WorldWideScience

Sample records for automatic vehicle detection and identification systems

  1. Intelligent system for automatic feature detection and selection or identification

    Science.gov (United States)

    Sun, C.T.; Shiang, P.S.; Jang, J.S.; Fu, C.Y.

    1997-09-02

    A neural network uses a fuzzy membership function, the parameters of which are adaptive during the training process, to parameterize the interconnection weights between an (n{minus}1)`th layer and an n`th layer of the network. Each j`th node in each k`th layer of the network except the input layer produces its output value y{sub k,j} according to the function shown in Equation 1 where N{sub k{minus}1} is the number of nodes in layer k{minus}1, i indexes the nodes of layer k{minus}1 and all the w{sub k,i,j} are interconnection weights. The interconnection weights to all nodes j in the n`th layer are given by w{sub n,i,j}=w{sub n,j} (i, p{sub n,j,1}, . . . , p{sub n,j},p{sub n}). The apparatus is trained by setting values for at least one of the parameters p{sub n,j,1}, . . . , p{sub n,j},Pn. Preferably the number of parameters P{sub n} is less than the number of nodes N{sub n{minus}1} in layer n{minus}1. W{sub n,j} (i,p{sub n,j,1}, . . . , p{sub n,j},Pn) can be convex in i, and it can be bell-shaped. Sample functions for w{sub n,j} (i, p{sub n,j,1}, . . . , p{sub n,j},Pn) include Equation 2, shown in the patent. 8 figs.

  2. Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.

    Science.gov (United States)

    2012-12-01

    This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...

  3. Forming and detection of digital watermarks in the System for Automatic Identification of VHF Transmissions

    Directory of Open Access Journals (Sweden)

    О. В. Шишкін

    2013-07-01

    Full Text Available Forming and detection algorithms for digital watermarks are designed for automatic identification of VHF radiotelephone transmissions in the maritime and aeronautical mobile services. An audible insensitivity and interference resistance of embedded digital data are provided by means of OFDM technology jointly with normalized distortions distribution and data packet detection by the hash-function. Experiments were carried out on the base of ship’s radio station RT-2048 Sailor and USB ADC-DAC module of type Е14-140M L-CARD in the off-line processing regime in Matlab medium

  4. Roadway weather information system and automatic vehicle location (AVL) coordination.

    Science.gov (United States)

    2011-02-28

    Roadway Weather Information System and Automatic Vehicle Location Coordination involves the : development of an Inclement Weather Console that provides a new capability for the state of Oklahoma : to monitor weather-related roadway conditions. The go...

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

    Science.gov (United States)

    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.

  6. Automatic Detection of Vehicles Using Intensity Laser and Anaglyph Image

    Directory of Open Access Journals (Sweden)

    Hideo Araki

    2006-12-01

    Full Text Available In this work is presented a methodology to automatic car detection motion presents in digital aerial image on urban area using intensity, anaglyph and subtracting images. The anaglyph image is used to identify the motion cars on the expose take, because the cars provide red color due the not homology between objects. An implicit model was developed to provide a digital pixel value that has the specific propriety presented early, using the ratio between the RGB color of car object in the anaglyph image. The intensity image is used to decrease the false positive and to do the processing to work into roads and streets. The subtracting image is applied to decrease the false positives obtained due the markings road. The goal of this paper is automatically detect motion cars presents in digital aerial image in urban areas. The algorithm implemented applies normalization on the left and right images and later form the anaglyph with using the translation. The results show the applicability of proposed method and it potentiality on the automatic car detection and presented the performance of proposed methodology.

  7. Estimating spatial travel times using automatic vehicle identification data

    Science.gov (United States)

    2001-01-01

    Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...

  8. Modeling and Prototyping of Automatic Clutch System for Light Vehicles

    Science.gov (United States)

    Murali, S.; Jothi Prakash, V. M.; Vishal, S.

    2017-03-01

    Nowadays, recycling or regenerating the waste in to something useful is appreciated all around the globe. It reduces greenhouse gas emissions that contribute to global climate change. This study deals with provision of the automatic clutch mechanism in vehicles to facilitate the smooth changing of gears. This study proposed to use the exhaust gases which are normally expelled out as a waste from the turbocharger to actuate the clutch mechanism in vehicles to facilitate the smooth changing of gears. At present, clutches are operated automatically by using an air compressor in the four wheelers. In this study, a conceptual design is proposed in which the clutch is operated by the exhaust gas from the turbocharger and this will remove the usage of air compressor in the existing system. With this system, usage of air compressor is eliminated and the riders need not to operate the clutch manually. This work involved in development, analysation and validation of the conceptual design through simulation software. Then the developed conceptual design of an automatic pneumatic clutch system is tested with proto type.

  9. MAC, A System for Automatically IPR Identification, Collection and Distribution

    Science.gov (United States)

    Serrão, Carlos

    Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

  10. Vehicle dynamic prediction systems with on-line identification of vehicle parameters and road conditions.

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-11-13

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.

  11. Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

  12. 2010 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2010 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  13. 2014 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2014 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  14. 2011 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2011 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  15. 2009 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2009 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  16. 2012 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2012 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  17. The systems of automatic weight control of vehicles in the road and rail transport in Poland

    Directory of Open Access Journals (Sweden)

    2011-09-01

    Full Text Available . Condition of roads in Poland, despite the on-going modernisation works is still unsatisfactory. One reason is the excessive wear caused by overloaded vehicles. This problem also applies to rail transport, although to a much lesser extent. One solution may be the system of automatic weight control of road and rail vehicles. The article describes the legal and organizational conditions of oversize vehicles inspection in Poland. Characterized current practices weighing road vehicles, based on measurements of static technology. The article includes the description of the existing applications of the automatic dynamic weighing technology, known as systems WIM (Weigh in Motion. Additionally, the weighing technology and construction of weighing stands in road and rail are characterized. The article ends with authors' conclusions indicating the direction and ways of improving the weighing control systems for vehicles.

  18. Design and Assessment of a Machine Vision System for Automatic Vehicle Wheel Alignment

    Directory of Open Access Journals (Sweden)

    Rocco Furferi

    2013-05-01

    Full Text Available Abstract Wheel alignment, consisting of properly checking the wheel characteristic angles against vehicle manufacturers' specifications, is a crucial task in the automotive field since it prevents irregular tyre wear and affects vehicle handling and safety. In recent years, systems based on Machine Vision have been widely studied in order to automatically detect wheels' characteristic angles. In order to overcome the limitations of existing methodologies, due to measurement equipment being mounted onto the wheels, the present work deals with design and assessment of a 3D machine vision-based system for the contactless reconstruction of vehicle wheel geometry, with particular reference to characteristic planes. Such planes, properly referred to as a global coordinate system, are used for determining wheel angles. The effectiveness of the proposed method was tested against a set of measurements carried out using a commercial 3D scanner; the absolute average error in measuring toe and camber angles with the machine vision system resulted in full compatibility with the expected accuracy of wheel alignment systems.

  19. Intelligent Storage System Based on Automatic Identification

    Directory of Open Access Journals (Sweden)

    Kolarovszki Peter

    2014-09-01

    Full Text Available This article describes RFID technology in conjunction with warehouse management systems. Article also deals with automatic identification and data capture technologies and each processes, which are used in warehouse management system. It describes processes from entering goods into production to identification of goods and also palletizing, storing, bin transferring and removing goods from warehouse. Article focuses on utilizing AMP middleware in WMS processes in Nowadays, the identification of goods in most warehouses is carried through barcodes. In this article we want to specify, how can be processes described above identified through RFID technology. All results are verified by measurement in our AIDC laboratory, which is located at the University of Žilina, and also in Laboratory of Automatic Identification Goods and Services located in GS1 Slovakia. The results of our research bring the new point of view and indicate the ways using of RFID technology in warehouse management system.

  20. Fault prevention by early stage symptoms detection for automatic vehicle transmission using pattern recognition and curve fitting

    Science.gov (United States)

    Balbin, Jessie R.; Cruz, Febus Reidj G.; Abu, Jon Ervin A.; Siño, Carlo G.; Ubaldo, Paolo E.; Zulueta, Christelle Jianne T.

    2017-06-01

    Automobiles have become essential parts of our everyday lives. It can correlate many factors that may affect a vehicle primarily those which may inconvenient or in some cases harm lives or properties. Thus, focusing on detecting an automatic transmission vehicle engine, body and other parts that cause vibration and sound may help prevent car problems using MATLAB. By using sound, vibration, and temperature sensors to detect the defects of the car and with the help of the transmitter and receiver to gather data wirelessly, it is easy to install on to the vehicle. A technique utilized from Toyota Balintawak Philippines that every car is treated as panels(a, b, c, d, and e) 'a' being from the hood until the front wheel of the car and 'e' the rear shield to the back of the car, this was applied on how to properly place the sensors so that precise data could be gathered. Data gathered would be compared to the normal graph taken from the normal status or performance of a vehicle, data that would surpass 50% of the normal graph would be considered that a problem has occurred. The system is designed to prevent car accidents by determining the current status or performance of the vehicle, also keeping people away from harm.

  1. Automatic vehicle detection based on automatic histogram-based fuzzy C-means algorithm and perceptual grouping using very high-resolution aerial imagery and road vector data

    Science.gov (United States)

    Ghaffarian, Saman; Gökaşar, Ilgın

    2016-01-01

    This study presents an approach for the automatic detection of vehicles using very high-resolution images and road vector data. Initially, road vector data and aerial images are integrated to extract road regions. Then, the extracted road/street region is clustered using an automatic histogram-based fuzzy C-means algorithm, and edge pixels are detected using the Canny edge detector. In order to automatically detect vehicles, we developed a local perceptual grouping approach based on fusion of edge detection and clustering outputs. To provide the locality, an ellipse is generated using characteristics of the candidate clusters individually. Then, ratio of edge pixels to nonedge pixels in the corresponding ellipse is computed to distinguish the vehicles. Finally, a point-merging rule is conducted to merge the points that satisfy a predefined threshold and are supposed to denote the same vehicles. The experimental validation of the proposed method was carried out on six very high-resolution aerial images that illustrate two highways, two shadowed roads, a crowded narrow street, and a street in a dense urban area with crowded parked vehicles. The evaluation of the results shows that our proposed method performed 86% and 83% in overall correctness and completeness, respectively.

  2. An object detection and tracking system for unmanned surface vehicles

    Science.gov (United States)

    Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao

    2017-10-01

    Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.

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

    Science.gov (United States)

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

    2018-03-01

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

  4. Sensor network based vehicle classification and license plate identification system

    Energy Technology Data Exchange (ETDEWEB)

    Frigo, Janette Rose [Los Alamos National Laboratory; Brennan, Sean M [Los Alamos National Laboratory; Rosten, Edward J [Los Alamos National Laboratory; Raby, Eric Y [Los Alamos National Laboratory; Kulathumani, Vinod K [WEST VIRGINIA UNIV.

    2009-01-01

    Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform. Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.

  5. Accident identification system with automatic detection of abnormal condition using quantum computation

    Energy Technology Data Exchange (ETDEWEB)

    Nicolau, Andressa dos Santos; Schirru, Roberto, E-mail: andressa@lmp.ufrj.br, E-mail: schirru@lmp.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil); Lima, Alan Miranda Monteiro de [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil)

    2011-07-01

    Transient identification systems have been proposed in order to maintain the plant operating in safe conditions and help operators in make decisions in emergency short time interval with maximum certainty associated. This article presents a system, time independent and without the use of an event that can be used as a starting point for t = 0 (reactor scram, for instance), for transient/accident identification of a pressurized water nuclear reactor (PWR). The model was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the Nuclear Power Plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). Were used several sets of process variables in order to establish a minimum set of variables considered necessary and sufficient. The optimization step of the identification algorithm is based upon the paradigm of Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and works as a data mining tool. The results obtained with the QEA without the time variable are compatible to the techniques in the reference literature, for the transient identification problem, with less computational effort (number of evaluations). This system allows a solution that approximates the ideal solution, the Voronoi Vectors with only one partition for the classes of accidents with robustness. (author)

  6. Accident identification system with automatic detection of abnormal condition using quantum computation

    International Nuclear Information System (INIS)

    Nicolau, Andressa dos Santos; Schirru, Roberto; Lima, Alan Miranda Monteiro de

    2011-01-01

    Transient identification systems have been proposed in order to maintain the plant operating in safe conditions and help operators in make decisions in emergency short time interval with maximum certainty associated. This article presents a system, time independent and without the use of an event that can be used as a starting point for t = 0 (reactor scram, for instance), for transient/accident identification of a pressurized water nuclear reactor (PWR). The model was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the Nuclear Power Plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). Were used several sets of process variables in order to establish a minimum set of variables considered necessary and sufficient. The optimization step of the identification algorithm is based upon the paradigm of Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and works as a data mining tool. The results obtained with the QEA without the time variable are compatible to the techniques in the reference literature, for the transient identification problem, with less computational effort (number of evaluations). This system allows a solution that approximates the ideal solution, the Voronoi Vectors with only one partition for the classes of accidents with robustness. (author)

  7. Identification and Damage Detection on Structural Systems

    DEFF Research Database (Denmark)

    Brincker, Rune; Kirkegaard, Poul Henning; Andersen, Palle

    1994-01-01

    A short introduction is given to system identification and damage assessment in civil engineering structures. The most commonly used FFT-based techniques for system identification are mentioned, and the Random decrement technique and parametric methods based on ARMA models are introduced. Speed...

  8. Automatic Arrhythmia Beat Detection: Algorithm, System, and Implementation

    Directory of Open Access Journals (Sweden)

    Wisnu Jatmiko

    2016-08-01

    Full Text Available Cardiac disease is one of the major causes of death in the world. Early diagnose of the symptoms depends on abnormality on heart beat pattern, known as Arrhythmia. A novel fuzzy neuro generalized learning vector quantization for automatic Arrhythmia heart beat classification is proposed. The algorithm is an extension from theGLVQ algorithm that employs a fuzzy logic concept as the discriminant function in order to develop a robust algorithmand improve the classification performance. The algorithm is testedagainst MIT-BIH arrhythmia database to measure theperformance. Based on the experiment result, FN-GLVQ is able to increase the accuracy of GLVQ by a soft margin. As we intend to build a device with automated Arrhythmia detection,FN-GLVQ is then implemented into Field Gate Programmable Array to prototype the system into a real device.

  9. Inertial Measurement Units-Based Probe Vehicles: Automatic Calibration, Trajectory Estimation, and Context Detection

    KAUST Repository

    Mousa, Mustafa

    2017-12-06

    Most probe vehicle data is generated using satellite navigation systems, such as the Global Positioning System (GPS), Globalnaya navigatsionnaya sputnikovaya Sistema (GLONASS), or Galileo systems. However, because of their high cost, relatively high position uncertainty in cities, and low sampling rate, a large quantity of satellite positioning data is required to estimate traffic conditions accurately. To address this issue, we introduce a new type of traffic monitoring system based on inexpensive inertial measurement units (IMUs) as probe sensors. IMUs as traffic probes pose unique challenges in that they need to be precisely calibrated, do not generate absolute position measurements, and their position estimates are subject to accumulating errors. In this paper, we address each of these challenges and demonstrate that the IMUs can reliably be used as traffic probes. After discussing the sensing technique, we present an implementation of this system using a custom-designed hardware platform, and validate the system with experimental data.

  10. A Study of Vehicle Detection and Counting System Based on Video

    OpenAIRE

    Shuang XU; Lingbin PANG; Huairuo YIN

    2014-01-01

    About the video image processing's vehicle detection and counting system research, which has video vehicle detection, vehicle targets' image processing, and vehicle counting function. Vehicle detection is the use of inter-frame difference method and vehicle shadow segmentation techniques for vehicle testing. Image processing functions is the use of color image gray processing, image segmentation, mathematical morphology analysis and image fills, etc. on target detection to be processed, and t...

  11. Optical Automatic Car Identification (OACI) : Volume 1. Advanced System Specification.

    Science.gov (United States)

    1978-12-01

    A performance specification is provided in this report for an Optical Automatic Car Identification (OACI) scanner system which features 6% improved readability over existing industry scanner systems. It also includes the analysis and rationale which ...

  12. AUTOMATIC PEDESTRIAN CROSSING DETECTION AND IMPAIRMENT ANALYSIS BASED ON MOBILE MAPPING SYSTEM

    Directory of Open Access Journals (Sweden)

    X. Liu

    2017-09-01

    Full Text Available Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians’ lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

  13. Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

    Science.gov (United States)

    Liu, X.; Zhang, Y.; Li, Q.

    2017-09-01

    Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

  14. Field-portable imaging remote sensing system for automatic identification and imaging of hazardous gases

    Science.gov (United States)

    Harig, R.; Rusch, P.; Peters, H.; Gerhard, J.; Braun, R.,; Sabbah, S.; Beecken, J.

    2009-09-01

    Hazardous compounds may be released into the atmosphere in the case of fires, chemical accidents, terrorist acts, or war. In these cases, information about the released compounds is required immediately in order to take appropriate measures to protect workers, residents, emergency response personnel at the site of the release, and the environment. Remote sensing by infrared spectroscopy allows detection and identification of hazardous clouds in the atmosphere from long distances. In addition, imaging spectroscopy allows an assessment of the location, the dimensions and the dispersion of a potentially hazardous cloud. This additional information may contribute significantly to a correct assessment of a situation by emergency response forces. Therefore an imaging remote sensing system based on a Fourier-transform spectrometer with a focal plane array detector for automatic identification and imaging of gases has been developed. Imaging systems allow the use of spatial information in addition to spectral information. Thus, in order to achieve low limits of detection, algorithms that combine algorithms for spectral analysis and image analysis have been developed. In this work, the system and first results of measurements are presented.

  15. Traffic Congestion Detection System through Connected Vehicles and Big Data.

    Science.gov (United States)

    Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

    2016-04-28

    This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

  16. An automatically tuning intrusion detection system.

    Science.gov (United States)

    Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

    2007-04-01

    An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

  17. DIRADTM - a system for real time detection and identification of radioactive objects

    International Nuclear Information System (INIS)

    Guillot, L.; Reboli, A.

    2009-01-01

    The authors present the DIRAD system (DIRAD stands for Detection and Identification of Radionuclides), an automatic system for real time identification of a radioactive anomaly and its interpretation in terms of risk level. It can be adapted to different contexts: pedestrian control, parcel or luggage control, road traffic control, and so on. In case of risk detection, an alert is transmitted in real time to a supervision station along with the whole set of spectral data

  18. Low-elevation tracking technique for X-band unmanned aerial vehicle automatic take-off and landing system

    Science.gov (United States)

    Lin, S.-Y.; Cho, M.-H.; Lin, M.-Y.; Hu, W.-Y.; Sun, J.-S.

    2017-05-01

    In this study, an automatic take-off and landing system (ATOLS) based on radar guidance was developed to provide day/night, all weather, automatic takeoff and landing for unmanned aerial vehicles (UAVs). The ATOLS contains a ground-based tracking radar subsystem and an airborne transponder subsystem. This X-band tracking radar can provide precise position information for UAV-control operations (transponder mode) and fire-control systems (skin mode). It provides 360 degrees of azimuth coverage and therefore can be employed for navigation applications. Its maximum tracking range is about 17 km and accuracy of altitude measurement is about 1 ft with a 50-ft decision height above ground level. To substantiate the proposed ATOLS system, a differential global positioning system (DGPS) was also developed. When a UAV at a low-elevation angle is detected and tracked by a tracking radar, multipath propagation often leads to the degradation of tracking accuracy or even cause the radar to break track. As a result, it becomes a potential risk to flight safety of the ATOLS guidance and control of UAVs. To overcome this technical difficulty, this paper proposes a solution based on optimization of radar parameters to mitigate the interference from multipath signals. The feasibility of proposed method has been experimentally proven through the flight trials of UAVs. Compared to the conventional low-elevation tracking techniques, the proposed one employs the radar signal processing, and does not consume additional hardware and resources.

  19. A Study of Vehicle Detection and Counting System Based on Video

    Directory of Open Access Journals (Sweden)

    Shuang XU

    2014-10-01

    Full Text Available About the video image processing's vehicle detection and counting system research, which has video vehicle detection, vehicle targets' image processing, and vehicle counting function. Vehicle detection is the use of inter-frame difference method and vehicle shadow segmentation techniques for vehicle testing. Image processing functions is the use of color image gray processing, image segmentation, mathematical morphology analysis and image fills, etc. on target detection to be processed, and then the target vehicle extraction. Counting function is to count the detected vehicle. The system is the use of inter-frame video difference method to detect vehicle and the use of the method of adding frame to vehicle and boundary comparison method to complete the counting function, with high recognition rate, fast, and easy operation. The purpose of this paper is to enhance traffic management modernization and automation levels. According to this study, it can provide a reference for the future development of related applications.

  20. Traffic Congestion Detection System through Connected Vehicles and Big Data

    Directory of Open Access Journals (Sweden)

    Néstor Cárdenas-Benítez

    2016-04-01

    Full Text Available This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

  1. The testing techniques of the automatics fire detection monitoring systems (A receiver and A transmitter)

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Yon Woo; Soong, Woong Sup; Kim, Kee Ha [Korea Atomic Energy Research Institute, Taejon (Korea)

    1999-04-01

    The major function of the automatic fire detection system is to use effectively the fire-fighting equipments and the shelter apparatus detecting immediately the fire and notifying the fire to a person in charge. To perform these functions, the automatic fire detection system is composed of a receiver and a transmitter which indicate the origin of a fire, sound facility, wiring and power supply. And the main purpose using this system is to stop the spread of the fire and minimize the damage of human life and properties of the facility. 12 refs., 17 figs., 11 tabs. (Author)

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

    Science.gov (United States)

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

    2017-07-01

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

  3. A Clonal Selection Algorithm for Minimizing Distance Travel and Back Tracking of Automatic Guided Vehicles in Flexible Manufacturing System

    Science.gov (United States)

    Chawla, Viveak Kumar; Chanda, Arindam Kumar; Angra, Surjit

    2018-03-01

    The flexible manufacturing system (FMS) constitute of several programmable production work centers, material handling systems (MHSs), assembly stations and automatic storage and retrieval systems. In FMS, the automatic guided vehicles (AGVs) play a vital role in material handling operations and enhance the performance of the FMS in its overall operations. To achieve low makespan and high throughput yield in the FMS operations, it is highly imperative to integrate the production work centers schedules with the AGVs schedules. The Production schedule for work centers is generated by application of the Giffler and Thompson algorithm under four kind of priority hybrid dispatching rules. Then the clonal selection algorithm (CSA) is applied for the simultaneous scheduling to reduce backtracking as well as distance travel of AGVs within the FMS facility. The proposed procedure is computationally tested on the benchmark FMS configuration from the literature and findings from the investigations clearly indicates that the CSA yields best results in comparison of other applied methods from the literature.

  4. Automatic system for detecting pornographic images

    Science.gov (United States)

    Ho, Kevin I. C.; Chen, Tung-Shou; Ho, Jun-Der

    2002-09-01

    Due to the dramatic growth of network and multimedia technology, people can more easily get variant information by using Internet. Unfortunately, it also makes the diffusion of illegal and harmful content much easier. So, it becomes an important topic for the Internet society to protect and safeguard Internet users from these content that may be encountered while surfing on the Net, especially children. Among these content, porno graphs cause more serious harm. Therefore, in this study, we propose an automatic system to detect still colour porno graphs. Starting from this result, we plan to develop an automatic system to search porno graphs or to filter porno graphs. Almost all the porno graphs possess one common characteristic that is the ratio of the size of skin region and non-skin region is high. Based on this characteristic, our system first converts the colour space from RGB colour space to HSV colour space so as to segment all the possible skin-colour regions from scene background. We also apply the texture analysis on the selected skin-colour regions to separate the skin regions from non-skin regions. Then, we try to group the adjacent pixels located in skin regions. If the ratio is over a given threshold, we can tell if the given image is a possible porno graph. Based on our experiment, less than 10% of non-porno graphs are classified as pornography, and over 80% of the most harmful porno graphs are classified correctly.

  5. An automatic window opening system to prevent drowning in vehicles sinking in water

    KAUST Repository

    Giesbrecht, Gordon G.

    2017-07-12

    Objective: Every year about 400 people die in submersed vehicles in North America and this number increases to 2,000–5,000 in all industrialized nations. The best way to survive is to quickly exit through the windows. An Automatic Window Opening System (AWOS; patent protected) was designed to sense when a vehicle is in water and to open the electric windows, but only when the vehicle is upright. Methods: The AWOS consists of a Detection Module (DM), in the engine compartment, and a Power Window Control Module (PWCM) inside the driver’s door. The DM contains a Water Sensor, a Level Sensor and a Microcontroller Unit (MCU). The Level Sensor provides the angular orientation of the car using a 3-axis acceleration sensor and prevents automatic window opening if the car is outside the orientation range (±20° in the roll axis, ±30° in the pitch axis, with a 2 s delay). Systems were installed on two cars and one SUV. A crane lowered vehicles in water either straight down (static tests) or by swinging the vehicles to produce forward movement (dynamic tests). Results: In all tests, when the vehicles landed upright, windows opened immediately and effectively. When vehicles landed inverted, or at a very steep angle, the system did not engage until an upright and level position was attained. Conclusions: This system may help decrease drowning deaths in sinking vehicles. If occupants do not know, or forget, what to do, the open window could hopefully prompt them to exit safely through that window.

  6. Automatic Supervision And Fault Detection In PV System By Wireless Sensors With Interfacing By Labview Program

    Directory of Open Access Journals (Sweden)

    Yousra M Abbas

    2015-08-01

    Full Text Available In this work a wireless monitoring system are designed for automatic detection localization fault in photovoltaic system. In order to avoid the use of modeling and simulation of the PV system we detected the fault by monitoring the output of each individual photovoltaic panel connected in the system by Arduino and transmit this data wirelessly to laptop then interface it by LabVIEW program which made comparison between this data and the measured data taking from reference module at the same condition. The proposed method is very simple but effective detecting and diagnosing the main faults of a PV system and was experimentally validated and has demonstrated its effectiveness in the detection and diagnosing of main faults present in the DC side of PV system.

  7. Conceptual design of a connected vehicle wrong-way driving detection and management system.

    Science.gov (United States)

    2016-04-01

    This report describes the tasks completed to develop a concept of operations, functional requirements, and : high-level system design for a Connected Vehicle (CV) Wrong-Way Driving (WWD) Detection and Management : System. This system was designed to ...

  8. Automatic construction of a recurrent neural network based classifier for vehicle passage detection

    Science.gov (United States)

    Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

    2017-03-01

    Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

  9. Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images.

    Directory of Open Access Journals (Sweden)

    Kajsa Møllersen

    Full Text Available Melanoma is the deadliest form of skin cancer, and early detection is crucial for patient survival. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classification of dermoscopic images of skin lesions was announced. A training set of 900 images with corresponding class labels and semi-automatic/manual segmentation masks was released for the challenge. An independent test set of 379 images, of which 75 were of melanomas, was used to rank the participants. This article demonstrates the impact of ranking criteria, segmentation method and classifier, and highlights the clinical perspective. We compare five different measures for diagnostic accuracy by analysing the resulting ranking of the computer systems in the challenge. Choice of performance measure had great impact on the ranking. Systems that were ranked among the top three for one measure, dropped to the bottom half when changing performance measure. Nevus Doctor, a computer system previously developed by the authors, was used to participate in the challenge, and investigate the impact of segmentation and classifier. The diagnostic accuracy when using an automatic versus the semi-automatic/manual segmentation is investigated. The unexpected small impact of segmentation method suggests that improvements of the automatic segmentation method w.r.t. resemblance to semi-automatic/manual segmentation will not improve diagnostic accuracy substantially. A small set of similar classification algorithms are used to investigate the impact of classifier on the diagnostic accuracy. The variability in diagnostic accuracy for different classifier algorithms was larger than the variability for segmentation methods, and suggests a focus for future investigations. From a clinical perspective, the misclassification of a melanoma as benign has far greater cost than the misclassification of a benign lesion. For computer systems to have

  10. Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images.

    Science.gov (United States)

    Møllersen, Kajsa; Zortea, Maciel; Schopf, Thomas R; Kirchesch, Herbert; Godtliebsen, Fred

    2017-01-01

    Melanoma is the deadliest form of skin cancer, and early detection is crucial for patient survival. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classification of dermoscopic images of skin lesions was announced. A training set of 900 images with corresponding class labels and semi-automatic/manual segmentation masks was released for the challenge. An independent test set of 379 images, of which 75 were of melanomas, was used to rank the participants. This article demonstrates the impact of ranking criteria, segmentation method and classifier, and highlights the clinical perspective. We compare five different measures for diagnostic accuracy by analysing the resulting ranking of the computer systems in the challenge. Choice of performance measure had great impact on the ranking. Systems that were ranked among the top three for one measure, dropped to the bottom half when changing performance measure. Nevus Doctor, a computer system previously developed by the authors, was used to participate in the challenge, and investigate the impact of segmentation and classifier. The diagnostic accuracy when using an automatic versus the semi-automatic/manual segmentation is investigated. The unexpected small impact of segmentation method suggests that improvements of the automatic segmentation method w.r.t. resemblance to semi-automatic/manual segmentation will not improve diagnostic accuracy substantially. A small set of similar classification algorithms are used to investigate the impact of classifier on the diagnostic accuracy. The variability in diagnostic accuracy for different classifier algorithms was larger than the variability for segmentation methods, and suggests a focus for future investigations. From a clinical perspective, the misclassification of a melanoma as benign has far greater cost than the misclassification of a benign lesion. For computer systems to have clinical impact

  11. Planning an Automatic Fire Detection, Alarm, and Extinguishing System for Research Laboratories

    Directory of Open Access Journals (Sweden)

    Rostam Golmohamadi

    2014-04-01

    Full Text Available Background & Objectives: Educational and research laboratories in universities have a high risk of fire, because they have a variety of materials and equipment. The aim of this study was to provide a technical plan for safety improvement in educational and research laboratories of a university based on the design of automatic detection, alarm, and extinguishing systems . Methods : In this study, fire risk assessment was performed based on the standard of Military Risk Assessment method (MIL-STD-882. For all laboratories, detection and fire alarm systems and optimal fixed fire extinguishing systems were designed. Results : Maximum and minimum risks of fire were in chemical water and wastewater (81.2% and physical agents (62.5% laboratories, respectively. For studied laboratories, we designed fire detection systems based on heat and smoke detectors. Also in these places, fire-extinguishing systems based on CO2 were designed . Conclusion : Due to high risk of fire in studied laboratories, the best control method for fire prevention and protection based on special features of these laboratories is using automatic detection, warning and fire extinguishing systems using CO2 .

  12. 'H-Bahn' - Dortmund demonstration system. Automatic vehicle protection system

    Energy Technology Data Exchange (ETDEWEB)

    Rosenkranz

    1984-01-01

    The automatic vehicle protection system of the H-Bahn at the Universtiy of Dortmund is responsible for fail-safe operating of the automatic vehicles. Its functions are protection of vehicle operation and protection of passengers boarding and leaving the vehicles. These functions are managed decentrally by two fail-safe operating controllers. Besides the well-known relay-techniques of railway-fail-safe systems, electronics are applied which are based on safe operating URTL-microcontrollers. These are controlled by software stored in EPROMs. A connection link using glass-fibres serves for safe data-exchange between the two fail-safe operating controllers. The experts' favourable reports on 'train protection and safety during passenger processing' were completed in March 84; thus, transportation of passengers could start in April 84.

  13. Traffic Congestion Detection System through Connected Vehicles and Big Data

    OpenAIRE

    C?rdenas-Ben?tez, N?stor; Aquino-Santos, Ra?l; Maga?a-Espinoza, Pedro; Aguilar-Velazco, Jos?; Edwards-Block, Arthur; Medina Cass, Aldo

    2016-01-01

    This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which ...

  14. Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification

    Directory of Open Access Journals (Sweden)

    Horak Karel

    2016-01-01

    Full Text Available The paper describes a colour-based segmentation method of European traffic signs for detection in an image and a feature-based recognition method for categorizing them into given classes. At first, we have performed analysis of several well-known colour spaces as the RGB, HSV and YCbCr often used for segmentation purposes. The HSV colour space has been chosen as the most convenient for segmentation step and colour-based models of traffic signs representatives were created. Next, the fast radial symmetry (FRS detection method and the Harris corner detector were used to recognize circles, triangles and squares as main geometrical shapes of the traffic signs. For these purposes a new gallery of real-life images containing traffic signs has been created and analysed. Overall efficiency of our recognition method is approx. 93 % on our gallery and is usable for real-time implementations.

  15. Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle.

    Science.gov (United States)

    Diaz-Varela, R A; Zarco-Tejada, P J; Angileri, V; Loudjani, P

    2014-02-15

    Agricultural terraces are features that provide a number of ecosystem services. As a result, their maintenance is supported by measures established by the European Common Agricultural Policy (CAP). In the framework of CAP implementation and monitoring, there is a current and future need for the development of robust, repeatable and cost-effective methodologies for the automatic identification and monitoring of these features at farm scale. This is a complex task, particularly when terraces are associated to complex vegetation cover patterns, as happens with permanent crops (e.g. olive trees). In this study we present a novel methodology for automatic and cost-efficient identification of terraces using only imagery from commercial off-the-shelf (COTS) cameras on board unmanned aerial vehicles (UAVs). Using state-of-the-art computer vision techniques, we generated orthoimagery and digital surface models (DSMs) at 11 cm spatial resolution with low user intervention. In a second stage, these data were used to identify terraces using a multi-scale object-oriented classification method. Results show the potential of this method even in highly complex agricultural areas, both regarding DSM reconstruction and image classification. The UAV-derived DSM had a root mean square error (RMSE) lower than 0.5 m when the height of the terraces was assessed against field GPS data. The subsequent automated terrace classification yielded an overall accuracy of 90% based exclusively on spectral and elevation data derived from the UAV imagery. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Development and Testing of a Prototype Connected Vehicle Wrong-Way Driving Detection and Management System

    Science.gov (United States)

    2018-02-01

    The primary objective of Phase II was to develop a prototype connected vehicle wrong-way driving detection and management system at the Texas A&M University Respect, Excellence, Leadership, Loyalty, Integrity, Selfless Service (RELLIS) campus. The pu...

  17. A semi-automatic traffic sign detection, classification, and positioning system

    Science.gov (United States)

    Creusen, I. M.; Hazelhoff, L.; de With, P. H. N.

    2012-01-01

    The availability of large-scale databases containing street-level panoramic images offers the possibility to perform semi-automatic surveying of real-world objects such as traffic signs. These inventories can be performed significantly more efficiently than using conventional methods. Governmental agencies are interested in these inventories for maintenance and safety reasons. This paper introduces a complete semi-automatic traffic sign inventory system. The system consists of several components. First, a detection algorithm locates the 2D position of the traffic signs in the panoramic images. Second, a classification algorithm is used to identify the traffic sign. Third, the 3D position of the traffic sign is calculated using the GPS position of the photographs. Finally, the results are listed in a table for quick inspection and are also visualized in a web browser.

  18. Novel vehicle detection system based on stacked DoG kernel and AdaBoost

    Science.gov (United States)

    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

  19. 33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Automatic Identification System Shipborne Equipment-Prince William Sound. 164.43 Section 164.43 Navigation and Navigable Waters COAST GUARD... Automatic Identification System Shipborne Equipment—Prince William Sound. (a) Until December 31, 2004, each...

  20. Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems

    Directory of Open Access Journals (Sweden)

    Yongwha Chung

    2013-09-01

    Full Text Available Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD and the Sparse Representation Classifier (SRC as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used and accurately (94% detection and 91% classification accuracy, either as a standalone solution or to complement known methods to obtain a more accurate solution.

  1. Embedded and real-time vehicle detection system for challenging on-road scenes

    Science.gov (United States)

    Gu, Qin; Yang, Jianyu; Kong, Lingjiang; Yan, Wei Qi; Klette, Reinhard

    2017-06-01

    Vehicle detection is an important topic for advanced driver-assistance systems. This paper proposes an adaptive approach for an embedded system by focusing on monocular vehicle detection in real time, also aiming at being accurate under challenging conditions. Scene classification is accomplished by using a simplified convolution neural network with hypothesis generation by SoftMax regression. The output is consequently taken into account to optimize detection parameters for hypothesis generation and testing. Thus, we offer a sample-reorganization mechanism to improve the performance of vehicle hypothesis verification. A hypothesis leap mechanism is in use to improve the operating efficiency of the on-board system. A practical on-road test is employed to verify vehicle detection (i.e., accuracy) and also the performance of the designed on-board system regarding speed.

  2. Automatic Identification System (AIS) Collection and Reach-back System: System Description

    Science.gov (United States)

    2014-08-20

    to playback previously recorded NMEA data (. rcd files), and parcel the RMC and AIVDM sentences to the com 19 and com 40s port and IP addresses. 4.1.1...Input . rcd file – P2 := ID21 VDM UDP Port # 1 – P3 := ID21 VDM IP Address # 1 – P4 := ID21 RMC UDP Port # 2 – P5 := ID21 RMC IP Address # 2 – P6 := RAW...DEBUG MESSAGE SELECTION – P12 := Platform ID • Usage example: crbsplay pm050714. rcd ,2944,127.0.0.1,2944,127.0.0.1,4944,10.250.14.8,5944,10.250.14.8

  3. AROMA-AIRWICK: a CHLOE/CDC-3600 system for the automatic identification of spark images and their association into tracks

    International Nuclear Information System (INIS)

    Clark, R.K.

    The AROMA-AIRWICK System for CHLOE, an automatic film scanning equipment built at Argonne by Donald Hodges, and the CDC-3600 computer is a system for the automatic identification of spark images and their association into tracks. AROMA-AIRWICK has been an outgrowth of the generally recognized need for the automatic processing of high energy physics data and the fact that the Argonne National Laboratory has been a center of serious spark chamber development in recent years

  4. ANALYSIS OF SOFTWARE THREATS TO THE AUTOMATIC IDENTIFICATION SYSTEM

    Directory of Open Access Journals (Sweden)

    Marijan Gržan

    2017-01-01

    Full Text Available Automatic Identification System (AIS represents an important improvement in the fields of maritime security and vessel tracking. It is used by the signatory countries to the SOLAS Convention and by private and public providers. Its main advantage is that it can be used as an additional navigation aids, especially in avoiding collision at sea and in search and rescue operations. The present work analyses the functioning of the AIS System and the ways of exchanging data among the users. We also study one of the vulnerabilities of the System that can be abused by malicious users. The threat itself is analysed in detail in order to provide insight into the very process from the creation of a program to its implementation.

  5. Vision systems for manned and robotic ground vehicles

    Science.gov (United States)

    Sanders-Reed, John N.; Koon, Phillip L.

    2010-04-01

    A Distributed Aperture Vision System for ground vehicles is described. An overview of the hardware including sensor pod, processor, video compression, and displays is provided. This includes a discussion of the choice between an integrated sensor pod and individually mounted sensors, open architecture design, and latency issues as well as flat panel versus head mounted displays. This technology is applied to various ground vehicle scenarios, including closed-hatch operations (operator in the vehicle), remote operator tele-operation, and supervised autonomy for multi-vehicle unmanned convoys. In addition, remote vision for automatic perimeter surveillance using autonomous vehicles and automatic detection algorithms is demonstrated.

  6. Integration of Disaster Detection and Warning System for a Smart Vehicle

    Directory of Open Access Journals (Sweden)

    Chun-Chieh Wang

    2014-02-01

    Full Text Available For firefighters and rescuers, the disaster relief works are difficulty performed in the tunnels because of their constricted space. To reduce the losses of accident, the safety of tunnels and factories should be ordinarily kept under surveillance. Hence, a multisensor based smart tracked vehicle is designed for the application of autonomous detection and surveillance in this paper. Besides, multisensors, communication modules, wireless cameras, an electronic compass, and a GPS module are installed in the vehicle. The key feature is the integration of disaster detection and warning systems so that the vehicle can move autonomously. Furthermore, a LabVIEW graphical programming software is applied to design a human machine interface (HMI and integrate all systems such that the vehicle can be guided by High Speed Downlink Packet Access (HSHPA based remote control. Moreover, basic stamp microcontrollers are utilized as its control kernel such that the remote monitoring and control system (RMCS can be constructed successfully.

  7. Vehicle fault diagnostics and management system

    Science.gov (United States)

    Gopal, Jagadeesh; Gowthamsachin

    2017-11-01

    This project is a kind of advanced automatic identification technology, and is more and more widely used in the fields of transportation and logistics. It looks over the main functions with like Vehicle management, Vehicle Speed limit and Control. This system starts with authentication process to keep itself secure. Here we connect sensors to the STM32 board which in turn is connected to the car through Ethernet cable, as Ethernet in capable of sending large amounts of data at high speeds. This technology involved clearly shows how a careful combination of software and hardware can produce an extremely cost-effective solution to a problem.

  8. Automatic Emergence Detection in Complex Systems

    Directory of Open Access Journals (Sweden)

    Eugene Santos

    2017-01-01

    Full Text Available Complex systems consist of multiple interacting subsystems, whose nonlinear interactions can result in unanticipated (emergent system events. Extant systems analysis approaches fail to detect such emergent properties, since they analyze each subsystem separately and arrive at decisions typically through linear aggregations of individual analysis results. In this paper, we propose a quantitative definition of emergence for complex systems. We also propose a framework to detect emergent properties given observations of its subsystems. This framework, based on a probabilistic graphical model called Bayesian Knowledge Bases (BKBs, learns individual subsystem dynamics from data, probabilistically and structurally fuses said dynamics into a single complex system dynamics, and detects emergent properties. Fusion is the central element of our approach to account for situations when a common variable may have different probabilistic distributions in different subsystems. We evaluate our detection performance against a baseline approach (Bayesian Network ensemble on synthetic testbeds from UCI datasets. To do so, we also introduce a method to simulate and a metric to measure discrepancies that occur with shared/common variables. Experiments demonstrate that our framework outperforms the baseline. In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.

  9. System for automatic detection of lung nodules exhibiting growth

    Science.gov (United States)

    Novak, Carol L.; Shen, Hong; Odry, Benjamin L.; Ko, Jane P.; Naidich, David P.

    2004-05-01

    Lung nodules that exhibit growth over time are considered highly suspicious for malignancy. We present a completely automated system for detection of growing lung nodules, using initial and follow-up multi-slice CT studies. The system begins with automatic detection of lung nodules in the later CT study, generating a preliminary list of candidate nodules. Next an automatic system for registering locations in two studies matches each candidate in the later study to its corresponding position in the earlier study. Then a method for automatic segmentation of lung nodules is applied to each candidate and its matching location, and the computed volumes are compared. The output of the system is a list of nodule candidates that are new or have exhibited volumetric growth since the previous scan. In a preliminary test of 10 patients examined by two radiologists, the automatic system identified 18 candidates as growing nodules. 7 (39%) of these corresponded to validated nodules or other focal abnormalities that exhibited growth. 4 of the 7 true detections had not been identified by either of the radiologists during their initial examinations of the studies. This technique represents a powerful method of surveillance that may reduce the probability of missing subtle or early malignant disease.

  10. SYSTEM FOR AUTOMATIC SELECTION OF THE SPEED RATE OF ELECTRIC VEHICLES FOR REDUCING THE POWER CONSUMPTION

    Directory of Open Access Journals (Sweden)

    K. O. Soroka

    2017-06-01

    Full Text Available Purpose. The work is aimed to design a system for automatic selection of the optimal traffic modes and automatic monitoring of the electric energy consumption by electric transport. This automatic system should provide for the minimum energy expenses. Methodology. Current methodologies: 1 mathematical modeling of traffic modes of ground electric vehicles; 2 comparison of modelling results with the statistical monitoring; 3 system development for automatic choice of traffic modes of electric transport with minimal electrical energy consumptions taking into account the given route schedules and the limitations imposed by the general traffic rules. Findings. The authors obtained a mathematical dependency of the energy consumption by electric transport enterprises on the monthly averaged environment temperature was obtained. A system which allows for an automatic selection of the speed limit and provides automatic monitoring of the electrical energy consumption by electric vehicles was proposed in the form of local network, which works together with existing GPS system. Originality. A mathematical model for calculating the motion curves and energy consumption of electric vehicles has been developed. This model takes into account the characteristic values of the motor engine and the steering system, the change of the mass when loading or unloading passengers, the slopes and radii of the roads, the limitations given by the general traffic rules, and other factors. The dependency of the energy consumption on the averaged monthly environment temperature for public electric transport companies has been calculated. Practical value. The developed mathematical model simplifies the calculations of the traffic dynamics and energy consumption. It can be used for calculating the routing maps, for design and upgrade of the power networks, for development of the electricity saving measures. The system simplifies the work of the vehicle driver and allows reducing

  11. SMART VIDEO SURVEILLANCE SYSTEM FOR VEHICLE DETECTION AND TRAFFIC FLOW CONTROL

    Directory of Open Access Journals (Sweden)

    A. A. SHAFIE

    2011-08-01

    Full Text Available Traffic signal light can be optimized using vehicle flow statistics obtained by Smart Video Surveillance Software (SVSS. This research focuses on efficient traffic control system by detecting and counting the vehicle numbers at various times and locations. At present, one of the biggest problems in the main city in any country is the traffic jam during office hour and office break hour. Sometimes it can be seen that the traffic signal green light is still ON even though there is no vehicle coming. Similarly, it is also observed that long queues of vehicles are waiting even though the road is empty due to traffic signal light selection without proper investigation on vehicle flow. This can be handled by adjusting the vehicle passing time implementing by our developed SVSS. A number of experiment results of vehicle flows are discussed in this research graphically in order to test the feasibility of the developed system. Finally, adoptive background model is proposed in SVSS in order to successfully detect target objects such as motor bike, car, bus, etc.

