Herpesvirus Nucleic Acids Using a Smartphone Accessory

PubMed Central

Mancuso, Matthew; Cesarman, Ethel; Erickson, David

2014-01-01

Kaposi's sarcoma (KS) is an infectious cancer occurring in immune-compromised patients, caused by Kaposi's sarcoma associated herpesvirus (KSHV). Our vision is to simplify the process of KS diagnosis through the creation of a smartphone based point-of-care system capable of yielding an actionable diagnostic readout starting from a raw biopsy sample. In this work we develop the sensing mechanism for the overall system, a smartphone accessory capable of detecting KSHV nucleic acids. The accessory reads out microfluidic chips filled with a colorimetric nanoparticle assay targeted at KSHV. We calculate that our final device can read out gold nanoparticle solutions with an accuracy of .05 OD, and we demonstrate that it can detect DNA sequences from KSHV down to 1 nM. We believe that through integration with our previously developed components, a smartphone based system like the one studied here can provide accurate detection information, as well as a simple platform for field based clinical diagnosis and research. PMID:25117534

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.

Novel Noninvasive Brain Disease Detection System Using a Facial Image Sensor

PubMed Central

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

Brain disease including any conditions or disabilities that affect the brain is fast becoming a leading cause of death. The traditional diagnostic methods of brain disease are time-consuming, inconvenient and non-patient friendly. As more and more individuals undergo examinations to determine if they suffer from any form of brain disease, developing noninvasive, efficient, and patient friendly detection systems will be beneficial. Therefore, in this paper, we propose a novel noninvasive brain disease detection system based on the analysis of facial colors. The system consists of four components. A facial image is first captured through a specialized sensor, where four facial key blocks are next located automatically from the various facial regions. Color features are extracted from each block to form a feature vector for classification via the Probabilistic Collaborative based Classifier. To thoroughly test the system and its performance, seven facial key block combinations were experimented. The best result was achieved using the second facial key block, where it showed that the Probabilistic Collaborative based Classifier is the most suitable. The overall performance of the proposed system achieves an accuracy −95%, a sensitivity −94.33%, a specificity −95.67%, and an average processing time (for one sample) of <1 min at brain disease detection. PMID:29292716

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems.

PubMed

Favazza, Christopher P; Fetterly, Kenneth A; Hangiandreou, Nicholas J; Leng, Shuai; Schueler, Beth A

2015-01-01

Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks.

Automatic non-proliferative diabetic retinopathy screening system based on color fundus image.

PubMed

Xiao, Zhitao; Zhang, Xinpeng; Geng, Lei; Zhang, Fang; Wu, Jun; Tong, Jun; Ogunbona, Philip O; Shan, Chunyan

2017-10-26

Non-proliferative diabetic retinopathy is the early stage of diabetic retinopathy. Automatic detection of non-proliferative diabetic retinopathy is significant for clinical diagnosis, early screening and course progression of patients. This paper introduces the design and implementation of an automatic system for screening non-proliferative diabetic retinopathy based on color fundus images. Firstly, the fundus structures, including blood vessels, optic disc and macula, are extracted and located, respectively. In particular, a new optic disc localization method using parabolic fitting is proposed based on the physiological structure characteristics of optic disc and blood vessels. Then, early lesions, such as microaneurysms, hemorrhages and hard exudates, are detected based on their respective characteristics. An equivalent optical model simulating human eyes is designed based on the anatomical structure of retina. Main structures and early lesions are reconstructed in the 3D space for better visualization. Finally, the severity of each image is evaluated based on the international criteria of diabetic retinopathy. The system has been tested on public databases and images from hospitals. Experimental results demonstrate that the proposed system achieves high accuracy for main structures and early lesions detection. The results of severity classification for non-proliferative diabetic retinopathy are also accurate and suitable. Our system can assist ophthalmologists for clinical diagnosis, automatic screening and course progression of patients.

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

PubMed

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

2014-05-01

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

Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

NASA Technical Reports Server (NTRS)

Gliese, U.; Avanov, L. A.; Barrie, A. C.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Gershman, D. J.; Dorelli, J. C.;

A Thermal Expert System (TEXSYS) development overview - AI-based control of a Space Station prototype thermal bus

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hack, E. C.

1990-01-01

A knowledge-based control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external thermal control system (TCS) is discussed in this paper. The Thermal Expert System (TEXSYS) has been demonstrated in recent tests to be capable of both fault anticipation and detection and real-time control of the thermal bus. Performance requirements were achieved by using a symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous during software development and testing. One representative example is given from on-line TCS tests of TEXSYS. The integration and testing of TEXSYS with a live TCS testbed provides some insight on the use of formal software design, development and documentation methodologies to qualify knowledge-based systems for on-line or flight applications.

