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Sample records for automatic vehicle detection and identification systems

  1. Automatically Identification and Classification of Moving Vehicles at Night

    Directory of Open Access Journals (Sweden)

    Atena Khodarahmi

    2012-07-01

    Full Text Available Todays moving object detection plays an important role in computer vision filed. Although a lot of moving objects detection methods has been proposed but monitoring at nights is still a challenging topic. In this paper, a robust algorithm is proposed for automatic detection moving vehicles at night or in environments with low level of light which has quality problems. In this algorithm, first preprocessing steps were conducted. Then all of vehicles in frame identify and classify according their type. Finally, the moving vehicles detected. The results demonstrate that the proposed algorithm significantly outperforms existing algorithm for the detecting and classification of moving vehicles at night.

  2. A Wireless Framework for Lecturers' Attendance System with Automatic Vehicle Identification (AVI Technology

    Directory of Open Access Journals (Sweden)

    Emammer Khamis Shafter

    2015-10-01

    Full Text Available Automatic Vehicle Identification (AVI technology is one type of Radio Frequency Identification (RFID method which can be used to significantly improve the efficiency of lecturers' attendance system. It provides the capability of automatic data capture for attendance records using mobile device equipped in users’ vehicle. The intent of this article is to propose a framework for automatic lecturers' attendance system using AVI technology. The first objective of this work involves gathering of requirements for Automatic Lecturers' Attendance System and to represent them using UML diagrams. The second objective is to put forward a framework that will provide guidelines for developing the system. A prototype has also been created as a pilot project.

  3. Automatic Vehicle License Recognition Based on Video Vehicular Detection System

    Institute of Scientific and Technical Information of China (English)

    YANG Zhaoxuan; CHEN Yang; HE Yinghua; WU Jun

    2006-01-01

    Traditional methods of license character extraction cannot meet the requirements of recognition accuracy and speed rendered by the video vehicular detection system.Therefore, a license plate localization method based on multi-scale edge detection and a character segmentation algorithm based on Markov random field model is presented.Results of experiments demonstrate that the method yields more accurate license character extraction in contrast to traditional localization method based on edge detection by difference operator and character segmentation based on threshold.The accuracy increases from 90% to 94% under preferable illumination, while under poor condition, it increases more than 5%.When the two improved algorithms are used, the accuracy and speed of automatic license recognition meet the system's requirement even under the noisy circumstance or uneven illumination.

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

    OpenAIRE

    Ling-Yuan Hsu; Tsung-Lin Chen

    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 coefficie...

  5. 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.

  6. Automatic player detection and identification for sports entertainment applications

    NARCIS (Netherlands)

    Mahmood, Zahid; Ali, Tauseef; Khattak, Shadid; Hasan, Laiq; Khan, Samee U.

    2014-01-01

    In this paper, we develop an augmented reality sports broadcasting application for automatic detection, recognition of players during play, followed by display of personal information of players. The proposed application can be divided into four major steps. In first step, each player in the image i

  7. 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.

  8. An automatic identification and monitoring system for coral reef fish

    Science.gov (United States)

    Wilder, Joseph; Tonde, Chetan; Sundar, Ganesh; Huang, Ning; Barinov, Lev; Baxi, Jigesh; Bibby, James; Rapport, Andrew; Pavoni, Edward; Tsang, Serena; Garcia, Eri; Mateo, Felix; Lubansky, Tanya M.; Russell, Gareth J.

    2012-10-01

    To help gauge the health of coral reef ecosystems, we developed a prototype of an underwater camera module to automatically census reef fish populations. Recognition challenges include pose and lighting variations, complicated backgrounds, within-species color variations and within-family similarities among species. An open frame holds two cameras, LED lights, and two `background' panels in an L-shaped configuration. High-resolution cameras send sequences of 300 synchronized image pairs at 10 fps to an on-shore PC. Approximately 200 sequences containing fish were recorded at the New York Aquarium's Glover's Reef exhibit. These contained eight `common' species with 85-672 images, and eight `rare' species with 5-27 images that were grouped into an `unknown/rare' category for classification. Image pre-processing included background modeling and subtraction, and tracking of fish across frames for depth estimation, pose correction, scaling, and disambiguation of overlapping fish. Shape features were obtained from PCA analysis of perimeter points, color features from opponent color histograms, and `banding' features from DCT of vertical projections. Images were classified to species using feedforward neural networks arranged in a three-level hierarchy in which errors remaining after each level are targeted by networks in the level below. Networks were trained and tested on independent image sets. Overall accuracy of species-specific identifications typically exceeded 96% across multiple training runs. A seaworthy version of our system will allow for population censuses with high temporal resolution, and therefore improved statistical power to detect trends. A network of such devices could provide an `early warning system' for coral ecosystem collapse.

  9. 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...

  10. 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...

  11. 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...

  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. Development of optical automatic positioning and wafer defect detection system

    International Nuclear Information System (INIS)

    The data of a wafer with defects can provide engineers with very important information and clues to improve the yield rate and quality in manufacturing. This paper presents a microscope automatic positioning and wafer detection system with human-machine interface based on image processing and fuzzy inference algorithms. In the proposed system, a XY table is used to move the position of each die on 6 inch or 8 inch wafers. Then, a high-resolution CCD and one set of two-axis optical linear encoder are used to accurately measure the position on the wafer. Finally, the developed human-machine interface is used to display the current position of an actual wafer in order to complete automatic positioning, and a wafer map database can be created. In the process of defect detection, CCD is used for image processing, and during preprocessing, it is required to filter noise, acquire the defect characteristics, define the defective template, and then take the characteristic points of the defective template as the reference input for fuzzy inference. A high-accuracy optical automatic positioning and wafer defect detection system is thus constructed. This study focused on automatic detection of spots, scratches, and bruises, and attempted to reduce the time to detect defective die and improve the accuracy of determining the defects of semiconductor devices. (paper)

  14. 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.

  15. 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.

  16. Computer systems for automatic earthquake detection

    Science.gov (United States)

    Stewart, S.W.

    1974-01-01

    U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

  17. An efficient automatic firearm identification system

    Science.gov (United States)

    Chuan, Zun Liang; Liong, Choong-Yeun; Jemain, Abdul Aziz; Ghani, Nor Azura Md.

    2014-06-01

    Automatic firearm identification system (AFIS) is highly demanded in forensic ballistics to replace the traditional approach which uses comparison microscope and is relatively complex and time consuming. Thus, several AFIS have been developed for commercial and testing purposes. However, those AFIS are still unable to overcome some of the drawbacks of the traditional firearm identification approach. The goal of this study is to introduce another efficient and effective AFIS. A total of 747 firing pin impression images captured from five different pistols of same make and model are used to evaluate the proposed AFIS. It was demonstrated that the proposed AFIS is capable of producing firearm identification accuracy rate of over 95.0% with an execution time of less than 0.35 seconds per image.

  18. Chemical detection, identification, and analysis system

    International Nuclear Information System (INIS)

    The chemical detection, identification, and analysis system (CDIAS) has three major goals. The first is to display safety information regarding chemical environment before personnel entry. The second is to archive personnel exposure to the environment. Third, the system assists users in identifying the stage of a chemical process in progress and suggests safety precautions associated with that process. In addition to these major goals, the system must be sufficiently compact to provide transportability, and it must be extremely simple to use in order to keep user interaction at a minimum. The system created to meet these goals includes several pieces of hardware and the integration of four software packages. The hardware consists of a low-oxygen, carbon monoxide, explosives, and hydrogen sulfide detector; an ion mobility spectrometer for airborne vapor detection; and a COMPAQ 386/20 portable computer. The software modules are a graphics kernel, an expert system shell, a data-base management system, and an interface management system. A supervisory module developed using the interface management system coordinates the interaction of the other software components. The system determines the safety of the environment using conventional data acquisition and analysis techniques. The low-oxygen, carbon monoxide, hydrogen sulfide, explosives, and vapor detectors are monitored for hazardous levels, and warnings are issued accordingly

  19. Time Synchronization Module for Automatic Identification System

    Institute of Scientific and Technical Information of China (English)

    Choi Il-heung; Oh Sang-heon; Choi Dae-soo; Park Chan-sik; Hwang Dong-hwan; Lee Sang-jeong

    2003-01-01

    This paper proposed a design and implementation procedure of the Time Synchronization Module (TSM) for the Automatic Identification System (AIS). The proposed TSM module uses a Temperature Compensated Crystal Oscillator (TCXO) as a local reference clock, and consists of a Digitally Controlled Oscillator (DCO), a divider, a phase discriminator, and register blocks. The TSM measures time difference between the 1 PPS from the Global Navigation Satellite System (GNSS) receiver and the generated transmitter clock. The measured time difference is compensated by controlling the DCO and the transmit clock is synchronized to the Universal Time Coordinated (UTC). The designed TSM can also be synchronized to the reference time derived from the received message. The proposed module is tested using the experimental AIS transponder set. The experimental results show that the proposed module satisfies the functional and timing specification of the AIS technical standard, ITU-R M.1371.

  20. Automatic control system of the radiometric system for inspection of large-scale vehicles and cargoes

    International Nuclear Information System (INIS)

    The automatic control system (ACS) is intended to control the equipment of the radiometric inspection system in the normal operating modes as well as during the preventive maintenance, maintenance/repair and adjustment works; for acquisition of the data on the status of the equipment, reliable protection of the personnel and equipment, acquisition, storage and processing of the results of operation and to ensure service maintenance.

  1. Automatic Vehicle Speed Reduction System Using Rf Technology

    Directory of Open Access Journals (Sweden)

    Deepa B Chavan

    2014-04-01

    Full Text Available For vehicle safety and safety for passengers in vehicle is an important parameter. Most of the vehicles get accident because no proper safety measures are taken especially at curves and hair pin bends humps and any obstacles in front of the vehicle. This system can be used for the prevention of such a problem by indicating a pre indication and also reducing the speed of vehicles by reducing the fuel rate of vehicle. As the action is in terms of fuel rate so the vehicle automatically goes to control and avoids the accidents. At curves and hair pin bends the line of sight is not possible for the drivers so the special kind of transmitter which is tuned at a frequency of 433MHZ are mounted as these transmitters continuously radiate a RF signal for some particular area. As the vehicle come within this radiation the receiver in the vehicle gets activate. The transmitter used here is a coded transmitter which is encoded with encoder. The encoder provides a 4 bit binary data which is serially transmitted to transmitter. The transmitter used here is ASK type (amplitude shift keying which emits the RF radiation.

  2. 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.

  3. A REVIEW OF COMPUTER VISION SYSTEM FOR THE VEHICLE IDENTIFICATION AND CLASSIFICATION FROM ONLINE AND OFFLINE VIDEOS

    Directory of Open Access Journals (Sweden)

    Baljit Singh Mokha

    2015-10-01

    Full Text Available The traffic on the roads is increasing day by day. There is dire need of developing an automation system that can effectively manage and control the traffic on roads. The traffic data of multiple vehicle types on roads is also important for taking various decisions related to traffic. A video based traffic data collection system for multiple vehicle types is helpful for monitoring vehicles under homogenous and heterogeneous traffic conditions. In this paper, we have studied different methods for the identification, classification and counting vehicles from online and offline videos in India as well as other countries. The paper also discusses the various applications of video based automatic traffic control system. The various challenges faced by the researchers for developing such systems are also discussed.

  4. Automatic procedure for mass and charge identification of light isotopes detected in CsI(Tl) of the GARFIELD apparatus

    Energy Technology Data Exchange (ETDEWEB)

    Morelli, L.; Bruno, M.; Baiocco, G. [Dipartimento di Fisica dell' Universita and INFN, Bologna (Italy); Bardelli, L.; Barlini, S.; Bini, M.; Casini, G. [Dipartimento di Fisica dell' Universita and INFN, Firenze (Italy); D' Agostino, M., E-mail: dagostino@bo.infn.i [Dipartimento di Fisica dell' Universita and INFN, Bologna (Italy); Degerlier, M.; Gramegna, F. [INFN, Laboratori Nazionali di Legnaro (Italy); Kravchuk, V.L. [Dipartimento di Fisica dell' Universita and INFN, Bologna (Italy); INFN, Laboratori Nazionali di Legnaro (Italy); Marchi, T. [Dipartimento di Fisica dell' Universita, Padova, ItalyNUCL-EX Collaboration (Italy); INFN, Laboratori Nazionali di Legnaro (Italy); Pasquali, G.; Poggi, G. [Dipartimento di Fisica dell' Universita and INFN, Firenze (Italy)

    2010-08-21

    Mass and charge identification of light charged particles detected with the 180 CsI(Tl) detectors of the GARFIELD apparatus is presented. A 'tracking' method to automatically sample the Z and A ridges of 'Fast-Slow' histograms is developed. An empirical analytic identification function is used to fit correlations between Fast and Slow, in order to determine, event by event, the atomic and mass numbers of the detected charged reaction products. A summary of the advantages of the proposed method with respect to 'hand-based' procedures is reported.

  5. Automatic procedure for mass and charge identification of light isotopes detected in CsI(Tl) of the GARFIELD apparatus

    Science.gov (United States)

    Morelli, L.; Bruno, M.; Baiocco, G.; Bardelli, L.; Barlini, S.; Bini, M.; Casini, G.; D'Agostino, M.; Degerlier, M.; Gramegna, F.; Kravchuk, V. L.; Marchi, T.; Pasquali, G.; Poggi, G.

    2010-08-01

    Mass and charge identification of light charged particles detected with the 180 CsI(Tl) detectors of the GARFIELD apparatus is presented. A "tracking" method to automatically sample the Z and A ridges of "Fast-Slow" histograms is developed. An empirical analytic identification function is used to fit correlations between Fast and Slow, in order to determine, event by event, the atomic and mass numbers of the detected charged reaction products. A summary of the advantages of the proposed method with respect to "hand-based" procedures is reported.

  6. Autonomous system for pathogen detection and identification

    Energy Technology Data Exchange (ETDEWEB)

    Belgrader, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Benett, W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bergman, W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Langlois, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mariella, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Milanovich, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Miles, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Venkateswaran, K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Long, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nelson, W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    1998-09-24

    This purpose of this project is to build a prototype instrument that will, running unattended, detect, identify, and quantify BW agents. In order to accomplish this, we have chosen to start with the world' s leading, proven, assays for pathogens: surface-molecular recognition assays, such as antibody-based assays, implemented on a high-performance, identification (ID)-capable flow cytometer, and the polymerase chain reaction (PCR) for nucleic-acid based assays. With these assays, we must integrate the capability to: l collect samples from aerosols, water, or surfaces; l perform sample preparation prior to the assays; l incubate the prepared samples, if necessary, for a period of time; l transport the prepared, incubated samples to the assays; l perform the assays; l interpret and report the results of the assays. Issues such as reliability, sensitivity and accuracy, quantity of consumables, maintenance schedule, etc. must be addressed satisfactorily to the end user. The highest possible sensitivity and specificity of the assay must be combined with no false alarms. Today, we have assays that can, in under 30 minutes, detect and identify simulants for BW agents at concentrations of a few hundred colony-forming units per ml of solution. If the bio-aerosol sampler of this system collects 1000 Ymin and concentrates the respirable particles into 1 ml of solution with 70% processing efficiency over a period of 5 minutes, then this translates to a detection/ID capability of under 0.1 agent-containing particle/liter of air.

  7. RESEARCH ON EXPERT SYSTEM OF FAULT DETECTION AND DIAGNOSING FOR PNEUMATIC SYSTEM OF AUTOMATIC PRODUCTION LINE

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Fault detection and diagnosis for pneumatic system of automatic production line are studied. An expert system using fuzzy-neural network and pneumatic circuit fault diagnosis instrument are designed. The mathematical model of various pneumatic faults and experimental device are built. In the end, some experiments are done, which shows that the expert system using fuzzy-neural network can diagnose fast and truly fault of pneumatic circuit.

  8. 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

    2016-01-01

    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 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. PMID:27136548

  9. 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

    2016-01-01

    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 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. PMID:27136548

  10. 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.

  11. Design and construction of an automatic system for minimizing the risk of sinking of water vehicle

    Science.gov (United States)

    Sutradhar, Amit; Rashid, Md. Mahbubur; Helal-An-Nahiyan, Md.; Mandal, Manash Kumar

    2016-07-01

    This paper focuses on the reduction of the risk of water vehicle like launch, ferry, ship and boat from sinking which is a burning problem of Bangladesh now-a-days. Every year death toll is rising by leaps and bounds due to this unexpected phenomenon. The sinking mostly occurs due to overloading and lack of consciousness. That's why, an automated system is introduced here to make the travelers warned about the overloading situation through raising alarm before the vehicle starts to move on. The tolerance limit of the vehicle is determined based on the theory of buoyancy and floatation. Moreover, while moving on the water, the vehicle may get victim of sinking due to rough weather, low visibility or machineries breakdown. So water level indicator is used to determine the safe level of water. When water level rises up to the safe limit or just before crossing the safe limit, another alarm will warn the passengers which will sound quite different from the first alarm as stated before. And at once the on board GPS sensor will record the current position of the vehicle and transmit the location to the nearest rescue authority via GSM module in the form of text message which will help them to take necessary steps for the rescue of the passengers as soon as possible. Effective implementation of this method can reduce the accident as well as this research can also be a helpful tool to organize further researches in this field for the sake of humanity.

  12. Automatic ultrasonic system for flaw detection and dimensional measurement of precision tubes

    International Nuclear Information System (INIS)

    This paper describes a system, which is installed at Nuclear Fuel Complex, Hyderabad. It is a tube rotation fixed probe type of system designed for fully automatic operation at high speed using immersion technique for ultrasonic flaw detection and dimensional measurement of precision of zirconium alloy seamless tubes used in fuel bundles for nuclear reactors

  13. Unattended vehicle detection for automatic traffic light control

    Science.gov (United States)

    Abdel Hady, Aya Salama; Moustafa, Mohamed

    2013-12-01

    Machine vision based traffic light control depends mainly on measuring traffic statistics at cross roads. Most of the previous studies have not taken unattended vehicles into consideration when calculating either the traffic density or the traffic flow. In this paper, we propose incorporating unattended vehicles into a new metric for measuring the traffic congestion. In addition to the vehicle motion analysis, opening the driver's side door is an important indicator that this vehicle is going to be unattended. Therefore, we focus in this paper on presenting how to detect this event for stationary vehicles from a live camera or a video feed. Through a set of experiments, we have found out that a Scale Invariant Feature Transform (SIFT) feature-descriptor with a Support Vector Machines (SVM) classifier was able to successfully classify open-door vehicles from closed-door ones in 96.7% of our test dataset.

  14. All-optical automatic pollen identification: Towards an operational system

    Science.gov (United States)

    Crouzy, Benoît; Stella, Michelle; Konzelmann, Thomas; Calpini, Bertrand; Clot, Bernard

    2016-09-01

    We present results from the development and validation campaign of an optical pollen monitoring method based on time-resolved scattering and fluorescence. Focus is first set on supervised learning algorithms for pollen-taxa identification and on the determination of aerosol properties (particle size and shape). The identification capability provides a basis for a pre-operational automatic pollen season monitoring performed in parallel to manual reference measurements (Hirst-type volumetric samplers). Airborne concentrations obtained from the automatic system are compatible with those from the manual method regarding total pollen and the automatic device provides real-time data reliably (one week interruption over five months). In addition, although the calibration dataset still needs to be completed, we are able to follow the grass pollen season. The high sampling from the automatic device allows to go beyond the commonly-presented daily values and we obtain statistically significant hourly concentrations. Finally, we discuss remaining challenges for obtaining an operational automatic monitoring system and how the generic validation environment developed for the present campaign could be used for further tests of automatic pollen monitoring devices.

  15. 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.

  16. 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.

  17. 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. PMID:24473345

  18. Automatic Classification of the Vestibulo-Ocular Reflex Nystagmus: Integration of Data Clustering and System Identification.

    Science.gov (United States)

    Ranjbaran, Mina; Smith, Heather L H; Galiana, Henrietta L

    2016-04-01

    The vestibulo-ocular reflex (VOR) plays an important role in our daily activities by enabling us to fixate on objects during head movements. Modeling and identification of the VOR improves our insight into the system behavior and improves diagnosis of various disorders. However, the switching nature of eye movements (nystagmus), including the VOR, makes dynamic analysis challenging. The first step in such analysis is to segment data into its subsystem responses (here slow and fast segment intervals). Misclassification of segments results in biased analysis of the system of interest. Here, we develop a novel three-step algorithm to classify the VOR data into slow and fast intervals automatically. The proposed algorithm is initialized using a K-means clustering method. The initial classification is then refined using system identification approaches and prediction error statistics. The performance of the algorithm is evaluated on simulated and experimental data. It is shown that the new algorithm performance is much improved over the previous methods, in terms of higher specificity. PMID:26357393

  19. Automatic Classification of the Vestibulo-Ocular Reflex Nystagmus: Integration of Data Clustering and System Identification.

    Science.gov (United States)

    Ranjbaran, Mina; Smith, Heather L H; Galiana, Henrietta L

    2016-04-01

    The vestibulo-ocular reflex (VOR) plays an important role in our daily activities by enabling us to fixate on objects during head movements. Modeling and identification of the VOR improves our insight into the system behavior and improves diagnosis of various disorders. However, the switching nature of eye movements (nystagmus), including the VOR, makes dynamic analysis challenging. The first step in such analysis is to segment data into its subsystem responses (here slow and fast segment intervals). Misclassification of segments results in biased analysis of the system of interest. Here, we develop a novel three-step algorithm to classify the VOR data into slow and fast intervals automatically. The proposed algorithm is initialized using a K-means clustering method. The initial classification is then refined using system identification approaches and prediction error statistics. The performance of the algorithm is evaluated on simulated and experimental data. It is shown that the new algorithm performance is much improved over the previous methods, in terms of higher specificity.

  20. Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

    Science.gov (United States)

    Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

    2016-03-01

    In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. PMID:26722989

  1. Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

    Science.gov (United States)

    Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

    2016-03-01

    In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature.

  2. A Communication Protocol and Monitoring Policy for Input/Output Vehicles in an Automatic Storage and Retrieval System

    Institute of Scientific and Technical Information of China (English)

    LI Li; LI Wenfeng; LIAO Xiaoping; SU Wengui; LIN Yizhong

    2006-01-01

    The acquisition and processing of equipment information is pivotal to control and management of the automated storage and retrieval system. The work of this paper is based on the automatic storage and retrieval experimental system of Wuhan University of Technology. First, the output/input flow and the control information of storage/retrieval vehicle are studied and the plotting finite state machine model of the stacking crane is established. Then, the communication protocol between the center control management computer and the PLC of stacking crane is designed. Finally, the stacking crane's monitoring data, which include operating time, running states and real-time position status, are gained by analyzing the communication protocol. The detailed program for the acquisition and processing of monitoring information is developed. This method is suitable for the equipment monitoring of the whole system, and provides a platform for studying the intelligent control and optimal scheduling strategies of AS/RS.

  3. Systems for Detection and Identification of Biological Aerosols (Review Paper)

    OpenAIRE

    Eva Švabenska

    2012-01-01

    Easy and inexpensive manufacturing of biological weapons, their complicated detection, expensive protection, difficult treating of affected individuals, selective impact only for people, animals or plants, are all factors making an effective defense against biological warfare agents very difficult. The aim of this study is an introduction to the systems for the detection and identification of biological aerosols containing dangerous bioagents. The basic techniques used for detection and ident...

  4. Shift Control System of Heavy-duty Vehicle Automatic Transmission

    Directory of Open Access Journals (Sweden)

    Yan Zhang

    2013-12-01

    Full Text Available Heavy-duty vehicle hydrodynamic mechanical automatic transmission shifting operation system was designed, mathematical model of its simplified hydraulic system was established and simulation model of shifting operation system was established with AMESim, the simulation experiment was carried out, then oil pressure curves of each clutch hydraulic cylinder were obtained when giving forward gear or reverse gear signals. The simulation results show that shifting operating system meets the design requirements, and verify the correctness of the model. The shift timing is correct, and there is no power interruption or gear overlap during the shift transition process. Joint oil pressure of designed system is stable, and shifting shock is small. The research results are providing the basis for further study of shifting operation system and a reasonable platform for the studying of shift schedule and quality. The theoretical design method and dynamic simulation experiment will be feasible for the real industrial applications. The research results can be used in design and optimization of hydraulic system

  5. Automatic Vehicle Detection during Nighttime Using Bright Pixel Segment with Spatial Temporal Technique

    Directory of Open Access Journals (Sweden)

    S.Nandhini

    2012-06-01

    Full Text Available The paper proposes an effective Traffic surveillance system for detecting and tracking moving vehicles in nighttime traffic. It identifies vehicles by detecting and locating vehicle headlights and taillights using image segmentation and pattern analysis technique. By preprocessing noise is removed using median filter. Morphological operation is used to extract candidate headlight objects and then perform shape analysis. Template matching or pattern classification to find the paired headlight of moving vehicles. Salient points are used to represent local properties of image classification. It carries information about image content. Gabor derivation is used for edge detection and feature extraction.

  6. An improved automatic computer aided tube detection and labeling system on chest radiographs

    Science.gov (United States)

    Ramakrishna, Bharath; Brown, Matthew; Goldin, Jonathan; Cagnon, Christopher; Enzmann, Dieter

    2012-03-01

    Tubes like Endotracheal (ET) tube used to maintain patient's airway and the Nasogastric (NG) tube used to feed the patient and drain contents of the stomach are very commonly used in Intensive Care Units (ICU). The placement of these tubes is critical for their proper functioning and improper tube placement can even be fatal. Bedside chest radiographs are considered the quickest and safest method to check the placement of these tubes. Tertiary ICU's typically generate over 250 chest radiographs per day to confirm tube placement. This paper develops a new fully automatic prototype computer-aided detection (CAD) system for tube detection on bedside chest radiographs. The core of the CAD system is the randomized algorithm which selects tubes based on their average repeatability from seed points. The CAD algorithm is designed as a 5 stage process: Preprocessing (removing borders, histogram equalization, anisotropic filtering), Anatomy Segmentation (to identify neck, esophagus, abdomen ROI's), Seed Generation, Region Growing and Tube Selection. The preliminary evaluation was carried out on 64 cases. The prototype CAD system was able to detect ET tubes with a True Positive Rate of 0.93 and False Positive Rate of 0.02/image and NG tubes with a True Positive Rate of 0.84 and False Positive Rate of 0.02/image respectively. The results from the prototype system show that it is feasible to automatically detect both tubes on chest radiographs, with the potential to significantly speed the delivery of imaging services while maintaining high accuracy.

  7. Automatic Prosodic Break Detection and Feature Analysis

    Institute of Scientific and Technical Information of China (English)

    Chong-Jia Ni; Ai-Ying Zhang; Wen-Ju Liu; Bo Xu

    2012-01-01

    Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis.In this paper,we discuss automatic prosodic break detection and feature analysis.The contributions of the paper are two aspects.One is that we use classifier combination method to detect Mandarin and English prosodic break using acoustic,lexical and syntactic evidence.Our proposed method achieves better performance on both the Mandarin prosodic annotation corpus — Annotated Speech Corpus of Chinese Discourse and the English prosodic annotation corpus —Boston University Radio News Corpus when compared with the baseline system and other researches' experimental results.The other is the feature analysis for prosodic break detection.The functions of different features,such as duration,pitch,energy,and intensity,are analyzed and compared in Mandarin and English prosodic break detection.Based on the feature analysis,we also verify some linguistic conclusions.

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

    OpenAIRE

    Shafie, A. A.; Ali, M.H.; FADHLAN HAFIZ; ROSLIZAR M. ALI

    2011-01-01

    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 c...

  9. Automatic Identification of Modal, Breathy and Creaky Voices

    Directory of Open Access Journals (Sweden)

    Poonam Sharma

    2013-12-01

    Full Text Available This paper presents a way for the automatic identification of different voice qualities present in a speech signal which is very beneficiary for detecting any kind of speech by an efficient speech recognition system. Proposed technique is based on three important characteristics of speech signal namely Zero Crossing Rate, Short Time Energy and Fundamental Frequency. The performance of the proposed algorithm is evaluated using the data collected from three different speakers and an overall accuracy of 87.2 % is achieved.

  10. Fiber optic system design for vehicle detection and analysis

    Science.gov (United States)

    Nedoma, Jan; Zboril, Ondrej; Fajkus, Marcel; Zavodny, Petr; Kepak, Stanislav; Bednarek, Lukas; Martinek, Radek; Vasinek, Vladimir

    2016-04-01

    Fiber optic interferometers belong to a group of highly sensitive and precise devices enabling to measure small changes in the deformation shapes, changes in pressure, temperature, vibration and so on. The basis of their activity is to evaluate the number of fringes over time, not changes in the intensity of the optical signal. The methodology described in the article is based on using the interferometer to monitor traffic density. The base of the solution is a Mach-Zehnder interferometer operating with single-mode G.652 optical fiber at the wavelength of 1550 nm excited by a DFB laser. The power distribution of the laser light into the individual arms of the interferometer is in the ratio 1:1. Realized measuring scheme was terminated by an optical receiver including InGaAs PIN photodiode. Registered signal from the photodetector was through 8 Hz high pass filter fed to the measuring card that captures the analog input voltage using an application written in LabView development environment. The interferometer was stored in a waterproof box and placed at the side of the road. Here panned individual transit of cars in his environs. Vertically across the road was placed in contact removable belt simulating a retarder, which was used when passing cars to create sufficient vibration response detecting interferometer. The results demonstrated that the individual vehicles passing around boxing showed characteristic amplitude spectra, which was unique for each object, and had sufficient value signal to noise ratio (SNR). The signal was processed by applications developed for the amplitude-frequency spectrum. Evaluated was the maximum amplitude of the signal and compared to the noise. The results were verified by repeated transit of the different types of cars.

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

    International Nuclear Information System (INIS)

    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

  12. 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.

  13. Detection and Identification System of Bacteria and Bacterial Endotoxin Based on Raman Spectroscopy

    Directory of Open Access Journals (Sweden)

    Muhammad Elsayeh

    2016-03-01

    Full Text Available Sepsis is a global health problem that causes risk of death. In the developing world, about 60 to 80 % of death cases are caused by Sepsis. Rapid methods for detecting its causes, represent one of the major factors that may reduce Sepsis risks. Such methods can provide microbial detection and identification which is critical to determine the right treatment for the patient. Microbial and Pyrogen detection is important for quality control system to ensure the absence of pathogens and Pyrogens in the manufacturing of both medical and food products. Raman spectroscopes represent a q uick and accurate identification and detection method, for bacteria and bacterial endotoxin, which this plays an important role in delivering high quality biomedical products using the power of Raman spectroscopy. It is a rapid method for chemical structure detection that can be used in identifying and classifying bacteria and bacterial endotoxin. Such a method acts as a solution for time and cost effective quality control procedures. This work presents an automatic system based on Raman spectroscopy to detect and identify bacteria and bacterial endotoxin. It uses the frequency properties of Raman scattering through the interaction between organic materials and electromagnetic waves. The scattered intensities are measured and wave number converted into frequency, then the cepstral coefficients are extracted for both the detection and identification. The methodology depends on normalization of Fourier transformed cepstral signal to extract their classification features. Experiments’ results proved effective identification and detection of bacteria and bacterial endotoxin even with concentrations as low as 0.0003 Endotoxin unit (EU/ml and 1 Colony Forming Unit (CFU/ml using signal processing based enhancement technique.

  14. Examination techniques of the automatics fire detection monitoring system

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Yon Woo [Korea Atomic Energy Research Institute, Taejon (Korea)

    1999-04-01

    The variety of the automatic fire detection monitoring systems has been developed because the multistory buildings were constructed and the various structural materials were used. To stop the spread of the fire and minimize the damage of human life and properties of the facility, it should be informed precisely to all the members of the facility. (author). 12 refs., 28 figs.

  15. Automatic Urban Illegal Building Detection Using Multi-Temporal Satellite Images and Geospatial Information Systems

    Science.gov (United States)

    Khalili Moghadam, N.; Delavar, M. R.; Hanachee, P.

    2015-12-01

    With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB) construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user's intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  16. Channel Access Algorithm Design for Automatic Identification System

    Institute of Scientific and Technical Information of China (English)

    Oh Sang-heon; Kim Seung-pum; Hwang Dong-hwan; Park Chan-sik; Lee Sang-jeong

    2003-01-01

    The Automatic Identification System (AIS) is a maritime equipment to allow an efficient exchange of the navigational data between ships and between ships and shore stations. It utilizes a channel access algorithm which can quickly resolve conflicts without any intervention from control stations. In this paper, a design of channel access algorithm for the AIS is presented. The input/output relationship of each access algorithm module is defined by drawing the state transition diagram, dataflow diagram and flowchart based on the technical standard, ITU-R M.1371. In order to verify the designed channel access algorithm, the simulator was developed using the C/C++ programming language. The results show that the proposed channel access algorithm can properly allocate transmission slots and meet the operational performance requirements specified by the technical standard.

  17. 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.

  18. Wavelet features for failure detection and identification in vibration systems

    Science.gov (United States)

    Deckert, James C.; Rhenals, Alonso E.; Tenney, Robert R.; Willsky, Alan S.

    1992-12-01

    The result of this effort is an extremely flexible and powerful methodology for failure detection and identification (FDI) in vibrating systems. The essential elements of this methodology are: (1) an off-line set of techniques to identify high-energy, statistically significant features in the continuous wavelet transform (CWT); (2) a CWT-based preprocessor to extract the most useful features from the sensor signal; and (3) simple artificial neural networks (incorporating a mechanism to defer any decision if the current feature sample is determined to be ambiguous) for the subsequent classification task. For the helicopter intermediate gearbox test-stand data and centrifugal and fire pump shipboard (mild operating condition) data used, the algorithms designed using this method achieved perfect detection performance (1.000 probability of detection, and 0.000 false alarm probability), with a probability less than 0.04 that a decision would be deferred-based on only 500 milliseconds of data from each sample case. While this effort shows the exceptional promise of our wavelet-based method for FDI in vibrating systems, more demanding applications, which also have other sources of high-energy vibration, raise additional technical issues that could provide the focus for a Phase 2 effort.

  19. An interactive system for seismic signal detection and identification

    International Nuclear Information System (INIS)

    The methods to distinguish an underground explosion from an earthquake are mainly based on exploiting the differences in the source functions of the two processes and locating the depth of source. Various characteristics of seismic signals generated by these sources are usually represented by different parameters or identifiers. However, it is not possible for a single identifier to distinguish an explosion from an earthquake with equal effectiveness in all situations. Usually a combination of several identifiers is found to provide effective means for the identification of seismic sources. In order to use the multiple parameters in an optimum way, an interactive system (IS) for detection and identification of global events has been developed using short period data of Gauribidanur array. This report describes the salient features of the IS and demonstrates its effectiveness in identifying an event using weighted combination of the parameters together with the depth of source. It is intended to augment the system with long period data in the next phase of the development. (author). 37 refs., 14 figs., 2 tabs

  20. 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.

  1. Variable identification and automatic tuning of the main module of a servo system of parallel mechanism

    Institute of Scientific and Technical Information of China (English)

    YANG Zhiyong; XU Meng; HUANG Tian; NI Yanbing

    2007-01-01

    The variables of the main module of a servo system for miniature reconfigurable parallel mechanism were identified and automatically tuned. With the reverse solution module of the translation, the module with the exerted translation joint was obtained, which included the location, velocity and acceleration of the parallelogram carriage- branch. The rigid dynamic reverse model was set as the virtual work principle. To identify the variables of the servo system, the triangle-shaped input signal with variable frequency was adopted to overcome the disadvantages of the pseudo-random number sequence, i.e., making the change of the vibration amplitude of the motor dramatically, easily impact the servo motor and make the velocity loop open and so on. Moreover, all the variables including,the rotary inertia of the servo system were identified by the additive mass. The overshoot and rise time were the optimum goals, the limited changing load with the attitude was considered, and the range of the controller variables in the servo system was identified. The results of the experiments prove that the method is accurate.

  2. 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 di

  3. 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.

  4. Automatic Emboli Detection System for the Artificial Heart

    Science.gov (United States)

    Steifer, T.; Lewandowski, M.; Karwat, P.; Gawlikowski, M.

    In spite of the progress in material engineering and ventricular assist devices construction, thromboembolism remains the most crucial problem in mechanical heart supporting systems. Therefore, the ability to monitor the patient's blood for clot formation should be considered an important factor in development of heart supporting systems. The well-known methods for automatic embolus detection are based on the monitoring of the ultrasound Doppler signal. A working system utilizing ultrasound Doppler is being developed for the purpose of flow estimation and emboli detection in the clinical artificial heart ReligaHeart EXT. Thesystem will be based on the existing dual channel multi-gate Doppler device with RF digital processing. A specially developed clamp-on cannula probe, equipped with 2 - 4 MHz piezoceramic transducers, enables easy system setup. We present the issuesrelated to the development of automatic emboli detection via Doppler measurements. We consider several algorithms for the flow estimation and emboli detection. We discuss their efficiency and confront them with the requirements of our experimental setup. Theoretical considerations are then met with preliminary experimental findings from a) flow studies with blood mimicking fluid and b) in-vitro flow studies with animal blood. Finally, we discuss some more methodological issues - we consider several possible approaches to the problem of verification of the accuracy of the detection system.

  5. Automatic Boat Identification System for VIIRS Low Light Imaging Data

    Directory of Open Access Journals (Sweden)

    Christopher D. Elvidge

    2015-03-01

    Full Text Available The ability for satellite sensors to detect lit fishing boats has been known since the 1970s. However, the use of the observations has been limited by the lack of an automatic algorithm for reporting the location and brightness of offshore lighting features arising from boats. An examination of lit fishing boat features in Visible Infrared Imaging Radiometer Suite (VIIRS day/night band (DNB data indicates that the features are essentially spikes. We have developed a set of algorithms for automatic detection of spikes and characterization of the sharpness of spike features. A spike detection algorithm generates a list of candidate boat detections. A second algorithm measures the height of the spikes for the discard of ionospheric energetic particle detections and to rate boat detections as either strong or weak. A sharpness index is used to label boat detections that appear blurry due to the scattering of light by clouds. The candidate spikes are then filtered to remove features on land and gas flares. A validation study conducted using analyst selected boat detections found the automatic algorithm detected 99.3% of the reference pixel set. VIIRS boat detection data can provide fishery agencies with up-to-date information of fishing boat activity and changes in this activity in response to new regulations and enforcement regimes. The data can provide indications of illegal fishing activity in restricted areas and incursions across Exclusive Economic Zone (EEZ boundaries. VIIRS boat detections occur widely offshore from East and Southeast Asia, South America and several other regions.

  6. VEHICLE IDENTIFICATION TASK SOLUTION BY WINDSCREEN MARKING WITH A BARCODE

    Directory of Open Access Journals (Sweden)

    A. Levterov

    2012-01-01

    Full Text Available The vehicle identification means are considered and the present-day traffic requirements are set. The vehicle automatic identification method concerned with barcode use is proposed and described.

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

    OpenAIRE

    KARASULU, B.

    2014-01-01

    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. Th...

  8. 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.

  9. 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.

