WorldWideScience

Sample records for automatic vehicle detection and identification systems

  1. 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.

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

    Institute of Scientific and Technical Information of China (English)

    YANG Zhaoxuan; CHEN Yang; HE Yinghua; WU Jun

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    ArtaIftikhar

    2013-04-01

    Full Text Available 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 divided into two types- Hardware based and software based detection. Various algorithms have been implemented to classify different vehicles from videos. In this paper an efficient and economical solution for automatic vehicle detection and classification is proposed. The proposed system first isolates the object through background subtraction followed by vehicle detection using ontology. Vehicle detection is based on low level features such as shape, size, and spatial location. Finally system classifies vehicles into one of the known classes of vehicle based on size.

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

    OpenAIRE

    Ling-Yuan Hsu; Tsung-Lin Chen

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficie...

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

    Science.gov (United States)

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

    2017-03-01

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

  6. 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.

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

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

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

  8. A Dynamic Visualization Environment For The Design And Evaluation Of Automatic Vehicle Control Systems

    OpenAIRE

    Xu, Z.

    1995-01-01

    This document presents Dynamic Visualization, a project associated with the California PATH Program. The objective of the project is to develop a software which can animate automated highways, visualize the dynamics of automatic vehicles, and help the design and evaluation of automatic vehicle systems. This report summarizes the accomplishments of the project, describes the functions of the developed software, and provides an explanation of how to use the software.

  9. Automatic player detection and identification for sports entertainment applications

    NARCIS (Netherlands)

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

    2014-01-01

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

  10. 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.

  11. 2014 United States Automatic Identification System Database

    Data.gov (United States)

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

  12. 2010 United States Automatic Identification System Database

    Data.gov (United States)

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

  13. Automatic vehicle counting system for traffic monitoring

    Science.gov (United States)

    Crouzil, Alain; Khoudour, Louahdi; Valiere, Paul; Truong Cong, Dung Nghy

    2016-09-01

    The article is dedicated to the presentation of a vision-based system for road vehicle counting and classification. The system is able to achieve counting with a very good accuracy even in difficult scenarios linked to occlusions and/or presence of shadows. The principle of the system is to use already installed cameras in road networks without any additional calibration procedure. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. First, the approach models each pixel of the background with an adaptive Gaussian distribution. This model is coupled with a motion detection procedure, which allows correctly location of moving vehicles in space and time. The nature of trials carried out, including peak periods and various vehicle types, leads to an increase of occlusions between cars and between cars and trucks. A specific method for severe occlusion detection, based on the notion of solidity, has been carried out and tested. Furthermore, the method developed in this work is capable of managing shadows with high resolution. The related algorithm has been tested and compared to a classical method. Experimental results based on four large datasets show that our method can count and classify vehicles in real time with a high level of performance (>98%) under different environmental situations, thus performing better than the conventional inductive loop detectors.

  14. System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator

    Science.gov (United States)

    2006-08-01

    System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator Jae-Jun Kim∗ and Brij N. Agrawal † Department of...TITLE AND SUBTITLE System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator 5a. CONTRACT NUMBER 5b...and Dynamics, Vol. 20, No. 4, July-August 1997, pp. 625-632. 6Schwartz, J. L. and Hall, C. D., “ System Identification of a Spherical Air-Bearing

  15. Intelligent Storage System Based on Automatic Identification

    Directory of Open Access Journals (Sweden)

    Kolarovszki Peter

    2014-09-01

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

  16. A Vehicle License Plate Detection and Recognition System

    Directory of Open Access Journals (Sweden)

    Khalid W. Maglad

    2012-01-01

    Full Text Available Problem statement: Automatic vehicle license plate detection and recognition is a key technique in most of traffic related applications and is an active research topic in the image processing domain. Different methods, techniques and algorithms have been developed for license plate detection and recognitions. Approach: Due to the varying characteristics of the license plate from country to country like numbering system, colors, language of characters, style (font and sizes of license plate, further research is still needed in this area. Results: In most of the Middle East countries, they use the combination of Arabic and English letters, along with their countries logo. Thus, it makes the localization of plate number, the differentiation between Arabic and English letters and logo’s object and finally the recognition of those characters become a more challenging research task. The use of artificial neural network has proved itself beneficial for plate recognition, but it has not been applied for the plate detection. Radial Basis Function (RBF neural network is used both for the detection and recognition of Saudi Arabian license plates. Conclusion/Recommendations: The proposed approach has been tested on 200 front images of national license plate of Saudi Arabia. A higher percentage of accuracy has been obtained to show that the significant of this approach. The study could be further investigated in other Middle East countries.

  17. An efficient automatic firearm identification system

    Science.gov (United States)

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

    2014-06-01

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

  18. Automatic solution for detection, identification and biomedical monitoring of a cow using remote sensing for optimised treatment of cattle

    Directory of Open Access Journals (Sweden)

    Yevgeny Beiderman

    2014-12-01

    Full Text Available In this paper we show how a novel photonic remote sensing system assembled on a robotic platform can extract vital biomedical parameters from cattle including their heart beating, breathing and chewing activity. The sensor is based upon a camera and a laser using selfinterference phenomena. The whole system intends to provide an automatic solution for detection, identification and biomedical monitoring of a cow. The detection algorithm is based upon image processing involving probability map construction. The identification algorithms involve well known image pattern recognition techniques. The sensor is used on top of an automated robotic platform in order to support animal decision making. Field tests and computer simulated results are presented.

  19. Identification and Damage Detection on Structural Systems

    DEFF Research Database (Denmark)

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

    1994-01-01

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

  20. Investigation of Ballistic Evidence through an Automatic Image Analysis and Identification System.

    Science.gov (United States)

    Kara, Ilker

    2016-05-01

    Automated firearms identification (AFI) systems contribute to shedding light on criminal events by comparison between different pieces of evidence on cartridge cases and bullets and by matching similar ones that were fired from the same firearm. Ballistic evidence can be rapidly analyzed and classified by means of an automatic image analysis and identification system. In addition, it can be used to narrow the range of possible matching evidence. In this study conducted on the cartridges ejected from the examined pistol, three imaging areas, namely the firing pin impression, capsule traces, and the intersection of these traces, were compared automatically using the image analysis and identification system through the correlation ranking method to determine the numeric values that indicate the significance of the similarities. These numerical features that signify the similarities and differences between pistol makes and models can be used in groupings to make a distinction between makes and models of pistols.

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

    Science.gov (United States)

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

    2016-04-28

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

  2. Time Synchronization Module for Automatic Identification System

    Institute of Scientific and Technical Information of China (English)

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

    2003-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Baljit Singh Mokha

    2015-10-01

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

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

    Science.gov (United States)

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

    2010-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-08-21

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

  6. Autonomous system for pathogen detection and identification

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-09-24

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

  7. An estimation-based automatic vehicle location system for public transport vehicles

    OpenAIRE

    Morenz, Tino; MEIER, RENE

    2008-01-01

    PUBLISHED Public transport vehicles often share a road network with other road users making their journeys susceptive to changing road conditions and especially to congestion. Travelers using such public transport increasingly depend on real-time information to plan their journeys. While such information can be provided by Automatic Vehicle Location (AVL) systems, AVLs depend heavily on large-scale deployment of designated sensory equipment, which may prevent their ...

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

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Néstor Cárdenas-Benítez

    2016-04-01

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

  10. 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

  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. A Novel OD Estimation Method Based on Automatic Vehicle Identification Data

    Science.gov (United States)

    Sun, Jian; Feng, Yu

    With the development and application of Automatic Vehicle Identification (AVI) technologies, a novel high resolution OD estimation method was proposed based on AVI detector information. 4 detected categories (Ox + Dy, Ox/Dy + Path(s), Ox/Dy, Path(s)) were divided at the first step. Then the initial OD matrix was updated using the Ox + Dy sample information considering the AVI detector errors. Referenced by particle filter, the link-path relationship data were revised using the last 3 categories information based on Bayesian inference and the possible trajectory and OD were determined using Monte Carlo random process at last. Finally, according to the current application of video detector in Shanghai, the North-South expressway was selected as the testbed which including 17 OD pairs and 9 AVI detectors. The results show that the calculated average relative error is 12.09% under the constraints that the simulation error is under 15% and the detector error is about 10%. It also shows that this method is highly efficient and can fully using the partial vehicle trajectory which can be satisfied with the dynamic traffic management application in reality.

  13. Maritime surveillance with synthetic aperture radar (SAR) and automatic identification system (AIS) onboard a microsatellite constellation

    Science.gov (United States)

    Peterson, E. H.; Zee, R. E.; Fotopoulos, G.

    2012-11-01

    New developments in small spacecraft capabilities will soon enable formation-flying constellations of small satellites, performing cooperative distributed remote sensing at a fraction of the cost of traditional large spacecraft missions. As part of ongoing research into applications of formation-flight technology, recent work has developed a mission concept based on combining synthetic aperture radar (SAR) with automatic identification system (AIS) data. Two or more microsatellites would trail a large SAR transmitter in orbit, each carrying a SAR receiver antenna and one carrying an AIS antenna. Spaceborne AIS can receive and decode AIS data from a large area, but accurate decoding is limited in high traffic areas, and the technology relies on voluntary vessel compliance. Furthermore, vessel detection amidst speckle in SAR imagery can be challenging. In this constellation, AIS broadcasts of position and velocity are received and decoded, and used in combination with SAR observations to form a more complete picture of maritime traffic and identify potentially non-cooperative vessels. Due to the limited transmit power and ground station downlink time of the microsatellite platform, data will be processed onboard the spacecraft. Herein we present the onboard data processing portion of the mission concept, including methods for automated SAR image registration, vessel detection, and fusion with AIS data. Georeferencing in combination with a spatial frequency domain method is used for image registration. Wavelet-based speckle reduction facilitates vessel detection using a standard CFAR algorithm, while leaving sufficient detail for registration of the filtered and compressed imagery. Moving targets appear displaced from their actual position in SAR imagery, depending on their velocity and the image acquisition geometry; multiple SAR images acquired from different locations are used to determine the actual positions of these targets. Finally, a probabilistic inference

  14. 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.

  15. 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.

  16. An Immunology-inspired Fault Detection and Identification System

    Directory of Open Access Journals (Sweden)

    Liguo Weng

    2012-09-01

    Full Text Available This paper presents a fault detection and identification (FDI approach inspired by the immune system. The salient features of the immune system, such as adaptability, robustness, flexibility, archival memory and distributed cognition abilities, have been the valuable source of inspiration for fundamentally new methods for fault detection and identification. This research makes use of immunological concepts to develop a robust fault detection and identification mechanism, capable of detecting and classifying diverse system faults dynamically. Such an FDI mechanism also has the ability to learn and classify overlapping faults using distributed sensing. Moreover, its detection accuracy can be continuously improved during system operation. As tested by numerical simulations in which faults are represented by overlapping banana functions, the proposed algorithms are adaptive to new types of faults and overlapping faults.

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

    Science.gov (United States)

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

    2014-02-15

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

  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. 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.

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

    Science.gov (United States)

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

    2016-03-01

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

  1. 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.

  2. Study of automatic and manual terminal guidance and control systems for space shuttle vehicles. Volume 1: Sections 1 through 3

    Science.gov (United States)

    Osder, S.; Keller, R.

    1971-01-01

    The results of a study to analyze, design, and evaluate guidance and control systems are presented that start at an altitude of about 100,000 feet and bring the unpowered space shuttle orbiters to a precision horizontal landing. The systems under consideration included fully automatic versions which involve no pilot participation as well as various manual configurations that provide combinations of displays and control augmentation which permit the pilot to control the vehicle to a successful landing. Two classes of vehicles were studied: the low cross range or straight-wing orbiter and the high cross range or delta-wing (delta body) orbiter. The recommended navigation, guidance and control system is shown to be compatible with realistic physical constraints that would exist in space shuttlecraft and to be consistent with the 1971 avionics equipment state of the art. Aircraft capable of aerodynamically simulating the various candidate space shuttlecraft in their unpowered, terminal area descent were investigated, and flight test recommendations, including system mechanizations, are made.

  3. Experimental analysis of vehicle-bridge interaction using a wireless monitoring system and a two-stage system identification technique

    Science.gov (United States)

    Kim, Junhee; Lynch, Jerome P.

    2012-04-01

    Deterioration of bridges under repeated traffic loading has called attention to the need for improvements in the understanding of vehicle-bridge interaction. While analytical and numerical models have been previously explored to describe the interaction that exists between a sprung mass (i.e., a moving vehicle) and an elastic beam (i.e., bridge), comparatively less research has been focused on the experimental observation of vehicle-bridge interaction. A wireless monitoring system with wireless sensors installed on both the bridge and moving vehicle is proposed to record the dynamic interaction between the bridge and vehicle. Time-synchronized vehicle-bridge response data is used within a two-stage system identification methodology. In the first stage, the free-vibration response of the bridge is used to identify the dynamic characteristics of the bridge. In the second stage, the vehicle-bridge response data is used to identify the time varying load imposed on the bridge from the vehicle. To test the proposed monitoring and system identification strategy, the 180 m long Yeondae Bridge (Icheon, Korea) was selected. A dense network of wireless sensors was installed on the bridge while wireless sensors were installed on a multi-axle truck. The truck was driven across the bridge at constant velocity with bridge and vehicle responses measured. Excellent agreement between the measured Yeondae Bridge response and that predicted by an estimated vehicle-bridge interaction model validates the proposed strategy.

  4. Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

    Directory of Open Access Journals (Sweden)

    Wei Huang

    2015-01-01

    Full Text Available This paper deals with the design of a fault detection and isolation (FDI system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS. The ADASs are outfitted with sensors for acquiring various information about the vehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed FDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies a generalized observer scheme (GOS. In the GOS, there is bank of extended Kalman filters (EKFs, each excited by all except one sensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults but one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The designed FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with diagnosing individual sensor faults and outputting fault-free vehicle states.

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

    Science.gov (United States)

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

    2012-03-01

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

  6. Fiber optic system design for vehicle detection and analysis

    Science.gov (United States)

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

    2016-04-01

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

  7. Study of automatic and manual terminal guidance and control systems for space shuttle vehicles. Volume 2: Section 4 through appendix B

    Science.gov (United States)

    Osder, S.; Keller, R.

    1971-01-01

    Guidance and control design studies that were performed for three specific space shuttle candidate vehicles are described. Three types of simulation were considered. The manual control investigations and pilot evaluations of the automatic system performance is presented. Recommendations for systems and equipment, both airborne and ground-based, necessary to flight test the guidance and control concepts for shuttlecraft terminal approach and landing are reported.

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

    Science.gov (United States)

    2014-08-20

    Supply Module ( PSM ) is shown in Fig. 14; specification highlights are listed below. The RPC and BPC use the same model PSM . • Manufacturer: WinSystems Inc...bit PC/104 Bus ACRBS 13 Fig. 14 — WinSystems PCM-DC/DC PSM 3.2.3.3 GPS Receiver Module The GPS receiver module is shown in Fig. 15; specification...as the RPC; it is described in Section 3.2.3.1. 3.3.3.2 Power Supply Module The BPC uses the same model PSM as the RPC; it is described in Section

  9. IDC: a system for automatically detecting and classifying manmade objects in overhead imagery

    Science.gov (United States)

    Carlotto, Mark J.; Nebrich, Mark; De Michael, David

    2010-04-01

    The automatic detection and classification of manmade objects in overhead imagery is key to generating geospatial intelligence (GEOINT) from today's high space-time bandwidth sensors in a timely manner. A flexible multi-stage object detection and classification capability known as the IMINT Data Conditioner (IDC) has been developed that can exploit different kinds of imagery using a mission-specific processing chain. A front-end data reader/tiler converts standard imagery products into a set of tiles for processing, which facilitates parallel processing on multiprocessor/multithreaded systems. The first stage of processing contains a suite of object detectors designed to exploit different sensor modalities that locate and chip out candidate object regions. The second processing stage segments object regions, estimates their length, width, and pose, and determines their geographic location. The third stage classifies detections into one of K predetermined object classes (specified in a models file) plus clutter. Detections are scored based on their salience, size/shape, and spatial-spectral properties. Detection reports can be output in a number of popular formats including flat files, HTML web pages, and KML files for display in Google Maps or Google Earth. Several examples illustrating the operation and performance of the IDC on Quickbird, GeoEye, and DCS SAR imagery are presented.