A PDMS-based cylindrical hybrid lens for enhanced fluorescence detection in microfluidic systems.

PubMed

Lin, Bor-Shyh; Yang, Yu-Ching; Ho, Chong-Yi; Yang, Han-Yu; Wang, Hsiang-Yu

2014-02-13

Microfluidic systems based on fluorescence detection have been developed and applied for many biological and chemical applications. Because of the tiny amount of sample in the system; the induced fluorescence can be weak. Therefore, most microfluidic systems deploy multiple optical components or sophisticated equipment to enhance the efficiency of fluorescence detection. However, these strategies encounter common issues of complex manufacturing processes and high costs. In this study; a miniature, cylindrical and hybrid lens made of polydimethylsiloxane (PDMS) to improve the fluorescence detection in microfluidic systems is proposed. The hybrid lens integrates a laser focusing lens and a fluorescence collecting lens to achieve dual functions and simplify optical setup. Moreover, PDMS has advantages of low-cost and straightforward fabrication compared with conventional optical components. The performance of the proposed lens is first examined with two fluorescent dyes and the results show that the lens provides satisfactory enhancement for fluorescence detection of Rhodamine 6G and Nile Red. The overall increments in collected fluorescence signal and detection sensitivity are more than 220% of those without lens, and the detection limits of Rhodamine 6G and Nile red are lowered to 0.01 μg/mL and 0.05 μg/mL, respectively. The hybrid lens is further applied to the detection of Nile red-labeled Chlorella vulgaris cells and it increases both signal intensity and detection sensitivity by more than 520%. The proposed hybrid lens also dramatically reduces the variation in detected signal caused by the deviation in incident angle of excitation light.

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

PubMed Central

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

2018-01-01

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

Analysis of a SCADA System Anomaly Detection Model Based on Information Entropy

DTIC Science & Technology

2014-03-27

20 Intrusion Detection...alarms ( Rem ). ............................................................................................................. 86 Figure 25. TP% for...literature concerning the focus areas of this research. The focus areas include SCADA vulnerabilities, information theory, and intrusion detection

Active Neutron-Based Interrogation System with D-D Neutron Source for Detection of Special Nuclear Materials

NASA Astrophysics Data System (ADS)

Takahashi, Y.; Misawa, T.; Yagi, T.; Pyeon, C. H.; Kimura, M.; Masuda, K.; Ohgaki, H.

2015-10-01

The detection of special nuclear materials (SNM) is an important issue for nuclear security. The interrogation systems used in a sea port and an airport are developed in the world. The active neutron-based interrogation system is the one of the candidates. We are developing the active neutron-based interrogation system with a D-D fusion neutron source for the nuclear security application. The D-D neutron source is a compact discharge-type fusion neutron source called IEC (Inertial-Electrostatic Confinement fusion) device which provides 2.45 MeV neutrons. The nuclear materials emit the highenergy neutrons by fission reaction. High-energy neutrons with energies over 2.45 MeV amount to 30% of all the fission neutrons. By using the D-D neutron source, the detection of SNMs is considered to be possible with the attention of fast neutrons if there is over 2.45 MeV. Ideally, neutrons at En>2.45 MeV do not exist if there is no nuclear materials. The detection of fission neutrons over 2.45 MeV are hopeful prospect for the detection of SNM with a high S/N ratio. In the future, the experiments combined with nuclear materials and a D-D neutron source will be conducted. Furthermore, the interrogation system will be numerically investigated by using nuclear materials, a D-D neutron source, and a steel container.

Automated multiple target detection and tracking in UAV videos

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

A real-time surface inspection system for precision steel balls based on machine vision

NASA Astrophysics Data System (ADS)

Chen, Yi-Ji; Tsai, Jhy-Cherng; Hsu, Ya-Chen

2016-07-01

Precision steel balls are one of the most fundament components for motion and power transmission parts and they are widely used in industrial machinery and the automotive industry. As precision balls are crucial for the quality of these products, there is an urgent need to develop a fast and robust system for inspecting defects of precision steel balls. In this paper, a real-time system for inspecting surface defects of precision steel balls is developed based on machine vision. The developed system integrates a dual-lighting system, an unfolding mechanism and inspection algorithms for real-time signal processing and defect detection. The developed system is tested under feeding speeds of 4 pcs s-1 with a detection rate of 99.94% and an error rate of 0.10%. The minimum detectable surface flaw area is 0.01 mm2, which meets the requirement for inspecting ISO grade 100 precision steel balls.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

