WorldWideScience

Sample records for automatic vehicle detection and identification systems

  1. INTELLIGENT FATIGUE DETECTION AND AUTOMATIC VEHICLE CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    Monali Gulhane

    2014-10-01

    Full Text Available This paper describes method for detecting the early signs of fatigue in train drivers. As soon as the train driver is falling in symptoms of fatigue immediate message will be transfer to the control room indicating the status of the drivers. In addition of the advance technology of heart rate sensors is also added in the system for correct detection of status of driver if in either case driver is falling to fatigue due to any sever medical problems .The fatigue is detected in the system by the image processing method of comparing the image(frames in the video and by using the human features we are able to estimate the indirect way of detecting fatigue. The technique also focuses on modes of person when driving the train i.e. awake, drowsy state or sleepy and sleep state. The system is very efficient to detect the fatigue and control the train also train can be controlled if it cross any such signal by which the train may collide on another train

  2. Intelligent Fatigue Detection and Automatic Vehicle Control System

    OpenAIRE

    Monali Gulhane; P.S.Mohod

    2014-01-01

    This paper describes method for detecting the early signs of fatigue in train drivers. As soon as the train driver is falling in symptoms of fatigue immediate message will be transfer to the control room indicating the status of the drivers. In addition of the advance technology of heart rate sensors is also added in the system for correct detection of status of driver if in either case driver is falling to fatigue due to any sever medical problems .The fatigue is detected in the system by th...

  3. Intelligent automatic overtaking system using vision for vehicle detection

    OpenAIRE

    Milanés Montero, Vicente; Fernández Llorca, David; Villagra Serrano, Jorge; Pérez, Joshué; Fernández López, Carlos; Parra Alonso, Ignacio; González Fernández-Vallejo, Carlos; Sotelo, Miguel Ángel

    2012-01-01

    There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manœuvres involving vehicles – overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomo...

  4. 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.

  5. Video Analytics Algorithm for Automatic Vehicle Classification (Intelligent Transport System)

    OpenAIRE

    ArtaIftikhar; Ali Javed

    2013-01-01

    Automated Vehicle detection and classification is an important component of intelligent transport system. Due to significant importance in various fields such as traffic accidents avoidance, toll collection, congestion avoidance, terrorist activities monitoring, security and surveillance systems, intelligent transport system has become important field of study. Various technologies have been used for detecting and classifying vehicles automatically. Automated vehicle detection is broadly divi...

  6. A multi-attribute based methodology for vehicle detection and identification

    Science.gov (United States)

    Elangovan, Vinayak; Alsaidi, Bashir; Shirkhodaie, Amir

    2013-05-01

    Robust vehicle detection and identification is required for the intelligent persistent surveillance systems. In this paper, we present a Multi-attribute Vehicle Detection and Identification technique (MVDI) for detection and classification of stationary vehicles. The proposed model uses a supervised Hamming Neural Network (HNN) for taxonomy of shape of the vehicle. Vehicles silhouette features are employed for the training of the HNN from a large array of training vehicle samples in different type, scale, and color variation. Invariant vehicle silhouette attributes are used as features for training of the HNN which is based on an internal Hamming Distance and shape features to determine degree of similarity of a test vehicle against those it's selectively trained with. Upon detection of class of the vehicle, the other vehicle attributes such as: color and orientation are determined. For vehicle color detection, provincial regions of the vehicle body are used for matching color of the vehicle. For the vehicle orientation detection, the key structural features of the vehicle are extracted and subjected to classification based on color tune, geometrical shape, and tire region detection. The experimental results show the technique is promising and has robustness for detection and identification of vehicle based on their multi-attribute features. Furthermore this paper demonstrates the importance of the vehicle attributes detection towards the identification of Human-Vehicle Interaction events.

  7. 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.

  8. Automatic resource identification for FPGA-based reconfigurable measurement and control systems with mezzanines in FMC standard

    Science.gov (United States)

    Wojenski, Andrzej; Kasprowicz, Grzegorz; Pozniak, Krzysztof T.; Romaniuk, Ryszard

    2013-10-01

    The paper describes a concept of automatic resources identification algorithm used in reconfigurable measurement systems. In the paper is also presented a concept of algorithm for automatic generation of HDL codes (firmware) and management of reconfigurable measurement and control systems. Following sections are described in details: definition of measurement system, FMC boards installation, automatic FPGA startup configuration, automatic FMC detection and automatic card identification. Reconfigurable measurement and control systems are using FPGA devices and mezzanines in FMC standard. This work is a part of a wider project for automatic firmware generation and management of reconfigurable systems.

  9. 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.

  10. 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...

  11. 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...

  12. 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...

  13. 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...

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

    Directory of Open Access Journals (Sweden)

    2011-09-01

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

  15. 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)

  16. Development of optical automatic positioning and wafer defect detection system

    Science.gov (United States)

    Tien, Chuen-Lin; Lai, Qun-Huang; Lin, Chern-Sheng

    2016-02-01

    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.

  17. Automatic Traffic Density Estimation and Vehicle Classification for Traffic Surveillance Systems using Neural Networks

    OpenAIRE

    Ozkurt, Celil; Camci, Fatih

    2009-01-01

    It is important to know the road traffic density real time especially in mega cities for signal control and effective traffic management. In recent years, video monitoring and surveillance systems have been widely used in traffic management. Hence, traffic density estimation and vehicle classification can be achieved using video monitoring systems. In most vehicle detection methods in the literature, only the detection of vehicles in frames of the given video is emphesized. However, further a...

  18. A New Algorithmic Approach for Detection and Identification of Vehicle Plate Numbers

    OpenAIRE

    Daya, B; Chauvet, P.; Akoum, A.

    2010-01-01

    This work proposes a method for the detection and identification of parked vehicles stationed. This technique composed many algorithms for the detection, localization, segmentation, extraction and recognition of number plates in images. It is acts of a technology of image processing used to identify the vehicles by their number plates. Knowing that we work on images whose level of gray is sampled with (120×180), resulting from a base of abundant data by PSA. We present two algorithms allowing...

  19. On the automatic detection of otolith features for fish species identification and their age estimation

    OpenAIRE

    Sória Pérez, José A. (José Antonio)

    2013-01-01

    This thesis deals with the automatic detection of features in signals, either extracted from photographs or captured by means of electronic sensors, and its possible application in the detection of morphological structures in fish otoliths so as to identify species and estimate their age at death. From a more biological perspective, otoliths, which are calcified structures located in the auditory system of all teleostean fish, constitute one of the main elements employed in the study and mana...

  20. 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.

  1. Evaluation of Methods for Robust, Automatic Detection of Net Tear with Remotely Operated Vehicle and Remote Sensing

    OpenAIRE

    Haugene, Tormod

    2014-01-01

    Accompanying the continuous growth of the aquaculture fish farming industry in the recent years, the usage of Remotely Operated Vehicles (ROV) for regular inspections of net integrity has become increasingly common. For a human ROV operator, routine inspections can be repetitious and time consuming, and improving the regularity and efficiency of these operations are of interest. The aim of this study was therefore be to develop a robust technique for automatic detection of net damage with an ...

  2. 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. 

  3. 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.

  4. 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

  5. INVESTMENT OF THE DEVELOPMENT OF ROAD-BUILD MEANS, AUTOMATIC AND INFORMATIONAL SYSTEMS TO INCREASE TRAFFIC SAFETY IN VEHICLE SYSTEMS

    Directory of Open Access Journals (Sweden)

    Shirokov Lev Alekseevich

    2015-09-01

    Full Text Available The modern transport system is a complex integrated object, which includes various road pavements, different technical means to provide vehicles motion, organizational systems of traffic management. In the contemporary conditions of construction industry functioning the task to create vehicle systems is of a great economic importance. Great labour and material resources are used for production of transport means for providing construction works and operation of these means. The authors consider the questions of theoretical and informational foundation development for the formation of the criteria basis of investment optimization task during construction of automatical and informational systems for increase of traffic safety in transport systems, providing zero accident rate.

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

    OpenAIRE

    Yan Zhang; Wenxing Ma; Xuesong Li

    2013-01-01

    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 ...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Alcohol Detection and Automatic Drunken Drive Avoiding System

    Directory of Open Access Journals (Sweden)

    Prof. P. H. Kulkarni

    2014-04-01

    Full Text Available The main aim of this project is to design an embedded system for implementing a efficient alcohol detection system that will be useful to avoid accidents. There are many different types of accidents which occur in daily life. Accidents may cause due to many reasons it may be due to brake fail. Most often accidents occur due to over drunken person. Though there are laws to punish drunken drivers they cannot be fully implemented. Because traffic police cannot stand on every road to check each and every car driver whether he/she has drunk or not. This can be a major reason for accidents. So there is a need for a effective system to check drunken drivers. Therefore in order to avoid these accidents we have implemented a prototype project. In our project, Initially we check whether the person has drunken or not by using the MQ3 GAS sensor. In this system, sensor circuit is used to detect whether the alcohol was consumed by driver or not. To this end, we have designed such a system that when alcohol concentration is detected then car will be stopped and the related information will go to nearby location through GSM. This project is based on EMBEDDED C programming using AVR-AT mega 16 microcontroller.

  12. 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

  13. 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

  14. Development of monitoring and automatic fault detection solutions for grid-connected photovoltaic systems

    OpenAIRE

    Capogna, Vicenzo

    2012-01-01

    In this Final Thesis work, the development of a new monitoring and automatic fault detection system for grid-connected photovoltaic systems is presented and described in its details. This product has been developed in JavaScript and HTLM protocols and it allow real time an online performance monitoring and comparison together with fault detection and causes diagnosis. The presented solution is focus on the DC side of the PV system and it includes: a simple and effective simulat...

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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

  2. 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

  3. Multi-objective Genetic Algorithm for System Identification and Controller Optimization of Automated Guided Vehicle

    OpenAIRE

    Xing Wu; Peihuang Lou; Dunbing Tang

    2011-01-01

    This paper presents a multi-objective genetic algorithm (MOGA) with Pareto optimality and elitist tactics for the control system design of automated guided vehicle (AGV). The MOGA is used to identify AGV driving system model and optimize its servo control system sequentially. In system identification, the model identified by least square method is adopted as an evolution tutor who selects the individuals having balanced performances in all objectives as elitists. In controller optimization, t...

  4. 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

  5. Automatic recognition of type III solar radio bursts. Automated radio burst identification system method and first observations

    International Nuclear Information System (INIS)

    Complete text of publication follows. Because of the rapidly increasing role of technology, including complicated electronic systems, spacecraft, etc., modern society has become more vulnerable to a set of extraterrestrial influences (space weather) and requires continuous observation and forecasts of space weather. The major space weather events like solar flares and coronal mass ejections are usually accompanied by solar radio bursts, which can be used for a real-time space weather forecast. Coronal type III radio bursts are produced near the local electron plasma frequency and near its harmonic by fast electrons ejected from the solar active regions and moving through the corona and solar wind. These bursts have dynamic spectra with frequency rapidly falling with time, the typical duration of the coronal burst being about 1-3 s. This paper presents a new method developed to detect coronal type III bursts automatically and its implementation in a new Automated Radio Burst Identification System (ARBIS), which is working in real-time. The central idea of the implementation is to use the Radon transform for more objective detection of the bursts as approximately straight lines in dynamic spectra. Preliminary tests of the method with the use of the spectra obtained during 13 days show that the performance of the current implementation is quite high, ∼84%, while no false positives are observed and 23 events not listed previously are found. The first automatically detected coronal type III radio bursts are presented.

  6. 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.

  7. 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

  8. A Microcontroller Based Car-Safety System Implementing Drowsiness Detection And Vehicle-Vehicle Distance Detection In Parallel.

    Directory of Open Access Journals (Sweden)

    Pragyaditya Das.

    2015-08-01

    Full Text Available Abstract Accidents due to drowsiness can be controlled and prevented with the help of eye blink sensor using IR rays. It consists of IR transmitter and an IR receiver. The transmitter transmits IR rays into the eye. If the eye is shut then the output is high. If the eye is open then the output is low. This output is interfaced with an alarm inside and outside the vehicle. This module can be connected to the braking system of the vehicle and can be used to reduce the speed of the vehicle. The alarm inside the vehicle will go on for a period of time until the driver is back to his senses. If the driver is unable to take control of the vehicle after that stipulated amount of time then the alarm outside the vehicle will go on to warn and tell others to help the driver.

  9. 33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

    Science.gov (United States)

    2010-07-01

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

  10. Vision-based object detection and recognition system for intelligent vehicles

    Science.gov (United States)

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

    1999-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Clark, R K

    1980-06-26

    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. 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

  13. 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.

  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. 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

  16. 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.

  17. AUTOMATIC URBAN ILLEGAL BUILDING DETECTION USING MULTI-TEMPORAL SATELLITE IMAGES AND GEOSPATIAL INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    N. Khalili Moghadam

    2015-12-01

    Full Text Available 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.

  18. An Adaptive Energy Management System for Electric Vehicles Based on Driving Cycle Identification and Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Qiao Zhang

    2016-05-01

    Full Text Available Since driving cycle greatly affects load power demand, driving cycle identification (DCI is proposed to predict power demand that can be expected to prepare for the power distribution between battery and supercapacitor. The DCI is developed based on a learning vector quantization (LVQ neural network method, which is assessed in both training and validation based on the statistical data obtained from six standard driving cycles. In order to ensure network accuracy, characteristic parameter and slide time window, which are two important factors ensuring the network accuracy for onboard hybrid energy storage system (HESS applications in electric vehicles, are discussed and designed. Based on the identification results, Multi-level Haar wavelet transform (Haar-WT is proposed for allocating the high frequency components of power demand into the supercapacitor which could damage battery lifetime and the corresponding low frequency components into the battery system. The proposed energy management system can better increase system efficiency and battery lifetime compared with the conventional sole frequency control. The advantages are demonstrated based on a randomly generated driving cycle from the standard driving cycle library via simulation.

  19. 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.

  20. 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.