  10. Los Alamos Scientific Laboratory electronic vehicle identification system

    International Nuclear Information System (INIS)

    A three-digit electronic identification system is described. Digits may be decimal (1000 combinations) or hexidecimal (8192 combinations). Battery-powered transponders are interrogated with a lower-power (1 W) radio signal. Line-of-sight interrogations up to 33 m (100 ft) are possible. Successful interrogations up to 7 m (20 ft) are possible for concealed transponders (that is, in the engine compartment). Vehicles moving at high rates of speed can be interrogated. This system provides data in a computer-compatible RS232 format. The system can be used for other applications with little or no modification. A similar system is in present use for identification and temperature monitoring of livestock. No unforeseen problems exist for expanding the coding scheme to identify larger numbers of objects

  11. 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 ana

  12. AUTOMATIC FAST VIDEO OBJECT DETECTION AND TRACKING ON VIDEO SURVEILLANCE SYSTEM

    Directory of Open Access Journals (Sweden)

    V. Arunachalam

    2012-08-01

    Full Text Available This paper describes the advance techniques for object detection and tracking in video. Most visual surveillance systems start with motion detection. Motion detection methods attempt to locate connected regions of pixels that represent the moving objects within the scene; different approaches include frame-to-frame difference, background subtraction and motion analysis. The motion detection can be achieved by Principle Component Analysis (PCA and then separate an objects from background using background subtraction. The detected object can be segmented. Segmentation consists of two schemes: one for spatial segmentation and the other for temporal segmentation. Tracking approach can be done in each frame of detected Object. Pixel label problem can be alleviated by the MAP (Maximum a Posteriori technique.

  13. Automatic Identification And Data Collection Via Barcode Laser Scanning.

    Science.gov (United States)

    Jacobeus, Michel

    1986-07-01

    How to earn over 100 million a year by investing 40 million ? No this is not the latest Wall Street "tip" but the costsavings obtained by the U.S. Department of Defense. 2 % savings on annual turnover claim supermarkets ! Millions of Dollars saved report automotive companies ! These are not daydreams, but tangible results measured by users after implemen-ting Automatic Identification and Data Collection systems, based on bar codes. To paraphrase the famous sentence "I think, thus I am", with AI/ADC systems "You knonw, thus you are". Indeed, in today's world, an immediate, accurate and precise information is a vital management need for companies growth and survival. AI/ADC techniques fullfill these objectives by supplying automatically and without any delay nor alteration the right information.

  14. Automatic Eye Blink Generation and Detection System in Digital Image Processing

    Directory of Open Access Journals (Sweden)

    Abha Dubey

    2012-09-01

    Full Text Available The eyes are tracked and correlation scores between the actual eye and the corresponding “closed-eye” template are used to detect blinks. However, it requires offline training for different depths from the camera for the computation of the distance. In addition, the system requires initialization in which an Eye blinking is one of the prominent areas to solve many real world problems. The process of blink detection consists of two phases. These are eye tracking followed by detection of blink. The work that has been carried out for eye tracking only is not suitable for eye blink detection. Stored template for a particular depth is chosen. Once the template is chosen and the system is in operation, the subject will be restricted to be at the specified distance. Another disadvantage of the system is that changing camera Positions require the whole system to be retrained. Further more. The same system in lay not be as effective if it were used on people of different races with disparate eye sizes and distance between the eyes. Therefore some approaches had been proposed for eye tracking along with eyes blink detection. This paper implements one of the approaches given by Michael et al [1,2,3]. The result of template creation accuracy and total blink detection to count number of eye blinks in an image sequence. Online template is completely independent of any past templates that may have been created during the run of the system. At last after analyzing all these approaches some of the parameters we obtained on which better performance of eye blink detection algorithm depend.

  15. Neutron Interrogation System For Underwater Threat Detection And Identification

    Science.gov (United States)

    Barzilov, Alexander P.; Novikov, Ivan S.; Womble, Phil C.

    2009-03-01

    Wartime and terrorist activities, training and munitions testing, dumping and accidents have generated significant munitions contamination in the coastal and inland waters in the United States and abroad. Although current methods provide information about the existence of the anomaly (for instance, metal objects) in the sea bottom, they fail to identify the nature of the found objects. Field experience indicates that often in excess of 90% of objects excavated during the course of munitions clean up are found to be non-hazardous items (false alarm). The technology to detect and identify waterborne or underwater threats is also vital for protection of critical infrastructures (ports, dams, locks, refineries, and LNG/LPG). We are proposing a compact neutron interrogation system, which will be used to confirm possible threats by determining the chemical composition of the suspicious underwater object. The system consists of an electronic d-T 14-MeV neutron generator, a gamma detector to detect the gamma signal from the irradiated object and a data acquisition system. The detected signal then is analyzed to quantify the chemical elements of interest and to identify explosives or chemical warfare agents.

  16. Automatic Time Skew Detection and Correction

    OpenAIRE

    Korchagin, Danil

    2011-01-01

    In this paper, we propose a new approach for the automatic time skew detection and correction for multisource audiovisual data, recorded by different cameras/recorders during the same event. All recorded data are successfully tested for potential time skew problem and corrected based on ASR-related features. The core of the algorithm is based on perceptual time-quefrency analysis with a precision of 10 ms. The results show correct time skew detection and elimination in 100% of cases for a rea...

  17. Automatic fault detection on BIPV systems without solar irradiation data

    CERN Document Server

    Leloux, Jonathan; Luna, Alberto; Desportes, Adrien

    2014-01-01

    BIPV systems are small PV generation units spread out over the territory, and whose characteristics are very diverse. This makes difficult a cost-effective procedure for monitoring, fault detection, performance analyses, operation and maintenance. As a result, many problems affecting BIPV systems go undetected. In order to carry out effective automatic fault detection procedures, we need a performance indicator that is reliable and that can be applied on many PV systems at a very low cost. The existing approaches for analyzing the performance of PV systems are often based on the Performance Ratio (PR), whose accuracy depends on good solar irradiation data, which in turn can be very difficult to obtain or cost-prohibitive for the BIPV owner. We present an alternative fault detection procedure based on a performance indicator that can be constructed on the sole basis of the energy production data measured at the BIPV systems. This procedure does not require the input of operating conditions data, such as solar ...

  18. 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...

  19. 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.

  20. Assessing facial wrinkles: automatic detection and quantification

    Science.gov (United States)

    Cula, Gabriela O.; Bargo, Paulo R.; Kollias, Nikiforos

    2009-02-01

    Nowadays, documenting the face appearance through imaging is prevalent in skin research, therefore detection and quantitative assessment of the degree of facial wrinkling is a useful tool for establishing an objective baseline and for communicating benefits to facial appearance due to cosmetic procedures or product applications. In this work, an algorithm for automatic detection of facial wrinkles is developed, based on estimating the orientation and the frequency of elongated features apparent on faces. By over-filtering the skin texture image with finely tuned oriented Gabor filters, an enhanced skin image is created. The wrinkles are detected by adaptively thresholding the enhanced image, and the degree of wrinkling is estimated based on the magnitude of the filter responses. The algorithm is tested against a clinically scored set of images of periorbital lines of different severity and we find that the proposed computational assessment correlates well with the corresponding clinical scores.

  1. Catching Of Stolen Vehicles With Unique Identification Code Using Embedded Systems

    Directory of Open Access Journals (Sweden)

    Mahesh Kumar Shakya

    2012-11-01

    Full Text Available The main purpose of this concept is to catch the stolen vehicles by a latest technology. This research work is developing a smart logic to identify the stolen vehicle on check post or Toll base. Still there is no technique to identify the vehicle on check posts by any mean. To employ this technology in use, we issue one unique identification code to every vehicle. This unique number is stored in the silicon chip and the chip is installed in the vehicle. No one can change this number because this UID chip is installed in the engine of the vehicle. This vehicle number is not available in the market. Now the vehicle is equipped with the UID code. This code is also stored in the Data base of check post or Toll base. Now when any vehicle passed through the check post/Toll then at the check post/Toll RF passive vehicle reader generates a 125 kHz frequency for decoding RF tag( which has been installed in the vehicle. If the data base does not find the stolen UID code then security gate gets OPEN and if the stolen UID code is matched with the data base then security gate remains closed and alarm becomes ON automatically and finally the stolen vehicle is caught

  2. Iris Recognition System using canny edge detection for Biometric Identification

    OpenAIRE

    Bhawna Chouhan; Dr.(Mrs) Shailja Shukla

    2011-01-01

    biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. Especially it focuses on image segmentation and feature extraction for iris recognition process...

  3. 移动车载激光点云的道路标线自动识别与提取%Automatic Road Marking Detection and Extraction Based on LiDAR Point Clouds from Vehicle- Borne MMS

    Institute of Scientific and Technical Information of China (English)

    邹晓亮; 缪剑; 郭锐增; 李星全; 赵桂华

    2012-01-01

    The research focuses on LiDAR point clouds of road surface acquired from vehicle - borne mobile mapping system - Land- Mark. An automatic road marking detection and extraction method is proposed. Combining LiDAR features of retro, angle and distance with the properties of traffic marking, point clouds of road marking is extracted. The road marking is best fitted in a least squares poly- nomial fitting method and CAD map is generated for automatic detection. Based on the experimental data from Sick laser scanner mounted on LandMark system, the experimental results show the method is feasible and available.%对移动车载激光测量LandMark系统获取的路面激光点云数据进行研究,结合激光点云的回波反射率、扫描角,以及量测距离等特征信息与道路标线的属性信息,提出了一种基于车载激光点云的道路标线自动识别与提取算法。从点云中提取道路标线,采用最小二乘线性最优拟合算法对提取的标线点云进行拟合,生成道路标线的CAD轮廓线,实现道路标线的自动化识别。以移动车载LandMark系统的Sick激光扫描仪获取的路面激光点云为例进行实验,实验结果表明该方法的可行性和有效性。

  4. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    Science.gov (United States)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  5. Antenna system analysis and design for automatic detection and real-time tracking of electron Bernstein waves in FTU

    Science.gov (United States)

    Bin, W.; Alessi, E.; Bruschi, A.; D'Arcangelo, O.; Figini, L.; Galperti, C.; Garavaglia, S.; Granucci, G.; Moro, A.

    2014-05-01

    The algorithm for the automatic control of the new front steering antenna of the Frascati Tokamak Upgrade device has been improved, in view of forthcoming experiments aimed at testing the mode conversion of electron cyclotron waves at a frequency of 140 GHz. The existing antenna system has been prepared to provide two-point real-time measurements of electron Bernstein waves and to allow real-time tracking of the optimal conversion region. This required an accurate analysis of the antenna to minimize the risk of a mechanical damage of the movable launching mirrors, when accessing the high toroidal launching angles needed for this kind of experiment. A detailed description is presented of the work carried out to safely reach and validate the desired range of steering angles, which include the region of interest, and a technique is proposed to track and chase the correct line of sight for electron Bernstein waves detection during the shot.

  6. Exploring Sound Signature for Vehicle Detection and Classification Using ANN

    Directory of Open Access Journals (Sweden)

    Jobin George

    2013-06-01

    Full Text Available This paper attempts to explore the possibility of using sound signatures for vehicle detection andclassification purposes. Sound emitted by vehicles are captured for a two lane undivided road carryingmoderate traffic. Simultaneous arrival of different types vehicles, overtaking at the study location, sound ofhorns, random but identifiable back ground noises, continuous high energy noises on the back ground arethe different challenges encountered in the data collection. Different features were explored out of whichsmoothed log energy was found to be useful for automatic vehicle detection by locating peaks. Mel-frequency ceptral coefficients extracted from fixed regions around the detected peaks along with themanual vehicle labels are utilised to train an Artificial Neural Network (ANN. The classifier for fourbroad classes heavy, medium, light and horns was trained. The ANN classifier developed was able topredict categories well.

  7. 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.

  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 braking system modification for the Advanced Transport Operating Systems (ATOPS) Transportation Systems Research Vehicle (TSRV)

    Science.gov (United States)

    Coogan, J. J.

    1986-01-01

    Modifications were designed for the B-737-100 Research Aircraft autobrake system hardware of the Advanced Transport Operating Systems (ATOPS) Program at Langley Research Center. These modifications will allow the on-board flight control computer to control the aircraft deceleration after landing to a continuously variable level for the purpose of executing automatic high speed turn-offs from the runway. A bread board version of the proposed modifications was built and tested in simulated stopping conditions. Test results, for various aircraft weights, turnoff speed, winds, and runway conditions show that the turnoff speeds are achieved generally with errors less than 1 ft/sec.

  10. DNA based typing, identification and detection systems for food spoilage microorganisms: development and implementation.

    Science.gov (United States)

    van der Vossen, J M; Hofstra, H

    1996-11-01

    The rapid identification of spoilage microorganisms is of eminent importance to the food industry. It provides the food industry with the opportunity to reduce economical losses by designing adequate intervention measures. The use of identification systems based on biochemical and physiological characteristics resulted often in disappointing identification results and misidentifications. This will inevitably lead to inappropriate strategies to prevent spoilage. This review discusses the potential of the DNA based identification technology including the polymerase chain reaction (PCR) for the identification and specific detection of microorganisms. Fingerprinting methods based on the DNA-probe technology enable a clear insight in the identity of microorganisms on different levels, varying from genus to strain level depending on the systems used. Discrimination between subspecies and strain level is shown to be helpful for investigating routes and sources of contamination. Differentiation at the species level is demonstrated to be essential in order to design a highly specific detection system enabling to signalize a microorganism that belongs to a particular species. Also indicated in this review is the necessity and the technical approach to detect microorganisms that display a particular undesirable trait.

  11. Controlling and Reducing of Speed for Vehicles Automatically By Using Rf Technology.

    Directory of Open Access Journals (Sweden)

    Y. Ravindra Babu,

    2014-11-01

    Full Text Available For vehicle safety and safety for passengers in vehicle is an important parameter. Most of the vehicles get accident because no proper safety measures are taken especially at curves and hair pin bends humps and any obstacles in front of the vehicle. This system can be used for the prevention of such a problem by indicating a pre indication and also reducing the speed of vehicles by reducing the fuel rate of vehicle. As the action is in terms of fuel rate so the vehicle automatically goes to control and avoids the accidents. At curves and hair pin bends the line of sight is not possible for the drivers so the special kind of transmitter which is tuned at a frequency of 433MHZ are mounted as these transmitters continuously radiate a RF signal for some particular area. As the vehicle come within this radiation the receiver in the vehicle gets activate. The transmitter used here is a coded transmitter which is encoded with encoder. The encoder provides a 4 bit binary data which is serially transmitted to transmitter. The transmitter used here is ASK type (amplitude shift keying which emits the RF radiation.

  12. 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...

  13. 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

  14. Development of an automated Red Light Violation Detection System (RLVDS) for Indian vehicles

    CERN Document Server

    Saha, Satadal; Nasipuri, Mita; Basu, Dipak Kumar

    2010-01-01

    Integrated Traffic Management Systems (ITMS) are now implemented in different cities in India to primarily address the concerns of road-safety and security. An automated Red Light Violation Detection System (RLVDS) is an integral part of the ITMS. In our present work we have designed and developed a complete system for generating the list of all stop-line violating vehicle images automatically from video snapshots of road-side surveillance cameras. The system first generates adaptive background images for each camera view, subtracts captured images from the corresponding background images and analyses potential occlusions over the stop-line in a traffic signal. Considering round-the-clock operations in a real-life test environment, the developed system could successfully track 92% images of vehicles with violations on the stop-line in a "Red" traffic signal.

  15. Electronic Vehicle Identification Architecture and Proof of Concept

    NARCIS (Netherlands)

    Passchier, I.; Chevrollier, N.G.; Mulder,A.; Vliet,A.O.T.van

    2009-01-01

    An architecture and a proof of concept for Electronic Vehicle Identification have beendeveloped. The system has been successfully tested in a pilot with 23 participants over a period of three months and a total distance of 75.000 km travelled. The architecture consists of a functional definition, a

  16. Iris Recognition System using canny edge detection for Biometric Identification

    Directory of Open Access Journals (Sweden)

    Bhawna Chouhan

    2011-01-01

    Full Text Available biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. Especially it focuses on image segmentation and feature extraction for iris recognition process. The performance of iris recognition system highly depends on edge detection. The Canny Edge Detector is one of the most commonly used image processing tools, detecting edges in a very robust manner. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. This paper presents a straightforward approach for segmenting the iris patterns. The used method determines an automated global threshold and the pupil center. Experiments are performed using iris images obtained from CASIA database (Institute of Automation, Chinese Academy of Sciences and Matlab application for its easy and efficient tools in image manipulation.

  17. Low-cost backpack-portable robot system for mine and UXO detection and identification

    Science.gov (United States)

    Nelson, Carl V.; Arabian, Adam K.

    2002-08-01

    The Johns Hopkins University Applied Physics Laboratory (JHU/APL) has developed a prototype backpack-portable robot system for mine and unexploded ordnance (UXO) detection and identification. The robot system is compact, lightweight and is estimated to be inexpensive to construct. The robot has been designed with an inexpensive, highly accurate, wide bandwidth time-domain electromagnetic induction (EMI) sensor for the detection and identification of metal components in mines and UXO. The robot can be configured for autonomous or person-in-the-loop control. The robot system can be configured with additional light-weight and low-cost mine and UXO sensors such as ground penetrating radar (GPR) and chemical explosive detectors.

  18. Automatic Encoding and Language Detection in the GSDL

    Directory of Open Access Journals (Sweden)

    Otakar Pinkas

    2014-10-01

    Full Text Available Automatic detection of encoding and language of the text is part of the Greenstone Digital Library Software (GSDL for building and distributing digital collections. It is developed by the University of Waikato (New Zealand in cooperation with UNESCO. The automatic encoding and language detection in Slavic languages is difficult and it sometimes fails. The aim is to detect cases of failure. The automatic detection in the GSDL is based on n-grams method. The most frequent n-grams for Czech are presented. The whole process of automatic detection in the GSDL is described. The input documents to test collections are plain texts encoded in ISO-8859-1, ISO-8859-2 and Windows-1250. We manually evaluated the quality of automatic detection. To the causes of errors belong the improper language model predominance and the incorrect switch to Windows-1250. We carried out further tests on documents that were more complex.

  19. AUTOMATIC LICENSE PLATE LOCALISATION AND IDENTIFICATION VIA SIGNATURE ANALYSIS

    Directory of Open Access Journals (Sweden)

    Lorita Angeline

    2014-02-01

    Full Text Available A new algorithm for license plate localisation and identification is proposed on the basis of Signature analysis. Signature analysis has been used to locate license plate candidate and its properties can be further utilised in supporting and affirming the license plate character recognition. This paper presents Signature Analysis and the improved conventional Connected Component Analysis (CCA to design an automatic license plate localisation and identification. A procedure called Euclidean Distance Transform is added to the conventional CCA in order to tackle the multiple bounding boxes that occurred. The developed algorithm, SAICCA achieved 92% successful rate, with 8% failed localisation rate due to the restrictions such as insufficient light level, clarity and license plate perceptual information. The processing time for a license plate localisation and recognition is a crucial criterion that needs to be concerned. Therefore, this paper has utilised several approaches to decrease the processing time to an optimal value. The results obtained show that the proposed system is capable to be implemented in both ideal and non-ideal environments.

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

    Energy Technology Data Exchange (ETDEWEB)

    Aldonate, J; Mercuri, C; Reta, J; Biurrun, J; Bonell, C; Gentiletti, G; Escobar, S; Acevedo, R [Laboratorio de Ingenieria en Rehabilitacion e Investigaciones Neuromusculares y Sensoriales (Argentina); Facultad de Ingenieria, Universidad Nacional de Entre Rios, Ruta 11 - Km 10, Oro Verde, Entre Rios (Argentina)

    2007-11-15

    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.

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

    Science.gov (United States)

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

    2007-11-01

    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.

  2. 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.

  3. 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.

  4. A Survey on Automatic Fall Detection in the Context of Ambient Assisted Living Systems

    Directory of Open Access Journals (Sweden)

    Velislava Spasova

    2014-03-01

    Full Text Available Ambient Assisted Living (AAL systems are a relatively new and expanding area of research. Due to current demographic trends towards gentrification of the population AAL systems are bound to become more important in todays and near future’s societies. Fall detection is an important component of AAL systems which could provide better safety and higher independency of the elderly. This paper presents a survey on automatic fall detection in the context of AAL systems.

  5. Attack Detection and Identification in Cyber-Physical Systems -- Part I: Models and Fundamental Limitations

    CERN Document Server

    Pasqualetti, Fabio; Bullo, Francesco

    2012-01-01

    Cyber-physical systems integrate computation, communication, and physical capabilities to interact with the physical world and humans. Besides failures of components, cyber-physical systems are prone to malignant attacks, and specific analysis tools as well as monitoring mechanisms need to be developed to enforce system security and reliability. This paper proposes a unified framework to analyze the resilience of cyber-physical systems against attacks cast by an omniscient adversary. We model cyber-physical systems as linear descriptor systems, and attacks as exogenous unknown inputs. Despite its simplicity, our model captures various real-world cyber-physical systems, and it includes and generalizes many prototypical attacks, including stealth, (dynamic) false-data injection and replay attacks. First, we characterize fundamental limitations of static, dynamic, and active monitors for attack detection and identification. Second, we provide constructive algebraic conditions to cast undetectable and unidentifia...

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

    International Nuclear Information System (INIS)

    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

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

    International Nuclear Information System (INIS)

    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

  8. 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...

  9. Automatic Medical Image Classification and Abnormality Detection Using KNearest Neighbour

    Directory of Open Access Journals (Sweden)

    Dr. R. J. Ramteke , Khachane Monali Y.

    2012-12-01

    Full Text Available This research work presents a method for automatic classification of medical images in two classes Normal and Abnormal based on image features and automatic abnormality detection. Our proposed system consists of four phases Preprocessing, Feature extraction, Classification, and Post processing. Statistical texture feature set is derived from normal and abnormal images. We used the KNN classifier for classifying image. The KNN classifier performance compared with kernel based SVM classifier (Linear and RBF. The confusion matrix computed and result shows that KNN obtain 80% classification rate which is more than SVM classification rate. So we choose KNN algorithm for classification of images. If image classified as abnormal then post processing step applied on the image and abnormal region is highlighted on the image. The system has been tested on the number of real CT scan brain images.

  10. Detection System Design of Electric Vehicle Wiring Harness

    Institute of Scientific and Technical Information of China (English)

    SUN Jian-Xin; LI Xiao-Peng

    2015-01-01

    This paper introduces a method of harness testing system for electric vehicle wiring harness wiring .The system has implemented some commonly used electric wiring harness state detection using the way of the upper machine and lower machine communicate with each other, Such as normal, open circuit, short circuit, fault, etc. And then the lower machine send the wiring harness status to the upper machine, and then the upper machine parses the line state, and at the same time shows the test results, And then stores the test results in the database. After all, we can call at any time to check the date and the results of detection. It changes the traditional manual test mode of operation and Implements the detection process of automation and intellectualization.

  11. POF hydrogen detection sensor systems for launch vehicles applications

    Science.gov (United States)

    Kazemi, Alex A.; Larson, David B.; Wuestling, Mark D.

    2011-06-01

    This paper describes the first successful Plastic Optical Fiber (POF) cable and glass fiber hydrogen detection sensor systems developed for Delta IV Launch Vehicle. Hydrogen detection in space application is very challenging; the hydrogen detection is priority for rocket industry and every transport device or any application where hydrogen is involved. H2 sensors are necessary to monitor the detection possible leak to avoid explosion, which can be highly dangerous. The hydrogen sensors had to perform in temperatures between -18° C to 60° C (0° F to 140° F). The response of the sensor in this temperature regime was characterized to ensure proper response of the sensors to fugitive hydrogen leakage during vehicle ground operations. We developed the first 75 m combination of POF and glass fiber H2 sensors. Performed detail investigation of POF-glass cables for attenuation loss, thermal, humidity, temperature, shock, accelerate testing for life expectancy. Also evaluated absorption, operating and high/low temperatures, and harsh environmental for glass-POF cables connectors. The same test procedures were performed for glass multi mode fiber part of the H2 and O2 sensors. A new optical waveguides was designed and developed to decrease the impact of both noise and long term drift of sensor. A field testing of sensors was performed at NASA Stennis on the Aerospike X-33 to quantify the element of the sensor package that was responsible for hydrogen detection and temperature.

  12. 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.

  13. Automatic Identification of Metaphoric Utterances

    Science.gov (United States)

    Dunn, Jonathan Edwin

    2013-01-01

    This dissertation analyzes the problem of metaphor identification in linguistic and computational semantics, considering both manual and automatic approaches. It describes a manual approach to metaphor identification, the Metaphoricity Measurement Procedure (MMP), and compares this approach with other manual approaches. The dissertation then…

  14. 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

    2016-01-01

    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. PMID:26907278

  15. Automatic detection of asteroids and meteoroids. A Wide Field Survey

    Science.gov (United States)

    Vereš, P.; Tóth, J.; Jedicke, R.; Tonry, J.; Denneau, L.; Wainscoat, R.; Kornoš, L.; Šilha, J.

    2014-07-01

    We propose a low-cost robotic optical survey aimed at 1-300 m Near Earth Objects (NEO) based on four state-of-the-art telescopes having extremely wide field of view. The small Near-Earth Asteroids (NEA) represent a potential risk but also easily accessible space resources for future robotic or human space in-situ exploration, or commercial activities. The survey system will be optimized for the detection of fast moving-trailed-asteroids, space debris and will provide real-time alert notifications. The expected cost of the system including 1-year development and 2-year operation is 1,000,000 EUR. The successful demonstration of the system will promote cost-effectiveicient ADAM-WFS (Automatic Detection of Asteroids and Meteoroids -- A Wide Field Survey) systems to be built around the world.

  16. Automatic Detection of Asteroids and Meteoroids - A Wide Field Survey

    CERN Document Server

    Vereš, P; Jedicke, R; Tonry, J; Denneau, L; Wainscoat, R; Kornoš, L; Šilha, J

    2014-01-01

    We propose a low-cost robotic optical survey aimed at $1-300$ m Near Earth Objects (NEO) based on four state-of-the-art telescopes having extremely wide field of view. The small Near-Earth Asteroids (NEA) represent a potential risk but also easily accessible space resources for future robotic or human space in-situ exploration, or commercial activities. The survey system will be optimized for the detection of fast moving - trailed - asteroids, space debris and will provide real-time alert notifications. The expected cost of the system including 1-year development and 2-year operation is 1,000,000 EUR. The successful demonstration of the system will promote cost-efficient ADAM-WFS (Automatic Detection of Asteroids and Meteoroids - A Wide Field Survey) systems to be built around the world.

  17. A Novel Morphological Method for Detection and Recognition of Vehicle License Plates

    Directory of Open Access Journals (Sweden)

    S. H.M. Kasaei

    2009-01-01

    Full Text Available Problem statement: License plate detection and recognition is an image-processing technique used to identify a vehicle by its license plate. This notable technology has got multiple applications in various traffic and security cases. To name but a few, toll roads, border control, security and car tracking are same of its applications. The main stage is the isolation of the license plate, from the digital image of the car obtained by a digital camera under different circumstances such as illumination, slop, distance and angle. Approach: This study presented a novel method of identifying and recognizing license plates based on the morphology and template matching. The algorithm started with reprocessing and signal conditioning. Next license plate is localized using morphological operators. Then a template matching scheme will be used to recognize the digits and characters within the plate. Results: The system was tested on Iranian car plate images and the performance was 97.3% of correct plates identification and localization and 92% of correct recognized characters. The results regarding the complexity of the problem and diversity of the test cases showed the high accuracy and robustness of the proposed method. The method could also be applicable for other applications in the transport information systems, where automatic recognition of registration plates, shields, signs and so on is often necessary. Conclusion: This system was customized for the identification of Iranian license plates. The results showed that this algorithm performs well on different types of vehicles including Iranian car and motorcycle plates as well as diverse circumstances. We believe that this system can be redesigned and tested for multi national car license plates in the future time regarding their own attributes.

  18. 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).

  19. AGV技术发展综述%Automatic Guided Vehicles System & Its Application

    Institute of Scientific and Technical Information of China (English)

    张正义

    2005-01-01

    @@ 定义 自动导引车系统AGVS(Automatic GuidedVehicles System)是指由自动导引车AGV和地面导引系统组成的、进行物料搬运作业的光机电信息技术一体化的系统.原美国物流协会对AGV的定义是:装备有电磁或光学等自动导引装置,能够沿规定的导引路径行驶,具有安全保护以及各种移载功能的运输车辆.

  20. 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

  1. Image-Based Vehicle Identification Technology for Homeland Security Applications

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G A

    2002-10-08

    The threat of terrorist attacks against US civilian populations is a very real, near-term problem that must be addressed, especially in response to possible use of Weapons of Mass Destruction. Several programs are now being funded by the US Government to put into place means by which the effects of a terrorist attack could be averted or limited through the use of sensors and monitoring technology. Specialized systems that detect certain threat materials, while effective within certain performance limits, cannot generally be used efficiently to track a mobile threat such as a vehicle over a large urban area. The key elements of an effective system are an image feature-based vehicle identification technique and a networked sensor system. We have briefly examined current uses of image and feature recognition techniques to the urban tracking problem and set forth the outlines of a proposal for application of LLNL technologies to this critical problem. The primary contributions of the proposed work lie in filling important needs not addressed by the current program: (1) The ability to create vehicle ''fingerprints,'' or feature information from images to allow automatic identification of vehicles. Currently, the analysis task is done entirely by humans. The goal is to aid the analyst by reducing the amount of data he/she must analyze and reduce errors caused by inattention or lack of training. This capability has broad application to problems associated with extraction of useful features from large data sets. (2) Improvements in the effectiveness of LLNL's WATS (Wide Area Tracking System) by providing it accurate threat vehicle location and velocity. Model predictability is likely to be enhanced by use of more information related to different data sets. We believe that the LLNL can accomplish the proposed tasks and enhance the effectiveness of the system now under development.

  2. Automatic Kurdish Dialects Identification

    Directory of Open Access Journals (Sweden)

    Hossein Hassani

    2016-02-01

    Full Text Available Automatic dialect identification is a necessary Lan guage Technology for processing multi- dialect languages in which the dialects are linguis tically far from each other. Particularly, this becomes crucial where the dialects are mutually uni ntelligible. Therefore, to perform computational activities on these languages, the sy stem needs to identify the dialect that is the subject of the process. Kurdish language encompasse s various dialects. It is written using several different scripts. The language lacks of a standard orthography. This situation makes the Kurdish dialectal identification more interesti ng and required, both form the research and from the application perspectives. In this research , we have applied a classification method, based on supervised machine learning, to identify t he dialects of the Kurdish texts. The research has focused on two widely spoken and most dominant Kurdish dialects, namely, Kurmanji and Sorani. The approach could be applied to the other Kurdish dialects as well. The method is also applicable to the languages which are similar to Ku rdish in their dialectal diversity and differences.

  3. Development of a Vehicle-Mounted Crop Detection System

    Institute of Scientific and Technical Information of China (English)

    ZHONG Zhen-jiang; SUN Hong; LI Min-zan; ZHANG Feng; LI Xiu-hua

    2014-01-01

    In order to monitor plant chlorophyll content in real-time, a new vehicle-mounted detection system was developed to measure crop canopy spectral characteristics. It was designed to work as a wireless sensor network with one control unit and one measuring unit. The control unit included a personal digital assistant (PDA) device with a ZigBee wireless network coordinator. As the coordinator of the whole wireless network, the control unit was used to receive, display and store all the data sent from sensor nodes. The measuring unit consisted of several optical sensor nodes. All the sensor nodes were mounted on an on-board mechanical structure so that the measuring unit could collect the canopy spectral data while moving. Each sensor node contained four optical channels to measure the light radiation at the wavebands of 550, 650, 766, and 850 nm. The calibration tests veriifed a good performance in terms of the wireless transmission ability and the sensor measurement precision. Both stationary and moving ifeld experiments were also conducted in a winter wheat experimental ifeld. There was a high correlation between chlorophyll content and vegetation index, and several estimation models of the chlorophyll content were established. The highest R2 of the estimation models was 0.718. The results showed that the vehicle-mounted crop detection system has potential for ifeld application.

  4. Automatic sign language identification

    OpenAIRE

    Gebre, B.G.; Wittenburg, P.; Heskes, T.

    2013-01-01

    We propose a Random-Forest based sign language identification system. The system uses low-level visual features and is based on the hypothesis that sign languages have varying distributions of phonemes (hand-shapes, locations and movements). We evaluated the system on two sign languages -- British SL and Greek SL, both taken from a publicly available corpus, called Dicta Sign Corpus. Achieved average F1 scores are about 95% - indicating that sign languages can be identified with high accuracy...

  5. BY USING BLUETOOTH TECHNOLOGY AUTOMATIC VEHICLE ACCIDENT DETECTION & LOCALIZATION OF AUTOMOBILE

    OpenAIRE

    Nitin Thakre; Nitin Raut; Shyam Dubey; Abdulla Shaikh

    2014-01-01

    Traffic accidents are one of the leading causes of fatalities in the world. An important indicator of survival rates after an accident is the time between the accident and when emergency medical personnel are dispatched to the location. Eliminating the time between when an accident occurs and when first responders are dispatched to the location decreases mortality rates by 6%. We propose an Android based application that location of the vehicle through an positive detectio...

  6. Incipient fault detection and identification in process systems using accelerating neural network learning

    International Nuclear Information System (INIS)

    The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary

  7. A multimodal temporal panorama approach for moving vehicle detection, reconstruction, and classification

    Science.gov (United States)

    Wang, Tao; Zhu, Zhigang

    2012-06-01

    Moving vehicle detection and classification using multimodal data is a challenging task in data collection, audio-visual alignment, data labeling and feature selection under uncontrolled environments with occlusions, motion blurs, varying image resolutions and perspective distortions. In this work, we propose an effective multimodal temporal panorama approach for the task using a novel long-range audio-visual sensing system. A new audio-visual vehicle (AVV) dataset for moving vehicle detection and classification is created, which features automatic vehicle detection and audio-visual alignment, accurate vehicle extraction and reconstruction, and efficient data labeling. In particular, vehicles' visual images are reconstructed once detected in order to remove most of the occlusions, motion blurs, and variations of perspective views. Multimodal audio-visual features are extracted, including global geometric features (aspect ratios, profiles), local structure features (HOGs), as well various audio features (MFCCs, etc). Using radial-based SVMs, the effectiveness of the integration of these multimodal features is thoroughly and systemically studied. The concept of MTP may not be only limited to visual, motion and audio modalities; it could also be applicable to other sensing modalities that can obtain data in the temporal domain.

  8. 基于RFID的车辆自动化智能管理系统研究%Research of vehicle automatic management system based on RFID

    Institute of Scientific and Technical Information of China (English)

    张丽然; 沈胜利

    2012-01-01

    In order to solve the current residential parking problem,the residential vehicle automatic management system is designed based on ETC technology. With the analysis of the actual demand, the system includes three parts: vehicle out and in management, vehicle positioning management and vehicle parking management. The vehicle out and in management system could identify and confirm the vehicles going into the community automatically; vehicle positioning management system is responsible for tracking and positioning the vehicle in the community; vehicle parking management system would assign and unlock the parking space for the vehicle automatically. After practices, it proves that the system has good performance and practical value.%基于解决当前小区停车难问题的目的,采用ETC电子不停车收费相关技术,设计了小区车辆自动化管理系统;通过对实际需求的分析,所设计的系统主要包括3个部分:车辆出入管理、定位管理以及停车管理。其中,车辆出入管理系统对进入的车辆进行身份的自动识别和确认;车辆定位管理系统负责对在小区申行驶的车辆进行追踪定位;车辆停车管理系统则为进入的车辆自动分配车住和开启车位锁。经过实践的证明,本系统性能良好,具有较好的实用价值。

  9. Automatic Tracking System of Vehicles Based on GPS and GSM%基于GPS和GSM的车辆自动跟踪系统

    Institute of Scientific and Technical Information of China (English)

    袁卫

    2011-01-01

    采用STC公司的STC12C5A60S2单片机为控制核心,在车辆被盗的情况下,利用GPS卫星定位系统确定车辆的位置,然后通过GSM网络将车辆的位置以短息的方式发送到车主指定的手机中,车主可远程控制使系统自动切断汽车内的点火电路,从而实现防盗功能。%The paper provides a system to ascertain vehicles' position by Global Position System in the case of vehicle theft, which taking STC12C5A60S2 microcomputer of STC company as control core and making use of GSM network to send position information of vehicl

  10. Automotive Control Systems: For Engine, Driveline, and Vehicle

    Science.gov (United States)

    Kiencke, Uwe; Nielsen, Lars

    Advances in automotive control systems continue to enhance safety and comfort and to reduce fuel consumption and emissions. Reflecting the trend to optimization through integrative approaches for engine, driveline, and vehicle control, this valuable book enables control engineers to understand engine and vehicle models necessary for controller design, and also introduces mechanical engineers to vehicle-specific signal processing and automatic control. The emphasis on measurement, comparisons between performance and modeling, and realistic examples derive from the authors' unique industrial experience

  11. System for Automatic Detection of Clustered Microcalcifications in Digital Mammograms

    Science.gov (United States)

    Bazzani, A.; Bollini, D.; Brancaccio, R.; Campanini, R.; Lanconelli, N.; Romani, D.; Bevilacqua, A.

    In this paper, we investigate the performance of a Computer Aided Diagnosis (CAD) system for the detection of clustered microcalcifications in mammograms. Our detection algorithm consists of the combination of two different methods. The first, based on difference-image techniques and gaussianity statistical tests, finds out the most obvious signals. The second, is able to discover more subtle microcalcifications by exploiting a multiresolution analysis by means of the wavelet transform. We can separately tune the two methods, so that each one of them is able to detect signals with similar features. By combining signals coming out from the two parts through a logical OR operation, we can discover microcalcifications with different characteristics. Our algorithm yields a sensitivity of 91.4% with 0.4 false positive cluster per image on the 40 images of the Nijmegen database.

  12. Automatic and Direct Identification of Blink Components from Scalp EEG

    Directory of Open Access Journals (Sweden)

    Guojun Dai

    2013-08-01

    Full Text Available Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA. Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn’t need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects.

  13. Automatic and direct identification of blink components from scalp EEG.

    Science.gov (United States)

    Kong, Wanzeng; Zhou, Zhanpeng; Hu, Sanqing; Zhang, Jianhai; Babiloni, Fabio; Dai, Guojun

    2013-08-16

    Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn't need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects.

  14. Automatic guided vehicle contributing to physical distribution of automobile parts; Butsuryu no jidoka ni kokensuru jidosha buhin mujin hanso system

    Energy Technology Data Exchange (ETDEWEB)

    Inaba, E. [Meidensha Corp., Tokyo (Japan)

    1997-06-30

    This paper presents one example of the unmanned carrying systems using the small automatic guided vehicles (AGV) recently delivered by Meidensha Corp. This system carries hand trucks or buckets loaded with such small parts for automobile engines as sensor and connector by the AGVs. The following abilities were required in adoption of this system: (1) Indication of destinations to several AGVs coming from different lines, and monitoring of traveling conditions of every AGV, (2) The optimum traveling/waiting control between AGVs at crossings, and (3) Hand truck carrying in consideration of an importance of safety. This system allows integrated control of ten and several AGVs using the AGV control board through the stationary radio control station and radio equipment on AGVs. In addition, this system allows indicating communication of destinations to AGVs, and realtime control of AGV traveling conditions. Waiting control of entrance/exit by intercommunication between AGVs is also possible. 7 figs., 2 tabs.

  15. Infrasound array criteria for automatic detection and front velocity estimation of snow avalanches: towards a real-time early-warning system

    Directory of Open Access Journals (Sweden)

    E. Marchetti

    2015-04-01

    Full Text Available Avalanche risk management is strongly related to the ability to identify and timely report the occurrence of snow avalanches. Infrasound has been applied to avalanche research and monitoring for the last 20 years but it never turned into an operational tool for the ambiguity to identify clear signals related to avalanches. We present here a new method based on the analysis of infrasound signals recorded by a small aperture array in Ischgl (Austria, which overcome now this limit. The method is based on array derived wave parameters, such as back-azimuth and apparent velocity. The method defines threshold criteria for automatic avalanche identification considering avalanches as a moving source of infrasound. We validate efficiency of the automatic infrasound detection with continuous observations with Doppler Radar and we show how dynamics parameters such as the velocity of a snow avalanche in any given path around the array can be efficiently derived. Our results indicate that a proper infrasound array analysis allows a robust, real-time, remote detection of snow avalanches that could thus contribute significantly to avalanche forecast and risk management.