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

    Directory of Open Access Journals (Sweden)

    Muhammad Elsayeh

    2016-03-01

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

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

    Directory of Open Access Journals (Sweden)

    A. A. SHAFIE

    2011-08-01

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

  12. Automatic Water Sensor Window Opening System

    KAUST Repository

    Percher, Michael

    2013-12-05

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

  13. 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.

  14. Automatic Identification System modular receiver for academic purposes

    Science.gov (United States)

    Cabrera, F.; Molina, N.; Tichavska, M.; Araña, V.

    2016-07-01

    The Automatic Identification System (AIS) standard is encompassed within the Global Maritime Distress and Safety System (GMDSS), in force since 1999. The GMDSS is a set of procedures, equipment, and communication protocols designed with the aim of increasing the safety of sea crossings, facilitating navigation, and the rescue of vessels in danger. The use of this system not only is increasingly attractive to security issues but also potentially creates intelligence products throughout the added-value information that this network can transmit from ships on real time (identification, position, course, speed, dimensions, flag, among others). Within the marine electronics market, commercial receivers implement this standard and allow users to access vessel-broadcasted information if in the range of coverage. In addition to satellite services, users may request actionable information from private or public AIS terrestrial networks where real-time feed or historical data can be accessed from its nodes. This paper describes the configuration of an AIS receiver based on a modular design. This modular design facilitates the evaluation of specific modules and also a better understanding of the standard and the possibility of changing hardware modules to improve the performance of the prototype. Thus, the aim of this paper is to describe the system's specifications, its main hardware components, and to present educational didactics on the setup and use of a modular and terrestrial AIS receiver. The latter is for academic purposes and in undergraduate studies such as electrical engineering, telecommunications, and maritime studies.

  15. 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.

  16. Channel Access Algorithm Design for Automatic Identification System

    Institute of Scientific and Technical Information of China (English)

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

    2003-01-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    1992-12-01

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

  19. 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.

  20. An Automatic System of Vehicle Number-Plate Recognition Based on Neural Networks

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents an automatic system of vehicle number-plate recognition based on neural networks. In this system, location of number-plate and recognition of characters in number-plate can be automatically completed. Pixel colors of Number-plate area are classified using neural network, then color features are extracted by analyzing scanning lines of the cross-section of number-plate. It takes full use of number-plate color features to locate number plate. Characters in number-plate can be effectively recognized using the neural networks. Experimental results show that the correct rate of number-plate location is close to 100%, and the time of number-plate location is less than 1 second. Moreover, recognition rate of characters is improved due to the known number-plate type. It is also observed that this system is not sensitive to variations of weather, illumination and vehicle speed. In addition, and also the size of number-plate need not to be known in prior. This system is of crucial significance to apply and spread the automatic system of vehicle number-plate recognition.

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

    Institute of Scientific and Technical Information of China (English)

    YANG Zhiyong; XU Meng; HUANG Tian; NI Yanbing

    2007-01-01

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

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

    Science.gov (United States)

    2012-05-01

    BIOAEROSOL DETECTION AND IDENTIFICATION SYSTEMS ECBC-TR-964 Jana Kesavan Deborah R. Schepers Jerold R. Bottiger RESEARCH AND TECHNOLOGY...Testing Of Bioaerosol Detection And Identification Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT...Medical Metered Dose Inhalers for Functionality Testing of Bioaerosol Detection and Identification Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

  3. 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.

  4. 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.

  5. 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.

  6. A low cost automatic detection and ranging system for space surveillance in the medium Earth orbit region and beyond.

    Science.gov (United States)

    Danescu, Radu; Ciurte, Anca; Turcu, Vlad

    2014-02-11

    The space around the Earth is filled with man-made objects, which orbit the planet at altitudes ranging from hundreds to tens of thousands of kilometers. Keeping an eye on all objects in Earth's orbit, useful and not useful, operational or not, is known as Space Surveillance. Due to cost considerations, the space surveillance solutions beyond the Low Earth Orbit region are mainly based on optical instruments. This paper presents a solution for real-time automatic detection and ranging of space objects of altitudes ranging from below the Medium Earth Orbit up to 40,000 km, based on two low cost observation systems built using commercial cameras and marginally professional telescopes, placed 37 km apart, operating as a large baseline stereovision system. The telescopes are pointed towards any visible region of the sky, and the system is able to automatically calibrate the orientation parameters using automatic matching of reference stars from an online catalog, with a very high tolerance for the initial guess of the sky region and camera orientation. The difference between the left and right image of a synchronized stereo pair is used for automatic detection of the satellite pixels, using an original difference computation algorithm that is capable of high sensitivity and a low false positive rate. The use of stereovision provides a strong means of removing false positives, and avoids the need for prior knowledge of the orbits observed, the system being able to detect at the same time all types of objects that fall within the measurement range and are visible on the image.

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

    DEFF Research Database (Denmark)

    2013-01-01

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

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

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2012-01-01

    The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy...... of the seizure from the patient showed that the simulated seizures were visually similar to the epileptic one. The multi-modal intelligent seizure acquisition (MISA) system showed high sensitivity, short detection latency and low false detection rate. The results showed superiority of the multi- modal detection...... system compared to the uni-modal one. The presented system has a promising potential for seizure detection based on multi-modal data....

  9. 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.

  10. 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.

  11. 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

  12. Damage detection in structures through nonlinear excitation and system identification

    Science.gov (United States)

    Hajj, Muhammad R.; Bordonaro, Giancarlo G.; Nayfeh, Ali H.; Duke, John C., Jr.

    2008-03-01

    Variations in parameters representing natural frequency, damping and effective nonlinearities before and after damage initiation in a beam carrying a lumped mass are assessed. The identification of these parameters is performed by exploiting and modeling nonlinear behavior of the beam-mass system and matching an approximate solution of the representative model with quantities obtained from spectral analysis of measured vibrations. The representative model and identified coefficients are validated through comparison of measured and predicted responses. Percentage variations of the identified parameters before and after damage initiation are determined to establish their sensitivities to the state of damage of the beam. The results show that damping and effective nonlinearity parameters are more sensitive to damage initiation than the system's natural frequency. Moreover, the sensitivity of nonlinear parameters to damage is better established using a physically-derived parameter rather than spectral amplitudes of harmonic components.

  13. 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

  14. Automatic Fall Detection System Based on the Combined Use of a Smartphone and a Smartwatch.

    Science.gov (United States)

    Casilari, Eduardo; Oviedo-Jiménez, Miguel A

    2015-01-01

    Due to their widespread popularity, decreasing costs, built-in sensors, computing power and communication capabilities, Android-based personal devices are being seen as an appealing technology for the deployment of wearable fall detection systems. In contrast with previous solutions in the existing literature, which are based on the performance of a single element (a smartphone), this paper proposes and evaluates a fall detection system that benefits from the detection performed by two popular personal devices: a smartphone and a smartwatch (both provided with an embedded accelerometer and a gyroscope). In the proposed architecture, a specific application in each component permanently tracks and analyses the patient's movements. Diverse fall detection algorithms (commonly employed in the literature) were implemented in the developed Android apps to discriminate falls from the conventional activities of daily living of the patient. As a novelty, a fall is only assumed to have occurred if it is simultaneously and independently detected by the two Android devices (which can interact via Bluetooth communication). The system was systematically evaluated in an experimental testbed with actual test subjects simulating a set of falls and conventional movements associated with activities of daily living. The tests were repeated by varying the detection algorithm as well as the pre-defined mobility patterns executed by the subjects (i.e., the typology of the falls and non-fall movements). The proposed system was compared with the cases where only one device (the smartphone or the smartwatch) is considered to recognize and discriminate the falls. The obtained results show that the joint use of the two detection devices clearly increases the system's capability to avoid false alarms or 'false positives' (those conventional movements misidentified as falls) while maintaining the effectiveness of the detection decisions (that is to say, without increasing the ratio of 'false

  15. Automatic Fall Detection System Based on the Combined Use of a Smartphone and a Smartwatch.

    Directory of Open Access Journals (Sweden)

    Eduardo Casilari

    Full Text Available Due to their widespread popularity, decreasing costs, built-in sensors, computing power and communication capabilities, Android-based personal devices are being seen as an appealing technology for the deployment of wearable fall detection systems. In contrast with previous solutions in the existing literature, which are based on the performance of a single element (a smartphone, this paper proposes and evaluates a fall detection system that benefits from the detection performed by two popular personal devices: a smartphone and a smartwatch (both provided with an embedded accelerometer and a gyroscope. In the proposed architecture, a specific application in each component permanently tracks and analyses the patient's movements. Diverse fall detection algorithms (commonly employed in the literature were implemented in the developed Android apps to discriminate falls from the conventional activities of daily living of the patient. As a novelty, a fall is only assumed to have occurred if it is simultaneously and independently detected by the two Android devices (which can interact via Bluetooth communication. The system was systematically evaluated in an experimental testbed with actual test subjects simulating a set of falls and conventional movements associated with activities of daily living. The tests were repeated by varying the detection algorithm as well as the pre-defined mobility patterns executed by the subjects (i.e., the typology of the falls and non-fall movements. The proposed system was compared with the cases where only one device (the smartphone or the smartwatch is considered to recognize and discriminate the falls. The obtained results show that the joint use of the two detection devices clearly increases the system's capability to avoid false alarms or 'false positives' (those conventional movements misidentified as falls while maintaining the effectiveness of the detection decisions (that is to say, without increasing the ratio

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

    Science.gov (United States)

    Henrique Castelo Branco, Luiz; César Lima Segantine, Paulo

    2015-09-01

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

  17. 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

    2015-04-16

    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%.

  18. 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.

  19. 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 ...

  20. 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...

  1. Automatic Registration of Wide Area Motion Imagery to Vector Road Maps by Exploiting Vehicle Detections.

    Science.gov (United States)

    Elliethy, Ahmed; Sharma, Gaurav

    2016-11-01

    To enrich large-scale visual analytics applications enabled by aerial wide area motion imagery (WAMI), we propose a novel methodology for accurately registering a geo-referenced vector roadmap to WAMI by using the locations of detected vehicles and determining a parametric transform that aligns these locations with the network of roads in the roadmap. Specifically, the problem is formulated in a probabilistic framework, explicitly allowing for spurious detections that do not correspond to on-road vehicles. The registration is estimated via the expectation-maximization (EM) algorithm as the planar homography that minimizes the sum of weighted squared distances between the homography-mapped detection locations and the corresponding closest point on the road network, where the weights are estimated posterior probabilities of detections being on-road vehicles. The weighted distance minimization is efficiently performed using the distance transform with the Levenberg-Marquardt nonlinear least-squares minimization procedure, and the fraction of spurious detections is estimated within the EM framework. The proposed method effectively sidesteps the challenges of feature correspondence estimation, applies directly to different imaging modalities, is robust to spurious detections, and is also more appropriate than feature matching for a planar homography. Results over three WAMI data sets captured by both visual and infrared sensors indicate the effectiveness of the proposed methodology: both visual comparison and numerical metrics for the registration accuracy are significantly better for the proposed method as compared with the existing alternatives.

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

    Science.gov (United States)

    Oh, Sang-Il; Kang, Hang-Bong

    2017-01-22

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

  3. Moving Vehicle Detection and Tracking Algorithm in Traffic Video

    Directory of Open Access Journals (Sweden)

    Shisong Zhu

    2013-06-01

    Full Text Available Aiming at the defects and shortages of traditional moving vehicles detection algorithms, by the analysis and comparison of the existing detection algorithms, we propose an algorithm that combined with frames with symmetric difference and background difference to detect moving vehicle in this paper. First, two different difference images by using frames with symmetric difference and background difference are gained respectively and two binary images can be gained by the appropriate threshold, then the contour of moving vehicles can be extracted by applying OR operation in the two binary images. Finally, the precise moving vehicles will be gained by mathematic morphological methods. In this paper we use Harris operator, Feature Points such as edges and corners are extracted, followed by block-matching to track the Feature Points in successive viedo frames. Many vehicles can be tracked at the same time automatically since  the  information is obtained from video sequences.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Safat B. Wali

    2015-01-01

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

  6. Assessing facial wrinkles: automatic detection and quantification

    Science.gov (United States)

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

    2009-02-01

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

  7. 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.

  8. Image structural analysis in the tasks of automatic navigation of unmanned vehicles and inspection of Earth surface

    Science.gov (United States)

    Lutsiv, Vadim; Malyshev, Igor

    2013-10-01

    The automatic analysis of images of terrain is urgent for several decades. On the one hand, such analysis is a base of automatic navigation of unmanned vehicles. On the other hand, the amount of information transferred to the Earth by modern video-sensors increases, thus a preliminary classification of such data by onboard computer becomes urgent. We developed an object-independent approach to structural analysis of images. While creating the methods of image structural description, we did our best to abstract away from the partial peculiarities of scenes. Only the most general limitations were taken into account, that were derived from the laws of organization of observable environment and from the properties of image formation systems. The practical application of this theoretic approach enables reliable matching the aerospace photographs acquired from differing aspect angles, in different day-time and seasons by sensors of differing types. The aerospace photographs can be matched even with the geographic maps. The developed approach enabled solving the tasks of automatic navigation of unmanned vehicles. The signs of changes and catastrophes can be detected by means of matching and comparison of aerospace photographs acquired at different time. We present the theoretical proofs of chosen strategy of structural description and matching of images. Several examples of matching of acquired images with template pictures and maps of terrain are shown within the frameworks of navigation of unmanned vehicles or detection of signs of disasters.

  9. Modeling and Model Identification of Autonomous Underwater Vehicles

    Science.gov (United States)

    2015-06-01

    IDENTIFICATION OF AUTONOMOUS UNDERWATER VEHICLES by Jose Alberti June 2015 Thesis Advisor: Noel du Toit Second Reader: Douglas...Master’s Thesis 4. TITLE AND SUBTITLE MODELING AND MODEL IDENTIFICATION OF AUTONOMOUS UNDERWATER VEHICLES 5. FUNDING NUMBERS 6. AUTHOR(S...unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) As autonomous underwater vehicles (AUVs) are deployed in more complex

  10. 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.

  11. 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.

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

    Science.gov (United States)

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

    2016-10-01

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

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

    Science.gov (United States)

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

    2014-05-01

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

  14. Electronic Vehicle Identification Architecture and Proof of Concept

    NARCIS (Netherlands)

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

    2009-01-01

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

  15. Bond graph modeling, simulation, and reflex control of the Mars planetary automatic vehicle

    Science.gov (United States)

    Amara, Maher; Friconneau, Jean Pierre; Micaelli, Alain

    1993-01-01

    The bond graph modeling, simulation, and reflex control study of the Planetary Automatic Vehicle are considered. A simulator derived from a complete bond graph model of the vehicle is presented. This model includes both knowledge and representation models of the mechanical structure, the floor contact, and the Mars site. The MACSYMEN (French acronym for aided design method of multi-energetic systems) is used and applied to study the input-output power transfers. The reflex control is then considered. Controller architecture and locomotion specificity are described. A numerical stage highlights some interesting results of the robot and the controller capabilities.