  1. Automatic Detection of Dominance and Expected Interest

    Directory of Open Access Journals (Sweden)

    M. Teresa Anguera

    2010-01-01

    Full Text Available Social Signal Processing is an emergent area of research that focuses on the analysis of social constructs. Dominance and interest are two of these social constructs. Dominance refers to the level of influence a person has in a conversation. Interest, when referred in terms of group interactions, can be defined as the degree of engagement that the members of a group collectively display during their interaction. In this paper, we argue that only using behavioral motion information, we are able to predict the interest of observers when looking at face-to-face interactions as well as the dominant people. First, we propose a simple set of movement-based features from body, face, and mouth activity in order to define a higher set of interaction indicators. The considered indicators are manually annotated by observers. Based on the opinions obtained, we define an automatic binary dominance detection problem and a multiclass interest quantification problem. Error-Correcting Output Codes framework is used to learn to rank the perceived observer's interest in face-to-face interactions meanwhile Adaboost is used to solve the dominant detection problem. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers in both dominance and interest detection problems.

  2. Multi-objective Genetic Algorithm for System Identification and Controller Optimization of Automated Guided Vehicle

    Directory of Open Access Journals (Sweden)

    Xing Wu

    2011-07-01

    Full Text Available This paper presents a multi-objective genetic algorithm (MOGA with Pareto optimality and elitist tactics for the control system design of automated guided vehicle (AGV. The MOGA is used to identify AGV driving system model and optimize its servo control system sequentially. In system identification, the model identified by least square method is adopted as an evolution tutor who selects the individuals having balanced performances in all objectives as elitists. In controller optimization, the velocity regulating capability required by AGV path tracking is employed as decision-making preferences which select Pareto optimal solutions as elitists. According to different objectives and elitist tactics, several sub-populations are constructed and they evolve concurrently by using independent reproduction, neighborhood mutation and heuristic crossover. The lossless finite precision method and the multi-objective normalized increment distance are proposed to keep the population diversity with a low computational complexity. Experiment results show that the cascaded MOGA have the capability to make the system model consistent with AGV driving system both in amplitude and phase, and to make its servo control system satisfy the requirements on dynamic performance and steady-state accuracy in AGV path tracking.

  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. 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.

  6. 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.

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

    OpenAIRE

    Saha, Satadal; Basu, Subhadip; 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 backgrou...

  8. 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...

  9. An image analysis and classification system for automatic weed species identification in different crops for precision weed management

    OpenAIRE

    Weis, Martin

    2010-01-01

    A system for the automatic weed detection in arable fields was developed in this thesis. With the resulting maps, weeds in fields can be controlled on a sub-field level, according to their abundance. The system contributes to the emerging field of Precision Farming technologies. Precision Farming technologies have been developed during the last two decades to refine the agricultural management practise. The goal of Precision Farming is to vary treatments within fields, according to the local ...

  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. 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.

  12. 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.

  13. Vision-based industrial automatic vehicle classifier

    Science.gov (United States)

    Khanipov, Timur; Koptelov, Ivan; Grigoryev, Anton; Kuznetsova, Elena; Nikolaev, Dmitry

    2015-02-01

    The paper describes the automatic motor vehicle video stream based classification system. The system determines vehicle type at payment collection plazas on toll roads. Classification is performed in accordance with a preconfigured set of rules which determine type by number of wheel axles, vehicle length, height over the first axle and full height. These characteristics are calculated using various computer vision algorithms: contour detectors, correlational analysis, fast Hough transform, Viola-Jones detectors, connected components analysis, elliptic shapes detectors and others. Input data contains video streams and induction loop signals. Output signals are vehicle enter and exit events, vehicle type, motion direction, speed and the above mentioned features.

  14. 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

  15. Thruster Modelling for Underwater Vehicle Using System Identification Method

    Directory of Open Access Journals (Sweden)

    Mohd Shahrieel Mohd Aras

    2013-05-01

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

  16. 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.

  17. Neutron Interrogation System For Underwater Threat Detection And Identification

    International Nuclear Information System (INIS)

    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.

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

    Science.gov (United States)

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

    2014-04-01

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

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

    International Nuclear Information System (INIS)

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

  20. 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.

  1. Automatic Accident Detection and Ambulance Rescue with Intelligent Traffic Light System

    Directory of Open Access Journals (Sweden)

    S.IYYAPPAN

    2013-04-01

    Full Text Available Nowadays the road accidents in modern urban areas are increased to uncertain level. The loss of human life due to accident is to be avoided. Traffic congestion and tidal flow are major facts that cause delay to ambulance. To bar loss of human life due to accidents we introduce a scheme called ITLS (Intelligent Traffic Light system. The main theme behind this scheme is to provide a smooth flow for the emergency vehicles like ambulance to reach the hospitals in time and thus minimizing the delay caused by traffic congestion. The idea behind this scheme is to implement ITLS which would control mechanically the traffic lights in the path of the ambulance. The ambulance is controlled by the control unit which furnishes adequate route to the ambulance and also controls the traffic light according to the ambulance location and thus reaching the hospital safely. The controller identifies the location of the accident spot through the sensor systems in the vehicle which determined the accident and thus the controller walks through the ambulance to the spot. This scheme is fully automated, thus it finds the accident spot, controls the traffic lights, helping to reach the hospital in time.

  2. 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.

  3. 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...

  4. 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 is...

  5. 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 ...

  6. 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...

  7. 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

  8. Integrated microfluidic system with automatic sampling for permanent molecular and antigen-based detection of CBRNE-related pathogens

    Science.gov (United States)

    Becker, Holger; Schattschneider, Sebastian; Klemm, Richard; Hlawatsch, Nadine; Gärtner, Claudia

    2015-03-01

    The continuous monitoring of the environment for lethal pathogens is a central task in the field of biothreat detection. Typical scenarios involve air-sampling in locations such as public transport systems or large public events and a subsequent analysis of the samples by a portable instrument. Lab-on-a-chip technologies are one of the promising technological candidates for such a system. We have developed an integrated microfluidic system with automatic sampling for the detection of CBRNE-related pathogens. The chip contains a two-pronged analysis strategy, on the one hand an immunological track using antibodies immobilized on a frit and a subsequent photometric detection, on the other hand a molecular biology approach using continuous-flow PCR with a fluorescence end-point detection. The cartridge contains two-component molded rotary valve to allow active fluid control and switching between channels. The accompanying instrument contains all elements for fluidic and valve actuation, thermal control, as well as the two detection modalities. Reagents are stored in dedicated reagent packs which are connected directly to the cartridge. With this system, we have been able to demonstrate the detection of a variety of pathogen species.

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

    Science.gov (United States)

    Henrique Castelo Branco, Luiz; César Lima Segantine, Paulo

    2015-09-01

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

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

    DEFF Research Database (Denmark)

    2013-01-01

    tuberculosis, in single or multiplexed formats enable diseases to be diagnosed, treated, or prevented through the identification of potentially harmful organisms. This disclosure includes also follow-up tests or continued monitoring to evaluate responses to treatment or eradication efforts. In a further aspect...... the technology enables the testing of medical or chemical treatments designed to cure or prevent diseases based upon drugs targeting type 1 topoisomerases. Finally, the reagents and platforms needed for said purposes can be compiled from loose parts or provided as user-friendly kits, potentially...

  11. Towards fully automatic object detection and segmentation

    Science.gov (United States)

    Schramm, Hauke; Ecabert, Olivier; Peters, Jochen; Philomin, Vasanth; Weese, Juergen

    2006-03-01

    An automatic procedure for detecting and segmenting anatomical objects in 3-D images is necessary for achieving a high level of automation in many medical applications. Since today's segmentation techniques typically rely on user input for initialization, they do not allow for a fully automatic workflow. In this work, the generalized Hough transform is used for detecting anatomical objects with well defined shape in 3-D medical images. This well-known technique has frequently been used for object detection in 2-D images and is known to be robust and reliable. However, its computational and memory requirements are generally huge, especially in case of considering 3-D images and various free transformation parameters. Our approach limits the complexity of the generalized Hough transform to a reasonable amount by (1) using object prior knowledge during the preprocessing in order to suppress unlikely regions in the image, (2) restricting the flexibility of the applied transformation to only scaling and translation, and (3) using a simple shape model which does not cover any inter-individual shape variability. Despite these limitations, the approach is demonstrated to allow for a coarse 3-D delineation of the femur, vertebra and heart in a number of experiments. Additionally it is shown that the quality of the object localization is in nearly all cases sufficient to initialize a successful segmentation using shape constrained deformable models.

  12. Automatic Road Lighting System (ARLS) Model Based on Image Processing of Captured Video of Vehicle Toy Motion

    CERN Document Server

    Suprijadi,; Viridi, Sparisoma

    2011-01-01

    Using a vehicle toy as a moving object an automatic road lighting system (ARLS) model is constructed. A video camera with 25 fps is used to capture the vehicle toy motion as it moves in the test segment of the road. Captured images are then processed to calculate vehicle toy speed. This information of the speed together with position of vehicle toy is then used to switch on and off the lighting system along the path that passes by the vehicle toy. Length of the road test segment is 1 m, the video camera is positioned about 1.075 m above the test segment, and the vehicle toy dimension is 13 cm x 9.3 cm. Maximum speed that ARLS can handle is about 1.32 m/s with error less than 23.48 %. The highest performance is obtained about 91 % at speed 0.93 m/s.

  13. 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.

  14. Vehicle and cargo inspection system

    Science.gov (United States)

    Verbinski, Victor V.; Orphan, Victor J.

    1997-02-01

    Vehicle and Cargo Inspection System (VACIS) is comprised of a 1 Curie 137Cs gamma-ray source in a shield and collimator which produces a fan-shaped beam designed to intercept a vertical array of gama-ray detectors contained in a tower structure. The source and detector modules straddle the vehicle or container being inspected and are mounted on self-propelled trolleys which travel in synchronization along two parallel tracks covering the length of the scanned object. The signals from the gamma-ray detector array are processed and displayed so as to produce a 2D gamma-radiographic image of the object. Testing of the system on a variety of empty and lightly-loaded vehicles and containers has demonstrated the effectiveness of VACIS in detecting hidden contraband. For example, a small sample of cocaine only 1.5 inches thick was readily detected in a container.

  15. 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.

  16. An automatic detection system for buried explosive hazards in FL-LWIR and FL-GPR data

    Science.gov (United States)

    Stone, K.; Keller, J. M.; Anderson, D. T.; Barclay, D. B.

    2012-06-01

    Improvements to an automatic detection system for locating buried explosive hazards in forward-looking longwave infrared (FL-LWIR) imagery, as well as the system's application to detection in confidence maps and forwardlooking ground penetrating radar (FL-GPR) data, are discussed. The detection system, described in previous work, utilizes an ensemble of trainable size-contrast filters and the mean-shift algorithm in Universal Transverse Mercator (UTM) coordinates. Improvements of the raw detection algorithm include weighted mean-shift within the individual size-contrast filters and a secondary classification step which exacts cell structured image space features, including local binary patterns (LBP), histogram of oriented gradients (HOG), edge histogram descriptor (EHD), and maximally stable extremal regions (MSER) segmentation based shape information, from one or more looks and classifies the resulting feature vector using a support vector machine (SVM). FL-LWIR specific improvements include elimination of the need for multiple models due to diurnal temperature variation. The improved algorithm is assessed on FL-LWIR and FL-GPR data from recent collections at a US Army test site.

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

    OpenAIRE

    Baljit Singh Mokha; Satish Kumar

    2015-01-01

    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 differ...

  18. 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.

  19. Improvement and development of automatic detection techniques

    International Nuclear Information System (INIS)

    For detection of radiation-induced mutation, establishment of a new sample preparation method and its procedures suitable for its automation is thought to be the key step to improve the detection efficacy and save labor. In this study, an investigation was made on the sensitivity to radiation exposure in respect of the occurrence of chromosomal breakage by high precision chromosome coloring method utilizing FISH. The number of chromosome breakage per cell was determined in chromosome 1, 4, 5, 9, 11 and 13 prepared from an identical sample exposed to three different grays. The breakage number was found to increase linearly as an increase in the amount of chromosomal DNA and hotspots of the radiation-induced breakages tended to concentrate in R band and the position of R band was almost coincident with the sites of chromosomal translocation breakages specific to leukemia, showing a correlation of radiation exposure to leukemia. Chromosome 13, 14 and 15, which were different in band pattern but similar in its length taken from cells exposed to X-ray at 5 Gy were investigated in detail and it was found that the sensitivity of chromosome to radiation was depending on the quantity and the quality of R band in each chromosome. The benefits of this chromosome coloring method for the analysis of chromosome breakage were as follows: when compared with the conventional dicentric method, the kinds of chromosomal abnormalities to be detectable were much more and its detection rate as well as accuracy was higher. In addition, the time required for determination was loess than one tenth of the conventional one. A breakage site was detectable with differences in color tone and thus, any special technique was not necessary. Therefore, the chromosome coloring method by FISH was demonstrated to be much suitable for automatic image analysis by computer. (M.N.)