  16. Automatic zebrafish heartbeat detection and analysis for zebrafish embryos.

    Science.gov (United States)

    Pylatiuk, Christian; Sanchez, Daniela; Mikut, Ralf; Alshut, Rüdiger; Reischl, Markus; Hirth, Sofia; Rottbauer, Wolfgang; Just, Steffen

    2014-08-01

    A fully automatic detection and analysis method of heartbeats in videos of nonfixed and nonanesthetized zebrafish embryos is presented. This method reduces the manual workload and time needed for preparation and imaging of the zebrafish embryos, as well as for evaluating heartbeat parameters such as frequency, beat-to-beat intervals, and arrhythmicity. The method is validated by a comparison of the results from automatic and manual detection of the heart rates of wild-type zebrafish embryos 36-120 h postfertilization and of embryonic hearts with bradycardia and pauses in the cardiac contraction.

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

    Science.gov (United States)

    Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing

    2015-01-01

    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%. PMID:25894940

  18. 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%.

  19. An ultrasonic sensor system based on a two-dimensional state method for highway vehicle violation detection applications.

    Science.gov (United States)

    Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing

    2015-01-01

    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%. PMID:25894940

  20. 33 CFR 401.20 - Automatic Identification System.

    Science.gov (United States)

    2010-07-01

    ... close to the primary conning position in the navigation bridge and a standard 120 Volt, AC, 3-prong power receptacle accessible for the pilot's laptop computer; and (5) The Minimum Keyboard Display (MKD) shall be located as close as possible to the primary conning position and be visible; (6) Computation...

  1. Automatic landslide and mudflow detection method via multichannel sparse representation

    Science.gov (United States)

    Chao, Chen; Zhou, Jianjun; Hao, Zhuo; Sun, Bo; He, Jun; Ge, Fengxiang

    2015-10-01

    Landslide and mudflow detection is an important application of aerial images and high resolution remote sensing images, which is crucial for national security and disaster relief. Since the high resolution images are often large in size, it's necessary to develop an efficient algorithm for landslide and mudflow detection. Based on the theory of sparse representation and, we propose a novel automatic landslide and mudflow detection method in this paper, which combines multi-channel sparse representation and eight neighbor judgment methods. The whole process of the detection is totally automatic. We make the experiment on a high resolution image of ZhouQu district of Gansu province in China on August, 2010 and get a promising result which proved the effective of using sparse representation on landslide and mudflow detection.

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

    Science.gov (United States)

    Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

    2016-01-01

    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. PMID:27347978

  3. 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.

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

    Science.gov (United States)

    Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

    2016-06-25

    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.

  5. Development of a new automatic incident detection system for freeways using a bi-classifier approach

    Energy Technology Data Exchange (ETDEWEB)

    Razavi, A.

    1998-12-31

    The development and assessment of a new automatic incident detection (AID) system for traffic management authorities was presented. The AID is designed to provide early response to traffic delays caused by traffic incidents. This newly proposed AID system makes effective use of information obtained from people travelling in the opposite direction of the traffic jam. The method was tested on a stretch of the Trans-Canada Highway and was used to develop a simulation model. A comparison of the new method with two other in-use systems showed that it is possible to reduce the detection time by about 40 per cent.

  6. Automatic Pipeline Surveillance Air-Vehicle

    OpenAIRE

    Alqaan, Hani

    2016-01-01

    This thesis presents the developments of a vision-based system for aerial pipeline Right-of-Way surveillance using optical/Infrared sensors mounted on Unmanned Aerial Vehicles (UAV). The aim of research is to develop a highly automated, on-board system for detecting and following the pipelines; while simultaneously detecting any third-party interference. The proposed approach of using a UAV platform could potentially reduce the cost of monitoring and surveying pipelines when...

  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. Automatic Identification of Silence, Unvoiced and Voiced Chunks in Speech

    Directory of Open Access Journals (Sweden)

    Poonam Sharma

    2013-05-01

    Full Text Available The objective of this work is to automatically seg ment the speech signal into silence, voiced and unvoiced regions which are very beneficial in incre asing the accuracy and performance of recognition systems. Proposed algorithm is based on three important characteristics of speech signal namely Zero Crossing Rate, Short Time Energy and Fundamental Frequency. The performance of the proposed algorithm is evaluated using the data collected from four different speakers and an overall accuracy of 96.61 % is achi eved.

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

    OpenAIRE

    Bohui Zhu; Yongsheng Ding; Kuangrong Hao

    2013-01-01

    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 ...

  10. 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)

  11. Automatic detection and analysis of nuclear plant malfunctions

    International Nuclear Information System (INIS)

    In this paper a system is proposed, which performs dynamically the detection and analysis of malfunctions in a nuclear plant. The proposed method was developed and implemented on a Reactor Simulator, instead of on a real one, thus allowing a wide range of tests. For all variables under control, a simulation module was identified and implemented on the reactor on-line computer. In the malfunction identification phase all modules run separately, processing plant input variables and producing their output variable in Real-Time; continuous comparison of the computed variables with plant variables allows malfunction's detection. At this moment the second phase can occur: when a malfunction is detected, all modules are connected, except the module simulating the wrong variable, and a fast simulation is carried on, to analyse the consequences. (author)

  12. Automatic character detection and segmentation in natural scene images

    Institute of Scientific and Technical Information of China (English)

    ZHU Kai-hua; QI Fei-hu; JIANG Ren-jie; XU Li

    2007-01-01

    We present a robust connected-component (CC) based method for automatic detection and segmentation of text in real-scene images. This technique can be applied in robot vision, sign recognition, meeting processing and video indexing. First, a Non-Linear Niblack method (NLNiblack) is proposed to decompose the image into candidate CCs. Then, all these CCs are fed into a cascade of classifiers trained by Adaboost algorithm. Each classifier in the cascade responds to one feature of the CC. Proposed here are 12 novel features which are insensitive to noise, scale, text orientation and text language. The classifier cascade allows non-text CCs of the image to be rapidly discarded while more computation is spent on promising text-like CCs. The CCs passing through the cascade are considered as text components and are used to form the segmentation result. A prototype system was built,with experimental results proving the effectiveness and efficiency of the proposed method.

  13. Front and Rear Vehicle Detection Using Hypothesis Generation and Verification

    Directory of Open Access Journals (Sweden)

    Nima Khairdoost

    2013-08-01

    Full Text Available Vehicle detection in traffic scenes is an important issue in driver assistance systems and self-guidedvehicles that includes two stages of Hypothesis Generation (HG and Hypothesis Verification (HV. Theboth stages are important and challenging. In the first stage, potential vehicles are hypothesized and in thesecond stage, all hypotheses are verified and classified into vehicle and non-vehicle classes. In this paper,we present a method for detecting front and rear on-road vehicles without lane information and priorknowledge about the position of the road. In the HG stage, a three-step method including shadow, textureand symmetry clues is applied. In the HV stage, we extract Pyramid Histograms of Oriented Gradients(PHOG features from a traffic image as basic features to detect vehicles. Principle Component Analysis(PCA is applied to these PHOG feature vectors as a dimension reduction tool to obtain the PHOG-PCAvectors. Then, we use Genetic Algorithm (GA and linear Support Vector Machine (SVM to improve theperformance and generalization of the PHOG-PCA features. Experimental results of the proposed HVstage showed good classification accuracy of more than 97% correct classification on realistic on-roadvehicle dataset images and also it has better classification accuracy in comparison with other approaches.

  14. Design of an Integrated Vehicle Chassis Control System with Driver Behavior Identification

    OpenAIRE

    Bing Zhu; Yizhou Chen; Jian Zhao; Yunfu Su

    2015-01-01

    An integrated vehicle chassis control strategy with driver behavior identification is introduced in this paper. In order to identify the different types of driver behavior characteristics, a driver behavior signals acquisition system was established using the dSPACE real-time simulation platform, and the driver inputs of 30 test drivers were collected under the double lane change test condition. Then, driver behavior characteristics were analyzed and identified based on the preview optimal cu...

  15. Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.

    Science.gov (United States)

    Baran Pouyan, Maziyar; Birjandtalab, Javad; Nourani, Mehrdad; Matthew Pompeo, M D

    2016-08-01

    Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. PMID:27268736

  16. 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.

  17. An Automatic Impact-based Delamination Detection System for Concrete Bridge Decks

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Gang; Harichandran, Ronald S.; Ramuhalli, Pradeep

    2012-01-02

    Delamination of concrete bridge decks is a commonly observed distress in corrosive environments. In traditional acoustic inspection methods, delamination is assessed by the "hollowness" of the sound created by impacting the bridge deck with a hammer or bar or by dragging a chain where the signals are often contaminated by ambient traffic noise and the detection is highly subjective. In the proposed method, a modified version of independent component analysis (ICA) is used to filter the traffic noise. To eliminate subjectivity, Mel-frequency cepstral coefficients (MFCC) are used as features for detection and the delamination is detected by a radial basis function (RBF) neural network. Results from both experimental and field data suggest that the proposed methods id noise robust and has satisfactory performance. The methods can also detect the delamination of repair patches and concrete below the repair patches. The algorithms were incorporated into an automatic impact-bases delamination detection (AIDD) system for field application.

  18. Protokol Interchangeable Data pada VMeS (Vessel Messaging System dan AIS (Automatic Identification System

    Directory of Open Access Journals (Sweden)

    Farid Andhika

    2012-09-01

    Full Text Available VMeS (Vessel Messaging System merupakan komunikasi berbasis radio untuk mengirimkan pesan antara VMeS terminal kapal di laut dengan VMeS gateway di darat. Dalam perkembangan sistem monitoring kapal di laut umumnya menggunakan AIS (Automatic Identification System yang telah digunakan di seluruh pelabuhan untuk memantau kondisi kapal dan mencegah tabrakan antar kapal. Dalam penelitian ini akan dirancang format data yang sesuai untuk VMeS agar bisa dilakukan proses interchangeable ke AIS sehingga bisa dibaca oleh AIS receiver yang ditujukan untuk kapal dengan ukuran dibawah 30 GT (Gross Tonnage. Format data VmeS dirancang dalam tiga jenis yaitu data posisi, data informasi kapal dan data pesan pendek yang akan dilakukan interchangeable dengan AIS tipe 1,4 dan 8. Pengujian kinerja sistem interchangeable menunjukkan bahwa dengan peningkatan periode pengiriman pesan maka lama delay total meningkat tetapi packet loss menurun. Pada pengiriman pesan setiap 5 detik dengan kecepatan 0-40 km/jam, 96,67 % data dapat diterima dengan baik. Data akan mengalami packet loss jika level daya terima dibawah -112 dBm . Jarak terjauh yang dapat dijangkau modem dengan kondisi bergerak yaitu informatika ITS dengan jarak 530 meter terhadap Laboratorium B406 dengan level daya terima -110 dBm.

  19. An improvement in rollover detection of articulated vehicles using the grey system theory

    Science.gov (United States)

    Chou, Tao; Chu, Tzyy-Wen

    2014-05-01

    A Rollover Index combined with the grey system theory, called a Grey Rollover Index (GRI), is proposed to assess the rollover threat for articulated vehicles with a tractor-semitrailer combination. This index can predict future trends of vehicle dynamics based on current vehicle motion; thus, it is suitable for vehicle-rollover detection. Two difficulties are encountered when applying the GRI for rollover detection. The first difficulty is effectively predicting the rollover threat of the vehicles, and the second difficulty is achieving a definite definition of the real rollover timing of a vehicle. The following methods are used to resolve these problems. First, a nonlinear mathematical model is constructed to accurately describe the vehicle dynamics of articulated vehicles. This model is combined with the GRI to predict rollover propensity. Finally, TruckSim™ software is used to determine the real rollover timing and facilitate the accurate supply of information to the rollover detection system through the GRI. This index is used to verify the simulation based on the common manoeuvres that cause rollover accidents to reduce the occurrence of false signals and effectively increase the efficiency of the rollover detection system.

  20. Gust Front Statistical Characteristics and Automatic Identification Algorithm for CINRAD

    Institute of Scientific and Technical Information of China (English)

    郑佳锋; 张杰; 朱克云; 刘黎平; 刘艳霞

    2014-01-01

    Gust front is a kind of meso-and micro-scale weather phenomenon that often causes serious ground wind and wind shear. This paper presents an automatic gust front identification algorithm. Totally 879 radar volume-scan samples selected from 21 gust front weather processes that occurred in China between 2009 and 2012 are examined and analyzed. Gust front echo statistical features in reflectivity, velocity, and spectrum width fields are obtained. Based on these features, an algorithm is designed to recognize gust fronts and generate output products and quantitative indices. Then, 315 samples are used to verify the algorithm and 3 typical cases are analyzed. Major conclusions include: 1) for narrow band echoes intensity is between 5 and 30 dBZ, widths are between 2 and 10 km, maximum heights are less than 4 km (89.33%are lower than 3 km), and the lengths are between 50 and 200 km. The narrow-band echo is higher than its surrounding echo. 2) Gust fronts present a convergence line or a wind shear in the velocity field;the frontal wind speed gradually decreases when the distance increases radially outward. Spectral widths of gust fronts are large, with 87.09% exceeding 4 m s-1 . 3) Using 315 gust front volume-scan samples to test the algorithm reveals that the algorithm is highly stable and has successfully recognized 277 samples. The algorithm also works for small-scale or weak gust fronts. 4) Radar data quality has certain impact on the algorithm.

  1. 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.

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

    International Nuclear Information System (INIS)

    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 × 106 copies

  3. Automatic detection of architectural violations in evolutionary systems

    OpenAIRE

    Albuquerque, Diego de Lara e

    2014-01-01

    Software applications evolve over the years at a cost: their architecture modularity tends to be degraded. This happens mainly because software application maintenance often leads to architectural degradation. In this context, software architects need to elaborate strategies for detecting architectural degradation symptoms and thus maintaining the software architectural quality. The elaborations of these strategies often rely on tools with domain-specific languages (DSLs), which help them to ...

  4. Practical automatic Arabic license plate recognition system

    Science.gov (United States)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

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

    Science.gov (United States)

    Bockelmann, Thomas R.; Hope, Mark E.; Zou, Zhanjiang; Kang, Xiaosong

    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.

  6. Automatic identification of origins of left and right coronary arteries in CT angiography for coronary arterial tree tracking and plaque detection

    Science.gov (United States)

    Zhou, Chuan; Chan, Heang-Ping; Chightai, Aamer; Wei, Jun; Hadjiiski, Lubomir M.; Agarwal, Prachi; Kuriakose, Jean W.; Kazerooni, Ella A.

    2013-03-01

    Automatic tracking and segmentation of the coronary arterial tree is the basic step for computer-aided analysis of coronary disease. The goal of this study is to develop an automated method to identify the origins of the left coronary artery (LCA) and right coronary artery (RCA) as the seed points for the tracking of the coronary arterial trees. The heart region and the contrast-filled structures in the heart region are first extracted using morphological operations and EM estimation. To identify the ascending aorta, we developed a new multiscale aorta search method (MAS) method in which the aorta is identified based on a-priori knowledge of its circular shape. Because the shape of the ascending aorta in the cCTA axial view is roughly a circle but its size can vary over a wide range for different patients, multiscale circularshape priors are used to search for the best matching circular object in each CT slice, guided by the Hausdorff distance (HD) as the matching indicator. The location of the aorta is identified by finding the minimum HD in the heart region over the set of multiscale circular priors. An adaptive region growing method is then used to extend the above initially identified aorta down to the aortic valves. The origins at the aortic sinus are finally identified by a morphological gray level top-hat operation applied to the region-grown aorta with morphological structuring element designed for coronary arteries. For the 40 test cases, the aorta was correctly identified in 38 cases (95%). The aorta can be grown to the aortic root in 36 cases, and 36 LCA origins and 34 RCA origins can be identified within 10 mm of the locations marked by radiologists.

  7. Automatic Number Plate Recognition System

    OpenAIRE

    Rajshree Dhruw; Dharmendra Roy

    2014-01-01

    Automatic Number Plate Recognition (ANPR) is a mass surveillance system that captures the image of vehicles and recognizes their license number. The objective is to design an efficient automatic authorized vehicle identification system by using the Indian vehicle number plate. In this paper we discus different methodology for number plate localization, character segmentation & recognition of the number plate. The system is mainly applicable for non standard Indian number plates by recognizing...

  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 mea

  9. Diagnostic performance of a commercially available computer-aided diagnosis system for automatic detection of pulmonary nodules: comparison with single and double reading

    International Nuclear Information System (INIS)

    Objective: To assess the diagnostic performance of a commercially available computer-aided diagnosis (CAD) system for automatic detection of pulmonary nodules with multi-row detector CT scans compared to single and double reading by radiologists. Materials and Methods: A CAD system for automatic nodule detection (Siemens LungCare NEV VB10) was applied to four-detector row low-dose CT (LDCT) performed on nine patients with pulmonary metastases and compared to the findings of three radiologists. A standard-dose CT (SDCT) was acquired simultaneously and used for establishing the reference data base. The study design was approved by the Institutional Review Board and the appropriate German authorities. The reference data base consisted of 457 nodules (mean size 3.9±3.1 mm) and was established by fusion of the sets of nodules detected by three radiologists independently reading LDCT and SDCT and by CAD. An independent radiologist used thin slices to eliminate false positive findings from the reference base. Results: An average sensitivity of 54% (range 51% to 55%) was observed for single reading by one radiologist. CAD demonstrated a similar sensitivity of 55%. Double reading by two radiologists increased the sensitivity to an average of 67% (range 67% to 68%). The difference to single reading was significant (p<0.001). CAD as second opinion after single reading increased the sensitivity to 79% (range 77% to 81%), which proved to be significantly better than double reading (p<0.001). CAD produced more false positive results (7.2%) than human readers but it was acceptable in clinical routine. (orig.)

  10. Fundamental problems in fault detection and identification

    DEFF Research Database (Denmark)

    Saberi, A.; Stoorvogel, A. A.; Sannuti, P.;

    2000-01-01

    A number of different fundamental problems in fault detection and fault identification are formulated in this paper. The fundamental problems include exact, almost, generic and class-wise fault detection and identification. Necessary and sufficient conditions for the solvability of the fundamental...

  11. A ROBUST GA/KNN BASED HYPOTHESIS VERIFICATION SYSTEM FOR VEHICLE DETECTION

    Directory of Open Access Journals (Sweden)

    Nima Khairdoost

    2015-03-01

    Full Text Available Vehicle detection is an important issue in driver assistance systems and self-guided vehicles that includes two stages of hypothesis generation and verification. In the first stage, potential vehicles are hypothesized and in the second stage, all hypothesis are verified. The focus of this work is on the second stage. We extract Pyramid Histograms of Oriented Gradients (PHOG features from a traffic image as candidates of feature vectors to detect vehicles. Principle Component Analysis (PCA and Linear Discriminant Analysis (LDA are applied to these PHOG feature vectors as dimension reduction and feature selection tools parallelly. After feature fusion, we use Genetic Algorithm (GA and cosine similarity-based K Nearest Neighbor (KNN classification to improve the performance and generalization of the features. Our tests show good classification accuracy of more than 97% correct classification on realistic on-road vehicle images.

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

    Science.gov (United States)

    Yoshida, Wataru; Kezuka, Aki; Murakami, Yoshiyuki; Lee, Jinhee; Abe, Koichi; Motoki, Hiroaki; Matsuo, Takafumi; Shimura, Nobuaki; Noda, Mamoru; Igimi, Shizunobu; Ikebukuro, Kazunori

    2013-11-01

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

  13. People Detection and Re-Identification in Complex Environments

    Science.gov (United States)

    Truong Cong, Dung-Nghi; Khoudour, Louahdi; Achard, Catherine; Douadi, Lounis

    This paper presents an automatic system for detecting and re-identifying people moving in different sites with non-overlapping views. We first propose an automatic process for silhouette extraction based on the combination of an adaptive background subtraction algorithm and a motion detection module. Such a combination takes advantage of both approaches and is able to tackle the problem of particular environments. The silhouette extraction results are then clustered based on their spatial belonging and colorimetric characteristics in order to preserve only the key regions that effectively represent the appearance of a person. The next important step consists in characterizing the extracted silhouettes by the appearance-based signatures. Our proposed descriptor, which includes both color and spatial feature of objects, leads to satisfying results compared to other descriptors in the literature. Since the passage of a person needs to be characterized by multiple frames, a large quantity of data has to be processed. Thus, a graph-based algorithm is used to realize the comparison of passages of people in front of cameras and to make the final decision of re-identification. The global system is tested on two real and difficult data sets recorded in very different environments. The experimental results show that our proposed system leads to very satisfactory results.

  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. Design of automatic leveling and centering system of theodolite

    Science.gov (United States)

    Liu, Chun-tong; He, Zhen-Xin; Huang, Xian-xiang; Zhan, Ying

    2012-09-01

    To realize the theodolite automation and improve the azimuth Angle measurement instrument, the theodolite automatic leveling and centering system with the function of leveling error compensation is designed, which includes the system solution, key components selection, the mechanical structure of leveling and centering, and system software solution. The redesigned leveling feet are driven by the DC servo motor; and the electronic control center device is installed. Using high precision of tilt sensors as horizontal skew detection sensors ensures the effectiveness of the leveling error compensation. Aiming round mark center is located using digital image processing through surface array CCD; and leveling measurement precision can reach the pixel level, which makes the theodolite accurate centering possible. Finally, experiments are conducted using the automatic leveling and centering system of the theodolite. The results show the leveling and centering system can realize automatic operation with high centering accuracy of 0.04mm.The measurement precision of the orientation angle after leveling error compensation is improved, compared with that of in the traditional method. Automatic leveling and centering system of theodolite can satisfy the requirements of the measuring precision and its automation.

  16. 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.

  17. Vehicle Theft Alert and Location Identification Using GSM, GPS and Web Technologies

    Directory of Open Access Journals (Sweden)

    Garba Suleiman

    2016-07-01

    Full Text Available Insecurity is one of the major challenges that the entire world is facing now, each country having their peculiar security issues. The crime rate in every part of the society these days has become a threatening issue such that vehicles are now used for committing criminal activities more than before. The issue of vehicle theft has increased tremendously, mostly at gunpoint or car parks. In view of these, there is a need for adequate records of stolen, identified and recovered vehicles which are not readily available in our society and as such very important. The development of a vehicle theft alert and location identification system becomes more necessary for vehicle owners to ensure theft prevention and a speedy identification towards recovery efforts in situations where a vehicle is missing, stolen or driven by an unauthorized person. The theft alert function makes use of a GSM application developed and installed in a mobile phone device which is embedded in the vehicle to communicate with the vehicle owner’s mobile phone. The communication is established via SMS (i.e. between the installed mobile phone device and that of the vehicle owner. The communications established include; (i. Sending an SMS alert from installed mobile phone device to vehicle owner mobile phone when the car ignition is put on. (ii. Sending an SMS from the vehicle owner’s mobile phone to start and stop the installed mobile phone device application. The location identification function makes use of a web application developed to; (i. Determine the real time location of a vehicle by means of tracking using GPS. (ii. Broadcast missing or stolen vehicle information to social media and security agency. The implementation of the installed mobile phone device application was done using JAVA because of its capabilities in programming mobile applications while PHP and MySQL was used for the web application functions. Integration testing of the system was carried out using

  18. Single-beam water vapor detection system with automatic photoelectric conversion gain control

    Science.gov (United States)

    Zhu, C. G.; Chang, J.; Wang, P. P.; Wang, Q.; Wei, W.; Liu, Z.; Zhang, S. S.

    2014-11-01

    A single-beam optical sensor system with automatic photoelectric conversion gain control is proposed for doing high reliability water vapor detection under relatively rough environmental conditions. Comparing to a dual-beam system, it can distinguish the finer photocurrent variations caused by the optical power drift and provide timely compensation by automatically adjusting the photoelectric conversion gain. This system can be rarely affected by the optical power drift caused by fluctuating ambient temperature or variation of fiber bending loss. The deviation of the single-beam system is below 1.11% when photocurrent decays due to fiber bending loss for bending radius of 5 mm, which is obviously lower than the dual-beam system (8.82%). We also demonstrate the long-term stability of the single-beam system by monitoring a 660 ppm by volume (ppmv) water vapor sample continuously for 24 h. The maximum deviation of the measured concentration during the whole testing period does not exceed 10 ppmv. Experiments have shown that the new system features better reliability and is more apt for remote sensing application which is often subject to light transmission loss.

  19. Automatic identification technology tracking weapons and ammunition for the Norwegian Armed Forces

    OpenAIRE

    Lien, Tord Hjalmar.

    2011-01-01

    Approved for public release; distribution is unlimited. The purpose of this study is to recommend technology and solutions that improve the accountability and accuracy of small arms and ammunition inventories in the Norwegian Armed Forces (NAF). Radio Frequency Identification (RFID) and Item Unique Identification (IUID) are described, and challenges and benefits of these two major automatic identification technologies are discussed. A case study for the NAF is conducted where processes a...

  20. Automatic detection of articulation disorders in children with cleft lip and palate.

    Science.gov (United States)

    Maier, Andreas; Hönig, Florian; Bocklet, Tobias; Nöth, Elmar; Stelzle, Florian; Nkenke, Emeka; Schuster, Maria

    2009-11-01

    Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement (kappa approximately 0.6) for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.

  1. Automatic verbal aggression detection for Russian and American imageboards

    OpenAIRE

    Gordeev, Denis

    2016-01-01

    The problem of aggression for Internet communities is rampant. Anonymous forums usually called imageboards are notorious for their aggressive and deviant behaviour even in comparison with other Internet communities. This study is aimed at studying ways of automatic detection of verbal expression of aggression for the most popular American (4chan.org) and Russian (2ch.hk) imageboards. A set of 1,802,789 messages was used for this study. The machine learning algorithm word2vec was applied to de...

  2. 被淹没地震信号的小波熵检测与自动识别方法%METHOD OF DETECTION BY WAVELET ENTROPY AND IDENTIFICATION AUTOMATICALLY FOR SUBMERGED SEISMIC SIGNAL

    Institute of Scientific and Technical Information of China (English)

    杨建平; 帅晓勇; 陶黄林

    2015-01-01

    In order to detect the micro-seismic before large earthquake, protect the important facilities, such as the large coal, oil, mine and so on. It’s an urgent need for seismic data processing technique, such as real-time process, recognize automatically and extract the submerged seismic onset point. A multi-resolution complexity parameter was acquired based on the wavelet transform and the theory of information entropy, the parameter can clearly shows the change in the exploration data from the arrivals of seismic waves. A simulation was done with the exploration data, Comparison of the monitoring effect of wavelet transform or digital band-pass filter, the results show that the parameter can be very good at the micro seismic onset point for automatic identification.%为探测大震前的微震,保护大型煤矿、油田和矿山等重要设施,急需地震信号的实时处理、自动识别和提取地震初至点等地震数据处理技术。采用了小波变换和信息熵理论相结合的一种具有多分辨率的复杂度参数——小波熵,该参数能够从被淹没环境中清晰地显示出勘探数据中地震波到达所带来的变化。结合实测数据进行了仿真,并对比了单一的小波变换、数字带通滤波器的监测效果,结果表明小波熵参数能够更好地自动识别微震初至点。

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Aircraft noise effects on sleep: a systematic comparison of EEG awakenings and automatically detected cardiac activations

    International Nuclear Information System (INIS)

    Polysomnography is the gold standard for investigating noise effects on sleep, but data collection and analysis are sumptuous and expensive. We recently developed an algorithm for the automatic identification of cardiac activations associated with cortical arousals, which uses heart rate information derived from a single electrocardiogram (ECG) channel. We hypothesized that cardiac activations can be used as estimates for EEG awakenings. Polysomnographic EEG awakenings and automatically detected cardiac activations were systematically compared using laboratory data of 112 subjects (47 male, mean ± SD age 37.9 ± 13 years), 985 nights and 23 855 aircraft noise events (ANEs). The probability of automatically detected cardiac activations increased monotonically with increasing maximum sound pressure levels of ANEs, exceeding the probability of EEG awakenings by up to 18.1%. If spontaneous reactions were taken into account, exposure–response curves were practically identical for EEG awakenings and cardiac activations. Automatically detected cardiac activations may be used as estimates for EEG awakenings. More investigations are needed to further validate the ECG algorithm in the field and to investigate inter-individual differences in its ability to predict EEG awakenings. This inexpensive, objective and non-invasive method facilitates large-scale field studies on the effects of traffic noise on sleep

  8. 基于ZigBee+GMR的车辆检测系统的设计%Design of Vehicle Detection System Based on ZigBee and GMR

    Institute of Scientific and Technical Information of China (English)

    邱意敏; 周力

    2012-01-01

    According to the problems of roadside stop,a vehicle detection system based on ZigBee and GMR is designed. In this paper, the giant magnetoresistance effect of giant magnetoresistance (GMR) sensors is used to detect vehicle information. The existence of a vehicle and the vehicle classification can be detected by processed data of MCU, and MCU uses ZigBee, which is a new kind of wireless access technology, to transmit the processed data to a portable charging machine. And then the portable charging machine transmits the information of parking occupancy to the roadside controller. So it can display the number of parking spaces and query parking status. At the same time, the vehicle detection system can make the portable charging machine record the vehicle type and parking time accurately.%针对路边停车存在的问题,提出了一种基于ZigBee+ GMR的车辆检测系统.首先,利用巨磁电阻传感器的巨磁效应检测车辆相关信息,并通过单片机处理数据以检测车辆的存在和识别车辆的类型;接着,利用新型的短距离无线接入技术ZigBee将得到的数据传输到手持式收费机,使手持式收费机准确记录车型和停车时间;最后,通过手持式收费机再将车位占用信息传送给路边控制器,从而实现路边停车位数量的显示和对停车位停车状态的查询.

  9. 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.

  10. Sliding Mode Based Analysis and Identification of Vehicle Dynamics

    OpenAIRE

    Imine, Hocine; Fridman, Leonid; Shraim, Hassan; Djemai, Mohamed

    2011-01-01

    Vehicles are complex mechanical systems with strong nonlinear characteristics and which can present some uncertainties due to their dynamic parameters such as masses, inertias, suspension springs, tires side slip coefficients, etc. A vehicle is composed of many parts, namely the unsprung mass, the sprung mass, the suspension which makes the link between these two masses and therefore ensures passenger comfort, and also the pneumatic which absorbs the energy coming from the road and ensures co...

  11. Design of an Integrated Vehicle Chassis Control System with Driver Behavior Identification

    Directory of Open Access Journals (Sweden)

    Bing Zhu

    2015-01-01

    Full Text Available An integrated vehicle chassis control strategy with driver behavior identification is introduced in this paper. In order to identify the different types of driver behavior characteristics, a driver behavior signals acquisition system was established using the dSPACE real-time simulation platform, and the driver inputs of 30 test drivers were collected under the double lane change test condition. Then, driver behavior characteristics were analyzed and identified based on the preview optimal curvature model through genetic algorithm and neural network method. Using it as a base, an integrated chassis control strategy with active front steering (AFS and direct yaw moment control (DYC considering driver characteristics was established by model predictive control (MPC method. Finally, simulations were carried out to verify the control strategy by CarSim and MATLAB/Simulink. The results show that the proposed method enables the control system to adjust its parameters according to the driver behavior identification results and the vehicle handling and stability performance are significantly improved.

  12. 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. .

  13. Implementation of a remote computer controlled automatic guided vehicle

    OpenAIRE

    Lu, Roberto F.

    1994-01-01

    The effectiveness of a material handling system is essential to a competitive manufacturing environment. Automatic Guided Vehicles (AGVs) are an irnportant technology within today's modern manufacturing facility. Academic programs in manufacturing and industrial engineering must find ways to include this technology in their instructional and research programs to provide the students with sufficient knowledge to address material handling systems design. This project was a fir...

  14. ARGALI: an automatic cup-to-disc ratio measurement system for glaucoma detection and AnaLysIs framework

    Science.gov (United States)

    Liu, J.; Wong, D. W. K.; Lim, J. H.; Li, H.; Tan, N. M.; Wong, T. Y.

    2009-02-01

    Glaucoma is an irreversible ocular disease leading to permanent blindness. However, early detection can be effective in slowing or halting the progression of the disease. Physiologically, glaucoma progression is quantified by increased excavation of the optic cup. This progression can be quantified in retinal fundus images via the optic cup to disc ratio (CDR), since in increased glaucomatous neuropathy, the relative size of the optic cup to the optic disc is increased. The ARGALI framework constitutes of various segmentation approaches employing level set, color intensity thresholds and ellipse fitting for the extraction of the optic cup and disc from retinal images as preliminary steps. Following this, different combinations of the obtained results are then utilized to calculate the corresponding CDR values. The individual results are subsequently fused using a neural network. The learning function of the neural network is trained with a set of 100 retinal images For testing, a separate set 40 images is then used to compare the obtained CDR against a clinically graded CDR, and it is shown that the neural network-based result performs better than the individual components, with 96% of the results within intra-observer variability. The results indicate good promise for the further development of ARGALI as a tool for the early detection of glaucoma.

  15. 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.

  16. The Design of Food Storage Guided Vehicle System Based on RFID Technology

    Directory of Open Access Journals (Sweden)

    Rui Xue

    2015-08-01

    Full Text Available According to the characteristics of the food transport system, RFID technology is integrated in the AGV automatic guided vehicle system in the food warehousing. The node RFID oriented method is chosen and the RFID note positioning function is used to realize more types and over horizon identification loading, handling and automatic storage function that improves the system flexibility through the design of tag oriented system.

  17. Automatic on-line monitoring of atmospheric volatile organic compounds: Gas chromatography-mass spectrometry and gas chromatography-flame ionization detection as complementary systems

    International Nuclear Information System (INIS)

    Traditionally air quality networks have been carrying out the continuous, on-line measurement of volatile organic compounds (VOC) in ambient air with GC-FID. In this paper some identification and coelution problems observed while using this technique in long-term measurement campaigns are described. In order to solve these problems a GC-MS was set up and operated simultaneously with a GC-FID for C2-C11 VOCs measurement. There are few on-line, unattended, long term measurements of atmospheric VOCs performed with GC-MS. In this work such a system has been optimized for that purpose, achieving good repeatability, linearity, and detection limits of the order of the GC-FID ones, even smaller in some cases. VOC quantification has been made by using response factors, which is not frequent in on-line GC-MS. That way, the identification and coelution problems detected in the GC-FID, which may led to reporting erroneous data, could be corrected. The combination of GC-FID and GC-MS as complementary techniques for the measurement of speciated VOCs in ambient air at sub-ppbv levels is proposed. Some results of the measurements are presented, including concentration values for some compounds not found until now on public ambient air VOC databases, which were identified and quantified combining both techniques. Results may also help to correct previously published VOC data with wrongly identified compounds by reprocessing raw chromatographic data.

  18. A novel microbial source tracking microarray for pathogen detection and fecal source identification in environmental systems.

    Science.gov (United States)

    Li, Xiang; Harwood, Valerie J; Nayak, Bina; Staley, Christopher; Sadowsky, Michael J; Weidhaas, Jennifer

    2015-06-16

    Pathogen detection and the identification of fecal contamination sources are challenging in environmental waters. Factors including pathogen diversity and ubiquity of fecal indicator bacteria hamper risk assessment and remediation of contamination sources. A custom microarray targeting pathogens (viruses, bacteria, protozoa), microbial source tracking (MST) markers, and antibiotic resistance genes was tested against DNA obtained from whole genome amplification (WGA) of RNA and DNA from sewage and animal (avian, cattle, poultry, and swine) feces. Perfect and mismatch probes established the specificity of the microarray in sewage, and fluorescence decrease of positive probes over a 1:10 dilution series demonstrated semiquantitative measurement. Pathogens, including norovirus, Campylobacter fetus, Helicobacter pylori, Salmonella enterica, and Giardia lamblia were detected in sewage, as well as MST markers and resistance genes to aminoglycosides, beta-lactams, and tetracycline. Sensitivity (percentage true positives) of MST results in sewage and animal waste samples (21-33%) was lower than specificity (83-90%, percentage of true negatives). Next generation DNA sequencing revealed two dominant bacterial families that were common to all sample types: Ruminococcaceae and Lachnospiraceae. Five dominant phyla and 15 dominant families comprised 97% and 74%, respectively, of sequences from all fecal sources. Phyla and families not represented on the microarray are possible candidates for inclusion in subsequent array designs. PMID:25970344

  19. 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.

  20. 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.

  1. Software Design and Application of Ultrasonic Automatic Flaw Detection System of Welded Steel Pipes%焊接钢管超声波自动探伤系统中的软件设计与应用

    Institute of Scientific and Technical Information of China (English)

    常少文

    2011-01-01

    The software design of pipe ultrasonic automatic flaw detection system, and its application on welded steel pipes production were introduced. It combined traditional ultrasonic inspection technology with some advanced technologies, such as industrial control computer, virtual instrument, intelligent flaw detection, etc. With the careful programming flaw detection operation, it could evaluate correctly and select strictly for complex flaw echo, its error in alarm could be effectively avoided. The review of flaw echo waveform overcame insufficiency of flaw category identification in ultrasonic automatic inspection, and achieved misinformation rate being smaller than 2%, and fail to report rate being zero.%分析了焊接钢管超声波自动探伤系统的软件设计以及在焊接钢管检测中的应用状况.把传统的超声波检测技术和先进的工业控制计算机、虚拟仪器和智能化探伤等技术相结合,配合精心编制的探伤操作程序,可做到对复杂缺陷回波的准确评价和严格筛选,有效地避免了系统的误报警.缺陷波形回放功能克服了超声波自动探伤中的缺陷种类难以识别的不足,并做到误报率<2%,漏报率为0.

  2. 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 ...

  3. Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish.

    Science.gov (United States)

    Vieira, Manuel; Fonseca, Paulo J; Amorim, M Clara P; Teixeira, Carlos J C

    2015-12-01

    The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types. PMID:26723348

  4. Information processes in visual and object buffers of scene understanding system for reliable target detection, separation from background, and identification

    Science.gov (United States)

    Kuvich, Gary

    2006-05-01

    Modern target recognition systems suffer from the lack of human-like abilities to understand the visual scene, detect, unambiguously identify and recognize objects. As result, the target recognition systems become dysfunctional if target doesn't demonstrate remarkably distinctive and contrast features that allow for unambiguous separation from background and identification upon such features. This is somewhat similar to visual systems of primitive animals like frogs, which can separate and recognize only moving objects. However, human vision unambiguously separates any object from its background. Human vision combines a rough but wide peripheral, and narrow but precise foveal systems with visual intelligence that utilize both scene and object contexts and resolve ambiguity and uncertainty in the visual information. Perceptual grouping is one of the most important processes in human vision, and it binds visual information into meaningful patterns and structures. Unlike the traditional computer vision models, biologically-inspired Network-Symbolic models convert image information into an "understandable" Network-Symbolic format, which is similar to relational knowledge models. The equivalent of interaction between peripheral and foveal systems in the network-symbolic system is achieved via interaction between Visual and Object Buffers and the top-level system of Visual Intelligence. This interaction provides recursive rough context identification of regions of interest in the visual scene and their analysis in the object buffer for precise and unambiguous separation of the object from background/clutter with following recognition of the target.