A Web-Based Multidrug-Resistant Organisms Surveillance and Outbreak Detection System with Rule-Based Classification and Clustering

PubMed Central

Tseng, Yi-Ju; Wu, Jung-Hsuan; Ping, Xiao-Ou; Lin, Hui-Chi; Chen, Ying-Yu; Shang, Rung-Ji; Chen, Ming-Yuan; Lai, Feipei

2012-01-01

Background The emergence and spread of multidrug-resistant organisms (MDROs) are causing a global crisis. Combating antimicrobial resistance requires prevention of transmission of resistant organisms and improved use of antimicrobials. Objectives To develop a Web-based information system for automatic integration, analysis, and interpretation of the antimicrobial susceptibility of all clinical isolates that incorporates rule-based classification and cluster analysis of MDROs and implements control chart analysis to facilitate outbreak detection. Methods Electronic microbiological data from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of MDROs. The numbers of organisms, patients, and incident patients in each MDRO pattern were presented graphically to describe spatial and time information in a Web-based user interface. Hierarchical clustering with 7 upper control limits (UCL) was used to detect suspicious outbreaks. The system’s performance in outbreak detection was evaluated based on vancomycin-resistant enterococcal outbreaks determined by a hospital-wide prospective active surveillance database compiled by infection control personnel. Results The optimal UCL for MDRO outbreak detection was the upper 90% confidence interval (CI) using germ criterion with clustering (area under ROC curve (AUC) 0.93, 95% CI 0.91 to 0.95), upper 85% CI using patient criterion (AUC 0.87, 95% CI 0.80 to 0.93), and one standard deviation using incident patient criterion (AUC 0.84, 95% CI 0.75 to 0.92). The performance indicators of each UCL were statistically significantly higher with clustering than those without clustering in germ criterion (P < .001), patient criterion (P = .04), and incident patient criterion (P < .001). Conclusion This system automatically identifies MDROs and accurately detects suspicious outbreaks of MDROs based on the antimicrobial susceptibility of all clinical isolates. PMID:23195868

Integration of bridge damage detection concepts and components, volume I : strain-based damage detection.

DOT National Transportation Integrated Search

2013-10-01

In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, a...

Integration of bridge damage detection concepts and components, volume II : acceleration-based damage detection.

DOT National Transportation Integrated Search

2013-10-01

In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, a...

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Franzl, Richard; Walker, Mark; Kapadia, Ravi; Venkatesh, Meera; Schmalzel, John

2010-01-01

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Structural damage detection based on stochastic subspace identification and statistical pattern recognition: I. Theory

NASA Astrophysics Data System (ADS)

Ren, W. X.; Lin, Y. Q.; Fang, S. E.

2011-11-01

One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.

Bulk-wave ultrasonic propagation imagers

NASA Astrophysics Data System (ADS)

Abbas, Syed Haider; Lee, Jung-Ryul

2018-03-01

Laser-based ultrasound systems are described that utilize the ultrasonic bulk-wave sensing to detect the damages and flaws in the aerospace structures. These systems apply pulse-echo or through transmission methods to detect longitudinal through-the-thickness bulk-waves. These thermoelastic waves are generated using Q-switched laser and non-contact sensing is performed using a laser Doppler vibrometer (LDV). Laser-based raster scanning is performed by either twoaxis translation stage for linear-scanning or galvanometer-based laser mirror scanner for angular-scanning. In all ultrasonic propagation imagers, the ultrasonic data is captured and processed in real-time and the ultrasonic propagation can be visualized during scanning. The scanning speed can go up to 1.8 kHz for two-axis linear translation stage based B-UPIs and 10 kHz for galvanometer-based laser mirror scanners. In contrast with the other available ultrasound systems, these systems have the advantage of high-speed, non-contact, real-time, and non-destructive inspection. In this paper, the description of all bulk-wave ultrasonic imagers (B-UPIs) are presented and their advantages are discussed. Experiments are performed with these system on various structures to proof the integrity of their results. The C-scan results produced from non-dispersive, through-the-thickness, bulk-wave detection show good agreement in detection of structural variances and damage location in all inspected structures. These results show that bulk-wave UPIs can be used for in-situ NDE of engineering structures.

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

PubMed

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

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

Probabilistic evaluation of on-line checks in fault-tolerant multiprocessor systems

NASA Technical Reports Server (NTRS)

Nair, V. S. S.; Hoskote, Yatin V.; Abraham, Jacob A.