  16. Vision system for driving control using camera mounted on an automatic vehicle. Jiritsu sokosha no camera ni yoru shikaku system

    Energy Technology Data Exchange (ETDEWEB)

    Nishimori, K.; Ishihara, K.; Tokutaka, H.; Kishida, S.; Fujimura, K. (Tottori University, Tottori (Japan). Faculty of Engineering); Okada, M. (Mazda Corp., Hiroshima (Japan)); Hirakawa, S. (Fujitsu Corp., Tokyo (Japan))

    1993-11-30

    The present report explains a vision system, in which a CCD camera, used for the model vehicle automatically traveling by fuzzy control, is used as a vision sensor. The vision system is composed of input image processing module, situation recognition/analysis module to three-dimensionally recover the road, route-selecting navigation module to avoid the obstacle and vehicle control module. The CCD camera is used as a vision sensor to make the model vehicle automatically travel by fuzzy control with the above modules. In the present research, the traveling is controlled by treating the position and configuration of objective in image as a fuzzy inferential variable. Based on the above method, the traveling simulation gave the following knowledge: even with the image information only from the vision system, the application of fuzzy control facilitates the traveling. If the objective is clearly known, the control is judged able to be made even from vague image which does not necessitate the exact locative information. 4 refs., 11 figs.

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

    Science.gov (United States)

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

    2014-01-01

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

  18. A new laser-based system for obstacle detection including step, hole and slope for Personal Mobility Vehicles

    OpenAIRE

    POLLARD, Evangeline; Fawzi NASHASHIBI

    2013-01-01

    International audience; Personal Mobility Vehicles (PMV) is is an important part of the Intelligent Transportation System (ITS) domain. These new transport systems have been designed for urban traffic areas, pedestrian streets, green zones and private parks. In these areas, steps and curbs make the movement of disable or mobility reduced people with PMV, and with standard chair wheels difficult. In this paper, we present a step and curb detection system based on laser sensors. This system is ...

  19. A multi-algorithm-based automatic person identification system

    Science.gov (United States)

    Monwar, Md. Maruf; Gavrilova, Marina

    2010-04-01

    Multimodal biometric is an emerging area of research that aims at increasing the reliability of biometric systems through utilizing more than one biometric in decision-making process. In this work, we develop a multi-algorithm based multimodal biometric system utilizing face and ear features and rank and decision fusion approach. We use multilayer perceptron network and fisherimage approaches for individual face and ear recognition. After face and ear recognition, we integrate the results of the two face matchers using rank level fusion approach. We experiment with highest rank method, Borda count method, logistic regression method and Markov chain method of rank level fusion approach. Due to the better recognition performance we employ Markov chain approach to combine face decisions. Similarly, we get combined ear decision. These two decisions are combined for final identification decision. We try with 'AND'/'OR' rule, majority voting rule and weighted majority voting rule of decision fusion approach. From the experiment results, we observed that weighted majority voting rule works better than any other decision fusion approaches and hence, we incorporate this fusion approach for the final identification decision. The final results indicate that using multi algorithm based can certainly improve the recognition performance of multibiometric systems.

  20. New Navigation System for Automatic Guided Vehicles Using an Ultrasonic Sensor Array

    Science.gov (United States)

    Tabata, Katsuhiko; Nishida, Yoshifumi; Iida, Yoshihiro; Iwai, Toshiaki

    We propose a new navigation system for Automatic Guided Vehicles (AGV) used as a carrier in the factory. The guided marker of the navigation system is composed of ultrasonic transducers instead of the traditional markers such as electromagnetic tape, light reflective tape and so on. The proposed system is available to be used not only indoors but also outdoors and adaptable to a temporary route. The ultrasonic sensor is generically susceptible to noise, so that we make the following propositions. First, a phased array of the ultrasonic sensors is employed in searching a land marker to improve the signal-to-noise ratio. Second, the specific ID with 7bits is assigned as the land marker to avoid the system errors ascribable to an ultrasonic interference. In addition, the proposed system is quite compact in virtue of the embedded technology of a microcomputer and Field Programmable Gate Array (FPGA). This paper reports the development of the proto-type system of navigation system and confirmation of its fundamental performances.

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

    Science.gov (United States)

    Jones, Christopher R; Fazio, Russell H

    2010-08-01

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

  2. AUTOMATIC RETINAL VESSEL DETECTION AND TORTUOSITY MEASUREMENT

    Directory of Open Access Journals (Sweden)

    Temitope Mapayi

    2016-07-01

    Full Text Available As retinopathies continue to be major causes of visual loss and blindness worldwide, early detection and management of these diseases will help achieve significant reduction of blindness cases. However, an efficient automatic retinal vessel segmentation approach remains a challenge. Since efficient vessel network detection is a very important step needed in ophthalmology for reliable retinal vessel characterization, this paper presents study on the combination of difference image and K-means clustering for the segmentation of retinal vessels. Stationary points in the vessel center-lines are used to model the detection of twists in the vessel segments. The combination of arc-chord ratio with stationary points is used to compute tortuosity index. Experimental results show that the proposed K-means combined with difference image achieved a robust segmentation of retinal vessels. A maximum average accuracy of 0.9556 and a maximum average sensitivity of 0.7581 were achieved on DRIVE database while a maximum average accuracy of 0.9509 and a maximum average sensitivity of 0.7666 were achieved on STARE database. When compared with the previously proposed techniques on DRIVE and STARE databases, the proposed technique yields higher mean sensitivity and mean accuracy rates in the same range of very good specificity. In a related development, a non-normalized tortuosity index that combined distance metric and the vessel twist frequency proposed in this paper also achieved a strong correlation of 0.80 with the expert ground truth.

  3. Carrier-phase differential GPS for automatic control of land vehicles

    Science.gov (United States)

    O'Connor, Michael Lee

    Real-time centimeter-level navigation has countless potential applications in land vehicles, including precise topographic field mapping, runway snowplowing in bad weather, and land mine detection and avoidance. Perhaps the most obvious and immediate need for accurate, robust land vehicle sensing is in the guidance and control of agricultural vehicles. Accurate guidance and automatic control of farm vehicles offers many potential advantages; however, previous attempts to automate these vehicles have been unsuccessful due to sensor limitations. With the recent development of real-time carrier-phase differential GPS (CDGPS), a single inexpensive GPS receiver can measure a vehicle's position to within a few centimeters and orientation to fractions of a degree. This ability to provide accurate real-time measurements of multiple vehicle states makes CDGPS ideal for automatic control of vehicles. This work describes the theoretical and experimental work behind the first successfully demonstrated automatic control system for land vehicles based on CDGPS. An extension of pseudolite-based CDGPS initialization methods was explored for land vehicles and demonstrated experimentally. Original land vehicle dynamic models were developed and identified using this innovative sensor. After initial automatic control testing using a Yamaha Fleetmaster golf cart, a centimeter-level, fully autonomous row guidance capability was demonstrated on a John Deere 7800 farm tractor.

  4. 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

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

    Science.gov (United States)

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

    2011-01-01

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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. Detection System Design of Electric Vehicle Wiring Harness

    Institute of Scientific and Technical Information of China (English)

    SUN Jian-Xin; LI Xiao-Peng

    2015-01-01

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

  13. Ability of automatic detection of conflict between planes in flight simulations with the help of expert system

    Directory of Open Access Journals (Sweden)

    Naděžda Bartošová

    2015-01-01

    Full Text Available This article examines options for applying expert systems for the needs of identification of conflict situations between planes in flight simulations, which are applied during basic training of air traffic controllers. It focuses on the conditions for basic training of military air traffic controllers and presents the use of rule systems to automatic detection of conflict between planes within a basic training polygon. The system of rules is a part of the expert system, consisting of realisation of tasks for identifying optimum resolution of conflict situations in selected types of simulations.

  14. 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.

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

    Science.gov (United States)

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-11-15

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

  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. Using Automatic Identification System Technology to Improve Maritime Border Security

    Science.gov (United States)

    2014-12-01

    passengers for hire; • High-speed passenger vessels with 12 or more passengers for hire; • Certain dredges and floating plants ; • Vessels moving...requirement did not apply to private visiting vessels.51 The Mexican government has also taken steps to improve identification requirements of vessels in...government of Mexico to “locate and identify (in real time) any small vessels cruising Mexican National waters.”53 As of June 2014, the Mexican

  19. 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...

  20. 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.

  1. Irregular and adaptive sampling for automatic geophysic measure systems

    Science.gov (United States)

    Avagnina, Davide; Lo Presti, Letizia; Mulassano, Paolo

    2000-07-01

    In this paper a sampling method, based on an irregular and adaptive strategy, is described. It can be used as automatic guide for rovers designed to explore terrestrial and planetary environments. Starting from the hypothesis that a explorative vehicle is equipped with a payload able to acquire measurements of interesting quantities, the method is able to detect objects of interest from measured points and to realize an adaptive sampling, while badly describing the not interesting background.

  2. 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.

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

    Science.gov (United States)

    Hess, Phillip; Colaninno, Robin C.

    2017-02-01

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

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

    Science.gov (United States)

    Yuan, Bo; He, Xiangqing; Liu, Ying

    2013-12-01

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

  5. Derivation and Testing of Computer Algorithms for Automatic Real-Time Determination of Space Vehicle Potentials in Various Plasma Environments

    Science.gov (United States)

    1988-05-31

    COMPUTER ALGORITHMS FOR AUTOMATIC REAL-TIME DETERMINATION OF SPACE VEHICLE POTENTIALS IN VARIOUS PLASMA ENVIRONMENTS May 31, 1988 Stanley L. Spiegel...crrnaion DiviSiofl 838 12 2 DERIVATION AND TESTING OF COMPUTER ALGORITHMS FOR AUTOMATIC REAL-TIME DETERMINATION OF SPACE VEHICLE POTENTIALS IN VARIOUS...S.L., "Derivation and testing of computer algorithms for automatic real time determination of space vehicle poteuatials in various plasma

  6. 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.

  7. 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…

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

    Science.gov (United States)

    Kiencke, Uwe; Nielsen, Lars

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

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

    Institute of Scientific and Technical Information of China (English)

    张丽然; 沈胜利

    2012-01-01

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

  10. System identification and automatic tuning of the controller in hydro power plants; Systemidentifikation und Reglerselbsteinstellung in Wasserkraftanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Anz, R.

    2002-07-01

    In this work a method is presented to generate dynamic nonlinear models for speed and power controlled hydro Power plants. The models are identified automatically with measured data during operation. The models can be used for optimisation of the parameters of the controller. In this approach local linear neuro-fuzzy models are used. They seem very suitable for modelling nonlinear static and dynamic Systems. For a given set of measured data the structure and the parameters of the model are generated with the LOLIMOT-algorithm which is well known from literature. Several modifications of this algorithm are investigated during application on hydro power stations. Unfortunately not sufficient measured data from real power plants were available therefore theoretical models based on physical law and equations had to be used instead. The parameters for speed and power control are optimises using a global optimisation method. Other optimisation and design methods can be used and are discussed. The controllers which are optimised with the experimentally generated local linear neuro-fuzzy model are tested with the theoretical model. A clear improvement of the controller can be confirmed. (orig.) [German] In der vorliegenden Arbeit wird ein Verfahren vorgestellt, mit dem dynamische Modelle von drehzahl- und leistungsgeregelten Wasserkraftanlagen aus gemessenen Betriebsdaten automatisch bestimmt werden koennen. Diese Modelle koennen fuer den Entwurf oder zur Optimierung von Reglerparametern herangezogen werden. Bei dem dynamischen Modell handelt es sich um ein lokal lineares Neuro-Fuzzy Netz. Dieser Ansatz ist geeignet, nichtlineare statische und dynamische Systeme abzubilden. Fuer einen gegebenen Satz gemessener Daten erfolgt die Modellerstellung weitgehend automatisch mit dem aus der Literatur bekannten LOLIMOT-Algorithmus. Verschiedene Varianten und Abaenderungen des Verfahrens werden am Beispiel von Wasserkraftanlagen in dieser Arbeit untersucht. Leider standen fuer die

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

    Directory of Open Access Journals (Sweden)

    Manabu OMAE

    2006-01-01

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

  12. Automatic Identification and Organization of Index Terms for Interactive Browsing.

    Science.gov (United States)

    Wacholder, Nina; Evans, David K.; Klavans, Judith L.

    The potential of automatically generated indexes for information access has been recognized for several decades, but the quantity of text and the ambiguity of natural language processing have made progress at this task more difficult than was originally foreseen. Recently, a body of work on development of interactive systems to support phrase…

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

    Science.gov (United States)

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

    2014-07-01

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

  14. 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.

  15. 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).

  16. 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.

  17. 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

  18. 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

  19. Automatic pterygium detection on cornea images to enhance computer-aided cortical cataract grading system.

    Science.gov (United States)

    Gao, Xinting; Wong, Damon Wing Kee; Aryaputera, Aloysius Wishnu; Sun, Ying; Cheng, Ching-Yu; Cheung, Carol; Wong, Tien Yin

    2012-01-01

    In this paper, we present a new method to detect pterygiums using cornea images. Due to the similarity of appearances and spatial locations between pterygiums and cortical cataracts, pterygiums are often falsely detected as cortical cataracts on retroillumination images by a computer-aided grading system. The proposed method can be used to filter out the pterygium which improves the accuracy of cortical cataract grading system. This work has three major contributions. First, we propose a new pupil segmentation method for visible wavelength images. Second, an automatic detection method of pterygiums is proposed. Third, we develop an enhanced compute-aided cortical cataract grading system that excludes pterygiums. The proposed method is tested using clinical data and the experimental results demonstrate that the proposed method can improve the existing automatic cortical cataract grading system.

  20. 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.

  1. 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%.

  2. 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...

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

    Science.gov (United States)

    2014-08-01

    also a concern – can these be modeled?  Chain of locks canal mentioned as a key area, also Lock 2 in Arkansas.  Recommended to start with top-ten in...division multiple access LOMA Lock Operations Management Application LOS Line of sight LPMS Lock Performance Monitoring System LTM Linked text...hydrographic data, carriage of dangerous cargos, safety and security zones, status of locks and Aids to Navigation (AtoNs), and other port/waterway

  4. Novel automatic eye detection and tracking algorithm

    Science.gov (United States)

    Ghazali, Kamarul Hawari; Jadin, Mohd Shawal; Jie, Ma; Xiao, Rui

    2015-04-01

    The eye is not only one of the most complex but also the most important sensory organ of the human body. Eye detection and eye tracking are basement and hot issue in image processing. A non-invasive eye location and eye tracking is promising for hands-off gaze-based human-computer interface, fatigue detection, instrument control by paraplegic patients and so on. For this purpose, an innovation work frame is proposed to detect and tracking eye in video sequence in this paper. The contributions of this work can be divided into two parts. The first contribution is that eye filters were trained which can detect eye location efficiently and accurately without constraints on the background and skin colour. The second contribution is that a framework of tracker based on sparse representation and LK optic tracker were built which can track eye without constraint on eye status. The experimental results demonstrate the accuracy aspects and the real-time applicability of the proposed approach.

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

    Directory of Open Access Journals (Sweden)

    Zehua Dong

    2016-12-01

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

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

    Science.gov (United States)

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

    2016-12-06

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

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

    Science.gov (United States)

    Walker, B. K.; Gai, E.