  5. Vehicle occupancy detection camera position optimization using design of experiments and standard image references

    Science.gov (United States)

    Paul, Peter; Hoover, Martin; Rabbani, Mojgan

    2013-03-01

    Camera positioning and orientation is important to applications in domains such as transportation since the objects to be imaged vary greatly in shape and size. In a typical transportation application that requires capturing still images, inductive loops buried in the ground or laser trigger sensors are used when a vehicle reaches the image capture zone to trigger the image capture system. The camera in such a system is in a fixed position pointed at the roadway and at a fixed orientation. Thus the problem is to determine the optimal location and orientation of the camera when capturing images from a wide variety of vehicles. Methods from Design for Six Sigma, including identifying important parameters and noise sources and performing systematically designed experiments (DOE) can be used to determine an effective set of parameter settings for the camera position and orientation under these conditions. In the transportation application of high occupancy vehicle lane enforcement, the number of passengers in the vehicle is to be counted. Past work has described front seat vehicle occupant counting using a camera mounted on an overhead gantry looking through the front windshield in order to capture images of vehicle occupants. However, viewing rear seat passengers is more problematic due to obstructions including the vehicle body frame structures and seats. One approach is to view the rear seats through the side window. In this situation the problem of optimally positioning and orienting the camera to adequately capture the rear seats through the side window can be addressed through a designed experiment. In any automated traffic enforcement system it is necessary for humans to be able to review any automatically captured digital imagery in order to verify detected infractions. Thus for defining an output to be optimized for the designed experiment, a human defined standard image reference (SIR) was used to quantify the quality of the line-of-sight to the rear seats of

  6. Application of Artificial Intelligent For Armour Vehicle Detection Using Digital Image Processing For Aerial Application

    Directory of Open Access Journals (Sweden)

    Kamaruddin Abd Ghani

    2011-01-01

    Full Text Available This paper will presents a new automatic target recognition (ATR algorithm to detect targets such as battle tanks and armoured personal carriers especially that been used by Malaysia Armed Forces from air-to- ground scenario. Numerous friendly-fire incidents justify the need for identification of armour vehicle in both command control and weapon systems. Rapid and reliable identification of the targets at maximum surveillance is a challenging problem. In this paper work, the reliable method to segregate the potential target from the background scene such as Fourier Transform is applied before the extracted target will be process in order to get the detail of edges and boundaries using Hough Transform. The edges will provide sufficient information for the system to generate training data for Artificial Neural Network simulation to recognize the potential target image.

  7. 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. PMID:24148491

  8. Automatic learning of state machines for fault detection systems in discrete event based distributed systems

    OpenAIRE

    Neuner, Oliver

    2011-01-01

    The electronic components in modern automobiles build up a distributed system with so called electronic control units connected via bus systems. As more safety- and security-relevant functions are implemented in such systems, the more important fault detection becomes. A promising approach to fault detection is to build a system model from state machines and compare its predictions with properties observed in a real system. In the automobile, potential are communication characteristics betwee...

  9. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors

    OpenAIRE

    Aníbal Ollero; Antidio Viguria; Luis Merino; Iván Maza; Fernando Caballero; Guillermo Heredia

    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...

  10. INTEGRATED VEHICLE PERFORMANCE AND EMISSION MONITORING SYSTEM

    Institute of Scientific and Technical Information of China (English)

    OCHIENGWY; NORTHRJ; QUDDUSM; NOLANDRB; POLAKJW

    2005-01-01

    This paper discusses a vehicle performance and emission monitoring system (VPEMS) capable of interfacing with either a vehicle engine management system (EMS) or a sensor array fitted to the vehicle. It also describes the procedures used to validate the data generated by both diesel and petrol powered vehicles. These include the results of bench and field experiments using two instrumented vehicles and of experiments on a chassis dynamometer emissions test facility. The prototype VPEMS attains the specified performance levels for each of the subsystems, with aggregate mass emissions agreeing with the reference to within 11.5%, 8.1% and 17.7% for CO, CO2 and NO, respectively. The collation of these data to produce coherent spatially and temporally referenced databases of vehicle performance and the emission is demonstrated.

  11. Real Time Vehicle Tracking System using GSM and GPS Technology- An Anti-theft Tracking System

    Directory of Open Access Journals (Sweden)

    Kunal Maurya

    2012-06-01

    Full Text Available A vehicle tracking system is an electronic device installed in a vehicle to enable the owner or a third party to track the vehicle's location. This paper proposed to design a vehicle tracking system that works using GPS and GSM technology, which would be the cheapest source of vehicle tracking and it would work as anti-theft system. It is an embedded system which is used for tracking and positioning of any vehicle by using Global Positioning System (GPS and Global system for mobile communication (GSM. This design will continuously monitor a moving Vehicle and report the status of the Vehicle on demand. For doing so an AT89C51 microcontroller is interfaced serially to a GSM Modem and GPS Receiver. A GSM modem is used to send the position (Latitude and Longitude of the vehicle from a remote place. The GPS modem will continuously give the data i.e. the latitude and longitude indicating the position of the vehicle. The same data is sent to the mobile at the other end from where the position of the vehicle is demanded. When the request by user is sent to the number at the GSM modem, the system automatically sends a return reply to that mobile indicating the position of the vehicle in terms of latitude and longitude in real time.

  12. GSM-GPS Based Intelligent Security and Control System for Vehicle

    Directory of Open Access Journals (Sweden)

    Mr. Kiran Gaikwad

    2013-05-01

    Full Text Available The revolution of Mobile and Technology has made ‘GSM based vehicle security system’. The vehicle security system is prominent worldwide. But it is not so much secure system. Every vehicle owner wants maximum protection of his vehicle; otherwise thief can easily trap the vehicle. So, by combing the idea of mobile and vehicle security system GSM based vehicle security system can be designed. So this GSM-GPS based vehicle security system works when someone tries to steal your vehicle. This paper deals with the design {&} development of an embedded system, which is being used to prevent/control the theft of a vehicle. The instrument is an embedded system based on GSM and GPS technology. The instrument is installed in the engine of the vehicle. The main objective of this instrument is to protect the vehicle from any unauthorized access, through entering a protected password and intimate the status and location of the same vehicle to the authorize person (owner using Global System for Mobile Communication (GSM and Global Positioning System (GPS technology. Here owner of vehicle can control system through Cell phone or a personal computer (PC. In this system new concept is inclusion of RTC (Real Time Clock by which vehicle can be permanently off depending upon date and time set. This system is intelligent because it performs many tasks automatically and also control vehicle on/off from a distance

  13. 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.

  14. AUTOMATIC TURBIDIMETRY IN DETECTING PROTEIN IN URINE AND CEREBROSPINAL FLUID

    Institute of Scientific and Technical Information of China (English)

    张建荣; 李闻捷; 徐德安

    2002-01-01

    Objective To evaluate and validate the performance of automatic turbidimetry in detecting protein in urine and cerebrospinal fluid.Methods The detection limits, reportable range of results, precision and accuracy of the method were investigated by using the Roche chemical reagent, benzethonium chloride.Results The functional sensitivity was 0.08g/L of protein, the reportable range of result was between 0.08g/L and 2.0g/L; the intra-batch coefficient of variation(CV) was 1.5% and the inter-batch CV was 2.2%, and the regression relation between new method and routine SSA method in patient sample determination was Y1 = 0.86X+0.068, r=0.972 and Y2=0.86X+0.056, r=0.980 for urine and cerebrospinal fluid respectively.Conclusion This method is simple, accurate, time saving with minimal sample volume 5~15μl, and suitalbe for clinical practice.

  15. Rapid and automatic detection of brain tumors in MR images

    Science.gov (United States)

    Wang, Zhengjia; Hu, Qingmao; Loe, KiaFock; Aziz, Aamer; Nowinski, Wieslaw L.

    2004-04-01

    An algorithm to automatically detect brain tumors in MR images is presented. The key concern is speed in order to process efficiently large brain image databases and provide quick outcomes in clinical setting. The method is based on study of asymmetry of the brain. Tumors cause asymmetry of the brain, so we detect brain tumors in 3D MR images using symmetry analysis of image grey levels with respect to the midsagittal plane (MSP). The MSP, separating the brain into two hemispheres, is extracted using our previously developed algorithm. By removing the background pixels, the normalized grey level histograms are calculated for both hemispheres. The similarity between these two histograms manifests the symmetry of the brain, and it is quantified by using four symmetry measures: correlation coefficient, root mean square error, integral of absolute difference (IAD), and integral of normalized absolute difference (INAD). A quantitative analysis of brain normality based on 42 patients with tumors and 55 normals is presented. The sensitivity and specificity of IAD and INAD were 83.3% and 89.1%, and 85.7% and 83.6%, respectively. The running time for each symmetry measure for a 3D 8bit MR data was between 0.1 - 0.3 seconds on a 2.4GHz CPU PC.

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

    DEFF Research Database (Denmark)

    Sun, Zhen

    different kinds of models, one is a type of state space model which is described by Itô Stochastic Differential Equations (ISDE), the other one is a nonlinear First Order Plus Dead Time (FOPDT) model. This thesis aims to investigate these two different kinds of nonlinear models and to propose the...... of model in the thesis. Moreover, a new method by combining Maximum Likelihood (ML) technique plus UKF is proposed and its convergence property with regard to the consistency and normality is also investigated. The developed methods and algorithms are tested and analyzed for a number of numerical...... make the parameters identification are proposed accordingly. Moreover, the proposed methods are further extended to make parameter identification of a kind of multiple inputs model. The proposed methods and algorithms are tested and analyzed for a number of numerical cases and finally applied to study...

  17. Automatic basal slice detection for cardiac analysis

    Science.gov (United States)

    Paknezhad, Mahsa; Marchesseau, Stephanie; Brown, Michael S.

    2016-03-01

    Identification of the basal slice in cardiac imaging is a key step to measuring the ejection fraction (EF) of the left ventricle (LV). Despite research on cardiac segmentation, basal slice identification is routinely performed manually. Manual identification, however, has been shown to have high inter-observer variability, with a variation of the EF by up to 8%. Therefore, an automatic way of identifying the basal slice is still required. Prior published methods operate by automatically tracking the mitral valve points from the long-axis view of the LV. These approaches assumed that the basal slice is the first short-axis slice below the mitral valve. However, guidelines published in 2013 by the society for cardiovascular magnetic resonance indicate that the basal slice is the uppermost short-axis slice with more than 50% myocardium surrounding the blood cavity. Consequently, these existing methods are at times identifying the incorrect short-axis slice. Correct identification of the basal slice under these guidelines is challenging due to the poor image quality and blood movement during image acquisition. This paper proposes an automatic tool that focuses on the two-chamber slice to find the basal slice. To this end, an active shape model is trained to automatically segment the two-chamber view for 51 samples using the leave-one-out strategy. The basal slice was detected using temporal binary profiles created for each short-axis slice from the segmented two-chamber slice. From the 51 successfully tested samples, 92% and 84% of detection results were accurate at the end-systolic and the end-diastolic phases of the cardiac cycle, respectively.

  18. Automatic Priming Effects for New Associations in Lexical Decision and Perceptual Identification

    NARCIS (Netherlands)

    D. Pecher (Diane); J.G.W. Raaijmakers (Jeroen)

    1999-01-01

    textabstractInformation storage in semantic memory was investigated by looking at automatic priming effects for new associations in two experiments. In the study phase word pairs were presented in a paired-associate learning task. Lexical decision and perceptual identification were used to examine p

  19. 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.

  20. Vehicle detection and tracking based on phase-correlation

    Institute of Scientific and Technical Information of China (English)

    Yi He(何毅); Xin Yang(杨新)

    2004-01-01

    This paper presents vehicle detection and tracking algorithms based on real-time background (RTB) and phase-correlation (PC) in the video sequence of urban highway with fixed camera. Firstly moving objects are obtained by subtracting RTB from serial images. After classification, PC is used to determine corresponding regions of moving objects between consecutive frames. The problems of vehicles' merging and splitting, sudden stop, and restart are also considered. Experiments show that the method is practical and can realize real-time detection and tracking of vehicles on highway.

  1. Long baseline stereovision for automatic detection and ranging of moving objects in the night sky.

    Science.gov (United States)

    Danescu, Radu; Oniga, Florin; Turcu, Vlad; Cristea, Octavian

    2012-01-01

    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. PMID:23201979

  2. 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.

  3. Anomaly Detection in Gamma-Ray Vehicle Spectra with Principal Components Analysis and Mahalanobis Distances

    International Nuclear Information System (INIS)

    The goal of primary radiation monitoring in support of routine screening and emergency response is to detect characteristics in vehicle radiation signatures that indicate the presence of potential threats. Two conceptual approaches to analyzing gamma-ray spectra for threat detection are isotope identification and anomaly detection. While isotope identification is the time-honored method, an emerging technique is anomaly detection that uses benign vehicle gamma ray signatures to define an expectation of the radiation signature for vehicles that do not pose a threat. Newly acquired spectra are then compared to this expectation using statistical criteria that reflect acceptable false alarm rates and probabilities of detection. The gamma-ray spectra analyzed here were collected at a U.S. land Port of Entry (POE) using a NaI-based radiation portal monitor (RPM). The raw data were analyzed to develop a benign vehicle expectation by decimating the original pulse-height channels to 35 energy bins, extracting composite variables via principal components analysis (PCA), and estimating statistically weighted distances from the mean vehicle spectrum with the mahalanobis distance (MD) metric. This paper reviews the methods used to establish the anomaly identification criteria and presents a systematic analysis of the response of the combined PCA and MD algorithm to modeled mono-energetic gamma-ray sources

  4. Offshore oil seepage visible from space : a Synthetic Aperture Radar (SAR) based automatic detection, mapping and quantification system

    OpenAIRE

    Suresh, Gopika

    2015-01-01

    Offshore oil seepage is believed to be the largest source of marine oil, yet very few of their locations and seepage fluxes have been discovered and reported. Natural oil seep sites are important as they serve as potential energy sources and because they are hosts to a very varied marine ecosystem. These seeps can also be associated with gas hydrates and methane emissions and hence, locating natural oil seeps can provide locations where the sources of greenhouse gases could be studied and qua...

  5. 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.

  6. 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. PMID:24151424

  7. Comparison of two chromogenic media and evaluation of two molecular based identification systems for Enterobacter sakazakii detection

    Directory of Open Access Journals (Sweden)

    Diep Benjamin

    2006-02-01

    Full Text Available Abstract Background Enterobacter sakazakii is a foodborne pathogen that has been associated with sporadic cases and outbreaks causing meningitis, necrotizing enterocolitis and sepsis especially in neonates. The current FDA detection method includes two enrichment steps, the subculturing of the second enrichment broth on a selective agar (VRBG, a further subculturing of selected grown colonies on TSA and the subsequent biochemical identification of yellow-pigmented colonies by API20E. However, there is a strong need for simplified methods for isolation and identification of E. sakazakii. In this study, two chromogenic media, which allow to indicate presumptive E. sakazakii colonies by the alpha glucosidase activity, as well as a newly developed 1,6-alpha-glucosidase based conventional PCR assay and a rRNA oligonucleotide probe based commercial test system for identification of presumptive E. sakazakii were evaluated on 98 target and non-target strains. The methods were compared with respect to specificity aspects. Results A total of 75 presumptive E. sakazakii and 23 non-target strains were analysed by using chromogenic media, alpha-glucosidase based PCR assay, and the VIT assay. For most presumptive E. sakazakii strains on the chromogenic media, the PCR and VIT assay confirmed the identification. However, for a number of presumptive E. sakazakii isolates from fruit powder, the alpha-glucosidase PCR and VIT assay did not correspond to the typical E. sakazakii colonies on DFI and ESIA. Further characterization by API32E identification, phylogenetic analysis of partial 16S rRNA sequences and ribotyping strongly suggested, that these strains did not belong to the species E. sakazakii. The newly developed alpha-glucosidase based PCR assay as well as the commercially available VIT Enterobacter sakazakii identification test showed an excellent correlation with the 16S rRNA data, and are thus well suited for identification of E. sakazakii. Conclusion

  8. Automatic detection of EEG artefacts arising from head movements using EEG and gyroscope signals.

    Science.gov (United States)

    O'Regan, Simon; Faul, Stephen; Marnane, William

    2013-07-01

    Contamination of EEG signals by artefacts arising from head movements has been a serious obstacle in the deployment of automatic neurological event detection systems in ambulatory EEG. In this paper, we present work on categorizing these head-movement artefacts as one distinct class and on using support vector machines to automatically detect their presence. The use of additional physical signals in detecting head-movement artefacts is also investigated by means of support vector machines classifiers implemented with gyroscope waveforms. Finally, the combination of features extracted from EEG and gyroscope signals is explored in order to design an algorithm which incorporates both physical and physiological signals in accurately detecting artefacts arising from head-movements.

  9. Comparative Analysis of Automatic Vehicle Classification Techniques: A Survey

    Directory of Open Access Journals (Sweden)

    Kanwal Yousaf

    2012-09-01

    Full Text Available Vehicle classification has emerged as a significant field of study because of its importance in variety of applications like surveillance, security system, traffic congestion avoidance and accidents prevention etc. So far numerous algorithms have been implemented for classifying vehicle. Each algorithm follows different procedures for detecting vehicles from videos. By evaluating some of the commonly used techniques we highlighted most beneficial methodology for classifying vehicles. In this paper we pointed out the working of several video based vehicle classification algorithms and compare these algorithms on the basis of different performance metrics such as classifiers, classification methodology or principles and vehicle detection ratio etc. After comparing these parameters we concluded that Hybrid Dynamic Bayesian Network (HDBN Classification algorithm is far better than the other algorithms due to its nature of estimating the simplest features of vehicles from different videos. HDBN detects vehicles by following important stages of feature extraction, selection and classification. It extracts the rear view information of vehicles rather than other information such as distance between the wheels and height of wheel etc.

  10. Automatic molecular collection and detection by using fuel-powered microengines

    Science.gov (United States)

    Han, Di; Fang, Yangfu; Du, Deyang; Huang, Gaoshan; Qiu, Teng; Mei, Yongfeng

    2016-04-01

    We design and fabricate a simple self-powered system to collect analyte molecules in fluids for surface-enhanced Raman scattering (SERS) detection. The system is based on catalytic Au/SiO/Ti/Ag-layered microengines by employing rolled-up nanotechnology. Pronounced SERS signals are observed on microengines with more carrier molecules compared with the same structure without automatic motions.We design and fabricate a simple self-powered system to collect analyte molecules in fluids for surface-enhanced Raman scattering (SERS) detection. The system is based on catalytic Au/SiO/Ti/Ag-layered microengines by employing rolled-up nanotechnology. Pronounced SERS signals are observed on microengines with more carrier molecules compared with the same structure without automatic motions. Electronic supplementary information (ESI) available: Experimental procedures, characterization, SERS enhancement factor calculation and videos. See DOI: 10.1039/c6nr00117c

  11. Abbreviation definition identification based on automatic precision estimates

    OpenAIRE

    Kim Won; Comeau Donald C; Sohn Sunghwan; Wilbur W John

    2008-01-01

    Abstract Background The rapid growth of biomedical literature presents challenges for automatic text processing, and one of the challenges is abbreviation identification. The presence of unrecognized abbreviations in text hinders indexing algorithms and adversely affects information retrieval and extraction. Automatic abbreviation definition identification can help resolve these issues. However, abbreviations and their definitions identified by an automatic process are of uncertain validity. ...

  12. GPS based Advanced Vehicle Tracking and Vehicle Control System

    Directory of Open Access Journals (Sweden)

    Mashood Mukhtar

    2015-02-01

    Full Text Available Security systems and navigators have always been a necessity of human‟s life. The developments of advanced electronics have brought revolutionary changes in these fields. In this paper, we will present a vehicle tracking system that employs a GPS module and a GSM modem to find the location of a vehicle and offers a range of control features. To complete the design successfully, a GPS unit, two relays, a GSM Modem and two MCU units are used. There are five features introduced in the project. The aim of this project is to remotely track a vehicle‟s location, remotely switch ON and OFF the vehicle‟s ignition system and remotely lock and unlock the doors of the vehicle. An SMS message is sent to the tracking system and the system responds to the users request by performing appropriate actions. Short text messages are assigned to each of these features. A webpage is specifically designed to view the vehicle‟s location on Google maps. By using relay based control concept introduced in this paper, number of control features such as turning heater on/off, radio on/off etc. can be implemented in the same fashion.

  13. Image-based Vehicle Classification System

    CERN Document Server

    Ng, Jun Yee

    2012-01-01

    Electronic toll collection (ETC) system has been a common trend used for toll collection on toll road nowadays. The implementation of electronic toll collection allows vehicles to travel at low or full speed during the toll payment, which help to avoid the traffic delay at toll road. One of the major components of an electronic toll collection is the automatic vehicle detection and classification (AVDC) system which is important to classify the vehicle so that the toll is charged according to the vehicle classes. Vision-based vehicle classification system is one type of vehicle classification system which adopt camera as the input sensing device for the system. This type of system has advantage over the rest for it is cost efficient as low cost camera is used. The implementation of vision-based vehicle classification system requires lower initial investment cost and very suitable for the toll collection trend migration in Malaysia from single ETC system to full-scale multi-lane free flow (MLFF). This project ...

  14. 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.

  15. Identification of an Underactuated Unmanned Surface Vehicle

    Institute of Scientific and Technical Information of China (English)

    Zhao Jiang; Yan Weisheng; Jin Xuelian; Gao Jian

    2012-01-01

    Hydrodynamic coefficients strongly affect the dynamic performance of underactuated unmanned surface vehicle (USV).Towing tank test is the traditional approach to identify these coefficients,however,the obtained values are not completely reliable since experimental difficulties and errors are involved.In this paper,an extended Kalman filter (EKF) method and a least squares (LS) method are proposed,only using onboard sensor data for identification of a small underactuated USV.The vehicle prototype as well as the system integration is delineated.Performance of the identification is evaluated by comparing the estimated coefficients,and the feasibility and accuracy of the proposed approach is demonstrated by simulation.

  16. Automatic identification of mass spectra

    International Nuclear Information System (INIS)

    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

  17. 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.

  18. Detection and identification of Trichophyton tonsurans from clinical isolates and hairbrush samples by loop-mediated isothermal amplification system.

    Science.gov (United States)

    Yo, Ayaka; Yamamoto, Mikachi; Nakayama, Takako; Ishikawa, Jun; Makimura, Koichi

    2016-09-01

    Since the 1990s, there have been reports of the spread of dermatophytosis caused by Trichophyton tonsurans among contact sports athletes in several countries, including Japan. This study was performed to develop a loop-mediated isothermal amplification (LAMP) system for rapid and accurate detection and identification of T. tonsurans from clinical isolates or hairbrush samples for diagnosis and to prevent the spread of infection. A specific primer set was prepared by comparing the whole genome sequence of T. tonsurans with those of six other closely related dermatophytes. After confirming the sensitivity and specificity of this system, LAMP assay was performed using 37 clinical samples obtained from three healthy volunteers and 24 judo athletes. A total of 155 fungal isolates (56 strains of various standard fungi, 96 identified T. tonsurans isolates, three hairbrush-cultured isolates from judo athletes) and 37 hairbrush samples (34 samples from 24 judo athletes, and three samples from three healthy volunteers) were used for culture and LAMP assay, respectively. The assay showed no cross-reactivity to standard strains other than T. tonsurans. The detection limit was 100 copies of DNA template per tube. All of the 96 T. tonsurans isolates were amplified, and all samples from healthy volunteers showed negative results. Four of the 34 hairbrush samples obtained from judo athletes showed positive results in LAMP assay, and two of the four were positive in both culture and LAMP assay. We developed a rapid LAMP system with high specificity and sensitivity for diagnosis of T. tonsurans infection. PMID:26892741

  19. Detection and identification of Trichophyton tonsurans from clinical isolates and hairbrush samples by loop-mediated isothermal amplification system.

    Science.gov (United States)

    Yo, Ayaka; Yamamoto, Mikachi; Nakayama, Takako; Ishikawa, Jun; Makimura, Koichi

    2016-09-01

    Since the 1990s, there have been reports of the spread of dermatophytosis caused by Trichophyton tonsurans among contact sports athletes in several countries, including Japan. This study was performed to develop a loop-mediated isothermal amplification (LAMP) system for rapid and accurate detection and identification of T. tonsurans from clinical isolates or hairbrush samples for diagnosis and to prevent the spread of infection. A specific primer set was prepared by comparing the whole genome sequence of T. tonsurans with those of six other closely related dermatophytes. After confirming the sensitivity and specificity of this system, LAMP assay was performed using 37 clinical samples obtained from three healthy volunteers and 24 judo athletes. A total of 155 fungal isolates (56 strains of various standard fungi, 96 identified T. tonsurans isolates, three hairbrush-cultured isolates from judo athletes) and 37 hairbrush samples (34 samples from 24 judo athletes, and three samples from three healthy volunteers) were used for culture and LAMP assay, respectively. The assay showed no cross-reactivity to standard strains other than T. tonsurans. The detection limit was 100 copies of DNA template per tube. All of the 96 T. tonsurans isolates were amplified, and all samples from healthy volunteers showed negative results. Four of the 34 hairbrush samples obtained from judo athletes showed positive results in LAMP assay, and two of the four were positive in both culture and LAMP assay. We developed a rapid LAMP system with high specificity and sensitivity for diagnosis of T. tonsurans infection.

  20. 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.

  1. Detection and identification of novel actinomycetes.

    Science.gov (United States)

    Williams, S T; Locci, R; Beswick, A; Kurtböke, D I; Kuznetsov, V D; Le Monnier, F J; Long, P F; Maycroft, K A; Palma, R A; Petrolini, B

    1993-10-01

    The actinomycetes are well known as a group of filamentous, Gram-positive bacteria that produce many useful secondary metabolites, including antibiotics and enzymes. Although they have been intensively studied for both theoretical and practical objectives, there is much scope for developing our basic knowledge of the means of detection and isolation of these microbes. This session concentrated on new methods for the detection and identification of novel actinomycetes from a range of environments. Approaches to the detection of actinomycetes ranged from investigations of neglected habitats and extreme environments (e.g. alkaline soils and oil drills) to the analysis of DNA extracted from the environment and use of specific phages. The continuing problems of the identification of actinomycete isolates were also considered. Topics discussed included use of phage typing, DNA probes, and correlation between phenetic and genotypic species of Streptomyces.

  2. Simultaneous Identification of Moving Vehicles and Bridge Damages Considering Road Rough Surface

    Directory of Open Access Journals (Sweden)

    Qingxia Zhang

    2013-01-01

    Full Text Available A method for the simultaneous identification of moving vehicles and the damages of the supporting structure from measured responses is presented. A two-axle vehicle model with two degrees of freedom (DOF is adopted. The extent of the damage and the vehicle parameters were chosen as the optimisation variables, which allow ill conditioning to be avoided and decrease the number of sensors required. The identification is performed by minimising the distance between the measured responses and the computed responses to given optimisation variables. The virtual distortion method (VDM was used, such that the response of the damaged structure can be computed from comparison with the intact structure subjected to the same vehicle excitation and to the response-coupled virtual distortions. These are related to the optimisation variables by the system impulse response matrix and are expressed by a linear system, which allowed both types of optimisation variables to be treated in a unified way. The numerical cost is reduced by using a moving influence matrix. The adjoint variable method is used for fast sensitivity analysis. A three-span bridge numerical example is presented, where the identification was verified with 5% root mean square (RMS measurement, and model, error whilst also considering the surface roughness of the road.

  3. Structural damage detection via nonlinear system identification and structural intensity methods

    Science.gov (United States)

    Semperlotti, Fabio

    sensory system for data acquisition. The second technique presented in this work is based on the use of Structural Intensity (SI) as a damage detection tool. Although SI has been used in the past for structural vibrations and noise control systems, applications to damage detection are still very limited. A numerical study exploring the relationship between several structural (loss factors, damage size) and experimental (frequency resolution, sensor size and placements) parameters and the SI field is presented. The changes in SI at discrete structural locations are used as the damage metric. In order to improve performance and adaptability of the SI based system over a wide spectrum of structures, the concept of Active Energy Sink (AES) is introduced. A feedback control system is used to realize the absorption device. The AES design is presented, and validated through experimental testing. An increase in the closed loop loss factors up to eta=29% was measured for the low frequency modes. Finally, the concept of Nonlinear Structural Surface Intensity (NSSI) is presented. The SI-based SHM was initially developed by relying on the availability of a baseline for the healthy structure. In order to develop a baseline-free technique, the HHRS is integrated into the SI concept. This approach results in a single technique which benefits from the localization capabilities from the HHRS approach and of the sizing capabilities proper of the SI approach.

  4. 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.

  5. Study on Ground Automatic Identification Technology for Intelligent Vehicle Based on Vision Sensor%基于视觉传感器的自主车辆地面自动辨识技术研究

    Institute of Scientific and Technical Information of China (English)

    崔根群; 余建明; 赵娴; 赵丛琳

    2011-01-01

    The ground automatic identification technology for intelligent vehicle is iaking Leobor-Edu autonomous vehicle as a test vector and using DH-HV2003UC-T vision sensor to collect image infarmaiion of five common lane roads( cobbled road, concrete road, dirt road, grass road, tile road) , then using MATLAB image processing module to perform coding compression, recovery reconstruction, smoothing, sharpening, enhancement, feature extraction and other related processing,then using MATLAB BP neural network module to carry on pattern recognition.Through analyzing the pattern recognition result, lt shows that the objective error is 20%, the road recognition rate has reached the intended requirement in the system,and it can be universally applied in the smart vehicle or robots and other related fields.%谊自主车辆地面自动辨识技术是以Leobot-Edu自主车辆作为试验载体,并应用DH-HV2003UC-T视觉传感器对常见的5种行车路面(石子路面、水泥路面、土壤路面、草地路面、砖地路面)进行图像信息的采集,应用Matlab图像处理模块对其依次进行压缩编码、复原重建、平滑、锐化、增强、特征提取等相关处理后,再应用Matlab BP神经网络模块进行模式识别.通过对模式识别结果分析可知,网络训练目标的函数误差为20%,该系统路面识别率达到预定要求,可以在智能车辆或移动机器人等相关领域普及使用.

  6. Design and Implementation of Dynamic Vehicle Overloading Pre- detection System%动态车辆超载预检系统的设计与实现

    Institute of Scientific and Technical Information of China (English)

    张海宁; 魏立锋

    2012-01-01

    In order to detect that whether dynamic vehicle is overloaded in real -time,the paper designed a prior detecting system which could detect that whether dynamic vehicle is overloaded. The hardware platform of this system applies IPC as its core processing unit, applies LED screens as its displaying unit and uses high precision multi -channel data acquisition card(PCI - 1716) to finish data acquisition. The software design based on C+ + language and used Visual C++6. 0 as developing tool designs a set of effective software system and realizes the function of hardware equipment control,data acquisition,data processing, data display, data communication and data storage etc. The result of testing shows that the system is stable and reliable, could accurately detect the overload vehicles,and realize the detection of overload vehicles in real - time.%为了实时的检测出动态车辆是否超载,设计出了一种动态车辆超载预检测系统.系统硬件平台以工控机为核心处理单元,以LED大屏幕为显示单元,用高精度多通道数据采集卡PCI- 1716完成数据采集.软件设计以C++作为编程语言,以Visual C++6.0作为前台开发工具,设计了一套高效、稳定的软件系统,实现了对硬件设备控制、数据采集、数据处理、数据显示、数据通信以及数据存储等功能.实验结果表明,系统运行稳定可靠,能够准确检测出超限车辆,实现了对超载车辆的实时检测.

  7. 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)

    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

  8. Research on Fuzzy Control for Automatic Transmission of Tracked Vehicles

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A principle of fuzzy control for tracked vehicles is proposed to make its automatic transmission system be able to adapt complex running conditions, and a model of its power train is established to be used in simulation. Based on the fuzzy control method, a fuzzy shift control system composed of a basic shift strategy and a fuzzy modification module is developed to improve the dynamic characteristics and cross-country maneuverability. Simulation results show that the fuzzy shift strategy can improve the shift quality under manifold driving conditions and avoid cycled shift effectively. Therefore,the proposed fuzzy shift strategies are proved to be feasible and practicable.

  9. Human identification system based on the detection of optical Disc Ring in retinal images

    OpenAIRE

    Chihaoui, Takwa; Kachouri, Rostom; Jlassi, Hejer; Akil, Mohamed; Hamrouni, Kamel

    2015-01-01

    Retinal identification is being studied as a hot research topic in the biometric field. Many factors such as the poor quality of retinal images and the huge execution time can seriously affect the performance of the retinal identification systems. In this context, in order to compromise the quality and the processing time, this paper presents a human identification system based on a new preprocessing method of retinal images that we call optical Disc Ring detection method. The proposed ODR me...

  10. Adaboost Technique for Vehicle Detection in Aerial Surveillance

    Directory of Open Access Journals (Sweden)

    R.Sindoori

    2013-04-01

    Full Text Available An approach for vehicle detection system from satellite images, which are used in many applications. Vehicle detection is done by pixelwise classification method instead sliding window and region based methods, which are used in existing system. The vital part of the paper is feature extraction and vehicle colour classification. Feature extraction includes edge and corner detection. For edgedetection, the Canny edge detector technique is applied. For, corner detection, the Harris corner detector process is applied. Adaboost is employed for vehicle colour extraction to separate vehicle and non-vehicle colours. Utterly, morphological operations are applied to enhance the vehicle detection.

  11. Automatic Detection of Electric Power Troubles (ADEPT)

    Science.gov (United States)

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

    1988-01-01

    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.

  12. Camouflage, detection and identification of moving targets.

    Science.gov (United States)

    Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

    2013-05-01

    Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage. PMID:23486439

  13. Automatic spikes detection in seismogram

    Institute of Scientific and Technical Information of China (English)

    王海军; 靳平; 刘贵忠

    2003-01-01

    @@ Data processing for seismic network is very complex and fussy, because a lot of data is recorded in seismic network every day, which make it impossible to process these data all by manual work. Therefore, seismic data should be processed automatically to produce a initial results about events detection and location. Afterwards, these results are reviewed and modified by analyst. In automatic processing data quality checking is important. There are three main problem data thatexist in real seismic records, which include: spike, repeated data and dropouts. Spike is defined as isolated large amplitude point; the other two problem datahave the same features that amplitude of sample points are uniform in a interval. In data quality checking, the first step is to detect and statistic problem data in a data segment, if percent of problem data exceed a threshold, then the whole data segment is masked and not be processed in the later process.

  14. Automatic graphene transfer system for improved material quality and efficiency

    OpenAIRE

    Alberto Boscá; Jorge Pedrós; Javier Martínez; Tomás Palacios; Fernando Calle

    2015-01-01

    In most applications based on chemical vapor deposition (CVD) graphene, the transfer from the growth to the target substrate is a critical step for the final device performance. Manual procedures are time consuming and depend on handling skills, whereas existing automatic roll-to-roll methods work well for flexible substrates but tend to induce mechanical damage in rigid ones. A new system that automatically transfers CVD graphene to an arbitrary target substrate has been developed. The proce...

  15. Adaptable System for Vehicle Health and Usage Monitoring

    Science.gov (United States)

    Woodart, Stanley E.; Woodman, Keith L.; Coffey, Neil C.; Taylor, Bryant D.

    2005-01-01

    Aircraft and other vehicles are often kept in service beyond their original design lives. As they age, they become susceptible to system malfunctions and fatigue. Unlike future aircraft that will include health-monitoring capabilities as integral parts in their designs, older aircraft have not been so equipped. The Adaptable Vehicle Health and Usage Monitoring System is designed to be retrofitted into a preexisting fleet of military and commercial aircraft, ships, or ground vehicles to provide them with state-of-the-art health- and usage-monitoring capabilities. The monitoring system is self-contained, and the integration of it into existing systems entails limited intrusion. In essence, it has bolt-on/ bolt-off simplicity that makes it easy to install on any preexisting vehicle or structure. Because the system is completely independent of the vehicle, it can be certified for airworthiness as an independent system. The purpose served by the health-monitoring system is to reduce vehicle operating costs and to increase safety and reliability. The monitoring system is a means to identify damage to, or deterioration of, vehicle subsystems, before such damage or deterioration becomes costly and/or disastrous. Frequent monitoring of a vehicle enables identification of the embryonic stages of damage or deterioration. The knowledge thus gained can be used to correct anomalies while they are still somewhat minor. Maintenance can be performed as needed, instead of having the need for maintenance identified during cyclic inspections that take vehicles off duty even when there are no maintenance problems. Measurements and analyses acquired by the health-monitoring system also can be used to analyze mishaps. Overall, vehicles can be made more reliable and kept on duty for longer times. Figure 1 schematically depicts the system as applied to a fleet of n vehicles. The system has three operational levels. All communication between system components is by use of wireless

  16. Camouflage, detection and identification of moving targets

    OpenAIRE

    Hall, Joanna R.; Cuthill, Innes C.; Baddeley, Roland; Shohet, Adam J.; Scott-Samuel, Nicholas E.

    2013-01-01

    Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, b...

  17. Automatic defect identification on PWR nuclear power station fuel pellets

    International Nuclear Information System (INIS)

    This article presents a new automatic identification technique of structural failures in nuclear green fuel pellet. This technique was developed to identify failures occurred during the fabrication process. It is based on a smart image analysis technique for automatic identification of the failures on uranium oxide pellets used as fuel in PWR nuclear power stations. In order to achieve this goal, an artificial neural network (ANN) has been trained and validated from image histograms of pellets containing examples not only from normal pellets (flawless), but from defective pellets as well (with the main flaws normally found during the manufacturing process). Based on this technique, a new automatic identification system of flaws on nuclear fuel element pellets, composed by the association of image pre-processing and intelligent, will be developed and implemented on the Brazilian nuclear fuel production industry. Based on the theoretical performance of the technology proposed and presented in this article, it is believed that this new system, NuFAS (Nuclear Fuel Pellets Failures Automatic Identification Neural System) will be able to identify structural failures in nuclear fuel pellets with virtually zero error margins. After implemented, the NuFAS will add value to control quality process of the national production of the nuclear fuel.

  18. 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....

  19. Sensor Fault Detection and Diagnosis for autonomous vehicles

    Directory of Open Access Journals (Sweden)

    Realpe Miguel

    2015-01-01

    Full Text Available In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.

  20. 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.

  1. 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.

  2. Automatic detection of asteroids and meteoroids --- a wide-field survey

    Science.gov (United States)

    Vereš, P.; Tóth, J.; Jedicke, R.; Tonry, J.; Denneau, L.; Wainscoat, R.; Kornoš, L.; Šilha, J.