1992-01-01

The analysis of fault-tolerant multiprocessor systems that use concurrent error detection (CED) schemes is much more difficult than the analysis of conventional fault-tolerant architectures. Various analytical techniques have been proposed to evaluate CED schemes deterministically. However, these approaches are based on worst-case assumptions related to the failure of system components. Often, the evaluation results do not reflect the actual fault tolerance capabilities of the system. A probabilistic approach to evaluate the fault detecting and locating capabilities of on-line checks in a system is developed. The various probabilities associated with the checking schemes are identified and used in the framework of the matrix-based model. Based on these probabilistic matrices, estimates for the fault tolerance capabilities of various systems are derived analytically.

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

NASA Astrophysics Data System (ADS)

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

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

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.

Standoff laser-based spectroscopy for explosives detection

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2007-10-01

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 activity is based on a combination of laser-based spectroscopic methods with orthogonal capabilities. Our technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We has applied optical techniques including gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Single-trial lie detection using a combined fNIRS-polygraph system

PubMed Central

Bhutta, M. Raheel; Hong, Melissa J.; Kim, Yun-Hee; Hong, Keum-Shik

2015-01-01

Deception is a human behavior that many people experience in daily life. It involves complex neuronal activities in addition to several physiological changes in the body. A polygraph, which can measure some of the physiological responses from the body, has been widely employed in lie-detection. Many researchers, however, believe that lie detection can become more precise if the neuronal changes that occur in the process of deception can be isolated and measured. In this study, we combine both measures (i.e., physiological and neuronal changes) for enhanced lie-detection. Specifically, to investigate the deception-related hemodynamic response, functional near-infrared spectroscopy (fNIRS) is applied at the prefrontal cortex besides a commercially available polygraph system. A mock crime scenario with a single-trial stimulus is set up as a deception protocol. The acquired data are classified into “true” and “lie” classes based on the fNIRS-based hemoglobin-concentration changes and polygraph-based physiological signal changes. Linear discriminant analysis is utilized as a classifier. The results indicate that the combined fNIRS-polygraph system delivers much higher classification accuracy than that of a singular system. This study demonstrates a plausible solution toward single-trial lie-detection by combining fNIRS and the polygraph. PMID:26082733

On detection and visualization techniques for cyber security situation awareness

NASA Astrophysics Data System (ADS)

Yu, Wei; Wei, Shixiao; Shen, Dan; Blowers, Misty; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe; Zhang, Hanlin; Lu, Chao

2013-05-01

Networking technologies are exponentially increasing to meet worldwide communication requirements. The rapid growth of network technologies and perversity of communications pose serious security issues. In this paper, we aim to developing an integrated network defense system with situation awareness capabilities to present the useful information for human analysts. In particular, we implement a prototypical system that includes both the distributed passive and active network sensors and traffic visualization features, such as 1D, 2D and 3D based network traffic displays. To effectively detect attacks, we also implement algorithms to transform real-world data of IP addresses into images and study the pattern of attacks and use both the discrete wavelet transform (DWT) based scheme and the statistical based scheme to detect attacks. Through an extensive simulation study, our data validate the effectiveness of our implemented defense system.

340 nm pulsed UV LED system for europium-based time-resolved fluorescence detection of immunoassays.

PubMed

Rodenko, Olga; Fodgaard, Henrik; Tidemand-Lichtenberg, Peter; Petersen, Paul Michael; Pedersen, Christian

2016-09-19

We report on the design, development and investigation of an optical system based on UV light emitting diode (LED) excitation at 340 nm for time-resolved fluorescence detection of immunoassays. The system was tested to measure cardiac marker Troponin I with a concentration of 200 ng/L in immunoassay. The signal-to-noise ratio was comparable to state-of-the-art Xenon flash lamp based unit with equal excitation energy and without overdriving the LED. We performed a comparative study of the flash lamp and the LED based system and discussed temporal, spatial, and spectral features of the LED excitation for time-resolved fluorimetry. Optimization of the suggested key parameters of the LED promises significant increase of the signal-to-noise ratio and hence of the sensitivity of immunoassay systems.

An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles.

PubMed

González, Iván; Fontecha, Jesús; Hervás, Ramón; Bravo, José

2015-07-09

A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

Electrochemical detection for microscale analytical systems: a review.