    1978-01-01

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

  8. Automatic identification and normalization of dosage forms in drug monographs

    Directory of Open Access Journals (Sweden)

    Li Jiao

    2012-02-01

    Full Text Available Abstract Background Each day, millions of health consumers seek drug-related information on the Web. Despite some efforts in linking related resources, drug information is largely scattered in a wide variety of websites of different quality and credibility. Methods As a step toward providing users with integrated access to multiple trustworthy drug resources, we aim to develop a method capable of identifying drug's dosage form information in addition to drug name recognition. We developed rules and patterns for identifying dosage forms from different sections of full-text drug monographs, and subsequently normalized them to standardized RxNorm dosage forms. Results Our method represents a significant improvement compared with a baseline lookup approach, achieving overall macro-averaged Precision of 80%, Recall of 98%, and F-Measure of 85%. Conclusions We successfully developed an automatic approach for drug dosage form identification, which is critical for building links between different drug-related resources.

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

    Directory of Open Access Journals (Sweden)

    Guojun Dai

    2013-08-01

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

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

    Science.gov (United States)

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

    2013-08-16

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

  11. 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.

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

    Science.gov (United States)

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

    2014-08-01

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

  13. 纯电动汽车自动同步换挡系统设计%Automatic Synchronization Shift of Pure Electric Vehicle System Design and Research

    Institute of Scientific and Technical Information of China (English)

    张进; 沈安文

    2011-01-01

    The transmission of the pure electric vehicle has important sense, can improve the electric starting performance and accelerating ability, climbing performance, high-speed performance and improve the maximum mileage of electric vehicle. Through the comparison and analysis of several existing transmission advantages and disadvantages, learn these types of transmission systems based on self-5development and design of a synchronous system (AST) .the article describes in detail the internal structure of AST systems, structural design and work principle, AST system experiment platform and gear shift strategy and process to achieve, through experimental results obtained a good description of AST system, excellent performance, with high practical value.%变速器对纯电动汽车具有重要意义,可以改善电动汽车的起步性能、加速性能、爬坡性能、高速性能以及提高电动汽车最高续航里程.本文对比分析现有几种变速器的优缺点,借鉴这几种变速器系统的基础上,自行开发设计自动同步换挡变速器系统(AST),文章详细介绍AST系统的内部结构,结构设计与工作原理,AST系统的实验平台以及AST换挡策略和换挡过程实现,通过实验得到的实验结果很好的说明AST系统优异性能,具有很高的实用价值.

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

    OpenAIRE

    Bing Zhu; Yizhou Chen; Jian Zhao; Yunfu Su

    2015-01-01

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

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

    Science.gov (United States)

    Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

    2016-06-25

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Razavi, A.

    1998-12-31

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

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

    Science.gov (United States)

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

    2015-10-01

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

  18. PLC Based Automatic Multistoried Car Parking System

    OpenAIRE

    2014-01-01

    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 detecte...

  19. Medical isotope identification with large mobile detection systems

    Science.gov (United States)

    Mukhopadhyay, Sanjoy; Maurer, Richard

    2012-10-01

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

  20. 自动识别环境下车辆的出行矩阵估计新方法%A New Method of OD Estimation Based On Automatic Vehicle Identification Data

    Institute of Scientific and Technical Information of China (English)

    孙剑; 冯羽

    2011-01-01

    鉴于以视频牌照识别系统为代表的车辆自动识别(automatic vehicle identification,AVI)技术在我国逐步应用的现实,提出了利用AVI检测信息估计高精度车辆起讫点矩阵(OD- matrix)的新方法.该方法首先将检测的车辆信息分为4类(起讫点已知、起点或终点及部分路径已知、仅知起点或终点、仅知部分路径),然后利用第1类信息根据AVI检测误差直接扩样更新基础OD矩阵;利用第2,3,4类信息,参照粒子滤波算法思想,基于贝叶斯估计理论修正更新路段-路径流量关系,进而用蒙特卡罗随机过程确定可能路径以及OD;最后根据AVI获得的路径流量信息反向验算校正OD.根据上海市目前视频牌照识别系统的应用现状,选择以南北高架快速路为研究对象,根据牌照识别系统检测的动态车辆信息,对布设9个视频检测器的南北高架沿线17个出入口的OD进行了估计应用.结果表明,在路网仿真模型误差≤15%、AVI设施覆盖率为27.2%以及检测误差在10%的前提下,运用本方法,OD估计的总体平均相对误差仅为11.09%.该方法能充分利用AVI检测的个体车辆不完整路径信息,且计算效率高,可满足实际动态交通管理的需求.%With the development and application of video license plate recognition system which represented the automatic vehicle identification (AVI) technologies in China,a novel high resolution OD estimation method was proposed based on AVI detector information. 4 detected categories (Ox + Dy, Ox/Dy + (8), Ox/Dy、 P(8)) were divided at the first step. Then the initial OD matrix was updated by using the Ox + Dy sample information considering the AVI detector errors. Referenced by particle filter, the link-path relationship data were revised by using the last 3 categories information based on Bayesian inference and the possible trajectory and OD were determined with the Monte Carlo random process. Then the OD was corrected

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

    Science.gov (United States)

    Chou, Tao; Chu, Tzyy-Wen

    2014-05-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-07-01

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

  3. Automatic character detection and segmentation in natural scene images

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

  4. Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

    Science.gov (United States)

    2014-03-27

    SALIENT FEATURE IDENTIFICATION AND ANALYSIS USING KERNEL-BASED CLASSIFICATION TECHNIQUES FOR SYNTHETIC APERTURE RADAR AUTOMATIC TARGET RECOGNITION...FEATURE IDENTIFICATION AND ANALYSIS USING KERNEL-BASED CLASSIFICATION TECHNIQUES FOR SYNTHETIC APERTURE RADAR AUTOMATIC TARGET RECOGNITION THESIS Presented...SALIENT FEATURE IDENTIFICATION AND ANALYSIS USING KERNEL-BASED CLASSIFICATION TECHNIQUES FOR SYNTHETIC APERTURE RADAR AUTOMATIC TARGET RECOGNITION

  5. 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...

  6. Sensitivity Based Segmentation and Identification in Automatic Speech Recognition.

    Science.gov (United States)

    1984-03-30

    by a network constructed from phonemic, phonetic , and phonological rules. Regardless of the speech processing system used, Klatt 1 2 has described...analysis, and its use in the segmentation and identification of the phonetic units of speech, that was initiated during the 1982 Summer Faculty Research...practicable framework for incorporation of acoustic- phonetic variance as well as time and talker normalization. XOI iF- ? ’:: .:- .- . . l ] 2 D

  7. A Control Allocation System for Automatic Detection and Compensation of Phase Shift Due to Actuator Rate Limiting

    Science.gov (United States)

    Yildiz, Yidiray; Kolmanovsky, Ilya V.; Acosta, Diana

    2011-01-01

    This paper proposes a control allocation system that can detect and compensate the phase shift between the desired and the actual total control effort due to rate limiting of the actuators. Phase shifting is an important problem in control system applications since it effectively introduces a time delay which may destabilize the closed loop dynamics. A relevant example comes from flight control where aggressive pilot commands, high gain of the flight control system or some anomaly in the system may cause actuator rate limiting and effective time delay introduction. This time delay can instigate Pilot Induced Oscillations (PIO), which is an abnormal coupling between the pilot and the aircraft resulting in unintentional and undesired oscillations. The proposed control allocation system reduces the effective time delay by first detecting the phase shift and then minimizing it using constrained optimization techniques. Flight control simulation results for an unstable aircraft with inertial cross coupling are reported, which demonstrate phase shift minimization and recovery from a PIO event.

  8. 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.

  9. 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.

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

    NARCIS (Netherlands)

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

    2008-01-01

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

  11. 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

  12. 无向简单图与无向连通图自动识别系统%Undirected Simple Graphs and Undirected Connected Graph Automatic Identification System

    Institute of Scientific and Technical Information of China (English)

    张娟

    2012-01-01

    近年来,图论越来越受到全世界数学界和其它科学界的广泛重视.图的理论及其在物理、化学、运筹学、计算机科学、电子学、信息论、控制论、网络理论、社会科学及经济管理等几乎所有学科领域中各方面的应用研究都迅速发展.无向图作为图论的重要组成部分,研究无向图的连通性问题具有很重要的意义.本文介绍了无向简单图与无向连通图自动识别系统的设计与实现过程.%In recent years, more and more attention was paid to the graph theory in Mathematics and other scientific fields; there is a great development in graph theory and the applying research of graph theory in the physical, chemical, operations research, computer science, electronics, information theory, cybernetics, network theory, social science and economic management and so on. As an important part of graph theory, it is very important to do the research about the connectivity of undirected simple graph. This paper introduces the designing and applying process of automatic identification system of undirected simple graph and undirected connected graph.

  13. 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.

  14. Vehicle Detection and Classification from High Resolution Satellite Images

    Science.gov (United States)

    Abraham, L.; Sasikumar, M.

    2014-11-01

    In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

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

    Directory of Open Access Journals (Sweden)

    Christopher C. Darlington

    2011-11-01

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

  16. Vision-based multiple vehicle detection and tracking at nighttime

    Science.gov (United States)

    Xu, Wencong; Liu, Hai

    2011-08-01

    In this paper, we develop a robust vision-based approach for real-time traffic data collection at nighttime. The proposed algorithm detects and tracks vehicles through detection and location of vehicle headlights. First, we extract headlights candidates by an adaptive image segmentation algorithm. Then we group headlights candidates that belong to the same vehicle by spatial clustering and generate vehicle hypotheses by rule-based reasoning. The potential vehicles are then tracked over frames by region search and pattern analysis methods. The spatial and temporal continuity extracted from tracking process is used to confirm vehicle's presence. To handle problem of occlusions, we apply Kalman Filter to motion estimation. We test the algorithm on the video clips of nighttime traffic under different conditions. The experimental results show that real-time vehicle counting and tacking for multi-lanes are achieved and the total detection rate is above 96%.

  17. 基于DSP的自动指纹识别系统%Automatic Fingerprint Identification System Based on DSP

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

    According to real - time ,accuracy ,low power consumption ,small volume ,portable request of the security access control system ,this paper proposed automatic fingerprint identification system based on DSP TMS320VC5509A and fingerprint acquisition sensor MBF310 .The system uses finger-print image matching algorithm based on fingerprint ridge line difference degree .The algorithm was used in DSP TMS320VC5509A successfully ,and improved the detection accuracy . The experiments show that the system has a higher intelligent and good stability .%  针对安全访问控制系统的实时性、精确性、低功耗、体积小、便携式等要求,提出一种基于 DSP TMS320VC5509A和指纹采集传感器 MBF310的自动指纹识别系统。该系统使用的基于指纹脊线差异度的指纹图像匹配算法应用于 DSP之中,提高了检测的准确性。实验表明,整个系统具有良好的智能化和稳定性。

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

    Science.gov (United States)

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

    2014-11-01

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

  19. Automatic Language Identification for Romance Languages using Stop Words and Diacritics

    OpenAIRE

    Truică, Ciprian-Octavian; Velcin, Julien; Boicea, Alexandru

    2015-01-01

    International audience; Automatic language identification is a natural language processing problem that tries to determine the natural language of a given content. In this paper we present a statistical method for automatic language identification of written text using dictionaries containing stop words and diacritics. We propose different approaches that combine the two dictionaries to accurately determine the language of textual corpora. This method was chosen because stop words and diacrit...

  20. 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.

  1. TEXT AREA IDENTIFICATION FOR RECOGNIZING DESTINATION PLACES FROM VEHICLES

    Directory of Open Access Journals (Sweden)

    Selvanayaki K.S

    2014-07-01

    Full Text Available Nowadays, automatic detection of text from the vehicles is an important problem in many applications. Text information present in an image can be easily understood by both human and computer. It has wide applications such as license plate reading, sign detection, identification of destination places, mobile text recognition and so on. This problem is challenging due to complex backgrounds, the non-uniform illuminations, variations of text font, size and line orientation. Once the text is identified, it can be analyzed, recognized and interpreted. Hence, there is a need for a better algorithm for detection and localization of text from vehicles. A method is proposed for detecting text from vehicles. The method makes use of features such as Histogram of oriented Gradients (HOG and Local Binary Pattern (LBP. These features are stored which can be further used for feature matching at the time of classification. After the text region is being detected, it can be further subjected to character segmentation and recognition thereby identifying the destination places. The ability to recognize text area from the vehicles, especially buses has obvious applications like traffic management in the bus stands. The obtained results are verified and performance parameters like speed, precision and recall are determined.

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

    Science.gov (United States)

    2015-12-01

    CCTV.52 The most common uses for CCTV by police are in car videos, interrogations rooms and ingress and egress into governmental buildings. Law...Law enforcement officials have been turning to social media sites such as Google +, Facebook and Twitter to collect and compare photographs of...tracking device to track a car through public streets.”118 The Court ruled that the use of this enhanced technology, deployed in the manner it was used in

  3. Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

    Science.gov (United States)

    Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

    2014-03-01

    Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

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

    Science.gov (United States)

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

    2013-03-01

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

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

    Science.gov (United States)

    Kotze, Ben; Jordaan, Gerrit

    2014-08-25

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

  6. 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.

  7. 利用Identifiler分型系统推断同胞关系%Research siblings identification by Identiffler system and automatic STR genetic

    Institute of Scientific and Technical Information of China (English)

    郭燕霞; 郝金萍; 刘路; 叶健; 徐小玉; 欧元; 张建; 林小健; 王华; 翟亚森; 米瑞华; 康艳荣; 李万水; 陈松; 张国臣; 刘开会; 郭燕东; 李嘉丽; 郭红玲

    2009-01-01

    目的 探讨自主开发的同胞关系鉴定自动分析软件(ASI)对ldentifiler分型系统进行同胞关系鉴定的可行性.方法 应用本课题组所开发的软件ASI,对151对同胞及31224对人工模拟拟无关个体进行Identifiler系统的15个常染色体STR基因座分型进行分析,计算亲权指数(PI)、同胞关系概率(W_ (FS))和等位基因匹配情况,所获数据进行统计分析,自动计算排序.结果 当W_ (FS)大于99.999%时,同胞个体占39.07%,无关个体占0%,两组具有显著差异,可以推断两个体同胞关系.当W_(FS)介于1%~99.999%范围内,同胞个体和无关个体有部分重叠,同胞个体占60.93%,无关个体占21.3%,两者具有一定差异,可以通过增加检测STR基因座,再结合案情加作Y-STR、mtDNA检测.以推断两个体是否具有同胞关系.当W_(FS)小于1%时,同胞个体占0%,无关个体占78.7%,可以推断两个体不具有同胞关系.个体间等位基因匹配结果表明:在检测Identifiler体系15个STR基因座时,当两个体常染色体STR基因座的全相同数目≥5时,或伞不同数目≤1时,提示为同胞关系;当两个体全不同数日≥6时,或伞相同数目≤1时.提示为无关个体,以此作为预测有无同胞关系的界值.结论 Identifiler系统及同胞关系鉴定自动分析软件ASI可用于推断同胞关系.%Objective To evaluate the probability of siblings identification in Identifiler system by using the software of automatic analysis.Methods Using the software of automatic analysis in siblings jdentification.STP genetic typing of 151 pairs of full siblings and 31224 pairs of unrelated individuals from manual simulation were analyzed in 15 STR loci of ldentifiler system.Results Kin probability(W_(FS))of 39.07% full siblings were more than 99.999% while W_(FS) of unrelated individual pairs were 0% .W_(FS) of 60.93% full siblings and 21.3% unrelated individual pairs were all at the range from 99.999% to 1% .W_(FS) of 78.7% unrelated

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

    Science.gov (United States)

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

    2013-11-01

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

  9. 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.