    2014-07-01

    The small Near-Earth Asteroids (NEAs) represent a potential risk but also an easily accessible space resource for future robotic or human in-situ space exploration or commercial activities. However, the population of 1--300 m NEAs is not well understood in terms of size- frequency and orbital distribution. NEAs with diameters below 200 m tend to have much faster spin rates than large objects and they are believed to be monolithic and not rubble-pile like their large counterparts. Moreover, the current surveys do not systematically search for the small NEAs that are mostly overlooked. We propose a low- cost robotic optical survey (ADAM-WFS) aimed at small NEAs based on four state-of-the-art telescopes having extremely wide fields of view. The four Houghton-Terebizh 30-cm astrographs (Fig. left) with 4096×4096 -pixel CCD cameras will acquire 96 square degrees in one exposure with the plate scale of 4.4 arcsec/pixel. In 30 seconds, the system will be able to reach +17.5 mag in unfiltered mode. The survey will be operated on semi-automatic basis, covering the entire night sky three times per night and optimized toward fast moving targets recognition. The advantage of the proposed system is the usage of existing of-the-shelf components and software for the image processing and object identification and linking (Denneau et al., 2013). The one-year simulation of the survey (Fig. right) at the testing location at AGO Modra observatory in Slovakia revealed that we will detect 60--240 NEAs between 1--300 m that get closer than 10 lunar distances from the Earth. The number of detections will rise by a factor of 1.5--2 in case the survey is placed at a superb observing location such as Canary Islands. The survey will also serve as an impact warning system for imminent impactors. Our simulation showed that we have a 20 % chance of finding a 50-m NEA on a direct impact orbit. The survey will provide multiple byproducts from the all-sky scans, such as comet discoveries, sparse

  3. Automatic Identification used in Audio-Visual indexing and Analysis

    Directory of Open Access Journals (Sweden)

    A. Satish Chowdary

    2011-09-01

    Full Text Available To locate a video clip in large collections is very important for retrieval applications, especially for digital rights management. We attempt to provide a comprehensive and high-level review of audiovisual features that can be extracted from the standard compressed domains, such as MPEG-1 and MPEG-2. This paper presents a graph transformation and matching approach to identify the occurrence of potentially different ordering or length due to content editing. With a novel batch query algorithm to retrieve similar frames, the mapping relationship between the query and database video is first represented by a bipartite graph. The densely matched parts along the long sequence are then extracted, followed by a filter-and-refine search strategy to prune some irrelevant subsequences. During the filtering stage, Maximum Size Matching is deployed for each sub graph constructed by the query and candidate subsequence to obtain a smaller set of candidates. During the refinement stage, Sub-Maximum Similarity Matching is devised to identify the subsequence with the highest aggregate score from all candidates, according to a robust video similarity model that incorporates visual content, temporal order, and frame alignment information. This new algorithm is based on dynamic programming that fully uses the temporal dimension to measure the similarity between two video sequences. A normalized chromaticity histogram is used as a feature which is illumination invariant. Dynamic programming is applied on shot level to find the optimal nonlinear mapping between video sequences. Two new normalized distance measures are presented for video sequence matching. One measure is based on the normalization of the optimal path found by dynamic programming. The other measure combines both the visual features and the temporal information. The proposed distance measures are suitable for variable-length comparisons.

  4. STARR: shortwave-targeted agile Raman robot for the detection and identification of emplaced explosives

    Science.gov (United States)

    Gomer, Nathaniel R.; Gardner, Charles W.

    2014-05-01

    In order to combat the threat of emplaced explosives (land mines, etc.), ChemImage Sensor Systems (CISS) has developed a multi-sensor, robot mounted sensor capable of identification and confirmation of potential threats. The system, known as STARR (Shortwave-infrared Targeted Agile Raman Robot), utilizes shortwave infrared spectroscopy for the identification of potential threats, combined with a visible short-range standoff Raman hyperspectral imaging (HSI) system for material confirmation. The entire system is mounted onto a Talon UGV (Unmanned Ground Vehicle), giving the sensor an increased area search rate and reducing the risk of injury to the operator. The Raman HSI system utilizes a fiber array spectral translator (FAST) for the acquisition of high quality Raman chemical images, allowing for increased sensitivity and improved specificity. An overview of the design and operation of the system will be presented, along with initial detection results of the fusion sensor.

  5. 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...

  6. 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.

  7. Research of brain-computer interface automatic vehicle system based on SSVEP%基于SSVEP的脑-机接口自动车系统研究

    Institute of Scientific and Technical Information of China (English)

    赵丽; 孙永; 马彦臻; 何洋

    2011-01-01

    This paper mainly carried out proposes the research of SSVEP brain-computer interface automatic vehicle control systems,which describes the principles of the visual evoked potentials that used in brain-computer interface,and the single-chip is used to designs visual stimulation. Base on the LABVIEW platform, it also uses Hilbert Huang Transform to extract evoked potential vector continuously,which produces brain-computer interface control signals that can be applied to automatic vehicle control system to control the car around before and after exercise. According to a lot of experiments to verify,this sistem can send out the control commands that the correct rate is higher than 83% and can also send a command less than 5 seconds compared with the average time based on SSVEP,so it proves that the system is feasible and has a high application value.%阐述了视觉诱发电位用于脑-机接口的原理,系统采用单片机设计视觉刺激器,同时在LABVIEW平台上,利用希尔伯特黄变换实时提取诱发电位向量,产生脑机接口控制信号,并用于自动车控制系统,从而控制小车的前后左右运动.通过大量实验验证,设计的基于稳态视觉诱发电位的脑-机接口自动车控制系统,发送控制命令正确率高于83%,发送一个命令的平均时间低于5 s,证明该系统的方案是可行的,具有较高的应用价值.

  8. The Iqmulus Urban Showcase: Automatic Tree Classification and Identification in Huge Mobile Mapping Point Clouds

    Science.gov (United States)

    Böhm, J.; Bredif, M.; Gierlinger, T.; Krämer, M.; Lindenberg, R.; Liu, K.; Michel, F.; Sirmacek, B.

    2016-06-01

    Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.

  9. Design and Development of Vehicle anti-collision System using Electromagnet and Ultrasonic Sensors

    Directory of Open Access Journals (Sweden)

    Shival Dubey

    2013-06-01

    Full Text Available Electromagnetic anti-collision device is proposed here in order to avoid Vehicular Head to Head/Back collision that estimates the distance between the two vehicles running extreme traffic condition. It incorporates distance finding between two vehicles using ultrasonic range finder. The vehicle collision and its impact emerged as the major problem in the last two decades when the use of the automobile increased to a subsequent number. In order to avoid vehicle collision/ road accidents this system will work in two stages: - A Range finder will continuously track the distance between two vehicles moving and sends it to the ECM using these inputs if it finds the vehicle in the vicinity of the other it will automatically actuate the sensor strip for Electromagnetic Induction. This system is reliable, cost-efficient and fault tolerable. These characteristics enable the vehicle anti-collision in adaptive control environment.

  10. Vehicle Remote Support and Surveillance System

    Directory of Open Access Journals (Sweden)

    Ahmed J. Abid

    2014-06-01

    Full Text Available the proposed design offers a complete solution to support and surveillance vehicles remotely. The offered algorithm allows a monitoring center to track vehicles; diagnoses fault remotely, control the traffic and control CO emission. The system is programmed to scan the on-board diagnostic OBD periodically or based on request to check if there are any faults and read all the available sensors, then make an early fault prediction based on the sensor readings, an experience with the vehicle type and fault history. It is so useful for people who are not familiar with fault diagnosis as well as the maintenance center. The system offers tracking the vehicle remotely, which protects it against theft and warn the driver if it exceeds the speed limit according to its location. Finally, it allows the user to report any traffic congestion and allows a vehicle navigator to be up to date with the traffic condition based on the other system’s user feedback.

  11. ALGORITHM FOR AUTOMATIC DETECTION OF ECG WAVES

    OpenAIRE

    Dib, Nabil; Bereksi-Reguig, Fethi

    2011-01-01

    An accurate measurement of the different electrocardiogram (ECG) intervals is dependent on the accurate identification of the beginning and the end of the P, QRS, and T waves. Available commercial systems provide a good QRS detection accuracy. However, the detection of the P and T waves remains a serious challenge due to their widely differing morphologies in normal and abnormal beats. In this paper, a new algorithm for the detection of the QRS complex as well as for P and T waves identificat...

  12. 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.

  13. 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.

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

    International Nuclear Information System (INIS)

    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)

  15. Design and testing of equipment for nondestructive detection and identification of the location and dimensions of materials defects, especially of cracks in welded joints of pipe systems

    International Nuclear Information System (INIS)

    The prototype of a testing device for the nondestructive detection and identification of defect location and dimensions in a piping, especially of cracks in welded joints, has been evaluated on a laboratory scale. For a variety of reasons, it was not possible yet to perform trials in an industrial-scale system, as eg. in a power plant pipe system or the like. (orig./BBR)

  16. System Identification

    NARCIS (Netherlands)

    Keesman, K.J.

    2011-01-01

    Summary System Identification Introduction.- Part I: Data-based Identification.- System Response Methods.- Frequency Response Methods.- Correlation Methods.- Part II: Time-invariant Systems Identification.- Static Systems Identification.- Dynamic Systems Identification.- Part III: Time-varying Syste

  17. RendezVous sensor for automatic guidance of transfer vehicles to ISS concept of the operational modes depending on actual optical and geometrical-dynamical conditions

    Science.gov (United States)

    Moebius, Bettina G.; Kolk, Karl-Hermann

    2000-10-01

    Based on an ATV RendezVous Predevelopment Program initiated by ESTEC, an automatically operating Rendez Vous Sensor has been developed. The sensor--a Scanning Tele-Goniometer--shall guide docking and retreat of the European Automatic Transfer Vehicle as well as berthing and retreat of the Japanese H-II Transfer Vehicle. The sensor performance will be strongly connected with the properties of cooperative targets, consisting of an arrangement of retro reflectors mounted on ISS each.

  18. Automatic Identification Systems the Effects of Class B on the Use of Class A Systems

    Science.gov (United States)

    Norris, Andy

    2006-05-01

    The standards for CSTDMA Class B AIS will shortly be published by the International Electrotechnical Commission and equipment will become available during 2006. The perceived benefits that Class B brings to leisure craft users and its relatively low cost will make it attractive in the market place. A rapid take-up of Class B use can therefore be expected. This paper considers the impact that increased use of Class B will have on users of Class A AIS that are compulsorily fitted to larger vessels to meet the requirements of the International Maritime Organization Safety of Life at Sea convention. The CSTDMA Class B system has been designed to prevent overloading of the AIS VHF data link. This is briefly reviewed but there are a number of other aspects that need to be considered. These include: the increased garbling of Class B messages compared to those of Class A; the problems accruing from the low update rate of Class B information; the increase in display information that will need to be managed; and the possible increase in inappropriate manoeuvres of leisure craft caused by misplaced reliance on AIS. As a result of the investigation the paper highlights the fact that Class B users must not assume that their own presence, in the form of Class B transmissions, will be particularly visible on the bridge of many SOLAS vessels. This will continue to be the case for many years into the future, until such vessels are mandated to carry radar with AIS target overlay capability.

  19. On-line identification of the speed, steering and diving response parameters of an autonomous underwater vehicle from experimental data

    OpenAIRE

    Bahrke, Fredric G.

    1992-01-01

    Approved for public release; distribution is unlimited. The experimental response data from autonomous maneuvering using the NPS AUV II vehicle has been analyzed with a view to defining Kalman filters to provide on-line estimates of system parameters and their variability. Kalman filters, designed for parameter estimation are expected to be the first step in the development of autonomous fault detection systems for underwater vehicles. Secondly, extraction of vehicle hydrodynamic coefficie...

  20. 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.

  1. Robust vehicle detection even in poor visibility conditions using infrared thermal images and its application to road traffic flow monitoring

    International Nuclear Information System (INIS)

    We propose an algorithm for detecting vehicle positions and their movements by using thermal images obtained through an infrared thermography camera. The infrared thermography camera offers high contrast images even in poor visibility conditions like snow and thick fog. The proposed algorithm specifies the area of moving vehicles based on the standard deviations of pixel values along the time direction of spatio-temporal images. It also specifies vehicle positions by applying the pattern recognition algorithm which uses Haar-like features per frame of the images. Moreover, to increase the accuracy of vehicle detection, correction procedures for misrecognition of vehicles are employed. The results of our experiments at three different temperatures show that the information about both vehicle positions and their movements can be obtained by combining those two kinds of detection, and the vehicle detection accuracy is 96.2%. Moreover, the proposed algorithm detects the vehicles robustly in the 222 continuous frames taken in poor visibility conditions like snow and thick fog. As an application of the algorithm, we also propose a method for estimating traffic flow conditions based on the results obtained by the algorithm. By using the method for estimating traffic flow conditions, automatic traffic flow monitoring can be achieved

  2. Vehicle parameter identification using population based algorithms

    OpenAIRE

    GÖKDAĞ, Hakan

    2015-01-01

    This work deals with parameter identification of a vehicle using population based algorithms such as Particle Swarm Optimization (PSO), Artificial Bee Colony Optimization (ABC) and Genetic Algorithm (GA). Full vehicle model with seven degree of freedom (DoF) is employed, and two objective functions based on reference and computed responses are proposed. Solving the optimization problem vehicle mass, moments of inertia and vehicle center of gravity parameters, which are necessary for later app...

  3. Automatic vehicle detection using spaceborne optical remote sensing images in city area%城市街区星载光学遥感图像车辆目标自动检测方法

    Institute of Scientific and Technical Information of China (English)

    李昭慧; 张建奇

    2014-01-01

    It is difficult to detect vehicles in city area by using paceborne optical remote sensing images, because the background in city area is too complex. In this paper, an automatic vehicle detection method was proposed to address the issue by using background segmentation method. Firstly, the physical property of the vegetation was analyzed and used to suppress the vegetation background of a scene by using the multi- spectral information of the scene. Next, the reflectance characteristics of city area cover types were analyzed. Based on the reflectance characteristics of building roofs and roads, the building background in the scene was removed by employing the binary morphological method on the panchromatic band image. Finally, the famous RX algorithm was introduced to detect the vehicles on the vegetation and building background suppressed image. The proposed method is applied to the actual Quickbird image for vehicle target detection. The results show that the proposed method has strong robustness, high efficiency, and automatic characteristics, and can be used for vehicle detection in city area.%针对星载光学遥感图像城市街区复杂背景问题,提出一种车辆目标自动检测方法。首先,利用场景中植被背景的物理属性,通过多光谱波段抑制场景中的植被背景,然后,在分析城市街区地物形态反射率特性的基础上,利用全色波段并结合二值形态学方法抑制场景中的建筑物,最后,引入著名的RX算法对抑制后的图像进行车辆目标检测。将文中提出的方法应用于实际Quickbird影像的车辆目标检测,结果表明所提出的方法具有鲁棒性强,执行效率高,不需要人工辅助等方面的特点,可用于城市街区车辆目标的自动检测。

  4. Automatic detection of moving objects in video surveillance

    OpenAIRE

    Guezouli, Larbi; Belhani, Hanane

    2016-01-01

    This work is in the field of video surveillance including motion detection. The video surveillance is one of essential techniques for automatic video analysis to extract crucial information or relevant scenes in video surveillance systems. The aim of our work is to propose solutions for the automatic detection of moving objects in real time with a surveillance camera. The detected objects are objects that have some geometric shape (circle, ellipse, square, and rectangle).

  5. Automatic control in systems of the detection and prevention in mines with coal seams liable to sudden landslide. Control automatico de sistemas de prevision y lucha para la explotacion mecanizada de una capa susceptible de desprendimientos instantaneos

    Energy Technology Data Exchange (ETDEWEB)

    Vildes Cechini, E.; Gutierrez Peinador, V. (Escuela de Capataces, Mieres (Spain))

    1992-01-01

    This paper studies an automatic system for the detection and analysis of microtremors which might be induced by the normal activity of coal mining on the terrain above, and the transmission of the acoustic waves which seem to precede a coal landslide caused by firedamp. Two networks of micro-seismic detection, one on the surface, the other underground, collect data which, once analysed, open up the possibility of establishing connections between mining activity and microtremors. Criteria could then be established to prevent such tremors without, however, claiming that prediction is as yet possible. The characteristics and technical specifications of the system used for both the surface and underground networks are described, together with an explanation of the method adopted and a review of the problems which the system presented in relation to its size and design.

  6. 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.

  7. 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.

  8. 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. PMID:27271802

  9. 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.

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

    Science.gov (United States)

    Kang, Min-Joo

    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. PMID:27271802

  11. Automatic Feature Detection, Description and Matching from Mobile Laser Scanning Data and Aerial Imagery

    Science.gov (United States)

    Hussnain, Zille; Oude Elberink, Sander; Vosselman, George

    2016-06-01

    In mobile laser scanning systems, the platform's position is measured by GNSS and IMU, which is often not reliable in urban areas. Consequently, derived Mobile Laser Scanning Point Cloud (MLSPC) lacks expected positioning reliability and accuracy. Many of the current solutions are either semi-automatic or unable to achieve pixel level accuracy. We propose an automatic feature extraction method which involves utilizing corresponding aerial images as a reference data set. The proposed method comprise three steps; image feature detection, description and matching between corresponding patches of nadir aerial and MLSPC ortho images. In the data pre-processing step the MLSPC is patch-wise cropped and converted to ortho images. Furthermore, each aerial image patch covering the area of the corresponding MLSPC patch is also cropped from the aerial image. For feature detection, we implemented an adaptive variant of Harris-operator to automatically detect corner feature points on the vertices of road markings. In feature description phase, we used the LATCH binary descriptor, which is robust to data from different sensors. For descriptor matching, we developed an outlier filtering technique, which exploits the arrangements of relative Euclidean-distances and angles between corresponding sets of feature points. We found that the positioning accuracy of the computed correspondence has achieved the pixel level accuracy, where the image resolution is 12cm. Furthermore, the developed approach is reliable when enough road markings are available in the data sets. We conclude that, in urban areas, the developed approach can reliably extract features necessary to improve the MLSPC accuracy to pixel level.

  12. 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.

  13. 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.

  14. Detection of pneumoconiosis opacities on CT images and its application to automatic diagnosis

    International Nuclear Information System (INIS)

    We propose an automatic diagnosis method of pneumoconiosis by extracting rounded opacities from chest CT images. It can meet the requirement better according to the ILO classification system whose categorization is based on the density of pneumoconiosis opacities. Profusion of small rounded and irregular opacities caused by pneumoconiosis is classified on 4 major categories based on the number of opacities per unit lung area. X-ray CT images give sectional images of human body. There are no overlapping between pneumoconiosis opacities, ribs and blood vessels. It is of great advantage from the viewpoint of image processing to realize automatic diagnosis system. This paper presents a fundamental approach of quantitative diagnosis of pneumoconiosis by detecting rounded opacities of pneumoconiosis on CT images. This method is based on mathematical morphology and consists of five processes. They are extraction of lung area, enhancement of rounded opacity candidates and vessels by morphological processing with multi-structuring elements, detection of rounded opacity, detection of vessels, and calculation of statistical values for quantitative diagnosis. Experiments showed that the correct classification rate on 12 categories was 83%. These results show the effectiveness of the proposed method. (author)

  15. Face Prediction Model for an Automatic Age-invariant Face Recognition System

    OpenAIRE

    Yadav, Poonam

    2015-01-01

    Automated face recognition and identification softwares are becoming part of our daily life; it finds its abode not only with Facebook's auto photo tagging, Apple's iPhoto, Google's Picasa, Microsoft's Kinect, but also in Homeland Security Department's dedicated biometric face detection systems. Most of these automatic face identification systems fail where the effects of aging come into the picture. Little work exists in the literature on the subject of face prediction that accounts for agin...

  16. 钢管焊缝超声自动检测系统能力的鉴定%Identification for the Ability of Steel Pipe Weld Automatic Ultrasonic Testing System

    Institute of Scientific and Technical Information of China (English)

    甘正红; 方晓东; 余洋; 苏继权

    2013-01-01

    In this article, it introduced the main contents to be detected in multichannel steel pipe weld automatic ultrasonic testing system, calibration method to detecting system(equipment), and service conditions of detecting system . Combined with steel pipe weld automatic ultrasonic testing requirements specified in API SPEC 5L/IS0 3183 standard, it discussed the main properties and identification method of multichannel steel pipe weld automatic ultrasonic testing system, provided specific requirements for linearity, horizontal linearity, dynamic range, comprehensive property and others. The feasibility of identification ability was proved through actual application.%介绍了多通道钢管焊缝超声波自动检测系统待检测的主要内容、对检测系统(设备)进行校准的方法以及检测系统的使用条件.结合API SPEC 5L/ISO 3183标准对钢管焊缝超声自动检测的要求,探讨了多通道钢管焊缝超声波自动检测系统的主要性能指标及鉴定方法,给出了主要性能指标如直线性和水平线性、动态范围、综合性能等的具体要求.并通过实际应用表明了鉴定能力的可行性.

  17. 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.

  18. Automatic detection of microcalcifications with multi-fractal spectrum.

    Science.gov (United States)

    Ding, Yong; Dai, Hang; Zhang, Hang

    2014-01-01

    For improving the detection of micro-calcifications (MCs), this paper proposes an automatic detection of MC system making use of multi-fractal spectrum in digitized mammograms. The approach of automatic detection system is based on the principle that normal tissues possess certain fractal properties which change along with the presence of MCs. In this system, multi-fractal spectrum is applied to reveal such fractal properties. By quantifying the deviations of multi-fractal spectrums between normal tissues and MCs, the system can identify MCs altering the fractal properties and finally locate the position of MCs. The performance of the proposed system is compared with the leading automatic detection systems in a mammographic image database. Experimental results demonstrate that the proposed system is statistically superior to most of the compared systems and delivers a superior performance. PMID:25227013

  19. 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

    CERN Document Server

    Møllersen, Kajsa; Zortea, Maciel; Schopf, Thomas R; Hindberg, Kristian; Godtliebsen, Fred

    2016-01-01

    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 percent melanoma sensitivity, ...

  20. Vehicle Tracking and Locking System Based on GSM and GPS

    Directory of Open Access Journals (Sweden)

    R.Ramani

    2013-08-01

    Full Text Available Currently almost of the public having an own vehicle, theft is happening on parking and sometimes driving insecurity places. The safe of vehicles is extremely essential for public vehicles. Vehicle tracking and locking system installed in the vehicle, to track the place and locking engine motor. The place of the vehicle identified using Global Positioning system (GPS and Global system mobile communication (GSM. These systems constantly watch a moving Vehicle and report the status on demand. When the theft identified, the responsible person send SMS to the microcontroller, then microcontroller issue the control signals to stop the engine motor. Authorized person need to send the password to controller to restart the vehicle and open the door. This is more secured, reliable and low cost.

  1. Automatic Detection and Decoding of Photogrammetric Coded Targets

    OpenAIRE

    Wijenayake, Udaya; Choi, Sung-In; Park, Soon-Yong

    2016-01-01

    Close-range Photogrammetry is widely used in many industries because of the cost effectiveness and efficiency of the technique. In this research, we introduce an automated coded target detection method which can be used to enhance the efficiency of the Photogrammetry.

  2. Line matching for automatic change detection algorithm

    Science.gov (United States)

    Dhollande, Jérôme; Monnin, David; Gond, Laetitia; Cudel, Christophe; Kohler, Sophie; Dieterlen, Alain

    2012-06-01

    During foreign operations, Improvised Explosive Devices (IEDs) are one of major threats that soldiers may unfortunately encounter along itineraries. Based on a vehicle-mounted camera, we propose an original approach by image comparison to detect signicant changes on these roads. The classic 2D-image registration techniques do not take into account parallax phenomena. The consequence is that the misregistration errors could be detected as changes. According to stereovision principles, our automatic method compares intensity proles along corresponding epipolar lines by extrema matching. An adaptive space warping compensates scale dierence in 3D-scene. When the signals are matched, the signal dierence highlights changes which are marked in current video.

  3. Human Body Motion Detective Home Security System with Automatic Lamp and User Programmable Text Alert GSM Mobile Phone Number, Unique PIN to Allow Universal Users Using PIR Sensor

    Directory of Open Access Journals (Sweden)

    Oyebola B. O

    2015-06-01

    Full Text Available Insecurity is not a credit to any responsible society, and the conventional use of watch-man has drawbacks of huge risk of life and cost intensive. The use home security system with user programmable text alert GSM mobile phone number with unique PIN to allow universal users with human body motion detective can overcome these limitations. This paper presents reliable security system that is able to recognize human body motion and send an alert message to inform the owner(at any location in the world where there is GSM mobile network coverage of the house through an SMS alert when an unwanted visitor or thief enters the range of the sensor. The system design is in three main phases: the sensitivity, central processing and action. The sensitivity is the perception section that is done through PIR sensor mounted at watch-area, central processing is performed by a programmed microcontroller, and the action (task is done through an interaction of an attached on-board GSM module to the processor (the microcontroller which then send an SMS alert to the user or owner mobile phone number. This system is design to only detect only (or part of human body motion.

  4. 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.

  5. Google Earth Visualizations of the Marine Automatic Identification System (AIS): Monitoring Ship Traffic in National Marine Sanctuaries

    Science.gov (United States)

    Schwehr, K.; Hatch, L.; Thompson, M.; Wiley, D.

    2007-12-01

    The Automatic Identification System (AIS) is a new technology that provides ship position reports with location, time, and identity information without human intervention from ships carrying the transponders to any receiver listening to the broadcasts. In collaboration with the USCG's Research and Development Center, NOAA's Stellwagen Bank National Marine Sanctuary (SBNMS) has installed 3 AIS receivers around Massachusetts Bay to monitor ship traffic transiting the sanctuary and surrounding waters. The SBNMS and the USCG also worked together propose the shifting the shipping lanes (termed the traffic separation scheme; TSS) that transit the sanctuary slightly to the north to reduce the probability of ship strikes of whales that frequent the sanctuary. Following approval by the United Nation's International Maritime Organization, AIS provided a means for NOAA to assess changes in the distribution of shipping traffic caused by formal change in the TSS effective July 1, 2007. However, there was no easy way to visualize this type of time series data. We have created a software package called noaadata-py to process the AIS ship reports and produce KML files for viewing in Google Earth. Ship tracks can be shown changing over time to allow the viewer to feel the motion of traffic through the sanctuary. The ship tracks can also be gridded to create ship traffic density reports for specified periods of time. The density is displayed as map draped on the sea surface or as vertical histogram columns. Additional visualizations such as bathymetry images, S57 nautical charts, and USCG Marine Information for Safety and Law Enforcement (MISLE) can be combined with the ship traffic visualizations to give a more complete picture of the maritime environment. AIS traffic analyses have the potential to give managers throughout NOAA's National Marine Sanctuaries an improved ability to assess the impacts of ship traffic on the marine resources they seek to protect. Viewing ship traffic

  6. 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.

  7. 全自动微生物分析系统对布鲁杆菌属和种鉴定效果的研究%Identification effects of automatic microbial analysis system on brucella genus and species

    Institute of Scientific and Technical Information of China (English)

    肖春霞; 赵鸿雁; 侯临平; 荣蓉; 刘熹; 赵赤鸿; 朴东日; 赵娜; 姜海

    2015-01-01

    Objective To identify and analyse the biochemical characterization of brucella and to evaluate its clinical application by VITEK2 COMPACT automatic microbial identification analyzer.Methods Seventeen strains of standard strains and 121 strains of experimental strains were from bacteria storehouse of brucella disease,Institute of Infectious Diseases Prevention and Control,China Center for Disease Control and Prevention.Experimental strains were from 26 provinces (municipalities and autonomous regions) from 1957 to 2014,including all previous strains from patients and goats,antelope,sheep,cattle,and pig.Reference standard strains and experimental strains were analyzed using the GN identification card on VITEK2 COMPACT automatic microbial identification analyzer,and biochemical identification of brucella strains was done.Identified abnormal strains were rechecked by traditional test methods,including oxidase experiment,urease experiment,semisolid experiment,determination of hydrogen sulfide experiment,basic fuchsin susceptibility experiment,phage lysis experiment,and A/M single-phase specific serum agglutination experiment.Results Of the 138 strains of brucella analyzed by the automatic microbial identification system,the results showed that the main identification indicators of brucella genus were:L-proline arylamidase (ProA),tyrosine arylamidase (TyrA),urease (URE),glycine arylamidase (GlyA),L-lactate alkalinisation (1LATK),and ELLMAN (ELLM).Compared with the system values,all strains biochemical function similar rate was 97.99% (135.23/138),including standard strains was 96.71% (16.44/17),experimental strains was 98.17% (118.79/ 121);time required for strains identification was 6.1-7.7 h,including standard strains was 7.3 h,experimental strains was 6.9 h.Identification indicators for distinguish brucella species were:ProA,TyrA,URE,and GlyA;for distinguish brucella melitensis was ELLM;for distinguish brucella abortus was 1LATK;for distinguish brucella suis was

  8. 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. Secti

  9. Automatic continuous monitoring system for dangerous sites and cargoes

    International Nuclear Information System (INIS)

    The problems of creation of automatic comprehensive continuous monitoring system for nuclear and radiation sites and cargoes of Rosatom Corporation, which carries out data collecting, processing, storage and transmission, including informational support to decision-making, as well as support to modelling and forecasting functions, are considered. The system includes components of two levels: site and industry. Currently the system is used to monitor over 8000 integrated parameters, which characterise the status of nuclear and radiation safety on Rosatom sites, environmental and fire safety

  10. Method and system for reducing errors in vehicle weighing systems

    Energy Technology Data Exchange (ETDEWEB)

    Hively, Lee M. (Philadelphia, TN); Abercrombie, Robert K. (Knoxville, TN)

    2010-08-24

    A method and system (10, 23) for determining vehicle weight to a precision of <0.1%, uses a plurality of weight sensing elements (23), a computer (10) for reading in weighing data for a vehicle (25) and produces a dataset representing the total weight of a vehicle via programming (40-53) that is executable by the computer (10) for (a) providing a plurality of mode parameters that characterize each oscillatory mode in the data due to movement of the vehicle during weighing, (b) by determining the oscillatory mode at which there is a minimum error in the weighing data; (c) processing the weighing data to remove that dynamical oscillation from the weighing data; and (d) repeating steps (a)-(c) until the error in the set of weighing data is <0.1% in the vehicle weight.

  11. Improvement and automatization of a proportional alpha-beta counting system - FAG

    International Nuclear Information System (INIS)

    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)

  12. Automatic Detection and Classification of Pole-Like Objects in Urban Point Cloud Data Using an Anomaly Detection Algorithm

    OpenAIRE

    Borja Rodríguez-Cuenca; Silverio García-Cortés; Celestino Ordóñez; Maria C. Alonso

    2015-01-01

    Detecting and modeling urban furniture are of particular interest for urban management and the development of autonomous driving systems. This paper presents a novel method for detecting and classifying vertical urban objects and trees from unstructured three-dimensional mobile laser scanner (MLS) or terrestrial laser scanner (TLS) point cloud data. The method includes an automatic initial segmentation to remove the parts of the original cloud that are not of interest for detecting vertical o...

  13. 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.

  14. Automatic Payroll Deposit System.

    Science.gov (United States)

    Davidson, D. B.

    1979-01-01

    The Automatic Payroll Deposit System in Yakima, Washington's Public School District No. 7, directly transmits each employee's salary amount for each pay period to a bank or other financial institution. (Author/MLF)

  15. 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 ...

  16. A wireless sensor network design and implementation for vehicle detection, classification, and tracking

    Science.gov (United States)

    Aljaafreh, A.; Al Assaf, A.

    2013-05-01

    Vehicle intrusion is considered a significant threat for critical zones specially the militarized zones and therefore vehicles monitoring has a great importance. In this paper a small wireless sensor network for vehicle intrusion monitoring consists of a five inexpensive sensor nodes distributed over a small area and connected with a gateway using star topology has been designed and implemented. The system is able to detect a passage of an intrusive vehicle, classify it either wheeled or tracked, and track the direction of its movement. The approach is based on Vehicle's ground vibrations for detection, vehicle's acoustic signature for classification and the Energy- based target localization for tracking. Detection and classification are implemented by using different algorithms and techniques including Analog to Digital Conversion, Fast Fourier Transformation (FFT) and Neural Network .All of these algorithms and techniques are implemented locally in the sensor node using Microchip dsPIC digital signal controller. Results are sent from the sensor node to the gateway using ZigBee technology and then from the gateway to a web server using GPRS technology.

  17. Simultaneous Multi-vehicle Detection and Tracking Framework with Pavement Constraints Based on Machine Learning and Particle Filter Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Ke; HUANG Zhi; ZHONG Zhihua

    2014-01-01

    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.

  18. Vehicle Safety Enhancement System: Sensing and Communication

    OpenAIRE

    Huihuan Qian; Yongquan Chen; Yuandong Sun; Niansheng Liu; Ning Ding; Yangsheng Xu; Guoqing Xu; Yunjian Tang; Jingyu Yan

    2013-01-01

    With the substantial increase of vehicles on road, driving safety and transportation efficiency have become increasingly concerned focus from drivers, passengers, and governments. Wireless networks constructed by vehicles and infrastructures provide abundant information to share for the sake of both enhanced safety and network efficiency. This paper presents the systematic research to enhance the vehicle safety by wireless communication, in the aspects of information acquisition through vehic...

  19. Automatic Palette Identification of Colored Graphics

    Science.gov (United States)

    Lacroix, Vinciane

    The median-shift, a new clustering algorithm, is proposed to automatically identify the palette of colored graphics, a pre-requisite for graphics vectorization. The median-shift is an iterative process which shifts each data point to the "median" point of its neighborhood defined thanks to a distance measure and a maximum radius, the only parameter of the method. The process is viewed as a graph transformation which converges to a set of clusters made of one or several connected vertices. As the palette identification depends on color perception, the clustering is performed in the L*a*b* feature space. As pixels located on edges are made of mixed colors not expected to be part of the palette, they are removed from the initial data set by an automatic pre-processing. Results are shown on scanned maps and on the Macbeth color chart and compared to well established methods.

  20. A hybrid fault detection and isolation strategy for a team of cooperating unmanned vehicles

    Science.gov (United States)

    Tousi, M. M.; Khorasani, K.

    2015-01-01

    In this paper, a hybrid fault detection and isolation (FDI) methodology is developed for a team of cooperating unmanned vehicles. The proposed approach takes advantage of the cooperative nature of the team to detect and isolate relatively low-severity actuator faults that are otherwise not detectable and isolable by the vehicles themselves individually. The approach is hybrid and consists of both low-level (agent/team level) and high-level [discrete-event systems (DES) level] FDI modules. The high-level FDI module is formulated in the DES supervisory control framework, whereas the low-level FDI module invokes classical FDI techniques. By properly integrating the two FDI modules, a larger class of faults can be detected and isolated as compared to the existing techniques in the literature that rely on each level separately. Simulation results for a team of five unmanned aerial vehicles are also presented to demonstrate the effectiveness and capabilities of our proposed methodology.

  1. Automatic graphene transfer system for improved material quality and efficiency

    Science.gov (United States)

    Boscá, Alberto; Pedrós, Jorge; Martínez, Javier; Palacios, Tomás; Calle, Fernando

    2016-02-01

    In most applications based on chemical vapor deposition (CVD) graphene, the transfer from the growth to the target substrate is a critical step for the final device performance. Manual procedures are time consuming and depend on handling skills, whereas existing automatic roll-to-roll methods work well for flexible substrates but tend to induce mechanical damage in rigid ones. A new system that automatically transfers CVD graphene to an arbitrary target substrate has been developed. The process is based on the all-fluidic manipulation of the graphene to avoid mechanical damage, strain and contamination, and on the combination of capillary action and electrostatic repulsion between the graphene and its container to ensure a centered sample on top of the target substrate. The improved carrier mobility and yield of the automatically transferred graphene, as compared to that manually transferred, is demonstrated by the optical and electrical characterization of field-effect transistors fabricated on both materials. In particular, 70% higher mobility values, with a 30% decrease in the unintentional doping and a 10% strain reduction are achieved. The system has been developed for lab-scale transfer and proved to be scalable for industrial applications.

  2. 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.

  3. Comparison of terahertz technologies for detection and identification of explosives

    Science.gov (United States)

    Beigang, René; Biedron, Sandra G.; Dyjak, Slawomir; Ellrich, Frank; Haakestad, Magnus W.; Hübsch, Daniel; Kartaloglu, Tolga; Ozbay, Ekmel; Ospald, Frank; Palka, Norbert; Puc, Uroš; Czerwińska, ElŻbieta; Sahin, Asaf B.; Sešek, Aleksander; Trontelj, Janez; Å vigelj, Andrej; Altan, Hakan; van Rheenen, Arthur D.; Walczakowski, Michał

    2014-05-01

    We present results on the comparison of different THz technologies for the detection and identification of a variety of explosives from our laboratory tests that were carried out in the framework of NATO SET-193 "THz technology for stand-off detection of explosives: from laboratory spectroscopy to detection in the field" under the same controlled conditions. Several laser-pumped pulsed broadband THz time-domain spectroscopy (TDS) systems as well as one electronic frequency-modulated continuous wave (FMCW) device recorded THz spectra in transmission and/or reflection.

  4. 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…

  5. A Method for Automatic Identification of Reliable Heart Rates Calculated from ECG and PPG Waveforms

    OpenAIRE

    Yu, Chenggang; Liu, Zhenqiu; McKenna, Thomas; Reisner, Andrew T.; Reifman, Jaques

    2006-01-01

    Objective: The development and application of data-driven decision-support systems for medical triage, diagnostics, and prognostics pose special requirements on physiologic data. In particular, that data are reliable in order to produce meaningful results. The authors describe a method that automatically estimates the reliability of reference heart rates (HRr) derived from electrocardiogram (ECG) waveforms and photoplethysmogram (PPG) waveforms recorded by vital-signs monitors. The reliabilit...

  6. 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

  7. Contribution to automatic speech recognition. Analysis of the direct acoustical signal. Recognition of isolated words and phoneme identification

    International Nuclear Information System (INIS)

    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)

  8. Vehicle Detection and Classification Using Passive Infrared Sensing

    KAUST Repository

    Oudat, Enas

    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.

  9. Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods

    Science.gov (United States)

    Maquet, Pierre

    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.

  10. 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.

  11. Adaboost Technique for Vehicle Detection in Aerial Surveillance

    OpenAIRE

    R. Sindoori; Ravichandran, K.S.; B. Santhi

    2013-01-01

    An approach for vehicle detection system from satellite images, which are used in many applications. Vehicle detection is done by pixelwise classification method instead sliding window and region based methods, which are used in existing system. The vital part of the paper is feature extraction and vehicle colour classification. Feature extraction includes edge and corner detection. For edgedetection, the Canny edge detector technique is applied. For, corner detection, the Harris corner detec...

  12. A semi-automatic method for peak and valley detection in free-breathing respiratory waveforms

    International Nuclear Information System (INIS)

    The existing commercial software often inadequately determines respiratory peaks for patients in respiration correlated computed tomography. A semi-automatic method was developed for peak and valley detection in free-breathing respiratory waveforms. First the waveform is separated into breath cycles by identifying intercepts of a moving average curve with the inspiration and expiration branches of the waveform. Peaks and valleys were then defined, respectively, as the maximum and minimum between pairs of alternating inspiration and expiration intercepts. Finally, automatic corrections and manual user interventions were employed. On average for each of the 20 patients, 99% of 307 peaks and valleys were automatically detected in 2.8 s. This method was robust for bellows waveforms with large variations

  13. Semi-automatic charge and mass identification in two-dimensional matrices

    CERN Document Server

    Gruyer, Diego; Chbihi, A; Frankland, J D; Barlini, S; Borderie, B; Bougault, R; Duenas, J A; Neindre, N Le; Lopez, O; Pastore, G; Piantelli, S; Valdre, S; Verde, G; Vient, E

    2016-01-01

    This article presents a new semi-automatic method for charge and mass identification in two-dimensional matrices. The proposed algorithm is based on the matrix's properties and uses as little information as possible on the global form of the iden tification lines, making it applicable to a large variety of matrices, including various $\\Delta$E-E correlations, or those coming from Pulse Shape Analysis of the charge signal in silicon detectors. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented.

  14. Automatic Screening of Missing Objects and Identification with Group Coding of RF Tags

    OpenAIRE

    G. Vijayaraju

    2013-01-01

    Here the container of the shipping based phenomena it is a collection of the objects in a well oriented fashion by which there is a group oriented fashion related to the well efficient strategy of the objects based on the physical phenomena in a well efficient fashion respectively. Here by the enabling of the radio frequency identification based strategy in which object identification takes place in the system in a well efficient fashion and followed by the container oriented strategy in ...

  15. Unmanned Aerial Vehicles for Alien Plant Species Detection and Monitoring

    Science.gov (United States)

    Dvořák, P.; Müllerová, J.; Bartaloš, T.; Brůna, J.