PubMed

Wang, Joseph

2002-02-11

As the field of chip-based microscale systems continues its rapid growth, there are urgent needs for developing compatible detection modes. Electrochemistry detection offers considerable promise for such microfluidic systems, with features that include remarkable sensitivity, inherent miniaturization and portability, independence of optical path length or sample turbidity, low cost, low-power requirements and high compatibility with advanced micromachining and microfabrication technologies. This paper highlights recent advances, directions and key strategies in controlled-potential electrochemical detectors for miniaturized analytical systems. Subjects covered include the design and integration of the electrochemical detection system, its requirements and operational principles, common electrode materials, derivatization reactions, electrical-field decouplers, typical applications and future prospects. It is expected that electrochemical detection will become a powerful tool for microscale analytical systems and will facilitate the creation of truly portable (and possibly disposable) devices.

[Design of Oxygen Saturation, Heart Rate, Respiration Rate Detection System Based on Smartphone of Android Operating System].

PubMed

Zhu, Mingshan; Zeng, Bixin

2015-03-01

In this paper, we designed an oxygen saturation, heart rate, respiration rate monitoring system based on smartphone of android operating system, physiological signal acquired by MSP430 microcontroller and transmitted by Bluetooth module.

Smartphone Cortex Controlled Real-Time Image Processing and Reprocessing for Concentration Independent LED Induced Fluorescence Detection in Capillary Electrophoresis.

PubMed

Szarka, Mate; Guttman, Andras

2017-10-17

We present the application of a smartphone anatomy based technology in the field of liquid phase bioseparations, particularly in capillary electrophoresis. A simple capillary electrophoresis system was built with LED induced fluorescence detection and a credit card sized minicomputer to prove the concept of real time fluorescent imaging (zone adjustable time-lapse fluorescence image processor) and separation controller. The system was evaluated by analyzing under- and overloaded aminopyrenetrisulfonate (APTS)-labeled oligosaccharide samples. The open source software based image processing tool allowed undistorted signal modulation (reprocessing) if the signal was inappropriate for the actual detection system settings (too low or too high). The novel smart detection tool for fluorescently labeled biomolecules greatly expands dynamic range and enables retrospective correction for injections with unsuitable signal levels without the necessity to repeat the analysis.

Detecting insider activity using enhanced directory virtualization.

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

Shin, Dongwan; Claycomb, William R.

2010-07-01

Insider threats often target authentication and access control systems, which are frequently based on directory services. Detecting these threats is challenging, because malicious users with the technical ability to modify these structures often have sufficient knowledge and expertise to conceal unauthorized activity. The use of directory virtualization to monitor various systems across an enterprise can be a valuable tool for detecting insider activity. The addition of a policy engine to directory virtualization services enhances monitoring capabilities by allowing greater flexibility in analyzing changes for malicious intent. The resulting architecture is a system-based approach, where the relationships and dependencies between datamore » sources and directory services are used to detect an insider threat, rather than simply relying on point solutions. This paper presents such an architecture in detail, including a description of implementation results.« less

Two New Real-Time PCR-based Surveillance Systems for “Candidatus Liberibacter” Species Detection

USDA-ARS?s Scientific Manuscript database

We developed two novel surveillance systems for “Candidatus Liberibacter” (CL) species detection and identification. The first system is called “single tube dual primer Taq-Man PCR” (STDP). The procedure involves two sequential rounds of PCR using the CL asiaticus species-specific outer and inner pr...

SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

NASA Astrophysics Data System (ADS)

Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

2010-12-01

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

Phase synchronization based on a Dual-Tree Complex Wavelet Transform

NASA Astrophysics Data System (ADS)

Ferreira, Maria Teodora; Domingues, Margarete Oliveira; Macau, Elbert E. N.

2016-11-01

In this work, we show the applicability of our Discrete Complex Wavelet Approach (DCWA) to verify the phenomenon of phase synchronization transition in two coupled chaotic Lorenz systems. DCWA is based on the phase assignment from complex wavelet coefficients obtained by using a Dual-Tree Complex Wavelet Transform (DT-CWT). We analyzed two coupled chaotic Lorenz systems, aiming to detect the transition from non-phase synchronization to phase synchronization. In addition, we check how good is the method in detecting periods of 2π phase-slips. In all experiments, DCWA is compared with classical phase detection methods such as the ones based on arctangent and Hilbert transform showing a much better performance.

[Quartz-enhanced photoacoustic spectroscopy trace gas detection system based on the Fabry-Perot demodulation].