  10. Automatic Sarcasm Detection: A Survey

    OpenAIRE

    Joshi, Aditya; Bhattacharyya, Pushpak; Carman, Mark James

    2016-01-01

    Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, sarcasm detection has witnessed great interest from the sentiment analysis community. This paper is the first known compilation of past work in automatic sarcasm detection. We observe three milestones in the research so far: semi-supervised pat...

  11. People Detection and Re-Identification in Complex Environments

    Science.gov (United States)

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

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

  12. 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.

  13. 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.

  14. Automatic classification and speaker identification of African elephant (Loxodonta africana) vocalizations

    Science.gov (United States)

    Clemins, Patrick J.; Johnson, Michael T.; Leong, Kirsten M.; Savage, Anne

    2005-02-01

    A hidden Markov model (HMM) system is presented for automatically classifying African elephant vocalizations. The development of the system is motivated by successful models from human speech analysis and recognition. Classification features include frequency-shifted Mel-frequency cepstral coefficients (MFCCs) and log energy, spectrally motivated features which are commonly used in human speech processing. Experiments, including vocalization type classification and speaker identification, are performed on vocalizations collected from captive elephants in a naturalistic environment. The system classified vocalizations with accuracies of 94.3% and 82.5% for type classification and speaker identification classification experiments, respectively. Classification accuracy, statistical significance tests on the model parameters, and qualitative analysis support the effectiveness and robustness of this approach for vocalization analysis in nonhuman species. .

  15. 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.

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

    Institute of Scientific and Technical Information of China (English)

    邱意敏; 周力

    2012-01-01

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

  17. 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.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Simona M.C. Porto

    2013-09-01

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

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

    Science.gov (United States)

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

    2009-11-01

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

  1. Towards an automatic spectral and modal identification from operational modal analysis

    Science.gov (United States)

    Vu, V. H.; Thomas, M.; Lafleur, F.; Marcouiller, L.

    2013-01-01

    A method is developed for the automatic identification of the spectrum and modal parameters of an operational modal analysis using multi sensors. A multivariate autoregressive model is presented, and its parameters are estimated by least squares via the implementation of QR factorization. A noise-independent minimum model order, from which all available physical modes may be identified, is developed. This so-called optimal model order is selected from the convergence of a global order-wise signal-to-noise ratio index. At this model order or higher, the modes are classified based on a decreasing damped modal signal-to-noise (DMSN) criterion. This decreasing order classification allows for easy identification of all the physical modes. A significant change in the DMSN index enables the determination of the number of physical modes in a specific frequency range, and thus, an automatic procedure for identifying the modal parameters can be developed to discriminate harmonic and natural frequencies from spurious ones. Furthermore, a multispectral matrix can be constructed from selected frequencies by introducing a powered amplification factor, which provides a smooth, balanced, noise-free spectrum with all main peaks. The proposed method has been performed on simulated multi-degree-of-freedom systems, on a laboratory test bench, and on an industrial operating high power hydro-electric generator offering the potential for automatic operational modal analysis and structural health monitoring.

  2. Automatic detection and segmentation of lymph nodes from CT data.

    Science.gov (United States)

    Barbu, Adrian; Suehling, Michael; Xu, Xun; Liu, David; Zhou, S Kevin; Comaniciu, Dorin

    2012-02-01

    Lymph nodes are assessed routinely in clinical practice and their size is followed throughout radiation or chemotherapy to monitor the effectiveness of cancer treatment. This paper presents a robust learning-based method for automatic detection and segmentation of solid lymph nodes from CT data, with the following contributions. First, it presents a learning based approach to solid lymph node detection that relies on marginal space learning to achieve great speedup with virtually no loss in accuracy. Second, it presents a computationally efficient segmentation method for solid lymph nodes (LN). Third, it introduces two new sets of features that are effective for LN detection, one that self-aligns to high gradients and another set obtained from the segmentation result. The method is evaluated for axillary LN detection on 131 volumes containing 371 LN, yielding a 83.0% detection rate with 1.0 false positive per volume. It is further evaluated for pelvic and abdominal LN detection on 54 volumes containing 569 LN, yielding a 80.0% detection rate with 3.2 false positives per volume. The running time is 5-20 s per volume for axillary areas and 15-40 s for pelvic. An added benefit of the method is the capability to detect and segment conglomerated lymph nodes.

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

    Science.gov (United States)

    Qu, Ming

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

  4. Automatic Identification of Axis Orbit Based on Both Wavelet Moment Invariants and Neural Network

    Institute of Scientific and Technical Information of China (English)

    FuXiang-qian; LiuGuang-lin; JiangJing; LiYou-ping

    2003-01-01

    Axis orbit is an important characteristic to be used in the condition monitoring and diagnosis system of rotating machine. The wavelet moment has the invariant to the translation, scaling and rotation. A method, which uses a neural network based on Radial Basis Function (RBF) and wavelet moment invariants to identify the orbit of shaft centerline of rotating machine is discussed in this paper. The principle and its application procedure of the method are introduced in detail. It gives simulation results of automatic identification for three typical axis orbits. It is proved that the method is effective and practicable.

  5. Automatic Identification of Axis Orbit Based on Both Wavelet Moment Invariants and Neural Network

    Institute of Scientific and Technical Information of China (English)

    Fu Xiang-qian; Liu Guang-lin; Jiang Jing; Li You-ping

    2003-01-01

    Axis orbit is an important characteristic to be used in the condition monitoring and diagnosis system of rota-ting machine. The wavelet moment has the invariant to the translation, scaling and rotation. A method, which uses a neural network based on Radial Basis Function (RBF) and wavelet moment invariants to identify the orbit of shaft centerline of rotating machine is discussed in this paper. The principle and its application procedure of the method are intro-duced in detail. It gives simulation results of automatic identi-fication for three typical axis orbits. It is proved that the method is effective and practicable.

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

    Science.gov (United States)

    Paul, Peter; Hoover, Martin; Rabbani, Mojgan

    2013-03-01

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

  7. Design and test of a closed-loop FES system for supporting function of the hemiparetic hand based on automatic detection using the Microsoft Kinect sensor

    DEFF Research Database (Denmark)

    Simonsen, Daniel; Spaich, Erika G.; Hansen, John

    2017-01-01

    This paper describes the design of a FES system automatically controlled in a closed loop using a Microsoft Kinect sensor, for assisting both cylindrical grasping and hand opening. The feasibility of the system was evaluated in real-time in stroke patients with hand function deficits. A hand...

  8. Automatic Language Identification

    Science.gov (United States)

    2000-08-01

    Phonology . A "phoneme" is an underlying men- THIS WORK WAS SPONSORED BY THE DEPARTMENT tal representation of a phonological unit in a lan- OF DEFENSE...34 is a realization of an acoustic- FORCE. phonetic unit or segment. It is the actual sound 106 ACOUSTIC AND LANGUAGE MODEL LIBRARY AFRIKAANS...LID. HMM-based language identification phonetic transcription (sequence of symbols representing was first proposed by House and Neuburg [17]. Savic

  9. Shipborne automatic identification system%船载自动识别系统

    Institute of Scientific and Technical Information of China (English)

    叶猛; 高璐; 纪圣谋; 葛中芹; 徐健健

    2013-01-01

    提出了一种满足TDMA相关协议的新型船载自动识别系统设计.系统选用基于ARM7TDMI核的S3C44130X处理器,配合一款基带信号处理器芯片CMX910.设计的船载自动识别系统实现了ITDMA、RATDMA和SOTDMA的通信协议,实现了系统同步、发射和接收工作的要求,并完成了键盘与显示系统之间进行信息交互等所有主题通信软件的设计.进行了直接连接I/Q信号,通过转发器获取发送、接收信号,以及改变发送率等相关试验.相关与发射接收速率改变关系分析,并完成了整机的运行试验.试验结果表明:系统可以正确入网,并与其他船载设备以及基站之间进行正常稳定的信息收发工作.%This paper presents a new shipborne automatic identification system (AIS) meeting with the TDMA communication protocol. This system takes S3C44130X of ARM7TDMI as the processor and implements the ITDMA, RATDMA and SOTDMA communication protocol,and completes the synchronization,transmission and reception. The system designed in this paper also accomplishes the software design of communication between the keyboard and display system,and so on. We have done some related experiments such as connecting the I/Q signal directly,transmitting and receiving with the transponder, changing the transmitting rate, and running the whole system. The whole system works well and can communicate with other mobile station on vessels and base station very well according to the communication protocol.

  10. Exciter system identification and automatic tuning of linear combination-type power system stabilizers Prony analysis; Prony kaiseki ni motozuku reijikei no dotei to hiritsu kasangata PSS no jido sekkei hoho

    Energy Technology Data Exchange (ETDEWEB)

    Amano, M.; Watanabe, M.; Banjo, M. [Hitachi, Ltd., Tokyo (Japan)

    1997-07-01

    The objective of this paper is to present anew automatic tuning method of power system stabilizers using Prony analysis. Irony analysis is used for detecting oscillation frequency, damping, phase, and amplitude from power oscillation waveform data. By applying the method to the waveform data of stabilizing signal and internal induced voltage, exciter system phase lag and oscillation frequency can be identified, and control parameters are decided using the identified values. Linear combination-type power system stabilizers are effective for damping low frequency oscillations using two control input signals, generator power and bus voltage frequency. The control parameters can be directly derived from the oscillation frequency and the excitation system phase lag without using phase compensation. Simulation results show that the proposed method is effective both in one machine-infinite bus system and in a multimachine system. The method can be used for off-line controller design and also for on-line adaptive control. 9 refs., 15 figs., 4 tabs.

  11. 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

  12. 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.

  13. 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.

  14. Developing a system that can automatically detect health changes using transfer times of older adults

    Directory of Open Access Journals (Sweden)

    Greet Baldewijns

    2016-02-01

    Full Text Available Abstract Background As gait speed and transfer times are considered to be an important measure of functional ability in older adults, several systems are currently being researched to measure this parameter in the home environment of older adults. The data resulting from these systems, however, still needs to be reviewed by healthcare workers which is a time-consuming process. Methods This paper presents a system that employs statistical process control techniques (SPC to automatically detect both positive and negative trends in transfer times. Several SPC techniques, Tabular cumulative sum (CUSUM chart, Standardized CUSUM and Exponentially Weighted Moving Average (EWMA chart were evaluated. The best performing method was further optimized for the desired application. After this, it was validated on both simulated data and real-life data. Results The best performing method was the Exponentially Weighted Moving Average control chart with the use of rational subgroups and a reinitialization after three alarm days. The results from the simulated data showed that positive and negative trends are detected within 14 days after the start of the trend when a trend is 28 days long. When the transition period is shorter, the number of days before an alert is triggered also diminishes. If for instance an abrupt change is present in the transfer time an alert is triggered within two days after this change. On average, only one false alarm is triggered every five weeks. The results from the real-life dataset confirm those of the simulated dataset. Conclusions The system presented in this paper is able to detect both positive and negative trends in the transfer times of older adults, therefore automatically triggering an alarm when changes in transfer times occur. These changes can be gradual as well as abrupt.

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

    Directory of Open Access Journals (Sweden)

    Kamaruddin Abd Ghani

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jie Su

    2016-01-01

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

  17. 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. .

  18. MOTOR VEHICLE SAFETY: NHTSA’s Ability to Detect and Recall Defective Replacement Crash Parts Is Limited

    Science.gov (United States)

    2001-01-01

    recycled airbag systems. However, NHTSA’s defect identification and recall system has limitations. The key database used to identify unsafe parts...product safety recall . The two studies on the safety of recycled airbags that we identified concluded that they can be a potentially safe...GAO United States General Accounting OfficeReport to Congressional RequestersJanuary 2001 MOTOR VEHICLE SAFETY NHTSA’s Ability to Detect and Recall

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

    Science.gov (United States)

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

    2015-03-01

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

  20. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Attayek, P.J. [Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431 (United States); Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7575 (United States); Meyer, E.S.; Lin, L. [Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431 (United States); Rich, G.C.; Clegg, T.B. [Triangle Universities Nuclear Laboratory (TUNL), Durham, NC 27708-0308 (United States); Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3255 (United States); Coronell, O., E-mail: coronell@unc.edu [Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431 (United States)

    2012-06-01

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

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

    Science.gov (United States)

    de Blas, Maite; Navazo, Marino; Alonso, Lucio; Durana, Nieves; Iza, Jon

    2011-11-15

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Blas, Maite de, E-mail: maite.deblas@ehu.es [Chemical and Environmental Engineering Department, University College of Technical Mining and Civil Engineering, University of the Basque Country, Colina de Beurco s/n, 48902 Barakaldo (Spain); Navazo, Marino; Alonso, Lucio; Durana, Nieves [Chemical and Environmental Engineering Department, School of Engineering, University of the Basque Country, Alameda de Urquijo s/n, 48013 Bilbao (Spain); Iza, Jon [Chemical and Environmental Engineering Department, Faculty of Pharmacy, University of the Basque Country, Paseo de la Universidad, 7, 01006, Vitoria-Gasteiz (Spain)

    2011-11-15

    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 C{sub 2}-C{sub 11} 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.

  4. 智能车载酒精检测及控制器设计%Intelligent Vehicle Alcohol Detection and Control System Design

    Institute of Scientific and Technical Information of China (English)

    万刘蝉; 付崇芳; 徐鑫刚; 周印亮; 李刚刚

    2012-01-01

    本文介绍了一种基于单片机低功耗酒精检测控制器,该控制器采用酒精传感器、压力传感器、语音报警、电子锁等与汽车组成车载酒精检测及安全控制系统。该系统可分为两部分:一个为检测部分,可手持,另一个为控制部分,安装于车内,从而实现智能车载酒精检测及安全控制。由于该系统具有高灵敏度和低功耗的功能,因此具有较高的实用价值。%This paper introduces a microcomputer-based low-power alcohol detection controller, the controller uses alcohol sensors, pressure sensors, voice alarm, electronic locks and automotive components vehicle alcohol detection and safety control system, the system can be divided into two parts, one for detecting part, can be hand-held, another for control part, installed in a vehicle, thus realizing the intelligent vehicle security control services. Because the system has the advantages of high sensitivity and low power consumption function, so it has practical and market value.

  5. Study on the Framework of Vehicle Automatic Navigation System%车辆自动导航系统基本框架研究

    Institute of Scientific and Technical Information of China (English)

    张可; 刘小明; 王笑京

    2001-01-01

    讨论了车辆自动导航系统的基本框架,将其划分为路网数据库管理、车辆定位、路线优化、路线引导4个子系统,并提出了各个子系统需要实现的功能,以及实现这些功能所需的关键技术%As one of the important research aspect of IntelligentTransportation System (ITS), the technique of vehicle automatic navigation has shown great prospect for application. This paper discusses the framework of the vehicle automatic navigation system, which could be divided into four subsystems: the database management subsystem for the road networks, the vehicle positioning subsystem, the route planning subsystem and the route guidance subsystem. The functions of each subsystem and the key techniques for realizing these functions are proposed.

  6. Complete approach to automatic identification and subpixel center location for ellipse feature

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    To meet the need of automatic image features extraction with high precision in visual inspection, a complete approach to automatic identification and sub-pixel center location for similar-ellipse feature is proposed. In the method, the feature area is identified automatically based on the edge attribute, and the sub-pixel center location is accomplished with the leastsquare algorithm. It shows that the method is valid, practical, and has high precision by experiment. Meanwhile this method can meet the need of instrumentation of visual inspection because of easy realization and without man-machine interaction.