    2015-08-01

    Invasive species spread rapidly and their eradication is difficult. New methods enabling fast and efficient monitoring are urgently needed for their successful control. Remote sensing can improve early detection of invading plants and make their management more efficient and less expensive. In an ongoing project in the Czech Republic, we aim at developing innovative methods of mapping invasive plant species (semi-automatic detection algorithms) by using purposely designed unmanned aircraft (UAV). We examine possibilities for detection of two tree and two herb invasive species. Our aim is to establish fast, repeatable and efficient computer-assisted method of timely monitoring, reducing the costs of extensive field campaigns. For finding the best detection algorithm we test various classification approaches (object-, pixel-based and hybrid). Thanks to its flexibility and low cost, UAV enables assessing the effect of phenological stage and spatial resolution, and is most suitable for monitoring the efficiency of eradication efforts. However, several challenges exist in UAV application, such as geometrical and radiometric distortions, high amount of data to be processed and legal constrains for the UAV flight missions over urban areas (often highly invaded). The newly proposed UAV approach shall serve invasive species researchers, management practitioners and policy makers.

  16. UNMANNED AERIAL VEHICLES FOR ALIEN PLANT SPECIES DETECTION AND MONITORING

    Directory of Open Access Journals (Sweden)

    P. Dvořák

    2015-08-01

    Full Text Available Invasive species spread rapidly and their eradication is difficult. New methods enabling fast and efficient monitoring are urgently needed for their successful control. Remote sensing can improve early detection of invading plants and make their management more efficient and less expensive. In an ongoing project in the Czech Republic, we aim at developing innovative methods of mapping invasive plant species (semi-automatic detection algorithms by using purposely designed unmanned aircraft (UAV. We examine possibilities for detection of two tree and two herb invasive species. Our aim is to establish fast, repeatable and efficient computer-assisted method of timely monitoring, reducing the costs of extensive field campaigns. For finding the best detection algorithm we test various classification approaches (object-, pixel-based and hybrid. Thanks to its flexibility and low cost, UAV enables assessing the effect of phenological stage and spatial resolution, and is most suitable for monitoring the efficiency of eradication efforts. However, several challenges exist in UAV application, such as geometrical and radiometric distortions, high amount of data to be processed and legal constrains for the UAV flight missions over urban areas (often highly invaded. The newly proposed UAV approach shall serve invasive species researchers, management practitioners and policy makers.

  17. Automatic segmentation and centroid detection of skin sensors for lung interventions

    Science.gov (United States)

    Lu, Kongkuo; Xu, Sheng; Xue, Zhong; Wong, Stephen T.

    2012-02-01

    Electromagnetic (EM) tracking has been recognized as a valuable tool for locating the interventional devices in procedures such as lung and liver biopsy or ablation. The advantage of this technology is its real-time connection to the 3D volumetric roadmap, i.e. CT, of a patient's anatomy while the intervention is performed. EM-based guidance requires tracking of the tip of the interventional device, transforming the location of the device onto pre-operative CT images, and superimposing the device in the 3D images to assist physicians to complete the procedure more effectively. A key requirement of this data integration is to find automatically the mapping between EM and CT coordinate systems. Thus, skin fiducial sensors are attached to patients before acquiring the pre-operative CTs. Then, those sensors can be recognized in both CT and EM coordinate systems and used calculate the transformation matrix. In this paper, to enable the EM-based navigation workflow and reduce procedural preparation time, an automatic fiducial detection method is proposed to obtain the centroids of the sensors from the pre-operative CT. The approach has been applied to 13 rabbit datasets derived from an animal study and eight human images from an observation study. The numerical results show that it is a reliable and efficient method for use in EM-guided application.

  18. Automatic detection of microaneurysms using microstructure and wavelet methods

    Indian Academy of Sciences (India)

    M Tamilarasi; K Duraiswamy

    2015-06-01

    Retinal microaneurysm is one of the earliest signs in diabetic retinopathy diagnosis. This paper has developed an approach to automate the detection of microaneurysms using wavelet-based Gaussian mixture model and microstructure texture feature extraction. First, the green channel of the colour retinal fundus image is extracted and pre-processed using various enhancement techniques such as bottom-hat filtering and gamma correction. Second, microstructures are extracted as Gaussian profiles in wavelet domain using the three-level generative model. Multiscale Gaussian kernels are obtained and histogram-based features are extracted from the best kernel. Using the Markov Chain Monte Carlo method, microaneurysms are classified using the optimal feature set. 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 specificity of 98.91 and 97.65 have been achieved. The accuracies achieved by the proposed algorithm are 97.86 and 98.33 using DIARETDB0 and DIARETDB1 datasets respectively. Based on ground truth validation, good segmentation results are achieved when compared to existing algorithms such as local relative entropy-based thresholding, inverse adaptive surface thresholding, inverse segmentation method, and dark object segmentation.

  19. Track identification and reconstruction in fast neutron detection by MPGD

    CERN Document Server

    Zhang, Yi; Zhao, Shengying; Hu, Bitao

    2015-01-01

    Micro pattern gaseous detectors have been widely used in position measurements of particle detection in the last two decades. In this work a novel method of track identification and reconstruction was developed for fast neutron detection by MPGD, which in most cases requires a strong rejection of the gamma background. Based on this method, an online tracking system can be built in a FPGA-based Daq system to significantly improve both the capability of counting rate and the spatial resolution. This work also offers a potential usage in future hadron experiments such as SoLID spectrometer in Jeffereson Lab.

  20. Explodet Project:. Methods of Automatic Data Processing and Analysis for the Detection of Hidden Explosive

    Science.gov (United States)

    Lecca, Paola

    2003-12-01

    The research of the INFN Gruppo Collegato di Trento in the ambit of EXPLODET project for the humanitarian demining, is devoted to the development of a software procedure for the automatization of data analysis and decision taking about the presence of hidden explosive. Innovative algorithms of likely background calculation, a system based on neural networks for energy calibration and simple statistical methods for the qualitative consistency check of the signals are the main parts of the software performing the automatic data elaboration.

  1. 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.

  2. Automatic System for Serving and Deploying Products into Advertising Space

    OpenAIRE

    Lepen, Nejc

    2014-01-01

    The purpose of the thesis is to present the problems of deploying and serving products into advertising space,encountered daily by online marketers,planners and leaseholders of advertising spaces.The aim of the thesis is to solve the problem in question with the help of a novel web application.Therefore,we have designed an automatic system,which consists of three key components:an online store,a surveillance system and websites accommodating advertising space.In the course of this thesis,we h...

  3. 航空影像辅助下的城区机载LiDAR汽车目标检测方法%Automatic Urban Vehicle Detection from Airborne LiDAR Data with Aerial Image

    Institute of Scientific and Technical Information of China (English)

    孙美玲; 李永树; 陈强

    2014-01-01

    The appearance of LiDAR technology provides a new method for automatic vehicle detection.In order to detect vehicle object from LiDAR data,according to the property features of different objects,a new method of automatic urban vehicle detection from airborne LiDAR data with aerial image is proposed in this paper.Firstly,it is classified ground and non-ground points using LiDAR filtering with morphological opening by reconstruction.Secondly,with the help of aerial image and its Normalized Differential Vegetation Index (NDVI) feature,it could classify LiDAR non-ground points into vegetation and non-vegetation objects.Finally,On the basis of non-vegetation objects,it could separate vehicle objects automatically from other non-vehicle objects by shape feature and height property.Three regions has been used to verify the feasibility and reliability of this method.The experiment results show that the proposed method can effectively extract vehicle objects.The mean of correctness and completeness of this method can reach 95% and 85 % respectively,which can meet the practical requirements.%机载激光雷达(LiDAR)技术的出现为地面汽车目标检测提供了新的途径.为了从机载Li-DAR点云数据中提取汽车对象,根据不同地物的属性特征,提出了一种航空影像辅助下的城区机载LiDAR汽车目标检测方法.首先利用形态学开重建滤波完成地面和地物的分类,然后在地物点的基础上结合正射影像,通过归一化植被指数(NDVI)特征完成对植被和非植被地物的初步分类,最后在非植被地物的基础上,根据地物对象的形状特征及高程信息完成汽车和建筑物及阴影植被等非汽车对象的分类,从而完成汽车目标的提取工作.3个实验区的计算结果表明:该方法能有效从LiDAR点云中提取汽车目标,正确度和完整度的均值分别为95%和85%,满足实用性要求.

  4. On the advances of automatic modal identification for SHM

    Directory of Open Access Journals (Sweden)

    Cardoso Rharã

    2015-01-01

    Full Text Available Structural health monitoring of civil infrastructures has great practical importance for engineers, owners and stakeholders. Numerous researches have been carried out using long-term monitoring, for instance the Rio-Niterói Bridge in Brazil, the former Z24 Bridge in Switzerland, the Millau Bridge in France, among others. In fact, some structures are monitored 24/7 in order to supply dynamic measurements that can be used for the identification of structural problems such as the presence of cracks, excessive vibration, damage or even to perform a quite extensive structural evaluation concerning its reliability and life cycle. The outputs of such an analysis, commonly entitled modal identification, are the so-called modal parameters, i.e. natural frequencies, damping ratios and mode shapes. Therefore, the development and validation of tools for the automatic identification of modal parameters based on the structural responses during normal operation is fundamental, as the success of subsequent damage detection algorithms depends on the accuracy of the modal parameters estimates. The proposed methodology uses the data driven stochastic subspace identification method (SSI-DATA, which is then complemented by a novel procedure developed for the automatic analysis of the stabilization diagrams provided by the SSI-DATA method. The efficiency of the proposed approach is attested via experimental investigations on a simply supported beam tested in laboratory and on a motorway bridge.

  5. AN AUTOMATIC LEAF RECOGNITION SYSTEM FOR PLANT IDENTIFICATION USING MACHINE VISION TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    VIJAY SATTI

    2013-04-01

    Full Text Available Plants are the backbone of all life on Earth and an essential resource for human well-being. Plant recognition is very important in agriculture for the management of plant species whereas botanists can use this application for medicinal purposes. Leaf of different plants have different characteristics which can be used to classify them.This paper presents a simple and computationally efficient method for plant identification using digital image processing and machine vision technology. The proposed approach consists of three phases: pre-processing, feature extraction and classification. Pre- processing is the technique of enhancing data images prior to computational processing. The feature extraction phase derives features based on color and shape of the leaf image. These features are used as inputs to the classifier for efficient classification and the results were tested and compared using Artificial Neural Network (ANN and Euclidean (KNN classifier. The network was trained with 1907 sample leaves of 33 different plant species taken form Flavia dataset. The proposed approach is 93.3 percent accurate using ANN classifier and the comparison of classifiers shows that ANN takes less average time for execution than Euclidean distance method.

  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. OPTIMAL CONTROL APPLIED IN AUTOMATIC CLUTCH ENGAGEMENTS OF VEHICLES

    Institute of Scientific and Technical Information of China (English)

    Sun Chengshun; Zhang Jianwu

    2004-01-01

    Start-up working condition is the key to the research of optimal engagement of automatic clutch for AMT.In order to guarantee an ideal dynamic performance of the clutch engagement,an optimal controller is designed by considering throttle angle,engine speed,gear ratio,vehicle acceleration and road condition.The minimum value principle is also introduced to achieve an optimal dynamic performance of the nonlinear system compromised in friction plate wear and vehicle drive quality.The optimal trajectory of the clutch engagement can be described in the form of explicit and analytical expressions and characterized by the deterministic and accurate control strategy in stead of indeterministic and soft control techniques which need thousands of experiments.For validation of the controller,test work is carried out for the automated clutch engagements in a commercial car with an traditional mechanical transmission,a hydraulic actuator,a group of sensors and a portable computer system.It is shown through experiments that dynamic behaviors of the clutch engagement operated by the optimal control are more effective and efficient than those by fuzzy control.

  8. Automatic data processing and analysis system for monitoring region around a planned nuclear power plant

    Science.gov (United States)

    Kortström, Jari; Tiira, Timo; Kaisko, Outi

    2016-03-01

    The Institute of Seismology of University of Helsinki is building a new local seismic network, called OBF network, around planned nuclear power plant in Northern Ostrobothnia, Finland. The network will consist of nine new stations and one existing station. The network should be dense enough to provide azimuthal coverage better than 180° and automatic detection capability down to ML -0.1 within a radius of 25 km from the site.The network construction work began in 2012 and the first four stations started operation at the end of May 2013. We applied an automatic seismic signal detection and event location system to a network of 13 stations consisting of the four new stations and the nearest stations of Finnish and Swedish national seismic networks. Between the end of May and December 2013 the network detected 214 events inside the predefined area of 50 km radius surrounding the planned nuclear power plant site. Of those detections, 120 were identified as spurious events. A total of 74 events were associated with known quarries and mining areas. The average location error, calculated as a difference between the announced location from environment authorities and companies and the automatic location, was 2.9 km. During the same time period eight earthquakes between magnitude range 0.1-1.0 occurred within the area. Of these seven could be automatically detected. The results from the phase 1 stations of the OBF network indicates that the planned network can achieve its goals.

  9. Automatic detection and morphological delineation of bacteriophages in electron microscopy images.

    Science.gov (United States)

    Gelzinis, A; Verikas, A; Vaiciukynas, E; Bacauskiene, M; Sulcius, S; Simoliunas, E; Staniulis, J; Paskauskas, R

    2015-09-01

    Automatic detection, recognition and geometric characterization of bacteriophages in electron microscopy images was the main objective of this work. A novel technique, combining phase congruency-based image enhancement, Hough transform-, Radon transform- and open active contours with free boundary conditions-based object detection was developed to detect and recognize the bacteriophages associated with infection and lysis of cyanobacteria Aphanizomenon flos-aquae. A random forest classifier designed to recognize phage capsids provided higher than 99% accuracy, while measurable phage tails were detected and associated with a correct capsid with 81.35% accuracy. Automatically derived morphometric measurements of phage capsids and tails exhibited lower variability than the ones obtained manually. The technique allows performing precise and accurate quantitative (e.g. abundance estimation) and qualitative (e.g. diversity and capsid size) measurements for studying the interactions between host population and different phages that infect the same host.

  10. 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.

  11. Internal combustion engine for vehicles with automatic gearbox. Brennkraftmaschine fuer Kraftfahrzeuge mit einem automatischen Getriebe

    Energy Technology Data Exchange (ETDEWEB)

    Hetmann, R.

    1982-04-19

    The invention refers to an internal combustion engine for vehicles with an automatic gearbox, where the internal combustion engine has a first group of cylinders and at least one second group of cylinders, and a device for affecting the fuel supply to the groups of cylinders, depending on the working parameters of the vehicle. The invention is characterised by the fact that the working parameters are the handbrake and footbrake of the vehicle, and that the device for affecting the fuel supply to the groups of cylinders when the footbrake or handbrake is operated makes it possible to supply fuel to only part of the groups of cylinders. The control switches of both braking systems are connected to the fuel supply control via a logic circuit. This arrangement of the system prevents damage when testing the braking speed of the automatic gearbox due to excessive loads.

  12. 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.

  13. Scheduling vehicles in automated transportation systems : algorithms and case study

    OpenAIRE

    Heijden, van der, T.G.C.; Ebben, MJR; Gademann, AJRM Noud; Harten, van, W.H.

    2000-01-01

    One of the major planning issues in large scale automated transportation systems is so-called empty vehicle management, the timely supply of vehicles to terminals in order to reduce cargo waiting times. Motivated by a Dutch pilot project on an underground cargo transportation system using Automated Guided Vehicles CAGV s), we developed several rules and algorithms for empty vehicle management, varying from trivial First-Come, First-Served (FCFS) via look-ahead rules to integral planning. For ...

  14. 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

    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...

  15. Desktop calibration of automatic transmission for passenger vehicle

    Institute of Scientific and Technical Information of China (English)

    FANG Chi; SHI Jian-peng; WANG Jun

    2014-01-01

    Desktop calibration of automatic transmission (AT) is a method which can reduce cost, enhance efficiency and shorten the development periods of a vehicle effectively. We primary introduced the principle and approach of desktop calibration of AT based on the condition of coupling characteristics between engine and torque converter and obtained right point exactly. It is shown to agree with experimental measurements reasonably well. It was used in different applications abroad based on AT technology and achieved a good performance of the vehicle compared with traditional AT technology which primary focuses on the drivability, performance and fuel consumption.

  16. Google started to build automatic driving vehicle

    Institute of Scientific and Technical Information of China (English)

    2014-01-01

    <正>The car will have a stop-go button but no controls,steering wheel or pedals.Pictures of the Google vehicle show it looks like a city car with a"friendly"face,designed to make it seem non-threatening and help people accept self-driving technology.Co-founder Sergey Brin revealed the plans at a conference in California."We’re really excited about this vehicle

  17. 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.

  18. Automatic landslides detection on Stromboli volcanic Island

    Science.gov (United States)

    Silengo, Maria Cristina; Delle Donne, Dario; Ulivieri, Giacomo; Cigolini, Corrado; Ripepe, Maurizio

    2016-04-01

    Landslides occurring in active volcanic islands play a key role in triggering tsunami and other related risks. Therefore, it becomes vital for a correct and prompt risk assessment to monitor landslides activity and to have an automatic system for a robust early-warning. We then developed a system based on a multi-frequency analysis of seismic signals for automatic landslides detection occurring at Stromboli volcano. We used a network of 4 seismic 3 components stations located along the unstable flank of the Sciara del Fuoco. Our method is able to recognize and separate the different sources of seismic signals related to volcanic and tectonic activity (e.g. tremor, explosions, earthquake) from landslides. This is done using a multi-frequency analysis combined with a waveform patter recognition. We applied the method to one year of seismic activity of Stromboli volcano centered during the last 2007 effusive eruption. This eruption was characterized by a pre-eruptive landslide activity reflecting the slow deformation of the volcano edifice. The algorithm is at the moment running off-line but has proved to be robust and efficient in picking automatically landslide. The method provides also real-time statistics on the landslide occurrence, which could be used as a proxy for the volcano deformation during the pre-eruptive phases. This method is very promising since the number of false detections is quite small (detection as an improving tool for early warnings of tsunami-genic landslide activity. We suggest that a similar approach could be also applied to other unstable non-volcanic also slopes.

  19. Automatic Vehicle Extraction from Airborne LiDAR Data Using an Object-Based Point Cloud Analysis Method

    Directory of Open Access Journals (Sweden)

    Jixian Zhang

    2014-09-01

    Full Text Available Automatic vehicle extraction from an airborne laser scanning (ALS point cloud is very useful for many applications, such as digital elevation model generation and 3D building reconstruction. In this article, an object-based point cloud analysis (OBPCA method is proposed for vehicle extraction from an ALS point cloud. First, a segmentation-based progressive TIN (triangular irregular network densification is employed to detect the ground points, and the potential vehicle points are detected based on the normalized heights of the non-ground points. Second, 3D connected component analysis is performed to group the potential vehicle points into segments. At last, vehicle segments are detected based on three features, including area, rectangularity and elongatedness. Experiments suggest that the proposed method is capable of achieving higher accuracy than the exiting mean-shift-based method for vehicle extraction from an ALS point cloud. Moreover, the larger the point density is, the higher the achieved accuracy is.

  20. Automatic program debugging for intelligent tutoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Murray, W.R.

    1986-01-01

    This thesis explores the process by which student programs can be automatically debugged in order to increase the instructional capabilities of these systems. This research presents a methodology and implementation for the diagnosis and correction of nontrivial recursive programs. In this approach, recursive programs are debugged by repairing induction proofs in the Boyer-Moore Logic. The potential of a program debugger to automatically debug widely varying novice programs in a nontrivial domain is proportional to its capabilities to reason about computational semantics. By increasing these reasoning capabilities a more powerful and robust system can result. This thesis supports these claims by examining related work in automated program debugging and by discussing the design, implementation, and evaluation of Talus, an automatic degugger for LISP programs. Talus relies on its abilities to reason about computational semantics to perform algorithm recognition, infer code teleology, and to automatically detect and correct nonsyntactic errors in student programs written in a restricted, but nontrivial, subset of LISP.

  1. The Design on Automatic Detection System of Ventilating and Leaking of Disposable Infusion Tube Based on PLC%基于PLC的一次性输液管通、漏气自动检测系统设计

    Institute of Scientific and Technical Information of China (English)

    夏链; 李福根; 韩春明

    2011-01-01

    一次性输液管是医疗行业不可或缺用来给病人进行静脉输液的器件.对其通气和漏气质量检测是其生产过程中极为重要的环节.通过调研发现,国内主要采用手工进行检测,自动检测装置很少,生产效率低.本文设计了一种基于PLC控制的自动检测装置.经过试验,能够实现自动检测,与手工检测相比,大大提高了工作效率和检测质量的可靠性.%Disposable infusion tube is essential for the medical industry,which is the device of intravenous infusion for the patient. The quality detecting of ventilating and leaking is an important part of the Production process. Through research, it has been found that most detecting is manual in our country and automatic detection devices are few,thus the production efficiency is low. A kind of automatic detection device based on PLC controlled has been designed. After testing, the results show that it can achieve automatic detection. Compared with the manual detecting,the efficiency and reliability of quality detecting greatly improve.

  2. 30 CFR 75.1103-3 - Automatic fire sensor and warning device systems; minimum requirements; general.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic fire sensor and warning device...-UNDERGROUND COAL MINES Fire Protection § 75.1103-3 Automatic fire sensor and warning device systems; minimum requirements; general. Automatic fire sensor and warning device systems installed in belt haulageways...

  3. Sideband Algorithm for Automatic Wind Turbine Gearbox Fault Detection and Diagnosis: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zappala, D.; Tavner, P.; Crabtree, C.; Sheng, S.

    2013-01-01

    Improving the availability of wind turbines (WT) is critical to minimize the cost of wind energy, especially for offshore installations. As gearbox downtime has a significant impact on WT availabilities, the development of reliable and cost-effective gearbox condition monitoring systems (CMS) is of great concern to the wind industry. Timely detection and diagnosis of developing gear defects within a gearbox is an essential part of minimizing unplanned downtime of wind turbines. Monitoring signals from WT gearboxes are highly non-stationary as turbine load and speed vary continuously with time. Time-consuming and costly manual handling of large amounts of monitoring data represent one of the main limitations of most current CMSs, so automated algorithms are required. This paper presents a fault detection algorithm for incorporation into a commercial CMS for automatic gear fault detection and diagnosis. The algorithm allowed the assessment of gear fault severity by tracking progressive tooth gear damage during variable speed and load operating conditions of the test rig. Results show that the proposed technique proves efficient and reliable for detecting gear damage. Once implemented into WT CMSs, this algorithm can automate data interpretation reducing the quantity of information that WT operators must handle.

  4. Breast Contrast Enhanced MR Imaging: Semi-Automatic Detection of Vascular Map and Predominant Feeding Vessel

    Science.gov (United States)

    Petrillo, Antonella; Fusco, Roberta; Filice, Salvatore; Granata, Vincenza; Catalano, Orlando; Vallone, Paolo; Di Bonito, Maurizio; D’Aiuto, Massimiliano; Rinaldo, Massimo; Capasso, Immacolata; Sansone, Mario

    2016-01-01

    Purpose To obtain breast vascular map and to assess correlation between predominant feeding vessel and tumor location with a semi-automatic method compared to conventional radiologic reading. Methods 148 malignant and 75 benign breast lesions were included. All patients underwent bilateral MR imaging. Written informed consent was obtained from the patients before MRI. The local ethics committee granted approval for this study. Semi-automatic breast vascular map and predominant vessel detection was performed on MRI, for each patient. Semi-automatic detection (depending on grey levels threshold manually chosen by radiologist) was compared with results of two expert radiologists; inter-observer variability and reliability of semi-automatic approach were assessed. Results Anatomic analysis of breast lesions revealed that 20% of patients had masses in internal half, 50% in external half and the 30% in subareolar/central area. As regards the 44 tumors in internal half, based on radiologic consensus, 40 demonstrated a predominant feeding vessel (61% were supplied by internal thoracic vessels, 14% by lateral thoracic vessels, 16% by both thoracic vessels and 9% had no predominant feeding vessel—p<0.01), based on semi-automatic detection, 38 tumors demonstrated a predominant feeding vessel (66% were supplied by internal thoracic vessels, 11% by lateral thoracic vessels, 9% by both thoracic vessels and 14% had no predominant feeding vessel—p<0.01). As regards the 111 tumors in external half, based on radiologic consensus, 91 demonstrated a predominant feeding vessel (25% were supplied by internal thoracic vessels, 39% by lateral thoracic vessels, 18% by both thoracic vessels and 18% had no predominant feeding vessel—p<0.01), based on semi-automatic detection, 94 demonstrated a predominant feeding vessel (27% were supplied by internal thoracic vessels, 45% by lateral thoracic vessels, 4% by both thoracic vessels and 24% had no predominant feeding vessel—p<0.01). An

  5. Automatic Detection of Buildings and Changes in Buildings for Updating of Maps

    Directory of Open Access Journals (Sweden)

    Harri Kaartinen

    2010-04-01

    Full Text Available There is currently high interest in developing automated methods to assist the updating of map databases. This study presents methods for automatic detection of buildings and changes in buildings from airborne laser scanner and digital aerial image data and shows the potential usefulness of the methods with thorough experiments in a 5 km2 suburban study area. 96% of buildings larger than 60 m2 were correctly detected in the building detection. The completeness and correctness of the change detection for buildings larger than 60 m2 were about 85% (including five classes. Most of the errors occurred in small or otherwise problematic buildings.

  6. Bayesian robot system identification with input and output noise.

    Science.gov (United States)

    Ting, Jo-Anne; D'Souza, Aaron; Schaal, Stefan

    2011-01-01

    For complex robots such as humanoids, model-based control is highly beneficial for accurate tracking while keeping negative feedback gains low for compliance. However, in such multi degree-of-freedom lightweight systems, conventional identification of rigid body dynamics models using CAD data and actuator models is inaccurate due to unknown nonlinear robot dynamic effects. An alternative method is data-driven parameter estimation, but significant noise in measured and inferred variables affects it adversely. Moreover, standard estimation procedures may give physically inconsistent results due to unmodeled nonlinearities or insufficiently rich data. This paper addresses these problems, proposing a Bayesian system identification technique for linear or piecewise linear systems. Inspired by Factor Analysis regression, we develop a computationally efficient variational Bayesian regression algorithm that is robust to ill-conditioned data, automatically detects relevant features, and identifies input and output noise. We evaluate our approach on rigid body parameter estimation for various robotic systems, achieving an error of up to three times lower than other state-of-the-art machine learning methods.

  7. A new vehicle detection method

    Directory of Open Access Journals (Sweden)

    Zebbara Khalid

    2011-09-01

    Full Text Available This paper presents a new vehicle detection method from images acquired by cameras embedded in a moving vehicle. Given the sequence of images, the proposed algorithms should detect out all cars in realtime. Related to the driving direction, the cars can be classified into two types. Cars drive in the same direction as the intelligent vehicle (IV and cars drive in the opposite direction. Due to the distinct features of these two types, we suggest to achieve this method in two main steps. The first one detects all obstacles from images using the so-called association combined with corner detector. The second step is applied to validate each vehicle using AdaBoost classifier. The new method has been applied to different images data and the experimental results validate the efficacy of our method.

  8. Model Identification of a Micro Air Vehicle

    Institute of Scientific and Technical Information of China (English)

    Jorge Ni(n)o; Flavius Mitrache; Peter Cosyn; Robin De Keyser

    2007-01-01

    This paper is focused on the model identification of a Micro Air Vehicle (MAV) in straight steady flight condition. The identification is based on input-output data collected from flight tests using both frequency and time dontain techniques. The vehicle is an in-house 40 cm wingspan airplane. Because of the complex coupled, multivariable and nonlinear dynamics of the aircraft, linear SISO structures for both the lateral and longitudinal models around a reference state were derived. The aim of the identification is to provide models that can be used in future development of control techniques for the MAV.

  9. 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.

  10. 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.

  11. 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.

  12. Explosive Detection and Identification by PGNAA

    International Nuclear Information System (INIS)

    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

  13. Automatic Identification of Storm Cells Using Doppler Radars

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Three storm automatic identification algorithms for Doppler radar axe discussed. The WSR-88D Build 7.0 (B7SI) tests the intensity and continuity of the objective echoes by multiple-prescribed thresholds to build 3D storms, and when storms are merging, splitting, or clustered closely, the detection errors become larger. The B9SI algorithm is part of the Build 9.0 Radar Products Generator of the WSR-88D system. It uses multiple thresholds of reflectivity, newly designs the techniques of cell nucleus extraction and close-storms processing, and therefore is capable of identifying embedded cells in multi-cellular storms. The strong area components at a long distance are saved as 2D storms. However, the B9SI cannot give information on the convection strength of storm, because texture and gradient of reflectivity are not calculated and radial velocity data are not used. To overcome this limitation, the CSI (Convective Storm Identification) algorithm is designed in this paper. By using the fuzzy logic technique, and under the condition that the levels of the seven reflectivity thresholds of B9SI are lowered, the CSI processes the radar base data and the output of B9SI to obtain the convection index of storm. Finally, the CSI is verified with the case of a supercell occurring in Guangzhou on 11 August 2004. The computational and analysis results show that the two rises of convection index matched well with a merging growth and strong convergent growth of the supercell, and the index was 0.744 when the supercell was the strongest, and then decreased. Correspondingly, the height of the maximum reflectivity, detected by the radar also reduced, and heavy rain also occurred in a large-scale area.

  14. Support Vector Machine Model for Automatic Detection and Classification of Seismic Events

    Science.gov (United States)

    Barros, Vesna; Barros, Lucas

    2016-04-01

    The automated processing of multiple seismic signals to detect, localize and classify seismic events is a central tool in both natural hazards monitoring and nuclear treaty verification. However, false detections and missed detections caused by station noise and incorrect classification of arrivals are still an issue and the events are often unclassified or poorly classified. Thus, machine learning techniques can be used in automatic processing for classifying the huge database of seismic recordings and provide more confidence in the final output. Applied in the context of the International Monitoring System (IMS) - a global sensor network developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) - we propose a fully automatic method for seismic event detection and classification based on a supervised pattern recognition technique called the Support Vector Machine (SVM). According to Kortström et al., 2015, the advantages of using SVM are handleability of large number of features and effectiveness in high dimensional spaces. Our objective is to detect seismic events from one IMS seismic station located in an area of high seismicity and mining activity and classify them as earthquakes or quarry blasts. It is expected to create a flexible and easily adjustable SVM method that can be applied in different regions and datasets. Taken a step further, accurate results for seismic stations could lead to a modification of the model and its parameters to make it applicable to other waveform technologies used to monitor nuclear explosions such as infrasound and hydroacoustic waveforms. As an authorized user, we have direct access to all IMS data and bulletins through a secure signatory account. A set of significant seismic waveforms containing different types of events (e.g. earthquake, quarry blasts) and noise is being analysed to train the model and learn the typical pattern of the signal from these events. Moreover, comparing the performance of the support

  15. 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.

  16. 交流接触器自动检测系统设计%Design of Automatic Detecting System of AC Contactor

    Institute of Scientific and Technical Information of China (English)

    李林; 强秀华; 邹斌

    2012-01-01

    针对交流接触器传统检测方法存在的缺点,设计了交流接触器自动检测系统.首先,对检测流程和设计要求做了说明;然后,给出了数据采集程序和PLC程序流程图.结果表明,该系统运行可靠,检测精度高,达到了规定的设计目标.%Focused on the defects of the traditional method of detecting for AC contactor, the paper designed the auto-matic detecting system of AC contactor. Firstly detecting process and design requirements were introduced, secondly the software flowchart of data acquisition program and PLC program were given. The results showed that this automatic detec-ting runs reliably and has high accuracy, it achieves the required goals and designed requirements.

  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. 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.

  19. Design and implementation of automatic color information collection system

    Science.gov (United States)

    Ci, Wenjie; Xie, Kai; Li, Tong

    2015-12-01

    In liquid crystal display (LCD) colorimetric characterization, it needs to convert RGB the device-dependent color space to CIEXYZ or CIELab the device-independent color space. Namely establishing the relationship between RGB and CIE using the data of device color and the corresponding data of CIE. Thus a color automatic message acquisition software is designed. We use openGL to fulfill the full screen display function, write c++ program and call the Eyeone equipment library functions to accomplish the equipment calibration, set the sample types, and realize functions such as sampling and preservation. The software can drive monitors or projectors display the set of sample colors automatically and collect the corresponding CIE values. The sample color of RGB values and the acquisition of CIE values can be stored in a text document, which is convenient for future extraction and analysis. Taking the cubic polynomial as an example, each channel is sampled of 17 sets using this system. And 100 sets of test data are also sampled. Using the least square method we can get the model. The average of color differences are around 2.4874, which is much lower than the CIE2000 commonly required level of 6.00.The successful implementation of the system saves the time of sample color data acquisition, and improves the efficiency of LCD colorimetric characterization.

  20. Control of AWD System for Vehicle Performance and Safety

    Directory of Open Access Journals (Sweden)

    Jung Hojin

    2016-01-01

    Full Text Available AWD (All-Wheel Drive system transfers drive force to all wheels so that it can help vehicle escape low mu surface or climb hill more conveniently. Recently, AWD system for on road vehicle has become popular to improve vehicle driving performance. However, there has not been enough research of applying AWD system for vehicle stability especially for lateral movement. Compared with ESC (Electronic Stability Control, AWD system does not cause any inconveniences to the driver because it controls vehicle only by distributing front and rear drive torque, without using brake. By allowing slipping/locking of wet clutch inside the transfer case, AWD system can distribute different amount of torque between front and rear axle. This paper introduces modelling of AWD system and suggests the control of AWD system based on peak slip ratio and slip angle at which tyre saturates. Carsim based vehicle simulation results of AWD controller is presented.

  1. Fusing moving average model and stationary wavelet decomposition for automatic incident detection: case study of Tokyo Expressway

    Directory of Open Access Journals (Sweden)

    Qinghua Liu

    2014-12-01

    Full Text Available Traffic congestion is a growing problem in urban areas all over the world. The transport sector has been in full swing event study on intelligent transportation system for automatic detection. The functionality of automatic incident detection on expressways is a primary objective of advanced traffic management system. In order to save lives and prevent secondary incidents, accurate and prompt incident detection is necessary. This paper presents a methodology that integrates moving average (MA model with stationary wavelet decomposition for automatic incident detection, in which parameters of layer coefficient are extracted from the difference between the upstream and downstream occupancy. Unlike other wavelet-based method presented before, firstly it smooths the raw data with MA model. Then it uses stationary wavelet to decompose, which can achieve accurate reconstruction of the signal, and does not shift the signal transfer coefficients. Thus, it can detect the incidents more accurately. The threshold to trigger incident alarm is also adjusted according to normal traffic condition with congestion. The methodology is validated with real data from Tokyo Expressway ultrasonic sensors. Experimental results show that it is accurate and effective, and that it can differentiate traffic accident from other condition such as recurring traffic congestion.

  2. 41 CFR 102-34.105 - Before we sell a motor vehicle, what motor vehicle identification must we remove?

    Science.gov (United States)

    2010-07-01

    ... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Before we sell a motor vehicle, what motor vehicle identification must we remove? 102-34.105 Section 102-34.105 Public Contracts... Vehicle Identification § 102-34.105 Before we sell a motor vehicle, what motor vehicle identification...

  3. 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.

  4. Systems identification - reprise and projections

    Science.gov (United States)

    Taylor, L. W., Jr.

    1974-01-01

    A state-of-the-arts review is given for the field of system identification. Progress in the field is traced from the early models of dynamic systems by Sir Isaac Newton up to the present day use of advanced techniques for numerous applications.

  5. 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.

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

    OpenAIRE

    Yassine Benabbas; Nacim Ihaddadene; Chaabane Djeraba

    2011-01-01

    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 ...

  7. 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, pa

  8. Automatic detection of sea-sky horizon line and small targets in maritime infrared imagery

    Science.gov (United States)

    Kong, Xiangyu; Liu, Lei; Qian, Yunsheng; Cui, Minjie

    2016-05-01

    It is usually difficult but important to extract distant targets from sea clutters and clouds since the targets are small compared to the pixel field of view. In this paper, an algorithm based on wavelet transformation is proposed for automatic detection of small targets under the maritime background. We recognize that the distant small targets generally appear near the sea-sky horizon line and noises lie along the direction of sea-sky horizon line. So the sea-sky horizon is located firstly by examining the approximate image of a Haar wavelet decomposition of the original image. And the equation of the sea-sky horizon is set up, no matter whether the sea-sky horizon is horizontal or not. Since the sea-sky horizon is located, not only the potential area but also the strip direction of noise is got. Then the modified mutual wavelet energy combination algorithm is applied to extract targets with targets being marked by red windows. Computer simulations are shown to validate the great adaptability of the sea-sky horizon line detection and the accuracy of the small targets detection. The algorithm should be useful to engineers and scientists to design precise guidance or maritime monitoring system.

  9. 30 CFR 75.1103-4 - Automatic fire sensor and warning device systems; installation; minimum requirements.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic fire sensor and warning device...-UNDERGROUND COAL MINES Fire Protection § 75.1103-4 Automatic fire sensor and warning device systems; installation; minimum requirements. (a) Effective December 31, 2009, automatic fire sensor and warning...

  10. 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.

  11. Tunable compression of template banks for fast gravitational wave detection and identification

    CERN Document Server

    Chua, Alvin J K

    2015-01-01

    One strategy for reducing the computational cost of matched-filter searches for gravitational wave sources is to introduce a compressed basis for the waveform template bank in a grid-based search. In this paper, we propose and investigate several tunable compression schemes that slide between maximal sensitivity and maximal compression; these might be useful for the fast detection and identification of sources with moderate to high signal-to-noise ratios. Lossless compression schemes offer automatic identification of the signal upon detection, but their accuracy is significantly reduced in the presence of noise. A lossy scheme that uses a straightforward partition of the template bank is found to yield better detection and identification performance at the same level of compression.

  12. 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.

  13. ANPS - AUTOMATIC NETWORK PROGRAMMING SYSTEM

    Science.gov (United States)

    Schroer, B. J.

    1994-01-01

    Development of some of the space program's large simulation projects -- like the project which involves simulating the countdown sequence prior to spacecraft liftoff -- requires the support of automated tools and techniques. The number of preconditions which must be met for a successful spacecraft launch and the complexity of their interrelationship account for the difficulty of creating an accurate model of the countdown sequence. Researchers developed ANPS for the Nasa Marshall Space Flight Center to assist programmers attempting to model the pre-launch countdown sequence. Incorporating the elements of automatic programming as its foundation, ANPS aids the user in defining the problem and then automatically writes the appropriate simulation program in GPSS/PC code. The program's interactive user dialogue interface creates an internal problem specification file from user responses which includes the time line for the countdown sequence, the attributes for the individual activities which are part of a launch, and the dependent relationships between the activities. The program's automatic simulation code generator receives the file as input and selects appropriate macros from the library of software modules to generate the simulation code in the target language GPSS/PC. The user can recall the problem specification file for modification to effect any desired changes in the source code. ANPS is designed to write simulations for problems concerning the pre-launch activities of space vehicles and the operation of ground support equipment and has potential for use in developing network reliability models for hardware systems and subsystems. ANPS was developed in 1988 for use on IBM PC or compatible machines. The program requires at least 640 KB memory and one 360 KB disk drive, PC DOS Version 2.0 or above, and GPSS/PC System Version 2.0 from Minuteman Software. The program is written in Turbo Prolog Version 2.0. GPSS/PC is a trademark of Minuteman Software. Turbo Prolog

  14. Automatic Person Identification in Camera Video by Motion Correlation

    Directory of Open Access Journals (Sweden)

    Dingbo Duan

    2014-01-01

    Full Text Available Person identification plays an important role in semantic analysis of video content. This paper presents a novel method to automatically label persons in video sequence captured from fixed camera. Instead of leveraging traditional face recognition approaches, we deal with the task of person identification by fusing information from motion sensor platforms, like smart phones, carried on human bodies and extracted from camera video. More specifically, a sequence of motion features extracted from camera video are compared with each of those collected from accelerometers of smart phones. When strong correlation is detected, identity information transmitted from the corresponding smart phone is used to identify the phone wearer. To test the feasibility and efficiency of the proposed method, extensive experiments are conducted which achieved impressive performance.