PubMed

Lin, Cheng; Zhu, Yong; Wei, Wei; Zhang, Jie; Tian, Li; Xu, Zu-Wen

2013-05-01

An all-optical quartz-enhanced photoacoustic spectroscopy system, based on the F-P demodulation, for trace gas detection in the open environment was proposed. In quartz-enhanced photoacoustic spectroscopy (QEPAS), an optical fiber Fabry-Perot method was used to replace the conventional electronic demodulation method. The photoacoustic signal was obtained by demodulating the variation of the Fabry-Perot cavity between the quartz tuning fork side and the fiber face. An experimental system was setup. The experiment for detection of water vapour in the open environment was carried on. A normalized noise equivalent absorption coefficient of 2.80 x 10(-7) cm(-1) x W x Hz(-1/2) was achieved. The result demonstrated that the sensitivity of the all-optical quartz-enhanced photoacoustic spectroscopy system is about 2.6 times higher than that of the conventional QEPAS system. The all-optical quartz-enhanced photoacoustic spectroscopy system is immune to electromagnetic interference, safe in flammable and explosive gas detection, suitable for high temperature and high humidity environments and realizable for long distance, multi-point and network sensing.

Performance enhanced piezoelectric-based crack detection system for high temperature I-beam SHM

NASA Astrophysics Data System (ADS)

Zhang, Chen; Zhang, Haifeng

2017-04-01

This paper proposes an innovative sensing system for high temperature (up to 150°C) I-beam crack detection. The proposed system is based on the piezoelectric effect and laser sensing mechanisms, which is proved to be effective at high temperature environment (up to 150°C). Different from other high temperature SHM approaches, the proposed sensing system is employing a piezoelectric disk as an actuator and a laser vibrometer as a sensor for remote detection. Lab tests are carried out and the vibrational properties are studied to characterize the relationship between crack depth and sensor responses by analyzing the RMS of sensor responses. Instead of utilizing a pair of piezoelectric actuator and sensor, using the laser vibrometer will enable 1) a more flexible detection, which will not be limited to specific area or dimension, 2) wireless sensing, which lowers the risk of operating at high temperature/harsh environment. The proposed sensing system can be applied to engineering structures such as in nuclear power plant reactor vessel and heat pipe structures/systems.

Colorimetric detection of melamine in milk by using gold nanoparticles-based LSPR via optical fibers

PubMed Central

Chang, Keke; Wang, Shun; Zhang, Hao; Guo, Qingqian; Hu, Xinran; Lin, Zhili; Sun, Haifeng; Jiang, Min

2017-01-01

A biosensing system with optical fibers is proposed for the colorimetric detection of melamine in liquid milk samples by using the localized surface plasmon resonance (LSPR) of unmodified gold nanoparticles (AuNPs). The biosensing system consists of a broadband light source that covers the spectral range from 200 nm to 1700 nm, an optical attenuator, three types of 600 μm premium optical fibers with SMA905 connectors and a miniature spectrometer with a linear charge coupled device (CCD) array. The biosensing system with optical fibers is low-cost, simple and is well-proven for the detection of melamine. Its working principle is based on the color changes of AuNPs solution from wine-red to blue due to the inter-particle coupling effect that causes the shifts of wavelength and absorbance in LSPR band after the to-be-measured melamine samples were added. Under the optimized conditions, the detection response of the LSPR biosensing system was found to be linear in melamine detection in the concentration range from 0μM to 0.9 μM with a correlation coefficient (R2) 0.99 and a detection limit 33 nM. The experimental results obtained from the established LSPR biosensing system in the actual detection of melamine concentration in liquid milk samples show that this technique is highly specific and sensitive and would have a huge application prospects. PMID:28475597

The INTELSAT VI SSTDMA network diagnostic system

NASA Astrophysics Data System (ADS)

Tamboli, Satish P.; Zhu, Xiaobo; Wilkins, Kim N.; Gupta, Ramesh K.

The system-level design of an expert-system-based, near-real-time diagnostic system for INTELSAT VI satellite-switched time-division multiple access (SSTDMA) network is described. The challenges of INTELSAT VI diagnostics are discussed, along with alternative approaches for network diagnostics and the rationale for choosing a method based on burst unique-word detection. The focal point of the diagnostic system is the diagnostic processor, which resides in the central control and monitoring facility known as the INTELSAT Operations Center TDMA Facility (IOCTF). As real-time information such as burst unique-word detection data, reference terminal status data, and satellite telemetry alarm data are received at the IOCTF, the diagnostic processor continuously monitors the data streams. When a burst status change is detected, a 'snapshot' of the real-time data is forwarded to the expert system. Receipt of the change causes a set of rules to be invoked which associate the traffic pattern with a set of probable causes. A user-friendly interface allows a graphical view of the burst time plan and provides the ability to browse through the knowledge bases.