  12. Automatic Water Sensor Window Opening System

    KAUST Repository

    Percher, Michael

    2013-12-05

    A system can automatically open at least one window of a vehicle when the vehicle is being submerged in water. The system can include a water collector and a water sensor, and when the water sensor detects water in the water collector, at least one window of the vehicle opens.

  13. Identification of Conflicts between Transmission and Distribution System Operators when Acquiring Ancillary Services from Electric Vehicles

    DEFF Research Database (Denmark)

    Zecchino, Antonio; Knezovic, Katarina; Marinelli, Mattia

    2017-01-01

    products according to requests coming from both distribution and transmission system operators. The goal of this paper is to provide an identification procedure that is able to detect, identify and catalogue possible conflicts among the involved stakeholders that take place when requesting and/or acquiring...... ancillary services from flexible units. The investigation is carried out considering a 3-area power system which allows to take into account local constraints as well as system-wide needs. As outcome, this paper identifies the conflicts from both a theoretical and a practical point of view, by means...

  14. Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System Data Integration Algorithm.

    Science.gov (United States)

    Nikolic, Dejan; Stojkovic, Nikola; Lekic, Nikola

    2018-04-09

    To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data.

  15. A Semiactive and Adaptive Hybrid Control System for a Tracked Vehicle Hydropneumatic Suspension Based on Disturbance Identification

    Directory of Open Access Journals (Sweden)

    Shousong Han

    2017-01-01

    Full Text Available The riding conditions for a high-speed tracked vehicle are quite complex. To enhance the adaptability of suspension systems to different riding conditions, a semiactive and self-adaptive hybrid control strategy based on disturbance velocity and frequency identification was proposed. A mathematical model of the semiactive, self-adaptive hybrid suspension control system, along with a performance evaluation function, was established. Based on a two-degree-of-freedom (DOF suspension system, the kinematic relations and frequency zero-crossing detection method were defined, and expressions for the disturbance velocity and disturbance frequency of the road were obtained. Optimal scheduling of the semiactive hybrid damping control gain (csky, cground, chybrid and self-adaptive control gain (cv under different disturbances were realized by exploiting the particle swarm multiobjective optimization algorithm. An experimental study using a carefully designed test rig was performed under a number of typical riding conditions of tracked vehicles, and the results showed that the proposed control strategy is capable of accurately recognizing different disturbances, shifting between control modes (semiactive/self-adaptive, and scheduling the damping control gain according to the disturbance identification outcomes; hence, the proposed strategy could achieve a good trade-off between ride comfort and ride safety and efficiently increase the overall performance of the suspension under various riding conditions.

  16. Conflict detection and resolution system architecture for unmanned aerial vehicles in civil airspace

    NARCIS (Netherlands)

    Jenie, Y.I.; van Kampen, E.J.; Ellerbroek, J.; Hoekstra, J.M.

    2015-01-01

    A novel architecture for a general Unmanned Aerial Vehicle (UAV) Conflict Detection and Resolution (CD&R) system, in the context of their integration into the civilian airspace, is proposed in this paper. The architecture consists of layers of safety approaches ,each representing a combination of

  17. Vision-based vehicle detection and tracking algorithm design

    Science.gov (United States)

    Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

    2009-12-01

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

  18. 46 CFR 161.002-10 - Automatic fire detecting system control unit.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting system control unit. 161.002-10...-10 Automatic fire detecting system control unit. (a) General. The fire detecting system control unit... inches) or other audible alarm that has an equivalent sound level and that is mounted at the control unit...

  19. System for identification of microorganism and detection of infectious disorder

    DEFF Research Database (Denmark)

    2013-01-01

    Methods for the identification of microorganisms or infectious disorders are disclosed, comprising obtaining a suitable sample from sources such as persons, animals, plants, food, water or soil. The methods also comprise providing tailored nucleic acid substrate(s) designed to react with a type 1...... topoisomerase from one or more microorganism(s) or infectious agent(s), and incubating said substrate with said sample, or extracts or preparations from the sample, so that the substrate is processed by said topoisomerase if said microorganism(s) or infectious agent(s) is present in the sample. Finally......, processed substrates are identified and potentially quantified by one or more of a range of standard molecular biology methods and read-out systems. The identification and potential quantification of microorganisms and infectious agents, including but not limited to Plasmodium falciparum and Mycobacterium...

  20. Fast and automatic thermographic material identification for the recycling process

    Science.gov (United States)

    Haferkamp, Heinz; Burmester, Ingo

    1998-03-01

    Within the framework of the future closed loop recycling process the automatic and economical sorting of plastics is a decisive element. The at the present time available identification and sorting systems are not yet suitable for the sorting of technical plastics since essential demands, as the realization of high recognition reliability and identification rates considering the variety of technical plastics, can not be guaranteed. Therefore the Laser Zentrum Hannover e.V. in cooperation with the Hoerotron GmbH and the Preussag Noell GmbH has carried out investigations on a rapid thermographic and laser-supported material- identification-system for automatic material-sorting- systems. The automatic identification of different engineering plastics coming from electronic or automotive waste is possible. Identification rates up to 10 parts per second are allowed by the effort from fast IR line scanners. The procedure is based on the following principle: within a few milliseconds a spot on the relevant sample is heated by a CO2 laser. The samples different and specific chemical and physical material properties cause different temperature distributions on their surfaces that are measured by a fast IR-linescan system. This 'thermal impulse response' has to be analyzed by means of a computer system. Investigations have shown that it is possible to analyze more than 18 different sorts of plastics at a frequency of 10 Hz. Crucial for the development of such a system is the rapid processing of imaging data, the minimization of interferences caused by oscillating samples geometries, and a wide range of possible additives in plastics in question. One possible application area is sorting of plastics coming from car- and electronic waste recycling.

  1. Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

    Science.gov (United States)

    Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

    2018-03-01

    Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

  2. An Automatic Optic Disk Detection and Segmentation System using Multi-level Thresholding

    Directory of Open Access Journals (Sweden)

    KARASULU, B.

    2014-05-01

    Full Text Available Optic disk (OD boundary localization is a substantial problem in ophthalmic image processing research area. In order to segment the region of OD, we developed an automatic system which involves a multi-level thresholding. The OD segmentation results of the system in terms of average precision, recall and accuracy for DRIVE database are 98.88%, 99.91%, 98.83%, for STARE database are 98.62%, 97.38%, 96.11%, and for DIARETDB1 database are 99.29%, 99.90%, 99.20%, respectively. The experimental results show that our system works properly on retinal image databases with diseased retinas, diabetic signs, and a large degree of quality variability.

  3. A stereo vision-based obstacle detection system in vehicles

    Science.gov (United States)

    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.

  4. 46 CFR 161.002-9 - Automatic fire detecting system, power supply.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002-9 Automatic fire detecting system, power...

  5. Automatic detection system for multiple region of interest registration to account for posture changes in head and neck radiotherapy

    Science.gov (United States)

    Mencarelli, A.; van Beek, S.; Zijp, L. J.; Rasch, C.; van Herk, M.; Sonke, J.-J.

    2014-04-01

    Despite immobilization of head and neck (H and N) cancer patients, considerable posture changes occur over the course of radiotherapy (RT). To account for the posture changes, we previously implemented a multiple regions of interest (mROIs) registration system tailored to the H and N region for image-guided RT correction strategies. This paper is focused on the automatic segmentation of the ROIs in the H and N region. We developed a fast and robust automatic detection system suitable for an online image-guided application and quantified its performance. The system was developed to segment nine high contrast structures from the planning CT including cervical vertebrae, mandible, hyoid, manubrium of sternum, larynx and occipital bone. It generates nine 3D rectangular-shaped ROIs and informs the user in case of ambiguities. Two observers evaluated the robustness of the segmentation on 188 H and N cancer patients. Bland-Altman analysis was applied to a sub-group of 50 patients to compare the registration results using only the automatically generated ROIs and those manually set by two independent experts. Finally the time performance and workload were evaluated. Automatic detection of individual anatomical ROIs had a success rate of 97%/53% with/without user notifications respectively. Following the notifications, for 38% of the patients one or more structures were manually adjusted. The processing time was on average 5 s. The limits of agreement between the local registrations of manually and automatically set ROIs was comprised between ±1.4 mm, except for the manubrium of sternum (-1.71 mm and 1.67 mm), and were similar to the limits agreement between the two experts. The workload to place the nine ROIs was reduced from 141 s (±20 s) by the manual procedure to 59 s (±17 s) using the automatic method. An efficient detection system to segment multiple ROIs was developed for Cone-Beam CT image-guided applications in the H and N region and is clinically implemented in

  6. Thruster Modelling for Underwater Vehicle Using System Identification Method

    Directory of Open Access Journals (Sweden)

    Mohd Shahrieel Mohd Aras

    2013-05-01

    Full Text Available Abstract This paper describes a study of thruster modelling for a remotely operated underwater vehicle (ROV by system identification using Microbox 2000/2000C. Microbox 2000/2000C is an XPC target machine device to interface between an ROV thruster with the MATLAB 2009 software. In this project, a model of the thruster will be developed first so that the system identification toolbox in MATLAB can be used. This project also presents a comparison of mathematical and empirical modelling. The experiments were carried out by using a mini compressor as a dummy depth pressure applied to a pressure sensor. The thruster model will thrust and submerge until it reaches a set point and maintain the set point depth. The depth was based on pressure sensor measurement. A conventional proportional controller was used in this project and the results gathered justified its selection.

  7. Statistical pattern recognition for automatic writer identification and verification

    NARCIS (Netherlands)

    Bulacu, Marius Lucian

    2007-01-01

    The thesis addresses the problem of automatic person identification using scanned images of handwriting.Identifying the author of a handwritten sample using automatic image-based methods is an interesting pattern recognition problem with direct applicability in the forensic and historic document

  8. Real-time automatic target identification system for air-to-ground targeting

    Science.gov (United States)

    Nicholas, Mike; Wood, Jonathan; Nothard, Jo

    2005-10-01

    Future targeting systems, for manned or unmanned combat aircraft, aim to provide increased mission success and platform survivability by successfully detecting and identifying even difficult targets at very long ranges. One of the key enabling technologies for such systems is robust automatic target identification (ATI), operating on high resolution electro-optic sensor imagery. QinetiQ have developed a real time ATI processor which will be demonstrated with infrared imagery from the Wescam MX15 in airborne trials in summer 2005. This paper describes some of the novel ATI algorithms, the challenges overcome to port the ATI from the laboratory onto a real time system and offers an assessment of likely airborne performance based on analysis of synthetic image sequences.

  9. Automatic Road Gap Detection Using Fuzzy Inference System

    Science.gov (United States)

    Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

    2011-09-01

    Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

  10. Performance Modelling of Automatic Identification System with Extended Field of View

    DEFF Research Database (Denmark)

    Lauersen, Troels; Mortensen, Hans Peter; Pedersen, Nikolaj Bisgaard

    2010-01-01

    This paper deals with AIS (Automatic Identification System) behavior, to investigate the severity of packet collisions in an extended field of view (FOV). This is an important issue for satellite-based AIS, and the main goal is a feasibility study to find out to what extent an increased FOV...

  11. Fault Detection Coverage Quantification of Automatic Test Functions of Digital I and C System in NPPs

    International Nuclear Information System (INIS)

    Choi, Jong Gyun; Lee, Seung Jun; Hur, Seop; Lee, Young Jun; Jang, Seung Cheol

    2011-01-01

    Recently, analog instrument and control (I and C) systems in nuclear power plants (NPPs) have been replaced with digital systems for safer and more efficient operations. Digital I and C systems have adopted various fault-tolerant techniques that help the system correctly and safely perform the specific required functions in spite of the presence of faults. Each fault-tolerant technique has a different inspection period from real-time monitoring to monthly testing. The range covered by each fault-tolerant technique is also different. The digital I and C system, therefore, adopts multiple barriers consisting of various fault-tolerant techniques to increase total fault detection coverage. Even though these fault-tolerant techniques are adopted to ensure and improve the safety of a system, their effects have not been properly considered yet in most PSA models. Therefore, it is necessary to develop an evaluation method that can describe these features of a digital I and C system. Several issues must be considered in the fault coverage estimation of a digital I and C system, and two of them were handled in this work. The first is to quantify the fault coverage of each fault-tolerant technique implemented in the system, and the second is to exclude the duplicated effect of fault-tolerant techniques implemented simultaneously at each level of the system's hierarchy, as a fault occurring in a system might be detected by one or more fault-tolerant techniques. For this work, fault injection experiment was used to obtain the exact relations between faults and multiple barriers of fault-tolerant techniques. This experiment was applied to a bistable processor (BP) of a reactor protection system

  12. An Automatic Traffic Sign Detection and Recognition System Based on Colour Segmentation, Shape Matching, and SVM

    Directory of Open Access Journals (Sweden)

    Safat B. Wali

    2015-01-01

    Full Text Available The main objective of this study is to develop an efficient TSDR system which contains an enriched dataset of Malaysian traffic signs. The developed technique is invariant in variable lighting, rotation, translation, and viewing angle and has a low computational time with low false positive rate. The development of the system has three working stages: image preprocessing, detection, and recognition. The system demonstration using a RGB colour segmentation and shape matching followed by support vector machine (SVM classifier led to promising results with respect to the accuracy of 95.71%, false positive rate (0.9%, and processing time (0.43 s. The area under the receiver operating characteristic (ROC curves was introduced to statistically evaluate the recognition performance. The accuracy of the developed system is relatively high and the computational time is relatively low which will be helpful for classifying traffic signs especially on high ways around Malaysia. The low false positive rate will increase the system stability and reliability on real-time application.

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

    Directory of Open Access Journals (Sweden)

    Baofeng Wang

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

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

    Science.gov (United States)

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

    2017-01-01

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

  15. Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

    Directory of Open Access Journals (Sweden)

    Sang-Il Oh

    2017-01-01

    Full Text Available To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN. The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

  16. MaNIAC-UAV - a methodology for automatic pavement defects detection using images obtained by Unmanned Aerial Vehicles

    Science.gov (United States)

    Henrique Castelo Branco, Luiz; César Lima Segantine, Paulo

    2015-09-01

    Intelligent Transportation Systems - ITS is a set of integrated technologies (Remote Sensing, Image Processing, Communications Systems and others) that aim to offer services and advanced traffic management for the several transportation modes (road, air and rail). Collect data on the characteristics and conditions of the road surface and keep them update is an important and difficult task that needs to be currently managed in order to reduce accidents and vehicle maintenance costs. Nowadays several roads and highways are paved, but usually there is insufficient updated data about current condition and status. There are different types of pavement defects on the roads and to keep them in good condition they should be constantly monitored and maintained according to pavement management strategy. This paper presents a methodology to obtain, automatically, information about the conditions of the highway asphalt pavement. Data collection was done through remote sensing using an UAV (Unmanned Aerial Vehicle) and the image processing and pattern recognition techniques through Geographic Information System.

  17. First tests of a multi-wavelength mini-DIAL system for the automatic detection of greenhouse gases

    Science.gov (United States)

    Parracino, S.; Gelfusa, M.; Lungaroni, M.; Murari, A.; Peluso, E.; Ciparisse, J. F.; Malizia, A.; Rossi, R.; Ventura, P.; Gaudio, P.

    2017-10-01

    Considering the increase of atmospheric pollution levels in our cities, due to emissions from vehicles and domestic heating, and the growing threat of terrorism, it is necessary to develop instrumentation and gather know-how for the automatic detection and measurement of dangerous substances as quickly and far away as possible. The Multi- Wavelength DIAL, an extension of the conventional DIAL technique, is one of the most powerful remote sensing methods for the identification of multiple substances and seems to be a promising solution compared to existing alternatives. In this paper, first in-field tests of a smart and fully automated Multi-Wavelength mini-DIAL will be presented and discussed in details. The recently developed system, based on a long-wavelength infrared (IR-C) CO2 laser source, has the potential of giving an early warning, whenever something strange is found in the atmosphere, followed by identification and simultaneous concentration measurements of many chemical species, ranging from the most important Greenhouse Gases (GHG) to other harmful Volatile Organic Compounds (VOCs). Preliminary studies, regarding the fingerprint of the investigated substances, have been carried out by cross-referencing database of infrared (IR) spectra, obtained using in-cell measurements, and typical Mixing Ratios in the examined region, extrapolated from the literature. First experiments in atmosphere have been performed into a suburban and moderately-busy area of Rome. Moreover, to optimize the automatic identification of the harmful species to be recognized on the basis of in cell measurements of the absorption coefficient spectra, an advanced multivariate statistical method for classification has been developed and tested.

  18. CASTE (Course Assembly System and Tutorial Environment) and CVI: (Combat Vehicle Identification) A First Application of an Intelligent Tutorial System to Combat Vehicle Identification.

    Science.gov (United States)

    1984-09-01

    Maturana , and Uribe’s (1974) living systems theory, and the new theoretical foundations for post-Einsteinian physics (Zukav, 1979) .’ Pedagogy...emerges as the same system. Maturana (1981) claims autopoiesis to be necessary and sufficient for a system to be living; in our case, the system is...System Research and Applied Epistemology. Montreal: Concordia University. Maturana , H. R. (1981). Autopoiesis. In M. Zeleny (Ed.), Autopoiesis: A

  19. Tidal Analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

    Science.gov (United States)

    2017-01-01

    referred to as static since it changes very infrequently, is manually generated. This is a two-digit code, described in the ITU technical ...develops innovative solutions in civil and military engineering, geospatial sciences, water resources, and environmental sciences for the Army, the...Department of Defense, civilian agencies, and our nation’s public good. Find out more at www.erdc.usace.army.mil. To search for other technical

  20. Tidal analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

    Science.gov (United States)

    2017-01-01

    Atmospheric Administration (NOAA) tides and currents applications program interface ( API ): http://tidesandcurrents.noaa.gov/ api /. AIS data AIS...files, organized by location. The data were processed using the Python programming language (van Rossum and Drake 2001), the Pandas data analysis...McKinney, W. 2012. Python for data analysis. Sebastopol, CA: O’Reilly Media, Inc. Mitchell, K. N. April. 2012. A review of coastal navigation asset

  1. Automatic guided vehicles fleet size optimization for flexible manufacturing system by grey wolf optimization algorithm

    Directory of Open Access Journals (Sweden)

    V. K. Chawla

    2018-02-01

    Full Text Available Automatic guided vehicle system (AGVs plays a vital role in material handling operations for a flexible manufacturing system (FMS.Optimum AGVs fleet size selection is one of the most sig-nificant decisions in effective design and control of automated material handling system. The fleet size estimation and optimization of AGVs requires an in-depth understanding of the various factors that AGVs in the FMS relies on. In this paper, an investigation for fleet size optimization of AGVs in different layouts of FMS by application of the analytical method and grey wolf optimization al-gorithm (GWO is carried out. Layout design is one of the significant factors for optimization of AGV’s fleet size in any FMS. Results yield from analytical and grey wolf optimization algorithm are compared and validated for the different sizes of FMS layouts by computational experiments.

  2. Exploration of available feature detection and identification systems and their performance on radiographs

    Science.gov (United States)

    Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

    2016-10-01

    Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

  3. Image enhancement and color constancy for a vehicle-mounted change detection system

    Science.gov (United States)

    Tektonidis, Marco; Monnin, David

    2016-10-01

    Vehicle-mounted change detection systems allow to improve situational awareness on outdoor itineraries of inter- est. Since the visibility of acquired images is often affected by illumination effects (e.g., shadows) it is important to enhance local contrast. For the analysis and comparison of color images depicting the same scene at different time points it is required to compensate color and lightness inconsistencies caused by the different illumination conditions. We have developed an approach for image enhancement and color constancy based on the center/surround Retinex model and the Gray World hypothesis. The combination of the two methods using a color processing function improves color rendition, compared to both methods. The use of stacked integral images (SII) allows to efficiently perform local image processing. Our combined Retinex/Gray World approach has been successfully applied to image sequences acquired on outdoor itineraries at different time points and a comparison with previous Retinex-based approaches has been carried out.

  4. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features

    Directory of Open Access Journals (Sweden)

    Mustain Billah

    2017-01-01

    Full Text Available Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW features and convolutional neural network (CNN features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM. Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%.

  5. Evaluation of a direct method for the identification and antibiotic susceptibility assessment of microrganisms isolated from blood cultures by automatic systems

    Directory of Open Access Journals (Sweden)

    Sergio Frugoni

    2008-03-01

    Full Text Available The purpose of blood cultures in the septic patient is to address a correct therapeutic approach. Identification and antibiotic susceptibility test carried out directly from the bottle may give important information in short time.The introduction of the automatic instrumentation has improved the discovering of pathogens in the blood, however the elapsing time between the positive detection and the microbiological report is still along. Is the evaluation of this study a fast, easy, cheap method to be applied to the routine, which could reduce the response time in the bacteraemia diagnosis.The automatic systems Vitek Senior (bioMérieux, and Vitek 2 (bioMérieux were used at Pio Albergo Trivulzio (Centre1 and at Istituto dei Tumori (Centre2 respectivetly.To remove blood cells, 7 ml. of the culture has been moved by vacuum sampling in a test tube and centrifuged for 10 minutes at 1000 rpm the supernatant has been further centrifuged for 10 minutes at 3000 rpm.0.5 ml. of BHI has been added to the pellet o sediment.The concentration of bacterial suspension has been fit for the inoculation. At the same time has been prepared standard cultures in suitable culture media were carried out for comparison. In the centro1 and centro2 have been isolated and identify respectively 63 and 31 Gram negative, and, 32 and 40 gram positive microorganisms have been isolated and identify in the Centre1 and Centre2 respectively.The identification Gram-negative and Gram positive microorganisms showed an agreement of 100% and 86.2% and 93.3% and 65.78% respectively between the direct and the standard method. For antibiotic susceptibility tests, 903 (Centre1 and 491 (Centre2 and 396 and 509 compounds were totally assessed in Gram negative and Gram positive bacteria respectively.The analysis has highlighted that: Centre1 has reported 0.30% very major errors (GE, 0.92% major errors (EM, 1.23% minor errors (Em. Centre 2 showed 0.57% very major errors (GE, 0.09% major errors

  6. Spike detection II: automatic, perception-based detection and clustering.

    Science.gov (United States)

    Wilson, S B; Turner, C A; Emerson, R G; Scheuer, M L

    1999-03-01

    We developed perception-based spike detection and clustering algorithms. The detection algorithm employs a novel, multiple monotonic neural network (MMNN). It is tested on two short-duration EEG databases containing 2400 spikes from 50 epilepsy patients and 10 control subjects. Previous studies are compared for database difficulty and reliability and algorithm accuracy. Automatic grouping of spikes via hierarchical clustering (using topology and morphology) is visually compared with hand marked grouping on a single record. The MMNN algorithm is found to operate close to the ability of a human expert while alleviating problems related to overtraining. The hierarchical and hand marked spike groupings are found to be strikingly similar. An automatic detection algorithm need not be as accurate as a human expert to be clinically useful. A user interface that allows the neurologist to quickly delete artifacts and determine whether there are multiple spike generators is sufficient.

  7. 46 CFR 161.002-8 - Automatic fire detecting systems, general requirements.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting systems, general requirements... Systems § 161.002-8 Automatic fire detecting systems, general requirements. (a) General. An automatic fire... combined with other power failure alarm systems when specifically approved. (b) [Reserved] [21 FR 9032, Nov...

  8. Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2012-01-01

    The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy...

  9. Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

    Science.gov (United States)

    Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

    2013-11-01

    The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

  10. Combining Facial Recognition, Automatic License Plate Readers and Closed Circuit Television to Create an Interstate Identification System for Wanted Subjects

    Science.gov (United States)

    2015-12-01

    Safety and Motor Vehicles, “DAVID—Law Enforcement’s Best Information Tool,” Legal Highway III, no. 1 (Spring/Summer, 2013): 1. 14 all phases of...Regional Research 28, no. 1 (2004): 201–211. 16 on a shopping mall’s CCTV system.34 This heinous crime demonstrated the need for surveillance... addiction -counseling meetings, doctors’ offices, health clinics or even staging areas for political protest.”110 This article could provide background

  11. Multispectral image fusion for vehicle identification and threat analysis

    Science.gov (United States)

    Zheng, Yufeng; Blasch, Erik

    2016-05-01

    Unauthorized vehicles become an increasing threat to US facilities and locations especially overseas. Vehicle detection is a well-studied area. However, vehicle identification and intension analysis have not been sufficiently investigated. We propose to use multispectral (visible, thermal) images (1) to match the vehicle types with the registered (or authorized) vehicle types; (2) to analyze the vehicle moving patterns, (3) and study methods to utilize open information such as GPS and traffic information. When a vehicle is either permitted to access to the facility, or subjected to further manual inspection (scrutiny), the additional information (e.g., text) can be compared against the imagery features. We use information fusion (at image, feature, and score level) and neural network to increase vehicle matching accuracy. For the vehicle moving patterns, we will classify them as "normal" and "abnormal" by using driving speed, acceleration, stop, zig-zag, etc. The methods would support directions in physical and human-based sensor fusion, patterns of life (POL) analysis, and contextual-enhanced information fusion.

  12. Person categorization and automatic racial stereotyping effects on weapon identification.

    Science.gov (United States)

    Jones, Christopher R; Fazio, Russell H

    2010-08-01

    Prior stereotyping research provides conflicting evidence regarding the importance of person categorization along a particular dimension for the automatic activation of a stereotype corresponding to that dimension. Experiment 1 replicated a racial stereotyping effect on object identification and examined whether it could be attenuated by encouraging categorization by age. Experiment 2 employed socially complex person stimuli and manipulated whether participants categorized spontaneously or by race. In Experiment 3, the distinctiveness of the racial dimension was manipulated by having Black females appear in the context of either Black males or White females. The results indicated that conditions fostering categorization by race consistently produced automatic racial stereotyping and that conditions fostering nonracial categorization can eliminate automatic racial stereotyping. Implications for the relation between automatic stereotype activation and dimension of categorization are discussed.

  13. Vision-based multi-scaled vehicle detection and distance relevant mix tracking for driver assistance system

    Science.gov (United States)

    Gu, Qin; Yang, Jianyu; Zhai, Yuqiang; Kong, Lingjiang

    2015-04-01

    This paper aims to improve the robustness of vision-based multi-scaled vehicle detection and tracking for an actual driver assistance system. Considering the problem of discontinuity of detection and tracking for multi-scaled vehicles especially in an ultra-close area, we propose a novel detection framework which concludes short-range local feature (license plate) detection and long-range skeleton detection. Specially, the rear license plate can be located accurately by introducing a multi-scaled morphological operator and analyzing the color information. Then, vehicles in a long supervising range can be detected with a Look-up Table-based AdaBoost classifier synchronically. Finally, an inverse perspective mapping-based tracking strategy is proposed to unite the location results in the framework. It is proved to make up the leak vehicle detection in the near supervising area and improve the robustness of tracking. The accuracy of license-based detection and the robust mix tracking have both been testified in several groups of experiments.

  14. Automatic Detect and Trace of Solar Filaments

    Science.gov (United States)

    Fang, Cheng; Chen, P. F.; Tang, Yu-hua; Hao, Qi; Guo, Yang

    We developed a series of methods to automatically detect and trace solar filaments in solar Hα images. The programs are able to not only recognize filaments and determine their properties, such as the position, the area and other relevant parameters, but also to trace the daily evolution of the filaments. For solar full disk Hα images, the method consists of three parts: first, preprocessing is applied to correct the original images; second, the Canny edge-detection method is used to detect the filaments; third, filament properties are recognized through the morphological operators. For each Hα filament and its barb features, we introduced the unweighted undirected graph concept and adopted Dijkstra shortest-path algorithm to recognize the filament spine; then, using polarity inversion line shift method for measuring the polarities in both sides of the filament to determine the filament axis chirality; finally, employing connected components labeling method to identify the barbs and calculating the angle between each barb and spine to indicate the barb chirality. Our algorithms are applied to the observations from varied observatories, including the Optical & Near Infrared Solar Eruption Tracer (ONSET) in Nanjing University, Mauna Loa Solar Observatory (MLSO) and Big Bear Solar Observatory (BBSO). The programs are demonstrated to be effective and efficient. We used our method to automatically process and analyze 3470 images obtained by MLSO from January 1998 to December 2009, and a butterfly diagram of filaments is obtained. It shows that the latitudinal migration of solar filaments has three trends in the Solar Cycle 23: The drift velocity was fast from 1998 to the solar maximum; after the solar maximum, it became relatively slow and after 2006, the migration became divergent, signifying the solar minimum. About 60% filaments with the latitudes larger than 50 degree migrate towards the Polar Regions with relatively high velocities, and the latitudinal migrating

  15. Automatic detection and visualisation of MEG ripple oscillations in epilepsy

    Directory of Open Access Journals (Sweden)

    Nicole van Klink

    2017-01-01

    Full Text Available High frequency oscillations (HFOs, 80–500 Hz in invasive EEG are a biomarker for the epileptic focus. Ripples (80–250 Hz have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

  16. Alternative vehicle detection technologies for traffic signal systems : technical report.

    Science.gov (United States)

    2009-02-01

    Due to the well-documented problems associated with inductive loops, most jurisdictions have : replaced many intersection loops with video image vehicle detection systems (VIVDS). While VIVDS : have overcome some of the problems with loops such as tr...

  17. Piloted Simulation Evaluation of a Model-Predictive Automatic Recovery System to Prevent Vehicle Loss of Control on Approach

    Science.gov (United States)

    Litt, Jonathan S.; Liu, Yuan; Sowers, Thomas S.; Owen, A. Karl; Guo, Ten-Huei

    2014-01-01

    This paper describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.

  18. Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System

    Science.gov (United States)

    Velazquez-Pupo, Roxana; Sierra-Romero, Alberto; Torres-Roman, Deni; Shkvarko, Yuriy V.; Romero-Delgado, Misael

    2018-01-01

    This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. PMID:29382078

  19. Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

    Science.gov (United States)

    Sa, Qila; Wang, Zhihui

    2018-03-01

    At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

  20. Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles

    Science.gov (United States)

    Grymin, David J.

    This dissertation addresses motion planning, modeling, and feedback control for autonomous vehicle systems. A hierarchical approach for motion planning and control of nonlinear systems operating in obstacle environments is presented. To reduce computation time during the motion planning process, dynamically feasible trajectories are generated in real-time through concatenation of pre-specified motion primitives. The motion planning task is posed as a search over a directed graph, and the applicability of informed graph search techniques is investigated. Specifically, a locally greedy algorithm with effective backtracking ability is developed and compared to weighted A* search. The greedy algorithm shows an advantage with respect to solution cost and computation time when larger motion primitive libraries that do not operate on a regular state lattice are utilized. Linearization of the nonlinear system equations about the motion primitive library results in a hybrid linear time-varying model, and an optimal control algorithm using the l 2-induced norm as the performance measure is applied to ensure that the system tracks the desired trajectory. The ability of the resulting controller to closely track the trajectory obtained from the motion planner, despite various disturbances and uncertainties, is demonstrated through simulation. Additionally, an approach for obtaining dynamically feasible reference trajectories and feedback controllers for a small unmanned aerial vehicle (UAV) based on an aerodynamic model derived from flight tests is presented. The modeling approach utilizes the two step method (TSM) with stepwise multiple regression to determine relevant explanatory terms for the aerodynamic models. Dynamically feasible trajectories are then obtained through the solution of an optimal control problem using pseudospectral optimal control software. Discretetime feedback controllers are then obtained to regulate the vehicle along the desired reference trajectory

  1. Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

    Directory of Open Access Journals (Sweden)

    Yang-Lang Chang

    2011-07-01

    Full Text Available This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions.

  2. Automatic detection and severity measurement of eczema using image processing.

    Science.gov (United States)

    Alam, Md Nafiul; Munia, Tamanna Tabassum Khan; Tavakolian, Kouhyar; Vasefi, Fartash; MacKinnon, Nick; Fazel-Rezai, Reza

    2016-08-01

    Chronic skin diseases like eczema may lead to severe health and financial consequences for patients if not detected and controlled early. Early measurement of disease severity, combined with a recommendation for skin protection and use of appropriate medication can prevent the disease from worsening. Current diagnosis can be costly and time-consuming. In this paper, an automatic eczema detection and severity measurement model are presented using modern image processing and computer algorithm. The system can successfully detect regions of eczema and classify the identified region as mild or severe based on image color and texture feature. Then the model automatically measures skin parameters used in the most common assessment tool called "Eczema Area and Severity Index (EASI)," by computing eczema affected area score, eczema intensity score, and body region score of eczema allowing both patients and physicians to accurately assess the affected skin.

  3. Automatic hearing loss detection system based on auditory brainstem response

    International Nuclear Information System (INIS)

    Aldonate, J; Mercuri, C; Reta, J; Biurrun, J; Bonell, C; Gentiletti, G; Escobar, S; Acevedo, R

    2007-01-01

    Hearing loss is one of the pathologies with the highest prevalence in newborns. If it is not detected in time, it can affect the nervous system and cause problems in speech, language and cognitive development. The recommended methods for early detection are based on otoacoustic emissions (OAE) and/or auditory brainstem response (ABR). In this work, the design and implementation of an automated system based on ABR to detect hearing loss in newborns is presented. Preliminary evaluation in adults was satisfactory

  4. Implementation Of Automatic Wiper Speed Control And Headlight Modes Control Systems Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    ThetKoKo

    2015-07-01

    Full Text Available Abstract This research paper describes the design and simulation of the automatic wiper speed and headlight modes controllers using fuzzy logic. This proposed system consists of a fuzzy logic controller to control a cars wiper speed and headlight modes. The automatic wiper system detects the rain and its intensity. And according to the rain intensity the wiper speed is automatically controlled. Headlight modes automatically changes either from low beam mode to high beam mode or form high beam mode to low beam mode depending on the light intensity from the other vehicle coming from the opposite direction. The system comprises of PIC impedance sensor piezoelectric vibration sensor LDR headlamps and a DC motor to accurate the windshield wiper. Piezoelectric sensor is used to detect the rain intensity which is based on the piezoelectric effect. MATLAB software is used to achieve the designed goal.

  5. Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

    Science.gov (United States)

    Brennan, Shane; Bajracharya, Max; Matthies, Larry H.; Howard, Andrew B.

    2012-01-01

    Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

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

    Science.gov (United States)

    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.

  7. Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

    Science.gov (United States)

    Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

    2017-05-01

    Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

  8. Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

    Science.gov (United States)

    Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

    2017-10-15

    Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

  9. X-ray based stem detection in an automatic tomato weeding system

    Science.gov (United States)

    A stem detection system was developed for automatic weed control in transplanted tomato fields. A portable x-ray source projected an x-ray beam perpendicular to the crop row and parallel to the soil surface. The plant’s main stem absorbs x-ray energy, decreasing the detected signal and allowing stem...

  10. Multi-Perspective Vehicle Detection and Tracking

    DEFF Research Database (Denmark)

    Dueholm, Jacob Velling; Kristoffersen, Miklas Strøm; Satzoda, Ravi K.

    2016-01-01

    The research community has shown significant improvements in both vision-based detection and tracking of vehicles, working towards a high level understanding of on-road maneuvers. Behaviors of surrounding vehicles in a highway environment is found as an interesting starting point, of why...... purposes to be used as traditional detection and tracking, together with tracking of vehicles across perspectives. Each of the four perspectives have been annotated, resulting in more than 4000 bounding boxes in order to evaluate and compare novel methods....

  11. A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

    Science.gov (United States)

    D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

    1993-01-01

    A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

  12. Real-time people and vehicle detection from UAV imagery

    Science.gov (United States)

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

    2011-01-01

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

  13. System for Automatic Detection and Analysis of Targets in FMICW Radar Signal

    Czech Academy of Sciences Publication Activity Database

    Rejfek, Luboš; Mošna, Zbyšek; Urbář, Jaroslav; Koucká Knížová, Petra

    2016-01-01

    Roč. 67, č. 1 (2016), s. 36-41 ISSN 1335-3632 R&D Projects: GA ČR(CZ) GAP209/12/2440; GA ČR(CZ) GA15-24688S Institutional support: RVO:68378289 Keywords : power spectral density (PSD) * FMICW radar * Doppler measurement * thresholding * false alert detection Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.483, year: 2016 http://iris.elf.stuba.sk/JEEEC/data/pdf/1_116-05.pdf

  14. An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments

    Directory of Open Access Journals (Sweden)

    Xiaojie Sun

    2018-01-01

    Full Text Available In recent years, unmanned surface vehicles (USVs have received notable attention because of their many advantages in civilian and military applications. To improve the autonomy of USVs, this paper describes a complete automatic navigation system (ANS with a path planning subsystem (PPS and collision avoidance subsystem (CAS. The PPS based on the dynamic domain tunable fast marching square (DTFMS method is able to build an environment model from a real electronic chart, where both static and dynamic obstacles are well represented. By adjusting the S a t u r a t i o n , the generated path can be changed according to the requirements for security and path length. Then it is used as a guidance trajectory for the CAS through a dynamic target point. In the CAS, according to finite control set model predictive control (FCS-MPC theory, a collision avoidance control algorithm is developed to track trajectory and avoid collision based on a three-degree of freedom (DOF planar motion model of USV. Its target point and security evaluation come from the planned path and environmental model of the PPS. Moreover, the prediction trajectory of the CAS can guide changes in the dynamic domain model of the vessel itself. Finally, the system has been tested and validated using the situations of three types of encounters in a realistic sea environment.

  15. System automation for a bacterial colony detection and identification instrument via forward scattering

    International Nuclear Information System (INIS)

    Bae, Euiwon; Hirleman, E Daniel; Aroonnual, Amornrat; Bhunia, Arun K; Robinson, J Paul

    2009-01-01

    A system design and automation of a microbiological instrument that locates bacterial colonies and captures the forward-scattering signatures are presented. The proposed instrument integrates three major components: a colony locator, a forward scatterometer and a motion controller. The colony locator utilizes an off-axis light source to illuminate a Petri dish and an IEEE1394 camera to capture the diffusively scattered light to provide the number of bacterial colonies and two-dimensional coordinate information of the bacterial colonies with the help of a segmentation algorithm with region-growing. Then the Petri dish is automatically aligned with the respective centroid coordinate with a trajectory optimization method, such as the Traveling Salesman Algorithm. The forward scatterometer automatically computes the scattered laser beam from a monochromatic image sensor via quadrant intensity balancing and quantitatively determines the centeredness of the forward-scattering pattern. The final scattering signatures are stored to be analyzed to provide rapid identification and classification of the bacterial samples

  16. A high-throughput multiplex genetic detection system for Helicobacter pylori identification, virulence and resistance analysis.

    Science.gov (United States)

    Hu, Binjie; Zhao, Fuju; Wang, Shiwen; Olszewski, Michal A; Bian, Haipeng; Wu, Yong; Kong, Mimi; Xu, Lingli; Miao, Yingxin; Fang, Yi; Yang, Changqing; Zhao, Hu; Zhang, Yanmei

    2016-10-01

    We established a high-throughput multiplex genetic detection system (HMGS) for identification of Helicobacter pylori with concomitant analysis of virulence and drug resistance. Confirmed 132 H. pylori cultures from gastric biopsies were screened by 20-gene site-HMGS, sequencing and E-test. HMGS was highly sensitive and specific for H. pylori identification. Concordance rate between HMGS and sequencing averaged 94.5% (virulence genes) and 97.3% (resistance genes). Observed resistance rates to four mainstream antibiotics were high, except for amoxicillin. Significant association between virulence genotype and risks for specific gastrointestinal diseases was found for five genes. Metronidazole resistance in peptic ulcer patients was significantly higher. HMGS is an effective method for H. pylori identification and analysis of virulence and drug resistance.

  17. Use of Medical Metered Dose Inhalers for Functionality Testing of Bioaerosol Detection and Identification Systems

    Science.gov (United States)

    2012-05-01

    testing of two near-real-time UV bioaerosol detectors. Aerosol generated from one actuation of a bioMDD containing 1 µm fluorescently tagged PSLs...resulted in complete alarming. 26 5. RECOMMENDATIONS In general , bioMDDs should be suitable for testing functionality of bioaerosol ... BIOAEROSOL DETECTION AND IDENTIFICATION SYSTEMS ECBC-TR-964 Jana Kesavan Deborah R. Schepers Jerold R. Bottiger RESEARCH AND TECHNOLOGY

  18. A Structurally-Integrated Ice Detection and De-Icing System for Unmanned Air Vehicles Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Unmanned air vehicles (UAVs) are becoming more prevalent for Suborbital Scientific Earth Exploration, which often involves high altitude, long endurance flight...

  19. Automatic identification of species with neural networks

    Directory of Open Access Journals (Sweden)

    Andrés Hernández-Serna

    2014-11-01

    Full Text Available A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.

  20. Development, modeling and research of the system of automatic control and equalization of the charge state of a battery pack of a hybrid engine of a vehicle

    Science.gov (United States)

    Bakhmutov, S.; Sizov, Y.; Kim, M.

    2018-02-01

    The article is devoted to the topical problem of developing effective means of monitoring and leveling the charge state of batteries in a power unit of hybrid and electric cars. A system for automatic control and equalization of the charge state of a battery pack of a combined power plant, the originality of which is protected by the Russian Federation patent, is developed and described. A distinctive feature of the device is the possibility of using it both in conditions of charging (power consumption) and in operating conditions (energy recovery). The device is characterized by high reliability, simplicity of the circuit-making solution, low self-consumption and low cost. To test the efficiency of the proposed device, its computer simulation and experimental research were carried out. As a result of multi factorial experiment, a regression equation has been obtained which makes it possible to judge the high efficiency of detecting the degree of inhomogeneity of controlled batteries with respect to the parameters of an equivalent replacement circuit: voltage, internal resistance and capacitance in the magnitude of the obtained coefficients of influence of each of these factors, and also take into account the effects of their pair interactions.

  1. Prototype Design and Application of a Semi-circular Automatic Parking System

    OpenAIRE

    Atacak, Ismail; Erdogdu, Ertugrul

    2017-01-01

    Nowadays, with the increasing population in urban areas, the number of vehicles used in traffic has also increased in these areas. This has brought with it major problems that are caused by insufficient parking areas, in terms of traffic congestion, drivers and environment. In this study, in order to overcome these problems, a multi-storey automatic parking system that automatically performs vehicle recognition, vehicle parking, vehicle delivery and pricing processes has been designed and the...

  2. Video monitoring of visible atmospheric emissions: from a manual device to a new fully automatic detection and classification device; Video surveillance des rejets atmospheriques d'un site siderurgique: d'un systeme manuel a la detection automatique

    Energy Technology Data Exchange (ETDEWEB)

    Bardet, I.; Ryckelynck, F.; Desmonts, T. [Sollac, 59 - Dunkerque (France)

    1999-11-01

    Complete text of publication follows: the context of strong local sensitivity to dust emissions from an integrated steel plant justifies the monitoring of the emissions of abnormally coloured smokes from this plant. In a first step, the watch is done 'visually' by screening and counting the puff emissions through a set of seven cameras and video recorders. The development of a new device making automatic picture analysis allowed to render the inspection automatic. The new system detects and counts the incidents and sends an alarm to the process operator. This way for automatic detection can be extended, after some tests, to other uses in the environmental field. (authors)

  3. ATLANTIDES: Automatic Configuration for Alert Verification in Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Crispo, B.; Etalle, Sandro

    2008-01-01

    We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

  4. Vehicle Tracking System, Vehicle Infrastructure Provided with Vehicle Tracking System and Method for Tracking

    NARCIS (Netherlands)

    Papp, Z.; Doodeman, G.J.N.; Nelisse, M.W.; Sijs, J.; Theeuwes, J.A.C.; Driessen, B.J.F.

    2010-01-01

    A vehicle tracking system is described comprising - a plurality of sensor nodes (10) that each provide a message (D) indicative for an occupancy status of a detection area of an vehicle infrastructure monitored by said sensor node, said sensor nodes (10) being arranged in the vehicle infrastructure

  5. Comparing Automatic CME Detections in Multiple LASCO and SECCHI Catalogs

    International Nuclear Information System (INIS)

    Hess, Phillip; Colaninno, Robin C.

    2017-01-01

    With the creation of numerous automatic detection algorithms, a number of different catalogs of coronal mass ejections (CMEs) spanning the entirety of the Solar and Heliospheric Observatory ( SOHO ) Large Angle Spectrometric Coronagraph (LASCO) mission have been created. Some of these catalogs have been further expanded for use on data from the Solar Terrestrial Earth Observatory ( STEREO ) Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) as well. We compare the results from different automatic detection catalogs (Solar Eruption Event Detection System (SEEDS), Computer Aided CME Tracking (CACTus), and Coronal Image Processing (CORIMP)) to ensure the consistency of detections in each. Over the entire span of the LASCO catalogs, the automatic catalogs are well correlated with one another, to a level greater than 0.88. Focusing on just periods of higher activity, these correlations remain above 0.7. We establish the difficulty in comparing detections over the course of LASCO observations due to the change in the instrument image cadence in 2010. Without adjusting catalogs for the cadence, CME detection rates show a large spike in cycle 24, despite a notable drop in other indices of solar activity. The output from SEEDS, using a consistent image cadence, shows that the CME rate has not significantly changed relative to sunspot number in cycle 24. These data, and mass calculations from CORIMP, lead us to conclude that any apparent increase in CME rate is a result of the change in cadence. We study detection characteristics of CMEs, discussing potential physical changes in events between cycles 23 and 24. We establish that, for detected CMEs, physical parameters can also be sensitive to the cadence.