  7. Vehicle detection and tracking based on phase-correlation

    Institute of Scientific and Technical Information of China (English)

    Yi He(何毅); Xin Yang(杨新)

    2004-01-01

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

  8. 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.

  9. 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.

  10. Vehicle management system-system analysis and design

    Institute of Scientific and Technical Information of China (English)

    CHENG Ke-fei; LONG Hua; ZHANG Cong

    2004-01-01

    This paper presents one of GPS Vehicle Monitor System on base of Web-GIS technology, which is very important in vehicle tracking, scheduling and management. In the paper, a real GPS vehicle monitor system which using Internet technology is introduced. This system have been putted into practice successfully.

  11. 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 ...

  12. 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.

  13. Mastitis therapy and control - Automatic on-line detection of abnormal milk.

    NARCIS (Netherlands)

    Hogeveen, H.

    2011-01-01

    Automated online detection of mastitis and abnormal milk is an important subject in the dairy industry, especially because of the introduction of automatic milking systems and the growing farm sizes with consequently less labor available per cow. Demands for performance, which is expressed as sensit

  14. Multiple damage identification and imaging in an aluminum plate using effective Lamb wave response automatic extraction technology

    Science.gov (United States)

    Ouyang, Qinghua; Zhou, Li; Liu, Xiaotong

    2016-04-01

    In order to identify multiple damage in the structure, a method of multiple damage identification and imaging based on the effective Lamb wave response automatic extraction algorithm is proposed. In this method, the detected key area in the structure is divided into a number of subregions, and then, the effective response signals including the structural damage information are automatically extracted from the entire Lamb wave responses which are received by the piezoelectric sensors. Further, the damage index values of every subregion based on the correlation coefficient are calculated using the effective response signals. Finally, the damage identification and imaging are performed using the reconstruction algorithm for probabilistic inspection of damage (RAPID) technique. The experimental research was conducted using an aluminum plate. The experimental results show that the method proposed in this research can quickly and effectively identify the single damage or multiple damage and image the damages clearly in detected area.

  15. Automatic identification for standing tree limb pruning

    Institute of Scientific and Technical Information of China (English)

    Sun Renshan; Li Wenbin; Tian Yongchen; Hua Li

    2006-01-01

    To meet the demand of automatic pruning machines,this paper presents a new method for dynamic automatic identification of standing tree limbs and capture of the digital images of Platycladus orientalis.Methods of computer vision,image processing and wavelet analysis technology were used to compress,filter,segment,abate noise and capture the outline of the picture.We then present the arithmetic for dynamic automatic identification of standing tree limbs,extracting basic growth characteristics of the standing trees such as the form,size,degree of bending and their relative spatial position.We use pattern recognition technology to confirm the proportionate relationship matching the database and thus achieve the goal of dynamic automatic identification of standing tree limbs.

  16. 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 ...

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

    Directory of Open Access Journals (Sweden)

    Ján HALGAŠ

    2014-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Kanwal Yousaf

    2012-09-01

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

  19. Vision-based Vehicle Detection Survey

    Directory of Open Access Journals (Sweden)

    Alex David S

    2016-03-01

    Full Text Available Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

  20. System identification of mechanomyograms detected with an acceleration sensor and a laser displacement meter.

    Science.gov (United States)

    Uchiyama, Takanori; Shinohara, Keita

    2011-01-01

    The purpose of this study is to investigate the transfer functions of mechanomyograms (MMGs) detected with an acceleration sensor and a laser displacement meter. The MMGs evoked by electrical stimulation to the peroneal nerve were recorded on the skin of the tibial anterior muscle. The displacement MMG (DMMG) and the acceleration MMG (AMMG) systems were identified using a singular value decomposition method. The appropriate order of the AMMG system was six and that of the DMMG system was four. The undamped natural frequencies of the systems were compared to resonance frequencies of human soft tissue. Some of the undamped natural frequencies estimated from the AMMG systems agreed with the resonance frequencies in the literature but others were lower than the resonance frequencies. The undamped natural frequencies estimated from the DMMG systems were lower than the resonance frequencies.

  1. Robust Vehicle Detection under Various Environmental Conditions Using an Infrared Thermal Camera and Its Application to Road Traffic Flow Monitoring

    Directory of Open Access Journals (Sweden)

    Toshiyuki Nakamiya

    2013-06-01

    Full Text Available We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as “our previous method” using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as “our new method”. Our new method detects vehicles based on tires’ thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8% out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal.

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

    Institute of Scientific and Technical Information of China (English)

    张建荣; 李闻捷; 徐德安

    2002-01-01

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

  3. Automatic basal slice detection for cardiac analysis

    Science.gov (United States)

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

    2016-03-01

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

  4. 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.

  5. Automatic Control of Personal Rapid Transit Vehicles

    Science.gov (United States)

    Smith, P. D.

    1972-01-01

    The requirements for automatic longitudinal control of a string of closely packed personal vehicles are outlined. Optimal control theory is used to design feedback controllers for strings of vehicles. An important modification of the usual optimal control scheme is the inclusion of jerk in the cost functional. While the inclusion of the jerk term was considered, the effect of its inclusion was not sufficiently studied. Adding the jerk term will increase passenger comfort.

  6. Automatic Detection and Processing of Attributes Inconsistency for Fuzzy Ontologies Merging

    Directory of Open Access Journals (Sweden)

    Yonghong Luo

    2013-11-01

    Full Text Available Semantic fusion of multiple data sources and semantic interoperability between heterogeneous systems in distributed environment can be implemented through integrating multiple fuzzy local ontologies. However, ontology merging is one of the valid ways for ontology integration. In order to solve the problem of attributes inconsistency for concept mapping in fuzzy ontology merging system, we present an automatic detection algorithm of inconsistency for the range, number and membership grade of attributes between mapping concepts, and adopt corresponding processing strategy during the fuzzy ontologies merging according to the different types of attributes inconsistency. Experiment results show that with regard to merging accuracy, the fuzzy ontology merging system in which the automatic detection algorithm and processing strategy of attributes inconsistency is embedded is better than those traditional ontology merging systems like GLUE, PROMPT and Chimaera.    

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

    Directory of Open Access Journals (Sweden)

    Hans Frimmel

    2001-01-01

    Full Text Available 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 paper, is based on a model of the slices and the landmark needles. The method has been used to register slices of prostates in order to create 3D computer models. Manual registration of the same prostates has been undertaken and compared with the results from the algorithm. Methods. Prostates from sixteen men who underwent radical prostatectomy were formalin fixed with landmark needles, sliced and the slices were computer reconstructed. The cost function takes rotation and translation for each prostate slice, as well as slope and offset for each landmark needle as input. The current quality of fit of the model, using the input parameters given, is returned. The function takes the built‐in instability of the model into account. The method uses a standard algorithm to optimize the prostate slice positions. To verify the result, s standard method in statistics was used. Results. The methods were evaluated for 16 prostates. When testing blindly, a physician could not determine whether the registration shown to him were created by the automated method described in this paper, or manually by an expert, except in one out of 16 cases. Visual inspection and analysis of the outlier confirmed that the input data had been deformed. The automatic detection of erroneous slices marked a few slices, including the outlier, as suspicious. Conclusions. The model based registration performs better than traditional simple slice‐wise registration. In the case of prostate

  8. Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

    Science.gov (United States)

    Gisser, D. G.; Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Yerazunis, S. Y.

    1975-01-01

    Problems related to an unmanned exploration of the planet Mars by means of an autonomous roving planetary vehicle are investigated. These problems include: design, construction and evaluation of the vehicle itself and its control and operating systems. More specifically, vehicle configuration, dynamics, control, propulsion, hazard detection systems, terrain sensing and modelling, obstacle detection concepts, path selection, decision-making systems, and chemical analyses of samples are studied. Emphasis is placed on development of a vehicle capable of gathering specimens and data for an Augmented Viking Mission or to provide the basis for a Sample Return Mission.

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

    Science.gov (United States)

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

    2013-07-01

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

  10. 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.

  11. 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.

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

    Science.gov (United States)

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

    2009-01-01

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

  13. Automatic detection and measurement of femur length from fetal ultrasonography

    Science.gov (United States)

    Mukherjee, Prateep; Swamy, Gokul; Gupta, Madhumita; Patil, Uday; Krishnan, Kajoli Banerjee

    2010-03-01

    Femur bone length is used in the assessment of fetal development and in the prediction of gestational age (GA). In this paper, we present a completely automated two-step method for identifying fetal femur and measuring its length from 2D ultrasound images. The detection algorithm uses a normalized score premised on the distribution of anatomical shape, size and presentation of the femur bone in clinically acceptable scans. The measurement process utilizes a polynomial curve fitting technique to determine the end-points of the bone from a 1D profile that is most distal from the transducer surface. The method has been tested with manual measurements made on 90 third trimester femur images by two radiologists. The measurements made by the experts are strongly correlated (Pearson's coefficient = 0.95). Likewise, the algorithm estimate is strongly correlated with expert measurements (Pearson's coefficient = 0.92 and 0.94). Based on GA estimates and their bounds specified in Standard Obstetric Tables, the GA predictions from automated measurements are found to be within +/-2SD of GA estimates from both manual measurements in 89/90 cases and within +/-3SD in all 90 cases. The method presented in this paper can be adapted to perform automatic measurement of other fetal limbs.

  14. Navigation System for Reusable Launch Vehicle

    OpenAIRE

    Schlotterer, Markus

    2008-01-01

    PHOENIX is a downscaled experimental vehicle to demonstrate automatic landing capabilities of future Reusable Launch Vehicles (RLVs). PHOENIX has flown in May 2004 at NEAT (North European Aerospace Test range) in Vidsel, Sweden. As the shape of the vehicle has been designed for re-entry, the dynamics are very high and almost unstable. This requires a fast and precise GNC system. This paper describes the navigation system and the navigation filter of PHOENIX. The system is introduced and the h...

  15. Automatic and Intelligent Power Quality Disturbances Monitoring Based on Multi-Agent Systems

    Directory of Open Access Journals (Sweden)

    M. Hajian

    2012-09-01

    Full Text Available Power quality monitoring is the first step in the identification of power quality disturbances and reducing them in order to improve the performance of the power system. The aim of this paper is to propose the architecture of a new intelligent strategy for online and offline power quality monitoring system based on multi-agent systems. In this study, a multi-agent system for solving some problems in power quality monitoring, including computational complexity, low accuracy, change in the data pattern, non adaptive structure of detection system to changing conditions is proposed. In the proposed strategy, the agent characteristics, such as automatic and dynamic performance, intelligent, learning, reasoning ability, objectively and interoperability of agents are used. This paper is presented in two stages. In the one stage, to indicate problems in power quality monitoring, different methods of feature extraction, feature selection and classification for automatic recognition of power quality disturbances have been analyzed. Optimal selection of input feature vector of distinguish system is applied using different methods of data mining. Also, three well-known classifiers are considered. In another stage of the paper, to solve some challenges, the design of investigated structures in the form of a multi-agent system is expressed. The results of the experiments in this paper demonstrate the superiority of agents and multi-agent systems for online and offline power quality monitoring.

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

    Science.gov (United States)

    Ahmad, S R

    2004-10-01

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

  17. Fundamental problems in fault detection and identification

    DEFF Research Database (Denmark)

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

    1999-01-01

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

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

    Science.gov (United States)

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

    2016-09-01

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

  19. 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...... 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 the superheat dynamic in a Danfoss...... be performed by identifying these fault related parameters. Afterwards, the decision whether the fault happened or how large the fault is can be made by comparison and analysis based on the estimated values....

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

    Science.gov (United States)

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

    1989-01-01

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

  1. 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.

  2. 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.

  3. Detection and identification of novel actinomycetes.

    Science.gov (United States)

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

    1993-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Mostafa Rabah

    2013-12-01

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

  5. Automatic Cell Detection in Bright-Field Microscope Images Using SIFT, Random Forests, and Hierarchical Clustering.

    Science.gov (United States)

    Mualla, Firas; Scholl, Simon; Sommerfeldt, Bjorn; Maier, Andreas; Hornegger, Joachim

    2013-12-01

    We present a novel machine learning-based system for unstained cell detection in bright-field microscope images. The system is fully automatic since it requires no manual parameter tuning. It is also highly invariant with respect to illumination conditions and to the size and orientation of cells. Images from two adherent cell lines and one suspension cell line were used in the evaluation for a total number of more than 3500 cells. Besides real images, simulated images were also used in the evaluation. The detection error was between approximately zero and 15.5% which is a significantly superior performance compared to baseline approaches.

  6. 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.

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

    Science.gov (United States)

    Dong, Jianfei; van Driel, Willem; Zhang, Guoqi

    2011-03-28

    This paper describes a new design concept of automatically diagnosing and compensating LED degradations in distributed solid state lighting (SSL) systems. A failed LED may significantly reduce the overall illumination level, and destroy the uniform illumination distribution achieved by a nominal system. To our knowledge, an automatic scheme to compensate LED degradations has not yet been seen in the literature, which requires a diagnostic step followed by control reconfigurations. The main challenge in diagnosing LED degradations lies in the usually unsatisfactory observability in a distributed SSL system, because the LED light output is usually not individually measured. In this work, we tackle this difficulty by using pulse width modulated (PWM) drive currents with a unique fundamental frequency assigned to each LED. Signal processing methods are applied in estimating the individual illumination flux of each LED. Statistical tests are developed to diagnose the degradation of LEDs. Duty cycle of the drive current signal to each LED is re-optimized once a fault is detected, in order to compensate the destruction of the uniform illumination pattern by the failed LED.

  8. Toward the Automatic Identification of Sublanguage Vocabulary.

    Science.gov (United States)

    Haas, Stephanie W.; He, Shaoyi

    1993-01-01

    Describes the development of a method for the automatic identification of sublanguage vocabulary words as they occur in abstracts. Highlights include research relating to sublanguages and their vocabulary; domain terms; evaluation criteria, including recall and precision; and implications for natural language processing and information retrieval.…

  9. Semi-automatic identification photo generation with facial pose and illumination normalization

    Science.gov (United States)

    Jiang, Bo; Liu, Sijiang; Wu, Song

    2016-07-01

    Identification photo is a category of facial image that has strict requirements on image quality like size, illumination, user expression, dressing, etc. Traditionally, these photos are taken in professional studios. With the rapid popularity of mobile devices, how to conveniently take identification photo at any time and anywhere with such devices is an interesting problem. In this paper, we propose a novel semi-automatic identification photo generation approach. Given a user image, facial pose and expression are first normalized to meet the basic requirements. To correct uneven lighting condition in photo, an facial illumination normalization approach is adopted to further improve the image quality. Finally, foreground user is extracted and re-targeted to a specific photo size. Besides, background can also be changed as required. Preliminary experimental results show that the proposed method is efficient and effective in identification photo generation compared to commercial software based manual tunning.

  10. 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.

  11. Automatic Fall Detection using Smartphone Acceleration Sensor

    Directory of Open Access Journals (Sweden)

    Tran Tri Dang

    2016-12-01

    Full Text Available In this paper, we describe our work on developing an automatic fall detection technique using smart phone. Fall is detected based on analyzing acceleration patterns generated during various activities. An additional long lie detection algorithm is used to improve fall detection rate while keeping false positive rate at an acceptable value. An application prototype is implemented on Android operating system and is used to evaluate the proposed technique performance. Experiment results show the potential of using this app for fall detection. However, more realistic experiment setting is needed to make this technique suitable for use in real life situations.