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

    OpenAIRE

    Ming-Shyan Wang; Seng-Chi Chen; Po-Hsiang Chuang; Shih-Yu Wu; Fu-Shung Hsu

    2015-01-01

    An automatic guided vehicle (AGV) is extensively used for productions in a flexible manufacture system with high efficiency and high flexibility. A servomotor-based AGV is designed and implemented in this paper. In order to steer the AGV to go along a predefined path with corner or arc, the conventional proportional-integral-derivative (PID) control is used in the system. However, it is difficult to tune PID gains at various conditions. As a result, the neural network (NN) control is consider...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Development of automatic reactor internal vibration monitoring system using fuzzy peak detection and vibration mode decision method

    International Nuclear Information System (INIS)

    In this work a method to detect the vibrational peak and to decide the vibrational mode of detected peak for internal vibration monitoring system which is particularly concerned on the core support barrel (CSB) and fuel assemblies is developed. Flow induced vibration and aging process in the reactor internals cause unsoundness of the internal structure. In order to monitor the vibrational status of core internal, signals from the ex-core neutron detectors are transformed into frequency domain. By analyzing transformed frequency domain signal, an analyst can acquire the information on the vibrational characteristics of the structure, i.e., vibration frequencies of each component, vibrational level, modes of vibration, and the causes of the abnormal vibration, if any. This study is focused on the development of the automated monitoring system. Several methods are surveyed to define the peaks in power spectrum and fuzzy theory is used to automatic detection of the vibrational peaks. Fuzzy algorithm is adopted to define the modes of vibration using the peak values from fuzzy peak recognition, phase spectrum, and coherence spectrum. (author)

  6. 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

  7. Vehicle Detection and Tracking Techniques : A Concise Review

    Directory of Open Access Journals (Sweden)

    Raad Ahmed Hadi

    2014-02-01

    Full Text Available Vehicle detection and tracking applications play an important role for civilian and military applications such as in highway traffic surveillance control, management and urban traffic planning. Vehicle detection process on road are used for vehicle tracking, counts, average speed of each individual vehicle, traffic analysis and vehicle categorizing objectives and may be implemented under different environments changes. In this review, we present a concise overview of image processing methods and analysis tools which used in building these previous mentioned applications that involved developing traffic surveillance systems. More precisely and in contrast with other reviews, we classified the processing methods under three categories for more clarification to explain the traffic systems.

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

    Directory of Open Access Journals (Sweden)

    Yang-Lang Chang

    2011-07-01

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

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

    Science.gov (United States)

    Grymin, David J.

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

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

    OpenAIRE

    Farid Andhika; Trika Pitana; Achmad Affandi

    2012-01-01

    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 sehin...

  11. 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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    ThetKoKo

    2015-07-01

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

  14. 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...

  15. 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.

  16. 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.

  17. 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.

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

    International Nuclear Information System (INIS)

    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

  19. 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

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

    Czech Academy of Sciences Publication Activity Database

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

    2016-01-01

    Roč. 67, č. 1 (2016), s. 36-41. ISSN 1335-3632 R&D Projects: GA ČR(CZ) GAP209/12/2440; GA ČR(CZ) GA15-24688S Institutional support: RVO:68378289 Keywords : power spectral density (PSD) * FMICW radar * Doppler measurement * thresholding * false alert detection Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.378, year: 2014 http://iris.elf.stuba.sk/JEEEC/data/pdf/1_116-05.pdf

  1. 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.

  2. 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...

  3. Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina.

    Science.gov (United States)

    Vibert, Jean-François; Valleron, Alain-jacques

    2003-01-01

    The incidence of breast cancer in France is roughly 26,000 and the annual number of deaths is 11,000. The mammography is the choice examination for the early identification of the tumours in an asymptomatic population. This is a simple, reliable, inexpensive examination, allowing to identify a grave and frequent pathology, but that can be the object of an effective treatment if early detected. The recognition of the microcalcifications in the mammographies is the key for early detection of cancers. Automatic detection methods were already proposed, but they have a very weak specificity and a relatively low sensibility. Currently, the eye of the expert still remains the better judge. We propose a neuromimetic method to localize automatically the microcalcifications. In this method, we devise a network of formal neurones inspired from the mammal retina architecture. This model mimics one characteristic of the retina which is is a sensor that automatically adapts to the image characteristics to analyse and realize the outlines extraction and adaptative filtering of the pictures, based on its network properties. The results were tested using a public standardized data set (DDSM), which was designed to test the automatic detection methods. We show that our "retina" can extracts most of the microcalcifications that can be grouped together in clusters. While we achieve a 95% sensitivity, we must acknowledge a low specificity (22%). Current efforts will focus to enhance this latter parameter. PMID:14664051

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

    OpenAIRE

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

    2010-01-01

    A traffic information unit (MD1, MD2, MD3) according to the invention comprises a facility (MI) for tracking vehicle state information of individual vehicles present at a traffic infrastructure and a facility (T) for transmitting said vehicle state information to a vehicle (70B, 70E). A traffic information system may comprise a plurality of these traffic information units. The invention further comprises a vehicle management system (C) for a target vehicle (70B, 70E) that is capable of receiv...

  5. 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.

  6. Visual Vehicle Identification Using Modern Smart Glasses

    OpenAIRE

    Malmgren, Andreas

    2015-01-01

    In recent years wearable devices have been advancing at a rapid pace and one of the largest growing segments is the smart glass segment. In this thesis the feasibility of today’s ARM-based smart glasses are evaluated for automatic license plate recognition (ALPR). The license plate is by far the most prominent visual feature to identify a spe- cific vehicle, and exists on both old and newly produced vehicles. This thesis propose an ALPR system based on a sequence of vertical edge detection, a...

  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. 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.

  9. 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…

  10. 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

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

    Directory of Open Access Journals (Sweden)

    Zutao Zhang

    2016-02-01

    Full Text Available 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.

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

    Science.gov (United States)

    Moncayo, Hever Y.

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

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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).

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Fault Detection of Railway Vehicle Suspension Systems Using Multiple-Model Approach

    Science.gov (United States)

    Hayashi, Yusuke; Tsunashima, Hitoshi; Marumo, Yoshitaka

    This paper demonstrates the possibility to detect suspension failures of railway vehicles using a multiple-model approach from on-board measurement data. The railway vehicle model used includes the lateral and yaw motions of the wheelsets and bogie, and the lateral motion of the vehicle body, with sensors measuring the lateral acceleration and yaw rate of the bogie, and lateral acceleration of the body. The detection algorithm is formulated based on the Interacting Multiple-Model (IMM) algorithm. The IMM method has been applied for detecting faults in vehicle suspension systems in a simulation study. The mode probabilities and states of vehicle suspension systems are estimated based on a Kalman Filter (KF). This algorithm is evaluated in simulation examples. Simulation results indicate that the algorithm effectively detects on-board faults of railway vehicle suspension systems.

  3. 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...

  4. 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...

  5. Reactor protection system with automatic self-testing and diagnostic

    International Nuclear Information System (INIS)

    A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ''identical'' values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs

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

    OpenAIRE

    Jose María Armingol; Arturo de la Escalera

    2010-01-01

    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 ana...

  7. 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

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Ming-Shyan Wang

    2015-01-01

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

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

    Science.gov (United States)

    Marchetti, E.; Ripepe, M.; Ulivieri, G.; Kogelnig, A.

    2015-11-01

    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 to identify clear signals related to avalanches. We present here a method based on the analysis of infrasound signals recorded by a small aperture array in Ischgl (Austria), which provides a significant improvement to overcome 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 by considering avalanches as a moving source of infrasound. We validate the efficiency of the automatic infrasound detection with continuous observations with Doppler radar and we show how 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 is able to provide the number and the time of occurrence of snow avalanches occurring all around the array, which represent key information for a proper validation of avalanche forecast models and risk management in a given area.

  11. 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%.

  12. 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

  13. 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.

  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. Automatic modal identification of cable-supported bridges instrumented with a long-term monitoring system

    Science.gov (United States)

    Ni, Y. Q.; Fan, K. Q.; Zheng, G.; Chan, T. H. T.; Ko, J. M.

    2003-08-01

    An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm to identify modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers deployed on the cable-stayed Ting Kau Bridge. With the continuously identified results, normal variability of modal vectors caused by varying environmental and operational conditions is observed. Such observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring applications.

  16. Aerial Radiation Detection Vehicle Manned and Unmanned Concepts

    International Nuclear Information System (INIS)

    We are developing an Unmanned Aerial Radiation Detection Vehicle that will give new abilities to the Manned Aerial Radiation Detection Vehicle, Air-Ram. A comparison between the two systems will be given, and a report to our first Unmanned Aerial Radiation Detection Vehicle flight. Air-Ram The Air-Ram system, figure 1, has been developed to measure and display online radiation level measurements taken above the radiation area with a chopper. The detected radiation levels are presented on a topographical map with the flight path colored with the radiation intensities. The air crew and controllers on the ground are updated every two seconds. It enables first responders to complete and real time picture of a radiological event which is essential in order to be able to activate and direct ground operations if necessary. The system measures radiation levels and produces a spectrum graph used to identify the isotopes

  17. Search and decoy: the automatic identification of mass spectra.

    Science.gov (United States)

    Eisenacher, Martin; Kohl, Michael; Turewicz, Michael; Koch, Markus-Hermann; Uszkoreit, Julian; Stephan, Christian

    2012-01-01

    In recent years, the generation and interpretation of MS/MS spectra for the identification of peptides and proteins has matured to a frequently used automatic workflow in Proteomics. Several software solutions for the automated analysis of MS/MS spectra allow for high-throughput/high-performance analyses of complex samples. Related to MS/MS searches, target-decoy approaches have gained more and more popularity: in a "decoy" part of the search database nonexistent sequences mimic real sequences (the "target" sequences). With their help, the number of falsely identified peptides/proteins can be estimated after a search and the resulting protein list can be cut at a specified false discovery rate (FDR). This is an essential prerequisite for all quantitative approaches, as they rely on correct identifications. Especially the label-free approach "spectral counting"-gaining more and more popularity due to low costs and simplicity-depends directly on the correctness of peptide-spectrum matches (PSMs). This work's aim is to describe five popular search engines-especially their general properties regarding protein identification, but also their quantification abilities, if those go beyond spectral counting. By doing so, Proteomics researchers are enabled to compare their features and to choose an appropriate solution for their specific question. Furthermore, the search engines are applied to a spectrum data set generated from a complex sample with a Thermo LTQ Velos OrbiTrap (Thermo Fisher Scientific, Waltham, MA, USA). The results of the search engines are compared, e.g., regarding time requirements, peptides and proteins found, and the search engines' behavior using the decoy approach. PMID:22665317

  18. 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...

  19. A Hessian-based methodology for automatic surface crack detection and classification from pavement images

    Science.gov (United States)

    Ghanta, Sindhu; Shahini Shamsabadi, Salar; Dy, Jennifer; Wang, Ming; Birken, Ralf

    2015-04-01

    Around 3,000,000 million vehicle miles are annually traveled utilizing the US transportation systems alone. In addition to the road traffic safety, maintaining the road infrastructure in a sound condition promotes a more productive and competitive economy. Due to the significant amounts of financial and human resources required to detect surface cracks by visual inspection, detection of these surface defects are often delayed resulting in deferred maintenance operations. This paper introduces an automatic system for acquisition, detection, classification, and evaluation of pavement surface cracks by unsupervised analysis of images collected from a camera mounted on the rear of a moving vehicle. A Hessian-based multi-scale filter has been utilized to detect ridges in these images at various scales. Post-processing on the extracted features has been implemented to produce statistics of length, width, and area covered by cracks, which are crucial for roadway agencies to assess pavement quality. This process has been realized on three sets of roads with different pavement conditions in the city of Brockton, MA. A ground truth dataset labeled manually is made available to evaluate this algorithm and results rendered more than 90% segmentation accuracy demonstrating the feasibility of employing this approach at a larger scale.

  20. 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.

  1. Characterization of Airborne Bacteria at a Subway Station: Implications for Testing and Evaluation of Biological Detection, Identification, and Monitoring Systems

    OpenAIRE

    Dybwad, Marius

    2014-01-01

    Biological detection, identification, and monitoring (BioDIM) systems that are able to provide rapid and reliable early-warning in the event of a bioterrorism attack may contribute to reduce the impact of such incidents. Currently, few if any available BioDIM systems have been able to meet all the users’ requirements with respect to reliable, sensitive, and selective detect-towarn capabilities in different operational environments. BioDIM efforts at most real life sites must be accomplished a...

  2. 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...

  3. 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.

  4. 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...

  5. 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 ...

  6. 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)

  7. Principal Component Analysis and Automatic Relevance Determination in Damage Identification

    CERN Document Server

    Mdlazi, L; Stander, C J; Scheffer, C; Heyns, P S

    2007-01-01

    This paper compares two neural network input selection schemes, the Principal Component Analysis (PCA) and the Automatic Relevance Determination (ARD) based on Mac-Kay's evidence framework. The PCA takes all the input data and projects it onto a lower dimension space, thereby reduc-ing the dimension of the input space. This input reduction method often results with parameters that have significant influence on the dynamics of the data being diluted by those that do not influence the dynamics of the data. The ARD selects the most relevant input parameters and discards those that do not contribute significantly to the dynamics of the data being modelled. The ARD sometimes results with important input parameters being discarded thereby compromising the dynamics of the data. The PCA and ARD methods are implemented together with a Multi-Layer-Perceptron (MLP) network for fault identification in structures and the performance of the two methods is as-sessed. It is observed that ARD and PCA give similar accu-racy le...

  8. The development of automatic detection monitoring system for thermal failure part by infrared thermal vision camera

    International Nuclear Information System (INIS)

    The most part of various electric has been affected by thermal failure due to electric overload. Contact-sensor has been used, for detection to this thermal failure, until now. But, it is impossible to detect the unsuitable element by using contact-temperature-sensor. This problem, with development of the infrared thermal vision camera, will be solved. Because it take some advantages which are composed of non-contact detect and non-destructive detect for temperature distribution, it is possible to detect on the temperature of revolution part, high temperature part. We developed the automatic detection monitoring system for thermal failure part on electric with overload by using the infrared thermal vision camera. The first stage, thermal signal was detected from the infrared thermal vision camera, and then the data that was wanted from user was shown. The second stage, if the temperature that was decided to failure coded to the program, automatically electric was shut off, This monitoring system is possible to apply on various conveniences in the whole industrial sites.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Upgrade of the Automatic Analysis System in the TJ-II Thomson Scattering Diagnostic: New Image Recognition Classifier and Fault Condition Detection

    International Nuclear Information System (INIS)

    Full text of publication follows: An automatic image classification system has been in operation for years in the TJ-II Thomson diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge, image during ECH phase, image during NBI phase and image after reaching the cut o density during ECH heating. Each kind of image implies the execution of different application software. Therefore, the classification system was developed to launch the corresponding software in an automatic way. The method to recognize the several classes was based on a learning system, in particular Support Vector Machines (SVM). Since the first implementation of the classifier, a relevant improvement has been accomplished in the diagnostic: a new notch filter is in operation, having a larger stray-light rejection at the ruby wavelength than the previous filter. On the other hand, its location in the optical system has been modified. As a consequence, the stray light pattern in the CCD image is located in a different position. In addition to these transformations, the power of neutral beams injected in the TJ-II plasma has been increased about a factor of 2. Due to the fact that the recognition system is based on a learning system and major modifications have been carried out in both the diagnostic (optics) and TJ-II plasmas (injected power), the classifier model is no longer valid. The creation of a new model (also based on SVM) under the present conditions has been necessary. Finally, specific error conditions in the data acquisition process can automatically be detected now. The recovering process can be automated, thereby avoiding the loss of data in ensuing discharges. (authors)

  15. 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...