  6. Comparing Automatic CME Detections in Multiple LASCO and SECCHI Catalogs

    Energy Technology Data Exchange (ETDEWEB)

    Hess, Phillip [NRC Research Associate, U.S. Naval Research Laboratory, Washington, DC (United States); Colaninno, Robin C., E-mail: phillip.hess.ctr@nrl.navy.mil, E-mail: robin.colaninno@nrl.navy.mil [U.S. Naval Research Laboratory, Washington, DC (United States)

    2017-02-10

    With the creation of numerous automatic detection algorithms, a number of different catalogs of coronal mass ejections (CMEs) spanning the entirety of the Solar and Heliospheric Observatory ( SOHO ) Large Angle Spectrometric Coronagraph (LASCO) mission have been created. Some of these catalogs have been further expanded for use on data from the Solar Terrestrial Earth Observatory ( STEREO ) Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) as well. We compare the results from different automatic detection catalogs (Solar Eruption Event Detection System (SEEDS), Computer Aided CME Tracking (CACTus), and Coronal Image Processing (CORIMP)) to ensure the consistency of detections in each. Over the entire span of the LASCO catalogs, the automatic catalogs are well correlated with one another, to a level greater than 0.88. Focusing on just periods of higher activity, these correlations remain above 0.7. We establish the difficulty in comparing detections over the course of LASCO observations due to the change in the instrument image cadence in 2010. Without adjusting catalogs for the cadence, CME detection rates show a large spike in cycle 24, despite a notable drop in other indices of solar activity. The output from SEEDS, using a consistent image cadence, shows that the CME rate has not significantly changed relative to sunspot number in cycle 24. These data, and mass calculations from CORIMP, lead us to conclude that any apparent increase in CME rate is a result of the change in cadence. We study detection characteristics of CMEs, discussing potential physical changes in events between cycles 23 and 24. We establish that, for detected CMEs, physical parameters can also be sensitive to the cadence.

  7. Corpus analysis and automatic detection of emotion-including keywords

    Science.gov (United States)

    Yuan, Bo; He, Xiangqing; Liu, Ying

    2013-12-01

    Emotion words play a vital role in many sentiment analysis tasks. Previous research uses sentiment dictionary to detect the subjectivity or polarity of words. In this paper, we dive into Emotion-Inducing Keywords (EIK), which refers to the words in use that convey emotion. We first analyze an emotion corpus to explore the pragmatic aspects of EIK. Then we design an effective framework for automatically detecting EIK in sentences by utilizing linguistic features and context information. Our system outperforms traditional dictionary-based methods dramatically in increasing Precision, Recall and F1-score.

  8. SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, J [Washington University in St Louis, Taian, Shandong (China); Yang, D [Washington University School of Medicine, St Louis, MO (United States)

    2015-06-15

    Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from

  9. SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

    International Nuclear Information System (INIS)

    Qiu, J; Yang, D

    2015-01-01

    Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from

  10. Hydrodynamic Coefficients Identification and Experimental Investigation for an Underwater Vehicle

    Directory of Open Access Journals (Sweden)

    Shaorong XIE

    2014-02-01

    Full Text Available Hydrodynamic coefficients are the foundation of unmanned underwater vehicles modeling and controller design. In order to reduce identification complexity and acquire necessary hydrodynamic coefficients for controllers design, the motion of the unmanned underwater vehicle was separated into vertical motion and horizontal motion models. Hydrodynamic coefficients were regarded as mapping parameters from input forces and moments to output velocities and acceleration of the unmanned underwater vehicle. The motion models of the unmanned underwater vehicle were nonlinear and Genetic Algorithm was adopted to identify those hydrodynamic coefficients. To verify the identification quality, velocities and acceleration of the unmanned underwater vehicle was measured using inertial sensor under the same conditions as Genetic Algorithm identification. Curves similarity between measured velocities and acceleration and those identified by Genetic Algorithm were used as optimizing standard. It is found that the curves similarity were high and identified hydrodynamic coefficients of the unmanned underwater vehicle satisfied the measured motion states well.

  11. Automatic detection and classification of leukocytes using convolutional neural networks.

    Science.gov (United States)

    Zhao, Jianwei; Zhang, Minshu; Zhou, Zhenghua; Chu, Jianjun; Cao, Feilong

    2017-08-01

    The detection and classification of white blood cells (WBCs, also known as Leukocytes) is a hot issue because of its important applications in disease diagnosis. Nowadays the morphological analysis of blood cells is operated manually by skilled operators, which results in some drawbacks such as slowness of the analysis, a non-standard accuracy, and the dependence on the operator's skills. Although there have been many papers studying the detection of WBCs or classification of WBCs independently, few papers consider them together. This paper proposes an automatic detection and classification system for WBCs from peripheral blood images. It firstly proposes an algorithm to detect WBCs from the microscope images based on the simple relation of colors R, B and morphological operation. Then a granularity feature (pairwise rotation invariant co-occurrence local binary pattern, PRICoLBP feature) and SVM are applied to classify eosinophil and basophil from other WBCs firstly. Lastly, convolution neural networks are used to extract features in high level from WBCs automatically, and a random forest is applied to these features to recognize the other three kinds of WBCs: neutrophil, monocyte and lymphocyte. Some detection experiments on Cellavison database and ALL-IDB database show that our proposed detection method has better effect almost than iterative threshold method with less cost time, and some classification experiments show that our proposed classification method has better accuracy almost than some other methods.

  12. Intelligent Traffic Control System Implementation for Traffic Violation Control, Congestion Control and Stolen Vehicle Detection

    Directory of Open Access Journals (Sweden)

    Swarup Suresh Kulkarni

    2017-07-01

    Full Text Available Traffic is significant issue in our nation, particularly in urban ranges. Aftereffect of this, activity clog issue happens. Crisis vehicle like rescue vehicle, fire unit, squad cars confront bunches of issue to achieve their goal on account of congested driving conditions, coming about loss of human lives. To minimize this issue we approach new idea name as ”Traffic control framework for blockage control and stolen Vehicle location”. In this framework activity freedom done by transforming Red flag into Green flag. We demonstrate idea of what is called ”Green wave”. Alongside this, we distinguish stolen vehicle by utilizing extremely advantageous RFID innovation. In the event that stolen vehicle is been distinguished, the framework gives ready sign through ringer. Framework sends Message with the assistance of GSM to Police station. In this framework we Use diverse RFID labels for recognizing rescue vehicle, stolen Vehicles. On the off chance that Red flag is on and IR sensor is initiated, then framework gives ringer alarm to movement police. This is novel framework which encourage great answer for comprehend traffic clog.

  13. Measuring Container Port Complementarity and Substitutability with Automatic Identification System (AIS Data – Studying the Inter-port Relationships in the Oslo Fjord Multi-port Gateway Region

    Directory of Open Access Journals (Sweden)

    Halvor Schøyen

    2017-06-01

    Full Text Available This paper considers the degree of competition among small and medium-sized container ports located in a multi-port gateway region. The level of port competition is evaluated by means of an analysis of the revealed preferences in the port-calling pattern of container feeder vessels deployed on their various links and routes. Unit of analysis is feeder vessel sailing legs and ports stays at/between adjacent container ports. At these ports’ terminals, ships are moored and loading and unloading of containers are performed. The vessel movement data is provided by the Automatic Identification System (AIS. A study of the principal container ports in the Oslo Fjord area is performed, measuring the actual container feeder traffic during the year of 2015. It is demonstrated to which extent ports in the Oslo Fjord region are acting as substitutes, and to which extent they are functioning more as a complement to each other.

  14. Proposal of an intelligent wayside monitoring system for detection of critical ice accumulations on railway vehicles

    Science.gov (United States)

    Michelberger, Frank; Wagner, Adrian; Ostermann, Michael; Maly, Thomas

    2017-09-01

    At railway lines with ballasted tracks, under unfavourable conditions, the so-called flying ballast can occur predominantly for trains driving at high speeds. Especially in wintertime, it is highly likely that the causes are adhered snow or ice deposits, which are falling off the vehicle. Due to the high kinetic energy, the impact can lead to the removal of ballast stones from the structure of the ballasted track. If the stones reach the height of vehicles underside, they may be accelerated significantly due to the collision with the vehicle or may detach further ice blocks. In the worst case, a reinforcing effect occurs, which can lead to considerable damage to railway vehicles (under-floor-area, vehicle exteriors, etc.) and infrastructure (signal masts, noise barriers, etc.). Additionally the flying gravel is a significant danger to people in the nearby area of the tracks. With this feasibility study the applicability and meaningfulness of an intelligent monitoring system for identification of the critical ice accumulation to prevent the ballast fly induced by ice dropping was examined. The key findings of the research are that the detection of ice on railway vehicles and the development of an intelligent monitoring seem to be possible with existing technologies, but a proof of concept in terms of field tests is necessary.

  15. Immunity-based detection, identification, and evaluation of aircraft sub-system failures

    Science.gov (United States)

    Moncayo, Hever Y.

    This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also

  16. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

    Science.gov (United States)

    Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

    2016-02-19

    In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  17. Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

    Science.gov (United States)

    Al Azzawi, Dia

    Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

  18. A web-based clinical decision support system for gestational diabetes: Automatic diet prescription and detection of insulin needs.

    Science.gov (United States)

    Caballero-Ruiz, Estefanía; García-Sáez, Gema; Rigla, Mercedes; Villaplana, María; Pons, Belen; Hernando, M Elena

    2017-06-01

    The growth of diabetes prevalence is causing an increasing demand in health care services which affects the clinicians' workload as medical resources do not grow at the same rate as the diabetic population. Decision support tools can help clinicians with the inspection of monitoring data, providing a preliminary analysis to ease their interpretation and reduce the evaluation time per patient. This paper presents Sinedie, a clinical decision support system designed to manage the treatment of patients with gestational diabetes. Sinedie aims to improve access to specialized healthcare assistance, to prevent patients from unnecessary displacements, to reduce the evaluation time per patient and to avoid gestational diabetes adverse outcomes. A web-based telemedicine platform was designed to remotely evaluate patients allowing them to upload their glycaemia data at home directly from their glucose meter, as well as report other monitoring variables like ketonuria and compliance to dietary treatment. Glycaemia values, not tagged by patients, are automatically labelled with their associated meal by a classifier based on the Expectation Maximization clustering algorithm and a C4.5 decision tree learning algorithm. Two finite automata are combined to determine the patient's metabolic condition, which is analysed by a rule-based knowledge base to generate therapy adjustment recommendations. Diet recommendations are automatically prescribed and notified to the patients, whereas recommendations about insulin requirements are notified also to the physicians, who will decide if insulin needs to be prescribed. The system provides clinicians with a view where patients are prioritized according to their metabolic condition. A randomized controlled clinical trial was designed to evaluate the effectiveness and safety of Sinedie interventions versus standard care and its impact in the professionals' workload in terms of the clinician's time required per patient; number of face

  19. Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    F.

    2012-04-01

    Full Text Available In this paper we propose a new approach for laser-based environment device control systems based on the automatic design of a Fuzzy Rule-Based System for laser pointer detection. The idea is to improve the success rate of the previous approaches decreasing as much as possible the false offs and increasing the success rate in images with laser spot, i.e., the detection of a false laser spot (since this could lead to dangerous situations. To this end, we propose to analyze both, the morphology and color of a laser spot image together, thus developing a new robust algorithm. Genetic Fuzzy Systems have also been employed to improve the laser spot system detection by means of a fine tuning of the involved membership functions thus reducing the system false offs, which is the main objective in this problem. The system presented in this paper, makes use of a Fuzzy Rule-Based System adjusted by a Genetic Algorithm, which, based on laser morphology and color analysis, shows a better success rate than previous approaches.

  20. Stereovision-based 3D field recognition for automatic guidance system of off-road vehicle

    Science.gov (United States)

    Zhang, Fangming; Ying, Yibin; Shen, Chuan; Jiang, Huanyu; Zhang, Qin

    2005-11-01

    A stereovision-based disparity evaluation algorithm was developed for rice crop field recognition. The gray level intensities and the correlation relation were integrated to produce the disparities of stereo-images. The surface of ground and rice were though as two rough planes, but their disparities waved in a narrow range. The cut/uncut edges of rice crops were first detected and track through the images. We used a step model to locate those edge positions. The points besides the edges were matched respectively to get disparity values using area correlation method. The 3D camera coordinates were computed based on those disparities. The vehicle coordinates were obtained by multiplying the 3D camera coordinates with a transform formula. It has been implemented on an agricultural robot and evaluated in rice crop field with straight rows. The results indicated that the developed stereovision navigation system is capable of reconstructing the field image.

  1. Automatic Microaneurysm Detection and Characterization Through Digital Color Fundus Images

    Energy Technology Data Exchange (ETDEWEB)

    Martins, Charles; Veras, Rodrigo; Ramalho, Geraldo; Medeiros, Fatima; Ushizima, Daniela

    2008-08-29

    Ocular fundus images can provide information about retinal, ophthalmic, and even systemic diseases such as diabetes. Microaneurysms (MAs) are the earliest sign of Diabetic Retinopathy, a frequently observed complication in both type 1 and type 2 diabetes. Robust detection of MAs in digital color fundus images is critical in the development of automated screening systems for this kind of disease. Automatic grading of these images is being considered by health boards so that the human grading task is reduced. In this paper we describe segmentation and the feature extraction methods for candidate MAs detection.We show that the candidate MAs detected with the methodology have been successfully classified by a MLP neural network (correct classification of 84percent).

  2. Development of automatic ultrasonic testing system and its application

    International Nuclear Information System (INIS)

    Oh, Sang Hong; Matsuura, Toshihiko; Iwata, Ryusuke; Nakagawa, Michio; Horikawa, Kohsuke; Kim, You Chul

    1997-01-01

    The radiographic testing (RT) has been usually applied to a nondestructive testing, which is carried out on purpose to detect internal defects at welded joints of a penstock. In the case that RT could not be applied to, the ultrasonic testing (UT) was performed. UT was generally carried out by manual scanning and the inspections data were recorded by the inspector in a site. So, as a weak point, there was no objective inspection records correspond to films of RT. It was expected that the automatic ultrasonic testing system by which automatic scanning and automatic recording are possible was developed. In this respect, the automatic ultrasonic testing system was developed. Using newly developed the automatic ultrasonic testing system, test results to the circumferential welded joints of the penstock at a site were shown in this paper.

  3. SLIDE: automatic spine level identification system using a deep convolutional neural network.

    Science.gov (United States)

    Hetherington, Jorden; Lessoway, Victoria; Gunka, Vit; Abolmaesumi, Purang; Rohling, Robert

    2017-07-01

    Percutaneous spinal needle insertion procedures often require proper identification of the vertebral level to effectively and safely deliver analgesic agents. The current clinical method involves "blind" identification of the vertebral level through manual palpation of the spine, which has only 30% reported accuracy. Therefore, there is a need for better anatomical identification prior to needle insertion. A real-time system was developed to identify the vertebral level from a sequence of ultrasound images, following a clinical imaging protocol. The system uses a deep convolutional neural network (CNN) to classify transverse images of the lower spine. Several existing CNN architectures were implemented, utilizing transfer learning, and compared for adequacy in a real-time system. In the system, the CNN output is processed, using a novel state machine, to automatically identify vertebral levels as the transducer moves up the spine. Additionally, a graphical display was developed and integrated within 3D Slicer. Finally, an augmented reality display, projecting the level onto the patient's back, was also designed. A small feasibility study [Formula: see text] evaluated performance. The proposed CNN successfully discriminates ultrasound images of the sacrum, intervertebral gaps, and vertebral bones, achieving 88% 20-fold cross-validation accuracy. Seventeen of 20 test ultrasound scans had successful identification of all vertebral levels, processed at real-time speed (40 frames/s). A machine learning system is presented that successfully identifies lumbar vertebral levels. The small study on human subjects demonstrated real-time performance. A projection-based augmented reality display was used to show the vertebral level directly on the subject adjacent to the puncture site.

  4. Upgrade of the automatic analysis system in the TJ-II Thomson Scattering diagnostic: New image recognition classifier and fault condition detection

    International Nuclear Information System (INIS)

    Makili, L.; Vega, J.; Dormido-Canto, S.; Pastor, I.; Pereira, A.; Farias, G.; Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M.C.; Busch, P.

    2010-01-01

    An automatic image classification system based on support vector machines (SVM) has been in operation for years in the TJ-II Thomson Scattering diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge, image during ECH phase, image during NBI phase and image after reaching the cut off density during ECH heating. Each kind of image implies the execution of different application software. Due to the fact that the recognition system is based on a learning system and major modifications have been carried out in both the diagnostic (optics) and TJ-II plasmas (injected power), the classifier model is no longer valid. A new SVM model has been developed with the current conditions. Also, specific error conditions in the data acquisition process can automatically be detected and managed now. The recovering process has been automated, thereby avoiding the loss of data in ensuing discharges.

  5. Automatic detection and decoding of honey bee waggle dances.

    Directory of Open Access Journals (Sweden)

    Fernando Wario

    Full Text Available The waggle dance is one of the most popular examples of animal communication. Forager bees direct their nestmates to profitable resources via a complex motor display. Essentially, the dance encodes the polar coordinates to the resource in the field. Unemployed foragers follow the dancer's movements and then search for the advertised spots in the field. Throughout the last decades, biologists have employed different techniques to measure key characteristics of the waggle dance and decode the information it conveys. Early techniques involved the use of protractors and stopwatches to measure the dance orientation and duration directly from the observation hive. Recent approaches employ digital video recordings and manual measurements on screen. However, manual approaches are very time-consuming. Most studies, therefore, regard only small numbers of animals in short periods of time. We have developed a system capable of automatically detecting, decoding and mapping communication dances in real-time. In this paper, we describe our recording setup, the image processing steps performed for dance detection and decoding and an algorithm to map dances to the field. The proposed system performs with a detection accuracy of 90.07%. The decoded waggle orientation has an average error of -2.92° (± 7.37°, well within the range of human error. To evaluate and exemplify the system's performance, a group of bees was trained to an artificial feeder, and all dances in the colony were automatically detected, decoded and mapped. The system presented here is the first of this kind made publicly available, including source code and hardware specifications. We hope this will foster quantitative analyses of the honey bee waggle dance.

  6. Farmers' preferences for automatic lameness-detection systems in dairy cattle.

    Science.gov (United States)

    Van De Gucht, T; Saeys, W; Van Nuffel, A; Pluym, L; Piccart, K; Lauwers, L; Vangeyte, J; Van Weyenberg, S

    2017-07-01

    As lameness is a major health problem in dairy herds, a lot of attention goes to the development of automated lameness-detection systems. Few systems have made it to the market, as most are currently still in development. To get these systems ready for practice, developers need to define which system characteristics are important for the farmers as end users. In this study, farmers' preferences for the different characteristics of proposed lameness-detection systems were investigated. In addition, the influence of sociodemographic and farm characteristics on farmers' preferences was assessed. The third aim was to find out if preferences change after the farmer receives extra information on lameness and its consequences. Therefore, a discrete choice experiment was designed with 3 alternative lameness-detection systems: a system attached to the cow, a walkover system, and a camera system. Each system was defined by 4 characteristics: the percentage missed lame cows, the percentage false alarms, the system cost, and the ability to indicate which leg is lame. The choice experiment was embedded in an online survey. After answering general questions and choosing their preferred option in 4 choice sets, extra information on lameness was provided. Consecutively, farmers were shown a second block of 4 choice sets. Results from 135 responses showed that farmers' preferences were influenced by the 4 system characteristics. The importance a farmer attaches to lameness, the interval between calving and first insemination, and the presence of an estrus-detection system contributed significantly to the value a farmer attaches to lameness-detection systems. Farmers who already use an estrus detection system were more willing to use automatic detection systems instead of visual lameness detection. Similarly, farmers who achieve shorter intervals between calving and first insemination and farmers who find lameness highly important had a higher tendency to choose for automatic

  7. Determination of navigation FDI thresholds using a Markov model. [Failure Detection and Identification in triplex inertial platform systems for Shuttle entry

    Science.gov (United States)

    Walker, B. K.; Gai, E.

    1978-01-01

    A method for determining time-varying Failure Detection and Identification (FDI) thresholds for single sample decision functions is described in the context of a triplex system of inertial platforms. A cost function consisting of the probability of vehicle loss due to FDI decision errors is minimized. A discrete Markov model is constructed from which this cost can be determined as a function of the decision thresholds employed to detect and identify the first and second failures. Optimal thresholds are determined through the use of parameter optimization techniques. The application of this approach to threshold determination is illustrated for the Space Shuttle's inertial measurement instruments.

  8. Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle

    Directory of Open Access Journals (Sweden)

    Ming-Shyan Wang

    2015-01-01

    Full Text Available An automatic guided vehicle (AGV is extensively used for productions in a flexible manufacture system with high efficiency and high flexibility. A servomotor-based AGV is designed and implemented in this paper. In order to steer the AGV to go along a predefined path with corner or arc, the conventional proportional-integral-derivative (PID control is used in the system. However, it is difficult to tune PID gains at various conditions. As a result, the neural network (NN control is considered to assist the PID control for gain tuning. The experimental results are first provided to verify the correctness of the neural network plus PID control for 400 W-motor control system. Secondly, the AGV includes two sets of the designed motor systems and CAN BUS transmission so that it can move along the straight line and curve paths shown in the taped videos.

  9. THE APPLICATION OF RTK-GPS AND STEER-BY-WIRE TECHNOLOGY TO THE AUTOMATIC DRIVING OF VEHICLES AND AN EVALUATION OF DRIVER BEHAVIOR

    Directory of Open Access Journals (Sweden)

    Manabu OMAE

    2006-01-01

    Full Text Available Automatic vehicle driving has long been the subject of research efforts designed to improve the safety and efficiency of automobile transportation. In recent years, increasingly sophisticated sensors and automobiles have brought automatic driving systems closer to reality. In this paper we describe an attempt to apply real-time kinematic GPS (RTK-GPS, a highly precise positioning system, and steer-by-wire body technology, which has advanced greatly in recent years, to automatic driving. In addition, we also describe the results of research into human factors related to automatic driving, which will become more and more important as automatic driving is put to practical use.

  10. 33 CFR 401.20 - Automatic Identification System.

    Science.gov (United States)

    2010-07-01

    ... more than 50 passengers for hire; and (2) Each dredge, floating plant or towing vessel over 8 meters in... close to the primary conning position in the navigation bridge and a standard 120 Volt, AC, 3-prong...

  11. Using automatic identification system technology to improve maritime border security

    OpenAIRE

    Lindstrom, Tedric R.

    2014-01-01

    Approved for public release; distribution is unlimited Our coastal waters are the United States’ most open and vulnerable borders. This vast maritime domain harbors critical threats from terrorism, criminal activities, and natural disasters. Maritime borders pose significant security challenges, as nefarious entities have used small boats to conduct illegal activities for years, and they continue to do so today. Illegal drugs, money, weapons, and migrants flow both directions across our ma...

  12. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Science.gov (United States)

    2010-10-01

    ...) The protocol shall be International Morse Code keyed by a 1200 Hz ±800 Hz tone representing a mark and... code programmed into the ATIS device in a permanent manner such that it cannot be readily changed by...

  13. Automatic Identification System (AIS) Transmit Testing in Louisville Phase 2

    Science.gov (United States)

    2014-08-01

    11  4.1.2  Paducah , KY...2013, team members traveled to Louisville, KY and Paducah , KY to gather input from various stakeholders. Since none of the stakeholders had used the...hours out from the lock. 4.1.2 Paducah , KY While in Paducah , a visit was made to Ingram barge. Mr. Mark Stevens (who has since retired) and Mr. Mike

  14. Using Automatic Identification System Technology to Improve Maritime Border Security

    Science.gov (United States)

    2014-12-01

    to transport WMD is of significant concern. Terrorists have demonstrated that they have the capability to use explosive-laden suicide boats as...Cost-Effective-ADS-B-Solution-General-Aviation#.VFBlQvTF_6I 42 When Malaysia Airlines flight MH...low-altitude coverage and coverage reliability.”123 Malaysia is also “implementing ADS-B surveillance to improve coverage of certain air routes

  15. Nonlinear System Identification and Its Applications in Fault Detection and Diagnosis

    DEFF Research Database (Denmark)

    Sun, Zhen

    Interest in nonlinear system identification has grown significantly in recent years. It is much more difficult to develop general results than the concern for linear models since the nonlinear model structures are often much more complicated. As a consequence, the thesis only considers two differ...... be performed by identifying these fault related parameters. Afterwards, the decision whether the fault happened or how large the fault is can be made by comparison and analysis based on the estimated values....... and then for a space robot system. Secondly, the system considered is described by a nonlinear FOPDT model. This type of FOPDT model is an extension of the traditional FOPDT model which pre-assumes all the model parameters are constants. The nonlinearity that is defined in the model is reflected in its two categories...... refrigeration system. The proposed models and methods are further extended for the purpose of Fault Detection and Diagnosis (FDD). In a system where it exists possible parametric fault, if some fault happens, one or several parameters related to fault may change their values. Then the FDD procedure can...

  16. An Ultrasonic Sensor System Based on a Two-Dimensional State Method for Highway Vehicle Violation Detection Applications

    Directory of Open Access Journals (Sweden)

    Jun Liu

    2015-04-01

    Full Text Available With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS and vehicular ad hoc networks (VANETs. Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%.

  17. Proposal for the award of a blanket purchase contract for the design, supply, installation and maintenance of automatic fire-detection, fire-protection and voice-alarm systems for the Super Proton Synchrotron

    CERN Document Server

    2017-01-01

    Proposal for the award of a blanket purchase contract for the design, supply, installation and maintenance of automatic fire-detection, fire-protection and voice-alarm systems for the Super Proton Synchrotron

  18. Vehicle Pose Estimation for Vehicle Detection and Tracking Based on Road Direction

    OpenAIRE

    Prahara, Adhi; Azhari, Ahmad; Murinto, Murinto

    2017-01-01

    Vehicle has several types and each of them has different color, size, and shape. The appearance of vehicle also changes if viewed from different viewpoint of traffic surveillance camera. This situation can create many possibilities of vehicle poses. However, the one in common, vehicle pose usually follows road direction. Therefore, this research proposes a method to estimate the pose of vehicle for vehicle detection and tracking based on road direction. Vehicle training data are generated fro...

  19. Detection and recognition of mechanical, digging and vehicle signals in the optical fiber pre-warning system

    Science.gov (United States)

    Tian, Qing; Yang, Dan; Zhang, Yuan; Qu, Hongquan

    2018-04-01

    This paper presents detection and recognition method to locate and identify harmful intrusions in the optical fiber pre-warning system (OFPS). Inspired by visual attention architecture (VAA), the process flow is divided into two parts, i.e., data-driven process and task-driven process. At first, data-driven process takes all the measurements collected by the system as input signals, which is handled by detection method to locate the harmful intrusion in both spatial domain and time domain. Then, these detected intrusion signals are taken over by task-driven process. Specifically, we get pitch period (PP) and duty cycle (DC) of the intrusion signals to identify the mechanical and manual digging (MD) intrusions respectively. For the passing vehicle (PV) intrusions, their strong low frequency component can be used as good feature. In generally, since the harmful intrusion signals only account for a small part of whole measurements, the data-driven process reduces the amount of input data for subsequent task-driven process considerably. Furthermore, the task-driven process determines the harmful intrusions orderly according to their severity, which makes a priority mechanism for the system as well as targeted processing for different harmful intrusion. At last, real experiments are performed to validate the effectiveness of this method.

  20. Metodology of identification parameters of models control objects of automatic trailing system

    Directory of Open Access Journals (Sweden)

    I.V. Zimchuk

    2017-04-01

    Full Text Available The determining factor for the successful solution of the problem of synthesis of optimal control systems of different processes are adequacy of mathematical model of control object. In practice, the options can differ from the objects taken priori, causing a need to clarification of them. In this context, the article presents the results of the development and application of methods parameters identification of mathematical models of control object of automatic trailing system. The stated problem in the article is solved provided that control object is fully controlled and observed, and a differential equation of control object is known a priori. The coefficients of this equation to be determined. Identifying quality criterion is to minimize the integral value of squared error of identification. The method is based on a description of the dynamics of the object in space state. Equation of identification synthesized using the vector-matrix representation of model. This equation describes the interconnection of coefficients of matrix state and control with inputs and outputs of object. The initial data for calculation are the results of experimental investigation of the reaction of phase coordinates of control object at a typical input signal. The process of calculating the model parameters is reduced to solving the system of equations of the first order each. Application the above approach is illustrated in the example identification of coefficients transfer function of control object first order. Results of digital simulation are presented, they are confirming the justice of set out mathematical calculations. The approach enables to do the identification of models of one-dimensional and multidimensional objects and does not require a large amount of calculation for its implementation. The order of identified model is limited capabilities of measurement phase coordinates of corresponding control object. The practical significance of the work is

  1. Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

    Directory of Open Access Journals (Sweden)

    Jaehoon Jung

    2016-06-01

    Full Text Available This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i automatic camera calibration using both moving objects and a background structure; (ii object depth estimation; and (iii detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems.

  2. Rapid Detection Methods for Asphalt Pavement Thicknesses and Defects by a Vehicle-Mounted Ground Penetrating Radar (GPR) System.

    Science.gov (United States)

    Dong, Zehua; Ye, Shengbo; Gao, Yunze; Fang, Guangyou; Zhang, Xiaojuan; Xue, Zhongjun; Zhang, Tao

    2016-12-06

    The thickness estimation of the top surface layer and surface layer, as well as the detection of road defects, are of great importance to the quality conditions of asphalt pavement. Although ground penetrating radar (GPR) methods have been widely used in non-destructive detection of pavements, the thickness estimation of the thin top surface layer is still a difficult problem due to the limitations of GPR resolution and the similar permittivity of asphalt sub-layers. Besides, the detection of some road defects, including inadequate compaction and delamination at interfaces, require further practical study. In this paper, a newly-developed vehicle-mounted GPR detection system is introduced. We used a horizontal high-pass filter and a modified layer localization method to extract the underground layers. Besides, according to lab experiments and simulation analysis, we proposed theoretical methods for detecting the degree of compaction and delamination at the interface, respectively. Moreover, a field test was carried out and the estimated results showed a satisfactory accuracy of the system and methods.

  3. Fault detection and identification for a class of continuous piecewise affine systems with unknown subsystems and partitions

    NARCIS (Netherlands)

    Le quang, Thuan; Baldi, S.

    2018-01-01

    This paper establishes a novel online fault detection and identification strategy for a class of continuous piecewise affine (PWA) systems, namely, bimodal and trimodal PWA systems. The main contributions with respect to the state-of-the-art are the recursive nature of the proposed scheme and the

  4. Medical isotope identification with large mobile detection systems

    Science.gov (United States)

    Mukhopadhyay, Sanjoy; Maurer, Richard

    2012-10-01

    The Remote Sensing laboratory (RSL) of National Security Technologies Inc. has built an array of large (5.08 - cm x 10.16 - cm x 40.6 - cm) thallium doped sodium iodide (NaI: Tl) scintillators to locate and screen gamma-ray emitting radioisotopes that are of interests to radiological emergency responders [1]. These vehicle mounted detectors provide the operators with rapid, simple, specific information for radiological threat assessment. Applications include large area inspection, customs inspection, border protection, emergency response, and monitoring of radiological facilities. These RSL mobile units are currently being upgraded to meet the Defense Threat Reduction Agency mission requirements for a next-generation system capable of detecting and identifying nuclear threat materials. One of the challenging problems faced by these gamma-ray detectors is the unambiguous identification of medical isotopes like 131I (364.49 keV [81.7%], 636.99 keV [7.17%]), 99Tcm (140.51 keV [89.1%]) and 67Ga (184.6 keV [19.7%], 300.2 [16.0%], 393.5 [4.5%] that are used in radionuclide therapy and often have overlapping gamma-ray energy regions of interest (ROI). The problem is made worse by short (about 5 seconds) acquisition time of the spectral data necessary for dynamic mobile detectors. This article describes attempts to identify medical isotopes from data collected from this mobile detection system in a short period of time (not exceeding 5 secs) and a large standoff distance (typically 10 meters) The mobile units offer identification capabilities that are based on hardware auto stabilization of the amplifier gain. The 1461 keV gamma-energy line from 40K is tracked. It uses gamma-ray energy windowing along with embedded mobile Gamma Detector Response and Analysis Software (GADRAS) [2] simultaneously to deconvolve any overlapping gamma-energy ROIs. These high sensitivity detectors are capable of resolving complex masking scenarios and exceed all ANSI N42.34 (2006) requirements

  5. An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images.

    Science.gov (United States)

    Hajimani, Elmira; Ruano, M G; Ruano, A E

    2017-07-01

    This paper presents a Radial Basis Functions Neural Network (RBFNN) based detection system, for automatic identification of Cerebral Vascular Accidents (CVA) through analysis of Computed Tomographic (CT) images. For the design of a neural network classifier, a Multi Objective Genetic Algorithm (MOGA) framework is used to determine the architecture of the classifier, its corresponding parameters and input features by maximizing the classification precision, while ensuring generalization. This approach considers a large number of input features, comprising first and second order pixel intensity statistics, as well as symmetry/asymmetry information with respect to the ideal mid-sagittal line. Values of specificity of 98% and sensitivity of 98% were obtained, at pixel level, by an ensemble of non-dominated models generated by MOGA, in a set of 150 CT slices (1,867,602pixels), marked by a NeuroRadiologist. This approach also compares favorably at a lesion level with three other published solutions, in terms of specificity (86% compared with 84%), degree of coincidence of marked lesions (89% compared with 77%) and classification accuracy rate (96% compared with 88%). Copyright © 2017. Published by Elsevier B.V.

  6. DETECTION AND IDENTIFICATION OF TOXIC AIR POLLUTANTS USING FIELD PORTABLE AND AIRBORNE REMOTE IMAGING SYSTEMS

    Science.gov (United States)

    Remote sensing technologies are a class of instrument and sensor systems that include laser imageries, imaging spectrometers, and visible to thermal infrared cameras. These systems have been successfully used for gas phase chemical compound identification in a variety of field e...

  7. Street-side vehicle detection, classification and change detection using mobile laser scanning data

    Science.gov (United States)

    Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

    2016-04-01

    Statistics on street-side car parks, e.g. occupancy rates, parked vehicle types, parking durations, are of great importance for urban planning and policy making. Related studies, e.g. vehicle detection and classification, mostly focus on static images or video. Whereas mobile laser scanning (MLS) systems are increasingly utilized for urban street environment perception due to their direct 3D information acquisition, high accuracy and movability. In this paper, we design a complete system for car park monitoring, including vehicle recognition, localization, classification and change detection, from laser scanning point clouds. The experimental data are acquired by an MLS system using high frequency laser scanner which scans the streets vertically along the system's moving trajectory. The point clouds are firstly classified as ground, building façade, and street objects which are then segmented using state-of-the-art methods. Each segment is treated as an object hypothesis, and its geometric features are extracted. Moreover, a deformable vehicle model is fitted to each object. By fitting an explicit model to the vehicle points, detailed information, such as precise position and orientation, can be obtained. The model parameters are also treated as vehicle features. Together with the geometric features, they are applied to a supervised learning procedure for vehicle or non-vehicle recognition. The classes of detected vehicles are also investigated. Whether vehicles have changed across two datasets acquired at different times is detected to estimate the durations. Here, vehicles are trained pair-wisely. Two same or different vehicles are paired up as training samples. As a result, the vehicle recognition, classification and change detection accuracies are 95.9%, 86.0% and 98.7%, respectively. Vehicle modelling improves not only the recognition rate, but also the localization precision compared to bounding boxes.

  8. Results of automatic system implementation for Cofrentes power plant detection system LPRM inspection execution

    Energy Technology Data Exchange (ETDEWEB)

    Palomo, M., E-mail: mpalomo@iqn.upv.es [Departamento de Ingenieria Quimica y Nuclear, Universidad Politecnica de Valencia (Spain); Urrea, M., E-mail: matias.urrea@iberdrola.es [C.N.Cofrentes - Iberdrola Generacion S.A., Valencia (Spain); Curiel, M., E-mail: m.curiel@lainsa.com [LAINSA, Grupo Dominguis, Valencia (Brazil); Arnaldos, A., E-mail: a.arnaldos@titaniast.com [TITANIA Servicios Teconologicos, Valencia (Spain)

    2011-07-01

    During this presentation we are going to introduce the results of Cofrentes nuclear power plant automation of the detection system LPRM (Local Power Range Monitor) inspection procedure. An LPRM's test system has been developed and it consists in a software application and data acquisition hardware that performs automatically the complete detection system process: refueling, storage and operation inspection: Ramp voltage generation, measured voltage Plateaux evaluation, qualification report emission; historical analysis to scan burn evolution. The inspections differentiations are developed by the different specifications that it has to fulfil: operation inspection: it is made to check the fission bolt wearing, the detection system functioning and to analyse malfunctioning. From technical specifications and curves analyses it can be determined each LPRM's substitution. Storage inspection: it is made to check the correct functioning and isolation losses before being installed in the core during refueling. Refueling inspection: it is checked that storage LPRM's installation is correct and that they are ready for new fuel cycle. The software application LPRM's Test has been developed by National Instruments LabVIEW, and it performs the following actions: Protocol IEEE-488 (GPIB) control of the source KEITHLEY 237. This source generates the ramp voltage and measure voltage; information acquisition of storage, process and source, identifying LPRM and realization conditions of the same; data analysis and conditions report, historical comparative analysis. (author)

  9. Proposal for the award of a blanket contract for automatic air-sampling systems for fire and gas detection in the LHC experiments

    CERN Document Server

    2004-01-01

    This document concerns the award of a blanket contract for automatic air-sampling systems for fire and gas detection in the LHC experiments. Following a market survey carried out among 119 firms in ten Member States, a call for tenders (IT-2891/ST) was sent on 1 August 2003 to four firms, in three Member States. By the closing date, CERN had received two tenders from one firm and one consortium, in three Member States. The Finance Committee is invited to agree to the negotiation of a blanket contract with ICARE (FR), the lowest bidder, for the supply of automatic air-sampling systems for fire and gas detection in the LHC experiments for a total amount not exceeding 1 750 000 euros (2 714 000 Swiss francs), subject to revision for inflation from 1 January 2007 with options for air-sampling smoke detection systems for electrical racks, for an additional amount of 400 000 euros (620 000 Swiss francs), subject to revision for inflation from 1 January 2007, bringing the total amount to a maximum of 2 150 000 euros...

  10. Automatic vehicle classification using linked visual words

    Science.gov (United States)

    Watcharapinchai, Nattachai; Aramvith, Supavadee; Siddhichai, Supakorn

    2017-07-01

    An improvement in the method of automatic vehicle classification is investigated. The challenges are to correctly classify vehicles regardless of changes in illumination, differences in points of view of the camera, and variations in the types of vehicles. Our proposed appearance-based feature extraction algorithm is called linked visual words (LVWs) and is based on the existing technique bag-of-visual word (BoVW) with the addition of spatial information to improve accuracy of classification. In addition, to prevent over-fitting due to a large number of LVWs, four common sampling techniques with LVWs are investigated. Our results suggest that the sampling of LVWs using TF-IDF with grouping improved the accuracy of classification for the test dataset. In summary, the proposed system is able to classify nine types of vehicles and work with surveillance cameras in real-world scenarios. The classification accuracy of the proposed system is 5.58% and 4.27% higher on average for three datasets when compared with BoVW + SVM and Lenet-5, respectively.

  11. Remote monitoring of emissions using on-vehicle sensing and vehicle to roadside communications

    Energy Technology Data Exchange (ETDEWEB)

    Davis, D.T.

    1995-06-01

    Recent developments in on-vehicle electronics makes practical remote monitoring of vehicle emissions compliance with CARB and EPA regulations. A system consisting of emission controls malfunction sensors, an on-board computer (OBC), and vehicle-to-roadside communications (VRC) would enable enforcement officials to remotely and automatically detect vehicle out-of-compliance status. Remote sensing could be accomplished at highway speeds as vehicles pass a roadside RF antenna and reader unit which would interrogate the on- vehicle monitoring and recording system. This paper will focus on the hardware system components require to achieve this goal with special attention to the VRC; a key element for remote monitoring. this remote sensing concept piggybacks on the development of inexpensive VRC equipment for automatic vehicle identification for electronic toll collection and intelligent transportation applications. Employing an RF transponder with appropriate interface to the OBC and malfunction sensors, a practical monitoring system can be developed with potentially important impact on air quality and enforcement. With such a system in place, the current -- and costly and ineffective -- emission control strategy of periodic smog checking could be replaced or modified.

  12. Robust Road Condition Detection System Using In-Vehicle Standard Sensors.

    Science.gov (United States)

    Castillo Aguilar, Juan Jesús; Cabrera Carrillo, Juan Antonio; Guerra Fernández, Antonio Jesús; Carabias Acosta, Enrique

    2015-12-19

    The appearance of active safety systems, such as Anti-lock Braking System, Traction Control System, Stability Control System, etc., represents a major evolution in road safety. In the automotive sector, the term vehicle active safety systems refers to those whose goal is to help avoid a crash or to reduce the risk of having an accident. These systems safeguard us, being in continuous evolution and incorporating new capabilities continuously. In order for these systems and vehicles to work adequately, they need to know some fundamental information: the road condition on which the vehicle is circulating. This early road detection is intended to allow vehicle control systems to act faster and more suitably, thus obtaining a substantial advantage. In this work, we try to detect the road condition the vehicle is being driven on, using the standard sensors installed in commercial vehicles. Vehicle models were programmed in on-board systems to perform real-time estimations of the forces of contact between the wheel and road and the speed of the vehicle. Subsequently, a fuzzy logic block is used to obtain an index representing the road condition. Finally, an artificial neural network was used to provide the optimal slip for each surface. Simulations and experiments verified the proposed method.

  13. Robust Road Condition Detection System Using In-Vehicle Standard Sensors

    Directory of Open Access Journals (Sweden)

    Juan Jesús Castillo Aguilar

    2015-12-01

    Full Text Available The appearance of active safety systems, such as Anti-lock Braking System, Traction Control System, Stability Control System, etc., represents a major evolution in road safety. In the automotive sector, the term vehicle active safety systems refers to those whose goal is to help avoid a crash or to reduce the risk of having an accident. These systems safeguard us, being in continuous evolution and incorporating new capabilities continuously. In order for these systems and vehicles to work adequately, they need to know some fundamental information: the road condition on which the vehicle is circulating. This early road detection is intended to allow vehicle control systems to act faster and more suitably, thus obtaining a substantial advantage. In this work, we try to detect the road condition the vehicle is being driven on, using the standard sensors installed in commercial vehicles. Vehicle models were programmed in on-board systems to perform real-time estimations of the forces of contact between the wheel and road and the speed of the vehicle. Subsequently, a fuzzy logic block is used to obtain an index representing the road condition. Finally, an artificial neural network was used to provide the optimal slip for each surface. Simulations and experiments verified the proposed method.

  14. Magnetic Detection and Tracking of Military Vehicles

    Science.gov (United States)

    Czipott, Peter V.; Perry, Alexander R.; Whitecotton, Brian R.; Dalichaouch, Yacine; Walsh, David O.

    2002-02-01

    Under the Next Generation Scatterable Mines (NGSM) program led by the U.S. Army TACOM-ARDEC (Technical Agent Tank-automotive and Armaments Command - Army Research, Development and Engineering Center) and as a subcontractor to IITRI (IIT (Illinois Institute of Technology) Research Institute), Quantum Magnetics (QM) has participated in several rounds of field experiments in magnetic detection and tracking of military vehicles. Field data were acquired by three generations of magnetoresistive (MR) magnetic tensor gradiometers and analyzed by QM and Vista Clara. Successive gradiometer design generations mark a path to meeting NGSM form factor constraints. Magnetic gradiometry can detect and unambiguously locate magnetic targets, even in magnetically contaminated environments, as shown by results presented below.

  15. Automatic target identification using neural networks

    Science.gov (United States)

    Abdallah, Mahmoud A.; Samu, Tayib I.; Grissom, William A.

    1995-10-01

    Neural network theories are applied to attain human-like performance in areas such as speech recognition, statistical mapping, and target recognition or identification. In target identification, one of the difficult tasks has been the extraction of features to be used to train the neural network which is subsequently used for the target's identification. The purpose of this paper is to describe the development of an automatic target identification system using features extracted from a specific class of targets. The extracted features were the graphical representations of the silhouettes of the targets. Image processing techniques and some Fast Fourier Transform (FFT) properties were implemented to extract the features. The FFT eliminates variations in the extracted features due to rotation or scaling. A Neural Network was trained with the extracted features using the Learning Vector Quantization paradigm. An identification system was set up to test the algorithm. The image processing software was interfaced with MATLAB Neural Network Toolbox via a computer program written in C language to automate the target identification process. The system performed well as at classified the objects used to train it irrespective of rotation, scaling, and translation. This automatic target identification system had a classification success rate of about 95%.

  16. Automatic detection of microaneurysms using microstructure and ...

    Indian Academy of Sciences (India)

    The proposed approach is experimented with DIARETDB0 and DIARETDB1 datasets using a classifier based on multi-layer perceptron procedure. For DIARETDB0 dataset, the proposed algorithm obtains the results with a sensitivity of 98.32 and specificity of 97.59. In the case of DIARETDB1 dataset, the sensitivity and ...

  17. Optics detection and laser countermeasures on a combat vehicle

    Science.gov (United States)

    Sjöqvist, Lars; Allard, Lars; Pettersson, Magnus; Börjesson, Per; Lindskog, Nils; Bodin, Johan; Widén, Anders; Persson, Hâkan; Fredriksson, Jan; Edström, Sten

    2016-10-01

    Magnifying optical assemblies used for weapon guidance or rifle scopes may possess a threat for a combat vehicle and its personnel. Detection and localisation of optical threats is consequently of interest in military applications. Typically a laser system is used in optics detection, or optical augmentation, to interrogate a scene of interest to localise retroreflected laser radiation. One interesting approach for implementing optics detection on a combat vehicle is to use a continuous scanning scheme. In addition, optics detection can be combined with laser countermeasures, or a laser dazzling function, to efficiently counter an optical threat. An optics detection laser sensor demonstrator has been implemented on a combat vehicle. The sensor consists of a stabilised gimbal and was integrated together with a LEMUR remote electro-optical sight. A narrow laser slit is continuously scanned around the horizon to detect and locate optical threats. Detected threats are presented for the operator within the LEMUR presentation system, and by cueing a countermeasure laser installed in the LEMUR sensor housing threats can be defeated. Results obtained during a field demonstration of the optics detection sensor and the countermeasure laser will be presented. In addition, results obtained using a dual-channel optics detection system designed for false alarm reduction are also discussed.