Assessing the performance of a motion tracking system based on optical joint transform correlation

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

2015-08-01

We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

Autoblocker: a system for detecting and blocking of network scanning based on analysis of netflow data

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

Bobyshev, A.; Lamore, D.; Demar, P.

2004-12-01

In a large campus network, such at Fermilab, with tens of thousands of nodes, scanning initiated from either outside of or within the campus network raises security concerns. This scanning may have very serious impact on network performance, and even disrupt normal operation of many services. In this paper we introduce a system for detecting and automatic blocking excessive traffic of different kinds of scanning, DoS attacks, virus infected computers. The system, called AutoBlocker, is a distributed computing system based on quasi-real time analysis of network flow data collected from the border router and core switches. AutoBlocker also has anmore » interface to accept alerts from IDS systems (e.g. BRO, SNORT) that are based on other technologies. The system has multiple configurable alert levels for the detection of anomalous behavior and configurable trigger criteria for automated blocking of scans at the core or border routers. It has been in use at Fermilab for about 2 years, and has become a very valuable tool to curtail scan activity within the Fermilab campus network.« less

Estimation of Temporal Gait Parameters Using a Wearable Microphone-Sensor-Based System

PubMed Central

Wang, Cheng; Wang, Xiangdong; Long, Zhou; Yuan, Jing; Qian, Yueliang; Li, Jintao

2016-01-01

Most existing wearable gait analysis methods focus on the analysis of data obtained from inertial sensors. This paper proposes a novel, low-cost, wireless and wearable gait analysis system which uses microphone sensors to collect footstep sound signals during walking. This is the first time a microphone sensor is used as a wearable gait analysis device as far as we know. Based on this system, a gait analysis algorithm for estimating the temporal parameters of gait is presented. The algorithm fully uses the fusion of two feet footstep sound signals and includes three stages: footstep detection, heel-strike event and toe-on event detection, and calculation of gait temporal parameters. Experimental results show that with a total of 240 data sequences and 1732 steps collected using three different gait data collection strategies from 15 healthy subjects, the proposed system achieves an average 0.955 F1-measure for footstep detection, an average 94.52% accuracy rate for heel-strike detection and 94.25% accuracy rate for toe-on detection. Using these detection results, nine temporal related gait parameters are calculated and these parameters are consistent with their corresponding normal gait temporal parameters and labeled data calculation results. The results verify the effectiveness of our proposed system and algorithm for temporal gait parameter estimation. PMID:27999321

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

PubMed Central

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

2016-01-01

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

High-throughput living cell-based optical biosensor for detection of bacterial lipopolysaccharide (LPS) using a red fluorescent protein reporter system.

PubMed

Jiang, Hui; Jiang, Donglei; Shao, Jingdong; Sun, Xiulan; Wang, Jiasheng

2016-11-14

Due to the high toxicity of bacterial lipopolysaccharide (LPS), resulting in sepsis and septic shock, two major causes of death worldwide, significant effort is directed toward the development of specific trace-level LPS detection systems. Here, we report sensitive, user-friendly, high-throughput LPS detection in a 96-well microplate using a transcriptional biosensor system, based on 293/hTLR4A-MD2-CD14 cells that are transformed by a red fluorescent protein (mCherry) gene under the transcriptional control of an NF-κB response element. The recognition of LPS activates the biosensor cell, TLR4, and the co-receptor-induced NF-κB signaling pathway, which results in the expression of mCherry fluorescent protein. The novel cell-based biosensor detects LPS with specificity at low concentration. The cell-based biosensor was evaluated by testing LPS isolated from 14 bacteria. Of the tested bacteria, 13 isolated Enterobacteraceous LPSs with hexa-acylated structures were found to increase red fluorescence and one penta-acylated LPS from Pseudomonadaceae appeared less potent. The proposed biosensor has potential for use in the LPS detection in foodstuff and biological products, as well as bacteria identification, assisting the control of foodborne diseases.

Idaho National Laboratory Supervisory Control and Data Acquisition Intrusion Detection System (SCADA IDS)

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

Jared Verba; Michael Milvich

2008-05-01

Current Intrusion Detection System (IDS) technology is not suited to be widely deployed inside a Supervisory, Control and Data Acquisition (SCADA) environment. Anomaly- and signature-based IDS technologies have developed methods to cover information technology-based networks activity and protocols effectively. However, these IDS technologies do not include the fine protocol granularity required to ensure network security inside an environment with weak protocols lacking authentication and encryption. By implementing a more specific and more intelligent packet inspection mechanism, tailored traffic flow analysis, and unique packet tampering detection, IDS technology developed specifically for SCADA environments can be deployed with confidence in detecting maliciousmore » activity.« less

Colorimetric test-systems for creatinine detection based on composite molecularly imprinted polymer membranes.