  16. Automatic Registration and Error Detection of Multiple Slices Using Landmarks

    OpenAIRE

    Frimmel, Hans; Egevad, Lars; Busch, Christer; Bengtsson, Ewert

    2001-01-01

    Objectives. When analysing the 3D structure of tissue, serial sectioning and staining of the resulting slices is sometimes the preferred option. This leads to severe registration problems. In this paper, a method for automatic registration and error detection of slices using landmark needles has been developed. A cost function takes some parameters from the current state of the problem to be solved as input and gives a quality of the current solution as output. The cost function used in this ...

  17. Determination of free and total sulfites in wine using an automatic flow injection analysis system with voltammetric detection.

    Science.gov (United States)

    Goncalves, Luis Moreira; Grosso Pacheco, Joao; Jorge Magalhaes, Paulo; Antonio Rodrigues, Jose; Araujo Barros, Aquiles

    2010-02-01

    An automated flow injection analysis (FIA) system, based on an initial analyte separation by gas-diffusion and subsequent determination by square-wave voltammetry (SWV) in a flow cell, was developed for the determination of total and free sulfur dioxide (SO(2)) in wine. The proposed method was compared with two iodometric methodologies (the Ripper method and a simplified method commonly used by the wine industry). The developed method displayed good repeatability (RSD lower than 6%) and linearity (between 10 and 250 mg l(-1)) as well as a suitable LOD (3 mg l(-1)) and LOQ (9 mg l(-1)). A major advantage of this system is that SO(2) is directly detected by flow SWV. PMID:20013444

  18. 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.

  19. 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

  20. 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 ...

  1. 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.

  2. 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

  3. 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.

  4. 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...

  5. 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.)

  6. A Survey on Automatic Vehicle Parking and Retrieval Using Android Smartphone

    Directory of Open Access Journals (Sweden)

    Arockia Muthu.A*

    2014-11-01

    Full Text Available This paper focuses the construction of the system which assists in parking and retrieving of the car automatically. Unlike previous generation this system drives automatically while parking which is controlled with the help of smart phone. Remote door control is another feature that helps the user to open the car door with aid of smart phone. The system is equipped with an alarm system in case of disturbance situation. The proposed system uses a 3-axis accelerometer which replaces the motion sensor in the existing system and provides a secure means of parking system. This system is going to be implemented using ARM cortex-M3 microcontroller.

  7. 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.

  8. 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.

  9. 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...

  10. 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。

  11. 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.

  12. 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.

  13. 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...

  14. 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.

  15. 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...

  16. Automatic laser tracking and ranging system.

    Science.gov (United States)

    Cooke, C R

    1972-02-01

    An automatic laser tracking and ranging system has been developed for use with cooperative retroreflective targets. Target position is determined with high precision at ranges out to 19 km and sample rates up to one hundred measurements per second. The data are recorded on a magnetic tape in the form of azimuth, elevation, range, and standard time and are computer-compatible. The system is fully automatic with the exception of the initial acquisition sequence, which is performed manually. This eliminates the need for expensive and time-consuming photographic data reduction. Also, position is uniquely determined by a single instrument. To provide convenient operation at remote sites, the system is van-mounted and operates off a portable power generator. The transmitter is a flash-pumped Q-spoiled Nd:YAG laser developing 1 MW peak power in a 10-mrad beam at a rate of 100 pps. The beam, which is coaxial with the receiver, is directed to the target by an azimuth-elevation mirror mount. The return beam is imaged o separate ranging and tracking receivers. The ranging receiver measures time of flight of the 25-nsec laser pulse with range accuracies of +/-15 cm. The tracking receiver uses a quadrant photodiode followed by matched log video amplifiers and achieves a tracking accuracy of +/-0.1 mrad. An optical dynamic range of 30 dB is provided to minimize error due to scintillation. Also, 80 dB of optical dynamic range is provided by adjustable neutral density filters to compensate for changes in target range. PMID:20111495

  17. 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.

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

    Science.gov (United States)

    McIntosh, Dawn

    2006-01-01

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

  19. 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.

  20. 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

  1. Preliminary results of a lidar-dial integrated system for the automatic detection of atmospheric pollutants

    Science.gov (United States)

    Gaudio, P.; Gelfusa, M.; Richetta, M.

    2012-11-01

    In the last decades, atmospheric pollution in urban and industrial areas has become a major concern of both developed and developing countries. In this context, surveying relative large areas in an automatic way is an increasing common objective of public health organisations. The Lidar-Dial techniques are widely recognized as a cost-effective approach to monitor large portions of the atmosphere and, for example, they have been successful applied to the early detection of forest fire. The studies and preliminary results reported in this paper concern the development of an integrated Lidar-Dial system able to detect sudden releases in air of harmful and polluting substances. The propose approach consists of continuous monitoring of the area under surveillance with a Lidar type measurement (by means of a low cost system). Once a significant increase in the density of a pollutant is revealed, the Dial technique is used to identify the released chemicals. In this paper, the specifications of the proposed station are discussed. The most stringent requirement is the need for a very compact system with a range of at least 600-700 m. Of course, the optical wavelengths must be in an absolute eye-safe range for humans. A conceptual design of the entire system is described and the most important characteristic of the main elements are provided. In particular the capability of the envisaged laser sources, Nd:YAG and CO2 lasers, to provide the necessary quality of the measurements is carefully assessed. Since the detection of dangerous substances must be performed in an automatic way, the monitoring station will be equipped with an adequate set of control and communication devices for independent autonomous operation. The results of the first preliminary tests illustrate the potential of the chosen approach.

  2. Identification of Car Passengers with RFID for Automatic Crash Notification

    OpenAIRE

    Ouyang, Dongfang

    2009-01-01

    Automatic Crash Notification is a system designed to be used in a crash situation. When a crash occurs, the intelligent system is activated and automatically sends select crash details to the appropriate Emergency Medical Service Center. These details can be the position of the vehicle and the likely severity of the damage. Using the information, the medical treatment resources demanded for the accident is assessed at Emergency Center. Accordingly, first-aid facilities are promptly and proper...

  3. 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

  4. A vehicle photoelectric detection system based on guidance of machine vision

    Science.gov (United States)

    Wang, Yawei; Liu, Yu; Chen, Wei; Chen, Jing; Guo, Jia; Zhou, Lijun; Zheng, Haotian; Zhang, Xuantao

    2015-04-01

    A vehicle photoelectric detection system based on guidance of machine vision is described in detail, which is composed of electric-optic turret, distributed perception module, position orientation system and data process terminal, etc. Simultaneously, a target detection method used in the system based on visual guide is also discussed in this paper. This method, based on the initial alignment of camera position and the precise alignment of target location, realizes the target acquisition and measurement by using the high-definition cameras of distributed perception module installed around the vehicle as the human eyes to guide the line of sight of optoelectronic devices on the turret to the field of view of one camera quickly and carry on small-scale target alignment operations. Simulation results show that the method could achieve the intelligent dynamic guide of photoelectric detection system, and improve the detection efficiency and accuracy.

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

    Science.gov (United States)

    Su, Jie; Xu, Xuan; He, Yongjun; Song, Jinming

    2016-01-01

    We proposed a method for automatic detection of cervical cancer cells in images captured from thin liquid based cytology slides. We selected 20,000 cells in images derived from 120 different thin liquid based cytology slides, which include 5000 epithelial cells (normal 2500, abnormal 2500), lymphoid cells, neutrophils, and junk cells. We first proposed 28 features, including 20 morphologic features and 8 texture features, based on the characteristics of each cell type. We then used a two-level cascade integration system of two classifiers to classify the cervical cells into normal and abnormal epithelial cells. The results showed that the recognition rates for abnormal cervical epithelial cells were 92.7% and 93.2%, respectively, when C4.5 classifier or LR (LR: logical regression) classifier was used individually; while the recognition rate was significantly higher (95.642%) when our two-level cascade integrated classifier system was used. The false negative rate and false positive rate (both 1.44%) of the proposed automatic two-level cascade classification system are also much lower than those of traditional Pap smear review. PMID:27298758

  6. 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.

  7. 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.

  8. Map++: A Crowd-sensing System for Automatic Map Semantics Identification

    OpenAIRE

    Aly, Heba; Basalamah, Anas; Youssef, Moustafa

    2015-01-01

    Digital maps have become a part of our daily life with a number of commercial and free map services. These services have still a huge potential for enhancement with rich semantic information to support a large class of mapping applications. In this paper, we present Map++, a system that leverages standard cell-phone sensors in a crowdsensing approach to automatically enrich digital maps with different road semantics like tunnels, bumps, bridges, footbridges, crosswalks, road capacity, among o...

  9. 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.

  10. 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.

  11. 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.

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

    Science.gov (United States)

    Zichner, Ralf; Baumann, Reinhard R.

    2013-05-01

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

  13. 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.

  14. 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

  15. 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...

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

    Science.gov (United States)

    Witkin, S. A.

    1976-01-01

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

  17. Automatic Aircraft Collision Avoidance System and Method

    Science.gov (United States)

    Skoog, Mark (Inventor); Hook, Loyd (Inventor); McWherter, Shaun (Inventor); Willhite, Jaimie (Inventor)

    2014-01-01

    The invention is a system and method of compressing a DTM to be used in an Auto-GCAS system using a semi-regular geometric compression algorithm. In general, the invention operates by first selecting the boundaries of the three dimensional map to be compressed and dividing the three dimensional map data into regular areas. Next, a type of free-edged, flat geometric surface is selected which will be used to approximate terrain data of the three dimensional map data. The flat geometric surface is used to approximate terrain data for each regular area. The approximations are checked to determine if they fall within selected tolerances. If the approximation for a specific regular area is within specified tolerance, the data is saved for that specific regular area. If the approximation for a specific area falls outside the specified tolerances, the regular area is divided and a flat geometric surface approximation is made for each of the divided areas. This process is recursively repeated until all of the regular areas are approximated by flat geometric surfaces. Finally, the compressed three dimensional map data is provided to the automatic ground collision system for an aircraft.

  18. 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. .

  19. 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.

  20. 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...

  1. 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 ...

  2. 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...

  3. 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.

  4. Automatic age-related macular degeneration detection and staging

    Science.gov (United States)

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

    2013-03-01

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

  5. 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.

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

    OpenAIRE

    Ramani, R.; Valarmathy, S.; N. Suthanthiravanitha; S.Selvaraju; M.Thiruppathi; R.Thangam

    2013-01-01

    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....

  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. 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.

  10. An affordable modular vehicle radar for landmine and IED detection

    Science.gov (United States)

    Daniels, David; Curtis, Paul; Dittmer, Jon; Hunt, Nigel; Graham, Blair; Allan, Robert

    2009-05-01

    This paper describes a vehicle mounted 8-channel radar system suitable for buried landmine and IED detection. The system is designed to find Anti Tank (AT) landmines and buried Improvised Explosive Devices (IEDs). The radar uses field-proven ground penetrating radar sub-system modules and is scalable to 16, 32 or 64 channels, for covering greater swathe widths and for providing higher cross track resolution. This offers the capability of detecting smaller targets down to a minimum dimension of 100mm. The current rate of advance of the technology demonstrator is 10 kph; this can be increased to 20 kph where required. The data output is triggered via shaft encoder or via GPS and, for each forward increment; the data output is variable from a single byte per channel through to the 512 samples per channel. Trials using an autonomous vehicle, combined with a COFDM wireless link for data and telemetry back to a base station, have proven successful and the system architecture is described in this paper. The GPR array can be used as a standalone sensor or can be integrated with off-the-shelf software and a metal detection array.

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

    International Nuclear Information System (INIS)

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

  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. 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

  14. 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

  15. 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

  16. 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.

  17. A detection system with broad angular acceptance for particle identification and angular distribution measurements

    International Nuclear Information System (INIS)

    A new detection system for time-optimized heavy-ion angular distribution measurements has been designed and constructed. This device is composed by an ionization chamber with a segmented-grid anode and three position-sensitive silicon detectors. This particular arrangement allows identifying reaction products emitted within a 30° wide angular range with better than 1° angular resolution. As a demonstration of its capabilities, angular distributions of the elastic scattering cross-section and the production of alpha particles in the 7Li+27Al system, at an energy above the Coulomb barrier, are presented. -- Highlights: • We constructed a detection system for time-optimized heavy-ion angular distribution measurements. • We characterized this device and obtained an energy resolution of 3% and an angular resolution of 1°. • We measured elastic scattering cross-sections in 7Li+27Al finding good agreement with previous data. • The performed tests included the measurement of alpha particle production cross-sections in 7Li+27Al

  18. 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.

  19. 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

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

    OpenAIRE

    Jia Wei Tang; Nasir Shaikh-Husin; Usman Ullah Sheikh; M. N. Marsono

    2016-01-01

    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 de...

  1. 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.

  2. 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...

  3. 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

    measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet packet transformation (WPT). Based on the extracted features all data segments were classified using a support vector machine (SVM) algorithm as simulated seizure or normal activity. A case study of the...

  4. 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.

  5. 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. ...

  6. 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.

  7. 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

  8. 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 ...

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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...

  14. 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.