  18. Automatic detection of microaneurysms using microstructure and ...

    Indian Academy of Sciences (India)

    Two dictionary elements of vessel and non-vessel were used in the sparse rep- resentation classifier process. Experimental results showed that the proposed method can well distinguish microaneurysms from non- microaneurysms objects. Cemal et al (2012) developed an approach called inverse segmentation method to ...

  19. Automatic detection of microaneurysms using microstructure and ...

    Indian Academy of Sciences (India)

    The names of the filters are mnemonics for “level,” “edge,” “spot,” “wave,” “ripple,” “undula- tion,” and “oscillation.” For most of the filters, the resulting gray values must be modified by a shift. This makes the different textures in the output image more comparable to each other. The name of the filter is composed of the letters of ...

  20. Autonomous Conflict Detection and Resolution for Unmanned Aerial Vehicles : On integration into the Airspace System

    NARCIS (Netherlands)

    Jenie, Y.I.

    2017-01-01

    In the last decade, the commercial values of Unmanned Aerial Vehicles (UAV), defined as devices that are capable of sustainable flights in the atmosphere that do not require to have a human (pilot) on-board, become widely recognized thanks to the advancement of technology in materials, sensors,

  1. A remotely controlled, semi-automatic target system for Rutherford backscattering spectrometry and elastic recoil detection analyses of polymeric membrane samples

    International Nuclear Information System (INIS)

    Attayek, P.J.; Meyer, E.S.; Lin, L.; Rich, G.C.; Clegg, T.B.; Coronell, O.

    2012-01-01

    A new target system for Rutherford backscattering spectrometry and elastic recoil detection analysis is described which enables remotely controlled, semi-automatic analysis of multiple organic polymer samples without exceeding damaging incident beam fluences. Control of fluence at a given beam current is achieved using two stepper motors to move a thin aluminum disk loaded with polymer samples both radially and azimuthally across the beam. Flexible beam spot locations and sample irradiation times are remotely controlled in two steps via two custom LabVIEW™ programs. In the first step, a digital image of the target disk is converted into precise radial and azimuthal coordinates for each mounted polymer sample. In the second step, the motors implement the user-directed sample irradiation and fluence. Schematics of the target system hardware, a block diagram of interactions between the target system components, a description of routine procedures, and illustrative data taken with a 2 MeV 4 He 2+ analysis beam are provided.

  2. Automatic polymerase chain reaction product detection system for food safety monitoring using zinc finger protein fused to luciferase

    Energy Technology Data Exchange (ETDEWEB)

    Yoshida, Wataru; Kezuka, Aki; Murakami, Yoshiyuki; Lee, Jinhee; Abe, Koichi [Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo 184-8588 (Japan); Motoki, Hiroaki; Matsuo, Takafumi; Shimura, Nobuaki [System Instruments Co., Ltd., 776-2 Komiya-cho, Hachioji, Tokyo 192-0031 (Japan); Noda, Mamoru; Igimi, Shizunobu [Division of Biomedical Food Research, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158-8501 (Japan); Ikebukuro, Kazunori, E-mail: ikebu@cc.tuat.ac.jp [Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo 184-8588 (Japan)

    2013-11-01

    Graphical abstract: -- Highlights: •Zif268 fused to luciferase was used for E. coli O157, Salmonella and coliform detection. •Artificial zinc finger protein fused to luciferase was constructed for Norovirus detection. •An analyzer that automatically detects PCR products by zinc finger protein fused to luciferase was developed. •Target pathogens were specifically detected by the automatic analyzer with zinc finger protein fused to luciferase. -- Abstract: An automatic polymerase chain reaction (PCR) product detection system for food safety monitoring using zinc finger (ZF) protein fused to luciferase was developed. ZF protein fused to luciferase specifically binds to target double stranded DNA sequence and has luciferase enzymatic activity. Therefore, PCR products that comprise ZF protein recognition sequence can be detected by measuring the luciferase activity of the fusion protein. We previously reported that PCR products from Legionella pneumophila and Escherichia coli (E. coli) O157 genomic DNA were detected by Zif268, a natural ZF protein, fused to luciferase. In this study, Zif268–luciferase was applied to detect the presence of Salmonella and coliforms. Moreover, an artificial zinc finger protein (B2) fused to luciferase was constructed for a Norovirus detection system. In the luciferase activity detection assay, several bound/free separation process is required. Therefore, an analyzer that automatically performed the bound/free separation process was developed to detect PCR products using the ZF–luciferase fusion protein. By means of the automatic analyzer with ZF–luciferase fusion protein, target pathogenic genomes were specifically detected in the presence of other pathogenic genomes. Moreover, we succeeded in the detection of 10 copies of E. coli BL21 without extraction of genomic DNA by the automatic analyzer and E. coli was detected with a logarithmic dependency in the range of 1.0 × 10 to 1.0 × 10{sup 6} copies.

  3. Adoption of automatic identification systems by grocery retailersin the Johannesburg area

    Directory of Open Access Journals (Sweden)

    Christopher C. Darlington

    2011-11-01

    Full Text Available Retailers not only need the right data capture technology to meet the requirements of their applications, they must also decide on what the optimum technology is from the different symbologies that have been developed over the years. Automatic identification systems (AIS are a priority to decision makers as they attempt to obtain the best blend of equipment to ensure greater loss prevention and higher reliability in data capture. However there is a risk of having too simplistic a view of adopting AIS, since no one solution is applicable across an industry or business model. This problem is addressed through an exploratory, descriptive study, where the nature and value of AIS adoption by grocery retailers in the Johannesburg area is interrogated. Mixed empirical results indicate that, as retailers adopt AIS in order to improve their supply chain management systems, different types of applications are associated with various constraints and opportunities. Overall this study is in line with previous research that supports the notion that supply chain decisions are of a strategic nature even though efficient management of information is a day-to-day business operational decision.

  4. Automatic identification and location technology of glass insulator self-shattering

    Science.gov (United States)

    Huang, Xinbo; Zhang, Huiying; Zhang, Ye

    2017-11-01

    The insulator of transmission lines is one of the most important infrastructures, which is vital to ensure the safe operation of transmission lines under complex and harsh operating conditions. The glass insulator often self-shatters but the available identification methods are inefficient and unreliable. Then, an automatic identification and localization technology of self-shattered glass insulators is proposed, which consists of the cameras installed on the tower video monitoring devices or the unmanned aerial vehicles, the 4G/OPGW network, and the monitoring center, where the identification and localization algorithm is embedded into the expert software. First, the images of insulators are captured by cameras, which are processed to identify the region of insulator string by the presented identification algorithm of insulator string. Second, according to the characteristics of the insulator string image, a mathematical model of the insulator string is established to estimate the direction and the length of the sliding blocks. Third, local binary pattern histograms of the template and the sliding block are extracted, by which the self-shattered insulator can be recognized and located. Finally, a series of experiments is fulfilled to verify the effectiveness of the algorithm. For single insulator images, Ac, Pr, and Rc of the algorithm are 94.5%, 92.38%, and 96.78%, respectively. For double insulator images, Ac, Pr, and Rc are 90.00%, 86.36%, and 93.23%, respectively.

  5. Automatic Language Identification

    Science.gov (United States)

    2000-08-01

    hundreds guish one language from another. The reader is referred of input languages would need to be supported , the cost of to the linguistics literature...eventually obtained bet- 108 TRAINING FRENCH GERMAN ITRAIING FRENCH M- ALGORITHM - __ GERMAN NHSPANISH TRAINING SPEECH SET OF MODELS: UTTERANCES ONE MODEL...i.e. vowels ) for each speech utterance are located malized to be insensitive to overall amplitude, pitch and automatically. Next, feature vectors

  6. Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery

    Science.gov (United States)

    Bockelmann, Thomas R [Battle Creek, MI; Beaty, Kevin D [Kalamazoo, MI; Zou, Zhanijang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI

    2009-07-21

    A battery control system for controlling a state of charge of a hybrid vehicle battery includes a detecting arrangement for determining a vehicle operating state or an intended vehicle operating state and a controller for setting a target state of charge level of the battery based on the vehicle operating state or the intended vehicle operating state. The controller is operable to set a target state of charge level at a first level during a mobile vehicle operating state and at a second level during a stationary vehicle operating state or in anticipation of the vehicle operating in the stationary vehicle operating state. The invention further includes a method for controlling a state of charge of a hybrid vehicle battery.

  7. Automatic decision support system based on SAR data for oil spill detection

    Science.gov (United States)

    Mera, David; Cotos, José M.; Varela-Pet, José; Rodríguez, Pablo G.; Caro, Andrés

    2014-11-01

    Global trade is mainly supported by maritime transport, which generates important pollution problems. Thus, effective surveillance and intervention means are necessary to ensure proper response to environmental emergencies. Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillages on the oceans surface. Several decision support systems have been based on this technology. This paper presents an automatic oil spill detection system based on SAR data which was developed on the basis of confirmed spillages and it was adapted to an important international shipping route off the Galician coast (northwest Iberian Peninsula). The system was supported by an adaptive segmentation process based on wind data as well as a shape oriented characterization algorithm. Moreover, two classifiers were developed and compared. Thus, image testing revealed up to 95.1% candidate labeling accuracy. Shared-memory parallel programming techniques were used to develop algorithms in order to improve above 25% of the system processing time.

  8. On-line identification of vehicle fuel consumption for energy and emission management: an LTP System Analysis

    NARCIS (Netherlands)

    Kessels, J.T.B.A.; Sijs, J.; Hermans, R.M.; Damen, A.A.H.; Bosch, P.P.J. van den; Papp, Z.; Lazar, M.

    2008-01-01

    Abstract—An Energy Management (EM) system traditionally relies on (quasi) static maps offering efficiency parameters of the vehicle powertrain. During a vehicle’s life span, these maps lose validity, so optimal performance for EM is not assured. This paper presents a proof-of-concept for a novel

  9. An Automatic Document Indexing System Based on Cooperating Expert Systems: Design and Development.

    Science.gov (United States)

    Schuegraf, Ernst J.; van Bommel, Martin F.

    1993-01-01

    Describes the design of an automatic indexing system that is based on statistical techniques and expert system technology. Highlights include system architecture; the derivation of topic indicators, including word frequency; experimental results using documents from ERIC; the effects of stemming; and the identification of characteristic…

  10. Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery

    Science.gov (United States)

    Bockelmann, Thomas R [Battle Creek, MI; Hope, Mark E [Marshall, MI; Zou, Zhanjiang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI

    2009-02-10

    A battery control system for hybrid vehicle includes a hybrid powertrain battery, a vehicle accessory battery, and a prime mover driven generator adapted to charge the vehicle accessory battery. A detecting arrangement is configured to monitor the vehicle accessory battery's state of charge. A controller is configured to activate the prime mover to drive the generator and recharge the vehicle accessory battery in response to the vehicle accessory battery's state of charge falling below a first predetermined level, or transfer electrical power from the hybrid powertrain battery to the vehicle accessory battery in response to the vehicle accessory battery's state of charge falling below a second predetermined level. The invention further includes a method for controlling a hybrid vehicle powertrain system.

  11. Implementation Of Automatic Wiper Speed Control And Headlight Modes Control Systems Using Fuzzy Logic

    OpenAIRE

    ThetKoKo; ZawMyoTun; Hla Myo Tun

    2015-01-01

    Abstract This research paper describes the design and simulation of the automatic wiper speed and headlight modes controllers using fuzzy logic. This proposed system consists of a fuzzy logic controller to control a cars wiper speed and headlight modes. The automatic wiper system detects the rain and its intensity. And according to the rain intensity the wiper speed is automatically controlled. Headlight modes automatically changes either from low beam mode to high beam mode or form high beam...

  12. Crescent Evaluation : appendix D : crescent computer system components evaluation report

    Science.gov (United States)

    1994-02-01

    In 1990, Lockheed Integrated Systems Company (LISC) was awarded a contract, under the Crescent Demonstration Project, to demonstrate the integration of Weigh In Motion (WIM), Automatic Vehicle Classification (AVC) and Automatic Vehicle Identification...

  13. Intraoperative multichannel audio-visual information recording and automatic surgical phase and incident detection.

    Science.gov (United States)

    Suzuki, Takashi; Sakurai, Yasuo; Yoshimitsu, Kitaro; Nambu, Kyojiro; Muragaki, Yoshihiro; Iseki, Hiroshi

    2010-01-01

    Identification, analysis, and treatment of potential risk in surgical workflow are the key to decrease medical errors in operating room. For the automatic analysis of recorded surgical information, this study reports multichannel audio visual recording system, and its review and analysis system. Motion in operating room is quantified using video file size without motion tracking. Conversation among surgical staff is quantified using fast Fourier transformation and frequency filter without speech recognition. The results suggested the progression phase of surgical procedure.

  14. Vehicle detection from high-resolution aerial images based on superpixel and color name features

    Science.gov (United States)

    Chen, Ziyi; Cao, Liujuan; Yu, Zang; Chen, Yiping; Wang, Cheng; Li, Jonathan

    2016-03-01

    Automatic vehicle detection from aerial images is emerging due to the strong demand of large-area traffic monitoring. In this paper, we present a novel framework for automatic vehicle detection from the aerial images. Through superpixel segmentation, we first segment the aerial images into homogeneous patches, which consist of the basic units during the detection to improve efficiency. By introducing the sparse representation into our method, powerful classification ability is achieved after the dictionary training. To effectively describe a patch, the Histogram of Oriented Gradient (HOG) is used. We further propose to integrate color information to enrich the feature representation by using the color name feature. The final feature consists of both HOG and color name based histogram, by which we get a strong descriptor of a patch. Experimental results demonstrate the effectiveness and robust performance of the proposed algorithm for vehicle detection from aerial images.

  15. Automatic control systems engineering

    International Nuclear Information System (INIS)

    Shin, Yun Gi

    2004-01-01

    This book gives descriptions of automatic control for electrical electronics, which indicates history of automatic control, Laplace transform, block diagram and signal flow diagram, electrometer, linearization of system, space of situation, state space analysis of electric system, sensor, hydro controlling system, stability, time response of linear dynamic system, conception of root locus, procedure to draw root locus, frequency response, and design of control system.

  16. Vehicle detection using normalized color and edge map.

    Science.gov (United States)

    Tsai, Luo-Wei; Hsieh, Jun-Wei; Fan, Kuo-Chin

    2007-03-01

    This paper presents a novel vehicle detection approach for detecting vehicles from static images using color and edges. Different from traditional methods, which use motion features to detect vehicles, this method introduces a new color transform model to find important "vehicle color" for quickly locating possible vehicle candidates. Since vehicles have various colors under different weather and lighting conditions, seldom works were proposed for the detection of vehicles using colors. The proposed new color transform model has excellent capabilities to identify vehicle pixels from background, even though the pixels are lighted under varying illuminations. After finding possible vehicle candidates, three important features, including corners, edge maps, and coefficients of wavelet transforms, are used for constructing a cascade multichannel classifier. According to this classifier, an effective scanning can be performed to verify all possible candidates quickly. The scanning process can be quickly achieved because most background pixels are eliminated in advance by the color feature. Experimental results show that the integration of global color features and local edge features is powerful in the detection of vehicles. The average accuracy rate of vehicle detection is 94.9%.

  17. Automatic Chessboard Detection for Intrinsic and Extrinsic Camera Parameter Calibration

    Directory of Open Access Journals (Sweden)

    Jose María Armingol

    2010-03-01

    Full Text Available There are increasing applications that require precise calibration of cameras to perform accurate measurements on objects located within images, and an automatic algorithm would reduce this time consuming calibration procedure. The method proposed in this article uses a pattern similar to that of a chess board, which is found automatically in each image, when no information regarding the number of rows or columns is supplied to aid its detection. This is carried out by means of a combined analysis of two Hough transforms, image corners and invariant properties of the perspective transformation. Comparative analysis with more commonly used algorithms demonstrate the viability of the algorithm proposed, as a valuable tool for camera calibration.

  18. Vehicle Detection Tool - VDtect

    OpenAIRE

    Prateek, GV; Hari, KVS

    2012-01-01

    The report talks about the implementation of Vehicle Detection tool using opensource software - WxPython. The main functionality of this tool includes collection of data, plotting of magnetometer data and the count of the vehicles detected. The report list about how installation process and various functionality of the tool.

  19. An automatic system for the detection of dairy cows lying behaviour in free-stall barns

    Directory of Open Access Journals (Sweden)

    Simona M.C. Porto

    2013-09-01

    Full Text Available In this paper, a method for the automatic detection of dairy cow lying behaviour in free-stall barns is proposed. A computer visionbased system (CVBS composed of a video-recording system and a cow lying behaviour detector based on the Viola Jones algorithm was developed. The CVBS performance was tested in a head-to-head free stall barn. Two classifiers were implemented in the software component of the CVBS to obtain the cow lying behaviour detector. The CVBS was validated by comparing its detection results with those generated from visual recognition. This comparison allowed the following accuracy indices to be calculated: the branching factor (BF, the miss factor (MF, the sensitivity, and the quality percentage (QP. The MF value of approximately 0.09 showed that the CVBS missed one cow every 11 well detected cows. Conversely, the BF value of approximately 0.08 indicated that one false positive was detected every 13 well detected cows. The high value of approximately 0.92 obtained for the sensitivity index and that obtained for QP of about 0.85 revealed the ability of the proposed system to detect cows lying in the stalls.

  20. Acoustics of snoring and automatic snore sound detection in children.

    Science.gov (United States)

    Çavuşoğlu, M; Poets, C F; Urschitz, M S

    2017-10-31

    Acoustic analyses of snoring sounds have been used to objectively assess snoring and applied in various clinical problems for adult patients. Such studies require highly automatized tools to analyze the sound recordings of the whole night's sleep, in order to extract clinically relevant snore- related statistics. The existing techniques and software used for adults are not efficiently applicable to snoring sounds in children, basically because of different acoustic signal properties. In this paper, we present a broad range of acoustic characteristics of snoring sounds in children (N  =  38) in comparison to adult (N  =  30) patients. Acoustic characteristics of the signals were calculated, including frequency domain representations, spectrogram-based characteristics, spectral envelope analysis, formant structures and loudness of the snoring sounds. We observed significant differences in spectral features, formant structures and loudness of the snoring signals of children compared to adults that may arise from the diversity of the upper airway anatomy as the principal determinant of the snore sound generation mechanism. Furthermore, based on the specific audio features of snoring children, we proposed a novel algorithm for the automatic detection of snoring sounds from ambient acoustic data specifically in a pediatric population. The respiratory sounds were recorded using a pair of microphones and a multi-channel data acquisition system simultaneously with full-night polysomnography during sleep. Brief sound chunks of 0.5 s were classified as either belonging to a snoring event or not with a multi-layer perceptron, which was trained in a supervised fashion using stochastic gradient descent on a large hand-labeled dataset using frequency domain features. The method proposed here has been used to extract snore-related statistics that can be calculated from the detected snore episodes for the whole night's sleep, including number of snore episodes

  1. Autonomous docking control of visual-servo type underwater vehicle system aiming at underwater automatic charging

    International Nuclear Information System (INIS)

    Yanou, Akira; Ohnishi, Shota; Ishiyama, Shintaro; Minami, Mamoru

    2015-01-01

    A visual-servo type remotely operated vehicle (ROV) system with binocular wide-angle lens was developed to survey submarine resources, decontaminate radiation from mud in dam lake and so on. This paper explores the experiments on regulator performance and underwater docking of the robot system utilizing Genetic Algorithm (GA) for real-time recognition of the robot's relative position and posture through 3D marker. The visual servoing performances have been verified as follows; (1) The stability performances of the proposed regulator system have been evaluated by exerting abrupt distrubane force while the ROV is controlled by visual servoing. (2) The proposed system can track time-variant desired target position in x-axis (front-back direction of the robot). (3) The underwater docking can be completed by switching visual servoing and docking modes based on the error threshold, and by giving time-varying desired target position and orientation to the controller as a desired pose. (author)

  2. Detection of unmanned aerial vehicles using a visible camera system.

    Science.gov (United States)

    Hu, Shuowen; Goldman, Geoffrey H; Borel-Donohue, Christoph C

    2017-01-20

    Unmanned aerial vehicles (UAVs) flown by adversaries are an emerging asymmetric threat to homeland security and the military. To help address this threat, we developed and tested a computationally efficient UAV detection algorithm consisting of horizon finding, motion feature extraction, blob analysis, and coherence analysis. We compare the performance of this algorithm against two variants, one using the difference image intensity as the motion features and another using higher-order moments. The proposed algorithm and its variants are tested using field test data of a group 3 UAV acquired with a panoramic video camera in the visible spectrum. The performance of the algorithms was evaluated using receiver operating characteristic curves. The results show that the proposed approach had the best performance compared to the two algorithmic variants.

  3. Automatic Registration and Mosaicking System for Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    Emiliano Castejon

    2006-04-01

    Full Text Available Image registration is an important operation in many remote sensing applications and it, besides other tasks, involves the identification of corresponding control points in the images. As manual identification of control points may be time-consuming and tiring, several automatic techniques have been developed. This paper describes a system for automatic registration and mosaic of remote sensing images under development at The National Institute for Space Research (INPE and at The University of California, Santa Barbara (UCSB. The user can provide information to the system in order to speed up the registration process as well as to avoid mismatched control points. Based on statistical procedure, the system gives an indication of the registration quality. This allows users to stop the processing, to modify the registration parameters or to continue the processing. Extensive system tests have been performed with different types of data (optical, radar, multi-sensor, high-resolution images and video sequences in order to check the system performance. An online demo system is available on the internet ( which contains several examples that can be carried out using web browser.

  4. Electric vehicle drive train with rollback detection and compensation

    Science.gov (United States)

    Konrad, C.E.

    1994-12-27

    An electric vehicle drive train includes a controller for detecting and compensating for vehicle rollback, as when the vehicle is started upward on an incline. The vehicle includes an electric motor rotatable in opposite directions corresponding to opposite directions of vehicle movement. A gear selector permits the driver to select an intended or desired direction of vehicle movement. If a speed and rotational sensor associated with the motor indicates vehicle movement opposite to the intended direction of vehicle movement, the motor is driven to a torque output magnitude as a nonconstant function of the rollback speed to counteract the vehicle rollback. The torque function may be either a linear function of speed or a function of the speed squared. 6 figures.

  5. Electric vehicle drive train with rollback detection and compensation

    Science.gov (United States)

    Konrad, Charles E.

    1994-01-01

    An electric vehicle drive train includes a controller for detecting and compensating for vehicle rollback, as when the vehicle is started upward on an incline. The vehicle includes an electric motor rotatable in opposite directions corresponding to opposite directions of vehicle movement. A gear selector permits the driver to select an intended or desired direction of vehicle movement. If a speed and rotational sensor associated with the motor indicates vehicle movement opposite to the intended direction of vehicle movement, the motor is driven to a torque output magnitude as a nonconstant function of the rollback speed to counteract the vehicle rollback. The torque function may be either a linear function of speed or a function of the speed squared.

  6. Vehicle detection in aerial surveillance using dynamic Bayesian networks.

    Science.gov (United States)

    Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

    2012-04-01

    We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

  7. A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Bohui Zhu

    2013-01-01

    Full Text Available This paper presents a novel maximum margin clustering method with immune evolution (IEMMC for automatic diagnosis of electrocardiogram (ECG arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias.

  8. Automatic solar feature detection using image processing and pattern recognition techniques

    Science.gov (United States)

    Qu, Ming

    The objective of the research in this dissertation is to develop a software system to automatically detect and characterize solar flares, filaments and Corona Mass Ejections (CMEs), the core of so-called solar activity. These tools will assist us to predict space weather caused by violent solar activity. Image processing and pattern recognition techniques are applied to this system. For automatic flare detection, the advanced pattern recognition techniques such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Support Vector Machine (SVM) are used. By tracking the entire process of flares, the motion properties of two-ribbon flares are derived automatically. In the applications of the solar filament detection, the Stabilized Inverse Diffusion Equation (SIDE) is used to enhance and sharpen filaments; a new method for automatic threshold selection is proposed to extract filaments from background; an SVM classifier with nine input features is used to differentiate between sunspots and filaments. Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are applied to determine filament properties. Furthermore, a filament matching method is proposed to detect filament disappearance. The automatic detection and characterization of flares and filaments have been successfully applied on Halpha full-disk images that are continuously obtained at Big Bear Solar Observatory (BBSO). For automatically detecting and classifying CMEs, the image enhancement, segmentation, and pattern recognition techniques are applied to Large Angle Spectrometric Coronagraph (LASCO) C2 and C3 images. The processed LASCO and BBSO images are saved to file archive, and the physical properties of detected solar features such as intensity and speed are recorded in our database. Researchers are able to access the solar feature database and analyze the solar data efficiently and effectively. The detection and characterization system greatly improves

  9. An Integrative Approach to Accurate Vehicle Logo Detection

    Directory of Open Access Journals (Sweden)

    Hao Pan

    2013-01-01

    required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM, resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.

  10. An integrated automatic system to evaluate U and Th dynamic lixiviation from solid matrices, and to extract/pre-concentrate leached analytes previous ICP-MS detection.

    Science.gov (United States)

    Ceballos, Melisa Rodas; García-Tenorio, Rafael; Estela, José Manuel; Cerdà, Víctor; Ferrer, Laura

    2017-12-01

    Leached fractions of U and Th from different environmental solid matrices were evaluated by an automatic system enabling the on-line lixiviation and extraction/pre-concentration of these two elements previous ICP-MS detection. UTEVA resin was used as selective extraction material. Ten leached fraction, using artificial rainwater (pH 5.4) as leaching agent, and a residual fraction were analyzed for each sample, allowing the study of behavior of U and Th in dynamic lixiviation conditions. Multivariate techniques have been employed for the efficient optimization of the independent variables that affect the lixiviation process. The system reached LODs of 0.1 and 0.7ngkg -1 of U and Th, respectively. The method was satisfactorily validated for three solid matrices, by the analysis of a soil reference material (IAEA-375), a certified sediment reference material (BCR- 320R) and a phosphogypsum reference material (MatControl CSN-CIEMAT 2008). Besides, environmental samples were analyzed, showing a similar behavior, i.e. the content of radionuclides decreases with the successive extractions. In all cases, the accumulative leached fraction of U and Th for different solid matrices studied (soil, sediment and phosphogypsum) were extremely low, up to 0.05% and 0.005% of U and Th, respectively. However, a great variability was observed in terms of mass concentration released, e.g. between 44 and 13,967ngUkg -1 . Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

    Science.gov (United States)

    McIntosh, Dawn

    2006-01-01

    This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

  12. Automated Vehicle Monitoring System

    OpenAIRE

    Wibowo, Agustinus Deddy Arief; Heriansyah, Rudi

    2014-01-01

    An automated vehicle monitoring system is proposed in this paper. The surveillance system is based on image processing techniques such as background subtraction, colour balancing, chain code based shape detection, and blob. The proposed system will detect any human's head as appeared at the side mirrors. The detected head will be tracked and recorded for further action.

  13. Automatic Detection of Cervical Cancer Cells by a Two-Level Cascade Classification System

    Directory of Open Access Journals (Sweden)

    Jie Su

    2016-01-01

    Full Text Available We proposed a method for automatic detection of cervical cancer cells in images captured from thin liquid based cytology slides. We selected 20,000 cells in images derived from 120 different thin liquid based cytology slides, which include 5000 epithelial cells (normal 2500, abnormal 2500, lymphoid cells, neutrophils, and junk cells. We first proposed 28 features, including 20 morphologic features and 8 texture features, based on the characteristics of each cell type. We then used a two-level cascade integration system of two classifiers to classify the cervical cells into normal and abnormal epithelial cells. The results showed that the recognition rates for abnormal cervical epithelial cells were 92.7% and 93.2%, respectively, when C4.5 classifier or LR (LR: logical regression classifier was used individually; while the recognition rate was significantly higher (95.642% when our two-level cascade integrated classifier system was used. The false negative rate and false positive rate (both 1.44% of the proposed automatic two-level cascade classification system are also much lower than those of traditional Pap smear review.

  14. Investigation of Matlab® as platform in navigation and control of an Automatic Guided Vehicle utilising an omnivision sensor.

    Science.gov (United States)

    Kotze, Ben; Jordaan, Gerrit

    2014-08-25

    Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed.

  15. Investigation of Matlab® as Platform in Navigation and Control of an Automatic Guided Vehicle Utilising an Omnivision Sensor

    Directory of Open Access Journals (Sweden)

    Ben Kotze

    2014-08-01

    Full Text Available Automatic Guided Vehicles (AGVs are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed.

  16. Real-time vehicle detection and tracking in video based on faster R-CNN

    Science.gov (United States)

    Zhang, Yongjie; Wang, Jian; Yang, Xin

    2017-08-01

    Vehicle detection and tracking is a significant part in auxiliary vehicle driving system. Using the traditional detection method based on image information has encountered enormous difficulties, especially in complex background. To solve this problem, a detection method based on deep learning, Faster R-CNN, which has very high detection accuracy and flexibility, is introduced. An algorithm of target tracking with the combination of Camshift and Kalman filter is proposed for vehicle tracking. The computation time of Faster R-CNN cannot achieve realtime detection. We use multi-thread technique to detect and track vehicle by parallel computation for real-time application.

  17. Automatic correspondence detection in mammogram and breast tomosynthesis images

    Science.gov (United States)

    Ehrhardt, Jan; Krüger, Julia; Bischof, Arpad; Barkhausen, Jörg; Handels, Heinz

    2012-02-01

    Two-dimensional mammography is the major imaging modality in breast cancer detection. A disadvantage of mammography is the projective nature of this imaging technique. Tomosynthesis is an attractive modality with the potential to combine the high contrast and high resolution of digital mammography with the advantages of 3D imaging. In order to facilitate diagnostics and treatment in the current clinical work-flow, correspondences between tomosynthesis images and previous mammographic exams of the same women have to be determined. In this paper, we propose a method to detect correspondences in 2D mammograms and 3D tomosynthesis images automatically. In general, this 2D/3D correspondence problem is ill-posed, because a point in the 2D mammogram corresponds to a line in the 3D tomosynthesis image. The goal of our method is to detect the "most probable" 3D position in the tomosynthesis images corresponding to a selected point in the 2D mammogram. We present two alternative approaches to solve this 2D/3D correspondence problem: a 2D/3D registration method and a 2D/2D mapping between mammogram and tomosynthesis projection images with a following back projection. The advantages and limitations of both approaches are discussed and the performance of the methods is evaluated qualitatively and quantitatively using a software phantom and clinical breast image data. Although the proposed 2D/3D registration method can compensate for moderate breast deformations caused by different breast compressions, this approach is not suitable for clinical tomosynthesis data due to the limited resolution and blurring effects perpendicular to the direction of projection. The quantitative results show that the proposed 2D/2D mapping method is capable of detecting corresponding positions in mammograms and tomosynthesis images automatically for 61 out of 65 landmarks. The proposed method can facilitate diagnosis, visual inspection and comparison of 2D mammograms and 3D tomosynthesis images for

  18. Towards an automatic lab-on-valve-ion mobility spectrometric system for detection of cocaine abuse.

    Science.gov (United States)

    Cocovi-Solberg, David J; Esteve-Turrillas, Francesc A; Armenta, Sergio; de la Guardia, Miguel; Miró, Manuel

    2017-08-25

    A lab-on-valve miniaturized system integrating on-line disposable micro-solid phase extraction has been interfaced with ion mobility spectrometry for the accurate and sensitive determination of cocaine and ecgonine methyl ester in oral fluids. The method is based on the automatic loading of 500μL of oral fluid along with the retention of target analytes and matrix clean-up by mixed-mode cationic/reversed-phase solid phase beads, followed by elution with 100μL of 2-propanol containing (3% v/v) ammonia, which are online injected into the IMS. The sorptive particles are automatically discarded after every individual assay inasmuch as the sorptive capacity of the sorbent material is proven to be dramatically deteriorated with reuse. The method provided a limit of detection of 0.3 and 0.14μgL -1 for cocaine and ecgonine methyl ester, respectively, with relative standard deviation values from 8 till 14% with a total analysis time per sample of 7.5min. Method trueness was evaluated by analyzing oral fluid samples spiked with cocaine at different concentration levels (1, 5 and 25μgL -1 ) affording relative recoveries within the range of 85±24%. Fifteen saliva samples were collected from volunteers and analysed following the proposed automatic procedure, showing a 40% cocaine occurrence with concentrations ranging from 1.3 to 97μgL -1 . Field saliva samples were also analysed by reference methods based on lateral flow immunoassay and gas chromatography-mass spectrometry. The application of this procedure to the control of oral fluids of cocaine consumers represents a step forward towards the development of a point-of-care cocaine abuse sensing system. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Automatic Rock Detection and Mapping from HiRISE Imagery

    Science.gov (United States)

    Huertas, Andres; Adams, Douglas S.; Cheng, Yang

    2008-01-01

    This system includes a C-code software program and a set of MATLAB software tools for statistical analysis and rock distribution mapping. The major functions include rock detection and rock detection validation. The rock detection code has been evolved into a production tool that can be used by engineers and geologists with minor training.

  20. Hybrid and Electric Advanced Vehicle Systems Simulation

    Science.gov (United States)

    Beach, R. F.; Hammond, R. A.; Mcgehee, R. K.

    1985-01-01

    Predefined components connected to represent wide variety of propulsion systems. Hybrid and Electric Advanced Vehicle System (HEAVY) computer program is flexible tool for evaluating performance and cost of electric and hybrid vehicle propulsion systems. Allows designer to quickly, conveniently, and economically predict performance of proposed drive train.

  1. Armor-piercing bullet: 3-T MRI findings and identification by a ferromagnetic detection system.

    Science.gov (United States)

    Karacozoff, Alexandra M; Pekmezci, Murat; Shellock, Frank G

    2013-03-01

    The objective of this project was to evaluate magnetic resonance imaging (MRI) issues at 3 T for an armor-piercing bullet and to determine if this item could be identified using a ferromagnetic detection system. An armor-piercing bullet (.30 caliber, 7.62 × 39, copper-jacketed round, steel core; Norinco) underwent evaluation for magnetic field interactions, heating, and artifacts using standardized techniques. Heating was assessed with the bullet in a gelled-saline-filled phantom with MRI performed using a transmit/receive radio frequency body coil at a whole-body-averaged specific absorption rate of 2.9 W/kg for 15 minutes. Artifacts were characterized using T1-weighted spin echo and gradient echo pulse sequences. In addition, a special ferromagnetic detection system (Ferroguard Screener; Metrasens, Lisle, Illinois) was used in an attempt to identify this armor-piercing bullet. The findings indicated that the armor-piercing bullet showed substantial magnetic field interactions. Heating was not excessive. Artifacts were large and may create diagnostic problems if the area of interest is close to this bullet. The ferromagnetic detection system yielded a positive result. We concluded that this armor-piercing bullet is MR unsafe. Importantly, this ballistic item was identified using the particular ferromagnetic detection system utilized in this investigation, which has important implications for MRI screening and patient safety. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

  2. Quality assurance program guidelines for application to and use by manufacturers of rail/guideway vehicles, buses, automatic train control systems, and their major subsystems

    Science.gov (United States)

    Witkin, S. A.

    1976-01-01

    Guidelines are presented for a quality assurance system to be implemented by the manufacturer in support of designing, developing, fabricating, assembling, inspecting, testing, handling, and delivery of equipment being procured for use in public urban mass transit systems. The guidelines apply to this equipment when being procured for: (1) use in revenue service; (2) demonstration of systems that will be revenue producing or used by the public; (3) use as a prototype for follow-on operational/revenue producing equipment procurements; and (4) qualification tests.

  3. Advanced hybrid and electric vehicles system optimization and vehicle integration

    CERN Document Server

    2016-01-01

    This contributed volume contains the results of the research program “Agreement for Hybrid and Electric Vehicles”, funded by the International Energy Agency. The topical focus lies on technology options for the system optimization of hybrid and electric vehicle components and drive train configurations which enhance the energy efficiency of the vehicle. The approach to the topic is genuinely interdisciplinary, covering insights from fields. The target audience primarily comprises researchers and industry experts in the field of automotive engineering, but the book may also be beneficial for graduate students.

  4. Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images

    Science.gov (United States)

    Suzani, Amin; Rasoulian, Abtin; Seitel, Alexander; Fels, Sidney; Rohling, Robert N.; Abolmaesumi, Purang

    2015-03-01

    This paper proposes an automatic method for vertebra localization, labeling, and segmentation in multi-slice Magnetic Resonance (MR) images. Prior work in this area on MR images mostly requires user interaction while our method is fully automatic. Cubic intensity-based features are extracted from image voxels. A deep learning approach is used for simultaneous localization and identification of vertebrae. The localized points are refined by local thresholding in the region of the detected vertebral column. Thereafter, a statistical multi-vertebrae model is initialized on the localized vertebrae. An iterative Expectation Maximization technique is used to register the vertebral body of the model to the image edges and obtain a segmentation of the lumbar vertebral bodies. The method is evaluated by applying to nine volumetric MR images of the spine. The results demonstrate 100% vertebra identification and a mean surface error of below 2.8 mm for 3D segmentation. Computation time is less than three minutes per high-resolution volumetric image.

  5. 2013 International Conference on Mechatronics and Automatic Control Systems

    CERN Document Server

    2014-01-01

    This book examines mechatronics and automatic control systems. The book covers important emerging topics in signal processing, control theory, sensors, mechanic manufacturing systems and automation. The book presents papers from the 2013 International Conference on Mechatronics and Automatic Control Systems held in Hangzhou, China on August 10-11, 2013. .

  6. Determination of Free and Total Sulfites in Wine using an Automatic Flow Injection Analysis System with Voltammetric Detection

    OpenAIRE

    Gonçalves, Luís Moreira; Pacheco, João Grosso; Magalhães, Paulo Jorge; Rodrigues, José António; Barros, Aquiles Araújo

    2009-01-01

    Abstract An automated Flow Injection Analysis (FIA) system based on a initial analyte separation by gas-diffusion and subsequent determination by square-wave voltammetry (SWV) in a flow cell is proposed for the determination of total and free content of sulphur dioxide (SO2) in wine. The proposed method was compared with two iodometric methodologies (the Ripper method and the simplified method commonly used by the wine industry). The developed method shown repeatability (RSD lower ...

  7. Biological agent detection and identification using pattern recognition

    Science.gov (United States)

    Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Transue, Kevin D.

    2005-05-01

    This paper discusses a novel approach for the automatic identification of biological agents. The essence of the approach is a combination of gene expression, microarray-based sensing, information fusion, machine learning and pattern recognition. Integration of these elements is a distinguishing aspect of the approach, leading to a number of significant advantages. Amongst them are the applicability to various agent types including bacteria, viruses, toxins, and other, ability to operate without the knowledge of a pathogen's genome sequence and without the need for bioagent-speciific materials or reagents, and a high level of extensibility. Furthermore, the approach allows detection of uncatalogued agents, including emerging pathogens. The approach offers a promising avenue for automatic identification of biological agents for applications such as medical diagnostics, bioforensics, and biodefense.

  8. Roll-to-Roll Screen Printed Radio Frequency Identification Transponder Antennas for Vehicle Tracking Systems

    Science.gov (United States)

    Zichner, Ralf; Baumann, Reinhard R.

    2013-05-01

    Vehicle tracking systems based on ultra high frequency (UHF) radio frequency identification (RFID) technology are already introduced to control the access to car parks and corporate premises. For this field of application so-called Windshield RFID transponder labels are used, which are applied to the inside of the windshield. State of the art for manufacturing these transponder antennas is the traditional lithography/etching approach. Furthermore the performance of these transponders is limited to a reading distance of approximately 5 m which results in car speed limit of 5 km/h for identification. However, to achieve improved performance compared to existing all-purpose transponders and a dramatic cost reduction, an optimized antenna design is needed which takes into account the special dielectric and in particular metallic car environment of the tag and an roll-to-roll (R2R) printing manufacturing process. In this paper we focus on the development of a customized UHF RFID transponder antenna design, which is adopted for vehicle geometry as well as R2R screen printing manufacturing processes.

  9. Infrared machine vision system for the automatic detection of olive fruit quality.

    Science.gov (United States)

    Guzmán, Elena; Baeten, Vincent; Pierna, Juan Antonio Fernández; García-Mesa, José A

    2013-11-15

    External quality is an important factor in the extraction of olive oil and the marketing of olive fruits. The appearance and presence of external damage are factors that influence the quality of the oil extracted and the perception of consumers, determining the level of acceptance prior to purchase in the case of table olives. The aim of this paper is to report on artificial vision techniques developed for the online estimation of olive quality and to assess the effectiveness of these techniques in evaluating quality based on detecting external defects. This method of classifying olives according to the presence of defects is based on an infrared (IR) vision system. Images of defects were acquired using a digital monochrome camera with band-pass filters on near-infrared (NIR). The original images were processed using segmentation algorithms, edge detection and pixel value intensity to classify the whole fruit. The detection of the defect involved a pixel classification procedure based on nonparametric models of the healthy and defective areas of olives. Classification tests were performed on olives to assess the effectiveness of the proposed method. This research showed that the IR vision system is a useful technology for the automatic assessment of olives that has the potential for use in offline inspection and for online sorting for defects and the presence of surface damage, easily distinguishing those that do not meet minimum quality requirements. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.

  10. Traffic Information Unit, Traffic Information System, Vehicle Management System, Vehicle, and Method of Controlling a Vehicle

    NARCIS (Netherlands)

    Papp, Z.; Doodeman, G.J.N.; Nelisse, M.W.; Sijs, J.; Theeuwes, J.A.C.; Driessen, B.J.F.

    2010-01-01

    A traffic information unit (MD1, MD2, MD3) according to the invention comprises a facility (MI) for tracking vehicle state information of individual vehicles present at a traffic infrastructure and a facility (T) for transmitting said vehicle state information to a vehicle (70B, 70E). A traffic

  11. Smart mobile in-vehicle systems next generation advancements

    CERN Document Server

    Abut, Huseyin; Takeda, Kazuya; Hansen, John

    2014-01-01

    This is an edited collection by world-class experts, from diverse fields, focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. The book presents developments on road safety, in-vehicle technologies and state-of-the art systems. Includes coverage of DSP technologies in adaptive automobiles, algorithms and evaluation of in-car communication systems, driver-status monitoring and stress detection, in-vehicle dialogue systems and human-machine interfaces, challenges in video and audio processing for in-vehicle products, multi-sensor fusion for driver identification and vehicle to infrastructure wireless technologies.

  12. Automatic age-related macular degeneration detection and staging

    Science.gov (United States)

    van Grinsven, Mark J. J. P.; Lechanteur, Yara T. E.; van de Ven, Johannes P. H.; van Ginneken, Bram; Theelen, Thomas; Sánchez, Clara I.

    2013-03-01

    Age-related macular degeneration (AMD) is a degenerative disorder of the central part of the retina, which mainly affects older people and leads to permanent loss of vision in advanced stages of the disease. AMD grading of non-advanced AMD patients allows risk assessment for the development of advanced AMD and enables timely treatment of patients, to prevent vision loss. AMD grading is currently performed manually on color fundus images, which is time consuming and expensive. In this paper, we propose a supervised classification method to distinguish patients at high risk to develop advanced AMD from low risk patients and provide an exact AMD stage determination. The method is based on the analysis of the number and size of drusen on color fundus images, as drusen are the early characteristics of AMD. An automatic drusen detection algorithm is used to detect all drusen. A weighted histogram of the detected drusen is constructed to summarize the drusen extension and size and fed into a random forest classifier in order to separate low risk from high risk patients and to allow exact AMD stage determination. Experiments showed that the proposed method achieved similar performance as human observers in distinguishing low risk from high risk AMD patients, obtaining areas under the Receiver Operating Characteristic curve of 0.929 and 0.934. A weighted kappa agreement of 0.641 and 0.622 versus two observers were obtained for AMD stage evaluation. Our method allows for quick and reliable AMD staging at low costs.

  13. Automatic facial pore analysis system using multi-scale pore detection.

    Science.gov (United States)

    Sun, J Y; Kim, S W; Lee, S H; Choi, J E; Ko, S J

    2017-08-01

    As facial pore widening and its treatments have become common concerns in the beauty care field, the necessity for an objective pore-analyzing system has been increased. Conventional apparatuses lack in usability requiring strong light sources and a cumbersome photographing process, and they often yield unsatisfactory analysis results. This study was conducted to develop an image processing technique for automatic facial pore analysis. The proposed method detects facial pores using multi-scale detection and optimal scale selection scheme and then extracts pore-related features such as total area, average size, depth, and the number of pores. Facial photographs of 50 subjects were graded by two expert dermatologists, and correlation analyses between the features and clinical grading were conducted. We also compared our analysis result with those of conventional pore-analyzing devices. The number of large pores and the average pore size were highly correlated with the severity of pore enlargement. In comparison with the conventional devices, the proposed analysis system achieved better performance showing stronger correlation with the clinical grading. The proposed system is highly accurate and reliable for measuring the severity of skin pore enlargement. It can be suitably used for objective assessment of the pore tightening treatments. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. Automatic Registration of Vehicle-borne Mobile Mapping Laser Point Cloud and Sequent Panoramas

    Directory of Open Access Journals (Sweden)

    CHEN Chi

    2018-02-01

    Full Text Available An automatic registration method of mobile mapping system laser point cloud and sequence panoramic image is proposed in this paper.Firstly,hierarchical object extraction method is applied on LiDAR data to extract the building façade and outline polygons are generated to construct the skyline vectors.A virtual imaging method is proposed to solve the distortion on panoramas and corners on skylines are further detected on the virtual images combining segmentation and corner detection results.Secondly,the detected skyline vectors are taken as the registration primitives.Registration graphs are built according to the extracted skyline vector and further matched under graph edit distance minimization criteria.The matched conjugate primitives are utilized to solve the 2D-3D rough registration model to obtain the initial transformation between the sequence panoramic image coordinate system and the LiDAR point cloud coordinate system.Finally,to reduce the impact of registration primitives extraction and matching error on the registration results,the optimal transformation between the multi view stereo matching dens point cloud generated from the virtual imaging of the sequent panoramas and the LiDAR point cloud are solved by a 3D-3D ICP registration algorithm variant,thus,refine the exterior orientation parameters of panoramas indirectly.Experiments are undertaken to validate the proposed method and the results show that 1.5 pixel level registration results are achieved on the experiment dataset.The registration results can be applied to point cloud and panoramas fusion applications such as true color point cloud generation.