  15. Automatic convey or System with In–Process Sorting Mechanism using PLC and HMI System

    Directory of Open Access Journals (Sweden)

    Y V Aruna

    2015-11-01

    Full Text Available Programmable logic controllers are widely used in many manufacturing process like machinery packaging material handling automatic assembly. These are special type of microprocessor based controller used for any application that needs any kind of electrical controller including lighting controller and HVAC control system. Automatic conveyor system is a computerized control method of controlling and managing the sorting mechanism at the same time maintaining the efficiency of the industry & quality of the products.HMI for automatic conveyor system is considered the primary way of controlling each operation. Text displays are available as well as graphical touch screens. It is used in touch panels and local monitoring of machines. This paper deals with the efficient use of PLC in automatic conveyor system and also building the accuracy in it.

  16. Automatic Meter Reading and Theft Control System by Using GSM

    Directory of Open Access Journals (Sweden)

    P. Rakesh Malhotra

    2013-04-01

    Full Text Available This paper deals with automatic meter reading and theft control system in energy meter. Current transformer is used to measure the total power consumption for house or industrial purpose. This recorded reading is transmitted to the electricity board for every 60 days once. For transmitting the reading of energy meter GSM module is used. To avoid theft, infrared sensor is placed in the screw portion of energy meter seal. If the screw is removed from the meter a message is sent to the electricity board. The measuring of energy meter and monitoring of IR sensor is done with a PIC microcontroller.The informative system will be helpful for the electricity board to monitor the entire supply and the correct billing accordingly without any mishap. This model reduces the manual manipulation work andtheft control.

  17. 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

  18. Explosives Detection and Identification by PGNAA

    International Nuclear Information System (INIS)

    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

  19. A detection system for the identification of heavy residues

    International Nuclear Information System (INIS)

    A detection system for heavy residues at low energies consisting of a time-of-flight (TOF) system and a ΔE-Esub(R) telescope is described. The start signal of the TOF system is obtained from a microchannelplate detector of the mirror type. The ΔE-Esub(R) telescope consists of an ionization counter as transmission detector and array of silicon surface barrier detectors to stop the heavy ions. The two position coordinates of the trajectory of the heavy ions are both determined with the drift time method. The intrinsic time resolution of the TOF system, measured with 47 MeV 63Cu ions, is 175 ps. The energy resolution of the ΔE-Esub(R) telescope is 310 keV for 39 MeV 12C ions, which is mainly due to the spread in the energy loss in the entrance window of the ionization chamber. The energy-loss resolution is mainly determined by energy straggling in the gas. The largest contribution to the position resolution is caused by multiple scattering in the counter gas. (orig.)

  20. Evaluation of automatic building detection approaches combining high resolution images and LiDAR data

    OpenAIRE

    Javier Estornell; Recio, Jorge A.; Txomin Hermosilla; Ruiz, Luis A.

    2011-01-01

    In this paper, two main approaches for automatic building detection and localization using high spatial resolution imagery and LiDAR data are compared and evaluated: thresholding-based and object-based classification. The thresholding-based approach is founded on the establishment of two threshold values: one refers to the minimum height to be considered as building, defined using the LiDAR data, and the other refers to the presence of vegetation, which is defined according to the spectral re...

  1. 2D signature for detection and identification of drugs

    Science.gov (United States)

    Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Shen, Jingling; Zhang, Cunlin; Zhou, Qingli; Shi, Yulei

    2011-06-01

    The method of spectral dynamics analysis (SDA-method) is used for obtaining the2D THz signature of drugs. This signature is used for the detection and identification of drugs with similar Fourier spectra by transmitted THz signal. We discuss the efficiency of SDA method for the identification problem of pure methamphetamine (MA), methylenedioxyamphetamine (MDA), 3, 4-methylenedioxymethamphetamine (MDMA) and Ketamine.

  2. Modularity, adaptability and evolution in the AUTOPIA architecture for control of autonomous vehicles. Updating Mechatronics of Automatic Cars

    OpenAIRE

    Pérez Rastelli, Joshué; González, Carlos; Milanés, Vicente; Onieva, Enrique; Godoy, Jorge; Pedro, Teresa de

    2009-01-01

    International audience Computer systems to carry out control algorithms on autonomous vehicles have been developed in recent years. However, the advances in peripheral devices allow connecting the actuator controllers to the control system by means of standard communication links (USB, CAN, Ethernet ... ).The goal is to permit the use of standard computers. In this paper, we present the evolution of AUTOPIA architecture and its modularity and adaptability to move the old system based on IS...

  3. Need of a consistent and convenient nucleus identification in ENDF files for the automatic construction of the depletion chains

    Science.gov (United States)

    Mosca, Pietro; Mounier, Claude

    2016-03-01

    The automatic construction of evolution chains recently implemented in GALILEE system is based on the analysis of several ENDF files : the multigroup production cross sections present in the GENDF files processed by NJOY from the ENDF evaluation, the decay file and the fission product yields (FPY) file. In this context, this paper highlights the importance of the nucleus identification to properly interconnect the data mentioned above. The first part of the paper describes the present status of the nucleus identification among the several ENDF files focusing, in particular, on the use of the excited state number and of the isomeric state number. The second part reviews the problems encountered during the automatic construction of the depletion chains using recent ENDF data. The processing of the JEFF-3.1.1, ENDF/B-VII.0 (decay and FPY) and the JEFF-3.2 (production cross section) points out problems about the compliance or not of the nucleus identifiers with the ENDF-6 format and sometimes the inconsistencies among the various ENDF files. In addition, the analysis of EAF-2003 and EAF-2010 shows some incoherence between the ZA product identifier and the reaction identifier MT for the reactions (n, pα) and (n, 2np). As a main result of this work, our suggestion is to change the ENDF format using systematically the isomeric state number to identify the nuclei. This proposal is already compliant to a huge amount ENDF data that are not in agreement with the present ENDF format. This choice is the most convenient because, ultimately, it allows one to give human readable names to the nuclei of the depletion chains.

  4. Automatic Detection and Classi cation of Objects in Point Clouds using multi-stage Semantics

    OpenAIRE

    Truong, Hung; Hmida, Helmi Ben; Boochs, Frank; Habed, Adlane; Cruz, Christophe; Voisin, Yvon; Nicolle, Christophe

    2013-01-01

    International audience Due to the increasing availability of large unstructured point clouds from lasers scanning and photogrammetry, there is a growing demand for automatic evaluation methods. Given the complexity of the underlying problems, several new methods resort to using semantic knowledge in particular for object detection and classification support. In this paper, we present a novel approach, which makes use of advanced algorithms, and benefits from intelligent knowledge managemen...

  5. Automatic detection and elimination of periodic pulse shaped interferences in partial discharge measurements

    OpenAIRE

    Nagesh, V.; Gururaj, BI

    1994-01-01

    The interferences present in partial discharge (PD) measurement can be classified as narrow-band and broad-band, the latter being pulsed shaped. The pulse shaped interferences can be periodic or random with respect to power frequency, the former being very common and strong. The paper describes an algorithm for automatic detection and elimination of periodic pulse shaped interferences in PD measurements. The algorithm is developed on lines similar to that used in decomposing an electromyogram...

  6. 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.

  7. 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

    2016-01-01

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

  8. Automatic Personal Identification Using Feature Similarity Index Matching

    Directory of Open Access Journals (Sweden)

    R. Gayathri

    2012-01-01

    Full Text Available Problem statement: Biometrics based personal identification is as an effective method for automatically recognizing, a persons identity with high confidence. Palmprint is an essential biometric feature for use in access control and forensic applications. In this study, we present a multi feature extraction, based on edge detection scheme, applying Log Gabor filter to enhance image structures and suppress noise. Approach: A novel Feature-Similarity Indexing (FSIM of image algorithm is used to generate the matching score between the original image in database and the input test image. Feature Similarity (FSIM index for full reference (image quality assurance IQA is proposed based on the fact that Human Visual System (HVS understands an image mainly according to its low-level features. Results and Conclusion: The experimental results achieve recognition accuracy using canny and perwitt FSIM of 97.3227 and 94.718%, respectively, on the publicly available database of Hong Kong Polytechnic University. Totally 500 images of 100 individuals, 4 samples for each palm are randomly selected to train in this research. Then we get every person each palm image as a template (total 100. Experimental evaluation using palmprint image databases clearly demonstrates the efficient recognition performance of the proposed algorithm compared with the conventional palmprint recognition algorithms.

  9. Automatic dental arch detection and panoramic image synthesis from CT images.

    Science.gov (United States)

    Sa-Ing, Vera; Wangkaoom, Kongyot; Thongvigitmanee, Saowapak S

    2013-01-01

    Due to accurate 3D information, computed tomography (CT), especially cone-beam CT or dental CT, has been widely used for diagnosis and treatment planning in dentistry. Axial images acquired from both medical and dental CT scanners can generate synthetic panoramic images similar to typical 2D panoramic radiographs. However, the conventional way to reconstruct the simulated panoramic images is to manually draw the dental arch on axial images. In this paper, we propose a new fast algorithm for automatic detection of the dental arch. Once the dental arch is computed, a series of synthetic panoramic images as well as a ray-sum panoramic image can be automatically generated. We have tested the proposed algorithm on 120 CT axial images and all of them can provide the decent estimate of the dental arch. The results show that our proposed algorithm can mostly detect the correct dental arch.

  10. PLC Based Automatic Multistoried Car Parking System

    Directory of Open Access Journals (Sweden)

    Swanand S .Vaze

    2014-12-01

    Full Text Available This project work presents the study and design of PLC based Automatic Multistoried Car Parking System. Multistoried car parking is an arrangement which is used to park a large number of vehicles in least possible place. For making this arrangement in a real plan very high technological instruments are required. In this project a prototype of such a model is made. This prototype model is made for accommodating twelve cars at a time. Availability of the space for parking is detected by optical proximity sensor which is placed on the pallet. A motor controlled elevator is used to lift the cars. Elevator status is indicated by LED which is placed on ground floor. Controlling of the platforms and checking the vacancies is done by PLC. For unparking of car, keyboard is interfaced with the model for selection of required platform. Automation is done to reduce requirement of space and also to reduce human errors, which in-turn results in highest security and greatest flexibility. Due to these advantages, this system can be used in hotels, railway stations, airports where crowding of car is more.

  11. A Stochastic Approach for Automatic and Dynamic Modeling of Students' Learning Styles in Adaptive Educational Systems

    OpenAIRE

    Fabiano Azevedo DORÇA; Luciano Vieira LIMA; Márcia Aparecida FERNANDES; Carlos Roberto LOPES

    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 precisely adjust students' learning styles, based on the non-deterministic and non-stationary aspects of learning styles. Because of the probabilistic an...

  12. Building Point Detection from Vehicle-Borne LiDAR Data Based on Voxel Group and Horizontal Hollow Analysis

    OpenAIRE

    Yu Wang; Liang Cheng; Yanming Chen; Yang Wu; Manchun Li

    2016-01-01

    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) cat...

  13. Automatic Earthquake Detection and Location by Waveform coherency in Alentejo (South Portugal) Using CatchPy

    Science.gov (United States)

    Custodio, S.; Matos, C.; Grigoli, F.; Cesca, S.; Heimann, S.; Rio, I.

    2015-12-01

    Seismic data processing is currently undergoing a step change, benefitting from high-volume datasets and advanced computer power. In the last decade, a permanent seismic network of 30 broadband stations, complemented by dense temporary deployments, covered mainland Portugal. This outstanding regional coverage currently enables the computation of a high-resolution image of the seismicity of Portugal, which contributes to fitting together the pieces of the regional seismo-tectonic puzzle. Although traditional manual inspections are valuable to refine automatic results they are impracticable with the big data volumes now available. When conducted alone they are also less objective since the criteria is defined by the analyst. In this work we present CatchPy, a scanning algorithm to detect earthquakes in continuous datasets. Our main goal is to implement an automatic earthquake detection and location routine in order to have a tool to quickly process large data sets, while at the same time detecting low magnitude earthquakes (i.e. lowering the detection threshold). CatchPY is designed to produce an event database that could be easily located using existing location codes (e.g.: Grigoli et al. 2013, 2014). We use CatchPy to perform automatic detection and location of earthquakes that occurred in Alentejo region (South Portugal), taking advantage of a dense seismic network deployed in the region for two years during the DOCTAR experiment. Results show that our automatic procedure is particularly suitable for small aperture networks. The event detection is performed by continuously computing the short-term-average/long-term-average of two different characteristic functions (CFs). For the P phases we used a CF based on the vertical energy trace while for S phases we used a CF based on the maximum eigenvalue of the instantaneous covariance matrix (Vidale 1991). Seismic event location is performed by waveform coherence analysis, scanning different hypocentral coordinates

  14. 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.

  15. Semi-Automatic Detection of Swimming Pools from Aerial High-Resolution Images and LIDAR Data

    OpenAIRE

    Borja Rodríguez-Cuenca; Maria C. Alonso

    2014-01-01

    Bodies of water, particularly swimming pools, are land covers of high interest. Their maintenance involves energy costs that authorities must take into consideration. In addition, swimming pools are important water sources for firefighting. However, they also provide a habitat for mosquitoes to breed, potentially posing a serious health threat of mosquito-borne disease. This paper presents a novel semi-automatic method of detecting swimming pools in urban environments from aerial images and L...

  16. Sensor Fault Detection and Diagnosis for autonomous vehicles

    OpenAIRE

    Realpe Miguel; Vintimilla Boris; Vlacic Ljubo

    2015-01-01

    In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed ar...

  17. 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.

  18. Autonomous detection and anticipation of jam fronts from messages propagated by inter-vehicle communication

    CERN Document Server

    Sch"onhof, M; Kesting, A; Helbing, D; Sch\\"onhof, Martin; Treiber, Martin; Kesting, Arne; Helbing, Dirk

    2006-01-01

    In this paper, a minimalist, completely distributed freeway traffic information system is introduced. It involves an autonomous, vehicle-based jam front detection, the information transmission via inter-vehicle communication, and the forecast of the spatial position of jam fronts by reconstructing the spatiotemporal traffic situation based on the transmitted information. The whole system is simulated with an integrated traffic simulator, that is based on a realistic microscopic traffic model for longitudinal movements and lane changes. The function of its communication module has been explicitly validated by comparing the simulation results with analytical calculations. By means of simulations, we show that the algorithms for a congestion-front recognition, message transmission, and processing predict reliably the existence and position of jam fronts for vehicle equipment rates as low as 3%. A reliable mode of operation already for small market penetrations is crucial for the successful introduction of inter-...

  19. 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.

  20. 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.

  1. Automatic detection and tracking of filaments for a solar feature database

    Directory of Open Access Journals (Sweden)

    J. Aboudarham

    2008-02-01

    Full Text Available A new method for the automatic detection and tracking of solar filaments is presented. The method addresses the problems facing existing catalogs, such as the one developed recently in the frame of the European Grid of Solar Observations (EGSO project. In particular, it takes into account the structural and temporal evolution of filaments, differences in intensity as seen from one observation to the next, and the possibility of sudden disappearance followed by reappearance. In this study, the problem of tracking is solved by plotting all detected filaments during each solar rotation on a Carrington map and then by applying region growing techniques on those plots. Using this approach, the "fixed" positions of the envelopes in the Carrington system can be deduced. This is followed by a backward tracking of each filament by considering one full solar rotation. The resulting shifted Carrington map then enables one to follow any filament from one rotation to the next. Such maps should prove valuable for studies of the role of filaments in solar activity, notably coronal mass ejections (CMEs.

  2. Trends and progress in system identification

    CERN Document Server

    Eykhoff, Pieter

    1981-01-01

    Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the """"classical"""" methods and time series estimation; application of least squares and related techniques for the e

  3. Automatic Hazard Detection for Landers

    Science.gov (United States)

    Huertas, Andres; Cheng, Yang; Matthies, Larry H.

    2008-01-01

    Unmanned planetary landers to date have landed 'blind'; that is, without the benefit of onboard landing hazard detection and avoidance systems. This constrains landing site selection to very benign terrain,which in turn constrains the scientific agenda of missions. The state of the art Entry, Descent, and Landing (EDL) technology can land a spacecraft on Mars somewhere within a 20-100km landing ellipse.Landing ellipses are very likely to contain hazards such as craters, discontinuities, steep slopes, and large rocks, than can cause mission-fatal damage. We briefly review sensor options for landing hazard detection and identify a perception approach based on stereo vision and shadow analysis that addresses the broadest set of missions. Our approach fuses stereo vision and monocular shadow-based rock detection to maximize spacecraft safety. We summarize performance models for slope estimation and rock detection within this approach and validate those models experimentally. Instantiating our model of rock detection reliability for Mars predicts that this approach can reduce the probability of failed landing by at least a factor of 4 in any given terrain. We also describe a rock detector/mapper applied to large-high-resolution images from the Mars Reconnaissance Orbiter (MRO) for landing site characterization and selection for Mars missions.

  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 (<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.

  5. Automatic detection and quantification of the Agatston coronary artery calcium score on contrast computed tomography angiography.

    Science.gov (United States)

    Ahmed, Wehab; de Graaf, Michiel A; Broersen, Alexander; Kitslaar, Pieter H; Oost, Elco; Dijkstra, Jouke; Bax, Jeroen J; Reiber, Johan H C; Scholte, Arthur J

    2015-01-01

    Potentially, Agatston coronary artery calcium (CAC) score could be calculated on contrast computed tomography coronary angiography (CTA). This will make a separate non-contrast CT scan superfluous. This study aims to assess the performance of a novel fully automatic algorithm to detect and quantify the Agatston CAC score in contrast CTA images. From a clinical registry, 20 patients were randomly selected for each CAC category (i.e. 0, 1-99, 100-399, 400-999, ≥1,000). The Agatston CAC score on non-contrast CT was calculated manually, while the novel algorithm was used to automatically detect and quantify Agatston CAC score in contrast CTA images. The resulting Agatston CAC scores were validated against the non-contrast images. A total of 100 patients (60 ± 11 years, 63 men) were included. The median CAC score on non-contrast CT was 145 (IQR 5-760), whereas the contrast CTA CAC score was 170 (IQR 23-594) (P = 0.004). The automatically computed CAC score showed a high correlation (R = 0.949; P < 0.001) and intra-class correlation (R = 0.863; P < 0.001) with non-contrast CT CAC score. Moreover, agreement within CAC categories was good (κ 0.588). Fully automatic detection of Agatston CAC score on contrast CTA is feasible and showed high correlation with non-contrast CT CAC score. This could imply a radiation dose reduction and time saving by omitting the non-contrast scan. PMID:25159031

  6. 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.

  7. 33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

    Science.gov (United States)

    2010-07-01

    ... correction messages; (3) VHF—FM transceiver capable of Digital Selective Calling (DSC) on the designated DSC... a VTS as DSC messages on the designated DSC frequency; (7) Receive and comply with RTCM messages... messages occurs; (10) Display a separate visual alarm which is triggered by a VTS utilizing a DSC...

  8. 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.)

  9. PARAMETRIC IDENTIFICATION AND SENSITIVITY ANALYSIS FOR AUTONOMOUS UNDERWATER VEHICLES IN DIVING PLANE

    Institute of Scientific and Technical Information of China (English)

    XU Feng; ZOU Zao-jian; YIN Jian-chuan; CAO Jian

    2012-01-01

    The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles (AUV),maneuvering motion in the diving plane determines its difficulty in parametric identification.The motion parameters in diving plane are obtained by executing the Zigzag-like motion based on a mathematical model of maneuvering motion.A separate identification method is put forward for parametric identification by investigating the motion equations.Support vector machine is proposed to estimate the hydrodynamic derivatives by analyzing the data of surge,heave and pitch motions.Compared with the standard coefficients,the identified parameters show the validation of the proposed identification method.Sensitivity analysis based on numerical simulation demonstrates that poor sensitive derivative gives bad estimation results.Finally the motion simulation is implemented based on the dominant sensitive derivatives to verify the reconstructed model.

  10. Automatic Epileptic Seizure Onset Detection Using Matching Pursuit

    DEFF Research Database (Denmark)

    Sorensen, Thomas Lynggaard; Olsen, Ulrich L.; Conradsen, Isa;

    2010-01-01

    An automatic alarm system for detecting epileptic seizure onsets could be of great assistance to patients and medical staff. A novel approach is proposed using the Matching Pursuit algorithm as a feature extractor combined with the Support Vector Machine (SVM) as a classifier for this purpose. The...... combination of Matching Pursuit and SVM for automatic seizure detection has never been tested before, making this a pilot study. Data from red different patients with 6 to 49 seizures are used to test our model. Three patients are recorded with scalp electroencephalography (sEEG) and three with intracranial...

  11. 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

  12. 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.

  13. Automatic face detection and tracking based on Adaboost with camshift algorithm

    Science.gov (United States)

    Lin, Hui; Long, JianFeng

    2011-10-01

    With the development of information technology, video surveillance is widely used in security monitoring and identity recognition. For most of pure face tracking algorithms are hard to specify the initial location and scale of face automatically, this paper proposes a fast and robust method to detect and track face by combining adaboost with camshift algorithm. At first, the location and scale of face is specified by adaboost algorithm based on Haar-like features and it will be conveyed to the initial search window automatically. Then, we apply camshift algorithm to track face. The experimental results based on OpenCV software yield good results, even in some special circumstances, such as light changing and face rapid movement. Besides, by drawing out the tracking trajectory of face movement, some abnormal behavior events can be analyzed.

  14. 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 related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

  15. Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.

    Science.gov (United States)

    Mannan, Malik M Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M Ahmad

    2016-01-01

    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 related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data. PMID:26907276

  16. Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

    Science.gov (United States)

    Mannan, Malik M. Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M. Ahmad

    2016-01-01

    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 related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data. PMID:26907276

  17. Flaw Determination and Evaluation of Ultrasonic Automatic Flaw Detection System for Welded Steel Pipes%焊接钢管超声波自动探伤中的缺陷相关评判方法

    Institute of Scientific and Technical Information of China (English)

    常少文; 吕育栋; 曹华勇; 田岩平; 刘常庆; 韩玉朝; 孙志敏

    2012-01-01

    分析了焊接钢管超声波自动探伤检测中的缺陷相关评判方法,配合编制的时间相关、位置相关、行为相关、特征相关、性质相关的5种相关法判伤软件程序,使自动化探伤系统具有了智能评判功能,可做到对复杂缺陷回波的准确评价和严格筛选,有效地避免了系统的误报警,可满足连续自动化探伤要求,并做到误报率〈2%,漏报率为0。%The flaw determination and evalution methods of ultrasonic automatic flaw detection examining on welded steel pipes are introduced. With the careful programming of time correlation, location correlation, behavior correlation, features correlation, and nature correlation together with related software program, the testing system thus has a smart judgment function to evaluate correctly and select strictly for complex flaw echo, and its error in alarm can be effectively avoided. So designed system was able to meet the continuous automation testing requirements and achieve misinformation rate smaller 2% and fail to report rate to 0.

  18. 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.

  19. Automatic detection and segmentation of stems of potted tomato plant using Kinect

    Science.gov (United States)

    Fu, Daichang; Xu, Lihong; Li, Dawei; Xin, Longjiao

    2014-04-01

    The automatic segmentation and recognition of greenhouse crop is an important aspect in digitized facility agriculture. Crop stems are closely related with the growth of the crop. Meanwhile, they are also an important physiological trait to identify the species of plants. For these reasons, this paper focuses on the digitization process to collect and analysis stems of greenhouse plants (tomatoes). An algorithm for automatic stem detection and extraction is proposed, based on a cheap and effective stereo vision system—Kinect. In order to demonstrate the usefulness and the potential applicability of our algorithm, a virtual tomato plant, whose stems are rendered by segmented stem texture samples, is reconstructed on OpenGL graphic platform.

  20. Vehicle detection in WorldView-2 satellite imagery based on Gaussian modeling and contextual learning

    Science.gov (United States)

    Shen, Bichuan; Chen, Chi-Hau; Marchisio, Giovanni B.

    2012-06-01

    In this paper, we aim to study the detection of vehicles from WorldView-2 satellite imagery. For this purpose, accurate modeling of vehicle features and signatures and efficient learning of vehicle hypotheses are critical. We present a joint Gaussian and maximum likelihood based modeling and machine learning approach using SVM and neural network algorithms to describe the local appearance densities and classify vehicles from non-vehicle buildings, objects, and backgrounds. Vehicle hypotheses are fitted by elliptical Gaussians and the bottom-up features are grouped by Gabor orientation filtering based on multi-scale analysis and distance transform. Global contextual information such as road networks and vehicle distributions can be used to enhance the recognition. In consideration of the problem complexity the practical vehicle detection task faces due to dense and overlapping vehicle distributions, partial occlusion and clutters by building, shadows, and trees, we employ a spectral clustering strategy jointly combined with bootstrapped learning to estimate the parameters of centroid, orientation, and extents for local densities. We demonstrate a high detection rate 94.8%,with a missing rate 5.2% and a false alarm rate 5.3% on the WorldView-2 satellite imagery. Experimental results show that our method is quite effective to model and detect vehicles.

  1. 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.

  2. Automatic Identification of Critical Data Items in a Database to Mitigate the Effects of Malicious Insiders

    Science.gov (United States)

    White, Jonathan; Panda, Brajendra

    A major concern for computer system security is the threat from malicious insiders who target and abuse critical data items in the system. In this paper, we propose a solution to enable automatic identification of critical data items in a database by way of data dependency relationships. This identification of critical data items is necessary because insider threats often target mission critical data in order to accomplish malicious tasks. Unfortunately, currently available systems fail to address this problem in a comprehensive manner. It is more difficult for non-experts to identify these critical data items because of their lack of familiarity and due to the fact that data systems are constantly changing. By identifying the critical data items automatically, security engineers will be better prepared to protect what is critical to the mission of the organization and also have the ability to focus their security efforts on these critical data items. We have developed an algorithm that scans the database logs and forms a directed graph showing which items influence a large number of other items and at what frequency this influence occurs. This graph is traversed to reveal the data items which have a large influence throughout the database system by using a novel metric based formula. These items are critical to the system because if they are maliciously altered or stolen, the malicious alterations will spread throughout the system, delaying recovery and causing a much more malignant effect. As these items have significant influence, they are deemed to be critical and worthy of extra security measures. Our proposal is not intended to replace existing intrusion detection systems, but rather is intended to complement current and future technologies. Our proposal has never been performed before, and our experimental results have shown that it is very effective in revealing critical data items automatically.

  3. An Automatic Number Plate Recognition System under Image Processing

    Directory of Open Access Journals (Sweden)

    Sarbjit Kaur

    2016-03-01

    Full Text Available Automatic Number Plate Recognition system is an application of computer vision and image processing technology that takes photograph of vehicles as input image and by extracting their number plate from whole vehicle image , it display the number plate information into text. Mainly the ANPR system consists of 4 phases: - Acquisition of Vehicle Image and Pre-Processing, Extraction of Number Plate Area, Character Segmentation and Character Recognition. The overall accuracy and efficiency of whole ANPR system depends on number plate extraction phase as character segmentation and character recognition phases are also depend on the output of this phase. Further the accuracy of Number Plate Extraction phase depends on the quality of captured vehicle image. Higher be the quality of captured input vehicle image more will be the chances of proper extraction of vehicle number plate area. The existing methods of ANPR works well for dark and bright/light categories image but it does not work well for Low Contrast, Blurred and Noisy images and the detection of exact number plate area by using the existing ANPR approach is not successful even after applying existing filtering and enhancement technique for these types of images. Due to wrong extraction of number plate area, the character segmentation and character recognition are also not successful in this case by using the existing method. To overcome these drawbacks I proposed an efficient approach for ANPR in which the input vehicle image is pre-processed firstly by iterative bilateral filtering , adaptive histogram equalization and number plate is extracted from pre-processed vehicle image using morphological operations, image subtraction, image binarization/thresholding, sobel vertical edge detection and by boundary box analysis. Sometimes the extracted plate area also contains noise, bolts, frames etc. So the extracted plate area is enhanced by using morphological operations to improve the quality of

  4. 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.

  5. 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...

  6. Development and Testing of an Automatic Transmission Shift Schedule Algorithm for Vehicle Simulation (SAE Paper 2015-01-1142)

    Science.gov (United States)

    The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) modeling tool was created by EPA to estimate greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle type...

  7. Automatic UltraWideband Radar System for Life Detection of Hidden Humans

    OpenAIRE

    Chao, Chengchung

    2012-01-01

    The ultra-wideband (UWB) is a radio technology which can be used at very low energy levels for short-range high-bandwidth communications by using a large portion of the radio spectrum. In February 2002, the Federal Communications Commission (FCC) gave the permission for UWB to be used for imaging and radar production. The corresponding technology is continuing to be developed furthermore, especially the radar applications of life detection. In various situations, the life-detection sy...

  8. Automatic detection and agronomic characterization of olive groves using high-resolution imagery and LIDAR data

    Science.gov (United States)

    Caruso, T.; Rühl, J.; Sciortino, R.; Marra, F. P.; La Scalia, G.

    2014-10-01

    The Common Agricultural Policy of the European Union grants subsidies for olive production. Areas of intensified olive farming will be of major importance for the increasing demand for oil production of the next decades, and countries with a high ratio of intensively and super-intensively managed olive groves will be more competitive than others, since they are able to reduce production costs. It can be estimated that about 25-40% of the Sicilian oliviculture must be defined as "marginal". Modern olive cultivation systems, which permit the mechanization of pruning and harvest operations, are limited. Agronomists, landscape planners, policy decision-makers and other professionals have a growing need for accurate and cost-effective information on land use in general and agronomic parameters in the particular. The availability of high spatial resolution imagery has enabled researchers to propose analysis tools on agricultural parcel and tree level. In our study, we test the performance of WorldView-2 imagery relative to the detection of olive groves and the delineation of olive tree crowns, using an object-oriented approach of image classification in combined use with LIDAR data. We selected two sites, which differ in their environmental conditions and in their agronomic parameters of olive grove cultivation. The main advantage of the proposed methodology is the low necessary quantity of data input and its automatibility. However, it should be applied in other study areas to test if the good results of accuracy assessment can be confirmed. Data extracted by the proposed methodology can be used as input data for decision-making support systems for olive grove management.

  9. Measuring Service Reliability Using Automatic Vehicle Location Data

    Directory of Open Access Journals (Sweden)

    Zhenliang Ma

    2014-01-01

    Full Text Available Bus service reliability has become a major concern for both operators and passengers. Buffer time measures are believed to be appropriate to approximate passengers' experienced reliability in the context of departure planning. Two issues with regard to buffer time estimation are addressed, namely, performance disaggregation and capturing passengers’ perspectives on reliability. A Gaussian mixture models based method is applied to disaggregate the performance data. Based on the mixture models distribution, a reliability buffer time (RBT measure is proposed from passengers’ perspective. A set of expected reliability buffer time measures is developed for operators by using different spatial-temporal levels combinations of RBTs. The average and the latest trip duration measures are proposed for passengers that can be used to choose a service mode and determine the departure time. Using empirical data from the automatic vehicle location system in Brisbane, Australia, the existence of mixture service states is verified and the advantage of mixture distribution model in fitting travel time profile is demonstrated. Numerical experiments validate that the proposed reliability measure is capable of quantifying service reliability consistently, while the conventional ones may provide inconsistent results. Potential applications for operators and passengers are also illustrated, including reliability improvement and trip planning.

  10. Automatic milking systems, farm size, and milk production.

    Science.gov (United States)

    Rotz, C A; Coiner, C U; Soder, K J

    2003-12-01

    Automatic milking systems (AMS) offer relief from the demanding routine of milking. Although many AMS are in use in Europe and a few are used in the United States, the potential benefit for American farms is uncertain. A farm-simulation model was used to determine the long-term, whole-farm effect of implementing AMS on farm sizes of 30 to 270 cows. Highest farm net return to management and unpaid factors was when AMS were used at maximal milking capacity. Adding stalls to increase milking frequency and possibly increase production generally did not improve net return. Compared with new traditional milking systems, the greatest potential economic benefit was a single-stall AMS on a farm size of 60 cows at a moderate milk production level (8600 kg/cow). On other farm sizes using single-stall type robotic units, losses in annual net return of 0 dollars to 300 dollars/cow were projected, with the greatest losses on larger farms and at high milk production (10,900 kg/cow). Systems with one robot serving multiple stalls provided a greater net return than single-stall systems, and this net return was competitive with traditional parlors for 50- to 130-cow farm sizes. The potential benefit of AMS was improved by 100 dollars/cow per year if the AMS increased production an additional 5%. A 20% reduction in initial equipment cost or doubling milking labor cost also improved annual net return of an AMS by up to 100 dollars/cow. Annual net return was reduced by 110 dollars/cow, though, if the economic life of the AMS was reduced by 3 yr for a more rapid depreciation than that normally used with traditional milking systems. Thus, under current assumptions, the economic return for an AMS was similar to that of new parlor systems on smaller farms when the milking capacity of the AMS was well matched to herd size and milk production level.

  11. 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.

  12. 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. PMID:25276855

  13. 智能建筑区门禁系统自动化识别技术分析%Analysis on Automatic Identification Technology of Intelligent Building Access Control System

    Institute of Scientific and Technical Information of China (English)

    张卉

    2015-01-01

    门禁系统是智能建筑区必备设施,可对建筑区提供安全防护、自动调控等多方面功能.指纹识别系统是人工智能改造的新系统,为门禁系统自动识别提供了科技化措施.本文分析了智能建筑发展趋势及指纹识别系统的基本构成,介绍了智能建筑门禁系统自动化识别技术的应用方法.%The access control system of intelligent building is a necessary facility, which provides security protection, automatic control and so on. Fingerprint identification system is a new artificial intelligence system, providing technological measures for the automatic identification of access control system. This paper analyzes the development trend of intelligent building and the basic structure of fingerprint identification system, introduces the application of automatic recognition technology in intelligent building access control system.

  14. A system for automatic on-line time detection and classification of neural spikes based on a digital signal processor and a FPGA controller

    OpenAIRE

    Biffi, Emilia; Ghezzi, Diego; Esposti, Federico; Menegon, Andrea; Signorini, Maria Gabriella; Valtorta, Flavia; Ferrigno, Giancarlo

    2007-01-01

    Definition of single spikes from multiunit spike trains plays a critical role in neurophysiology and in neuroengineering as it does the question of how much information is encoded by single neurons in a neuronal network. Moreover, the possibility to develop a bidirectional communication between electronic devices and neuronal networks provides great perspectives in neuroengineering. Traditionally, the functional properties of neurons and neuronal networks have been investigated using conventi...

  15. Making sense of sensor data : detecting clinical mastitis in automatic milking systems

    NARCIS (Netherlands)

    Kamphuis, C.

    2010-01-01

    Farmers milking dairy cows are obliged to exclude milk with abnormal homogeneity or color for human consumption (e.g., Regulation (EC) No 853/2004), where most abnormal milk is caused by clinical mastitis (CM). With automatic milking (AM), farmers are no longer physically present during the milking

  16. Digital Receiver-based Electronic Intelligence System Configuration for the Detection and Identification of Intrapulse Modulated Radar Signals

    Directory of Open Access Journals (Sweden)

    A. K. Singh

    2014-03-01

    Full Text Available 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 measurement with sector selection based on amplitude direction finding technique. Advanced signal processing algorithms with time frequency analysis are implemented in real time in field programmable gate array to extract all the basic as well as advanced parameters of frequency and phase modulations such as chirp, barker, and poly-phase (Frank, P1-P4 codes in addition to the pulse and continuous wave signals. The intercepted intrapulse modulated signal parameters have been extracted with very high accuracy and sensitivity.Defence Science Journal, 2014, 64(2, pp. 152-158. DOI: http://dx.doi.org/10.14429/dsj.64.5091

  17. Robust parameter design for automatically controlled systems and nanostructure synthesis

    Science.gov (United States)

    Dasgupta, Tirthankar

    2007-12-01

    This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor

  18. Automatic identification of corrosion damage using image processing techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bento, Mariana P.; Ramalho, Geraldo L.B.; Medeiros, Fatima N.S. de; Ribeiro, Elvis S. [Universidade Federal do Ceara (UFC), Fortaleza, CE (Brazil); Medeiros, Luiz C.L. [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

    2009-07-01

    This paper proposes a Nondestructive Evaluation (NDE) method for atmospheric corrosion detection on metallic surfaces using digital images. In this study, the uniform corrosion is characterized by texture attributes extracted from co-occurrence matrix and the Self Organizing Mapping (SOM) clustering algorithm. We present a technique for automatic inspection of oil and gas storage tanks and pipelines of petrochemical industries without disturbing their properties and performance. Experimental results are promising and encourage the possibility of using this methodology in designing trustful and robust early failure detection systems. (author)

  19. Fully automatic lung segmentation and rib suppression methods to improve nodule detection in chest radiographs.

    Science.gov (United States)

    Soleymanpour, Elaheh; Pourreza, Hamid Reza; Ansaripour, Emad; Yazdi, Mehri Sadooghi

    2011-07-01

    Computer-aided Diagnosis (CAD) systems can assist radiologists in several diagnostic tasks. Lung segmentation is one of the mandatory steps for initial detection of lung cancer in Posterior-Anterior chest radiographs. On the other hand, many CAD schemes in projection chest radiography may benefit from the suppression of the bony structures that overlay the lung fields, e.g. ribs. The original images are enhanced by an adaptive contrast equalization and non-linear filtering. Then an initial estimation of lung area is obtained based on morphological operations and then it is improved by growing this region to find the accurate final contour, then for rib suppression, we use oriented spatial Gabor filter. The proposed method was tested on a publicly available database of 247 chest radiographs. Results show that this method outperformed greatly with accuracy of 96.25% for lung segmentation, also we will show improving the conspicuity of lung nodules by rib suppression with local nodule contrast measures. Because there is no additional radiation exposure or specialized equipment required, it could also be applied to bedside portable chest x-rays. In addition to simplicity of these fully automatic methods, lung segmentation and rib suppression algorithms are performed accurately with low computation time and robustness to noise because of the suitable enhancement procedure.

  20. Network of wireless gamma ray sensors for radiological detection and identification

    Science.gov (United States)

    Barzilov, A.; Womble, P.; Novikov, I.; Paschal, J.; Board, J.; Moss, K.

    2007-04-01

    The paper describes the design and development of a network of wireless gamma-ray sensors based on cell phone or WiFi technology. The system is intended for gamma-ray detection and automatic identification of radioactive isotopes and nuclear materials. The sensor is a gamma-ray spectrometer that uses wireless technology to distribute the results. A small-size sensor module contains a scintillation detector along with a small size data acquisition system, PDA, battery, and WiFi radio or a cell phone modem. The PDA with data acquisition and analysis software analyzes the accumulated spectrum on real-time basis and returns results to the screen reporting the isotopic composition and intensity of detected radiation source. The system has been programmed to mitigate false alarms from medical isotopes and naturally occurring radioactive materials. The decision-making software can be "trained" to indicate specific signatures of radiation sources like special nuclear materials. The sensor is supplied with GPS tracker coupling radiological information with geographical coordinates. The sensor is designed for easy use and rapid deployment in common wireless networks.