  12. Detection and Classification of Motor Vehicle Noise in a Forested Landscape

    Science.gov (United States)

    Brown, Casey L.; Reed, Sarah E.; Dietz, Matthew S.; Fristrup, Kurt M.

    2013-11-01

    Noise emanating from human activity has become a common addition to natural soundscapes and has the potential to harm wildlife and erode human enjoyment of nature. In particular, motor vehicles traveling along roads and trails produce high levels of both chronic and intermittent noise, eliciting varied responses from a wide range of animal species. Anthropogenic noise is especially conspicuous in natural areas where ambient background sound levels are low. In this article, we present an acoustic method to detect and analyze motor vehicle noise. Our approach uses inexpensive consumer products to record sound, sound analysis software to automatically detect sound events within continuous recordings and measure their acoustic properties, and statistical classification methods to categorize sound events. We describe an application of this approach to detect motor vehicle noise on paved, gravel, and natural-surface roads, and off-road vehicle trails in 36 sites distributed throughout a national forest in the Sierra Nevada, CA, USA. These low-cost, unobtrusive methods can be used by scientists and managers to detect anthropogenic noise events for many potential applications, including ecological research, transportation and recreation planning, and natural resource management.

  13. Automatic spikes detection in seismogram

    Institute of Scientific and Technical Information of China (English)

    王海军; 靳平; 刘贵忠

    2003-01-01

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

  14. Target Acquisition and Analysis Training System: Evaluation of the Basic Thermal Combat Vehicle Identification (TCVI) Training Program

    Science.gov (United States)

    1987-11-01

    TCVI training, or vice versa) was important. Both types of training were given, preceded, and followed by the corresponding photopic or thermal test . Because...70%) or 19D (15%) MOS. Training Procedure At both sites, soldiers were tested on a CVI/ Thermal test before and after training on 120 slides composed...miltary unit. Only thermal training was to be given to tank crews. They were measured before and after training on the CVI/ Thermal test . The soldiers

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

    DEFF Research Database (Denmark)

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

    1998-01-01

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

  16. 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.

  17. 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.

  18. Electromagnetic Detection and Identification of Complex Structures

    Science.gov (United States)

    2008-12-01

    1 ELECTROMAGNETIC DETECTION AND IDENTIFICATION OF COMPLEX STRUCTURES I. Kohlberg Kohlberg Associates Reston, Virginia, 20190-4440 S.A...TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Kohlberg Associates Reston, Virginia, 20190-4440 8...Electromagnetic Theory, 2 nd ed. IEEE Press, New York. von Laven, S.A., Albritton, N.G., Baginski, T.A., Hodel, A.S., McMillan, R.W., Kohlberg

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

    NARCIS (Netherlands)

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

    2010-01-01

    An automatic image classification system based on support vector machines (SVM) has been in operation for years in the TJ-II Thomson Scattering diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge, imag

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

    Directory of Open Access Journals (Sweden)

    Yingfeng Cai

    2016-01-01

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

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

    Science.gov (United States)

    Iwasaki, Yoichiro; Kawata, Shinya; Nakamiya, Toshiyuki

    2011-08-01

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

  2. Automatic and Hierarchical Verification for Concurrent Systems

    Institute of Scientific and Technical Information of China (English)

    赵旭东; 冯玉琳

    1990-01-01

    Proving correctness of concurrent systems is quite difficult because of the high level of nondeterminism,especially in large and complex ones.AMC is a model checking system for verifying asynchronous concurrent systems by using branching time temporal logic.This paper introduces the techniques of the modelling approach,especially how to construct models for large concurrent systems with the concept of hierarchy,which has been proved to be effective and practical in verifying large systems without a large growth of cost.

  3. Mathematical Techniques for System Realization and Identification.

    Science.gov (United States)

    1986-02-26

    IEEE Transactions on Automatic Control , AC-27: 196-198. J...and P. P. KHARGONEKAR- (1982] "Regulation of split linear systems over rings: coefficient assignment and observers", IEEE Transactions on Automatic Control , AC...Journal on Control and Optimization, 20: 497-505. (1983a] "Linear dynamic output feedback: invariants and stability", .%.. 0 IEEE Transactions on Automatic Control ,

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

    Science.gov (United States)

    Gomer, Nathaniel R.; Gardner, Charles W.

    2014-05-01

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

  5. Research in Adaptronic Automatic Control System and Biosensor System Modelling

    Directory of Open Access Journals (Sweden)

    Skopis Vladimir

    2015-07-01

    Full Text Available This paper describes the research on adaptronic systems made by the author and offers to use biosensors that can be later inserted into the adaptronic systems. Adaptronic systems are based, on the one hand, on the adaptronic approach when the system is designed not to always meet the worst condition, but to change the structure of the system according to the external conditions. On the other hand, it is an extension of common automatic control ad adaptive systems. So, in the introduction firstly the adaptronic approach and biosensor as a term is explained. Adaptive systems, upon which adaptronic ones are based, are also mentioned. Then the construction of biosensor is described, as well as some information is given about the classification of biosensors and their main groups. Also it is suggested to use lichen indicators in industry to control concentration of chemical substances in the air. After that mathematical models and computer experiments for adaptronic system and biosensor analysis are given.

  6. 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.

  7. 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

  8. Robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels

    Institute of Scientific and Technical Information of China (English)

    Niu Erzhuo; Wang Qing; Dong Chaoyang

    2014-01-01

    The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective-ness of the proposed approach.

  9. 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.

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

    Science.gov (United States)

    Kang, Min-Joo; Kang, Je-Won

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jia Wei Tang

    2016-01-01

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

  12. Multibody simulation of vehicles equipped with an automatic transmission

    Science.gov (United States)

    Olivier, B.; Kouroussis, G.

    2016-09-01

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

  13. 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。

  14. 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...

  15. Automatic identification and restriction of the cointegration space

    NARCIS (Netherlands)

    Omtzigt, P.H.

    2003-01-01

    We automate the process of finding the cointegration relations in a cointegrated VAR. There is a rigorous separation between the theory part (search directions must be defined, a final model chosen) and the automated search. The decision rules are set in such a way that a theoretical upper limit can

  16. Automatic type classification and speaker identification of african elephant (Loxodonta africana) vocalizations

    Science.gov (United States)

    Clemins, Patrick J.; Johnson, Michael T.

    2003-04-01

    This paper presents a system for automatically classifying African elephant vocalizations based on systems used for human speech recognition and speaker identification. The experiments are performed on vocalizations collected from captive elephants in a naturalistic environment. Features used for classification include Mel-Frequency Cepstral Coefficients (MFCCs) and log energy which are the most common features used in human speech processing. Since African elephants use lower frequencies than humans in their vocalizations, the MFCCs are computed using a shifted Mel-Frequency filter bank to emphasize the infrasound range of the frequency spectrum. In addition to these features, the use of less traditional features such as those based on fundamental frequency and the phase of the frequency spectrum is also considered. A Hidden Markov Model with Gaussian mixture state probabilities is used to model each type of vocalization. Vocalizations are classified based on type, speaker and estrous cycle. Experiments on continuous call type recognition, which can classify multiple vocalizations in the same utterance, are also performed. The long-term goal of this research is to develop a universal analysis framework and robust feature set for animal vocalizations that can be applied to many species.

  17. An Automatic Number Plate Recognition System under Image Processing

    OpenAIRE

    Sarbjit Kaur

    2016-01-01

    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 whol...

  18. 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.

  19. 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.

  20. Multichannel System Identification and Detection Using Output Data Techniques. Volume 1

    Science.gov (United States)

    1997-05-01

    that originate in the sinus node fibers pass on to the three internodal pathways that extend from the sinus node to the atrioventricular (A-V) node...constitute the cardiac conduction system and are referred to as nodes, pathways , bundles, and bundle branches. Conduction system fibers lack contractile...node A-V bundle Internodal Left bundlepathwaysf "-..’. - -. ..... /o ,"branch Right .- atrium R ight --------------- .... ventricle Right bundle Apex

  1. Design and Test of a Closed-Loop FES System for Supporting Function of the Hemiparetic Hand Based on Automatic Detection using the Microsoft Kinect sensor.

    Science.gov (United States)

    Simonsen, Daniel; Spaich, Erika G; Hansen, John; Andersen, Ole K

    2016-10-26

    This paper describes the design of a FES system automatically controlled in a closed loop using a Microsoft Kinect sensor, for assisting both cylindrical grasping and hand opening. The feasibility of the system was evaluated in real-time in stroke patients with hand function deficits. A hand function exercise was designed in which the subjects performed an arm and hand exercise in sitting position. The subject had to grasp one of two differently sized cylindrical objects and move it forward or backwards in the sagittal plane. This exercise was performed with each cylinder with and without FES support. Results showed that the stroke patients were able to perform up to 29% more successful grasps when they were assisted by FES. Moreover, the hand grasp-and-hold and hold-and-release durations were shorter for the smaller of the two cylinders. FES was appropriately timed in more than 95% of all trials indicating successful closed loop FES control. Future studies should incorporate options for assisting forward reaching in order to target a larger group of stroke patients.

  2. 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.

  3. Automatic Detection and Vulnerability Analysis of Areas Endangered by Heavy Rain

    Science.gov (United States)

    Krauß, Thomas; Fischer, Peter

    2016-08-01

    In this paper we present a new method for fully automatic detection and derivation of areas endangered by heavy rainfall based only on digital elevation models. Tracking news show that the majority of occuring natural hazards are flood events. So already many flood prediction systems were developed. But most of these existing systems for deriving areas endangered by flooding events are based only on horizontal and vertical distances to existing rivers and lakes. Typically such systems take not into account dangers arising directly from heavy rain events. In a study conducted by us together with a german insurance company a new approach for detection of areas endangered by heavy rain was proven to give a high correlation of the derived endangered areas and the losses claimed at the insurance company. Here we describe three methods for classification of digital terrain models and analyze their usability for automatic detection and vulnerability analysis for areas endangered by heavy rainfall and analyze the results using the available insurance data.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-08-24

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

  5. 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.

  6. 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 ...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1992-01-01

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

  8. 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.

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

    Science.gov (United States)

    1992-11-01

    Parameters ................... 18 V Description of Amplification and Digitalisation Parameters ...... ... 19 VI Manufacturer’s Properties of the...UNCLASSIFIED 19 Table V Description of Amplification and Digitalisation Parameters Preamplifier Manufacturer Perry Amplifier Transimpedance Gain 200K V/A...the six different mines used in this study are shown. Their name, the mine type (anti-tank or anti-personnel), and the construction material are

  10. Critique of Test Methodologies for Biological Agent Detection and Identification Systems for Military and First Responders

    Science.gov (United States)

    2002-01-01

    Critical Control Point ( HACCP ) programs within the food industry worldwide (Cutter et al., 1996). Additionally, the ATP test with Luciferin Luciferase...Cutter, C. N., W. J. Dorsa, and G. R. Siragusa. 1996. A rapid microbial ATP bioluminescence assay for meat carcasses. Dairy, Food & Environ. San. 16...No. 73. In program and abstract book, 83rd Annual Meeting of IAMFES, p. 50. 6. Northcutt, J., and S. M. Russell. 1996. Making HACCP happen in your

  11. Systems and methods for vehicle speed management

    Energy Technology Data Exchange (ETDEWEB)

    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.

  12. Constrained and regularized system identification

    Directory of Open Access Journals (Sweden)

    Tor A. Johansen

    1998-04-01

    Full Text Available Prior knowledge can be introduced into system identification problems in terms of constraints on the parameter space, or regularizing penalty functions in a prediction error criterion. The contribution of this work is mainly an extension of the well known FPE (Final Production Error statistic to the case when the system identification problem is constrained and contains a regularization penalty. The FPECR statistic (Final Production Error with Constraints and Regularization is of potential interest as a criterion for selection of both regularization parameters and structural parameters such as order.

  13. 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.

  14. 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.

  15. 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.

  16. Gaussian Mixture Model and Deep Neural Network based Vehicle Detection and Classification

    Directory of Open Access Journals (Sweden)

    S Sri Harsha

    2016-09-01

    Full Text Available The exponential rise in the demand of vision based traffic surveillance systems have motivated academia-industries to develop optimal vehicle detection and classification scheme. In this paper, an adaptive learning rate based Gaussian mixture model (GMM algorithm has been developed for background subtraction of multilane traffic data. Here, vehicle rear information and road dash-markings have been used for vehicle detection. Performing background subtraction, connected component analysis has been applied to retrieve vehicle region. A multilayered AlexNet deep neural network (DNN has been applied to extract higher layer features. Furthermore, scale invariant feature transform (SIFT based vehicle feature extraction has been performed. The extracted 4096-dimensional features have been processed for dimensional reduction using principle component analysis (PCA and linear discriminant analysis (LDA. The features have been mapped for SVM-based classification. The classification results have exhibited that AlexNet-FC6 features with LDA give the accuracy of 97.80%, followed by AlexNet-FC6 with PCA (96.75%. AlexNet-FC7 feature with LDA and PCA algorithms has exhibited classification accuracy of 91.40% and 96.30%, respectively. On the contrary, SIFT features with LDA algorithm has exhibited 96.46% classification accuracy. The results revealed that enhanced GMM with AlexNet DNN at FC6 and FC7 can be significant for optimal vehicle detection and classification.

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

    Science.gov (United States)

    Tousi, M. M.; Khorasani, K.

    2015-01-01

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

  18. Automatic colonic lesion detection and tracking in endoscopic videos

    Science.gov (United States)

    Li, Wenjing; Gustafsson, Ulf; A-Rahim, Yoursif

    2011-03-01

    The biology of colorectal cancer offers an opportunity for both early detection and prevention. Compared with other imaging modalities, optical colonoscopy is the procedure of choice for simultaneous detection and removal of colonic polyps. Computer assisted screening makes it possible to assist physicians and potentially improve the accuracy of the diagnostic decision during the exam. This paper presents an unsupervised method to detect and track colonic lesions in endoscopic videos. The aim of the lesion screening and tracking is to facilitate detection of polyps and abnormal mucosa in real time as the physician is performing the procedure. For colonic lesion detection, the conventional marker controlled watershed based segmentation is used to segment the colonic lesions, followed by an adaptive ellipse fitting strategy to further validate the shape. For colonic lesion tracking, a mean shift tracker with background modeling is used to track the target region from the detection phase. The approach has been tested on colonoscopy videos acquired during regular colonoscopic procedures and demonstrated promising results.

  19. Research and Simulation of the Electrical Vehicle Based Dynamical System

    Directory of Open Access Journals (Sweden)

    Ko-Chun Chen

    2015-01-01

    Full Text Available This study developed a dynamic model of electric vehicle system by using the MATLAB/Simulink tool. The vehicle model comprises two system components: an electrical system and a suspension system. This study also designed various road conditions for simulating the motion of vehicle traveling along a road. The results show that the electrical and suspension system parameters can be adjusted immediately to enhance passenger comfort. The findings of this research have practical teaching applications. Students can modify the vehicle model parameters byes using the MATLAB graphical user interface, allowing them to observe the motion of vehicle under various road conditions.

  20. Modeling and identification of flexible joints in vehicle structures

    OpenAIRE

    Lee, Kwangju

    1991-01-01

    A simple, design-oriented model of joints in vehicle structures is developed. This model accounts for the flexibility, the offsets of rotation centers of joint branches, and the coupling between rotations of a joint branch in different planes. The model parameters consist of torsional spring rates, the coordinates of the flexible hinges, and the orientations of planes in which the torsional springs are located. The model parameters are selected to be physically meaningful. In s...