  15. VEDS-Automated system for inspection of vehicles and containers for explosives and other threats

    International Nuclear Information System (INIS)

    Gozani, T.; Liu, F.; Sivakumar, M.

    2004-01-01

    Many parts of national infrastructures around the world are very vulnerable to terrorist threats in the form of large vehicle bombs. The larger bomb, the larger is the damage and its extent. The number of containers and vehicles crossing land or sea ports of entry is huge. Tough the probability is low, any vehicle may contain a threat. Any system addressing these enormous security tasks should obviously be based on excellent human intelligence to focus the attention on a much smaller number of high-risk containers and vehicles. These containers must then be subjected to a thorough and reliable inspection for the threats.Viable security system must incorporate a credible and effective inspection to achieve its purposes. It should have high performance and be operationally acceptable. This means the system must possess high detection capabilities, low false positive rate, fast response and provide automatic decision eliminating the need for human interpretation. Ancore has developed a range of new inspection devices, which are highly suitable for the above tasks. All the systems are automatic, material specific, high performance for a wide range and type of threats. Some of them are also highly modular, and compact. Some of the systems are fixed, other are relocatable, or fully mobile. The presentation will discuss Ancore's VEDS (Vehicle Explosive Detection System) which detects bulk explosives (expandable also to radiological and nuclear threats)) in marine containers, trucks and cars. The compact and rugged nature of the VEDS sensor makes it suitable for many forms of conveyance: mobile (van mounted), portal, forklift mounted, or mounted on container unloading rig. The physics principles of the system and some recent applications and results will be presented

  16. AUTOMATIC IDENTIFICATION OF ITEMS IN WAREHOUSE MANAGEMENT

    OpenAIRE

    Vladimír Modrák; Peter Knuth

    2010-01-01

    Automatic identification of items saves time and is beneficial in various areas, including warehouse management. Identification can be done by many technologies, but RFID technology seems to be one of the smartest solutions. This article deals with testing and possible use of RFID technology in warehouse management. All results and measurement outcomes are documented in form of graphs followed by comprehensive analysis.

  17. Vehicle detection based on the use of shadow region and edge

    Science.gov (United States)

    Jeong, Sangheon; Kang, Seongkoo; Kim, Joongkyu

    2013-07-01

    Automotive and advanced driver assistance systems have attracted a great deal of attention lately. In these systems, effective and reliable vehicle detection is important because such systems can reduce the number of accidents and save human' lives. This paper describes an approach to detecting a forward vehicle using a camera mounted on the moving vehicle. In this paper, we describe two methods to detect a vehicle on the road. First, by using the vehicle's shadow, we can obtain the general location of the vehicular candidate. Second, we can identify the strong vertical edges at the left and right position of a vehicle. By combining the shadows and the edge, we can detect the vehicle's location. But other regions may also be detected, such as car windows, reflections, and illumination by the sun. In order to remove these other factors, defined as noises, we need to use a filter. After using the filter, we can calculate the exact location of the vehicle. Additionally, by using connected component labeling, we can obtain coordinates and establish the vehicle's location. Connected component labeling find all connected components in an image and assigns a unique label to all points in the same component. These methods are very useful for vehicle detection and the development of the driving assistance systems, and they can protect drivers' safety from having an accident.

  18. Quaternized magnetic nanoparticles-fluorescent polymer system for detection and identification of bacteria.

    Science.gov (United States)

    Wan, Yi; Sun, Yan; Qi, Peng; Wang, Peng; Zhang, Dun

    2014-05-15

    Nanomaterial-based 'chemical nose' sensor with sufficient sensing specificity is a useful analytical tool for the detection of toxicologically important substances in complicated biological systems. A sensor array containing three quaternized magnetic nanoparticles (q-MNPs)-fluorescent polymer systems has been designed to identify and quantify bacteria. The bacterial cell membranes disrupt the q-MNP-fluorescent polymer, generating unique fluorescence response array. The response intensity of the array is dependent on the level of displacement determined by the relative q-MNP-fluorescent polymer binding strength and bacteria cells-MNP interaction. These characteristic responses show a highly repeatable bacteria cells and can be differentiated by linear discriminant analysis (LDA). Based on the array response matrix from LDA, our approach has been used to measure bacteria with an accuracy of 87.5% for 10(7) cfu mL(-1) within 20 min. Combined with UV-vis measurement, the method can be successfully performed to identify and detect eight different pathogen samples with an accuracy of 96.8%. The measurement system has a potential for further applications and provides a facile and simple method for the rapid analysis of protein, DNA, and pathogens. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. Hotspot Patterns: The Formal Definition and Automatic Detection of Architecture Smells

    Science.gov (United States)

    2015-01-15

    Hotspot Patterns: The Formal Definition and Automatic Detection of Architecture Smells Ran Mo∗, Yuanfang Cai∗, Rick Kazman†, Lu Xiao∗ ∗ Drexel...they are associated with extremely high error-proneness and/or change-proneness, cannot be characterized by existing notions such as code smells [7...software system. Code Smell Detection: Fowler [7] describes the concept of a “bad smell ” as a heuristic for identifying refactoring opportunities. Code

  20. Building a robust vehicle detection and classification module

    Science.gov (United States)

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

    2015-12-01

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

  1. Implementation of a real-time automatic onset time detection for surface electromyography measurement systems using NI myRIO

    Directory of Open Access Journals (Sweden)

    Lersviriyanantakul Chaiwat

    2016-01-01

    Full Text Available For using surface electromyography (sEMG in various applications, the process consists of three parts: an onset time detection for detecting the first point of movement signals, a feature extraction for extracting the signal attribution, and a feature classification for classifying the sEMG signals. The first and the most significant part that influences the accuracy of other parts is the onset time detection, particularly for automatic systems. In this paper, an automatic and simple algorithm for the real-time onset time detection is presented. There are two main processes in the proposed algorithm; a smoothing process for reducing the noise of the measured sEMG signals and an automatic threshold calculation process for determining the onset time. The results from the algorithm analysis demonstrate the performance of the proposed algorithm to detect the sEMG onset time in various smoothing-threshold equations. Our findings reveal that using a simple square integral (SSI as the smoothing-threshold equation with the given sEMG signals gives the best performance for the onset time detection. Additionally, our proposed algorithm is also implemented on a real hardware platform, namely NI myRIO. Using the real-time simulated sEMG data, the experimental results guarantee that the proposed algorithm can properly detect the onset time in the real-time manner.

  2. Automatic Detection of Fake News

    OpenAIRE

    Pérez-Rosas, Verónica; Kleinberg, Bennett; Lefevre, Alexandra; Mihalcea, Rada

    2017-01-01

    The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online news. Our contribution is twofold. First, we introduce two novel datasets for the task of fake news...

  3. Fundamental problems in fault detection and identification

    DEFF Research Database (Denmark)

    Saberi, Ali; Stoorvogel, Anton A.; Sannuti, Peddapullaiah

    1999-01-01

    For certain fundamental problems in fault detection and identification, the necessary and sufficient conditions for their solvability are derived. These conditions are weaker than the ones found in the literature, since we do not assume any particular structure for the residual generator......For certain fundamental problems in fault detection and identification, the necessary and sufficient conditions for their solvability are derived. These conditions are weaker than the ones found in the literature, since we do not assume any particular structure for the residual generator...

  4. Automatic Detection and Resolution of Lexical Ambiguity in Process Models

    NARCIS (Netherlands)

    Pittke, F.; Leopold, H.; Mendling, J.

    2015-01-01

    System-related engineering tasks are often conducted using process models. In this context, it is essential that these models do not contain structural or terminological inconsistencies. To this end, several automatic analysis techniques have been proposed to support quality assurance. While formal

  5. Lane Detection in Video-Based Intelligent Transportation Monitoring via Fast Extracting and Clustering of Vehicle Motion Trajectories

    Directory of Open Access Journals (Sweden)

    Jianqiang Ren

    2014-01-01

    Full Text Available Lane detection is a crucial process in video-based transportation monitoring system. This paper proposes a novel method to detect the lane center via rapid extraction and high accuracy clustering of vehicle motion trajectories. First, we use the activity map to realize automatically the extraction of road region, the calibration of dynamic camera, and the setting of three virtual detecting lines. Secondly, the three virtual detecting lines and a local background model with traffic flow feedback are used to extract and group vehicle feature points in unit of vehicle. Then, the feature point groups are described accurately by edge weighted dynamic graph and modified by a motion-similarity Kalman filter during the sparse feature point tracking. After obtaining the vehicle trajectories, a rough k-means incremental clustering with Hausdorff distance is designed to realize the rapid online extraction of lane center with high accuracy. The use of rough set reduces effectively the accuracy decrease, which results from the trajectories that run irregularly. Experimental results prove that the proposed method can detect lane center position efficiently, the affected time of subsequent tasks can be reduced obviously, and the safety of traffic surveillance systems can be enhanced significantly.

  6. Encryption and validation of multiple signals for optical identification systems

    Energy Technology Data Exchange (ETDEWEB)

    Perez-Cabre, E [Universitat PoliteGcnica de Catalunya, Department Optica i Optometria, Violinista Vellsola 37, 08222 Terrassa (Spain); Millan, M S [Universitat PoliteGcnica de Catalunya, Department Optica i Optometria, Violinista Vellsola 37, 08222 Terrassa (Spain); Javidi, B [University of Connecticut, Electrical and Computer Engineering Department, 371 Fairfield Road, CT 06269 Storrs (United States)

    2007-07-15

    Multifactor encryption-authentication technique reinforces optical security by allowing the simultaneous A N D-verification of more than one primary image. Instead of basing the identification on a unique signature or piece of information, our goal is to authenticate a given person, object, vehicle by the simultaneous recognition of several factors. Some of them are intrinsic to the person and object or vehicle under control. Other factors, act as keys of the authentication step. Such a system is proposed for situations such as the access control to restricted areas, where the demand of security is high. The multifactor identification method involves double random-phase encoding, fully phase-based encryption and a combined nonlinear joint transform correlator and a classical 4f-correlator for simultaneous recognition and authentication of multiple images. The encoded signal fulfils the general requirements of invisible content, extreme difficulty in counterfeiting and real-time automatic verification. Four reference double-phase encoded images are compared with the retrieved input images obtained in situ from the person or the vehicle whose authentication is wanted and from a database. A recognition step based on the correlation between the signatures and the stored references determines the authentication or rejection of the person and object under surveillance.

  7. Long Baseline Stereovision for Automatic Detection and Ranging of Moving Objects in the Night Sky

    Directory of Open Access Journals (Sweden)

    Vlad Turcu

    2012-09-01

    Full Text Available As the number of objects in Earth’s atmosphere and in low Earth orbit is continuously increasing; accurate surveillance of these objects has become important. This paper presents a generic, low cost sky surveillance system based on stereovision. Two cameras are placed 37 km apart and synchronized by a GPS-controlled external signal. The intrinsic camera parameters are calibrated before setup in the observation position, the translation vectors are determined from the GPS coordinates and the rotation matrices are continuously estimated using an original automatic calibration methodology based on following known stars. The moving objects in the sky are recognized as line segments in the long exposure images, using an automatic detection and classification algorithm based on image processing. The stereo correspondence is based on the epipolar geometry and is performed automatically using the image detection results. The resulting experimental system is able to automatically detect moving objects such as planes, meteors and Low Earth Orbit satellites, and measure their 3D position in an Earth-bound coordinate system.

  8. Extended-Search, Bézier Curve-Based Lane Detection and Reconstruction System for an Intelligent Vehicle

    Directory of Open Access Journals (Sweden)

    Xiaoyun Huang

    2015-09-01

    Full Text Available To improve the real-time performance and detection rate of a Lane Detection and Reconstruction (LDR system, an extended-search-based lane detection method and a Bézier curve-based lane reconstruction algorithm are proposed in this paper. The extended-search-based lane detection method is designed to search boundary blocks from the initial position, in an upwards direction and along the lane, with small search areas including continuous search, discontinuous search and bending search in order to detect different lane boundaries. The Bézier curve-based lane reconstruction algorithm is employed to describe a wide range of lane boundary forms with comparatively simple expressions. In addition, two Bézier curves are adopted to reconstruct the lanes' outer boundaries with large curvature variation. The lane detection and reconstruction algorithm — including initial-blocks' determining, extended search, binarization processing and lane boundaries' fitting in different scenarios — is verified in road tests. The results show that this algorithm is robust against different shadows and illumination variations; the average processing time per frame is 13 ms. Significantly, it presents an 88.6% high-detection rate on curved lanes with large or variable curvatures, where the accident rate is higher than that of straight lanes.

  9. Automatic Test Systems Aquisition

    National Research Council Canada - National Science Library

    1994-01-01

    We are providing this final memorandum report for your information and use. This report discusses the efforts to achieve commonality in standards among the Military Departments as part of the DoD policy for automatic test systems (ATS...

  10. Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles.

    Science.gov (United States)

    Yoon, Hyungchul; Hoskere, Vedhus; Park, Jong-Woong; Spencer, Billie F

    2017-09-11

    Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc.) are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs) to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1) estimation of an appropriate scale factor; and (2) compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach.

  11. Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Hyungchul Yoon

    2017-09-01

    Full Text Available Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc. are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1 estimation of an appropriate scale factor; and (2 compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach.

  12. Vehicles Potholes Detection Based Blob Detection Method and Neural Network Backpropagation Model

    OpenAIRE

    Dewiani, Dewiani; Achmad, Andani; Parung, Rivanto

    2016-01-01

    In Indonesia, especially on developing area, many potholes are occurred almost on every part of the road. The situation is exacerbated on how potholes location data gathering is performed manually by field personnel of the Department of Transportation or other related services, which would require more time and cost. This study aimed to produce a prototype of detection system and potholes location automatically. The prototype is a device attached on public transport so that it can be a soluti...

  13. Automatic identification of algal community from microscopic images.

    Science.gov (United States)

    Santhi, Natchimuthu; Pradeepa, Chinnaraj; Subashini, Parthasarathy; Kalaiselvi, Senthil

    2013-01-01

    A good understanding of the population dynamics of algal communities is crucial in several ecological and pollution studies of freshwater and oceanic systems. This paper reviews the subsequent introduction to the automatic identification of the algal communities using image processing techniques from microscope images. The diverse techniques of image preprocessing, segmentation, feature extraction and recognition are considered one by one and their parameters are summarized. Automatic identification and classification of algal community are very difficult due to various factors such as change in size and shape with climatic changes, various growth periods, and the presence of other microbes. Therefore, the significance, uniqueness, and various approaches are discussed and the analyses in image processing methods are evaluated. Algal identification and associated problems in water organisms have been projected as challenges in image processing application. Various image processing approaches based on textures, shapes, and an object boundary, as well as some segmentation methods like, edge detection and color segmentations, are highlighted. Finally, artificial neural networks and some machine learning algorithms were used to classify and identifying the algae. Further, some of the benefits and drawbacks of schemes are examined.

  14. Tracking of Vehicle Movement on a Parking Lot Based on Video Detection

    Directory of Open Access Journals (Sweden)

    Ján HALGAŠ

    2014-06-01

    Full Text Available This article deals with topic of transport vehicles identification for dynamic and static transport based on video detection. It explains some of the technologies and approaches necessary for processing of specific image information (transport situation. The paper also describes a design of algorithm for vehicle detection on parking lot and consecutive record of trajectory into virtual environment. It shows a new approach to moving object detection (vehicles, people, and handlers on an enclosed area with emphasis on secure parking. The created application enables automatic identification of trajectory of specific objects moving within the parking area. The application was created in program language C++ with using an open source library OpenCV.

  15. Developmental differences in auditory detection and localization of approaching vehicles.

    Science.gov (United States)

    Barton, Benjamin K; Lew, Roger; Kovesdi, Casey; Cottrell, Nicholas D; Ulrich, Thomas

    2013-04-01

    Pedestrian safety is a significant problem in the United States, with thousands being injured each year. Multiple risk factors exist, but one poorly understood factor is pedestrians' ability to attend to vehicles using auditory cues. Auditory information in the pedestrian setting is increasing in importance with the growing number of quieter hybrid and all-electric vehicles on America's roadways that do not emit sound cues pedestrians expect from an approaching vehicle. Our study explored developmental differences in pedestrians' detection and localization of approaching vehicles. Fifty children ages 6-9 years, and 35 adults participated. Participants' performance varied significantly by age, and with increasing speed and direction of the vehicle's approach. Results underscore the importance of understanding children's and adults' use of auditory cues for pedestrian safety and highlight the need for further research. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Assessment of cognitive workload of in-vehicle systems using a visual peripheral and tactile detection task setting.

    Science.gov (United States)

    Bengler, Klaus; Kohlmann, Martin; Lange, Christian

    2012-01-01

    The increase of driver information and infotainment systems includes also interaction technologies like speech interaction that minimize visual-manual demand and put the focus to cognitive demand. The question is whether this could lead to distraction effects and decreased traffic safety. This study presents an evaluation method for cognitive demand based on different detection paradigms in a dual task setting. A listening and a backward counting task are realized on three difficulty levels as simulations of cognitively loading secondary tasks and investigated using a visual versus a tactile detection paradigm. The results show that both detection paradigms are able to discriminate the task levels and that subjects successfully apply compensation strategies in the dual task setting especially during the listening task.

  17. Terminal Sliding Mode Tracking Controller Design for Automatic Guided Vehicle

    Science.gov (United States)

    Chen, Hongbin

    2018-03-01

    Based on sliding mode variable structure control theory, the path tracking problem of automatic guided vehicle is studied, proposed a controller design method based on the terminal sliding mode. First of all, through analyzing the characteristics of the automatic guided vehicle movement, the kinematics model is presented. Then to improve the traditional expression of terminal sliding mode, design a nonlinear sliding mode which the convergence speed is faster than the former, verified by theoretical analysis, the design of sliding mode is steady and fast convergence in the limited time. Finally combining Lyapunov method to design the tracking control law of automatic guided vehicle, the controller can make the automatic guided vehicle track the desired trajectory in the global sense as well as in finite time. The simulation results verify the correctness and effectiveness of the control law.

  18. A smart pattern recognition system for the automatic identification of aerospace acoustic sources

    Science.gov (United States)

    Cabell, R. H.; Fuller, C. R.

    1989-01-01

    An intelligent air-noise recognition system is described that uses pattern recognition techniques to distinguish noise signatures of five different types of acoustic sources, including jet planes, propeller planes, a helicopter, train, and wind turbine. Information for classification is calculated using the power spectral density and autocorrelation taken from the output of a single microphone. Using this system, as many as 90 percent of test recordings were correctly identified, indicating that the linear discriminant functions developed can be used for aerospace source identification.

  19. Safety problems in vehicles with adaptive cruise control system

    Directory of Open Access Journals (Sweden)

    Yadav Arun K.

    2017-06-01

    Full Text Available In today’s world automotive industries are still putting efforts towards more autonomous vehicles (AVs. The main concern of introducing the autonomous technology is safety of driver. According to a survey 90% of accidents happen due to mistake of driver. The adaptive cruise control system (ACC is a system which combines cruise control with a collision avoidance system. The ACC system is based on laser and radar technologies. This system is capable of controlling the velocity of vehicle automatically to match the velocity of car, bus or truck in front of vehicle. If the lead vehicle gets slow down or accelerate, than ACC system automatically matches that velocity. The proposed paper is focusing on more accurate methods of detecting the preceding vehicle by using a radar and lidar sensors by considering the vehicle side slip and by controlling the distance between two vehicles. By using this approach i.e. logic for calculation of former vehicle distance and controlling the throttle valve of ACC equipped vehicle, an improvement in driving stability was achieved. The own contribution results with fuel efficient driving and with more safer and reliable driving system, but still some improvements are going on to make it more safe and reliable.

  20. Automatic identification of mass spectra

    International Nuclear Information System (INIS)

    Drabloes, F.

    1992-01-01

    Several approaches to preprocessing and comparison of low resolution mass spectra have been evaluated by various test methods related to library search. It is shown that there is a clear correlation between the nature of any contamination of a spectrum, the basic principle of the transformation or distance measure, and the performance of the identification system. The identification of functionality from low resolution spectra has also been evaluated using several classification methods. It is shown that there is an upper limit to the success of this approach, but also that this can be improved significantly by using a very limited amount of additional information. 10 refs

  1. Child vocalization composition as discriminant information for automatic autism detection.

    Science.gov (United States)

    Xu, Dongxin; Gilkerson, Jill; Richards, Jeffrey; Yapanel, Umit; Gray, Sharmi

    2009-01-01

    Early identification is crucial for young children with autism to access early intervention. The existing screens require either a parent-report questionnaire and/or direct observation by a trained practitioner. Although an automatic tool would benefit parents, clinicians and children, there is no automatic screening tool in clinical use. This study reports a fully automatic mechanism for autism detection/screening for young children. This is a direct extension of the LENA (Language ENvironment Analysis) system, which utilizes speech signal processing technology to analyze and monitor a child's natural language environment and the vocalizations/speech of the child. It is discovered that child vocalization composition contains rich discriminant information for autism detection. By applying pattern recognition and machine learning approaches to child vocalization composition data, accuracy rates of 85% to 90% in cross-validation tests for autism detection have been achieved at the equal-error-rate (EER) point on a data set with 34 children with autism, 30 language delayed children and 76 typically developing children. Due to its easy and automatic procedure, it is believed that this new tool can serve a significant role in childhood autism screening, especially in regards to population-based or universal screening.

  2. Nuclear Materials Identification System (NMIS) with Gamma Spectrometry for Attributes of Pu, HEU, and Detection of HE and Chemical Agents

    International Nuclear Information System (INIS)

    Mihalczo, J. T.; Mattingly, J. K.; Mullens, J. A.; Neal, J. S.

    2002-01-01

    A combined Nuclear Materials Identification System (NMIS)-gamma ray spectrometry system can be used passively to obtain the following attributes of Pu: presence, fissile mass, 240/239 ratio, and metal vs. oxide. This system can also be used with a small, portable, DT neutron generator to measure the attributes of highly enriched uranium (HEU): presence, fissile mass, enrichment, metal vs. oxide; and detect the presence of high explosives (HE). For the passive system, time-dependent coincidence distributions can be used for the presence, fissile mass, metal vs. oxide for Pu, and gamma-ray spectrometry can be used for 239/240 ratio and presence. So presence can be confirmed by two methods. For the active system with a DT neutron generator, all four attributes for both Pu and HEU can be determined from various features of the time-dependent coincidence distribution measurements for both Pu and HEU. Active gamma ray spectrometry would also give presence and 240/239 ratio for Pu, enrichment for HEU, and metal vs. oxide for both. Active gamma ray spectrometry would determine the presence of HE. The various features of time-dependent coincidence distributions and gamma ray spectrometry that determine these attributes are discussed with some examples from previous determinations

  3. Efficient video-equipped fire detection approach for automatic fire alarm systems

    Science.gov (United States)

    Kang, Myeongsu; Tung, Truong Xuan; Kim, Jong-Myon

    2013-01-01

    This paper proposes an efficient four-stage approach that automatically detects fire using video capabilities. In the first stage, an approximate median method is used to detect video frame regions involving motion. In the second stage, a fuzzy c-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and nonfire. Experimental results indicate that the proposed four-stage approach outperforms other fire detection algorithms in terms of consistently increasing the accuracy of fire detection in both indoor and outdoor test videos.

  4. Anatomy-based automatic detection and segmentation of major vessels in thoracic CTA images

    International Nuclear Information System (INIS)

    Zou Xiaotao; Liang Jianming; Wolf, M.; Salganicoff, M.; Krishnan, A.; Nadich, D.P.

    2007-01-01

    Existing approaches for automated computerized detection of pulmonary embolism (PE) using computed tomography angiography (CTA) usually focus on segmental and sub-segmental emboli. The goal of our current research is to extend our existing approach to automated detection of central PE. In order to detect central emboli, the major vessels must be first identified and segmented automatically. This submission presents an anatomy-based method for automatic computerized detection and segmentation of aortas and main pulmonary arteries in CTA images. (orig.)

  5. Deploying Electronic Roadside Vehicle Identification Technology to ...

    African Journals Online (AJOL)

    challenges to handle in order to liberate her citizens from the bondage of insecurity of lives and property ... light armour and helicopters”. Though .... These problems and more can be avoided if automated road side vehicle identification system is deployed at the road sides. This will track down any arms or ammunition being.

  6. A new technology for automatic identification and sorting of plastics for recycling.

    Science.gov (United States)

    Ahmad, S R

    2004-10-01

    A new technology for automatic sorting of plastics, based upon optical identification of fluorescence signatures of dyes, incorporated in such materials in trace concentrations prior to product manufacturing, is described. Three commercial tracers were selected primarily on the basis of their good absorbency in the 310-370 nm spectral band and their identifiable narrow-band fluorescence signatures in the visible band of the spectrum when present in binary combinations. This absorption band was selected because of the availability of strong emission lines in this band from a commercial Hg-arc lamp and high fluorescence quantum yields of the tracers at this excitation wavelength band. The plastics chosen for tracing and identification are HDPE, LDPE, PP, EVA, PVC and PET and the tracers were compatible and chemically non-reactive with the host matrices and did not affect the transparency of the plastics. The design of a monochromatic and collimated excitation source, the sensor system are described and their performances in identifying and sorting plastics doped with tracers at a few parts per million concentration levels are evaluated. In an industrial sorting system, the sensor was able to sort 300 mm long plastic bottles at a conveyor belt speed of 3.5 m.sec(-1) with a sorting purity of -95%. The limitation was imposed due to mechanical singulation irregularities at high speed and the limited processing speed of the computer used.

  7. Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm

    Directory of Open Access Journals (Sweden)

    Yazan M. Alomari

    2014-01-01

    Full Text Available Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs and red blood cells (RBCs in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD algorithm to solve the initialization problem, detecting irregular circles (cells, selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.

  8. Characteristics and design improvement of AP1000 automatic depressurization system

    International Nuclear Information System (INIS)

    Jin Fei

    2012-01-01

    Automatic depressurization system, as a specialty of AP1000 Design, enhances capability of mitigating design basis accidents for plant. Advancement of the system is discussed by comparing with traditional PWR design and analyzing system functions, such as depressurizing and venting. System design improvement during China Project performance is also described. At the end, suggestions for the system in China Project are listed. (author)

  9. Automatic concrete cracks detection and mapping of terrestrial laser scan data

    Directory of Open Access Journals (Sweden)

    Mostafa Rabah

    2013-12-01

    The current paper submits a method for automatic concrete cracks detection and mapping from the data that was obtained during laser scanning survey. The method of cracks detection and mapping is achieved by three steps, namely the step of shading correction in the original image, step of crack detection and finally step of crack mapping and processing steps. The detected crack is defined in a pixel coordinate system. To remap the crack into the referred coordinate system, a reverse engineering is used. This is achieved by a hybrid concept of terrestrial laser-scanner point clouds and the corresponding camera image, i.e. a conversion from the pixel coordinate system to the terrestrial laser-scanner or global coordinate system. The results of the experiment show that the mean differences between terrestrial laser scan and the total station are about 30.5, 16.4 and 14.3 mms in x, y and z direction, respectively.

  10. Automatic Detection of Epilepsy and Seizure Using Multiclass Sparse Extreme Learning Machine Classification.

    Science.gov (United States)

    Wang, Yuanfa; Li, Zunchao; Feng, Lichen; Zheng, Chuang; Zhang, Wenhao

    2017-01-01

    An automatic detection system for distinguishing normal, ictal, and interictal electroencephalogram (EEG) signals is of great help in clinical practice. This paper presents a three-class classification system based on discrete wavelet transform (DWT) and the nonlinear sparse extreme learning machine (SELM) for epilepsy and epileptic seizure detection. Three-level lifting DWT using Daubechies order 4 wavelet is introduced to decompose EEG signals into delta, theta, alpha, and beta subbands. Considering classification accuracy and computational complexity, the maximum and standard deviation values of each subband are computed to create an eight-dimensional feature vector. After comparing five multiclass SELM strategies, the one-against-one strategy with the highest accuracy is chosen for the three-class classification system. The performance of the designed three-class classification system is tested with publicly available epilepsy dataset. The results show that the system achieves high enough classification accuracy by combining the SELM and DWT and reduces training and testing time by decreasing computational complexity and feature dimension. With excellent classification performance and low computation complexity, this three-class classification system can be utilized for practical epileptic EEG detection, and it offers great potentials for portable automatic epilepsy and seizure detection system in the future hardware implementation.

  11. Adaptive Filtering and System Identification

    National Research Council Canada - National Science Library

    Gibson, Steve

    2007-01-01

    .... Additional application areas include optical wireless communication systems, blind identification and deconvolution in wireless communications, and active control of noise and vibration. This report discusses recent collaborations with the Air Force Research Laboratory (AFRL) and industry.

  12. Automatic Detection of Electric Power Troubles (ADEPT)

    Science.gov (United States)

    Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint; Brady, Mike; Ford, Donnie

    1988-11-01

    Automatic Detection of Electric Power Troubles (A DEPT) is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system. It is designed for two modes of operation: real time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a laser printer. This system consists of a simulated space station power module using direct-current power supplies for solar arrays on three power buses. For tests of the system's ablilty to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three buses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modeling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base.

  13. Automatic Data Logging and Quality Analysis System for Mobile Devices

    Directory of Open Access Journals (Sweden)

    Yong-Yi Fanjiang

    2017-01-01

    Full Text Available The testing phase of mobile device products includes two important test projects that must be completed before shipment: the field trial and the beta user trial. During the field trial, the product is certified based on its integration and stability with the local operator’s system, and, during the beta user trial, the product is certified by multiple users regarding its daily use, where the goal is to detect and solve early problems. In the traditional approach used to issue returns, testers must log into a web site, fill out a problem form, and then go through a browser or FTP to upload logs; however, this is inconvenient, and problems are reported slowly. Therefore, we propose an “automatic logging analysis system” (ALAS to construct a convenient test environment and, using a record analysis (log parser program, automate the parsing of log files and have questions automatically sent to the database by the system. Finally, the mean time between failures (MTBF is used to establish measurement indicators for the beta user trial.

  14. Automatic solar panel recognition and defect detection using infrared imaging

    Science.gov (United States)

    Gao, Xiang; Munson, Eric; Abousleman, Glen P.; Si, Jennie

    2015-05-01

    Failure-free operation of solar panels is of fundamental importance for modern commercial solar power plants. To achieve higher power generation efficiency and longer panel life, a simple and reliable panel evaluation method is required. By using thermal infrared imaging, anomalies can be detected without having to incorporate expensive electrical detection circuitry. In this paper, we propose a solar panel defect detection system, which automates the inspection process and mitigates the need for manual panel inspection in a large solar farm. Infrared video sequences of each array of solar panels are first collected by an infrared camera mounted to a moving cart, which is driven from array to array in a solar farm. The image processing algorithm segments the solar panels from the background in real time, with only the height of the array (specified as the number of rows of panels in the array) being given as prior information to aid in the segmentation process. In order to "count" the number the panels within any given array, frame-to frame panel association is established using optical flow. Local anomalies in a single panel such as hotspots and cracks will be immediately detected and labeled as soon as the panel is recognized in the field of view. After the data from an entire array is collected, hot panels are detected using DBSCAN clustering. On real-world test data containing over 12,000 solar panels, over 98% of all panels are recognized and correctly counted, with 92% of all types of defects being identified by the system.

  15. Electric vehicle battery model identification and state of charge estimation in real world driving cycles

    OpenAIRE

    Fotouhi, Abbas; Propp, Karsten; Auger, Daniel J.

    2015-01-01

    This paper describes a study demonstrating a new method of state-of-charge (SoC) estimation for batteries in real-world electric vehicle applications. This method combines realtime model identification with an adaptive neuro-fuzzy inference system (ANFIS). In the study, investigations were carried down on a small-scale battery pack. An equivalent circuit network model of the pack was developed and validated using pulse-discharge experiments. The pack was then subjected to demands representing...

  16. Automatic Management of Parallel and Distributed System Resources

    Science.gov (United States)

    Yan, Jerry; Ngai, Tin Fook; Lundstrom, Stephen F.

    1990-01-01

    Viewgraphs on automatic management of parallel and distributed system resources are presented. Topics covered include: parallel applications; intelligent management of multiprocessing systems; performance evaluation of parallel architecture; dynamic concurrent programs; compiler-directed system approach; lattice gaseous cellular automata; and sparse matrix Cholesky factorization.

  17. Automatic identification and characterization of radial files in light microscopy images of wood.

    Science.gov (United States)

    Brunel, Guilhem; Borianne, Philippe; Subsol, Gérard; Jaeger, Marc; Caraglio, Yves

    2014-09-01

    Analysis of anatomical sections of wood provides important information for understanding the secondary growth and development of plants. This study reports on a new method for the automatic detection and characterization of cell files in wood images obtained by light microscopy. To facilitate interpretation of the results, reliability coefficients have been determined, which characterize the files, their cells and their respective measurements. Histological sections and blocks of the gymnosperms Pinus canariensis, P. nigra and Abies alba were used, together with histological sections of the angiosperm mahogany (Swietenia spp.). Samples were scanned microscopically and mosaic images were built up. After initial processing to reduce noise and enhance contrast, cells were identified using a 'watershed' algorithm and then cell files were built up by the successive aggregation of cells taken from progressively enlarged neighbouring regions. Cell characteristics such as thickness and size were calculated, and a method was developed to determine the reliability of the measurements relative to manual methods. Image analysis using this method can be performed in less than 20 s, which compares with a time of approx. 40 min to produce the same results manually. The results are accompanied by a reliability indicator that can highlight specific configurations of cells and also potentially erroneous data. The method provides a fast, economical and reliable tool for the identification of cell files. The reliability indicator characterizing the files permits quick filtering of data for statistical analysis while also highlighting particular biological configurations present in the wood sections.

  18. A Portable Automatic Endpoint Detection System for Amplicons of Loop Mediated Isothermal Amplification on Microfluidic Compact Disk Platform

    Directory of Open Access Journals (Sweden)

    Shah Mukim Uddin

    2015-03-01

    Full Text Available In recent years, many improvements have been made in foodborne pathogen detection methods to reduce the impact of food contamination. Several rapid methods have been developed with biosensor devices to improve the way of performing pathogen detection. This paper presents an automated endpoint detection system for amplicons generated by loop mediated isothermal amplification (LAMP on a microfluidic compact disk platform. The developed detection system utilizes a monochromatic ultraviolet (UV emitter for excitation of fluorescent labeled LAMP amplicons and a color sensor to detect the emitted florescence from target. Then it processes the sensor output and displays the detection results on liquid crystal display (LCD. The sensitivity test has been performed with detection limit up to 2.5 × 10−3 ng/µL with different DNA concentrations of Salmonella bacteria. This system allows a rapid and automatic endpoint detection which could lead to the development of a point-of-care diagnosis device for foodborne pathogens detection in a resource-limited environment.

  19. Systems Engineering of Electric and Hybrid Vehicles

    Science.gov (United States)

    Kurtz, D. W.; Levin, R. R.

    1986-01-01

    Technical paper notes systems engineering principles applied to development of electric and hybrid vehicles such that system performance requirements support overall program goal of reduced petroleum consumption. Paper discusses iterative design approach dictated by systems analyses. In addition to obvious peformance parameters of range, acceleration rate, and energy consumption, systems engineering also considers such major factors as cost, safety, reliability, comfort, necessary supporting infrastructure, and availability of materials.

  20. Analytical Model-based Fault Detection and Isolation in Control Systems

    DEFF Research Database (Denmark)

    Vukic, Z.; Ozbolt, H.; Blanke, M.

    1998-01-01

    The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault diag...... diagnosis methods, often viewed as the classical or deterministic ones. Emphasis is placed on the algorithms suitable for ship automation, unmanned underwater vehicles, and other systems of automatic control....

  1. Full-automatic Special Drill Hydraulic System and PLC Control

    Directory of Open Access Journals (Sweden)

    Tian Xue Jun

    2016-01-01

    Full Text Available A hydraulic-driven and PLC full-automatic special drill is introduced, working principle of the hydraulic system and PLC control system are analyzed and designed, this equipment has the advantages of high efficiency, superior quality and low cost etc.

  2. Vehicle Remote Health Monitoring and Prognostic Maintenance System

    Directory of Open Access Journals (Sweden)

    Uferah Shafi

    2018-01-01

    Full Text Available In many industries inclusive of automotive vehicle industry, predictive maintenance has become more important. It is hard to diagnose failure in advance in the vehicle industry because of the limited availability of sensors and some of the designing exertions. However with the great development in automotive industry, it looks feasible today to analyze sensor’s data along with machine learning techniques for failure prediction. In this article, an approach is presented for fault prediction of four main subsystems of vehicle, fuel system, ignition system, exhaust system, and cooling system. Sensor is collected when vehicle is on the move, both in faulty condition (when any failure in specific system has occurred and in normal condition. The data is transmitted to the server which analyzes the data. Interesting patterns are learned using four classifiers, Decision Tree, Support Vector Machine, K Nearest Neighbor, and Random Forest. These patterns are later used to detect future failures in other vehicles which show the similar behavior. The approach is produced with the end goal of expanding vehicle up-time and was demonstrated on 70 vehicles of Toyota Corolla type. Accuracy comparison of all classifiers is performed on the basis of Receiver Operating Characteristics (ROC curves.

  3. Behavioral aspects of automatic vehicle guidance : relationship between headway and driver comfort

    Science.gov (United States)

    1997-01-01

    Automation of road traffic has the potential to greatly improve the performance of traffic systems. The acceptance of automated driving may play an important role in the feasibility of automated vehicle guidance (AVG), comparable to automated highway...

  4. Energy scavenging using piezoelectric sensors to power in pavement intelligent vehicle detection systems

    Science.gov (United States)

    Parhad, Ashutosh

    Intelligent transportation systems use in-pavement inductive loop sensors to collect real time traffic data. This method is very expensive in terms of installation and maintenance. Our research is focused on developing advanced algorithms capable of generating high amounts of energy that can charge a battery. This electromechanical energy conversion is an optimal way of energy scavenging that makes use of piezoelectric sensors. The power generated is sufficient to run the vehicle detection module that has several sensors embedded together. To achieve these goals, we have developed a simulation module using software's like LabVIEW and Multisim. The simulation module recreates a practical scenario that takes into consideration vehicle weight, speed, wheel width and frequency of the traffic.

  5. A Narrative Approach to Detect the Vehicles using color, texture and edge based techniques

    Directory of Open Access Journals (Sweden)

    Gaurav Ravi

    2016-01-01

    Full Text Available Vehicle recognition is the chief stride in observing the speeding vehicles in a thruway. The feature arrangements caught by a stationary camera demonstrate to us that there’s a requirement for a vehicle location calculation which handles sudden light change furthermore the situations where the closer view converges away from plain sight. This paper gives us a study of different foundation subtraction systems that are utilized for recognizing the vehicles effectively. Vehicles proceeding onward street are of significance on the grounds that issues like movement blockage, monetary waste, sticking on the underpasses and over-extensions (if the vehicle going through is not of the passable size are connected with them. Index Terms—Vehicle Detection, video sequences, foreground, background, MATLAB, RGB conversion.

  6. Automatic Tracking Evaluation and Development System (ATEDS)

    Data.gov (United States)

    Federal Laboratory Consortium — The heart of the ATEDS network consists of four SGI Octane computers running the IRIX operating system and equipped with V12 hardware graphics to support synthetic...

  7. Automatic detection, segmentation and assessment of snoring from ambient acoustic data.

    Science.gov (United States)

    Duckitt, W D; Tuomi, S K; Niesler, T R

    2006-10-01

    Snoring is a prevalent condition with a variety of negative social effects and associated health problems. Treatments, both surgical and therapeutic, have been developed, but the objective non-invasive monitoring of their success remains problematic. We present a method which allows the automatic monitoring of snoring characteristics, such as intensity and frequency, from audio data captured via a freestanding microphone. This represents a simple and portable diagnostic alternative to polysomnography. Our system is based on methods that have proved effective in the field of speech recognition. Hidden Markov models (HMMs) were employed as basic elements with which to model different types of sound by means of spectrally based features. This allows periods of snoring to be identified, while rejecting silence, breathing and other sounds. Training and test data were gathered from six subjects, and annotated appropriately. The system was tested by requiring it to automatically classify snoring sounds in new audio recordings and then comparing the result with manually obtained annotations. We found that our system was able to correctly identify snores with 82-89% accuracy, despite the small size of the training set. We could further demonstrate how this segmentation can be used to measure the snoring intensity, snoring frequency and snoring index. We conclude that a system based on hidden Markov models and spectrally based features is effective in the automatic detection and monitoring of snoring from audio data.

  8. Analysis and Trial of an Active Longwave Infrared Imaging System for Minefield Detection and Identification

    Science.gov (United States)

    1992-11-01

    Parameters ................... 18 V Description of Amplification and Digitalisation Parameters ...... ... 19 VI Manufacturer’s Properties of the...UNCLASSIFIED 19 Table V Description of Amplification and Digitalisation Parameters Preamplifier Manufacturer Perry Amplifier Transimpedance Gain 200K V/A

  9. Automatic heart sound segmentation and murmur detection in pediatric phonocardiograms.

    Science.gov (United States)

    Pedrosa, Joao; Castro, Ana; Vinhoza, Tiago T V

    2014-01-01

    The digital analysis of heart sounds has revealed itself as an evolving field of study. In recent years, numerous approaches to create decision support systems were attempted. This paper proposes two novel algorithms: one for the segmentation of heart sounds into heart cycles and another for detecting heart murmurs. The segmentation algorithm, based on the autocorrelation function to find the periodic components of the PCG signal had a sensitivity and positive predictive value of 89.2% and 98.6%, respectively. The murmur detection algorithm is based on features collected from different domains and was evaluated in two ways: a random division between train and test set and a division according to patients. The first returned sensitivity and specificity of 98.42% and 97.21% respectively for a minimum error of 2.19%. The second division had a far worse performance with a minimum error of 33.65%. The operating point was chosen at sensitivity 69.67% and a specificity 46.91% for a total error of 38.90% by varying the percentage of segments classified as murmurs needed for a positive murmur classification.

  10. A semi-automatic system for labelling seafood products and ...

    African Journals Online (AJOL)

    STORAGESEVER

    2010-05-10

    May 10, 2010 ... information system; EAN, European article numbering; RFID, radio frequency identification; VMS, vessel ... market channel down to the end consumer. Furthermore, this identification system allowed for ..... monitors resources with a new sensitivity and social responsibility such an approach well regarded by ...

  11. Predictability in space launch vehicle anomaly detection using intelligent neuro-fuzzy systems

    Science.gov (United States)

    Gulati, Sandeep; Toomarian, Nikzad; Barhen, Jacob; Maccalla, Ayanna; Tawel, Raoul; Thakoor, Anil; Daud, Taher

    1994-01-01

    Included in this viewgraph presentation on intelligent neuroprocessors for launch vehicle health management systems (HMS) are the following: where the flight failures have been in launch vehicles; cumulative delay time; breakdown of operations hours; failure of Mars Probe; vehicle health management (VHM) cost optimizing curve; target HMS-STS auxiliary power unit location; APU monitoring and diagnosis; and integration of neural networks and fuzzy logic.

  12. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

    Directory of Open Access Journals (Sweden)

    Min-Joo Kang

    Full Text Available A novel intrusion detection system (IDS using a deep neural network (DNN is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN, therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN bus.

  13. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

    Science.gov (United States)

    Kang, Min-Joo; Kang, Je-Won

    2016-01-01

    A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

  14. A Robust Vision-based Runway Detection and Tracking Algorithm for Automatic UAV Landing

    KAUST Repository

    Abu Jbara, Khaled F.

    2015-05-01

    This work presents a novel real-time algorithm for runway detection and tracking applied to the automatic takeoff and landing of Unmanned Aerial Vehicles (UAVs). The algorithm is based on a combination of segmentation based region competition and the minimization of a specific energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates are updated using a Kalman Filter, which can integrate other sensory information such as position and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center. Results show an accurate tracking of the runway edges during the landing phase under various lighting conditions. Also, it suggests that such positional estimates would greatly improve the positional accuracy of the UAV during takeoff and landing phases. The robustness of the proposed algorithm is further validated using Hardware in the Loop simulations with diverse takeoff and landing videos generated using a commercial flight simulator.