  15. Automatic detection of abnormalities in mammograms

    OpenAIRE

    Suhail, Zobia; Sarwar, Mansoor; Murtaza, Kashif

    2015-01-01

    Background In recent years, an increased interest has been seen in the area of medical image processing and, as a consequence, Computer Aided Diagnostic (CAD) systems. The basic purpose of CAD systems is to assist doctors in the process of diagnosis. CAD systems, however, are quite expensive, especially, in most of the developing countries. Our focus is on developing a low-cost CAD system. Today, most of the CAD systems regarding mammogram classification target automatic detection of calcific...

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

    Science.gov (United States)

    Bengler, Klaus; Kohlmann, Martin; Lange, Christian

    2012-01-01

    The increase of driver information and infotainment systems includes also interaction technologies like speech interaction that minimize visual-manual demand and put the focus to cognitive demand. The question is whether this could lead to distraction effects and decreased traffic safety. This study presents an evaluation method for cognitive demand based on different detection paradigms in a dual task setting. A listening and a backward counting task are realized on three difficulty levels as simulations of cognitively loading secondary tasks and investigated using a visual versus a tactile detection paradigm. The results show that both detection paradigms are able to discriminate the task levels and that subjects successfully apply compensation strategies in the dual task setting especially during the listening task. PMID:22317480

  17. Diagnostics of machines and structures: dynamic identification and damage detection

    OpenAIRE

    Gandino, Edoardo

    2013-01-01

    This research work deals with damage detection of engineering machines and structures. This topic, developed in particular for bearing diagnostics in the first part of the work, is strictly related to dynamic identification when structures are considered. Thus, subspace-based methods are investigated in the second part of the work, with particular attention to nonlinear system identification. Changes in operational and environmental conditions for structures (such as air temperature, temperat...

  18. 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.

  19. 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.

  20. Multi-sensorial collision prevention system for bidirectional identification of accident risks by vehicles in open-cast and deep mines; Integriertes Konzept zur Kollisionsvermeidung zwischen Personen und Fahrzeugen im Untertagebergbau

    Energy Technology Data Exchange (ETDEWEB)

    Becker, Franz; Becker, Stephan [Becker Mining Systems AG, Friedrichsthal (Germany)

    2011-01-15

    On the basis of the gradual exhaustion of the deposits near the surface there is evidence of a clear trend from open-cast to deep mining and thus to workings under difficult geological conditions. Because of the extensive underground road networks in high-output mines and the modern working methods trackless vehicles and mobile equipment are being used to an increasing extent. Many vehicles and personnel are en route at the same time in these road networks, so that collisions with each other or accidents involving persons must be anticipated. Becker Mining Systems has successfully developed a multisensorial collision prevention system for bidirectional identification of accident risks by vehicles in open-cast and deep mines. (orig.)

  1. 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...

  2. 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.

  3. Vehicle License Plate Recognition System

    Directory of Open Access Journals (Sweden)

    Meenakshi

    2012-12-01

    Full Text Available The vehicle license plate recognition system has greater efficiency for vehicle monitoring in automatic zone access control. This Plate recognition system will avoid special tags, since all vehicles possess a unique registration number plate. A number of techniques have been used for car plate characters recognition. This system uses neural network character recognition and pattern matching of characters as two character recognition techniques. In this approach multilayer feed-forward back-propagation algorithm is used. The performance of the proposed algorithm has been tested on several car plates and provides very satisfactory results.

  4. Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

    OpenAIRE

    Pastell, Matti

    2007-01-01

    The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feedi...

  5. Detection and tracking of overtaking vehicles

    OpenAIRE

    Hultqvist, Daniel

    2013-01-01

    The car has become bigger, faster and more advanced for each passing year since its first appearance, and the safety requirements have also become stricter. Computer vision based support is a growing area of safety features where the car is equipped with a mono- or stereo camera. It can be used for detecting pedestrians walking out in the street, give a warning for wild-life during a cold January night using night-vision cameras and much more. This master thesis investigates the problem of d...

  6. 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.

  7. 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.

  8. Identification time constants of the synchronous machine in high reliability power supply systems in Kozloduy NPP for mathematical modeling of automatical control system

    International Nuclear Information System (INIS)

    This article presents the results of subjects identification, for following of creating base models in Simulink (included in Matlab5.3) of automatic control system, synchronous generator and motor. The method for timing rows analysis is used the received third line contains the machine's time constants: d axis transient short - circuit time constant Td' and consist of mechanical parameters, initial conditions and saturation parameters. The results of research allow creating models of type 'machine-regulator', for analysis in Simulink to Matlab identically by specification objects. (authors)

  9. 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.

  10. 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

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

    Science.gov (United States)

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

    2015-05-01

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

  12. Discovery of mass spectral characteristics and automatic identification of wax esters from gas chromatography mass spectrometry data.

    Science.gov (United States)

    Zhang, Liang-xiao; Yun, Yi-feng; Liang, Yi-zeng; Cao, Dong-sheng

    2010-06-01

    The mass spectral characteristics of wax esters were systemically summarized and interpreted through data mining of their standard mass spectra taken from NIST standard mass spectral library. Combining with the rules of retention indices described in the previous study, an automatic system was subsequently developed to identify the structural information for wax esters from GC/MS data. After tested and illustrated by both simulated and real GC/MS data, the results indicate that this system could identify wax esters except the polyunsaturated ones and the mass spectral characteristics are useful and effective information for identification of wax esters. PMID:20417935

  13. 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.

  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. 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.

  16. Mathematical modelling and quality indices optimization of automatic control systems of reactor facility

    International Nuclear Information System (INIS)

    The mathematical modeling of automatic control systems of reactor facility WWER-1000 with various regulator types is considered. The linear and nonlinear models of neutron power control systems of nuclear reactor WWER-1000 with various group numbers of delayed neutrons are designed. The results of optimization of direct quality indexes of neutron power control systems of nuclear reactor WWER-1000 are designed. The identification and optimization of level control systems with various regulator types of steam generator are executed

  17. Automatic firewall rules generator for anomaly detection systems with Apriori algorithm

    OpenAIRE

    Saboori, Ehsan; Parsazad, Shafigh; Sanatkhani, Yasaman

    2012-01-01

    Network intrusion detection systems have become a crucial issue for computer systems security infrastructures. Different methods and algorithms are developed and proposed in recent years to improve intrusion detection systems. The most important issue in current systems is that they are poor at detecting novel anomaly attacks. These kinds of attacks refer to any action that significantly deviates from the normal behaviour which is considered intrusion. This paper proposed a model to improve t...

  18. Automatic Management of Parallel and Distributed System Resources

    Science.gov (United States)

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

    1990-01-01

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

  19. Systems Engineering of Electric and Hybrid Vehicles

    Science.gov (United States)

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

    1986-01-01

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

  20. 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.

  1. Development of Automatic 3D Blood Vessel Search and Automatic Blood Sampling System by Using Hybrid Stereo-Autofocus Method

    OpenAIRE

    Eiji Nakamachi; Yusuke Morita; Yoshifumi Mizuno

    2012-01-01

    We developed an accurate three-dimensional blood vessel search (3D BVS) system and an automatic blood sampling system. They were implemented into a point-of-care system designed for medical care, installed in a portable self-monitoring blood glucose (SMBG) device. The system solves problems of human error caused by complicated manual operations of conventional SMBG devices. We evaluated its accuracy of blood-vessel position detection. The 3D BVS system uses near-infrared (NIR) light imaging a...

  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. System Identification and Robust Control

    DEFF Research Database (Denmark)

    Tøffner-Clausen, S.

    uncertainty structures permitted by m is definitely much more flexible than those used in H inifity. Unfortunately m synthesis is a very difficult mathematical problem which is only well developed for purely complex perturbation sets. In order to develop our main result we will unfortunately need to...... these uncertainty ellipses may be represented or, more correct, approximated with a mixed complex and real perturbation set. This is the link needed to combine the results in robust control and system identification into a step-by-step design philosophy for synthesis of robust control systems for scalar......The main purpose of this work is to develop a coherent system identification based robust control design methodology by combining recent results from system identification and robust control. In order to accomplish this task new theoretical results will be given in both fields. Firstly, however, an...

  4. 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)

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Automatic Speaker Recognition System

    Directory of Open Access Journals (Sweden)

    Parul,R. B. Dubey

    2012-12-01

    Full Text Available Spoken language is used by human to convey many types of information. Primarily, speech convey message via words. Owing to advanced speech technologies, people's interactions with remote machines, such as phone banking, internet browsing, and secured information retrieval by voice, is becoming popular today. Speaker verification and speaker identification are important for authentication and verification in security purpose. Speaker identification methods can be divided into text independent and text-dependent. Speaker recognition is the process of automatically recognizing speaker voice on the basis of individual information included in the input speech waves. It consists of comparing a speech signal from an unknown speaker to a set of stored data of known speakers. This process recognizes who has spoken by matching input signal with pre- stored samples. The work is focussed to improve the performance of the speaker verification under noisy conditions.

  10. 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...

  11. Detection and identification of unexploded ordnance (UXO) by neutron interrogation

    International Nuclear Information System (INIS)

    This document reviews the principle of operation and unexploded ordnance (UXO) signatures of the PINS Chemical Assay System, a prompt-gamma-ray neutron activation analysis (PGNAA) for the identification of recovered UXO. Two related low cost methods for buried landmine detection are also suggested. Nuclear methods may compliment existing search techniques to improve the overall probability of detection and to reduce the false positive rate of other technologies. In addition, nuclear methods are a proven method for identification of UXO such as landmines

  12. 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...

  13. 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.

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

    KAUST Repository

    Abu Jbara, Khaled F.

    2015-05-01

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

  15. 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)

  16. 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...

  17. 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...

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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。

  5. 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.

  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. Wireless Vehicular Communications for Automatic Incident Detection and Recovery

    OpenAIRE

    Joaquim José Castro Ferreira; José Alberto Gouveia Fonseca; Lopes, Jorge Alves

    2012-01-01

    Incident detection is the process by which an incident is brought to the attention of traffic operators in order to design and activate a response plan. To minimize the detection time is crucial to mitigate the incident severity for victims as well to reduce the risk of secondary crashes. Automated incident information dissemination and traffic conditions is useful to alert in-route drivers to decide alternative routes on unexpected traffic congestion and may be also used for the incident rec...

  8. 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.

  9. 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)

  10. 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.

  11. PCR Based Systems in Rapid Detection and Identification of Biological Agents

    OpenAIRE

    Taleski, Vaso

    2012-01-01

    Of all weapons of mass destruction, biological weapons (BW) today present the greatest danger. A belief that state sponsored armies or terrorist organizations, groups or individuals will use this type of weapon has never been greater which demands a capability for rapid medical response and early intervention. The specter of potential BA is well known and includes: anti-human, anti-plant and anti-animal agents. Unusual outbreaks of illnesses might be essential suspicion in recognizing of deli...

  12. 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...

  13. Automatic intraocular lens segmentation and detection in optical coherence tomography images.

    Science.gov (United States)

    Gillner, Melanie; Eppig, Timo; Langenbucher, Achim

    2014-05-01

    We present a new algorithm for automatic segmentation and detection of an accommodative intraocular lens implanted in a biomechanical eye model. We extracted lens curvature and position. The algorithm contains denoising and fan correction by a multi-level calibration routine. The segmentation is realized by an adapted canny edge detection algorithm followed by a detection of lens surface with an automatic region of interest search to suppress non-optical surfaces like the lens haptic. The optical distortion of lens back surface is corrected by inverse raytracing. Lens geometry was extracted by a spherical fit. We implemented and demonstrated a powerful algorithm for automatic segmentation, detection and surface analysis of intraocular lenses in vitro. The achieved accuracy is within the expected range determined by previous studies. Future improvements will include the transfer to clinical anterior segment OCT devices. PMID:23928353

  14. 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.

  15. An automatic system for measuring road and tunnel lighting performance

    OpenAIRE

    Greffier, Florian; Charbonnier, Pierre; Tarel, Jean-Philippe; Boucher, Vincent; FOURNELA, Fabrice

    2015-01-01

    Various problems in different domains are related to the operation of the Human Visual System (HVS). This is notably the case when considering the driver's visual perception, and road safety in general. That is why several standards of road equipments are directly derived from human visual abilities and especially in road and tunnel lighting installations design. This paper introduces an automatic system for measuring road and tunnel lighting performance. The proposed device is based on an em...

  16. 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, ...

  17. Utilization of advanced clutter suppression algorithms for improved standoff detection and identification of radionuclide threats

    Science.gov (United States)

    Cosofret, Bogdan R.; Shokhirev, Kirill; Mulhall, Phil; Payne, David; Harris, Bernard

    2014-05-01

    Technology development efforts seek to increase the capability of detection systems in low Signal-to-Noise regimes encountered in both portal and urban detection applications. We have recently demonstrated significant performance enhancement in existing Advanced Spectroscopic Portals (ASP), Standoff Radiation Detection Systems (SORDS) and handheld isotope identifiers through the use of new advanced detection and identification algorithms. The Poisson Clutter Split (PCS) algorithm is a novel approach for radiological background estimation that improves the detection and discrimination capability of medium resolution detectors. The algorithm processes energy spectra and performs clutter suppression, yielding de-noised gamma-ray spectra that enable significant enhancements in detection and identification of low activity threats with spectral target recognition algorithms. The performance is achievable at the short integration times (0.5 - 1 second) necessary for operation in a high throughput and dynamic environment. PCS has been integrated with ASP, SORDS and RIID units and evaluated in field trials. We present a quantitative analysis of algorithm performance against data collected by a range of systems in several cluttered environments (urban and containerized) with embedded check sources. We show that the algorithm achieves a high probability of detection/identification with low false alarm rates under low SNR regimes. For example, utilizing only 4 out of 12 NaI detectors currently available within an ASP unit, PCS processing demonstrated Pd,ID > 90% at a CFAR (Constant False Alarm Rate) of 1 in 1000 occupancies against weak activity (7 - 8μCi) and shielded sources traveling through the portal at 30 mph. This vehicle speed is a factor of 6 higher than was previously possible and results in significant increase in system throughput and overall performance.