  1. Automatic Identification of Interictal Epileptiform Discharges in Secondary Generalized Epilepsy

    Science.gov (United States)

    Chang, Won-Du; Cha, Ho-Seung; Lee, Chany; Kang, Hoon-Chul; Im, Chang-Hwan

    2016-01-01

    Ictal epileptiform discharges (EDs) are characteristic signal patterns of scalp electroencephalogram (EEG) or intracranial EEG (iEEG) recorded from patients with epilepsy, which assist with the diagnosis and characterization of various types of epilepsy. The EEG signal, however, is often recorded from patients with epilepsy for a long period of time, and thus detection and identification of EDs have been a burden on medical doctors. This paper proposes a new method for automatic identification of two types of EDs, repeated sharp-waves (sharps), and runs of sharp-and-slow-waves (SSWs), which helps to pinpoint epileptogenic foci in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). In the experiments with iEEG data acquired from a patient with LGS, our proposed method detected EDs with an accuracy of 93.76% and classified three different signal patterns with a mean classification accuracy of 87.69%, which was significantly higher than that of a conventional wavelet-based method. Our study shows that it is possible to successfully detect and discriminate sharps and SSWs from background EEG activity using our proposed method. PMID:27379172

  2. Automatic Identification of Interictal Epileptiform Discharges in Secondary Generalized Epilepsy

    Directory of Open Access Journals (Sweden)

    Won-Du Chang

    2016-01-01

    Full Text Available Ictal epileptiform discharges (EDs are characteristic signal patterns of scalp electroencephalogram (EEG or intracranial EEG (iEEG recorded from patients with epilepsy, which assist with the diagnosis and characterization of various types of epilepsy. The EEG signal, however, is often recorded from patients with epilepsy for a long period of time, and thus detection and identification of EDs have been a burden on medical doctors. This paper proposes a new method for automatic identification of two types of EDs, repeated sharp-waves (sharps, and runs of sharp-and-slow-waves (SSWs, which helps to pinpoint epileptogenic foci in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS. In the experiments with iEEG data acquired from a patient with LGS, our proposed method detected EDs with an accuracy of 93.76% and classified three different signal patterns with a mean classification accuracy of 87.69%, which was significantly higher than that of a conventional wavelet-based method. Our study shows that it is possible to successfully detect and discriminate sharps and SSWs from background EEG activity using our proposed method.

  3. Automatic License Plate Recoganization System Based on Image Processing Using LabVIEW

    Directory of Open Access Journals (Sweden)

    Rachana Chahar

    2014-05-01

    Full Text Available Automatic License plate recognition (ALPR system is one kind of an intelligent transport system and is of considerable interest because of its potential applications in highway electronic toll collection and traffic monitoring systems. This allows traffic fines to be automatically generated and sent to the appropriate violator without the need for human intervention. An ALPR system can be located on the side of or above a roadway, at a toll booth, or at another type of entrance way. All ALPR systems follow a basic high level process. The process starts when a sensor detects the presence of a vehicle and signals the system camera to record an image of the passing vehicle. The image is passed on to a computer where software running on the computer extracts the license plate number from the image. License plate numbers can then be recorded in a database with other information such as time vehicle past and speed of vehicle. And finally, chain code concept with different parameter is used for recognition of the characters. The performance of the proposed algorithm has been tested on real images. The Proposed system has been implemented using Vision Assistant {&} LabVIEW

  4. Real Time Vehicle Tracking System using GSM and GPS Technology- An Anti-theft Tracking System

    OpenAIRE

    Kunal Maurya; Mandeep Singh; Neelu Jain

    2012-01-01

    A vehicle tracking system is an electronic device installed in a vehicle to enable the owner or a third party to track the vehicle's location. This paper proposed to design a vehicle tracking system that works using GPS and GSM technology, which would be the cheapest source of vehicle tracking and it would work as anti-theft system. It is an embedded system which is used for tracking and positioning of any vehicle by using Global Positioning System (GPS) and Global system for mobile communica...

  5. A new automatic Planetary Boundary Layers height detection and diurnal evolution with compact EZ Lidar

    Science.gov (United States)

    Loaec, S.; Boquet, M.,; Sauvage, L.; Lolli, S.; Rouget, V.

    2009-04-01

    Bigger strongly urbanized cities in the world are often exposed to atmospheric pollution events. To understand the chemical and physical processes that are taking place in these areas it is necessary to describe correctly the Planetary Boundary Layer (PBL) dynamics and the PBL height evolution. For these proposals, a compact and rugged eye safe UV Lidar, the EZLIDAR™, was developed together by CEA/LMD and LEOSPHERE (France) to study and investigate structural and optical properties of clouds and aerosols and PBL time evolution. EZLIDAR™ has been validated by different remote and in-situ instruments as MPL Type-4 Lidar manufactured by NASA at ARM/SGP site or the LNA (Lidar Nuage Aerosol) at the Laboratoire de Metereologie Dynamique LMD (France) and during several intercomparison campaigns. EZLIDAR™ algorithm retrieves automatically the PBL height in real-time. The method is based on the detection of the slope of the signal linked to a sharp change in concentration of the aerosols. Once detected, the different layers are filtered on a 15mn sample and classified between nocturnal, convective or residual layer, depending on the time and date. This method has been validated against those retrieved by the algorithm STRAT from data acquired at IPSL, France, showing 95% of correlation. In this paper are presented the results of the intercomparison campaign that took place in Orleans, France in the framework of ICOS (Integrated Carbon Observation System) project, where the EZ Lidar™ worked under all weather conditions, clear sky, fog, low clouds, during the whole month of October 2008. Moreover, thanks to its 3D scanning capability, the EZLIDAR was able to provide the variability of the PBL height around the site, enabling the scientists to estimate the flux intensities that play a key role in the radiative transfer budget and in the atmospheric pollutants dispersion.

  6. Automatic detection and classification of obstacles with applications in autonomous mobile robots

    Science.gov (United States)

    Ponomaryov, Volodymyr I.; Rosas-Miranda, Dario I.

    2016-04-01

    Hardware implementation of an automatic detection and classification of objects that can represent an obstacle for an autonomous mobile robot using stereo vision algorithms is presented. We propose and evaluate a new method to detect and classify objects for a mobile robot in outdoor conditions. This method is divided in two parts, the first one is the object detection step based on the distance from the objects to the camera and a BLOB analysis. The second part is the classification step that is based on visuals primitives and a SVM classifier. The proposed method is performed in GPU in order to reduce the processing time values. This is performed with help of hardware based on multi-core processors and GPU platform, using a NVIDIA R GeForce R GT640 graphic card and Matlab over a PC with Windows 10.

  7. Design of a Computer-Assisted System to Automatically Detect Cell Types Using ANA IIF Images for the Diagnosis of Autoimmune Diseases.

    Science.gov (United States)

    Cheng, Chung-Chuan; Lu, Chun-Feng; Hsieh, Tsu-Yi; Lin, Yaw-Jen; Taur, Jin-Shiuh; Chen, Yung-Fu

    2015-10-01

    Indirect immunofluorescence technique applied on HEp-2 cell substrates provides the major screening method to detect ANA patterns in the diagnosis of autoimmune diseases. Currently, the ANA patterns are mostly inspected by experienced physicians to identify abnormal cell patterns. The objective of this study is to design a computer-assisted system to automatically detect cell patterns of IIF images for the diagnosis of autoimmune diseases in the clinical setting. The system simulates the functions of modern flow cytometer and provides the diagnostic reports generated by the system to the technicians and physicians through the radar graphs, box-plots, and tables. The experimental results show that, among the IIF images collected from 17 patients, 6 were classified as coarse-speckled, 3 as diffused, 2 as discrete-speckled, 1 as fine-speckled, 2 as nucleolar, and 3 as peripheral patterns, which were consistent with the patterns determined by the physicians. In addition to recognition of cell patterns, the system also provides the function to automatically generate the report for each patient. The time needed for the whole procedure is less than 30 min, which is more efficient than the manual operation of the physician after inspecting the ANA IIF images. Besides, the system can be easily deployed on many desktop and laptop computers. In conclusion, the designed system, containing functions for automatic detection of ANA cell pattern and generation of diagnostic report, is effective and efficient to assist physicians to diagnose patients with autoimmune diseases. The limitations of the current developed system include (1) only a unique cell pattern was considered for the IIF images collected from a patient, and (2) the cells during the process of mitosis were not adopted for cell classification. PMID:26289629

  8. Wavelet Entropy Automatically Detects Episodes of Atrial Fibrillation from Single-Lead Electrocardiograms

    Directory of Open Access Journals (Sweden)

    Juan Ródenas

    2015-09-01

    Full Text Available This work introduces for the first time the application of wavelet entropy (WE to detect episodes of the most common cardiac arrhythmia, atrial fibrillation (AF, automatically from the electrocardiogram (ECG. Given that AF is often asymptomatic and usually presents very brief initial episodes, its early automatic detection is clinically relevant to improve AF treatment and prevent risks for the patients. After discarding noisy TQ intervals from the ECG, the WE has been computed over the median TQ segment obtained from the 10 previous noise-free beats under study. In this way, the P-waves or the fibrillatory waves present in the recording were highlighted or attenuated, respectively, thus enabling the patient’s rhythm identification (sinus rhythm or AF. Results provided a discriminant ability of about 95%, which is comparable to previous works. However, in contrast to most of them, which are mainly based on quantifying RR series variability, the proposed algorithm is able to deal with patients under rate-control therapy or with a reduced heart rate variability during AF. Additionally, it also presents interesting properties, such as the lowest delay in detecting AF or sinus rhythm, the ability to detect episodes as brief as five beats in length or its integration facilities under real-time beat-by-beat ECG monitoring systems. Consequently, this tool may help clinicians in the automatic detection of a wide variety of AF episodes, thus gaining further knowledge about the mechanisms initiating this arrhythmia.

  9. Early Automatic Detection of Parkinson's Disease Based on Sleep Recordings

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Sorensen, Helge B D; Nikolic, Miki;

    2014-01-01

    SUMMARY: Idiopathic rapid-eye-movement (REM) sleep behavior disorder (iRBD) is most likely the earliest sign of Parkinson's Disease (PD) and is characterized by REM sleep without atonia (RSWA) and consequently increased muscle activity. However, some muscle twitching in normal subjects occurs...... during REM sleep. PURPOSE: There are no generally accepted methods for evaluation of this activity and a normal range has not been established. Consequently, there is a need for objective criteria. METHOD: In this study we propose a full-automatic method for detection of RSWA. REM sleep identification...... the number of outliers during REM sleep was used as a quantitative measure of muscle activity. RESULTS: The proposed method was able to automatically separate all iRBD test subjects from healthy elderly controls and subjects with periodic limb movement disorder. CONCLUSION: The proposed work is considered...

  10. Precise 3D Lug Pose Detection Sensor for Automatic Robot Welding Using a Structured-Light Vision System

    Directory of Open Access Journals (Sweden)

    Il Jae Lee

    2009-09-01

    Full Text Available In this study, we propose a precise 3D lug pose detection sensor for automatic robot welding of a lug to a huge steel plate used in shipbuilding, where the lug is a handle to carry the huge steel plate. The proposed sensor consists of a camera and four laser line diodes, and its design parameters are determined by analyzing its detectable range and resolution. For the lug pose acquisition, four laser lines are projected on both lug and plate, and the projected lines are detected by the camera. For robust detection of the projected lines against the illumination change, the vertical threshold, thinning, Hough transform and separated Hough transform algorithms are successively applied to the camera image. The lug pose acquisition is carried out by two stages: the top view alignment and the side view alignment. The top view alignment is to detect the coarse lug pose relatively far from the lug, and the side view alignment is to detect the fine lug pose close to the lug. After the top view alignment, the robot is controlled to move close to the side of the lug for the side view alignment. By this way, the precise 3D lug pose can be obtained. Finally, experiments with the sensor prototype are carried out to verify the feasibility and effectiveness of the proposed sensor.

  11. Bacteriophage Amplification-Coupled Detection and Identification of Bacterial Pathogens

    Science.gov (United States)

    Cox, Christopher R.; Voorhees, Kent J.

    Current methods of species-specific bacterial detection and identification are complex, time-consuming, and often require expensive specialized equipment and highly trained personnel. Numerous biochemical and genotypic identification methods have been applied to bacterial characterization, but all rely on tedious microbiological culturing practices and/or costly sequencing protocols which render them impractical for deployment as rapid, cost-effective point-of-care or field detection and identification methods. With a view towards addressing these shortcomings, we have exploited the evolutionarily conserved interactions between a bacteriophage (phage) and its bacterial host to develop species-specific detection methods. Phage amplification-coupled matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to rapidly detect phage propagation resulting from species-specific in vitro bacterial infection. This novel signal amplification method allowed for bacterial detection and identification in as little as 2 h, and when combined with disulfide bond reduction methods developed in our laboratory to enhance MALDI-TOF-MS resolution, was observed to lower the limit of detection by several orders of magnitude over conventional spectroscopy and phage typing methods. Phage amplification has been combined with lateral flow immunochromatography (LFI) to develop rapid, easy-to-operate, portable, species-specific point-of-care (POC) detection devices. Prototype LFI detectors have been developed and characterized for Yersinia pestis and Bacillus anthracis, the etiologic agents of plague and anthrax, respectively. Comparable sensitivity and rapidity was observed when phage amplification was adapted to a species-specific handheld LFI detector, thus allowing for rapid, simple, POC bacterial detection and identification while eliminating the need for bacterial culturing or DNA isolation and amplification techniques.

  12. Application of Machine Vision to Vehicle Automatic Collision Warning Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Jiang-feng; GAO Feng; XU Guo-yan; YAO Sheng-zhuo

    2008-01-01

    Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system(CWS) can acquire road condition, adjacent vehicle march condition as well as its dynamics performance continuously, then it can forecast the oncoming potential collision and give a warning. Based on the analysis of driver's driving behavior, algorithm's warning norms are determined. Based on warning norms adopting machine vision method, the cooperation collision warning algorithm(CWA) model with multi-input and multi-output is established which is used in supporting vehicle CWS. The CWA is tested using the actual data and the result shows that this algorithm can identify and carry out warning for vehicle collision efficiently, which has important meaning for improving the vehicle travel safety.

  13. Automatic Detection and Evaluation of Solar Cell Micro-Cracks in Electroluminescence Images Using Matched Filters

    DEFF Research Database (Denmark)

    Spataru, Sergiu; Hacke, Peter; Sera, Dezso

    2016-01-01

    how to automatically estimate the total length of each micro-crack from these maps, and propose a method to identify severe types of micro-cracks, such as parallel, dendritic, and cracks with multiple orientations. With an optimized threshold parameter, the technique detects over 90 % of cracks larger...... than 3 cm in length. The method shows great potential for quantifying micro-crack damage after manufacturing or module transportation for the determination of a module quality criterion for cell cracking in PV modules....

  14. Chemical Detection and Identification Techniques for Exobiology Flight Experiments

    Science.gov (United States)

    Kojiro, Daniel R.; Sheverev, Valery A.; Khromov, Nikolai A.

    2002-01-01

    Exobiology flight experiments require highly sensitive instrumentation for in situ analysis of the volatile chemical species that occur in the atmospheres and surfaces of various bodies within the solar system. The complex mixtures encountered place a heavy burden on the analytical Instrumentation to detect and identify all species present. The minimal resources available onboard for such missions mandate that the instruments provide maximum analytical capabilities with minimal requirements of volume, weight and consumables. Advances in technology may be achieved by increasing the amount of information acquired by a given technique with greater analytical capabilities and miniaturization of proven terrestrial technology. We describe here methods to develop analytical instruments for the detection and identification of a wide range of chemical species using Gas Chromatography. These efforts to expand the analytical capabilities of GC technology are focused on the development of detectors for the GC which provide sample identification independent of the GC retention time data. A novel new approach employs Penning Ionization Electron Spectroscopy (PIES).

  15. Modelling and simulation of vehicle electric power system

    Science.gov (United States)

    Lee, Wootaik; Choi, Daeho; Sunwoo, Myoungho

    In recent years, the demand for an increased number of vehicle functions by legislation and customer expectations has introduced many electronic control systems and electrical driven units in vehicles and has resulted in steadily increasing electrical loads. Moreover, due to heavy urban traffic conditions, the idling time fraction has increased and reduced the power generation of the alternator. In the vehicle design phase, in order to avoid an over- or under-design problem of the electric power system, it is necessary to understand both the characteristics of each component of the vehicle electric power system and the interactions between the components. For this purpose, model and simulation algorithms of the vehicle power system are required. In this study, the vehicle electric power system, which is mainly composed of a generator and battery, is modelled and evaluated. Among the various proposed battery models, two types are compared in terms of accuracy and ease-of-use. These two models are distinguished by the consideration of inrush current at the beginning of charging and discharging. In addition, a variable terminal voltage alternator model (VTVA model) is proposed, and is compared with a constant terminal voltage alternator model (CTVA model). Based on the major component model, a simulation algorithm is developed and used to perform a case study. Compared with real data from the vehicle, the simulation results of energy generation and consumption are comparable.

  16. Identification and Control of Mechanical Systems

    Science.gov (United States)

    Juang, Jer-Nan; Phan, Minh Q.

    2001-08-01

    The control of vibrating systems is a significant issue in the design of aircraft, spacecraft, bridges, and high-rise buildings. This book discusses the control of vibrating systems, integrating structural dynamics, vibration analysis, modern control, and system identification. By integrating these subjects engineers will need only one book, rather than several texts or courses, to solve vibration control problems. The authors cover key developments in aerospace control and identification theory, including virtual passive control, observer and state-space identification, and data-based controller synthesis. They address many practical issues and applications, and show examples of how various methods are applied to real systems. Some methods show the close integration of system identification and control theory from the state-space perspective, rather than from the traditional input-output model perspective of adaptive control. This text will be useful for advanced undergraduate and beginning graduate students in aerospace, mechanical, and civil engineering, as well as for practicing engineers.

  17. Comparing technical efficiency of farms with an automatic milking system and a conventional milking system

    NARCIS (Netherlands)

    Steeneveld, W.; Tauer, L.W.; Hogeveen, H.; Oude Lansink, A.G.J.M.

    2012-01-01

    Changing from a conventional milking system (CMS) to an automatic milking system (AMS) necessitates a new management approach and a corresponding change in labor tasks. Together with labor savings, AMS farms have been found to have higher capital costs, primarily because of higher maintenance costs

  18. Automatic Emotional State Detection using Facial Expression Dynamic in Videos

    Directory of Open Access Journals (Sweden)

    Hongying Meng

    2014-11-01

    Full Text Available In this paper, an automatic emotion detection system is built for a computer or machine to detect the emotional state from facial expressions in human computer communication. Firstly, dynamic motion features are extracted from facial expression videos and then advanced machine learning methods for classification and regression are used to predict the emotional states. The system is evaluated on two publicly available datasets, i.e. GEMEP_FERA and AVEC2013, and satisfied performances are achieved in comparison with the baseline results provided. With this emotional state detection capability, a machine can read the facial expression of its user automatically. This technique can be integrated into applications such as smart robots, interactive games and smart surveillance systems.

  19. Modeling and Identification of Multirate Systems

    Institute of Scientific and Technical Information of China (English)

    Feng DING; Tongwen CHEN

    2005-01-01

    Multirate systems are abundant in industry; for example, many soft-sensor design problems are related to modeling, parameter identification, or state estimation involving multirate systems. The study of multirate systems goes back to the early 1950's, and has become an active research area in systems and control. This paper briefly surveys the history of development in the area of multirate systems, and introduces some basic concepts and latest results on multirate systems, including a polynomial transformation technique and the lifting technique as tools for handling multirate systems, lifted state space models, parameter identification of dual-rate systems, how to determine fast single-rate models from dual-rate models and directly from dual-rate data, and a hierarchical identification method for general multirate systems. Finally, some further research topics for multirate systems are given.

  20. Automatic Screening of Missing Objects and Identification with Group Coding of RF Tags

    Directory of Open Access Journals (Sweden)

    G. Vijayaraju

    2013-11-01

    Full Text Available Here the container of the shipping based phenomena it is a collection of the objects in a well oriented fashion by which there is a group oriented fashion related to the well efficient strategy of the objects based on the physical phenomena in a well efficient fashion respectively. Here by the enabling of the radio frequency identification based strategy in which object identification takes place in the system in a well efficient fashion and followed by the container oriented strategy in a well effective fashion respectively. Here there is a problem with respect to the present strategy in which there is a problem with respect to the design oriented mechanism by which there is a no proper analysis takes place for the accurate identification of the objects based on the missing strategy plays a major role in the system based aspect respectively. Here a new technique is proposed in order to overcome the problem of the previous method here the present design oriented powerful strategy includes the object oriented determination of the ID based on the user oriented phenomena in a well effective manner where the data related to the strategy of the missing strategy plays a major role in the system based aspect in a well effective fashion by which that is from the perfect analysis takes place from the same phenomena without the help of the entire database n a well respective fashion takes place in the system respectively. Here the main key aspect of the present method is to effectively divide the entire data related to the particular aspect and define based on the present strategy in a well effective manner in which there is coordination has to be maintained in the system based aspect respectively. Simulations have been conducted on the present method and a lot of analysis takes place on the large number of the data sets in a well oriented fashion with respect to the different environmental conditions where there is an accurate analysis with respect to

  1. Access control and personal identification systems

    CERN Document Server

    Bowers, Dan M

    1988-01-01

    Access Control and Personal Identification Systems provides an education in the field of access control and personal identification systems, which is essential in selecting the appropriate equipment, dealing intelligently with vendors in purchases of the equipment, and integrating the equipment into a total effective system. Access control devices and systems comprise an important part of almost every security system, but are seldom the sole source of security. In order for the goals of the total system to be met, the other portions of the security system must also be well planned and executed

  2. Multifeature Fusion Vehicle Detection Algorithm Based on Choquet Integral

    Directory of Open Access Journals (Sweden)

    Wenhui Li

    2014-01-01

    Full Text Available Vision-based multivehicle detection plays an important role in Forward Collision Warning Systems (FCWS and Blind Spot Detection Systems (BSDS. The performance of these systems depends on the real-time capability, accuracy, and robustness of vehicle detection methods. To improve the accuracy of vehicle detection algorithm, we propose a multifeature fusion vehicle detection algorithm based on Choquet integral. This algorithm divides the vehicle detection problem into two phases: feature similarity measure and multifeature fusion. In the feature similarity measure phase, we first propose a taillight-based vehicle detection method, and then vehicle taillight feature similarity measure is defined. Second, combining with the definition of Choquet integral, the vehicle symmetry similarity measure and the HOG + AdaBoost feature similarity measure are defined. Finally, these three features are fused together by Choquet integral. Being evaluated on public test collections and our own test images, the experimental results show that our method has achieved effective and robust multivehicle detection in complicated environments. Our method can not only improve the detection rate but also reduce the false alarm rate, which meets the engineering requirements of Advanced Driving Assistance Systems (ADAS.

  3. Passive detection of vehicle loading

    Science.gov (United States)

    McKay, Troy R.; Salvaggio, Carl; Faulring, Jason W.; Salvaggio, Philip S.; McKeown, Donald M.; Garrett, Alfred J.; Coleman, David H.; Koffman, Larry D.

    2012-01-01

    The Digital Imaging and Remote Sensing Laboratory (DIRS) at the Rochester Institute of Technology, along with the Savannah River National Laboratory is investigating passive methods to quantify vehicle loading. The research described in this paper investigates multiple vehicle indicators including brake temperature, tire temperature, engine temperature, acceleration and deceleration rates, engine acoustics, suspension response, tire deformation and vibrational response. Our investigation into these variables includes building and implementing a sensing system for data collection as well as multiple full-scale vehicle tests. The sensing system includes; infrared video cameras, triaxial accelerometers, microphones, video cameras and thermocouples. The full scale testing includes both a medium size dump truck and a tractor-trailer truck on closed courses with loads spanning the full range of the vehicle's capacity. Statistical analysis of the collected data is used to determine the effectiveness of each of the indicators for characterizing the weight of a vehicle. The final sensing system will monitor multiple load indicators and combine the results to achieve a more accurate measurement than any of the indicators could provide alone.

  4. PASSIVE DETECTION OF VEHICLE LOADING

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.

    2012-01-03

    The Digital Imaging and Remote Sensing Laboratory (DIRS) at the Rochester Institute of Technology, along with the Savannah River National Laboratory is investigating passive methods to quantify vehicle loading. The research described in this paper investigates multiple vehicle indicators including brake temperature, tire temperature, engine temperature, acceleration and deceleration rates, engine acoustics, suspension response, tire deformation and vibrational response. Our investigation into these variables includes building and implementing a sensing system for data collection as well as multiple full-scale vehicle tests. The sensing system includes; infrared video cameras, triaxial accelerometers, microphones, video cameras and thermocouples. The full scale testing includes both a medium size dump truck and a tractor-trailer truck on closed courses with loads spanning the full range of the vehicle's capacity. Statistical analysis of the collected data is used to determine the effectiveness of each of the indicators for characterizing the weight of a vehicle. The final sensing system will monitor multiple load indicators and combine the results to achieve a more accurate measurement than any of the indicators could provide alone.

  5. An overview of system modeling and identification

    OpenAIRE

    Favier, Gérard

    2010-01-01

    International audience System identification consists in building mathematical models of dynamical systems from experimental data. Such a methodology was mainly developed for designing model-based control systems. More generally, parameter estimation is at the heart of many signal processing applications aiming to extract information from signals, like radar, sonar, seismic, speech, communication, or biomedical (EEG, ECG, EMG) signals. Nowadays, dynamical models and identification methods ...

  6. Colour transformations and K-means segmentation for automatic cloud detection

    Directory of Open Access Journals (Sweden)

    Martin Blazek

    2015-08-01

    Full Text Available The main aim of this work is to find simple criteria for automatic recognition of several meteorological phenomena using optical digital sensors (e.g., Wide-Field cameras, automatic DSLR cameras or robotic telescopes. The output of those sensors is commonly represented in RGB channels containing information about both colour and luminosity even when normalised. Transformation into other colour spaces (e.g., CIE 1931 xyz, CIE L*a*b*, YCbCr can separate colour from luminosity, which is especially useful in the image processing of automatic cloud boundary recognition. Different colour transformations provide different sectorization of cloudy images. Hence, the analysed meteorological phenomena (cloud types, clear sky project differently into the colour diagrams of each international colour systems. In such diagrams, statistical tools can be applied in search of criteria which could determine clear sky from a covered one and possibly even perform a meteorological classification of cloud types. For the purpose of this work, a database of sky images (both clear and cloudy, with emphasis on a variety of different observation conditions (e.g., time, altitude, solar angle, etc. was acquired. The effectiveness of several colour transformations for meteorological application is discussed and the representation of different clouds (or clear sky in those colour systems is analysed. Utilisation of this algorithm would be useful in all-sky surveys, supplementary meteorological observations, solar cell effectiveness predictions or daytime astronomical solar observations.

  7. Vehicle detection based on visual saliency and deep sparse convolution hierarchical model

    Science.gov (United States)

    Cai, Yingfeng; Wang, Hai; Chen, Xiaobo; Gao, Li; Chen, Long

    2016-07-01

    Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification. These types of methods generally have high processing times and low vehicle detection performance. To address this issue, a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed. A visual saliency calculation is firstly used to generate a small vehicle candidate area. The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection. The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group, which outperforms the existing state-of-the-art algorithms. More importantly, high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.

  8. Smart Vehicle Tracking System

    Directory of Open Access Journals (Sweden)

    K.P.Kamble

    2012-08-01

    Full Text Available It is amazing to know how simple ideas can give a whole new dimension to the tracking and navigation industry and smart vehicle tracking system is used for tracking the vehicles. You can optimize driver routes, save petrol or gas and time, reduce theft and control the vehicle functions. Many a times it is not required to track your vehicle or target globally. In majority of cases tracking is more restricted to local purposes only, such as tracking movement of vehicle within city, tracking the raw materials within industrial estate or to know the present position of your daughter or son within city. But unfortunately in the pursuit of making things complex this simple idea is forgotten. This simple yet powerful idea forms the basis of this revolutionary project. All this coupled with a very low cost, a robust design and tremendous market potential makes this model even more attractive.

  9. Selective detection and characterization of nanoparticles from motor vehicles.

    Science.gov (United States)

    Johnston, Murray V; Klems, Joseph P; Zordan, Christopher A; Pennington, M Ross; Smith, James N

    2013-02-01

    Numerous studies have shown that exposure to motor vehicle emissions increases the probability of heart attacks, asthma attacks, and hospital visits among at-risk individuals. However, while many studies have focused on measurements of ambient nanoparticles near highways, they have not focused on specific road-level domains, such as intersections near population centers. At these locations, very intense spikes in particle number concentration have been observed. These spikes have been linked to motor vehicle activity and have the potential to increase exposure dramatically. Characterizing both the contribution and composition of these spikes is critical in developing exposure models and abatement strategies. To determine the contribution of the particle spikes to the ambient number concentration, we implemented wavelet-based algorithms to isolate the particle spikes from measurements taken during the summer and winter of 2009 in Wilmington, Delaware, adjacent to a roadway intersection that approximately 28,000 vehicles pass through daily. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC*; TSI, Inc., St. Paul, MN) and a fast mobility particle sizer (FMPS). The high-frequency portion of the signal, consisting of a series of abrupt spikes in number concentration that varied in length from a few seconds to tens of seconds, accounted for 3% to 35% of the daily ambient number concentration, with spike contributions sometimes greater than 50% of hourly number concentrations. When the data were weighted by particle volume, this portion of the signal contributed an average of 10% to 20% to the daily concentration of particulate matter (PM) vehicles accelerated after a red traffic light turned green. As the distance or transit time from emission to sampling increased, the size distribution shifted to a larger particle size, which confirmed the source assignments. To determine the

  10. STUDY ON SHIFT SCHEDULE AND SIMULATION OF AUTOMATIC TRANSMISSION

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    From the point of view of saving energy, a new shift schedule and auto-controlling strategy for automatic transmission are proposed. In order to verify this shift schedule,a simulation program using a software package of Matlab/Simulink is developed. The simulation results show the shift schedule is correct. This shift schedule has enriched the theory of vehicle automatic maneuvering and will improve the efficiency of hydrodynanic drive system of the vehicle.

  11. An automatic seismic signal detection method based on fourth-order statistics and applications

    Institute of Scientific and Technical Information of China (English)

    Liu Xi-Qiang; Cai Yin; Zhao Rui; Zhao Yin-Gang; Qu Bao-An; Feng Zhi-Jun; Li Hong

    2014-01-01

    Real-time, automatic, and accurate determination of seismic signals is critical for rapid earthquake reporting and early warning. In this study, we present a correction trigger function (CTF) for automatically detecting regional seismic events and a fourth-order statistics algorithm with the Akaike information criterion (AIC) for determining the direct wave phase, based on the differences, or changes, in energy, frequency, and amplitude of the direct P- or S-waves signal and noise. Simulations suggest for that the proposed fourth-order statistics result in high resolution even for weak signal and noise variations at different amplitude, frequency, and polarization characteristics. To improve the precision of establishing the S-waves onset,fi rst a specifi c segment of P-wave seismograms is selected and the polarization characteristics of the data are obtained. Second, the S-wave seismograms that contained the specifi c segment of P-wave seismograms are analyzed by S-wave polarizationfi ltering. Finally, the S-wave phase onset times are estimated. The proposed algorithm was used to analyze regional earthquake data from the Shandong Seismic Network. The results suggest that compared with conventional methods, the proposed algorithm greatly decreased false and missed earthquake triggers, and improved the detection precision of direct P- and S-wave phases.

  12. Automatic detection of human and Energy saving based on Zigbee Communication

    Directory of Open Access Journals (Sweden)

    Chinnam Sujana,

    2011-06-01

    Full Text Available This paper proposes automatic detection of human and Energy saving room architecture to reduce standby power consumption and to make the room easily controllable with an IR remote control of a home appliance. To realize the proposed room architecture, we proposed and designed the Zigbee communication. Zigbee is a low-cost, low-power, wireless mesh networking. The low cost allows the technology to be widely deployed in wireless control and monitoring applications, the low power-usage allows longer life with smaller batteries, and the mesh networking provides high reliability and larger range. The proposed auto detection of human done using the IR sensor to indicate the entering or exit of the persons. Microcontroller continuously monitors the infrared receiver. When any object pass through the IR receiver then the IR rays falling on the receiver are obstructed, this obstruction is sensed by the microcontroller (LPC2148-ARM7 also PIR sensor will check the presence of human beings with the help of radiations emitted by human beings. Then microcontroller will check the input coming from these two sensors and simultaneously if somebody is present then automatically checks for the light intensity and the temperature. And then if the room is found dark it switches ON the lights and if the temperature is more it switches ON the fans. And if nobody is present then all the lights will be switched offautomatically.

  13. Automatic event detection for tennis broadcasting

    OpenAIRE

    Enebral González, Javier

    2011-01-01

    Within the image digital processing framework, this thesis is situated in the automatic content indexation field. Specifically during the project, different methods and techniques will be developed in order to achieve event detection for broadcasting tennis videos. Audiovisual indexation consists in the generation of descriptive tags based on the existing audiovisual data. All these tags are used to search the desired material in an efficient way. Televisions and other entities are l...

  14. Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring

    Directory of Open Access Journals (Sweden)

    Wenyu Zhang

    2014-10-01

    Full Text Available Cracks are an important indicator reflecting the safety status of infrastructures. This paper presents an automatic crack detection and classification methodology for subway tunnel safety monitoring. With the application of high-speed complementary metal-oxide-semiconductor (CMOS industrial cameras, the tunnel surface can be captured and stored in digital images. In a next step, the local dark regions with potential crack defects are segmented from the original gray-scale images by utilizing morphological image processing techniques and thresholding operations. In the feature extraction process, we present a distance histogram based shape descriptor that effectively describes the spatial shape difference between cracks and other irrelevant objects. Along with other features, the classification results successfully remove over 90% misidentified objects. Also, compared with the original gray-scale images, over 90% of the crack length is preserved in the last output binary images. The proposed approach was tested on the safety monitoring for Beijing Subway Line 1. The experimental results revealed the rules of parameter settings and also proved that the proposed approach is effective and efficient for automatic crack detection and classification.

  15. Intelligent CAD System for Automatic Detection of Mitotic Cells from Breast Cancer Histology Slide Images Based on Teaching-Learning-Based Optimization

    Directory of Open Access Journals (Sweden)

    Ramin Nateghi

    2014-01-01

    Full Text Available This paper introduces a computer-assisted diagnosis (CAD system for automatic mitosis detection from breast cancer histopathology slide images. In this system, a new approach for reducing the number of false positives is proposed based on Teaching-Learning-Based optimization (TLBO. The proposed CAD system is implemented on the histopathology slide images acquired by Aperio XT scanner (scanner A. In TLBO algorithm, the number of false positives (falsely detected nonmitosis candidates as mitosis ones is defined as a cost function and, by minimizing it, many of nonmitosis candidates will be removed. Then some color and texture (textural features such as those derived from cooccurrence and run-length matrices are extracted from the remaining candidates and finally mitotic cells are classified using a specific support vector machine (SVM classifier. The simulation results have proven the claims about the high performance and efficiency of the proposed CAD system.

  16. Impact of a radio-frequency identification system and information interchange on clearance processes for cargo at border posts

    Directory of Open Access Journals (Sweden)

    Ernest Bhero

    2015-02-01

    Full Text Available Background: Improved operational efficiency is important to role players in cross-border logistics and trade corridors. Cargo owners and cargo forwarders have been particularly concerned about long delays in the processing and clearing of cargo at border posts. Field studies suggest that these delays are due to a combination of factors, such as a lack of optimum system configurations and non-optimised human-dependent operations, which make the operations prone to corruption and other malpractices.Objectives: This article presents possible strategies for improving some of the operations in this sector. The research hinges on two key questions: (1 what is the impact of information interchange between stakeholders on the cargo transit time and (2 how will cargo transit time be impacted upon by automatic identification of cargo and the status of cargo seals on arriving vehicles at the border?Method: The use of information communication systems enabled by automatic identification systems (incorporating radio-frequency identification technology is suggested.Results: Results obtained by the described simulation model indicate that improvements of up to 82% with regard to transit time are possible using these techniques.Conclusion: The findings therefore demonstrate how operations at border posts can be improved through the use of appropriate technology and configuration of the operations.

  17. Using Massive Vehicle Positioning Data to Improve Control and Planning of Public Road Transport

    Directory of Open Access Journals (Sweden)

    Gabino Padrón

    2014-04-01

    Full Text Available This study describes a system for the automatic recording of positioning data for public transport vehicles used on roads. With the data provided by this system, transportation-regulatory authorities can control, verify and improve the routes that vehicles use, while also providing new data to improve the representation of the transportation network and providing new services in the context of intelligent metropolitan areas. The system is executed autonomously in the vehicles, by recording their massive positioning data and transferring them to remote data banks for subsequent processing. To illustrate the utility of the system, we present a case of application that consists of identifying the points at which vehicles stop systematically, which may be points of scheduled stops or points at which traffic signals or road topology force the vehicle to stop. This identification is performed using pattern recognition techniques. The system has been applied under real operating conditions, providing the results discussed in the present study.

  18. The Effects of Degraded Vision and Automatic Combat Identification Reliability on Infantry Friendly Fire Engagements

    OpenAIRE

    Kogler, Timothy Michael

    2003-01-01

    Fratricide is one of the most devastating consequences of any military conflict. Target identification failures have been identified as the last link in a chain of mistakes that can lead to fratricide. Other links include weapon and equipment malfunctions, command, control, and communication failures, navigation failures, fire discipline failures, and situation awareness failures. This research examined the effects of degraded vision and combat identification reliability on the time-stress...

  19. A Study of Applications of Multiagent System Specificaitons and the Key Techniques in Automatic Abstracts System

    Institute of Scientific and Technical Information of China (English)

    HUShun-geng; ZHONGYi-xin

    2001-01-01

    In this thesis, multiagent system specifications, multiagent system architectures, agent communica-tion languages and agent communication protocols, automatic abstracting based on multiagent technolo-gies are studied.Some concerned problems of de-signs and realization of automatic abstracting sys-tems based on multiagent technologies are strdied, too.Chapter 1 shows the significance and objectives of the thesis, its main contents are summarized, and innovations of the thesis are showed.Some basic concepts of agents and multiagent systems are stud-ied in Chapter2.The definitions of agents and mul-tiagent systems are given, and the theory, technolo-gies and applications of multiagent systems are sum-marized .Furthermore, some important studying trends of multiagent systems are set forward.Multi-agent system specifications are strdied in Chapter30MAS/KIB-a multiagent system specification is built using mental states such as K(Know), B(Be-lief), and I(Intention), its grammar and seman-teme are discussed, axioms and inference rules are given, and some properties are researched.We also compare MAS/KIB with other existing specifica-tions.MAS/KIB has the following characteristicsL1)each agent has its own world outlood;(2)no global data in the system;(3)processes of state changes are used as indexes to systems;(4)it has the characteristics of not only time series logic but also dynamic logic;and (5) interactive actions are included.The architectures of multiagent systems are studied in Chapter 4.First, we review some typical architecture of multiagent systems, agent network architecture, agent federated architecture, agent blackboard architenture ,and Foundation of Intelligent Physical Agent(FIPA) architecture.For the first time, we set forward and study the layering and partitioning models of the architectures of multi-agent systems,organizing architecture models, and interoperability architecture model of multiagent sys-tems .Chapter 5 studies agent communication lan

  20. A fully automatic wildlife acoustic monitor and survey system

    OpenAIRE

    Boucher, Neil; Jinnai, Michihiro; Smolders, Andrew

    2012-01-01

    International audience We describe a fully automated, PC based wildlife monitoring and survey system that is used for diverse species studies. The system uses a wide-area recorder that can record over areas of up to several square kilometres. The recorder can run, unattended for more than a month. The recordings can either be analysed in real time to produce a particular response (e.g. send an SMS if a rare parrot is detected), or can be analysed later on a PC. Any number of different spec...