  15. FPGA-Based Real-Time Moving Target Detection System for Unmanned Aerial Vehicle Application

    Directory of Open Access Journals (Sweden)

    Jia Wei Tang

    2016-01-01

    Full Text Available Moving target detection is the most common task for Unmanned Aerial Vehicle (UAV to find and track object of interest from a bird’s eye view in mobile aerial surveillance for civilian applications such as search and rescue operation. The complex detection algorithm can be implemented in a real-time embedded system using Field Programmable Gate Array (FPGA. This paper presents the development of real-time moving target detection System-on-Chip (SoC using FPGA for deployment on a UAV. The detection algorithm utilizes area-based image registration technique which includes motion estimation and object segmentation processes. The moving target detection system has been prototyped on a low-cost Terasic DE2-115 board mounted with TRDB-D5M camera. The system consists of Nios II processor and stream-oriented dedicated hardware accelerators running at 100 MHz clock rate, achieving 30-frame per second processing speed for 640 × 480 pixels’ resolution greyscale videos.

  16. Vehicle Theft Identification and Intimation Using GSM & IOT

    Science.gov (United States)

    Eswar Kumar, M.; Thippa Reddy, G.; Sudheer, K.; Reddy, M. Praveen Kumar; Kaluri, Rajesh; Singh Rajput, Dharmendra; Lakshmanna, Kuruva

    2017-11-01

    Internet of Things is the most predominant innovation associates the things through web. IoT is a technology which interfaces things from different places on the planet. Home mechanization is a wide range innovation in IoT technology on the planet. Home automation constitutes in security issues, controlling gadgets and so on. In existing model, the vehicle theft is distinguished and controlled by physically with GSM module. Furthermore, there are a few in controlling the vehicle is major issue for owner from theft. Here in this paper a technique described to overcome issue of existing one. In this the vehicle is identified, controlled and connected updates with Internet in a simple way. By utilization of AT commands of GSM module a message will be send to the owner that the vehicle is recognized. Action can be taken by sending a reply to GSM module to stop motor of vehicle. Arduino uno board is used to interface the GSM and engine of vehicle with appropriate sensors. Visual studio, Arduino uno are the programming software used to outline this application.

  17. Automatic progressive damage detection of rotor bar in induction motor using vibration analysis and multiple classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Cruz-Vega, Israel; Rangel-Magdaleno, Jose; Ramirez-Cortes, Juan; Peregrina-Barreto, Hayde [Santa María Tonantzintla, Puebla (Mexico)

    2017-06-15

    There is an increased interest in developing reliable condition monitoring and fault diagnosis systems of machines like induction motors; such interest is not only in the final phase of the failure but also at early stages. In this paper, several levels of damage of rotor bars under different load conditions are identified by means of vibration signals. The importance of this work relies on a simple but effective automatic detection algorithm of the damage before a break occurs. The feature extraction is based on discrete wavelet analysis and auto- correlation process. Then, the automatic classification of the fault degree is carried out by a binary classification tree. In each node, com- paring the learned levels of the breaking off correctly identifies the fault degree. The best results of classification are obtained employing computational intelligence techniques like support vector machines, multilayer perceptron, and the k-NN algorithm, with a proper selection of their optimal parameters.

  18. Automatic progressive damage detection of rotor bar in induction motor using vibration analysis and multiple classifiers

    International Nuclear Information System (INIS)

    Cruz-Vega, Israel; Rangel-Magdaleno, Jose; Ramirez-Cortes, Juan; Peregrina-Barreto, Hayde

    2017-01-01

    There is an increased interest in developing reliable condition monitoring and fault diagnosis systems of machines like induction motors; such interest is not only in the final phase of the failure but also at early stages. In this paper, several levels of damage of rotor bars under different load conditions are identified by means of vibration signals. The importance of this work relies on a simple but effective automatic detection algorithm of the damage before a break occurs. The feature extraction is based on discrete wavelet analysis and auto- correlation process. Then, the automatic classification of the fault degree is carried out by a binary classification tree. In each node, com- paring the learned levels of the breaking off correctly identifies the fault degree. The best results of classification are obtained employing computational intelligence techniques like support vector machines, multilayer perceptron, and the k-NN algorithm, with a proper selection of their optimal parameters.

  19. Study on Safety of Navigation using Automatic Identification System for Marine Traffic Area Case Study: Malacca Straits

    Directory of Open Access Journals (Sweden)

    Muhammad Badrus Zaman

    2016-12-01

    Full Text Available International Maritime Organization (IMO has recommended the implementation of Automatic Identification System (AIS to improve the safety of navigation at marine traffic area. Based on regulation, IMO requires AIS to be fitted aboard all ships of 300 gross tonnage and upwards engaged on international voyages, cargo ships of 500 gross tonnage and upwards not engaged on international voyages and all passenger ships irrespective of size. The function of the AIS is to make communication between ship to ship and communication between ship to the port or land area. In this study, the study area is the Malacca Strait. Malacca Straits is the strait categorized as high risk level. Malacca straits is also busy area for maritime transportation because it is an area for international transportation lines. Many captains feel anxious and cautiously when passes through the strait. AIS receiver was used in this study which has been installed at Universiti Teknologi Malaysia by Kobe University Japan. Using AIS receiver, the current condition of the ship in the Malacca Straits area can be monitored properly. In addition, the data recorded on the AIS receiver can be used for research to enhance safety of navigation.

  20. Investigation of Using Radio Frequency Identification (RFID) System for Gear Tooth Crack Detection

    Science.gov (United States)

    2014-06-01

    on a conveyor belt at a certain speed. When compared to the static application, moving tags spend less time in the read field and require a higher...UNCLASSIFIED UNCLASSIFIED Investigation of using Radio Frequency Identification (RFID) System for Gear Tooth Crack Detection Eric...using passive low frequency (LF) and high frequency (HF) radio frequency identification (RFID) systems as embedded sensors for early gear tooth

  1. Algorithms for the automatic identification of MARFEs and UFOs in JET database of visible camera videos

    International Nuclear Information System (INIS)

    Murari, A.; Camplani, M.; Cannas, B.; Usai, P.; Mazon, D.; Delaunay, F.

    2010-01-01

    MARFE instabilities and UFOs leave clear signatures in JET fast visible camera videos. Given the potential harmful consequences of these events, particularly as triggers of disruptions, it would be important to have the means of detecting them automatically. In this paper, the results of various algorithms to identify automatically the MARFEs and UFOs in JET visible videos are reported. The objective is to retrieve the videos, which have captured these events, exploring the whole JET database of images, as a preliminary step to the development of real-time identifiers in the future. For the detection of MARFEs, a complete identifier has been finalized, using morphological operators and Hu moments. The final algorithm manages to identify the videos with MARFEs with a success rate exceeding 80%. Due to the lack of a complete statistics of examples, the UFO identifier is less developed, but a preliminary code can detect UFOs quite reliably. (authors)

  2. Night-Time Vehicle Detection Algorithm Based on Visual Saliency and Deep Learning

    Directory of Open Access Journals (Sweden)

    Yingfeng Cai

    2016-01-01

    Full Text Available Night vision systems get more and more attention in the field of automotive active safety field. In this area, a number of researchers have proposed far-infrared sensor based night-time vehicle detection algorithm. However, existing algorithms have low performance in some indicators such as the detection rate and processing time. To solve this problem, we propose a far-infrared image vehicle detection algorithm based on visual saliency and deep learning. Firstly, most of the nonvehicle pixels will be removed with visual saliency computation. Then, vehicle candidate will be generated by using prior information such as camera parameters and vehicle size. Finally, classifier trained with deep belief networks will be applied to verify the candidates generated in last step. The proposed algorithm is tested in around 6000 images and achieves detection rate of 92.3% and processing time of 25 Hz which is better than existing methods.

  3. Diagnosis - Using automatic test equipment and artificial intelligence expert systems

    Science.gov (United States)

    Ramsey, J. E., Jr.

    Three expert systems (ATEOPS, ATEFEXPERS, and ATEFATLAS), which were created to direct automatic test equipment (ATE), are reviewed. The purpose of the project was to develop an expert system to troubleshoot the converter-programmer power supply card for the F-15 aircraft and have that expert system direct the automatic test equipment. Each expert system uses a different knowledge base or inference engine, basing the testing on the circuit schematic, test requirements document, or ATLAS code. Implementing generalized modules allows the expert systems to be used for any different unit under test. Using converted ATLAS to LISP code allows the expert system to direct any ATE using ATLAS. The constraint propagated frame system allows for the expansion of control by creating the ATLAS code, checking the code for good software engineering techniques, directing the ATE, and changing the test sequence as needed (planning).

  4. Microcontroller-based Vehicle Security System with Tracking Capability using GSM and GPS Technologies

    Directory of Open Access Journals (Sweden)

    Engr. Orven F. Mendoza

    2017-05-01

    Full Text Available The security of vehicles is ext remely essential for vehicle owners especially to those whose hard - earned income was used to avail of one or simply, its loss would mean inconveniences to family and work. With these, it becomes the major problem of every vehicle owner. This thesis, Microc ontroller - based Vehicle Security System with Tracking Capability using GSM and GPS Technologies, is a system that can be used to increase vehicle security, as it can track location of missing vehicle, and help authorities have credible evidence that the ve hicle is stolen. The project uses the Global System for Mobile (GSM and the Global Positioning System (GPS technology, which includes the use of GPS receiver module, GSM module, and microcontroller as its primary components. It also uses a vibration sens or that senses vehicle movement and a buzzer that sends an alarm when sensors are triggered. A confirmation message is sent to the vehicle owner of the vehicle by the device. The system also features capability of tracking the location of the vehicle with the help of the GPS receiver which gives data to the location of the vehicle by way of coordinates. These coordinates provide exact location of the motor vehicle. The SMS message that the vehicle owner will send to the device attached to the vehicle should follow correct format of limitation for successful use and the use of the four character password followed by the command. The command is for power switching or activating automatically the key switch, engine and alarm. If not observed, the device would not work. The project is deemed to provide vehicle owners the security of their vehicle. The system will not only ensure vehicle security but also lessen the threats on vehicles.

  5. A semi-automatic system for labelling seafood products and ...

    African Journals Online (AJOL)

    A semi-automatic system for labelling seafood products and obtaining fishery management data: A case study of the bottom trawl fishery in the central ... policies, such as date and catch area, can be acquired and recorded on the label by user-friendly automated software that excludes any possible manipulation by the crew.

  6. Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images

    Directory of Open Access Journals (Sweden)

    Kajsa Møllersen

    2015-01-01

    Full Text Available Commercially available clinical decision support systems (CDSSs for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer types, that is, nonmelanoma skin cancer (NMSC. As early diagnosis of skin cancer is essential, there is a need for a CDSS that is applicable to all types of skin lesions and is suitable for nonexperts. Nevus Doctor (ND is a CDSS being developed by the authors. We here investigate ND’s ability to detect both melanoma and NMSC and the opportunities for improvement. An independent test set of dermoscopic images of 870 skin lesions, including 44 melanomas and 101 NMSCs, were analysed by ND. Its sensitivity to melanoma and NMSC was compared to that of Mole Expert (ME, a commercially available CDSS, using the same set of lesions. ND and ME had similar sensitivity to melanoma. For ND at 95% melanoma sensitivity, the NMSC sensitivity was 100%, and the specificity was 12%. The melanomas misclassified by ND at 95% sensitivity were correctly classified by ME, and vice versa. ND is able to detect NMSC without sacrificing melanoma sensitivity.

  7. Behavioral and electrophysiological evidence for early and automatic detection of phonological equivalence in variable speech inputs.

    Science.gov (United States)

    Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

    2011-11-01

    Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.

  8. Automatic reactor protection system tester

    International Nuclear Information System (INIS)

    Deliant, J.D.; Jahnke, S.; Raimondo, E.

    1988-01-01

    The object of this paper is to present the automatic tester of reactor protection systems designed and developed by EDF and Framatome. In order, the following points are discussed: . The necessity for reactor protection system testing, . The drawbacks of manual testing, . The description and use of the Framatome automatic tester, . On-site installation of this system, . The positive results obtained using the Framatome automatic tester in France

  9. A semi-automatic system for labelling seafood products and ...

    African Journals Online (AJOL)

    STORAGESEVER

    2010-05-10

    May 10, 2010 ... This study is on the implementation of a semi-automatic labelling system (LS) of the Mediterranean Sea seafood harvest to address the increased need for seafood authentication and inherent difficulties of commonly used indirect techniques for estimating fisheries yield and fishing effort. Sensitive data.

  10. Automatic diagnosis and control of distributed solid state lighting systems

    NARCIS (Netherlands)

    Dong, J.; Van Driel, W.; Zhnag, G.

    2011-01-01

    This paper describes a new design concept of automatically diagnosing and compensating LED degradations in distributed solid state lighting (SSL) systems. A failed LED may significantly reduce the overall illumination level, and destroy the uniform illumination distribution achieved by a nominal

  11. AUTOMATIC DETECTION AND CLASSIFICATION OF RETINAL VASCULAR LANDMARKS

    Directory of Open Access Journals (Sweden)

    Hadi Hamad

    2014-06-01

    Full Text Available The main contribution of this paper is introducing a method to distinguish between different landmarks of the retina: bifurcations and crossings. The methodology may help in differentiating between arteries and veins and is useful in identifying diseases and other special pathologies, too. The method does not need any special skills, thus it can be assimilated to an automatic way for pinpointing landmarks; moreover it gives good responses for very small vessels. A skeletonized representation, taken out from the segmented binary image (obtained through a preprocessing step, is used to identify pixels with three or more neighbors. Then, the junction points are classified into bifurcations or crossovers depending on their geometrical and topological properties such as width, direction and connectivity of the surrounding segments. The proposed approach is applied to the public-domain DRIVE and STARE datasets and compared with the state-of-the-art methods using proper validation parameters. The method was successful in identifying the majority of the landmarks; the average correctly identified bifurcations in both DRIVE and STARE datasets for the recall and precision values are: 95.4% and 87.1% respectively; also for the crossovers, the recall and precision values are: 87.6% and 90.5% respectively; thus outperforming other studies.

  12. Genetic algorithms approach to the problem of the automated vehicle identification equipment location

    Energy Technology Data Exchange (ETDEWEB)

    Teodorovic, D.; Van Aerde, M.; Zhu, F.; Dion, F. [Virginia Polytechnic Instutute and State University, Dept. of Civil and Environmental Engineering, Blacksburg, VA (United States)

    2002-12-31

    Automated Vehicle Identification technology allows vehicles equipped with special tags to be detected at specific points in the transportation network without any action by the driver as they pass under a reading station. Benefits of the systems are found in the real-time measurement of traffic patterns, traffic operations and control, reduction of traffic congestion at transportation facilities, transportation planning studies, information and control, electronic toll collection, vehicle identification and other related functions. The objective of this paper is to develop a heuristic model for the optimal location of automated vehicle identification equipment using generic algorithms. A model is proposed and it is tested for the case of a relatively small hypothetical transportation network. Testing the model showed promising results. As the subject of future research other metaheuristic approaches such as simulated annealing and taboo searching have been identified as most important directions. 4 refs., 1 tab., 11 figs.

  13. Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

    Directory of Open Access Journals (Sweden)

    Kemal Akyol

    2016-01-01

    Full Text Available With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC.

  14. Fault detection and identification methodology under an incremental learning framework applied to industrial electromechanical systems

    OpenAIRE

    Cariño Corrales, Jesús Adolfo

    2017-01-01

    Condition Based Maintenance is a program that recommends actions based on the information collected and interpreted through condition monitoring and has become accepted since a decade ago by the industry as a key factor to avoiding expensive unplanned machine stoppages and reaching high production ratios. Among the condition based maintenance strategies, data-driven fault diagnosis methodologies have gained increased attention because of the high performance and widen range of applicability d...

  15. Final Environmental Assessment for Rapid Attack Identification, Detection, and Reporting System - Block 10

    Science.gov (United States)

    2007-05-03

    and best available sea turtle lighting technology . The Environmental Office would then consult with the USFWS for plan approval. As a result, the...AFB Environmental Office in development of a Light Management Plan that incorporates the latest and best available sea turtle lighting technology . The...Office in development of a Light Management Plan that incorporates the latest and best available sea turtle lighting technology . The Environmental

  16. An automatized frequency analysis for vine plot detection and delineation in remote sensing

    OpenAIRE

    Delenne , Carole; Rabatel , G.; Deshayes , M.

    2008-01-01

    The availability of an automatic tool for vine plot detection, delineation, and characterization would be very useful for management purposes. An automatic and recursive process using frequency analysis (with Fourier transform and Gabor filters) has been developed to meet this need. This results in the determination of vine plot boundary and accurate estimation of interrow width and row orientation. To foster large-scale applications, tests and validation have been carried out on standard ver...

  17. Detection and Identification of Bacteria Using Automated Biological Sample Processing With a Relational Database Management System

    Science.gov (United States)

    2005-10-01

    other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently ...pretreatment module is necessary to separate the interferential species that are not compatible with LC such as cellular debris, large particulates and

  18. Obtaining accurate utilization and fuel use data for vehicle maintenance reporting systems. SAE Paper 780276

    Energy Technology Data Exchange (ETDEWEB)

    Nation, R.T.

    1978-01-01

    A new fuel control system has been developed which records vehicle utilization and fuel and oil use automatically at the fueling installation. The system provides security against unauthorized fuel use, is free from any manual input, and is very practical and economical to install and operate.

  19. Multibody simulation of vehicles equipped with an automatic transmission

    Science.gov (United States)

    Olivier, B.; Kouroussis, G.

    2016-09-01

    Nowadays automotive vehicles remain as one of the most used modes of transportation. Furthermore automatic transmissions are increasingly used to provide a better driving comfort and a potential optimization of the engine performances (by placing the gear shifts at specific engine and vehicle speeds). This paper presents an effective modeling of the vehicle using the multibody methodology (numerically computed under EasyDyn, an open source and in-house library dedicated to multibody simulations). However, the transmission part of the vehicle is described by the usual equations of motion computed using a systematic matrix approach: del Castillo's methodology for planetary gear trains. By coupling the analytic equations of the transmission and the equations computed by the multibody methodology, the performances of any vehicle can be obtained if the characteristics of each element in the vehicle are known. The multibody methodology offers the possibilities to develop the vehicle modeling from 1D-motion to 3D-motion by taking into account the rotations and implementing tire models. The modeling presented in this paper remains very efficient and provides an easy and quick vehicle simulation tool which could be used in order to calibrate the automatic transmission.

  20. AUTOMATIC SHADOW DETECTION IN AERIAL AND TERRESTRIAL IMAGES

    Directory of Open Access Journals (Sweden)

    Vander Luis de Souza Freitas

    Full Text Available Abstract: Shadows exist in almost all aerial and outdoor images, and they can be useful for estimating Sun position estimation or measuring object size. On the other hand, they represent a problem in processes such as object detection/recognition, image matching, etc., because they may be confused with dark objects and change the image radiometric properties. We address this problem on aerial and outdoor color images in this work. We use a filter to find low intensities as a first step. For outdoor color images, we analyze spectrum ratio properties to refine the detection, and the results are assessed with a dataset containing ground truth. For the aerial case we validate the detections depending of the hue component of pixels. This stage takes into account that, in deep shadows, most pixels have blue or violet wavelengths because of an atmospheric scattering effect.

  1. System and method for charging a plug-in electric vehicle

    Energy Technology Data Exchange (ETDEWEB)

    Bassham, Marjorie A.; Spigno, Jr., Ciro A.; Muller, Brett T.; Newhouse, Vernon L.

    2017-05-02

    A charging system and method that may be used to automatically apply customized charging settings to a plug-in electric vehicle, where application of the settings is based on the vehicle's location. According to an exemplary embodiment, a user may establish and save a separate charging profile with certain customized charging settings for each geographic location where they plan to charge their plug-in electric vehicle. Whenever the plug-in electric vehicle enters a new geographic area, the charging method may automatically apply the charging profile that corresponds to that area. Thus, the user does not have to manually change or manipulate the charging settings every time they charge the plug-in electric vehicle in a new location.

  2. System and method for charging a plug-in electric vehicle

    Science.gov (United States)

    Bassham, Marjorie A.; Spigno, Jr., Ciro A.; Muller, Brett T.; Newhouse, Vernon L.

    2017-05-02

    A charging system and method that may be used to automatically apply customized charging settings to a plug-in electric vehicle, where application of the settings is based on the vehicle's location. According to an exemplary embodiment, a user may establish and save a separate charging profile with certain customized charging settings for each geographic location where they plan to charge their plug-in electric vehicle. Whenever the plug-in electric vehicle enters a new geographic area, the charging method may automatically apply the charging profile that corresponds to that area. Thus, the user does not have to manually change or manipulate the charging settings every time they charge the plug-in electric vehicle in a new location.

  3. Elevation scanning laser/multi-sensor hazard detection system controller and mirror/mast speed control components. [roving vehicle electromechanical devices

    Science.gov (United States)

    Craig, J.; Yerazunis, S. W.

    1978-01-01

    The electro-mechanical and electronic systems involved with pointing a laser beam from a roving vehicle along a desired vector are described. A rotating 8 sided mirror, driven by a phase-locked dc motor servo system, and monitored by a precision optical shaft encoder is used. This upper assembly is then rotated about an orthogonal axis to allow scanning into all 360 deg around the vehicle. This axis is also driven by a phase locked dc motor servo-system, and monitored with an optical shaft encoder. The electronics are realized in standard TTL integrated circuits with UV-erasable proms used to store desired coordinates of laser fire. Related topics such as the interface to the existing test vehicle are discussed.

  4. Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

    Science.gov (United States)

    Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

    2018-04-30

    Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Capacitive system detects and locates fluid leaks

    Science.gov (United States)

    1966-01-01

    Electronic monitoring system automatically detects and locates minute leaks in seams of large fluid storage tanks and pipelines covered with thermal insulation. The system uses a capacitive tape-sensing element that is adhesively bonded over seams where fluid leaks are likely to occur.

  6. Automatic identification of watercourses in flat and engineered landscapes by computing the skeleton of a LiDAR point cloud

    Science.gov (United States)

    Broersen, Tom; Peters, Ravi; Ledoux, Hugo

    2017-09-01

    Drainage networks play a crucial role in protecting land against floods. It is therefore important to have an accurate map of the watercourses that form the drainage network. Previous work on the automatic identification of watercourses was typically based on grids, focused on natural landscapes, and used mostly the slope and curvature of the terrain. We focus in this paper on areas that are characterised by low-lying, flat, and engineered landscapes; these are characteristic to the Netherlands for instance. We propose a new methodology to identify watercourses automatically from elevation data, it uses solely a raw classified LiDAR point cloud as input. We show that by computing twice a skeleton of the point cloud-once in 2D and once in 3D-and that by using the properties of the skeletons we can identify most of the watercourses. We have implemented our methodology and tested it for three different soil types around Utrecht, the Netherlands. We were able to detect 98% of the watercourses for one soil type, and around 75% for the worst case, when we compared to a reference dataset that was obtained semi-automatically.

  7. Automatic computer aided analysis algorithms and system for adrenal tumors on CT images.

    Science.gov (United States)

    Chai, Hanchao; Guo, Yi; Wang, Yuanyuan; Zhou, Guohui

    2017-12-04

    The adrenal tumor will disturb the secreting function of adrenocortical cells, leading to many diseases. Different kinds of adrenal tumors require different therapeutic schedules. In the practical diagnosis, it highly relies on the doctor's experience to judge the tumor type by reading the hundreds of CT images. This paper proposed an automatic computer aided analysis method for adrenal tumors detection and classification. It consisted of the automatic segmentation algorithms, the feature extraction and the classification algorithms. These algorithms were then integrated into a system and conducted on the graphic interface by using MATLAB Graphic user interface (GUI). The accuracy of the automatic computer aided segmentation and classification reached 90% on 436 CT images. The experiments proved the stability and reliability of this automatic computer aided analytic system.

  8. Integrated vehicle-based safety systems light-vehicle field operational test, methodology and results report.

    Science.gov (United States)

    2010-12-01

    "This document presents the methodology and results from the light-vehicle field operational test conducted as part of the Integrated Vehicle-Based Safety Systems program. These findings are the result of analyses performed by the University of Michi...

  9. 41 CFR 102-34.85 - What motor vehicles require motor vehicle identification?

    Science.gov (United States)

    2010-07-01

    ... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What motor vehicles require motor vehicle identification? 102-34.85 Section 102-34.85 Public Contracts and Property Management... 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Motor Vehicle Identification...

  10. Detection and identification of platelet antibodies using a sensitive multiplex assay system-platelet antibody bead array.

    Science.gov (United States)

    Metzner, Krista; Bauer, Julie; Ponzi, Heather; Ujcich, Allison; Curtis, Brian R

    2017-07-01

    Tests for platelet-specific antibodies are important in the diagnosis of immune platelet disorders. Monoclonal antibody glycoprotein capture assays have been the gold standards in platelet antibody detection for almost 30 years. However, such assays are complex and cumbersome to perform, which limits their routine use. We report the performance of a newly developed, easy to perform platelet antibody bead array (PABA) for the detection of platelet-specific antibodies. PABA is the equivalent of the monoclonal antigen capture enzyme-linked immunosorbent assay (ELISA) (MACE) on a bead and instead with fluorescent detection of immunoglobulin (Ig)G platelet antibodies by Luminex. Antibodies against platelet glycoproteins (GP) GPIIb/IIIa, GPIb/IX, GPIa/IIa, GPIV, and class I human leukocyte antigen (HLA) could be detected in a patient's serum simultaneously in a single well of a microplate. Results from 80 patient samples and 20 normal donor samples were compared using PABA, MACE, and a commercial ELISA kit. PABA detected all antibodies, with specificity for human platelet antigens (HPAs) HPA-1a, HPA-1b, HPA-2a, HPA-2b, HPA-3a, HPA-3b, HPA-4a, HPA-4b, HPA-5a, HPA-5b, HPA-15b, and HLA. Overall, compared with MACE, the sensitivity and specificity of PABA were 99% and 97%, respectively, and both were significantly better than those of the commercial ELISA. PABA had greater analytic sensitivity than MACE for HPA-1a, HPA-3a, and HPA-5b antibodies. In addition, PABA detected HPA-5b and HPA-3b antibodies that were missed by MACE. The overall false-positive rate of PABA compared with MACE was 2.7%. The PABA is a rapid, highly sensitive and specific, multiplex bead-based assay for detecting human platelet antibodies. Such a simple yet high-throughput platform will facilitate practical, routine testing for the identification of platelet-specific antibodies. © 2017 AABB.

  11. Automatic stereoscopic system for person recognition

    Science.gov (United States)

    Murynin, Alexander B.; Matveev, Ivan A.; Kuznetsov, Victor D.

    1999-06-01

    A biometric access control system based on identification of human face is presented. The system developed performs remote measurements of the necessary face features. Two different scenarios of the system behavior are implemented. The first one assumes the verification of personal data entered by visitor from console using keyboard or card reader. The system functions as an automatic checkpoint, that strictly controls access of different visitors. The other scenario makes it possible to identify visitors without any person identifier or pass. Only person biometrics are used to identify the visitor. The recognition system automatically finds necessary identification information preliminary stored in the database. Two laboratory models of recognition system were developed. The models are designed to use different information types and sources. In addition to stereoscopic images inputted to computer from cameras the models can use voice data and some person physical characteristics such as person's height, measured by imaging system.

  12. Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones.

    Science.gov (United States)

    Lu, Dang-Nhac; Nguyen, Duc-Nhan; Nguyen, Thi-Hau; Nguyen, Ha-Nam

    2018-03-29

    In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers' vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features) as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine) contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97.33% that is

  13. Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones

    Directory of Open Access Journals (Sweden)

    Dang-Nhac Lu

    2018-03-01

    Full Text Available In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS, that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers’ vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97

  14. Automatic detection of NIL defects using microscopy and image processing

    KAUST Repository

    Pietroy, David

    2013-12-01

    Nanoimprint Lithography (NIL) is a promising technology for low cost and large scale nanostructure fabrication. This technique is based on a contact molding-demolding process, that can produce number of defects such as incomplete filling, negative patterns, sticking. In this paper, microscopic imaging combined to a specific processing algorithm is used to detect numerically defects in printed patterns. Results obtained for 1D and 2D imprinted gratings with different microscopic image magnifications are presented. Results are independent on the device which captures the image (optical, confocal or electron microscope). The use of numerical images allows the possibility to automate the detection and to compute a statistical analysis of defects. This method provides a fast analysis of printed gratings and could be used to monitor the production of such structures. © 2013 Elsevier B.V. All rights reserved.

  15. Automatic optical detection and classification of marine animals around MHK converters using machine vision

    Energy Technology Data Exchange (ETDEWEB)

    Brunton, Steven [Univ. of Washington, Seattle, WA (United States)

    2018-01-15

    Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robust principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.

  16. The new generation of detection and identification equipment

    International Nuclear Information System (INIS)

    Schultz, F.; Guerin, M.; Fort, Ph.

    2009-01-01

    The authors address the highly sensitive detection issue with real time identification of the risk nature, a problem which occurs every time a source is only fleetingly present (a pedestrian, a vehicle or an object on a conveyor belt passing by). They briefly present a range of instruments specially designed for this purpose, the SPIR-Ident instruments. These equipment use one or several large sensors, digital multichannel analyzers (one per sensor) and neutron and gamma measurements. Spectra are continuously processed, stabilized, linearized and normalized, and finally analyzed by an algorithm. The authors evoke the performance characterization and a return on experience after a 6 month-use for the control of passengers and luggage in airport

  17. Using Polarization features of visible light for automatic landmine detection

    NARCIS (Netherlands)

    Jong, W. de; Schavemaker, J.G.M.

    2007-01-01

    This chapter describes the usage of polarization features of visible light for automatic landmine detection. The first section gives an introduction to land-mine detection and the usage of camera systems. In section 2 detection concepts and methods that use polarization features are described.

  18. Design and research on the electronic parking brake system of the medium and heavy duty vehicles

    Directory of Open Access Journals (Sweden)

    Hongliang WANG

    2015-04-01

    Full Text Available Focusing on auto control of parking brake system of the medium and heavy duty vehicles, the key problems are studied including the system design and control strategies. The structure and working principle of the parking brake system of the medium and heavy duty vehicles are analyzed. The functions of EPB are proposed. The important information of the vehicle are analyzed which could influence the EPB system. The overall plan of the pneumatic EPB system is designed, which adopts the two-position three-way electromagnetic valve with double coil as actuator. The system could keep the vehicle parking brake status or parking release status for a long time without power supply. The function modules of the system are planned, and the control strategies of automatic parking brake and parking release are made. The experiment is performed on a medium-sized commercial vehicle which is experimentally modified. The overall plan of the pneumatic EPB system and the automatic parking function are proved through real vehicle tests.

  19. A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    N. Zarrinpanjeh

    2017-09-01

    Full Text Available Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  20. a Fuzzy Automatic CAR Detection Method Based on High Resolution Satellite Imagery and Geodesic Morphology

    Science.gov (United States)

    Zarrinpanjeh, N.; Dadrassjavan, F.

    2017-09-01

    Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  1. Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance

    Directory of Open Access Journals (Sweden)

    Benabbas Yassine

    2011-01-01

    Full Text Available Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearance ambiguity, and occlusion. In this work, we propose to deal with this problem by modeling the global motion information obtained from optical flow vectors. The obtained direction and magnitude models learn the dominant motion orientations and magnitudes at each spatial location of the scene and are used to detect the major motion patterns. The applied region-based segmentation algorithm groups local blocks that share the same motion direction and speed and allows a subregion of the scene to appear in different patterns. The second part of the approach consists in the detection of events related to groups of people which are merge, split, walk, run, local dispersion, and evacuation by analyzing the instantaneous optical flow vectors and comparing the learned models. The approach is validated and experimented on standard datasets of the computer vision community. The qualitative and quantitative results are discussed.

  2. Digital Signal Processing for In-Vehicle Systems and Safety

    CERN Document Server

    Boyraz, Pinar; Takeda, Kazuya; Abut, Hüseyin

    2012-01-01

    Compiled from papers of the 4th Biennial Workshop on DSP (Digital Signal Processing) for In-Vehicle Systems and Safety this edited collection features world-class experts from diverse fields focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. Digital Signal Processing for In-Vehicle Systems and Safety presents new approaches on how to reduce driver inattention and prevent road accidents. The material addresses DSP technologies in adaptive automobiles, in-vehicle dialogue systems, human machine interfaces, video and audio processing, and in-vehicle speech systems. The volume also features: Recent advances in Smart-Car technology – vehicles that take into account and conform to the driver Driver-vehicle interfaces that take into account the driving task and cognitive load of the driver Best practices for In-Vehicle Corpus Development and distribution Information on multi-sensor analysis and fusion techniques for robust driver monitoring and driver recognition ...

  3. Systems and methods for vehicle speed management

    Science.gov (United States)

    Sujan, Vivek Anand; Vajapeyazula, Phani; Follen, Kenneth; Wu, An; Forst, Howard Robert

    2016-03-01

    Controlling a speed of a vehicle based on at least a portion of a route grade and a route distance divided into a plurality of route sections, each including at least one of a section grade and section length. Controlling the speed of the vehicle is further based on determining a cruise control speed mode for the vehicle for each of the plurality of route sections and determining a speed reference command of the vehicle based on at least one of the cruise control speed mode, the section length, the section grade, and a current speed.

  4. Camera positioning and calibration techniques for integrating traffic surveillance video systems with machine-vision vehicle detection devices.

    Science.gov (United States)

    2002-12-01

    The Virginia Department of Transportation, like many other transportation agencies, has invested significantly in extensive closed circuit television (CCTV) systems to monitor freeways in urban areas. Although these systems have proven very effective...

  5. Vehicle Detection and Classification Using Passive Infrared Sensing

    KAUST Repository

    Odat, Enas M.

    2015-10-19

    We propose a new sensing device that can simultaneously monitor urban traffic congestion and another phenomenon of interest (flash floods on the present case). This sensing device is based on the combination of an ultrasonic rangefinder with one or multiple remote temperature sensors. We show an implementation of this device, and illustrate its performance in both traffic flow sensing. Field data shows that the sensor can detect vehicles with a 99% accuracy, in addition to estimating their speed and classifying them in function of their length. The same sensor can also monitor urban water levels with an accuracy of less than 2 cm.

  6. Exploiting ensemble learning for automatic cataract detection and grading.

    Science.gov (United States)

    Yang, Ji-Jiang; Li, Jianqiang; Shen, Ruifang; Zeng, Yang; He, Jian; Bi, Jing; Li, Yong; Zhang, Qinyan; Peng, Lihui; Wang, Qing

    2016-02-01

    Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs. To date, studies reported in the literature utilize a single learning model for retinal image classification in grading cataract severity. We present an ensemble learning based approach as a means to improving diagnostic accuracy. Three independent feature sets, i.e., wavelet-, sketch-, and texture-based features, are extracted from each fundus image. For each feature set, two base learning models, i.e., Support Vector Machine and Back Propagation Neural Network, are built. Then, the ensemble methods, majority voting and stacking, are investigated to combine the multiple base learning models for final fundus image classification. Empirical experiments are conducted for cataract detection (two-class task, i.e., cataract or non-cataractous) and cataract grading (four-class task, i.e., non-cataractous, mild, moderate or severe) tasks. The best performance of the ensemble classifier is 93.2% and 84.5% in terms of the correct classification rates for cataract detection and grading tasks, respectively. The results demonstrate that the ensemble classifier outperforms the single learning model significantly, which also illustrates the effectiveness of the proposed approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. Simultaneous multi-vehicle detection and tracking framework with pavement constraints based on machine learning and particle filter algorithm

    Science.gov (United States)

    Wang, Ke; Huang, Zhi; Zhong, Zhihua

    2014-11-01

    Due to the large variations of environment with ever-changing background and vehicles with different shapes, colors and appearances, to implement a real-time on-board vehicle recognition system with high adaptability, efficiency and robustness in complicated environments, remains challenging. This paper introduces a simultaneous detection and tracking framework for robust on-board vehicle recognition based on monocular vision technology. The framework utilizes a novel layered machine learning and particle filter to build a multi-vehicle detection and tracking system. In the vehicle detection stage, a layered machine learning method is presented, which combines coarse-search and fine-search to obtain the target using the AdaBoost-based training algorithm. The pavement segmentation method based on characteristic similarity is proposed to estimate the most likely pavement area. Efficiency and accuracy are enhanced by restricting vehicle detection within the downsized area of pavement. In vehicle tracking stage, a multi-objective tracking algorithm based on target state management and particle filter is proposed. The proposed system is evaluated by roadway video captured in a variety of traffics, illumination, and weather conditions. The evaluating results show that, under conditions of proper illumination and clear vehicle appearance, the proposed system achieves 91.2% detection rate and 2.6% false detection rate. Experiments compared to typical algorithms show that, the presented algorithm reduces the false detection rate nearly by half at the cost of decreasing 2.7%-8.6% detection rate. This paper proposes a multi-vehicle detection and tracking system, which is promising for implementation in an on-board vehicle recognition system with high precision, strong robustness and low computational cost.

  8. Adaptive neuro-fuzzy inference systems for automatic detection of breast cancer.

    Science.gov (United States)

    Ubeyli, Elif Derya

    2009-10-01

    This paper intends to an integrated view of implementing adaptive neuro-fuzzy inference system (ANFIS) for breast cancer detection. The Wisconsin breast cancer database contained records of patients with known diagnosis. The ANFIS classifiers learned how to differentiate a new case in the domain by given a training set of such records. The ANFIS classifier was used to detect the breast cancer when nine features defining breast cancer indications were used as inputs. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the impacts of features on the detection of breast cancer were obtained through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performances and classification accuracies and the results confirmed that the proposed ANFIS model has potential in detecting the breast cancer.

  9. Design And Analysis Of Doppler Radar-Based Vehicle Speed Detection

    Directory of Open Access Journals (Sweden)

    Su Myat Paing

    2015-08-01

    Full Text Available The most unwanted thing to happen to a road user is road accident. Most of the fatal accidents occur due to over speeding. Faster vehicles are more prone to accident than the slower one. Among the various methods for detecting speed of the vehicle object detection systems based on Radar have been replaced for about a century for various purposes like detection of aircrafts spacecraft ships navigation reading weather formations and terrain mapping. The essential feature in adaptive vehicle activated sign systems is the accurate measurement of a vehicles velocity. The velocities of the vehicles are acquired from a continuous wave Doppler radar. A very low amount of power is consumed in this system and only batteries can use to operate. The system works on the principle of Doppler Effect by detecting the Doppler shift in microwaves reflected from a moving object. Since the output of the sensor is sinusoidal wave with very small amplitude and needs to be amplified with the help of the amplifier before further processing. The purpose to calculate and display the speed on LCD is performed by the microcontroller.

  10. DESIGN AND DEVELOP A COMPUTER AIDED DESIGN FOR AUTOMATIC EXUDATES DETECTION FOR DIABETIC RETINOPATHY SCREENING

    Directory of Open Access Journals (Sweden)

    C. A. SATHIYAMOORTHY

    2016-04-01

    Full Text Available Diabetic Retinopathy is a severe and widely spread eye disease which can lead to blindness. One of the main symptoms for vision loss is Exudates and it could be prevented by applying an early screening process. In the Existing systems, a Fuzzy C-Means Clustering technique is used for detecting the exudates for analyzation. The main objective of this paper is, to improve the efficiency of the Exudates detection in diabetic retinopathy images. To do this, a three Stage – [TS] approach is introduced for detecting and extracting the exudates automatically from the retinal images for screening the Diabetic retinopathy. TS functions on the image in three levels such as Pre-processing the image, enhancing the image and detecting the Exudates accurately. After successful detection, the detected exudates are classified using GLCM method for finding the accuracy. The TS approach is experimented using MATLAB software and the performance evaluation can be proved by comparing the results with the existing approach’s result and with the hand-drawn ground truths images from the expert ophthalmologist.

  11. Increasing accuracy of vehicle detection from conventional vehicle detectors - counts, speeds, classification, and travel time.

    Science.gov (United States)

    2014-09-01

    Vehicle classification is an important traffic parameter for transportation planning and infrastructure : management. Length-based vehicle classification from dual loop detectors is among the lowest cost : technologies commonly used for collecting th...

  12. [Detection of Brucella with an automatic hemoculture system: Bact/Alert].

    Science.gov (United States)

    Casas, J; Partal, Y; Llosá, J; Leiva, J; Navarro, J M; de la Rosa, M

    1994-12-01

    The ability of in vitro and in vivo detection of Brucella spp. with the Bact/Alert system was studied. Three strains of Brucella melitensis and two of Brucella abortus were used. Different dilutions of the five strains were performed in trypticase soy broth (TSB), achieving concentrations of 1 cfu/ml, 5 cfu/ml, 10 cfu/ml and 100 cfu/ml. Ten ml of each dilution and strain were inoculated into 5 aerobic bottles Bact/Alert and 5 biphasic Hemóline bottles. Furthermore, over a 9 month period, 8,216 bottles of Bact/Alert bottles from hospitalized patients and from the emergency department were processed in the authors' laboratory. The mean detection time for Brucella growth was from 2 to 3 days with the Bact/Alert system, and 14 days in the biphasic bottles. Former bottles processed in the authors' laboratory, 11 aerobic bottles belonged to 5 patients in whom brucelosis was confirmed by bloodculture. The Bact/Alert system detected Brucella melitensis in only on bottle at 2.9 days of incubation. In 7 bottles Bact/Alert detected B. melitensis by a blind pass of these bottles at 10 to 20 days of incubation. These results suggest that the Bact/Alert system does not totally solve the diagnosis of brucellosis. Blind passes of the bloodcultures are required.

  13. Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

    Directory of Open Access Journals (Sweden)

    Maíla de Lima Claro

    2016-08-01

    Full Text Available The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classiffication of images in glaucomatous or not. We obtained results of 93% accuracy.

  14. System parameter identification information criteria and algorithms

    CERN Document Server

    Chen, Badong; Hu, Jinchun; Principe, Jose C

    2013-01-01

    Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors' research pr

  15. The Commercial Vehicle Information Systems and Network program, 2012.

    Science.gov (United States)

    2014-03-01

    The Commercial Vehicle Information Systems and : Networks (CVISN) program supports that safety : mission by providing grant funds to States for: : Improving safety and productivity of motor : carriers, commercial motor vehicles : (CMVs), and thei...

  16. Digital Receiver-based Electronic Intelligence System Configuration for the Detection and Identification of Intrapulse Modulated Radar Signals

    OpenAIRE

    A. K. Singh; K. Subba Rao

    2014-01-01

    An optimum electronic intelligence system configuration incorporating the state of the art technologies and achieving the highest parameter accuracies while processing the complex intrapulse modulated radar signals is presented in this paper. The system is based on the quad digital receiver, a state of the art single board solution for the detection and analysis of modern radar signals. The system consists of base line interferometry  configuration for high accuracy direction finding measurem...

  17. Usefulness of Cone-Beam Computed Tomography and Automatic Vessel Detection Software in Emergency Transarterial Embolization

    Energy Technology Data Exchange (ETDEWEB)

    Carrafiello, Gianpaolo, E-mail: gcarraf@gmail.com; Ierardi, Anna Maria, E-mail: amierardi@yahoo.it; Duka, Ejona, E-mail: ejonaduka@hotmail.com [Insubria University, Department of Radiology, Interventional Radiology (Italy); Radaelli, Alessandro, E-mail: alessandro.radaelli@philips.com [Philips Healthcare (Netherlands); Floridi, Chiara, E-mail: chiara.floridi@gmail.com [Insubria University, Department of Radiology, Interventional Radiology (Italy); Bacuzzi, Alessandro, E-mail: alessandro.bacuzzi@ospedale.varese.it [University of Insubria, Anaesthesia and Palliative Care (Italy); Bucourt, Maximilian de, E-mail: maximilian.de-bucourt@charite.de [Charité - University Medicine Berlin, Department of Radiology (Germany); Marchi, Giuseppe De, E-mail: giuseppedemarchi@email.it [Insubria University, Department of Radiology, Interventional Radiology (Italy)

    2016-04-15

    BackgroundThis study was designed to evaluate the utility of dual phase cone beam computed tomography (DP-CBCT) and automatic vessel detection (AVD) software to guide transarterial embolization (TAE) of angiographically challenging arterial bleedings in emergency settings.MethodsTwenty patients with an arterial bleeding at computed tomography angiography and an inconclusive identification of the bleeding vessel at the initial 2D angiographic series were included. Accuracy of DP-CBCT and AVD software were defined as the ability to detect the bleeding site and the culprit arterial bleeder, respectively. Technical success was defined as the correct positioning of the microcatheter using AVD software. Clinical success was defined as the successful embolization. Total volume of iodinated contrast medium and overall procedure time were registered.ResultsThe bleeding site was not detected by initial angiogram in 20 % of cases, while impossibility to identify the bleeding vessel was the reason for inclusion in the remaining cases. The bleeding site was detected by DP-CBCT in 19 of 20 (95 %) patients; in one case CBCT-CT fusion was required. AVD software identified the culprit arterial branch in 18 of 20 (90 %) cases. In two cases, vessel tracking required manual marking of the candidate arterial bleeder. Technical success was 95 %. Successful embolization was achieved in all patients. Mean contrast volume injected for each patient was 77.5 ml, and mean overall procedural time was 50 min.ConclusionsC-arm CBCT and AVD software during TAE of angiographically challenging arterial bleedings is feasible and may facilitate successful embolization. Staff training in CBCT imaging and software manipulation is necessary.