  18. Improvement and development of techniques for automatic detection of mutation

    International Nuclear Information System (INIS)

    This study was made as a part of ''Developments of techniques for detection and analysis of radiation-induced mutation using new methods for DNA analysis'', 5-year research project started from the fiscal year 1994. The availability of a new detection method using FISH for radiation-induced chromosome aberrations was examined using lymphocytes. Chromosome painting was performed with DNA probes purified from human chromosomes. Thus, estimation of radiated dose was made based on the rate of cleavage in the target chromosome. This method was most effective for analysis of structural changes in chromosome caused by radiation and this is expected to be as a rapid and labor-saving procedure. The present results indicate that this method has a high detectability and a high accuracy. The duration required for microscopic observation was less than one tenth in this method compared with the conventional method. The cleavage frequency was proportional to the chromosome length. The distribution of the cleavages was well coincident with the positions of chromosome translocations specific to leukemia. These results suggest that this detection method for chromosomal cleavages is very useful and convenient for the estimation of radiation dose. (M.N.)

  19. 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.

  20. Automatic Detection and Correction for Glossy Reflections in Digital Photograph

    Directory of Open Access Journals (Sweden)

    Rong-Chi Chang

    2011-04-01

    Full Text Available The popularization of digital technology has made shooting digital photos and using related applications a part of daily life. However, the use of flash, to compensate for low atmospheric lighting, often leads to overexposure or glossy reflections. This study proposes an auto-detection and inpainting technique to correct overexposed faces in digital photography. This algorithm segments the skin color in the photo as well as uses face detection and capturing to determine candidate bright spots on the face. Based on the statistical analysis of color brightness and filtering, the bright spots are identified. Finally, bright spots are corrected through inpainting technology. From the experimental results, this study demonstrates the high accuracy and efficiency of the method.

  1. 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.

  2. 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.

  3. 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

  4. Consistent detection and identification of individuals in a large camera network

    Science.gov (United States)

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

    2007-10-01

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

  5. 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.

  6. 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.

  7. An intelligent system for automatic detection of gastrointestinal adenomas in video endoscopy.

    Science.gov (United States)

    Iakovidis, Dimitris K; Maroulis, Dimitris E; Karkanis, Stavros A

    2006-10-01

    Today 95% of all gastrointestinal carcinomas are believed to arise from adenomas. The early detection of adenomas could prevent their evolution to cancer. A novel system for the support of the detection of adenomas in gastrointestinal video endoscopy is presented. Unlike other systems, it accepts standard low-resolution video input thus requiring less computational resources and facilitating both portability and the potential to be used in telemedicine applications. It combines intelligent processing techniques of SVMs and color-texture analysis methodologies into a sound pattern recognition framework. Concerning the system's accuracy this was measured using ROC analysis and found to exceed 94%. PMID:16293240

  8. 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.

  9. Path selection system simulation and evaluation for a Martian roving vehicle

    Science.gov (United States)

    Frederick, D. K.

    1975-01-01

    A comprehensive digital computer simulation program has been developed for evaluating the path-selection system performance of an autonomous roving vehicle being designed for the exploration of Mars. Vehicle performance over realistic three-dimensional terrains in the presence of random motion disturbances and sensor measurement noise is simulated and plotted on a terrain contour map. In addition, a numerical figure-of-merit is computed automatically for each run.

  10. Automatic quadrature control and measuring system

    Science.gov (United States)

    Hamlet, J. F.

    1973-01-01

    Quadrature is separated from amplified signal by use of phase detector, with phase shifter providing appropriate reference. Output of phase detector is further amplified and filtered by dc amplifier. Output of dc amplifier provides signal to neutralize quadrature component of transducer signal.

  11. Automatic detection of lameness in gestating group-housed sows using positioning and acceleration measurements.

    Science.gov (United States)

    Traulsen, I; Breitenberger, S; Auer, W; Stamer, E; Müller, K; Krieter, J

    2016-06-01

    Lameness is an important issue in group-housed sows. Automatic detection systems are a beneficial diagnostic tool to support management. The aim of the present study was to evaluate data of a positioning system including acceleration measurements to detect lameness in group-housed sows. Data were acquired at the Futterkamp research farm from May 2012 until April 2013. In the gestation unit, 212 group-housed sows were equipped with an ear sensor to sample position and acceleration per sow and second. Three activity indices were calculated per sow and day: path length walked by a sow during the day (Path), number of squares (25×25 cm) visited during the day (Square) and variance of the acceleration measurement during the day (Acc). In addition, data on lameness treatments of the sows and a weekly lameness score were used as reference systems. To determine the influence of a lameness event, all indices were analysed in a linear random regression model. Test day, parity class and day before treatment had a significant influence on all activity indices (P<0.05). In healthy sows, indices Path and Square increased with increasing parity, whereas variance slightly decreased. The indices Path and Square showed a decreasing trend in a 14-day period before a lameness treatment and to a smaller extent before a lameness score of 2 (severe lameness). For the index acceleration, there was no obvious difference between the lame and non-lame periods. In conclusion, positioning and acceleration measurements with ear sensors can be used to describe the activity pattern of sows. However, improvements in sampling rate and analysis techniques should be made for a practical application as an automatic lameness detection system. PMID:27074864

  12. 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

  13. 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.

  14. 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...

  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. 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...

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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.

  2. 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...

  3. 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)

  4. 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 ...

  5. 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)

  6. 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

  7. 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.

  8. 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.

  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. 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)

  12. 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.

  13. 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

  14. Architectural design for a low cost FPGA-based traffic signal detection system in vehicles

    Science.gov (United States)

    López, Ignacio; Salvador, Rubén; Alarcón, Jaime; Moreno, Félix

    2007-05-01

    In this paper we propose an architecture for an embedded traffic signal detection system. Development of Advanced Driver Assistance Systems (ADAS) is one of the major trends of research in automotion nowadays. Examples of past and ongoing projects in the field are CHAMELEON ("Pre-Crash Application all around the vehicle" IST 1999-10108), PREVENT (Preventive and Active Safety Applications, FP6-507075, http://www.prevent-ip.org/) and AVRT in the US (Advanced Vision-Radar Threat Detection (AVRT): A Pre-Crash Detection and Active Safety System). It can be observed a major interest in systems for real-time analysis of complex driving scenarios, evaluating risk and anticipating collisions. The system will use a low cost CCD camera on the dashboard facing the road. The images will be processed by an Altera Cyclone family FPGA. The board does median and Sobel filtering of the incoming frames at PAL rate, and analyzes them for several categories of signals. The result is conveyed to the driver. The scarce resources provided by the hardware require an architecture developed for optimal use. The system will use a combination of neural networks and an adapted blackboard architecture. Several neural networks will be used in sequence for image analysis, by reconfiguring a single, generic hardware neural network in the FPGA. This generic network is optimized for speed, in order to admit several executions within the frame rate. The sequence will follow the execution cycle of the blackboard architecture. The global, blackboard architecture being developed and the hardware architecture for the generic, reconfigurable FPGA perceptron will be explained in this paper. The project is still at an early stage. However, some hardware implementation results are already available and will be offered in the paper.

  15. 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…

  16. 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.

  17. Computer-based automatic finger- and speech-tracking system.

    Science.gov (United States)

    Breidegard, Björn

    2007-11-01

    This article presents the first technology ever for online registration and interactive and automatic analysis of finger movements during tactile reading (Braille and tactile pictures). Interactive software has been developed for registration (with two cameras and a microphone), MPEG-2 video compression and storage on disk or DVD as well as an interactive analysis program to aid human analysis. An automatic finger-tracking system has been implemented which also semiautomatically tracks the reading aloud speech on the syllable level. This set of tools opens the way for large scale studies of blind people reading Braille or tactile images. It has been tested in a pilot project involving congenitally blind subjects reading texts and pictures. PMID:18183897

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. A novel method for detecting and tracking vehicles in traffic-image sequence

    Science.gov (United States)

    Xu, Jieqiong; Wang, Guoyu; Sun, Feifei

    2013-07-01

    A novel method for detecting and tracking vehicles is proposed. The method which based on motion object segmentation used Cellular Neural Network (CNN) in the background substraction for motion detection in order to distinguish the vehicles from others of the interested regions. Meanwhile a tracking method based on regional characteristic matching is proposed, by which the distance between characteristic vectors can be used to match current motion regions and track the vehicles. Perceptual grouping refers to the organization ability that visual system detect image features in accordance with certain cues such as proximity, continuity, closure, etc, and attracts wide attentions and high regards in computer vision. In this paper, we proposed a new approach for occlution elimination by combining perceptual grouping with Optical flow field. Experimental results show that the methods can extract traffic information with high accuracy and efficiency.

  5. 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.

  6. 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.

  7. Identification and Modelling of Linear Dynamic Systems

    Directory of Open Access Journals (Sweden)

    Stanislav Kocur

    2006-01-01

    Full Text Available System identification and modelling are very important parts of system control theory. System control is only as good as good is created model of system. So this article deals with identification and modelling problems. There are simple classification and evolution of identification methods, and then the modelling problem is described. Rest of paper is devoted to two most known and used models of linear dynamic systems.

  8. An effective fovea detection and automatic assessment of diabetic maculopathy in color fundus images.

    Science.gov (United States)

    Medhi, Jyoti Prakash; Dandapat, Samarendra

    2016-07-01

    Prolonged diabetes causes severe damage to the vision through leakage of blood and blood constituents over the retina. The effect of the leakage becomes more threatening when these abnormalities involve the macula. This condition is known as diabetic maculopathy and it leads to blindness, if not treated in time. Early detection and proper diagnosis can help in preventing this irreversible damage. To achieve this, the possible way is to perform retinal screening at regular intervals. But the ratio of ophthalmologists to patients is very small and the process of evaluation is time consuming. Here, the automatic methods for analyzing retinal/fundus images prove handy and help the ophthalmologists to screen at a faster rate. Motivated from this aspect, an automated method for detection and analysis of diabetic maculopathy is proposed in this work. The method is implemented in two stages. The first stage involves preprocessing required for preparing the image for further analysis. During this stage the input image is enhanced and the optic disc is masked to avoid false detection during bright lesion identification. The second stage is maculopathy detection and its analysis. Here, the retinal lesions including microaneurysms, hemorrhages and exudates are identified by processing the green and hue plane color images. The macula and the fovea locations are determined using intensity property of processed red plane image. Different circular regions are thereafter marked in the neighborhood of the macula. The presence of lesions in these regions is identified to confirm positive maculopathy. Later, the information is used for evaluating its severity. The principal advantage of the proposed algorithm is, utilization of the relation of blood vessels with optic disc and macula, which enhances the detection process. Proper usage of various color plane information sequentially enables the algorithm to perform better. The method is tested on various publicly available databases

  9. 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 ...

  10. Automatic limit switch system for scintillation device and method of operation

    International Nuclear Information System (INIS)

    A scintillation scanner is described having an automatic limit switch system for setting the limits of travel of the radiation detection device which is carried by a scanning boom. The automatic limit switch system incorporates position responsive circuitry for developing a signal representative of the position of the boom, reference signal circuitry for developing a signal representative of a selected limit of travel of the boom, and comparator circuitry for comparng these signals in order to control the operation of a boom drive and indexing mechanism. (author)

  11. 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.

  12. The design and manufacture of the automatic distance position-fixing system in 60Co γ-ray calibrator

    International Nuclear Information System (INIS)

    The author introduces the design principle and technical index of the automatic position-fixing system. This system consists of the PC computer control, loading vehicle and track. The authors used Pentium PC and Intel 8089 as an intelligent card to drive the stepping motor and to power the vehicle by rack, so as to realize the function of the automatic position control, demonstration and output online. The fixed position of the track vehicle has a basic point. In used scope (it is 0.5-6.2 m distant from 60Co source), the maximum deviation of the fixed position point is 0.5 mm , and the deviation of the fixed position point which is 1 m distant from 60Co source is 0.05%

  13. 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.

  14. 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.

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

    Science.gov (United States)

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

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented. PMID:22400008

  16. 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...

  17. Automatic tuning of MST segmentation of mammograms for registration and mass detection algorithms

    OpenAIRE

    Mariusz Bajger; Fei Ma; Bottema, Murk J.

    2009-01-01

    A technique utilizing an entropy measure is developed for automatically tuning the segmentation of screening mammograms by minimum spanning trees (MST). The lack of such technique has been a major obstacle in previous work to segment mammograms for registration and applying mass detection algorithms.

  18. Automatic detection and spatial clustering of interictal discharges in invasive recordings

    Czech Academy of Sciences Publication Activity Database

    Janča, R.; Ježdík, P.; Čmejla, R.; Kršek, P.; Jefferys, J. G. R.; Marusič, P.; Jiruška, Přemysl

    Ottawa: IEEE Instrumentation & Measurement Society IEEE Ottawa Section, 2013, s. 219-223. ISBN 978-1-4673-5195-9. [IEEE International Symposium on Medical Measurements and Applications /8./. Gatineau (CA), 04.05.2013-05.05.2013] Institutional support: RVO:67985823 Keywords : epilepsy * interictal discharges * intracranial electroencephalography * automatic detection * clustering Subject RIV: FH - Neurology

  19. Automatic detection of pulmonary nodules at spiral CT: clinical application of a computer-aided diagnosis system

    International Nuclear Information System (INIS)

    The aim of this study was to evaluate a computer-aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Eighty-eight consecutive spiral-CT examinations were reported by two radiologists in consensus. All examinations were reviewed using a CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm is designed to detect nodules with diameters of at least 5 mm. A total of 153 nodules were detected with at least one modality (radiologists in consensus, CAD, 85 nodules with diameter <5 mm, 68 with diameter ≥5 mm). The results of automatic nodule detection were compared to nodules detected with any modality as gold standard. Computer-aided diagnosis correctly identified 26 of 59 (38%) nodules with diameters ≥5 mm detected by visual assessment by the radiologists; of these, CAD detected 44% (24 of 54) nodules without pleural contact. In addition, 12 nodules ≥5 mm were detected which were not mentioned in the radiologist's report but represented real nodules. Sensitivity for detection of nodules ≥5 mm was 85% (58 of 68) for radiologists and 38% (26 of 68) for CAD. There were 5.8±3.6 false-positive results of CAD per CT study. Computer-aided diagnosis improves detection of pulmonary nodules at spiral CT and is a valuable second opinion in a clinical setting for lung cancer screening despite of its still limited sensitivity. (orig.)