PubMed

Sergeyeva, T A; Gorbach, L A; Piletska, E V; Piletsky, S A; Brovko, O O; Honcharova, L A; Lutsyk, O D; Sergeeva, L M; Zinchenko, O A; El'skaya, A V

2013-04-03

An easy-to-use colorimetric test-system for the efficient detection of creatinine in aqueous samples was developed. The test-system is based on composite molecularly imprinted polymer (MIP) membranes with artificial receptor sites capable of creatinine recognition. A thin MIP layer was created on the surface of microfiltration polyvinylidene fluoride (PVDF) membranes using method of photo-initiated grafting polymerization. The MIP layer was obtained by co-polymerization of a functional monomer (e.g. 2-acrylamido-2-methyl-1-propanesulfonic acid, itaconic acid or methacrylic acid) with N, N'-methylenebisacrylamide as a cross-linker. The choice of the functional monomer was based on the results of computational modeling. The creatinine-selective composite MIP membranes were used for measuring creatinine in aqueous samples. Creatinine molecules were selectively adsorbed by the MIP membranes and quantified using color reaction with picrates. The intensity of MIP membranes staining was proportional to creatinine concentration in an analyzed sample. The colorimetric test-system based on the composite MIP membranes was characterized with 0.25 mM detection limit and 0.25-2.5mM linear dynamic range. Storage stability of the MIP membranes was estimated as at least 1 year at room temperature. As compared to the traditional methods of creatinine detection the developed test-system is characterized by simplicity of operation, small size and low cost. Copyright © 2013 Elsevier B.V. All rights reserved.

Automated baseline change detection -- Phases 1 and 2. Final report

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

Byler, E.

1997-10-31

The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrelmore » and on feature recognition in images. The ABCD image processing software was installed on a robotic vehicle developed under a related DOE/FETC contract DE-AC21-92MC29112 Intelligent Mobile Sensor System (IMSS) and integrated with the electronics and software. This vehicle was designed especially to navigate in DOE Waste Storage Facilities. Initial system testing was performed at Fernald in June 1996. After some further development and more extensive integration the prototype integrated system was installed and tested at the Radioactive Waste Management Facility (RWMC) at INEEL beginning in April 1997 through the present (November 1997). The integrated system, composed of ABCD imaging software and IMSS mobility base, is called MISS EVE (Mobile Intelligent Sensor System--Environmental Validation Expert). Evaluation of the integrated system in RWMC Building 628, containing approximately 10,000 drums, demonstrated an easy to use system with the ability to properly navigate through the facility, image all the defined drums, and process the results into a report delivered to the operator on a GUI interface and on hard copy. Further work is needed to make the brassboard system more operationally robust.« less

Suspicious Behavior Detection System for an Open Space Parking Based on Recognition of Human Elemental Actions

NASA Astrophysics Data System (ADS)

Inomata, Teppei; Kimura, Kouji; Hagiwara, Masafumi

Studies for video surveillance applications for preventing various crimes such as stealing and violence have become a hot topic. This paper proposes a new video surveillance system that can detect suspicious behaviors such as a car break-in and vandalization in an open space parking, and that is based on image processing. The proposed system has the following features: it 1)deals time series data flow, 2)recognizes “human elemental actions” using statistic features, and 3)detects suspicious behavior using Subspace method and AdaBoost. We conducted the experiments to test the performance of the proposed system using open space parking scenes. As a result, we obtained about 10.0% for false positive rate, and about 4.6% for false negative rate.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

A fibre optic fluorescence sensor to measure redox level in tissues

NASA Astrophysics Data System (ADS)

Zhang, Wen Qi; Morrison, Janna L.; Darby, Jack R. T.; Plush, Sally; Sorvina, Alexandra; Brooks, Doug; Monro, Tanya M.; Afshar Vahid, Shahraam

2018-01-01

We report the design of a fibre optic-based redox detection system for investigating differences in metabolic activities of tissues. Our system shows qualitative agreement with the results collected from a commercial two- photon microscope system. Thus, demonstrating the feasibility of building an ex vivo and in vivo redox detection system that is low cost and portable.