  18. Usefulness of Cone-Beam Computed Tomography and Automatic Vessel Detection Software in Emergency Transarterial Embolization

    International Nuclear Information System (INIS)

    Carrafiello, Gianpaolo; Ierardi, Anna Maria; Duka, Ejona; Radaelli, Alessandro; Floridi, Chiara; Bacuzzi, Alessandro; Bucourt, Maximilian de; Marchi, Giuseppe De

    2016-01-01

    BackgroundThis study was designed to evaluate the utility of dual phase cone beam computed tomography (DP-CBCT) and automatic vessel detection (AVD) software to guide transarterial embolization (TAE) of angiographically challenging arterial bleedings in emergency settings.MethodsTwenty patients with an arterial bleeding at computed tomography angiography and an inconclusive identification of the bleeding vessel at the initial 2D angiographic series were included. Accuracy of DP-CBCT and AVD software were defined as the ability to detect the bleeding site and the culprit arterial bleeder, respectively. Technical success was defined as the correct positioning of the microcatheter using AVD software. Clinical success was defined as the successful embolization. Total volume of iodinated contrast medium and overall procedure time were registered.ResultsThe bleeding site was not detected by initial angiogram in 20 % of cases, while impossibility to identify the bleeding vessel was the reason for inclusion in the remaining cases. The bleeding site was detected by DP-CBCT in 19 of 20 (95 %) patients; in one case CBCT-CT fusion was required. AVD software identified the culprit arterial branch in 18 of 20 (90 %) cases. In two cases, vessel tracking required manual marking of the candidate arterial bleeder. Technical success was 95 %. Successful embolization was achieved in all patients. Mean contrast volume injected for each patient was 77.5 ml, and mean overall procedural time was 50 min.ConclusionsC-arm CBCT and AVD software during TAE of angiographically challenging arterial bleedings is feasible and may facilitate successful embolization. Staff training in CBCT imaging and software manipulation is necessary.

  19. Automatic detection and treatment of oscillatory and/or stiff ordinary differential equations

    Energy Technology Data Exchange (ETDEWEB)

    Gear, C. W.

    1980-06-01

    The next generation of ODE software can be expected to detect special problems and to adapt to their needs. The low-cost, automatic detection of oscillatory behavior, the determination of its period, and methods for its subsequent efficient integration are addressed here, along with stiffness detection. In the first phase, the method for oscillatory problems discussed examines the output of any integrator to determine if the output is nearly periodic. At the point this answer is positive, the second phase is entered and an automatic, nonstiff, multirevolutionary method is invoked. This requires the occasional solution of a nearly periodic initial-value problem over one period by a standard method and the re-determination of its period. Because the multirevolutionary method uses a very large step, the problem has a high probability of being stiff in this second phase. Hence, it is important to detect if stiffness is present so that an appropriate stiff, multirevolutionary method can be selected. 6 figures.

  20. Improvement and automatization of a proportional alpha-beta counting system - FAG

    International Nuclear Information System (INIS)

    German, U.; Levinson, S.; Pelled, O.; Shemesh, Y.; Assido, H.

    1997-01-01

    An alpha and beta counting system - FAG*, for planchette samples is operated at the Health Physics department's laboratory of the NRCN. The original operation mode of the system was based on manual tasks handled by the FHT1 100 electronics. An option for a basic computer keyboard operation was available too. A computer with an appropriate I/O card was connected to the system and a new operating program was developed which enables full automatic control of the various components. The program includes activity calculations and statistical checks as well as data management. A bar-code laser system for sample number reading was integrated into the Alpha-Beta automatic counting system. The sample identification by means of an attached bar-code label enables unmistakable and reliable attribution of results to the counted sample. authors)

  1. Automatic Sensor-Fault Detection System for Comprehensive Structural Health Monitoring System

    National Research Council Canada - National Science Library

    Chan, Hian-Leng; Zhang, Chang; Qing, Peter X; Ooi, Teng K; Marotta, Steve A

    2005-01-01

    Structural health monitoring systems are viewed as viable means to reduce life-cycle costs, increase structural reliability, and extend the operational hours for a wide variety of composite structures...

  2. Ground Vehicle System Integration (GVSI) and Design Optimization Model

    National Research Council Canada - National Science Library

    Horton, William

    1996-01-01

    This report documents the Ground Vehicle System Integration (GVSI) and Design Optimization Model GVSI is a top-level analysis tool designed to support engineering tradeoff studies and vehicle design optimization efforts...

  3. Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods

    Directory of Open Access Journals (Sweden)

    Dorothée Coppieters ’t Wallant

    2016-01-01

    Full Text Available Sleep spindle is a peculiar oscillatory brain pattern which has been associated with a number of sleep (isolation from exteroceptive stimuli, memory consolidation and individual characteristics (intellectual quotient. Oddly enough, the definition of a spindle is both incomplete and restrictive. In consequence, there is no consensus about how to detect spindles. Visual scoring is cumbersome and user dependent. To analyze spindle activity in a more robust way, automatic sleep spindle detection methods are essential. Various algorithms were developed, depending on individual research interest, which hampers direct comparisons and meta-analyses. In this review, sleep spindle is first defined physically and topographically. From this general description, we tentatively extract the main characteristics to be detected and analyzed. A nonexhaustive list of automatic spindle detection methods is provided along with a description of their main processing principles. Finally, we propose a technique to assess the detection methods in a robust and comparable way.

  4. Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods.

    Science.gov (United States)

    Coppieters 't Wallant, Dorothée; Maquet, Pierre; Phillips, Christophe

    2016-01-01

    Sleep spindle is a peculiar oscillatory brain pattern which has been associated with a number of sleep (isolation from exteroceptive stimuli, memory consolidation) and individual characteristics (intellectual quotient). Oddly enough, the definition of a spindle is both incomplete and restrictive. In consequence, there is no consensus about how to detect spindles. Visual scoring is cumbersome and user dependent. To analyze spindle activity in a more robust way, automatic sleep spindle detection methods are essential. Various algorithms were developed, depending on individual research interest, which hampers direct comparisons and meta-analyses. In this review, sleep spindle is first defined physically and topographically. From this general description, we tentatively extract the main characteristics to be detected and analyzed. A nonexhaustive list of automatic spindle detection methods is provided along with a description of their main processing principles. Finally, we propose a technique to assess the detection methods in a robust and comparable way.

  5. A Stochastic Approach for Automatic and Dynamic Modeling of Students' Learning Styles in Adaptive Educational Systems

    Science.gov (United States)

    Dorça, Fabiano Azevedo; Lima, Luciano Vieira; Fernandes, Márcia Aparecida; Lopes, Carlos Roberto

    2012-01-01

    Considering learning and how to improve students' performances, an adaptive educational system must know how an individual learns best. In this context, this work presents an innovative approach for student modeling through probabilistic learning styles combination. Experiments have shown that our approach is able to automatically detect and…

  6. Composite armor, armor system and vehicle including armor system

    Science.gov (United States)

    Chu, Henry S.; Jones, Warren F.; Lacy, Jeffrey M.; Thinnes, Gary L.

    2013-01-01

    Composite armor panels are disclosed. Each panel comprises a plurality of functional layers comprising at least an outermost layer, an intermediate layer and a base layer. An armor system incorporating armor panels is also disclosed. Armor panels are mounted on carriages movably secured to adjacent rails of a rail system. Each panel may be moved on its associated rail and into partially overlapping relationship with another panel on an adjacent rail for protection against incoming ordnance from various directions. The rail system may be configured as at least a part of a ring, and be disposed about a hatch on a vehicle. Vehicles including an armor system are also disclosed.

  7. Improving the safety and protective automatic actions of the CMS electromagnetic calorimeter detector control system

    CERN Document Server

    Jimenez Estupinan, Raul; Cirkovic, Predrag; Di Calafiori, Diogo Raphael; Dissertori, Guenther; Djambazov, Lubomir; Jovanovic, Dragoslav; Lustermann, Werner; Milenovic, Predrag; Zelepoukine, Serguei

    2017-01-01

    The CMS ECAL Detector Control System (DCS) features several monitoring mechanisms able to react and perform automatic actions based on pre-defined action matrices. The DCS is capable of early detection of anomalies inside the ECAL and on its off-detector support systems, triggering automatic actions to mitigate the impact of these events and preventing them from escalating to the safety system. The treatment of such events by the DCS allows for a faster recovery process, better understanding of the development of issues, and in most cases, actions with higher granularity than the safety system. This paper presents the details of the DCS automatic action mechanisms, as well as their evolution based on several years of CMS ECAL operations.

  8. Automatic centroid detection and surface measurement with a digital Shack–Hartmann wavefront sensor

    International Nuclear Information System (INIS)

    Yin, Xiaoming; Zhao, Liping; Li, Xiang; Fang, Zhongping

    2010-01-01

    With the breakthrough of manufacturing technologies, the measurement of surface profiles is becoming a big issue. A Shack–Hartmann wavefront sensor (SHWS) provides a promising technology for non-contact surface measurement with a number of advantages over interferometry. The SHWS splits the incident wavefront into many subsections and transfers the distorted wavefront detection into the centroid measurement. So the accuracy of the centroid measurement determines the accuracy of the SHWS. In this paper, we have presented a new centroid measurement algorithm based on an adaptive thresholding and dynamic windowing method by utilizing image-processing techniques. Based on this centroid detection method, we have developed a digital SHWS system which can automatically detect centroids of focal spots, reconstruct the wavefront and measure the 3D profile of the surface. The system has been tested with various simulated and real surfaces such as flat surfaces, spherical and aspherical surfaces as well as deformable surfaces. The experimental results demonstrate that the system has good accuracy, repeatability and immunity to optical misalignment. The system is also suitable for on-line applications of surface measurement

  9. Contribution to automatic speech recognition. Analysis of the direct acoustical signal. Recognition of isolated words and phoneme identification

    International Nuclear Information System (INIS)

    Dupeyrat, Benoit

    1981-01-01

    This report deals with the acoustical-phonetic step of the automatic recognition of the speech. The parameters used are the extrema of the acoustical signal (coded in amplitude and duration). This coding method, the properties of which are described, is simple and well adapted to a digital processing. The quality and the intelligibility of the coded signal after reconstruction are particularly satisfactory. An experiment for the automatic recognition of isolated words has been carried using this coding system. We have designed a filtering algorithm operating on the parameters of the coding. Thus the characteristics of the formants can be derived under certain conditions which are discussed. Using these characteristics the identification of a large part of the phonemes for a given speaker was achieved. Carrying on the studies has required the development of a particular methodology of real time processing which allowed immediate evaluation of the improvement of the programs. Such processing on temporal coding of the acoustical signal is extremely powerful and could represent, used in connection with other methods an efficient tool for the automatic processing of the speech.(author) [fr

  10. Combining Front Vehicle Detection with 3D Pose Estimation for a Better Driver Assistance

    Directory of Open Access Journals (Sweden)

    Yu Peng

    2012-09-01

    Full Text Available Driver assistant systems enhance traffic safety and efficiency. The accurate 3D pose of a front vehicle can help a driver to make the right decision on the road. We propose a novel real-time system to estimate the 3D pose of the front vehicle. This system consists of two parallel threads: vehicle rear tracking and mapping. The vehicle rear is first identified in the video captured by an onboard camera, after license plate localization and foreground extraction. The 3D pose estimation technique is then employed with respect to the extracted vehicle rear. Most current 3D pose estimation techniques need prior models or a stereo initialization with user cooperation. It is extremely difficult to obtain prior models due to the varying appearance of vehicles' rears. Moreover, it is unsafe to ask for drivers' cooperation when a vehicle is running. In our system, two initial keyframes for stereo algorithms are automatically extracted by vehicle rear detection and tracking. Map points are defined as a collection of point features extracted from the vehicle's rear with their 3D information. These map points are inferences that relate the 2D features detected in following vehicles' rears with the 3D world. The relative 3D pose of the onboard camera to the front vehicle rear is then estimated through matching the map points with point features detected on the front vehicle rear. We demonstrate the capabilities of our system by testing on real-time and synthesized videos. In order to make the experimental analysis visible, we demonstrated an estimated 3D pose through augmented reality, which needs accurate and real-time 3D pose estimation.

  11. Automatic limit switch system for scintillation device and method of operation

    International Nuclear Information System (INIS)

    Brunnett, C.J.; Ioannou, B.N.

    1976-01-01

    A scintillation scanner is described having an automatic limit switch system for setting the limits of travel of the radiation detection device which is carried by a scanning boom. The automatic limit switch system incorporates position responsive circuitry for developing a signal representative of the position of the boom, reference signal circuitry for developing a signal representative of a selected limit of travel of the boom, and comparator circuitry for comparng these signals in order to control the operation of a boom drive and indexing mechanism. (author)

  12. Flight Testing a Real-Time Hazard Detection System for Safe Lunar Landing on the Rocket-Powered Morpheus Vehicle

    Science.gov (United States)

    Trawny, Nikolas; Huertas, Andres; Luna, Michael E.; Villalpando, Carlos Y.; Martin, Keith E.; Carson, John M.; Johnson, Andrew E.; Restrepo, Carolina; Roback, Vincent E.

    2015-01-01

    The Hazard Detection System (HDS) is a component of the ALHAT (Autonomous Landing and Hazard Avoidance Technology) sensor suite, which together provide a lander Guidance, Navigation and Control (GN&C) system with the relevant measurements necessary to enable safe precision landing under any lighting conditions. The HDS consists of a stand-alone compute element (CE), an Inertial Measurement Unit (IMU), and a gimbaled flash LIDAR sensor that are used, in real-time, to generate a Digital Elevation Map (DEM) of the landing terrain, detect candidate safe landing sites for the vehicle through Hazard Detection (HD), and generate hazard-relative navigation (HRN) measurements used for safe precision landing. Following an extensive ground and helicopter test campaign, ALHAT was integrated onto the Morpheus rocket-powered terrestrial test vehicle in March 2014. Morpheus and ALHAT then performed five successful free flights at the simulated lunar hazard field constructed at the Shuttle Landing Facility (SLF) at Kennedy Space Center, for the first time testing the full system on a lunar-like approach geometry in a relevant dynamic environment. During these flights, the HDS successfully generated DEMs, correctly identified safe landing sites and provided HRN measurements to the vehicle, marking the first autonomous landing of a NASA rocket-powered vehicle in hazardous terrain. This paper provides a brief overview of the HDS architecture and describes its in-flight performance.

  13. Building Point Detection from Vehicle-Borne LiDAR Data Based on Voxel Group and Horizontal Hollow Analysis

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2016-05-01

    Full Text Available Information extraction and three-dimensional (3D reconstruction of buildings using the vehicle-borne laser scanning (VLS system is significant for many applications. Extracting LiDAR points, from VLS, belonging to various types of building in large-scale complex urban environments still retains some problems. In this paper, a new technical framework for automatic and efficient building point extraction is proposed, including three main steps: (1 voxel group-based shape recognition; (2 category-oriented merging; and (3 building point identification by horizontal hollow ratio analysis. This article proposes a concept of “voxel group” based on the voxelization of VLS points: each voxel group is composed of several voxels that belong to one single real-world object. Then the shapes of point clouds in each voxel group are recognized and this shape information is utilized to merge voxel group. This article puts forward a characteristic nature of vehicle-borne LiDAR building points, called “horizontal hollow ratio”, for efficient extraction. Experiments are analyzed from two aspects: (1 building-based evaluation for overall experimental area; and (2 point-based evaluation for individual building using the completeness and correctness. The experimental results indicate that the proposed framework is effective for the extraction of LiDAR points belonging to various types of buildings in large-scale complex urban environments.

  14. System identification of a small low-cost unmanned aerial vehicle using flight data from low-cost sensors

    Science.gov (United States)

    Hoffer, Nathan Von

    Remote sensing has traditionally been done with satellites and manned aircraft. While. these methods can yield useful scientificc data, satellites and manned aircraft have limitations in data frequency, process time, and real time re-tasking. Small low-cost unmanned aerial vehicles (UAVs) provide greater possibilities for personal scientic research than traditional remote sensing platforms. Precision aerial data requires an accurate vehicle dynamics model for controller development, robust flight characteristics, and fault tolerance. One method of developing a model is system identification (system ID). In this thesis system ID of a small low-cost fixed-wing T-tail UAV is conducted. The linerized longitudinal equations of motion are derived from first principles. Foundations of Recursive Least Squares (RLS) are presented along with RLS with an Error Filtering Online Learning scheme (EFOL). Sensors, data collection, data consistency checking, and data processing are described. Batch least squares (BLS) and BLS with EFOL are used to identify aerodynamic coecoefficients of the UAV. Results of these two methods with flight data are discussed.

  15. Explosive Detection and Identification by PGNAA

    Energy Technology Data Exchange (ETDEWEB)

    E.H. Seabury; A.J. Caffrey

    2004-11-01

    The goal of this project was to determine the feasibility of using field-portable prompt gamma-ray neutron activation analysis (PGNAA) to detect and identify explosives in improvised nuclear devices (INDs). The studies were carried out using the Monte Carlo N-Particle (MCNP) code developed at Los Alamos National Laboratory. The model results were tested experimentally using explosive simulants and the PINS PGNAA system developed at Idaho National Engineering and Environmental Laboratory (INEEL). The results of the MCNP calculations and PINS measurements are presented in this report. The calculations and measurements were in good agreement and indicate that most explosives are readily distinguishable from one another.

  16. Automatic detecting method of LED signal lamps on fascia based on color image

    Science.gov (United States)

    Peng, Xiaoling; Hou, Wenguang; Ding, Mingyue

    2009-10-01

    Instrument display panel is one of the most important parts of automobiles. Automatic detection of LED signal lamps is critical to ensure the reliability of automobile systems. In this paper, an automatic detection method was developed which is composed of three parts in the automatic detection: the shape of LED lamps, the color of LED lamps, and defect spots inside the lamps. More than hundreds of fascias were detected with the automatic detection algorithm. The speed of the algorithm is quite fast and satisfied with the real-time request of the system. Further, the detection result was demonstrated to be stable and accurate.

  17. Vehicle capture system

    Science.gov (United States)

    Tacke, Kenneth L.

    1998-12-01

    Primex Aerospace Company, under contract with the U.S. Army Armament Research Development & Engineering Center (ARDEC), has developed a portable vehicle capture system for use at vehicle checkpoints. Currently when a vehicle does not stop at a checkpoint, there are three possible reactions: let the vehicle go unchallenged, pursue the vehicle or stop the vehicle with lethal force. This system provides a non-lethal alternative that will stop and contain the vehicle. The system is completely portable with the heaviest component weighing less than 120 pounds. It can be installed with no external electrical power or permanent anchors required. In its standby mode, the system does not impede normal traffic, but on command erects a barrier in less than 1.5 seconds. System tests have been conducted using 5,100 and 8.400 pound vehicles, traveling at speeds up to 45 mph. The system is designed to minimize vehicle damage and occupant injury, typically resulting in deceleration forces of less than 2.5 gs on the vehicle. According to the drivers involved in tests at 45 mph, the stopping forces feel similar to a panic stop with the vehicle brakes locked. The system is completely reusable and be rapidly reset.

  18. Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Min-Yin Liu

    2017-05-01

    Full Text Available Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz measured by electroencephalography (EEG mostly during non-rapid eye movement (NREM stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1 the lack of common benchmark databases, and (2 the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA, the Strength Pareto Evolutionary Algorithm (SPEA2, to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT, and two Hilbert-Huang transform (HHT based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726–0.737.

  19. A novel method for detecting and tracking vehicles in traffic-image sequence

    Science.gov (United States)

    Xu, Jieqiong; Wang, Guoyu; Sun, Feifei

    2013-07-01

    A novel method for detecting and tracking vehicles is proposed. The method which based on motion object segmentation used Cellular Neural Network (CNN) in the background substraction for motion detection in order to distinguish the vehicles from others of the interested regions. Meanwhile a tracking method based on regional characteristic matching is proposed, by which the distance between characteristic vectors can be used to match current motion regions and track the vehicles. Perceptual grouping refers to the organization ability that visual system detect image features in accordance with certain cues such as proximity, continuity, closure, etc, and attracts wide attentions and high regards in computer vision. In this paper, we proposed a new approach for occlution elimination by combining perceptual grouping with Optical flow field. Experimental results show that the methods can extract traffic information with high accuracy and efficiency.

  20. Identification of mycobacterium tuberculosis in sputum smear slide using automatic scanning microscope

    Science.gov (United States)

    Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

    2015-04-01

    Sputum smear observation has an important role in tuberculosis (TB) disease diagnosis, because it needs accurate identification to avoid high errors diagnosis. In development countries, sputum smear slide observation is commonly done with conventional light microscope from Ziehl-Neelsen stained tissue and it doesn't need high cost to maintain the microscope. The clinicians do manual screening process for sputum smear slide which is time consuming and needs highly training to detect the presence of TB bacilli (mycobacterium tuberculosis) accurately, especially for negative slide and slide with less number of TB bacilli. For helping the clinicians, we propose automatic scanning microscope with automatic identification of TB bacilli. The designed system modified the field movement of light microscope with stepper motor which was controlled by microcontroller. Every sputum smear field was captured by camera. After that some image processing techniques were done for the sputum smear images. The color threshold was used for background subtraction with hue canal in HSV color space. Sobel edge detection algorithm was used for TB bacilli image segmentation. We used feature extraction based on shape for bacilli analyzing and then neural network classified TB bacilli or not. The results indicated identification of TB bacilli that we have done worked well and detected TB bacilli accurately in sputum smear slide with normal staining, but not worked well in over staining and less staining tissue slide. However, overall the designed system can help the clinicians in sputum smear observation becomes more easily.

  1. Automatic contact in DYNA3D for vehicle crashworthiness

    International Nuclear Information System (INIS)

    Whirley, R.G.; Engelmann, B.E.

    1994-01-01

    This paper presents a new formulation for the automatic definition and treatment of mechanical contact in explicit, nonlinear, finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. The authors have used a new four-step automatic contact algorithm. Key aspects of the proposed method include (1) automatic identification of adjacent and opposite surfaces in the global search phase, and (2) the use of a smoothly varying surface normal that allows a consistent treatment of shell intersection and corner contact conditions without ad hoc rules. Three examples are given to illustrate the performance of the newly proposed algorithm in the public DYNA3D code

  2. Image-Based Pothole Detection System for ITS Service and Road Management System

    Directory of Open Access Journals (Sweden)

    Seung-Ki Ryu

    2015-01-01

    Full Text Available Potholes can generate damage such as flat tire and wheel damage, impact and damage of lower vehicle, vehicle collision, and major accidents. Thus, accurately and quickly detecting potholes is one of the important tasks for determining proper strategies in ITS (Intelligent Transportation System service and road management system. Several efforts have been made for developing a technology which can automatically detect and recognize potholes. In this study, a pothole detection method based on two-dimensional (2D images is proposed for improving the existing method and designing a pothole detection system to be applied to ITS service and road management system. For experiments, 2D road images that were collected by a survey vehicle in Korea were used and the performance of the proposed method was compared with that of the existing method for several conditions such as road, recording, and brightness. The results are promising, and the information extracted using the proposed method can be used, not only in determining the preliminary maintenance for a road management system and in taking immediate action for their repair and maintenance, but also in providing alert information of potholes to drivers as one of ITS services.

  3. Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

    Science.gov (United States)

    Giménez, Estela; Gay, Marina; Vilaseca, Marta

    2017-01-30

    Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Raft and floating radio frequency identification (RFID) antenna systems for detecting and estimating abundance of PIT-tagged fish in rivers

    Science.gov (United States)

    Fetherman, Eric R.; Avila, Brian W.; Winkelman, Dana L.

    2016-01-01

    Portable radio frequency identification (RFID) PIT tag antenna systems are increasingly being used in studies examining aquatic animal movement, survival, and habitat use, and their design flexibility permits application in a wide variety of settings. We describe the construction, use, and performance of two portable floating RFID PIT tag antenna systems designed to detect fish that were unavailable for recapture using stationary antennas or electrofishing. A raft antenna system was designed to detect and locate PIT-tagged fish in relatively long (i.e., ≥10 km) river reaches, and consisted of two antennas: (1) a horizontal antenna (4 × 1.2 m) installed on the bottom of the raft and used to detect fish in shallower river reaches (test using rocks marked with 32-mm PIT tags. Detection probability of PIT-tagged fish in the Cache la Poudre River, Colorado, using the raft antenna system, which covered 21% of the wetted area, was 0.14 ± 0.14. A shore-deployed floating antenna (14.6 × 0.6 m), which covered 100% of the wetted area, was designed for use by two operators for detecting and locating PIT-tagged fish in shorter (i.e., alternative to estimating abundance using traditional sampling methods such as electrofishing.

  5. Fault detection and isolation for a full-scale railway vehicle suspension with multiple Kalman filters

    Science.gov (United States)

    Jesussek, Mathias; Ellermann, Katrin

    2014-12-01

    Reliability and dependability in complex mechanical systems can be improved by fault detection and isolation (FDI) methods. These techniques are key elements for maintenance on demand, which could decrease service cost and time significantly. This paper addresses FDI for a railway vehicle: the mechanical model is described as a multibody system, which is excited randomly due to track irregularities. Various parameters, like masses, spring- and damper-characteristics, influence the dynamics of the vehicle. Often, the exact values of the parameters are unknown and might even change over time. Some of these changes are considered critical with respect to the operation of the system and they require immediate maintenance. The aim of this work is to detect faults in the suspension system of the vehicle. A Kalman filter is used in order to estimate the states. To detect and isolate faults the detection error is minimised with multiple Kalman filters. A full-scale train model with nonlinear wheel/rail contact serves as an example for the described techniques. Numerical results for different test cases are presented. The analysis shows that for the given system it is possible not only to detect a failure of the suspension system from the system's dynamic response, but also to distinguish clearly between different possible causes for the changes in the dynamical behaviour.

  6. An automatic speech recognition system with speaker-independent identification support

    Science.gov (United States)

    Caranica, Alexandru; Burileanu, Corneliu

    2015-02-01

    The novelty of this work relies on the application of an open source research software toolkit (CMU Sphinx) to train, build and evaluate a speech recognition system, with speaker-independent support, for voice-controlled hardware applications. Moreover, we propose to use the trained acoustic model to successfully decode offline voice commands on embedded hardware, such as an ARMv6 low-cost SoC, Raspberry PI. This type of single-board computer, mainly used for educational and research activities, can serve as a proof-of-concept software and hardware stack for low cost voice automation systems.

  7. Parameter design and performance analysis of shift actuator for a two-speed automatic mechanical transmission for pure electric vehicles

    Directory of Open Access Journals (Sweden)

    Jianjun Hu

    2016-08-01

    Full Text Available Recent developments of pure electric vehicles have shown that pure electric vehicles equipped with two-speed or multi-speed gearbox possess higher energy efficiency by ensuring the drive motor operates at its peak performance range. This article presents the design, analysis, and control of a two-speed automatic mechanical transmission for pure electric vehicles. The shift actuator is based on a motor-controlled camshaft where a special geometric groove is machined, and the camshaft realizes the axial positions of the synchronizer sleeve for gear engaging, disengaging, and speed control of the drive motor. Based on the force analysis of shift process, the parameters of shift actuator and shift motor are designed. The drive motor’s torque control strategy before shifting, speed governing control strategy before engaging, shift actuator’s control strategy during gear engaging, and drive motor’s torque recovery strategy after shift process are proposed and implemented with a prototype. To validate the performance of the two-speed gearbox, a test bed was developed based on dSPACE that emulates various operation conditions. The experimental results indicate that the shift process with the proposed shift actuator and control strategy could be accomplished within 1 s under various operation conditions, with shift smoothness up to passenger car standard.

  8. Automatic detection and tracking of dust particles in a RF plasma sheath

    OpenAIRE

    Zayachuk, Y.; Brochard, F.; Bardin, S.; Briançon, J-L.; Hugon, R.; Bougdira, J.

    2010-01-01

    A method enabling automatic detection and tracking of large amounts of individual dust particles in plasmas is presented. Individual trajectories can be found with a good spatiotemporal resolution, even without applying any external light source to facilitate detection. Main advantages of this method is a high portability and the possibility of making statistical analyses of the trajectories of a large amount of non uniformly size distributed particles, under challenging illumination conditio...

  9. A SIMULATION ENVIRONMENT FOR AUTOMATIC NIGHT DRIVING AND VISUAL CONTROL

    OpenAIRE

    Arroyo Rubio, Fernando

    2012-01-01

    This project consists on developing an automatic night driving system in a simulation environment. The simulator I have used is TORCS. TORCS is an Open Source car racing simulator written in C++. It is used as an ordinary car racing game, as a IA racing game and as a research platform. The goal of this thesis is to implement an automatic driving system to control the car under night conditions using computer vision. A camera is implemented inside the vehicle and it will detect the reflective ...

  10. Vehicle health management for guidance, navigation and control systems

    Science.gov (United States)

    Radke, Kathleen; Frazzini, Ron; Bursch, Paul; Wald, Jerry; Brown, Don

    The objective of the program was to architect a vehicle health management (VHM) system for space systems avionics that assures system readiness for launch vehicles and for space-based dormant vehicles. The platforms which were studied and considered for application of VHM for guidance, navigation and control (GN&C) included the Advanced Manned Launch System (AMLS), the Horizontal Landing-20/Personnel Launch System (HL-20/PLS), the Assured Crew Return Vehicle (ACRV) and the Extended Duration Orbiter (EDO). This set was selected because dormancy and/or availability requirements are driving the designs of these future systems.

  11. Long Range Target Recognition and Identification of Camouflaged Armored Vehicles

    Science.gov (United States)

    1979-05-01

    benefit attributable to pattern painting was dis- covered during the MASSTER evaluation. It seems that observations made with image-intensification...under tle. sameL conditt ons of observatt ott Observers viewed : acai e model MCA) t anks and Ml1,3 A11C. on it terra in board at a scit led range of- 1045...are ever in combat. As a consequence, by doing your best, you will benefit not only the Army in its threat recognition/ identification research, but

  12. Detection and identification of human targets in radar data

    Science.gov (United States)

    Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

    2007-04-01

    Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

  13. Detection and 3d Modelling of Vehicles from Terrestrial Stereo Image Pairs

    Science.gov (United States)

    Coenen, M.; Rottensteiner, F.; Heipke, C.

    2017-05-01

    The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, obtained from a moving vehicle. Processing every stereo pair individually, our approach is divided into two subsequent steps: the vehicle detection and the modelling step. For the detection, we make use of the 3D stereo information and incorporate geometric assumptions on vehicle inherent properties in a firstly applied generic 3D object detection. By combining our generic detection approach with a state of the art vehicle detector, we are able to achieve satisfying detection results with values for completeness and correctness up to more than 86%. By fitting an object specific vehicle model into the vehicle detections, we are able to reconstruct the vehicles in 3D and to derive pose estimations as well as shape parameters for each vehicle. To deal with the intra-class variability of vehicles, we make use of a deformable 3D active shape model learned from 3D CAD vehicle data in our model fitting approach. While we achieve encouraging values up to 67.2% for correct position estimations, we are facing larger problems concerning the orientation estimation. The evaluation is done by using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012).

  14. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors

    Science.gov (United States)

    Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented. PMID:22400008

  15. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

    Science.gov (United States)

    Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

  16. Edge detection of iris of the eye for human biometric identification system

    Directory of Open Access Journals (Sweden)

    Kateryna O. Tryfonova

    2015-03-01

    Full Text Available Method of human biometric identification by iris of the eye is considered as one of the most accurate and reliable methods of identification. Aim of the research is to solve the problem of edge detection of digital image of the human eye iris to be able to implement human biometric identification system by means of mobile device. To achieve this aim the algorithm of edge detection by Canny is considered in work. It consists of the following steps: smoothing, finding gradients, non-maximum suppression, double thresholding with hysteresis. The software implementation of the Canny algorithm is carried out for the Android mobile platform with the use of high level programming language Java.

  17. Performance evaluation and design of flight vehicle control systems

    CERN Document Server

    Falangas, Eric T

    2015-01-01

    This book will help students, control engineers and flight dynamics analysts to model and conduct sophisticated and systemic analyses of early flight vehicle designs controlled with multiple types of effectors and to design and evaluate new vehicle concepts in terms of satisfying mission and performance goals. Performance Evaluation and Design of Flight Vehicle Control Systems begins by creating a dynamic model of a generic flight vehicle that includes a range of elements from airplanes and launch vehicles to re-entry vehicles and spacecraft. The models may include dynamic effects dealing with structural flexibility, as well as dynamic coupling between structures and actuators, propellant sloshing, and aeroelasticity, and they are typically used for control analysis and design. The book shows how to efficiently combine different types of effectors together, such as aero-surfaces, TVC, throttling engines and RCS, to operate as a system by developing a mixing logic atrix. Methods of trimming a vehicle controll...

  18. Automatic visual impairment detection system for age-related eye diseases through gaze analysis.

    Science.gov (United States)

    Ai Ping Yow; Damon Wong; Huiying Liu; Hongyuan Zhu; Ivy Jing-Wen Ong; Laude, Augustinus; Tock Han Lim

    2017-07-01

    Visual impairment associated with Age-related Macular Degeneration (AMD) often results in a central scotoma which is an alteration in the central vision, leading to distortion or loss of vision. Current methods for assessing visual performance such as Amsler grid and Microperimetry are typically manual and have limitations as an indicator of visual field. In this paper, we present an automated system for detecting visual impairment through gaze tracking (AVIGA). Two types of assessments namely, Impulse Stimuli Response (ISR) test and Pursuit Stimuli Response (PSR) test were implemented in AVIGA system. A Support Vector Regression (SVR)-based approach is applied on the assessment results to differentiate the severity of visual impairment. The results show that AVIGA system is well-correlated to visual acuity test (VA) and performs better in identifying presence of visual impairments in eyes, compared to Microperimetry.

  19. Electronic Toll And Traffic Management Systems, National Cooperative Highway Research Program Synthesis

    Science.gov (United States)

    1993-01-01

    ELECTRONIC TOLL COLLECTION OR ETC AND TRAFFIC MANAGEMENT OR ETTM, AUTOMATIC VEHICLE IDENTIFICATION OR AVI : ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT (ETTM) SYSTEMS ARE NOT A FUTURISTIC DREAM, THEY ARE OPERATING OR ARE BEING TESTED TODAY I...

  20. Automatic Generation of Overlays and Offset Values Based on Visiting Vehicle Telemetry and RWS Visuals

    Science.gov (United States)

    Dunne, Matthew J.

    2011-01-01

    The development of computer software as a tool to generate visual displays has led to an overall expansion of automated computer generated images in the aerospace industry. These visual overlays are generated by combining raw data with pre-existing data on the object or objects being analyzed on the screen. The National Aeronautics and Space Administration (NASA) uses this computer software to generate on-screen overlays when a Visiting Vehicle (VV) is berthing with the International Space Station (ISS). In order for Mission Control Center personnel to be a contributing factor in the VV berthing process, computer software similar to that on the ISS must be readily available on the ground to be used for analysis. In addition, this software must perform engineering calculations and save data for further analysis.

  1. Automatic detection of diabetic foot complications with infrared thermography by asymmetric analysis

    NARCIS (Netherlands)

    Liu, C.; van Netten, Jaap J.; van Baal, Jeff G.; Bus, Sicco A.; van der Heijden, Ferdinand

    2015-01-01

    Early identification of diabetic foot complications and their precursors is essential in preventing their devastating consequences, such as foot infection and amputation. Frequent, automatic risk assessment by an intelligent telemedicine system might be feasible and cost effective. Infrared

  2. Studies and Proposals for an Automatic Crystal Control System

    CERN Document Server

    Drobychev, Gleb; Khruschinsky, A A; Korzhik, Mikhail; Missevitch, Oleg; Oriboni, André; Peigneux, Jean-Pierre; Schneegans, Marc

    1997-01-01

    This document presents the status of the studies for an Automatic Crystal Control System ( ACCOS) performed since autumn 1995 for the CMS collaboration. Evaluation of a startstop method for light yield, light uniformity and decay time measurements of PbWO4 crystals is presented, as well as the first results obtained with a compact double-beam spectrophotometer for transverse transmission. Various overall schemes are proposed for an integrated set-up including crystal dimension measurement. The initial financial evaluationperformed is also given.

  3. Automatic change detection: does the auditory system use representations of individual stimulus features or gestalts?

    Science.gov (United States)

    Deacon, D; Nousak, J M; Pilotti, M; Ritter, W; Yang, C M

    1998-07-01

    The effects of global and feature-specific probabilities of auditory stimuli were manipulated to determine their effects on the mismatch negativity (MMN) of the human event-related potential. The question of interest was whether the automatic comparison of stimuli indexed by the MMN was performed on representations of individual stimulus features or on gestalt representations of their combined attributes. The design of the study was such that both feature and gestalt representations could have been available to the comparator mechanism generating the MMN. The data were consistent with the interpretation that the MMN was generated following an analysis of stimulus features.

  4. Explosives Detection and Identification by PGNAA

    Energy Technology Data Exchange (ETDEWEB)

    E. H. Seabury; A. J. Caffrey

    2006-04-01

    The feasibility of using field-portable prompt gamma-ray neutron activation analysis (PGNAA) to detect and identify explosives in improvised nuclear devices has been studied computationally, using the Monte Carlo N-Particle (MCNP) code developed at Los Alamos National Laboratory. The Monte Carlo results, in turn were tested experimentally using explosive simulants and the PINS PGNAA system developed at Idaho National Laboratory (INL). The results of the MCNP calculations and PINS measurements have been previously reported. In this report we describe measurements performed on actual explosives and compare the results with calculations. The calculations and measurements were in good agreement and indicate that most explosives are readily distinguishable from one another by PGNAA

  5. Automatic detection of osteoporotic vertebral fractures in routine thoracic and abdominal MDCT.

    Science.gov (United States)

    Baum, Thomas; Bauer, Jan S; Klinder, Tobias; Dobritz, Martin; Rummeny, Ernst J; Noël, Peter B; Lorenz, Cristian

    2014-04-01

    To develop a prototype algorithm for automatic spine segmentation in MDCT images and use it to automatically detect osteoporotic vertebral fractures. Cross-sectional routine thoracic and abdominal MDCT images of 71 patients including 8 males and 9 females with 25 osteoporotic vertebral fractures and longitudinal MDCT images of 9 patients with 18 incidental fractures in the follow-up MDCT were retrospectively selected. The spine segmentation algorithm localised and identified the vertebrae T5-L5. Each vertebra was automatically segmented by using corresponding vertebra surface shape models that were adapted to the original images. Anterior, middle, and posterior height of each vertebra was automatically determined; the anterior-posterior ratio (APR) and middle-posterior ratio (MPR) were computed. As the gold standard, radiologists graded vertebral fractures from T5 to L5 according to the Genant classification in consensus. Using ROC analysis to differentiate vertebrae without versus with prevalent fracture, AUC values of 0.84 and 0.83 were obtained for APR and MPR, respectively (p vertebrae without versus with incidental fracture (ΔAPR: -8.5 % ± 8.6 % versus -1.6 % ± 4.2 %, p = 0.002; ΔMPR: -11.4 % ± 7.7 % versus -1.2 % ± 1.6 %, p osteoporotic vertebral fractures so that appropriate therapy can be initiated. • This spine segmentation algorithm automatically localised, identified, and segmented the vertebrae in MDCT images. • Osteoporotic vertebral fractures could be automatically detected using this prototype algorithm. • The prototype algorithm helps radiologists to report underdiagnosed osteoporotic vertebral fractures.

  6. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    International Nuclear Information System (INIS)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing

    2016-01-01

    Purpose: Radiation treatment planning involves a complex workflow that has multiple potential points of vulnerability. This study utilizes an incident reporting system to identify the origination and detection points of near-miss errors, in order to guide their departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or applied a near-miss risk index (NMRI) to gauge severity. Methods: From 3/2012 to 3/2014, 1897 incidents were analyzed from a departmental incident learning system. All incidents were prospectively reviewed weekly by a multidisciplinary team and assigned a NMRI score ranging from 0 to 4 reflecting potential harm to the patient (no potential harm to potential critical harm). Incidents were classified by point of incident origination and detection based on a 103-step workflow. The individual steps were divided among nine broad workflow categories (patient assessment, imaging for radiation therapy (RT) planning, treatment planning, pretreatment plan review, treatment delivery, on-treatment quality management, post-treatment completion, equipment/software quality management, and other). The average NMRI scores of incidents originating or detected within each broad workflow area were calculated. Additionally, out of 103 individual process steps, 35 were classified as safety barriers, the process steps whose primary function is to catch errors. The safety barriers which most frequently detected incidents were identified and analyzed. Finally, the distance between event origination and detection was explored by grouping events by the number of broad workflow area events passed through before detection, and average NMRI scores were compared. Results: Near-miss incidents most commonly originated within treatment planning (33%). However, the incidents with the highest average NMRI scores originated during imaging for RT planning (NMRI = 2.0, average NMRI of all events = 1.5), specifically

  7. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    Energy Technology Data Exchange (ETDEWEB)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing, E-mail: jzeng13@uw.edu [Department of Radiation Oncology, University of Washington Medical Center, 1959 NE Pacific Street, Campus Box 356043, Seattle, Washington 98195 (United States)

    2016-05-15

    Purpose: Radiation treatment planning involves a complex workflow that has multiple potential points of vulnerability. This study utilizes an incident reporting system to identify the origination and detection points of near-miss errors, in order to guide their departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or applied a near-miss risk index (NMRI) to gauge severity. Methods: From 3/2012 to 3/2014, 1897 incidents were analyzed from a departmental incident learning system. All incidents were prospectively reviewed weekly by a multidisciplinary team and assigned a NMRI score ranging from 0 to 4 reflecting potential harm to the patient (no potential harm to potential critical harm). Incidents were classified by point of incident origination and detection based on a 103-step workflow. The individual steps were divided among nine broad workflow categories (patient assessment, imaging for radiation therapy (RT) planning, treatment planning, pretreatment plan review, treatment delivery, on-treatment quality management, post-treatment completion, equipment/software quality management, and other). The average NMRI scores of incidents originating or detected within each broad workflow area were calculated. Additionally, out of 103 individual process steps, 35 were classified as safety barriers, the process steps whose primary function is to catch errors. The safety barriers which most frequently detected incidents were identified and analyzed. Finally, the distance between event origination and detection was explored by grouping events by the number of broad workflow area events passed through before detection, and average NMRI scores were compared. Results: Near-miss incidents most commonly originated within treatment planning (33%). However, the incidents with the highest average NMRI scores originated during imaging for RT planning (NMRI = 2.0, average NMRI of all events = 1.5), specifically

  8. A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

    Science.gov (United States)

    Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus

    2014-12-01

    An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.

  9. Automatic object recognition and change detection of urban trees

    NARCIS (Netherlands)

    Van der Sande, C.J.

    2010-01-01

    Monitoring of tree objects is relevant in many current policy issues and relate to the quality of the public space, municipal urban green management, management fees for green areas or Kyoto protocol reporting and all have one thing in common: the need for an up to date tree database. This study,

  10. Efficient and automatic image reduction framework for space debris detection based on GPU technology

    Science.gov (United States)

    Diprima, Francesco; Santoni, Fabio; Piergentili, Fabrizio; Fortunato, Vito; Abbattista, Cristoforo; Amoruso, Leonardo

    2018-04-01

    In the last years, the increasing number of space debris has triggered the need of a distributed monitoring system for the prevention of possible space collisions. Space surveillance based on ground telescope allows the monitoring of the traffic of the Resident Space Objects (RSOs) in the Earth orbit. This space debris surveillance has several applications such as orbit prediction and conjunction assessment. In this paper is proposed an optimized and performance-oriented pipeline for sources extraction intended to the automatic detection of space debris in optical data. The detection method is based on the morphological operations and Hough Transform for lines. Near real-time detection is obtained using General Purpose computing on Graphics Processing Units (GPGPU). The high degree of processing parallelism provided by GPGPU allows to split data analysis over thousands of threads in order to process big datasets with a limited computational time. The implementation has been tested on a large and heterogeneous images data set, containing both imaging satellites from different orbit ranges and multiple observation modes (i.e. sidereal and object tracking). These images were taken during an observation campaign performed from the EQUO (EQUatorial Observatory) observatory settled at the Broglio Space Center (BSC) in Kenya, which is part of the ASI-Sapienza Agreement.

  11. EVEREST: automatic identification and classification of protein domains in all protein sequences

    Directory of Open Access Journals (Sweden)

    Linial Nathan

    2006-06-01

    Full Text Available Abstract Background Proteins are comprised of one or several building blocks, known as domains. Such domains can be classified into families according to their evolutionary origin. Whereas sequencing technologies have advanced immensely in recent years, there are no matching computational methodologies for large-scale determination of protein domains and their boundaries. We provide and rigorously evaluate a novel set of domain families that is automatically generated from sequence data. Our domain family identification process, called EVEREST (EVolutionary Ensembles of REcurrent SegmenTs, begins by constructing a library of protein segments that emerge in an all vs. all pairwise sequence comparison. It then proceeds to cluster these segments into putative domain families. The selection of the best putative families is done using machine learning techniques. A statistical model is then created for each of the chosen families. This procedure is then iterated: the aforementioned statistical models are used to scan all protein sequences, to recreate a library of segments and to cluster them again. Results Processing the Swiss-Prot section of the UniProt Knoledgebase, release 7.2, EVEREST defines 20,230 domains, covering 85% of the amino acids of the Swiss-Prot database. EVEREST annotates 11,852 proteins (6% of the database that are not annotated by Pfam A. In addition, in 43,086 proteins (20% of the database, EVEREST annotates a part of the protein that is not annotated by Pfam A. Performance tests show that EVEREST recovers 56% of Pfam A families and 63% of SCOP families with high accuracy, and suggests previously unknown domain families with at least 51% fidelity. EVEREST domains are often a combination of domains as defined by Pfam or SCOP and are frequently sub-domains of such domains. Conclusion The EVEREST process and its output domain families provide an exhaustive and validated view of the protein domain world that is automatically

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  14. Human factors in automatic image retrieval system design and evaluation

    Science.gov (United States)

    Jaimes, Alejandro

    2006-01-01

    Image retrieval is a human-centered task: images are created by people and are ultimately accessed and used by people for human-related activities. In designing image retrieval systems and algorithms, or measuring their performance, it is therefore imperative to consider the conditions that surround both the indexing of image content and the retrieval. This includes examining the different levels of interpretation for retrieval, possible search strategies, and image uses. Furthermore, we must consider different levels of similarity and the role of human factors such as culture, memory, and personal context. This paper takes a human-centered perspective in outlining levels of description, types of users, search strategies, image uses, and human factors that affect the construction and evaluation of automatic content-based retrieval systems, such as human memory, context, and subjectivity.