  20. 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.

  1. Electric Vehicle Propulsion System

    OpenAIRE

    Keshri, Ritesh Kumar

    2014-01-01

    Electric vehicles are being considered as one of the pillar of eco-friendly solutions to overcome the problem of global pollution and radiations due to greenhouse gases. Present thesis work reports the improvement in overall performance of the propulsion system of an electric vehicle by improving autonomy and torque-speed characteristic. Electric vehicle propulsion system consists of supply and traction system, and are coordinated by the monitoring & control system. Case of light electric veh...

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Design, development, and evaluation of an automatic guidance system for tractor tracking along the contour line on inclined surfaces

    Directory of Open Access Journals (Sweden)

    S Dehghani

    2016-04-01

    Full Text Available Introduction: Automatic guidance of tractors in the mechanized farming practice has taken the attention of agricultural engineers in the last two decades. For this to be truly practical on the farm, it should be economical, simple to operate and entirely contained on the vehicle. Different types of steering systems such as leader- cable, laser- controlled, radio- operated and contactor- type have been developed for automatic guidance. The automatic leveling system is used on hillside machines to keep the separator level when operating on hillsides. This system has three parts: fluid level system, electrical system and hydraulic system. The fluid level system consists of fluid reservoir and a leveling control switch box. The fluid level system actuates the electrical system of the leveling unit. The electrical system which actuated by the fluid system consist of four micro switches in the leveling control switch box, two micro switches in the limit control box, a solenoid in the hydraulic control level, manual leveling control switch, and a leveling limit warning light. The hydraulic system maintains the level of the separator when the machine is operating on a hillside. The present study was aimed to develop a reliable, versatile and easy to maintain system to fit our economy and low technology level of farmers for hillside- range development or fallow farming. The automatic guidance system has been implemented successfully on agricultural vehicles on the basis of three components, i.e. sensors, processors and actuator elements. The study site (N, latitude; E, longitude; and 1810 m above sea level was located at the Agricultural Research Center, Shiraz University, 15 km northwest of Shiraz, Fars Province, Iran. MF-399 agricultural tractor manufactured by ITMCO, Tabriz, Iran was used for doing the experiments. Materials and Methods:The Level Sensing System: The biaxial tilt industrial sensor (ZCT245AL- China with digital output can be connected

  7. 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.

  8. 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...

  9. 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...

  10. 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.

  11. Automatic exploitation system for photographic dosemeters

    International Nuclear Information System (INIS)

    The Laboratory of Dosimetry Exploitation (LED) has realized an equipment allowing to exploit automatically photographic film dosemeters. This system uses an identification of the films by code-bars and gives the doses measurement with a completely automatic reader. The principle consists in putting in ribbon the emulsions to be exploited and to develop them in a circulation machine. The measurement of the blackening film is realized on a reading plate having fourteen points of reading, in which are circulating the emulsions in ribbon. The exploitation is made with the usual dose calculation method, with special computers codes. A comparison on 2000 dosemeters has shown that the results are the same in manual and automatical methods. This system has been operating since July 1995 by the LED. (N.C.)

  12. 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

  13. 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

  14. 41 CFR 102-34.85 - What motor vehicles require motor vehicle identification?

    Science.gov (United States)

    2010-07-01

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

  15. Vehicle Security and Accident Information System

    OpenAIRE

    D.Satheeshbabu*; B.Govardhana

    2014-01-01

    The main aim of this project is to offer an advance security system in CAR, which consists of a face detection subsystem, a GPS module, a GSM module and a control platform. The face detection subsystem can detect faces in cars during the period in which nobody should be in the car, and make an alarm loudly or soundlessly. The other modules transmit necessary information to users and help to keep eyes on cars all the time, even when the car is lost. In today’s world, many new techn...

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. Analgorithmic Framework for Automatic Detection and Tracking Moving Point Targets in IR Image Sequences

    Directory of Open Access Journals (Sweden)

    R. Anand Raji

    2015-05-01

    Full Text Available Imaging sensors operating in infrared (IR region of electromagnetic spectrum are gaining importance in airborne automatic target recognition (ATR applications due to their passive nature of operation. IR imaging sensors exploit the unintended IR radiation emitted by the targets of interest for detection. The ATR systems based on the passive IR imaging sensors employ a set of signal processing algorithms for processing the image information in real-time. The real-time execution of signal processing algorithms provides the sufficient reaction time to the platform carrying ATR system to react upon the target of interest. These set of algorithms include detection, tracking, and classification of low-contrast, small sized-targets. Paper explained a signal processing framework developed to detect and track moving point targets from the acquired IR image sequences in real-time.Defence Science Journal, Vol. 65, No. 3, May 2015, pp.208-213, DOI: http://dx.doi.org/10.14429/dsj.65.8164

  1. 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.

  2. 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.)

  3. 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...... and differentiate all types of phytoplasmas in one assay. The present protocol describes a microarray-based method for identification of phytoplasmas to 16Sr group level....

  4. 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.

  5. Automatic quadrature control and measuring system. [using optical coupling circuitry

    Science.gov (United States)

    Hamlet, J. F. (Inventor)

    1974-01-01

    A quadrature component cancellation and measuring system comprising a detection system for detecting the quadrature component from a primary signal, including reference circuitry to define the phase of the quadrature component for detection is described. A Raysistor optical coupling control device connects an output from the detection system to a circuit driven by a signal based upon the primary signal. Combining circuitry connects the primary signal and the circuit controlled by the Raysistor device to subtract quadrature components. A known current through the optically sensitive element produces a signal defining the magnitude of the quadrature component.

  6. Identification of barriers and least cost paths for autonomous vehicle navigation using airborne LIDAR data

    OpenAIRE

    Poudel, Om Prakash

    2007-01-01

    In the past several years, the Defense Advanced Research Projects Agency (DARPA) has sponsored two Grand Challenges, races among autonomous ground vehicles in rural environments. These vehicles must follow a course delineated by Global Positioning System waypoints using no human guidance. Airborne LIDAR data and GIS can play a significant role in identifying barriers and least cost paths for such vehicles. Least cost paths minimize the sum of impedance across a surface. Impedance can be mea...

  7. An Intelligent Vehicle Traffic Information System Mode and Evaluation

    OpenAIRE

    Zhang Qi; Zheng Hao; Zhang Jianping; Peng Hong

    2014-01-01

    The investment of centralized traffic information system is large and data processing is too concentrate, the autonomous traffic information system based on vehicle-to-vehicle communication is mostly limited to information on safe driving, less involved with the research of the whole road network congestion information collection and transmission. This study puts forward an autonomous intelligent vehicle traffic information system mode which is for the whole urba...

  8. 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 ...

  9. 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.

  10. 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.

  11. 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.

  12. Inertial Aided Cycle Slip Detection and Identification for Integrated PPP GPS and INS

    Directory of Open Access Journals (Sweden)

    Yang Gao

    2012-10-01

    Full Text Available The recently developed integrated Precise Point Positioning (PPP GPS/INS system can be useful to many applications, such as UAV navigation systems, land vehicle/machine automation and mobile mapping systems. Since carrier phase measurements are the primary observables in PPP GPS, cycle slips, which often occur due to high dynamics, signal obstructions and low satellite elevation, must be detected and repaired in order to ensure the navigation performance. In this research, a new algorithm of cycle slip detection and identification has been developed. With the aiding from INS, the proposed method jointly uses WL and EWL phase combinations to uniquely determine cycle slips in the L1 and L2 frequencies. To verify the efficiency of the algorithm, both tactical-grade and consumer-grade IMUs are tested by using a real dataset collected from two field tests. The results indicate that the proposed algorithm can efficiently detect and identify the cycle slips and subsequently improve the navigation performance of the integrated system.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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...

  18. 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.

  19. DRCPlus in a router: automatic elimination of lithography hotspots using 2D pattern detection and correction

    Science.gov (United States)

    Yang, Jie; Rodriguez, Norma; Omedes, Olivier; Gennari, Frank; Lai, Ya-Chieh; Mankad, Viral

    2010-03-01

    As technology processes continue to shrink, standard design rule checking (DRC) has become insufficient to guarantee design manufacturability. DRCPlus is a powerful technique for capturing yield detractors related to complex 2D situations1,2. DRCPlus is a pattern-based 2D design rule check beyond traditional width and space DRC that can identify problematic 2D configurations which are difficult to manufacture. This paper describes a new approach for applying DRCPlus in a router, enabling an automated approach to detecting and fixing known lithography hotspots using an integrated fast 2D pattern matching engine. A simple pass/no-pass criterion associated with each pattern offers designers guidance on how to fix these problematic patterns. Since it does not rely on compute intensive simulations, DRCPlus can be applied on fairly large design blocks and enforced in conjunction with standard DRC in the early stages of the design flow. By embedding this capability into the router, 2D yield detractors can be identified and fixed by designers in a push-button manner without losing design connectivity. More robust designs can be achieved and the impact on parasitics can be easily assessed. This paper will describe a flow using a fast 2D pattern matching engine integrated into the router in order to enforce DRCPlus rules. An integrated approach allows for rapid identification of hotspot patterns and, more importantly, allows for rapid fixing and verification of these hotspots by a tool that understands design intent and constraints. The overall flow is illustrated in Figure 1. An inexact search pattern is passed to the integrated pattern matcher. The match locations are filtered by the router through application of a DRC constraint (typically a recommended rule). Matches that fail this constraint are automatically fixed by the router, with the modified regions incrementally re-checked to ensure no additional DRCPlus violations are introduced.

  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. 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...

  2. 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-...

  3. 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...

  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. 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...

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications

    OpenAIRE

    Muhammad Zuhair Qadir; Atif Nisar Jilani; Hassam Ullah Sheikh

    2014-01-01

    Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big concern. As the number of new Android applications tends to be rapidly increased in the near future, there is a need for automatic malware detection quickly and efficiently. In this paper, we define a simple static analysis approach to first extract the features of the android application based on intents and categori...

  12. A new rechargeable intelligent vehicle detection sensor

    International Nuclear Information System (INIS)

    Intelligent Transportation System (ITS) is a valid approach to solve the increasing transportation issue in cities. Vehicle detection is one of the key technologies in ITS. The ITS collects and processes traffic data (vehicle flow, vehicular speed, vehicle density and occupancy ratios) from vehicle detection sensors buried under the road or installed along the road. Inductive loop detector as one type of the vehicle detector is applied extensively, with the characters of stability, high value to cost ratio and feasibility. On the other hand, most of the existing inductive loop vehicle detection sensors have some weak points such as friability of detective loop, huge engineering for setting and traffic interruption during installing the sensor. The design and reality of a new rechargeable intelligent vehicle detection sensor is presented in this paper against these weak points existing now. The sensor consists of the inductive loop detector, the rechargeable batteries, the MCU (microcontroller) and the transmitter. In order to reduce the installing project amount, make the loop durable and easily maintained, the volume of the detective loop is reduced as much as we can. Communication in RF (radio frequency) brings on the advantages of getting rid of the feeder cable completely and reducing the installing project amount enormously. For saving the cable installation, the sensor is supplied by the rechargeable batteries. The purpose of the intelligent management of the energy and transmitter by means of MCU is to minimize the power consumption and prolong the working period of the sensor. In a word, the new sensor is more feasible with smaller volume, wireless communication, rechargeable batteries, low power consumption, low cost, high detector precision and easy maintenance and installation

  13. An Automatic Detection Method of Nanocomposite Film Element Based on GLCM and Adaboost M1

    Directory of Open Access Journals (Sweden)

    Hai Guo

    2015-01-01

    Full Text Available An automatic detection model adopting pattern recognition technology is proposed in this paper; it can realize the measurement to the element of nanocomposite film. The features of gray level cooccurrence matrix (GLCM can be extracted from different types of surface morphology images of film; after that, the dimension reduction of film can be handled by principal component analysis (PCA. So it is possible to identify the element of film according to the Adaboost M1 algorithm of a strong classifier with ten decision tree classifiers. The experimental result shows that this model is superior to the ones of SVM (support vector machine, NN and BayesNet. The method proposed can be widely applied to the automatic detection of not only nanocomposite film element but also other nanocomposite material elements.

  14. 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 (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., 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.

  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. 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.

  17. 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

  18. 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...

  19. A LabVIEW-based Autonomous Vehicle Navigation System using Robot Vision and Fuzzy Control

    OpenAIRE

    Ramírez-Cortés J.M.; Gómez-Gil P.; Martínez-Carballido J.; López-Larios F.

    2011-01-01

    This paper describes a navigation system for an autonomous vehicle using machine vision techniques applied to real-time captured images of the track, for academic purposes. The experiment consists of the automatic navigation of a remote control car through a closed circuit. Computer vision techniques are used for the sensing of the environment through a wireless camera. The received images are captured into the computer through the acquisition card NI USB-6009, and processed in a system devel...

  20. 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.

  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. A Multiagent System for Edge Detection and Continuity Perception on Fish Otolith Images

    Science.gov (United States)

    Guillaud, Anne; Troadec, Herve; Benzinou, Abdesslam; Le Bihan, Jean; Rodin, Vincent

    2002-12-01

    We present an algorithm for fish otolith growth ring detection using a multiagent system. Up to now, the identification of growth rings, for age estimation, is routinely achieved by human readers, but this task is tedious and depends on the reader subjectivity. One of the major problems encountered during an automatic contour detection is the lack of ring continuity perception. We present an approach to improve this continuity perception based on a 2D reconstruction of rings using a multiagent system. The originality of the approach is to use local edge detection achieved by agents and combine it with continuity perception that active contours allow.

  3. A Multiagent System for Edge Detection and Continuity Perception on Fish Otolith Images

    Directory of Open Access Journals (Sweden)

    Anne Guillaud

    2002-07-01

    Full Text Available We present an algorithm for fish otolith growth ring detection using a multiagent system. Up to now, the identification of growth rings, for age estimation, is routinely achieved by human readers, but this task is tedious and depends on the reader subjectivity. One of the major problems encountered during an automatic contour detection is the lack of ring continuity perception. We present an approach to improve this continuity perception based on a 2D reconstruction of rings using a multiagent system. The originality of the approach is to use local edge detection achieved by agents and combine it with continuity perception that active contours allow.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. Automatic detection of osteoporotic vertebral fractures in routine thoracic and abdominal MDCT

    International Nuclear Information System (INIS)

    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.)

  15. 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.)

  16. GPU-accelerated automatic identification of robust beam setups for proton and carbon-ion radiotherapy

    International Nuclear Information System (INIS)

    We demonstrate acceleration on graphic processing units (GPU) of automatic identification of robust particle therapy beam setups, minimizing negative dosimetric effects of Bragg peak displacement caused by treatment-time patient positioning errors. Our particle therapy research toolkit, RobuR, was extended with OpenCL support and used to implement calculation on GPU of the Port Homogeneity Index, a metric scoring irradiation port robustness through analysis of tissue density patterns prior to dose optimization and computation. Results were benchmarked against an independent native CPU implementation. Numerical results were in agreement between the GPU implementation and native CPU implementation. For 10 skull base cases, the GPU-accelerated implementation was employed to select beam setups for proton and carbon ion treatment plans, which proved to be dosimetrically robust, when recomputed in presence of various simulated positioning errors. From the point of view of performance, average running time on the GPU decreased by at least one order of magnitude compared to the CPU, rendering the GPU-accelerated analysis a feasible step in a clinical treatment planning interactive session. In conclusion, selection of robust particle therapy beam setups can be effectively accelerated on a GPU and become an unintrusive part of the particle therapy treatment planning workflow. Additionally, the speed gain opens new usage scenarios, like interactive analysis manipulation (e.g. constraining of some setup) and re-execution. Finally, through OpenCL portable parallelism, the new implementation is suitable also for CPU-only use, taking advantage of multiple cores, and can potentially exploit types of accelerators other than GPUs.

  17. 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.

  18. 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...

  19. 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.

  20. Automatic detection of apnoea of prematurity

    International Nuclear Information System (INIS)

    The detection of the incidents of apnoea of prematurity (AP) in preterm infants is important in the intensive care unit, but this detection is often based on simple threshold techniques, which suffer from poor specificity. Three methods for the automatic detection of AP were designed, tested and evaluated using approximately 2426 h of continuous recording from 54 neonates (μ = 44 h and σ = 7 h). The first method was based on the cumulative sum of the time series of heart rate (HR), respiratory rate (RR) and oxygen saturation (SpO2) along with the sum of their Shannon entropy. The performance of this method gave 94.53% sensitivity, 74.72% specificity and 77.84% accuracy. The second method was based on the correlation between the time series of HR, RR and SpO2, which were used as inputs to an artificial neural network. This gave 81.85% sensitivity, 75.83% specificity and 76.78% accuracy. The third method utilized the derivative of the three time series and yielded a performance of 100% sensitivity, 96.19% specificity and 96.79% accuracy. Although not optimized to work in real time, the latter method has the potential for forming the basis of a real time system for the detection of incidents of AP

  1. From Automatic Sign Detection To Space Usage Rules Mining For Autonomous Driving

    OpenAIRE

    SAMSONOV, Pavel; Hecht, Brent; SCHOENING, Johannes

    2015-01-01

    While there is a large body of related work on the automatic detecting of road signs for (semi-)autonomous vehicles, we believe that these vehicles should also be aware of so-called “space usage rules” (SURs) more generally. Vehicles that understand SURs – e.g. “no swimming”, “no drone flying”, - could provide a novel set of context-aware services for autonomous driving. For instance, an autonomous car navigation system could provide directions to the nearest beach, where swimming is al...

  2. 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.

  3. 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.

  4. 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.

  5. 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).

  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. 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

  8. 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...

  9. 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.

  10. 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)

  11. 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.

  12. 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.

  13. 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...

  14. Detection and Identification of Android Malware Based on Information Flow Monitoring

    OpenAIRE

    Andriatsimandefitra, Radoniaina; Viet Triem Tong, Valérie

    2015-01-01

    Information flow monitoring has been mostly used to detect privacy leaks. In a previous work, we showed that they can also be used to characterize Android malware behaviours and in the current one we show that these flows can also be used to detect and identify Android malware. The characterization consists in computing automatically System Flow Graphs that describe how a malware disseminates its data in the system. In the current work, we propose a method that uses these SFG- based malware p...

  15. 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

  16. 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...

  17. 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 ...

  18. 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.

  19. 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.

  20. 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.

  1. Vehicle and cargo container inspection system for drugs

    Science.gov (United States)

    Verbinski, Victor V.; Orphan, Victor J.

    1999-06-01

    A vehicle and cargo container inspection system has been developed which uses gamma-ray radiography to produce digital images useful for detection of drugs and other contraband. The system is comprised of a 1 Ci Cs137 gamma-ray source collimated into a fan beam which is aligned with a linear array of NaI gamma-ray detectors located on the opposite side of the container. The NaI detectors are operated in the pulse-counting mode. A digital image of the vehicle or container is obtained by moving the aligned source and detector array relative to the object. Systems have been demonstrated in which the object is stationary (source and detector array move on parallel tracks) and in which the object moves past a stationary source and detector array. Scanning speeds of ˜30 cm/s with a pixel size (at the object) of ˜1 cm have been achieved. Faster scanning speeds of ˜2 m/s have been demonstrated on railcars with more modest spatial resolution (4 cm pixels). Digital radiographic images are generated from the detector count rates. These images, recorded on a PC-based data acquisition and display system, are shown from several applications: 1) inspection of trucks and containers at a border crossing, 2) inspection of railcars at a border crossing, 3) inspection of outbound cargo containers for stolen automobiles, and 4) inspection of trucks and cars for terrorist bombs.

  2. Vehicle and cargo container inspection system for drugs

    International Nuclear Information System (INIS)

    A vehicle and cargo container inspection system has been developed which uses gamma-ray radiography to produce digital images useful for detection of drugs and other contraband. The system is comprised of a 1 Ci Cs137 gamma-ray source collimated into a fan beam which is aligned with a linear array of NaI gamma-ray detectors located on the opposite side of the container. The NaI detectors are operated in the pulse-counting mode. A digital image of the vehicle or container is obtained by moving the aligned source and detector array relative to the object. Systems have been demonstrated in which the object is stationary (source and detector array move on parallel tracks) and in which the object moves past a stationary source and detector array. Scanning speeds of ∼30 cm/s with a pixel size (at the object) of ∼1 cm have been achieved. Faster scanning speeds of ∼2 m/s have been demonstrated on railcars with more modest spatial resolution (4 cm pixels). Digital radiographic images are generated from the detector count rates. These images, recorded on a PC-based data acquisition and display system, are shown from several applications: 1) inspection of trucks and containers at a border crossing, 2) inspection of railcars at a border crossing, 3) inspection of outbound cargo containers for stolen automobiles, and 4) inspection of trucks and cars for terrorist bombs

  3. 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.

  4. 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

  5. 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...... which 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...... 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...

  6. 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

  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. 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.

  9. 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

  10. Commercial vehicles. Fundamentals, systems, components. 3. rev. and enl. ed.; Nutzfahrzeugtechnik. Grundlagen, Systeme, Komponenten

    Energy Technology Data Exchange (ETDEWEB)

    Hoepke, E. (ed.); Appel, W.; Braehler, H.; Dahlhaus, U.; Esch, T.; Graefenstein, J.

    2004-09-15

    This book presents all components and types of commercial vehicles, i.e. classic design theory, vehicle mechanics and theromodynamics, as well as the latest developments in engine and vehicle engineering up to electronic vehicle management. This is the third edition; it contains some new chapters on four-wheel drive design, commercial vehicle engineering, test cycles up to EURO 5, particulate filters and four-wheel drives for light commercial vehicles. Subjects: Fundamentals; Undercarriage; Design of commercial vehicles; Supporting structures and top structures; Propulsion systems; Speed converters; Electrical and electronic systems; Seals; Outlook. (orig.)

  11. System identification and optimal control of a small-scale unmanned helicopter / Marthinus Christoffel Terblanche

    OpenAIRE

    Terblanche, Marthinus Christoffel

    2014-01-01

    The use of rotary winged unmanned aerial vehicles in military and civilian applications is rapidly increasing. The primary objective of this study is to develop an automatic flight control system for a radio controlled (RC) helicopter. There is a need for a simple, easy to use methodology to develop automatic flight controllers for first-flight. In order to make the work accessible to new research groups without physical helicopter platforms, a simulation environment is created fo...

  12. 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.

  13. Multistage audiovisual integration of speech: dissociating identification and detection

    DEFF Research Database (Denmark)

    Eskelund, Kasper; Tuomainen, Jyrki; Andersen, Tobias

    2011-01-01

    signal. Here we show that identification of phonetic content and detection can be dissociated as speech-specific and non-specific audiovisual integration effects. To this end, we employed synthetically modified stimuli, sine wave speech (SWS), which is an impoverished speech signal that only observers...

  14. Detection and identification of phytoplasmas in Ribes

    Czech Academy of Sciences Publication Activity Database

    Navrátil, M.; Přibylová, Jaroslava; Válová, P.; Fialová, R.; Šafářová, D.; Špak, Josef; Kubelková, Darina; Petrzik, Karel; Karešová, R.; Špaková, Vlastimila

    2007-01-01

    Roč. 60, č. 2 (2007), s. 123-124. ISSN 1721-8861 R&D Projects: GA ČR GA522/02/0040 Institutional research plan: CEZ:AV0Z50510513 Keywords : plant virology * phytoplasma detection Subject RIV: EE - Microbiology, Virology Impact factor: 0.381, year: 2007

  15. Minimum Hamiltonian Ascent Trajectory Evaluation (MASTRE) program (update to automatic flight trajectory design, performance prediction, and vehicle sizing for support of Shuttle and Shuttle derived vehicles) engineering manual

    Science.gov (United States)

    Lyons, J. T.

    1993-01-01

    The Minimum Hamiltonian Ascent Trajectory Evaluation (MASTRE) program and its predecessors, the ROBOT and the RAGMOP programs, have had a long history of supporting MSFC in the simulation of space boosters for the purpose of performance evaluation. The ROBOT program was used in the simulation of the Saturn 1B and Saturn 5 vehicles in the 1960's and provided the first utilization of the minimum Hamiltonian (or min-H) methodology and the steepest ascent technique to solve the optimum trajectory problem. The advent of the Space Shuttle in the 1970's and its complex airplane design required a redesign of the trajectory simulation code since aerodynamic flight and controllability were required for proper simulation. The RAGMOP program was the first attempt to incorporate the complex equations of the Space Shuttle into an optimization tool by using an optimization method based on steepest ascent techniques (but without the min-H methodology). Development of the complex partial derivatives associated with the Space Shuttle configuration and using techniques from the RAGMOP program, the ROBOT program was redesigned to incorporate these additional complexities. This redesign created the MASTRE program, which was referred to as the Minimum Hamiltonian Ascent Shuttle TRajectory Evaluation program at that time. Unique to this program were first-stage (or booster) nonlinear aerodynamics, upper-stage linear aerodynamics, engine control via moment balance, liquid and solid thrust forces, variable liquid throttling to maintain constant acceleration limits, and a total upgrade of the equations used in the forward and backward integration segments of the program. This modification of the MASTRE code has been used to simulate the new space vehicles associated with the National Launch Systems (NLS). Although not as complicated as the Space Shuttle, the simulation and analysis of the NLS vehicles required additional modifications to the MASTRE program in the areas of providing

  16. 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.

  17. Detection and Identification of Rare Audiovisual Cues

    CERN Document Server

    Anemüller, Jörn; Gool, Luc

    2012-01-01

    Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later applied to future data in order to estimate the current state of the world. An implied assumption is that the future is stochastically similar to the past. The approach fails when the system encounters situations that are not anticipated from the past experience. In contrast, successful natural organisms identify new unanticipated stimuli and situations and frequently generate appropriate responses. The observation described above lead to the initiation of the DIRAC EC project in 2006. In 2010 a workshop was held, aimed to bring together researchers and students from different disciplines in order to present and discuss new approaches for identifying and reacting to unexpected events in information-rich environments. This book includes a summary of the achievements of the DIRAC project in chapter 1, and a collection of the papers presented in this workshop in ...

  18. Image-processing algorithms for detecting and counting vehicles waiting at a traffic light

    Science.gov (United States)

    de La Rocha, Ernesto; Palacios, Rafael

    2010-10-01

    Traffic lights at most road intersections operate on a fixed timing schedule that leads to suboptimal traffic management, with unnecessary delays, higher fuel consumption, and higher emissions. Traffic management can be improved by installing inductive loops; however, installation involves temporary road closures and high maintenance costs, especially if there is normally a lot of heavy traffic on the road. We present a vehicle detection and counting system based on digital image-processing techniques. These images can be taken by digital cameras installed at the top of existing traffic lights. By using the proposed approach, it is possible to detect the number of vehicles waiting on each side of the intersection, hence, providing the necessary information for optimal traffic management. Results achieved after testing this methodology on three real intersections are promising, attaining high accuracy during the day (98.8%) and the night (91.3%) while counting several vehicles at the same time. Hence, the system is equivalent to installing multiple inductive loops in all the streets of the intersection, but with lower installation and maintenance costs. After integrating the proposed algorithms into a traffic-management system, it was possible to reduce fuel and CO2 emissions by half compared to the standard fixed-time scheduler.

  19. 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.

  20. A Portable System for Nuclear, Chemical Agent and Explosives Identification

    International Nuclear Information System (INIS)

    The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electrochemically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine an active neutron interrogation and analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material