  15. Oocytes Polar Body Detection for Automatic Enucleation

    Directory of Open Access Journals (Sweden)

    Di Chen

    2016-02-01

    Full Text Available Enucleation is a crucial step in cloning. In order to achieve automatic blind enucleation, we should detect the polar body of the oocyte automatically. The conventional polar body detection approaches have low success rate or low efficiency. We propose a polar body detection method based on machine learning in this paper. On one hand, the improved Histogram of Oriented Gradient (HOG algorithm is employed to extract features of polar body images, which will increase success rate. On the other hand, a position prediction method is put forward to narrow the search range of polar body, which will improve efficiency. Experiment results show that the success rate is 96% for various types of polar bodies. Furthermore, the method is applied to an enucleation experiment and improves the degree of automatic enucleation.

  16. Rheticus Displacement: an Automatic Geo-Information Service Platform for Ground Instabilities Detection and Monitoring

    Science.gov (United States)

    Chiaradia, M. T.; Samarelli, S.; Agrimano, L.; Lorusso, A. P.; Nutricato, R.; Nitti, D. O.; Morea, A.; Tijani, K.

    2016-12-01

    Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and a minimum interaction with human operators. This target is achieved by means of programmable components working as different software layers in a modern enterprise system which relies on SOA (service-oriented-architecture) model. Due to its architecture, where every functionality is well defined and encapsulated in a standalone component, Rheticus is potentially highly scalable and distributable allowing different configurations depending on the user needs. Rheticus offers a portfolio of services, ranging from the detection and monitoring of geohazards and infrastructural instabilities, to marine water quality monitoring, wildfires detection or land cover monitoring. In this work, we outline the overall cloud-based platform and focus on the "Rheticus Displacement" service, aimed at providing accurate information to monitor movements occurring across landslide features or structural instabilities that could affect buildings or infrastructures. Using Sentinel-1 (S1) open data images and Multi-Temporal SAR Interferometry techniques (i.e., SPINUA), the service is complementary to traditional survey methods, providing a long-term solution to slope instability monitoring. Rheticus automatically browses and accesses (on a weekly basis) the products of the rolling archive of ESA S1 Scientific Data Hub; S1 data are then handled by a mature running processing chain, which is responsible of producing displacement maps immediately usable to measure with sub-centimetric precision movements of coherent points. Examples are provided, concerning the automatic displacement map generation process, as well as the integration of point and distributed scatterers, the integration of multi-sensors displacement maps (e.g., Sentinel-1 IW and COSMO-SkyMed HIMAGE), the combination of displacement rate maps acquired along both ascending

  17. An autonomous vehicle: Constrained test and evaluation

    Science.gov (United States)

    Griswold, Norman C.

    1991-11-01

    The objective of the research is to develop an autonomous vehicle which utilizes stereo camera sensors (using ambient light) to follow complex paths at speeds up to 35 mph with consideration of moving vehicles within the path. The task is intended to demonstrate the contribution to safety of a vehicle under automatic control. All of the long-term scenarios investigating future reduction in congestion involve an automatic system taking control, or partial control, of the vehicle. A vehicle which includes a collision avoidance system is a prerequisite to an automatic control system. The report outlines the results of a constrained test of a vision controlled vehicle. In order to demonstrate its ability to perform on the current street system the vehicle was constrained to recognize, approach, and stop at an ordinary roadside stop sign.

  18. A method for unsupervised change detection and automatic radiometric normalization in multispectral data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton John

    2011-01-01

    Based on canonical correlation analysis the iteratively re-weighted multivariate alteration detection (MAD) method is used to successfully perform unsupervised change detection in bi-temporal Landsat ETM+ images covering an area with villages, woods, agricultural fields and open pit mines in North...... Rhine- Westphalia, Germany. A link to an example with ASTER data to detect change with the same method after the 2005 Kashmir earthquake is given. The method is also used to automatically normalize multitemporal, multispectral Landsat ETM+ data radiometrically. IDL/ENVI, Python and Matlab software...

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

    Science.gov (United States)

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

    2016-08-19

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

  20. Stakeholders' opinions on a future in-vehicle alcohol detection system for prevention of drunk driving.

    Science.gov (United States)

    Anund, Anna; Antonson, Hans; Ihlström, Jonas

    2015-01-01

    There is a common understanding that driving under the influence of alcohol is associated with higher risk of being involved in crashes with injuries and possible fatalities as the outcome. Various countermeasures have therefore from time to time been taken by the authorities to prevent drunk driving. One of them has been the alcohol interlock. Up to now, interlocks have mainly been used by previously convicted drunk drivers and in the commercial road transport sector, but not in private cars. New technology has today reached a level where broader implementation might be possible. To our knowledge, however, little is known about different stakeholders' opinions of a broader implementation of such systems. In order to increase that knowledge, we conducted a focus group study to collect in-depth thoughts from different stakeholders on this topic. Eight focus groups representing a broad societal span were recruited and conducted for the purpose. The results show that most stakeholders thought that an integrated system for alcohol detection in vehicles might be beneficial in lowering the number of drunk driving crashes. They said that the system would probably mainly prevent driving by people who unintentionally and unknowingly drive under the influence of alcohol. The groups did, however, not regard the system as a final solution to the drunk driving problem, and believed that certain groups, such as criminals and alcoholics, would most likely find a way around the system. Concerns were raised about the risk of increased sleepy driving and driving just under the legal blood alcohol concentration (BAC) limit. The results also indicate that stakeholders preferred a system that provides information on the BAC up to the legal limit, but not for levels above the limit; for those, the system should simply prevent the car from starting. Acceptance of the system depended on the reliability of the system, on its ability to perform fast sampling, and on the analytical process

  1. 14 CFR 25.672 - Stability augmentation and automatic and power-operated systems.

    Science.gov (United States)

    2010-01-01

    ... power-operated systems. 25.672 Section 25.672 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Construction Control Systems § 25.672 Stability augmentation and automatic and power-operated systems. If the functioning of stability augmentation or other automatic or power-operated systems is necessary to show...

  2. Automatic Laser Light Detection and Filtering Using a Liquid Crystal Lyot Filter

    Science.gov (United States)

    Rees, S.; Staromlynska, J.

    A device which acts as both a simple cw laser warner and anti-dazzle protection device has been designed and tested. The design is based on a single stage, double element, tunable liquid crystal Lyot filter. Laboratory tests have shown that the detection sensitivity of the device for monochromatic cw radiation is approximately 43×10-9 W/cm2 and that the achievable contrast ratio is greater than 100:1 Automatic detection and filtering of a cw laser source has been demonstrated. Results indicate that the algorithm to automatically filter the laser radiation works well and that the extinction obtained is good. Factors which affect the contrast ratio are discussed and improved device design suggested.

  3. Automatic Identification of Physical Activity Intensity and Modality from the Fusion of Accelerometry and Heart Rate Data.

    Science.gov (United States)

    García-García, Fernando; Benito, Pedro J; Hernando, María E

    2016-12-07

    Physical activity (PA) is essential to prevent and to treat a variety of chronic diseases. The automated detection and quantification of PA over time empowers lifestyle interventions, facilitating reliable exercise tracking and data-driven counseling. We propose and compare various combinations of machine learning (ML) schemes for the automatic classification of PA from multi-modal data, simultaneously captured by a biaxial accelerometer and a heart rate (HR) monitor. Intensity levels (low / moderate / vigorous) were recognized, as well as for vigorous exercise, its modality (sustained aerobic / resistance / mixed). In total, 178.63 h of data about PA intensity (65.55 % low / 18.96 % moderate / 15.49 % vigorous) and 17.00 h about modality were collected in two experiments: one in free-living conditions, another in a fitness center under controlled protocols. The structure used for automatic classification comprised: a) definition of 42 time-domain signal features, b) dimensionality reduction, c) data clustering, and d) temporal filtering to exploit time redundancy by means of a Hidden Markov Model (HMM). Four dimensionality reduction techniques and four clustering algorithms were studied. In order to cope with class imbalance in the dataset, a custom performance metric was defined to aggregate recognition accuracy, precision and recall. The best scheme, which comprised a projection through Linear Discriminant Analysis (LDA) and k-means clustering, was evaluated in leave-one-subject-out cross-validation; notably outperforming the standard industry procedures for PA intensity classification: score 84.65 %, versus up to 63.60 %. Errors tended to be brief and to appear around transients. The application of ML techniques for pattern identification and temporal filtering allowed to merge accelerometry and HR data in a solid manner, and achieved markedly better recognition performances than the standard methods for PA intensity estimation.

  4. An integrated flow cytometry-based system for real-time, high sensitivity bacterial detection and identification.

    Directory of Open Access Journals (Sweden)

    Dan A Buzatu

    Full Text Available Foodborne illnesses occur in both industrialized and developing countries, and may be increasing due to rapidly evolving food production practices. Yet some primary tools used to assess food safety are decades, if not centuries, old. To improve the time to result for food safety assessment a sensitive flow cytometer based system to detect microbial contamination was developed. By eliminating background fluorescence and improving signal to noise the assays accurately measure bacterial load or specifically identify pathogens. These assays provide results in minutes or, if sensitivity to one cell in a complex matrix is required, after several hours enrichment. Conventional assessments of food safety require 48 to 56 hours. The assays described within are linear over 5 orders of magnitude with results identical to culture plates, and report live and dead microorganisms. This system offers a powerful approach to real-time assessment of food safety, useful for industry self-monitoring and regulatory inspection.

  5. Automatic detection of abnormalities in mammograms

    International Nuclear Information System (INIS)

    Suhail, Zobia; Sarwar, Mansoor; Murtaza, Kashif

    2015-01-01

    In recent years, an increased interest has been seen in the area of medical image processing and, as a consequence, Computer Aided Diagnostic (CAD) systems. The basic purpose of CAD systems is to assist doctors in the process of diagnosis. CAD systems, however, are quite expensive, especially, in most of the developing countries. Our focus is on developing a low-cost CAD system. Today, most of the CAD systems regarding mammogram classification target automatic detection of calcification and abnormal mass. Calcification normally indicates an early symptom of breast cancer if it appears as a small size bright spot in a mammogram image. Based on the observation that calcification appears as small bright spots on a mammogram image, we propose a new scale-specific blob detection technique in which the scale is selected through supervised learning. By computing energy for each pixel at two different scales, a new feature “Ratio Energy” is introduced for efficient blob detection. Due to the imposed simplicity of the feature and post processing, the running time of our algorithm is linear with respect to image size. Two major types of calcification, microcalcification and macrocalcification have been identified and highlighted by drawing a circular boundary outside the area that contains calcification. Results are quite visible and satisfactory, and the radiologists can easily view results through the final detected boundary. CAD systems are designed to help radiologists in verifying their diagnostics. A new way of identifying calcification is proposed based on the property that microcalcification is small in size and appears in clusters. Results are quite visible and encouraging, and can assist radiologists in early detection of breast cancer

  6. Automated Feature Set Selection and Its Application to MCC Identification in Digital Mammograms for Breast Cancer Detection

    Directory of Open Access Journals (Sweden)

    Wu-Chung Shen

    2013-04-01

    Full Text Available We propose a fully automated algorithm that is able to select a discriminative feature set from a training database via sequential forward selection (SFS, sequential backward selection (SBS, and F-score methods. We applied this scheme to microcalcifications cluster (MCC detection in digital mammograms for early breast cancer detection. The system was able to select features fully automatically, regardless of the input training mammograms used. We tested the proposed scheme using a database of 111 clinical mammograms containing 1,050 microcalcifications (MCs. The accuracy of the system was examined via a free response receiver operating characteristic (fROC curve of the test dataset. The system performance for MC identifications was Az = 0.9897, the sensitivity was 92%, and 0.65 false positives (FPs were generated per image for MCC detection.

  7. Raft and floating radio frequency identification (RFID) antenna systems for detecting and estimating abundance of PIT-tagged fish in rivers

    Science.gov (United States)

    Fetherman, Eric R.; Avila, Brian W.; Winkelman, Dana L.

    2016-01-01

    Portable radio frequency identification (RFID) PIT tag antenna systems are increasingly being used in studies examining aquatic animal movement, survival, and habitat use, and their design flexibility permits application in a wide variety of settings. We describe the construction, use, and performance of two portable floating RFID PIT tag antenna systems designed to detect fish that were unavailable for recapture using stationary antennas or electrofishing. A raft antenna system was designed to detect and locate PIT-tagged fish in relatively long (i.e., ≥10 km) river reaches, and consisted of two antennas: (1) a horizontal antenna (4 × 1.2 m) installed on the bottom of the raft and used to detect fish in shallower river reaches (<1 m), and (2) a vertical antenna (2.7 × 1.2 m) for detecting fish in deeper pools (≥1 m). Detection distances of the horizontal antenna were between 0.7 and 1.0 m, and detection probability was 0.32 ± 0.02 (mean ± SE) in a field test using rocks marked with 32-mm PIT tags. Detection probability of PIT-tagged fish in the Cache la Poudre River, Colorado, using the raft antenna system, which covered 21% of the wetted area, was 0.14 ± 0.14. A shore-deployed floating antenna (14.6 × 0.6 m), which covered 100% of the wetted area, was designed for use by two operators for detecting and locating PIT-tagged fish in shorter (i.e., <2 km) river reaches. Detection distances of the shore-deployed floating antenna were between 0.7 and 0.8 m, and detection probabilities during field deployment in the St. Vrain River exceeded 0.52. The shore-deployed floating antenna was also used to estimate abundance of PIT-tagged fish. Results suggest that the shore-deployed floating antenna could be used as an alternative to estimating abundance using traditional sampling methods such as electrofishing.

  8. Architecture Design of the Vehicle Tracking System Based on RFID

    OpenAIRE

    Jianxin Deng

    2013-01-01

    Vehicle tracking plays more important roles in modern transportation and logistics operation. This paper deals with a new approach to track vehicles based on RFID (Radio Frequency Identification) technology. The vehicle tracking system is designed overallly  supported by Axiomatic Design theory.The basic steps of vehicle tracking based on RFID are developed and a six-layered architecture for the vehicle tracking system integrating databases, RFID tags, RFID readers, data centers, networks an...

  9. Vehicle usage verification system

    NARCIS (Netherlands)

    Scanlon, W.G.; McQuiston, Jonathan; Cotton, Simon L.

    2012-01-01

    EN)A computer-implemented system for verifying vehicle usage comprising a server capable of communication with a plurality of clients across a communications network. Each client is provided in a respective vehicle and with a respective global positioning system (GPS) by which the client can

  10. Electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, Susan R.

    1995-01-01

    An antiskid braking and traction control system for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes one or more sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensors and determining if regenerative antiskid braking control, requiring hydrualic braking control, or requiring traction control are required. The processor then employs a control strategy based on the determined vehicle state and provides command signals to a motor controller to control the operation of the electric traction motor and to a brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative antiskid braking control, hydraulic braking control, and traction control.

  11. Inertial aided cycle slip detection and identification for integrated PPP GPS and INS.

    Science.gov (United States)

    Du, Shuang; Gao, Yang

    2012-10-25

    The recently developed integrated Precise Point Positioning (PPP) GPS/INS system can be useful to many applications, such as UAV navigation systems, land vehicle/machine automation and mobile mapping systems. Since carrier phase measurements are the primary observables in PPP GPS, cycle slips, which often occur due to high dynamics, signal obstructions and low satellite elevation, must be detected and repaired in order to ensure the navigation performance. In this research, a new algorithm of cycle slip detection and identification has been developed. With the aiding from INS, the proposed method jointly uses WL and EWL phase combinations to uniquely determine cycle slips in the L1 and L2 frequencies. To verify the efficiency of the algorithm, both tactical-grade and consumer-grade IMUs are tested by using a real dataset collected from two field tests. The results indicate that the proposed algorithm can efficiently detect and identify the cycle slips and subsequently improve the navigation performance of the integrated system.

  12. Inertial Aided Cycle Slip Detection and Identification for Integrated PPP GPS and INS

    Directory of Open Access Journals (Sweden)

    Yang Gao

    2012-10-01

    Full Text Available The recently developed integrated Precise Point Positioning (PPP GPS/INS system can be useful to many applications, such as UAV navigation systems, land vehicle/machine automation and mobile mapping systems. Since carrier phase measurements are the primary observables in PPP GPS, cycle slips, which often occur due to high dynamics, signal obstructions and low satellite elevation, must be detected and repaired in order to ensure the navigation performance. In this research, a new algorithm of cycle slip detection and identification has been developed. With the aiding from INS, the proposed method jointly uses WL and EWL phase combinations to uniquely determine cycle slips in the L1 and L2 frequencies. To verify the efficiency of the algorithm, both tactical-grade and consumer-grade IMUs are tested by using a real dataset collected from two field tests. The results indicate that the proposed algorithm can efficiently detect and identify the cycle slips and subsequently improve the navigation performance of the integrated system.

  13. An Automatic Detection Method of Nanocomposite Film Element Based on GLCM and Adaboost M1

    Directory of Open Access Journals (Sweden)

    Hai Guo

    2015-01-01

    Full Text Available An automatic detection model adopting pattern recognition technology is proposed in this paper; it can realize the measurement to the element of nanocomposite film. The features of gray level cooccurrence matrix (GLCM can be extracted from different types of surface morphology images of film; after that, the dimension reduction of film can be handled by principal component analysis (PCA. So it is possible to identify the element of film according to the Adaboost M1 algorithm of a strong classifier with ten decision tree classifiers. The experimental result shows that this model is superior to the ones of SVM (support vector machine, NN and BayesNet. The method proposed can be widely applied to the automatic detection of not only nanocomposite film element but also other nanocomposite material elements.

  14. Automatic Detection of Cow’s Oestrus in Audio Surveillance System

    Directory of Open Access Journals (Sweden)

    Y. Chung

    2013-07-01

    Full Text Available Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea. In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone and accurately (over 94% accuracy, either as a standalone solution or to complement known methods.

  15. Automatic Detection and Classification of Diabetic Retinopathy Using Retinal Fundus Images

    OpenAIRE

    A. Biran; P. Sobhe Bidari; A. Almazroe V. Lakshminarayanan; K. Raahemifar

    2016-01-01

    Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLA...

  16. Object-based detection of vehicles using combined optical and elevation data

    Science.gov (United States)

    Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

    2018-02-01

    The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consists of three consecutive stages: candidate identification, classification, and single vehicle extraction. Unlike in most previous approaches, fusion of both data sources is strongly pursued at all stages. While the first stage utilizes the fact that most man-made objects are rectangular in shape, the second and third stages employ machine learning techniques combined with specific features. The stages are designed to handle multiple sensor input, which results in a significant improvement. A detailed evaluation shows the benefits of our workflow, which includes hand-tailored features; even in comparison with classification approaches based on Convolutional Neural Networks, which are state of the art in computer vision, we could obtain a comparable or superior performance (F1 score of 0.96-0.94).

  17. Potato Operation: automatic detection of potato diseases

    Science.gov (United States)

    Lefebvre, Marc; Zimmerman, Thierry; Baur, Charles; Guegerli, Paul; Pun, Thierry

    1995-01-01

    The Potato Operation is a collaborative, multidisciplinary project in the domain of destructive testing of agricultural products. It aims at automatizing pulp sampling of potatoes in order to detect possible viral diseases. Such viruses can decrease fields productivity by a factor of up to ten. A machine, composed of three conveyor belts, a vision system, a robotic arm and controlled by a PC has been built. Potatoes are brought one by one from a bulk to the vision system, where they are seized by a rotating holding device. The sprouts, where the viral activity is maximum, are then detected by an active vision process operating on multiple views. The 3D coordinates of the sampling point are communicated to the robot arm holding a drill. Some flesh is then sampled by the drill, then deposited into an Elisa plate. After sampling, the robot arm washes the drill in order to prevent any contamination. The PC computer simultaneously controls these processes, the conveying of the potatoes, the vision algorithms and the sampling procedure. The master process, that is the vision procedure, makes use of three methods to achieve the sprouts detection. A profile analysis first locates the sprouts as protuberances. Two frontal analyses, respectively based on fluorescence and local variance, confirm the previous detection and provide the 3D coordinate of the sampling zone. The other two processes work by interruption of the master process.

  18. Nasal pressure recordings for automatic snoring detection.

    Science.gov (United States)

    Lee, Hyo-Ki; Kim, Hojoong; Lee, Kyoung-Joung

    2015-11-01

    This study presents a rule-based method for automated, real-time snoring detection using nasal pressure recordings during overnight sleep. Although nasal pressure recordings provide information regarding nocturnal breathing abnormalities in a polysomnography (PSG) study or continuous positive airway pressure (CPAP) system, an objective assessment of snoring detection using these nasal pressure recordings has not yet been reported in the literature. Nasal pressure recordings were obtained from 55 patients with obstructive sleep apnea. The PSG data were also recorded simultaneously to evaluate the proposed method. This rule-based method for automatic, real-time snoring detection employed preprocessing, short-time energy and the central difference method. Using this methodology, a sensitivity of 85.4% and a positive predictive value of 92.0% were achieved in all patients. Therefore, we concluded that the proposed method is a simple, portable and cost-effective tool for real-time snoring detection in PSG and CPAP systems that does not require acoustic analysis using a microphone.

  19. Radar image processing of real aperture SLAR data for the detection and identification of iceberg and ship targets

    Science.gov (United States)

    Marthaler, J. G.; Heighway, J. E.

    1979-01-01

    An iceberg detection and identification system consisting of a moderate resolution Side Looking Airborne Radar (SLAR) interfaced with a Radar Image Processor (RIP) based on a ROLM 1664 computer with a 32K core memory updatable to 64K is described. The system can be operated in high- or low-resolution sampling modes. Specifically designed algorithms are applied to digitized signal returns to provide automatic target detection and location, geometrically correct video image display and data recording. The real aperture Motorola AN/APS-94D SLAR operates in the X-band and is tunable between 9.10 and 9.40 GHz; its output power is 45 kW peak with a pulse repetition rate of 750 pulses per hour. Schematic diagrams of the system are provided, together with preliminary test data.

  20. Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region

    Science.gov (United States)

    Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir

    2008-03-01

    Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.

  1. Detection and intelligent systems for homeland security

    CERN Document Server

    Voeller, John G

    2014-01-01

    Detection and Intelligent Systems for Homeland Security features articles from the Wiley Handbook of Science and Technology for Homeland Security covering advanced technology for image and video interpretation systems used for surveillance, which help in solving such problems as identifying faces from live streaming or stored videos. Biometrics for human identification, including eye retinas and irises, and facial patterns are also presented. The book then provides information on sensors for detection of explosive and radioactive materials and methods for sensing chemical

  2. Privacy Impact Assessment for the Light-Duty In-Use Vehicle Testing Program Information System

    Science.gov (United States)

    EPA's Light-Duty In-Use Vehicle Testing Program Information System contains car owner names, addresses, vehicle identification numbers, etc. The EPA uses this information to recruit and test vehicles for emissions standards compliance.

  3. Label-free detection and identification of waterborne parasites using a microfluidic multi-angle laser scattering system

    Science.gov (United States)

    Huang, Wei; Yang, Limei; Lei, Lei; Li, Feng

    2017-10-01

    A microfluidic-based multi-angle laser scattering (MALS) system capable of acquiring scattering patterns of a single particle is designed and demonstrated. The system includes a sheathless nozzle microfluidic glass chip, and an on-chip MALS unit being in alignment with the nozzle exit in the chip. The size and relative refractive indices (RI) of polystyrene (PS) microspheres were deduced with accuracies of 60 nm and 0.002 by comparing the experimental scattering patterns with theoretical ones. We measured scattering patterns of waterborne parasites i.e., Cryptosporidium parvum (C.parvum) and Giardia lamblia (G. lamblia), and some other representative species suspended in deionized water at a maximum flow rate of 12 μL/min, and a maximum of 3000 waterborne parasites can be identified within one minute with a mean accuracy higher than 96% by classification of distinctive scattering patterns using a support-vector-machine (SVM) algorithm. The system provides a promising tool for label-free detection of waterborne parasites and other biological contaminants.

  4. Automatic Smoker Detection from Telephone Speech Signals

    DEFF Research Database (Denmark)

    Alavijeh, Amir Hossein Poorjam; Hesaraki, Soheila; Safavi, Saeid

    2017-01-01

    This paper proposes an automatic smoking habit detection from spontaneous telephone speech signals. In this method, each utterance is modeled using i-vector and non-negative factor analysis (NFA) frameworks, which yield low-dimensional representation of utterances by applying factor analysis on G...

  5. Compensation of Cable Voltage Drops and Automatic Identification of Cable Parameters in 400 Hz Ground Power Units

    DEFF Research Database (Denmark)

    Borup, Uffe; Nielsen, Bo Vork; Blaabjerg, Frede

    2004-01-01

    self and mutual impedance parameters. The model predicts the voltage drop at both symmetrical and unbalanced loads. In order to determine the cable model parameters an automatic identification concept is derived. The concept is tested in full scale on a 90-kVA 400-Hz GPU with two different cables....... It is concluded that the performance is significantly improved both with symmetrical and unsymmetrical cables and with balanced and unbalanced loads....

  6. Automatic Detection of the Uterus and Fallopian Tube Junctions in Laparoscopic Images.

    Science.gov (United States)

    Prokopetc, Kristina; Collins, Toby; Bartoli, Adrien

    2015-01-01

    We present a method for the automatic detection of the uterus and the Fallopian tube/Uterus junctions (FU-junctions) in a monocular laparoscopic image. The main application is to perform automatic registration and fusion between preoperative radiological images of the uterus and laparoscopic images for image-guided surgery. In the broader context of computer assisted intervention, our method is the first that detects an organ and registration landmarks from laparoscopic images without manual input. Our detection problem is challenging because of the large inter-patient anatomical variability and pathologies such as uterine fibroids. We solve the problem using learned contextual geometric constraints that statistically model the positions and orientations of the FU-junctions relative to the uterus' body. We train the uterus detector using a modern part-based approach and the FU-junction detector using junction-specific context-sensitive features. We have trained and tested on a database of 95 uterus images with cross validation, and successfully detected the uterus with Recall = 0.95 and average Number of False Positives per Image (NFPI) = 0.21, and FU-junctions with Recall = 0.80 and NFPI = 0.50. Our experimental results show that the contextual constraints are fundamental to achieve high quality detection.

  7. Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID) of Penguins.

    Science.gov (United States)

    Afanasyev, Vsevolod; Buldyrev, Sergey V; Dunn, Michael J; Robst, Jeremy; Preston, Mark; Bremner, Steve F; Briggs, Dirk R; Brown, Ruth; Adlard, Stacey; Peat, Helen J

    2015-01-01

    A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus) at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

  8. Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID of Penguins.

    Directory of Open Access Journals (Sweden)

    Vsevolod Afanasyev

    Full Text Available A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

  9. Vehicle barrier systems

    International Nuclear Information System (INIS)

    Sena, P.A.

    1986-01-01

    The ground vehicle is one of the most effective tools available to an adversary force. Vehicles can be used to penetrate many types of perimeter barriers, transport equipment and personnel rapidly over long distances, and deliver large amounts of explosives directly to facilities in suicide missions. The function of a vehicle barrier system is to detain or disable a defined threat vehicle at a selected distance from a protected facility. Numerous facilities are installing, or planning to install, vehicle barrier systems and many of these facilities are requesting guidance to do so adequately. Therefore, vehicle barriers are being evaluated to determine their stopping capabilities so that systems can be designed that are both balanced and capable of providing a desired degree of protection. Equally important, many of the considerations that should be taken into account when establishing a vehicle barrier system have been identified. These considerations which pertain to site preparation, barrier selection, system integration and operation, and vehicle/barrier interaction, are discussed in this paper

  10. Application of Image Processing and Three-Dimensional Data Reconstruction Algorithm Based on Traffic Video in Vehicle Component Detection

    Directory of Open Access Journals (Sweden)

    Gang Li

    2017-01-01

    Full Text Available Vehicle detection is one of the important technologies in intelligent video surveillance systems. Owing to the perspective projection imaging principle of cameras, traditional two-dimensional (2D images usually distort the size and shape of vehicles. In order to solve these problems, the traffic scene calibration and inverse projection construction methods are used to project the three-dimensional (3D information onto the 2D images. In addition, a vehicle target can be characterized by several components, and thus vehicle detection can be fulfilled based on the combination of these components. The key characteristics of vehicle targets are distinct during a single day; for example, the headlight brightness is more significant at night, while the vehicle taillight and license plate color are much more prominent in the daytime. In this paper, by using the background subtraction method and Gaussian mixture model, we can realize the accurate detection of target lights at night. In the daytime, however, the detection of the license plate and taillight of a vehicle can be fulfilled by exploiting the background subtraction method and the Markov random field, based on the spatial geometry relation between the corresponding components. Further, by utilizing Kalman filters to follow the vehicle tracks, detection accuracy can be further improved. Finally, experiment results demonstrate the effectiveness of the proposed methods.

  11. CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal-neutron-activated samples

    International Nuclear Information System (INIS)

    Giannini, M.; Oliva, P.R.; Ramorino, M.C.

    1979-01-01

    A computer code that automatically analyzes gamma-ray spectra obtained with Ge(Li) detectors is described. The program contains such features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification, and calculation of masses and errors. Finally, the results obtained with this computer code for a lunar sample are reported and briefly discussed

  12. Accurate Localization of Communicant Vehicles using GPS and Vision Systems

    Directory of Open Access Journals (Sweden)

    Georges CHALLITA

    2009-07-01

    Full Text Available The new generation of ADAS systems based on cooperation between vehicles can offer serious perspectives to the road security. The inter-vehicle cooperation is made possible thanks to the revolution in the wireless mobile ad hoc network. In this paper, we will develop a system that will minimize the imprecision of the GPS used to car tracking, based on the data given by the GPS which means the coordinates and speed in addition to the use of the vision data that will be collected from the loading system in the vehicle (camera and processor. Localization information can be exchanged between the vehicles through a wireless communication device. The creation of the system must adopt the Monte Carlo Method or what we call a particle filter for the treatment of the GPS data and vision data. An experimental study of this system is performed on our fleet of experimental communicating vehicles.

  13. Automatic detection of osteoporotic vertebral fractures in routine thoracic and abdominal MDCT

    Energy Technology Data Exchange (ETDEWEB)

    Baum, Thomas; Dobritz, Martin; Rummeny, Ernst J.; Noel, Peter B. [Technische Universitaet Muenchen, Institut fuer Radiologie, Klinikum rechts der Isar, Muenchen (Germany); Bauer, Jan S. [Technische Universitaet Muenchen, Abteilung fuer Neuroradiologie, Klinikum rechts der Isar, Muenchen (Germany); Klinder, Tobias; Lorenz, Cristian [Philips Research Laboratories, Hamburg (Germany)

    2014-04-15

    To develop a prototype algorithm for automatic spine segmentation in MDCT images and use it to automatically detect osteoporotic vertebral fractures. Cross-sectional routine thoracic and abdominal MDCT images of 71 patients including 8 males and 9 females with 25 osteoporotic vertebral fractures and longitudinal MDCT images of 9 patients with 18 incidental fractures in the follow-up MDCT were retrospectively selected. The spine segmentation algorithm localised and identified the vertebrae T5-L5. Each vertebra was automatically segmented by using corresponding vertebra surface shape models that were adapted to the original images. Anterior, middle, and posterior height of each vertebra was automatically determined; the anterior-posterior ratio (APR) and middle-posterior ratio (MPR) were computed. As the gold standard, radiologists graded vertebral fractures from T5 to L5 according to the Genant classification in consensus. Using ROC analysis to differentiate vertebrae without versus with prevalent fracture, AUC values of 0.84 and 0.83 were obtained for APR and MPR, respectively (p < 0.001). Longitudinal changes in APR and MPR were significantly different between vertebrae without versus with incidental fracture (ΔAPR: -8.5 % ± 8.6 % versus -1.6 % ± 4.2 %, p = 0.002; ΔMPR: -11.4 % ± 7.7 % versus -1.2 % ± 1.6 %, p < 0.001). This prototype algorithm may support radiologists in reporting currently underdiagnosed osteoporotic vertebral fractures so that appropriate therapy can be initiated. circle This spine segmentation algorithm automatically localised, identified, and segmented the vertebrae in MDCT images. (orig.)

  14. Microarrays for Universal Detection and Identification of Phytoplasmas

    DEFF Research Database (Denmark)

    Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

    2013-01-01

    Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...

  15. Identification for automotive systems

    CERN Document Server

    Hjalmarsson, Håkan; Re, Luigi

    2012-01-01

    Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.

  16. Automatic extraction and identification of users' responses in Facebook medical quizzes.

    Science.gov (United States)

    Rodríguez-González, Alejandro; Menasalvas Ruiz, Ernestina; Mayer Pujadas, Miguel A

    2016-04-01

    In the last few years the use of social media in medicine has grown exponentially, providing a new area of research based on the analysis and use of Web 2.0 capabilities. In addition, the use of social media in medical education is a subject of particular interest which has been addressed in several studies. One example of this application is the medical quizzes of The New England Journal of Medicine (NEJM) that regularly publishes a set of questions through their Facebook timeline. We present an approach for the automatic extraction of medical quizzes and their associated answers on a Facebook platform by means of a set of computer-based methods and algorithms. We have developed a tool for the extraction and analysis of medical quizzes stored on Facebook timeline at the NEJM Facebook page, based on a set of computer-based methods and algorithms using Java. The system is divided into two main modules: Crawler and Data retrieval. The system was launched on December 31, 2014 and crawled through a total of 3004 valid posts and 200,081 valid comments. The first post was dated on July 23, 2009 and the last one on December 30, 2014. 285 quizzes were analyzed with 32,780 different users providing answers to the aforementioned quizzes. Of the 285 quizzes, patterns were found in 261 (91.58%). From these 261 quizzes where trends were found, we saw that users follow trends of incorrect answers in 13 quizzes and trends of correct answers in 248. This tool is capable of automatically identifying the correct and wrong answers to a quiz provided on Facebook posts in a text format to a quiz, with a small rate of false negative cases and this approach could be applicable to the extraction and analysis of other sources after including some adaptations of the information on the Internet. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. 14 CFR 27.672 - Stability augmentation, automatic, and power-operated systems.

    Science.gov (United States)

    2010-01-01

    ... power-operated systems. 27.672 Section 27.672 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Construction Control Systems § 27.672 Stability augmentation, automatic, and power-operated systems. If the functioning of stability augmentation or other automatic or power-operated systems is necessary to show...

  18. 14 CFR 29.672 - Stability augmentation, automatic, and power-operated systems.

    Science.gov (United States)

    2010-01-01

    ... power-operated systems. 29.672 Section 29.672 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Construction Control Systems § 29.672 Stability augmentation, automatic, and power-operated systems. If the functioning of stability augmentation or other automatic or power-operated system is necessary to show...

  19. Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Macam S. Dattathreya

    2012-01-01

    Full Text Available This paper presents a novel fuzzy deterministic noncontroller type (FDNCT system and an FDNCT inference algorithm (FIA. The FDNCT uses fuzzy inputs and produces a deterministic non-fuzzy output. The FDNCT is an extension and alternative for the existing fuzzy singleton inference algorithm. The research described in this paper applies FDNCT to build an architecture for an intelligent system to detect and to eliminate potential fires in the engine and battery compartments of a hybrid electric vehicle. The fuzzy inputs consist of sensor data from the engine and battery compartments, namely, temperature, moisture, and voltage and current of the battery. The system synthesizes the data and detects potential fires, takes actions for eliminating the hazard, and notifies the passengers about the potential fire using an audible alarm. This paper also presents the computer simulation results of the comparison between the FIA and singleton inference algorithms for detecting potential fires and determining the actions for eliminating them.

  20. Unmanned Aerial Vehicle Mission Planning for Combined Iceberg Detection and Tracking Missions

    OpenAIRE

    Langeveld, Sindre Matthijs

    2017-01-01

    In this master thesis, iceberg detection and tracking by Unmanned Aerial Vehicles has been studied. Currently, most systems for ice management separate these two tasks. However, combining these tasks into a single algorithm might only require one UAV, which could reduce the operating costs. In this thesis, we propose a combined search and track algorithm and investigate its performance and viability. To test the algorithm, a simulator has been developed. A Kalman filter has been used to ...

  1. Depth Level Control System using Peripheral Interface Controller for Underwater Vehicle

    Directory of Open Access Journals (Sweden)

    Muhamad Fadli Ghani

    2013-01-01

    Full Text Available This research explained on a design and development of an Automatic Depth Control System for underwater vehicle. Definition of underwater vehicle is a robotic sub-sea that is a part of the emerging field of autonomous and unmanned vehicles. This project shows the implementation’s development of an Automatic Depth Control System on a test prototyping vehicle especially involved small-scale and low cost sub-sea robots. The Automatic Depth Control System assembled with mechanical system and module of electronic system for development of a controller.

  2. Simplified bionic solutions: a simple bio-inspired vehicle collision detection system.

    Science.gov (United States)

    Hartbauer, Manfred

    2017-02-15

    Modern cars are equipped with both active and passive sensor systems that can detect potential collisions. In contrast, locusts avoid collisions solely by responding to certain visual cues that are associated with object looming. In neurophysiological experiments, I investigated the possibility that the 'collision-detector neurons' of locusts respond to impending collisions in films recorded with dashboard cameras of fast driving cars. In a complementary modelling approach, I developed a simple algorithm to reproduce the neuronal response that was recorded during object approach. Instead of applying elaborate algorithms that factored in object recognition and optic flow discrimination, I tested the hypothesis that motion detection restricted to a 'danger zone', in which frontal collisions on the motorways are most likely, is sufficient to estimate the risk of a collision. Furthermore, I investigated whether local motion vectors, obtained from the differential excitation of simulated direction-selective networks, could be used to predict evasive steering maneuvers and prevent undesired responses to motion artifacts. The results of the study demonstrate that the risk of impending collisions in real traffic scenes is mirrored in the excitation of the collision-detecting neuron (DCMD) of locusts. The modelling approach was able to reproduce this neuronal response even when the vehicle was driving at high speeds and image resolution was low (about 200  ×  100 pixels). Furthermore, evasive maneuvers that involved changing the steering direction and steering force could be planned by comparing the differences in the overall excitation levels of the simulated right and left direction-selective networks. Additionally, it was possible to suppress undesired responses of the algorithm to translatory movements, camera shake and ground shadows by evaluating local motion vectors. These estimated collision risk values and evasive steering vectors could be used as input

  3. A Novel Vehicle Stationary Detection Utilizing Map Matching and IMU Sensors

    Directory of Open Access Journals (Sweden)

    Md. Syedul Amin

    2014-01-01

    Full Text Available Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS built from the inertial measurement unit (IMU sensors is proposed. Besides, the map matching (MM algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.

  4. A novel vehicle stationary detection utilizing map matching and IMU sensors.

    Science.gov (United States)

    Amin, Md Syedul; Reaz, Mamun Bin Ibne; Nasir, Salwa Sheikh; Bhuiyan, Mohammad Arif Sobhan; Ali, Mohd Alauddin Mohd

    2014-01-01

    Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.

  5. Automatic Parking Based on a Bird's Eye View Vision System

    Directory of Open Access Journals (Sweden)

    Chunxiang Wang

    2014-03-01

    Full Text Available This paper aims at realizing an automatic parking method through a bird's eye view vision system. With this method, vehicles can make robust and real-time detection and recognition of parking spaces. During parking process, the omnidirectional information of the environment can be obtained by using four on-board fisheye cameras around the vehicle, which are the main part of the bird's eye view vision system. In order to achieve this purpose, a polynomial fisheye distortion model is firstly used for camera calibration. An image mosaicking method based on the Levenberg-Marquardt algorithm is used to combine four individual images from fisheye cameras into one omnidirectional bird's eye view image. Secondly, features of the parking spaces are extracted with a Radon transform based method. Finally, double circular trajectory planning and a preview control strategy are utilized to realize autonomous parking. Through experimental analysis, we can see that the proposed method can get effective and robust real-time results in both parking space recognition and automatic parking.

  6. CURRENT STATE ANALYSIS OF AUTOMATIC BLOCK SYSTEM DEVICES, METHODS OF ITS SERVICE AND MONITORING

    Directory of Open Access Journals (Sweden)

    A. M. Beznarytnyy

    2014-01-01

    Full Text Available Purpose. Development of formalized description of automatic block system of numerical code based on the analysis of characteristic failures of automatic block system and procedure of its maintenance. Methodology. For this research a theoretical and analytical methods have been used. Findings. Typical failures of the automatic block systems were analyzed, as well as basic reasons of failure occur were found out. It was determined that majority of failures occurs due to defects of the maintenance system. Advantages and disadvantages of the current service technology of automatic block system were analyzed. Works that can be automatized by means of technical diagnostics were found out. Formal description of the numerical code of automatic block system as a graph in the state space of the system was carried out. Originality. The state graph of the numerical code of automatic block system that takes into account gradual transition from the serviceable condition to the loss of efficiency was offered. That allows selecting diagnostic information according to attributes and increasing the effectiveness of recovery operations in the case of a malfunction. Practical value. The obtained results of analysis and proposed the state graph can be used as the basis for the development of new means of diagnosing devices for automatic block system, which in turn will improve the efficiency and service of automatic block system devices in general.

  7. Automatic fishing net detection and recognition based on optical gated viewing for underwater obstacle avoidance

    Science.gov (United States)

    Liu, Xiaoquan; Wang, Xinwei; Ren, Pengdao; Cao, Yinan; Zhou, Yan; Liu, Yuliang

    2017-08-01

    An automatic fishing net detection and recognition method for underwater obstacle avoidance is proposed. In the method, optical gated viewing technology is utilized to obtain high-resolution fishing net images and extend detection distance by suppressing water backscattering and background noise. The fishing net recognition is based on the proposed histograms of slope lines (HSLs) descriptors plus a support vector machine classifier. The extraction of HSL descriptors includes five steps of contrast-limited adaptive histogram equalization, the Gaussian low-pass filtering, the Canny detection, the Hough transform, and weighted vote. In the proof experiments, the detection distance of the fishing net reaches 5.7 attenuation length and the recognition accuracy reaches 93.79%.

  8. Structural Acoustic UXO Detection and Identification in Marine Environments

    Science.gov (United States)

    2016-05-01

    high performance structural acoustic (SA) feature-based underwater sonar technology that can detect and localize buried (and proud) targets and...MR2103), we demonstrated the structural acoustic technology with an autonomous underwater vehicle (AUV) - based SA sonar successfully detecting UXO...We examined the acoustic color maps visually for the presence of a frequency/x position (aspect angle) feature that we had seen earlier in laboratory

  9. Behaviour-based anomaly detection of cyber-physical attacks on a robotic vehicle

    OpenAIRE

    Bezemskij, Anatolij; Loukas, George; Anthony, Richard J.; Gan, Diane

    2017-01-01

    Security is one of the key challenges in cyber-physical systems, because by their nature, any cyber attack against them can have physical repercussions. This is a critical issue for autonomous vehicles; if compromised in terms of their communications or computation they can cause considerable physical damage due to their mobility. Our aim here is to facilitate the automatic detection of cyber attacks on a robotic vehicle. For this purpose, we have developed a detection mechanism, which monito...

  10. Method and system for detecting explosives

    Science.gov (United States)

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

    2009-03-10

    A method of detecting explosives in a vehicle includes providing a first rack on one side of the vehicle, the rack including a neutron generator and a plurality of gamma ray detectors; providing a second rack on another side of the vehicle, the second rack including a neutron generator and a plurality of gamma ray detectors; providing a control system, remote from the first and second racks, coupled to the neutron generators and gamma ray detectors; using the control system, causing the neutron generators to generate neutrons; and performing gamma ray spectroscopy on spectra read by the gamma ray detectors to look for a signature indicative of presence of an explosive. Various apparatus and other methods are also provided.

  11. Automatic metal parts inspection: Use of thermographic images and anomaly detection algorithms

    Science.gov (United States)

    Benmoussat, M. S.; Guillaume, M.; Caulier, Y.; Spinnler, K.

    2013-11-01

    A fully-automatic approach based on the use of induction thermography and detection algorithms is proposed to inspect industrial metallic parts containing different surface and sub-surface anomalies such as open cracks, open and closed notches with different sizes and depths. A practical experimental setup is developed, where lock-in and pulsed thermography (LT and PT, respectively) techniques are used to establish a dataset of thermal images for three different mockups. Data cubes are constructed by stacking up the temporal sequence of thermogram images. After the reduction of the data space dimension by means of denoising and dimensionality reduction methods; anomaly detection algorithms are applied on the reduced data cubes. The dimensions of the reduced data spaces are automatically calculated with arbitrary criterion. The results show that, when reduced data cubes are used, the anomaly detection algorithms originally developed for hyperspectral data, the well-known Reed and Xiaoli Yu detector (RX) and the regularized adaptive RX (RARX), give good detection performances for both surface and sub-surface defects in a non-supervised way.

  12. Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

    OpenAIRE

    Hyungchul Yoon; Vedhus Hoskere; Jong-Woong Park; Billie F. Spencer

    2017-01-01

    Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc.) are often difficult to access, being constructed over rivers, roads, or other obstacles. T...

  13. Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

    Directory of Open Access Journals (Sweden)

    Malik M. Naeem Mannan

    2016-02-01

    Full Text Available Contamination of eye movement and blink artifacts in Electroencephalogram (EEG recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI. In this paper, we proposed an automatic framework based on independent component analysis (ICA and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity relate