  1. Automatic stereoscopic system for person recognition

    Science.gov (United States)

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

    1999-06-01

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

  2. Estimation and Identification for Modeling Dynamic Systems.

    Science.gov (United States)

    1980-02-01

    IEEE Transactions on Automatic Control , Vol. AC-20, pp. 775- 782, December 1975. [2] J.M. Mendel...Diego, California, Septer 1975. [3) J.M. Mendel, "Extension of Friedland’s Bias Filtering Technique to a Class of Nonlinear Systems," IEEE Transactions on Automatic Control , Vol...Time Linear Systems," IEEE Transactions on Automatic Control , April 1980. [8] M.S. Grewal and K. Glover, "Relationships

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

    Science.gov (United States)

    Ding, Yong; Dai, Hang; Zhang, Hang

    2014-01-01

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

  4. Vehicle Detection and Classification Using Passive Infrared Sensing

    KAUST Repository

    Odat, Enas M.

    2015-10-19

    We propose a new sensing device that can simultaneously monitor urban traffic congestion and another phenomenon of interest (flash floods on the present case). This sensing device is based on the combination of an ultrasonic rangefinder with one or multiple remote temperature sensors. We show an implementation of this device, and illustrate its performance in both traffic flow sensing. Field data shows that the sensor can detect vehicles with a 99% accuracy, in addition to estimating their speed and classifying them in function of their length. The same sensor can also monitor urban water levels with an accuracy of less than 2 cm.

  5. 46 CFR 112.01-10 - Automatic emergency lighting and power system.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Automatic emergency lighting and power system. 112.01-10... EMERGENCY LIGHTING AND POWER SYSTEMS Definitions of Emergency Lighting and Power Systems § 112.01-10 Automatic emergency lighting and power system. An automatic emergency lighting and power system is one...

  6. The management of complex system innovations. A theoretic approach to network formation and critical success factor identification using the case of fuel cell vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Venghaus, Sandra

    2011-07-01

    Given the economic, ecological and social importance of automotive transportation, the development of alternative fueling and propulsion technologies requires a wise and sustainable political course of action. Not least the public debate on the impact of transport emissions on climate change and the call for limits to automotive CO-2-emissions reflect the relevance of the topic. In the search for innovative alternatives to the conventional gasoline or diesel propulsion technology, electromobility and hydrogen-based fuel cell vehicles constitute the two most widely discussed long-term options. The market introduction of fuel cell vehicles serves as an expedient example of a highly complex system innovation (CSI), which requires the cooperation of a variety of actors from formerly independent economic sectors in order to overcome the significant barriers to market entry. As will be discussed, such CSI can only be successfully implemented in an environment, within which the complexity-induced knowledge gap is reduced by a systematic exchange of information with respect to both the critical success factors identified by each of the involved stakeholders as well as their cooperation needs and expectations. Given this challenge, a framework is developed, which serves as the basis for a structured dialogue among the multiple stakeholders involved in the development process of a complex system innovation. The framework can thus best be classified as a corporate moderation and decision-support tool to achieve transparency in and impose structure on complex contexts. Methodically, the presented thesis addresses the development of a holistic approach to the management of complex system innovations from two perspectives: (1) a theoretical perspective of analyzing underlying structures and processes of CSI management (i.e., the CSI Management Framework), as well as (2) the development of a strategic approach for the practical implementation of CSI management in complex networks

  7. QUASILINEARIZATION, SYSTEM IDENTIFICATION, AND PREDICTION

    Science.gov (United States)

    regime in an effort to improve the quality of the control exerted. A mathematical formulation and computational solution of the problems of system ... identification and the determination of unmeasurable state variables on the basis of observations of a process, two topics of central importance in the

  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

    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, ...

  9. Line matching for automatic change detection algorithm

    Science.gov (United States)

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

    2012-06-01

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

  10. 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.

  11. 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.

  12. 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.

  13. Electric Vehicle Propulsion System

    OpenAIRE

    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...

  14. 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.

  15. 基于多传感器信息融合的汽车酒驾测控系统设计%The design on vehicle alcohol detection and control system based on multi-sensor data fusion

    Institute of Scientific and Technical Information of China (English)

    刘艳红; 柏逢明

    2015-01-01

    To overcome the impact of detection precision and accuracy of interior vehicle flow in traditional vehicle alcohol detection and control system with a single sensor, a vehicle alcohol detection and control system via multi-sensor fusion technologies is proposed. Based on D-S evidence theory, an information fusion structure is given. The mainly hardware modules of the system are also designed. The designing scheme of vehicle alcohol detection and control system via multi-sensor data fusion approach is finished.%针对传统单点汽车酒驾检测系统忽略了车内气流流动对检测精度和准确度的影响,文章探索性地提出了一种基于多传感器融合技术的汽车室内酒驾测控方法。基于D-S证据理论设计信息融合算法,并设计了酒驾测控系统的主要硬件系统与工作模式,完成了基于多传感器检测的汽车酒驾检测与控制系统方案设计。

  16. 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.

  17. The integrated manual and automatic control of complex flight systems

    Science.gov (United States)

    Schmidt, David K.

    1991-01-01

    Research dealt with the general area of optimal flight control synthesis for manned flight vehicles. The work was generic; no specific vehicle was the focus of study. However, the class of vehicles generally considered were those for which high authority, multivariable control systems might be considered, for the purpose of stabilization and the achievement of optimal handling characteristics. Within this scope, the topics of study included several optimal control synthesis techniques, control-theoretic modeling of the human operator in flight control tasks, and the development of possible handling qualities metrics and/or measures of merit. Basic contributions were made in all these topics, including human operator (pilot) models for multi-loop tasks, optimal output feedback flight control synthesis techniques; experimental validations of the methods developed, and fundamental modeling studies of the air-to-air tracking and flared landing tasks.

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

    Science.gov (United States)

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

    2007-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Oyebola B. O

    2015-06-01

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

  20. 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.

  1. Automatic detection of laughter

    NARCIS (Netherlands)

    Truong, K.P.; Leeuwen, D.A. van

    2005-01-01

    In the context of detecting ‘paralinguistic events’ with the aim to make classification of the speaker’s emotional state possible, a detector was developed for one of the most obvious ‘paralinguistic events’, namely laughter. Gaussian Mixture Models were trained with Perceptual Linear Prediction fea

  2. Online automatic identification of the modal parameters of a long span arch bridge

    Science.gov (United States)

    Magalhães, Filipe; Cunha, Álvaro; Caetano, Elsa

    2009-02-01

    The "Infante D. Henrique" bridge is a concrete arch bridge, with a span of 280 m that crosses the Douro River, linking the cities of Porto and Gaia located in the North of Portugal. This structure is being monitored by a recently installed dynamic monitoring system that comprises 12 acceleration channels. This paper describes the bridge structure, its dynamic parameters identified with a previously developed ambient vibration test, the installed monitoring equipment and the software that continuously processes the data received from the bridge through an Internet connection. Special emphasis is given to the algorithms that have been developed and implemented to perform the online automatic identification of the structure modal parameters from its measured responses during normal operation. The proposed methodology uses the covariance driven stochastic subspace identification method (SSI-COV), which is then complemented by a new algorithm developed for the automatic analysis of stabilization diagrams. This new tool, based on a hierarchical clustering algorithm, proved to be very efficient on the identification of the bridge first 12 modes. The results achieved during 2 months of observation, which involved the analysis of more than 2500 datasets, are presented in detail. It is demonstrated that with the combination of high-quality equipment and powerful identification algorithms, it is possible to estimate, in an automatic manner, accurate modal parameters for several modes. These can then be used as inputs for damage detection algorithms.

  3. 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.

  4. 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

  5. Automatic Scheduling and Planning (ASAP) in future ground control systems

    Science.gov (United States)

    Matlin, Sam

    1988-01-01

    This report describes two complementary approaches to the problem of space mission planning and scheduling. The first is an Expert System or Knowledge-Based System for automatically resolving most of the activity conflicts in a candidate plan. The second is an Interactive Graphics Decision Aid to assist the operator in manually resolving the residual conflicts which are beyond the scope of the Expert System. The two system designs are consistent with future ground control station activity requirements, support activity timing constraints, resource limits and activity priority guidelines.

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

    Energy Technology Data Exchange (ETDEWEB)

    Hetmann, R.

    1982-04-19

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

  7. 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.

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

    Science.gov (United States)

    2007-05-03

    Name Scientific Name Federal Status Florida Status Known to Occur1 Reptiles and Amphibians Green sea turtle Chelonia mydas mydas Endangered...species: green ( Chelonia mydas ), leatherback (Dermochelys coriacea), Kemp’s ridley (Lepidochelys kempii), hawksbill (Eretmochelys imbricata) and

  9. Vehicle health management for guidance, navigation and control systems

    Science.gov (United States)

    Radke, Kathleen; Frazzini, Ron; Bursch, Paul; Wald, Jerry; Brown, Don

    1993-01-01

    The objective of the program was to architect a vehicle health management (VHM) system for space systems avionics that assures system readiness for launch vehicles and for space-based dormant vehicles. The platforms which were studied and considered for application of VHM for guidance, navigation and control (GN&C) included the Advanced Manned Launch System (AMLS), the Horizontal Landing-20/Personnel Launch System (HL-20/PLS), the Assured Crew Return Vehicle (ACRV) and the Extended Duration Orbiter (EDO). This set was selected because dormancy and/or availability requirements are driving the designs of these future systems.

  10. Automatic Sarcasm Detection in Twitter Messages

    OpenAIRE

    Ræder, Johan Georg Cyrus Mazaher

    2016-01-01

    In the past decade, social media like Twitter have become popular and a part of everyday life for many people. Opinion mining of the thoughts and opinions they share can be of interest to, e.g., companies and organizations. The sentiment of a text can be drastically altered when figurative language such as sarcasm is used. This thesis presents a system for automatic sarcasm detection in Twitter messages. To get a better understanding of the field, state-of-the-art systems fo...

  11. A bias identification and state estimation methodology for nonlinear systems

    Science.gov (United States)

    Caglayan, A. K.; Lancraft, R. E.

    1983-01-01

    A computational algorithm for the identification of input and output biases in discrete-time nonlinear stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.

  12. Low Power, Room Temperature Systems for the Detection and Identification of Radionuclides from Atmospheric Nuclear Test

    Science.gov (United States)

    2013-07-01

    JjlMll’I1T’H.’~ ,"mIl l’ll.ITk,r 1.,t.\\fJj; nl’,’d !(I be .,I~’\\·!·Io •• t:,~:J. ’nt.- ’~m ... un’ (II’ c.m~:;~ l’\\’ Ibr r.h", trIO . · ... ·It. llf’ i’J...Symposium on Cadmium Telluride: Physical Properties and Applications, Strasbourg ( 1976 ) 2. Proceedings ofSPIE on "Hard X-ray, Gamma-Ray, and Neutron...original concentration of 10%. Although. the resistivity was optimized in the other regions to obtain high breakdown voltage for speetnun analysis

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

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

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

  14. 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...

  15. Automatic detection of scoliotic curves in posteroanterior radiographs.

    Science.gov (United States)

    Duong, Luc; Cheriet, Farida; Labelle, Hubert

    2010-05-01

    Spinal deformities are diagnosed using posteroanterior (PA) radiographs. Automatic detection of the spine on conventional radiographs would be of interest to quantify curve severity, would help reduce observer variability and would allow large-scale retrospective studies on radiographic databases. The goal of this paper is to present a new method for automatic detection of spinal curves from a PA radiograph. A region of interest (ROI) is first extracted according to the 2-D shape variability of the spine obtained from a set of PA radiographs of scoliotic patients. This region includes 17 bounding boxes delimiting each vertebral level from T1 to L5. An adaptive filter combining shock with complex diffusion is used to individually restore the image of each vertebral level. Then, texture descriptors of small block elements are computed and submitted for training to support vector machines (SVM). Vertebral body's locations are thereby inferred for a particular vertebral level. The classifications of block elements for all 17 SVMs are identified in the image and a voting system is introduced to cumulate correctly predicted blocks. A spline curve is then fitted through the centers of the predicted vertebral regions and compared to a manual identification using a Student t-test. A clinical validation is performed using 100 radiographs of scoliotic patients (not used for training) and the detected spinal curve is found to be statistically similar (p < 0.05) in 93% of cases to the manually identified curve.

  16. Parameter design and performance analysis of shift actuator for a two-speed automatic mechanical transmission for pure electric vehicles

    Directory of Open Access Journals (Sweden)

    Jianjun Hu

    2016-08-01

    Full Text Available Recent developments of pure electric vehicles have shown that pure electric vehicles equipped with two-speed or multi-speed gearbox possess higher energy efficiency by ensuring the drive motor operates at its peak performance range. This article presents the design, analysis, and control of a two-speed automatic mechanical transmission for pure electric vehicles. The shift actuator is based on a motor-controlled camshaft where a special geometric groove is machined, and the camshaft realizes the axial positions of the synchronizer sleeve for gear engaging, disengaging, and speed control of the drive motor. Based on the force analysis of shift process, the parameters of shift actuator and shift motor are designed. The drive motor’s torque control strategy before shifting, speed governing control strategy before engaging, shift actuator’s control strategy during gear engaging, and drive motor’s torque recovery strategy after shift process are proposed and implemented with a prototype. To validate the performance of the two-speed gearbox, a test bed was developed based on dSPACE that emulates various operation conditions. The experimental results indicate that the shift process with the proposed shift actuator and control strategy could be accomplished within 1 s under various operation conditions, with shift smoothness up to passenger car standard.

  17. Desktop calibration of automatic transmission for passenger vehicle

    Institute of Scientific and Technical Information of China (English)

    FANG Chi; SHI Jian-peng; WANG Jun

    2014-01-01

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

  18. 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.

  19. Flight Testing a Real-Time Hazard Detection System for Safe Lunar Landing on the Rocket-Powered Morpheus Vehicle

    Science.gov (United States)

    Trawny, Nikolas; Huertas, Andres; Luna, Michael E.; Villalpando, Carlos Y.; Martin, Keith E.; Carson, John M.; Johnson, Andrew E.; Restrepo, Carolina; Roback, Vincent E.

    2015-01-01

    The Hazard Detection System (HDS) is a component of the ALHAT (Autonomous Landing and Hazard Avoidance Technology) sensor suite, which together provide a lander Guidance, Navigation and Control (GN&C) system with the relevant measurements necessary to enable safe precision landing under any lighting conditions. The HDS consists of a stand-alone compute element (CE), an Inertial Measurement Unit (IMU), and a gimbaled flash LIDAR sensor that are used, in real-time, to generate a Digital Elevation Map (DEM) of the landing terrain, detect candidate safe landing sites for the vehicle through Hazard Detection (HD), and generate hazard-relative navigation (HRN) measurements used for safe precision landing. Following an extensive ground and helicopter test campaign, ALHAT was integrated onto the Morpheus rocket-powered terrestrial test vehicle in March 2014. Morpheus and ALHAT then performed five successful free flights at the simulated lunar hazard field constructed at the Shuttle Landing Facility (SLF) at Kennedy Space Center, for the first time testing the full system on a lunar-like approach geometry in a relevant dynamic environment. During these flights, the HDS successfully generated DEMs, correctly identified safe landing sites and provided HRN measurements to the vehicle, marking the first autonomous landing of a NASA rocket-powered vehicle in hazardous terrain. This paper provides a brief overview of the HDS architecture and describes its in-flight performance.

  20. Automatic control and tracking of periodic orbits in chaotic systems.

    Science.gov (United States)

    Ando, Hiroyasu; Boccaletti, S; Aihara, Kazuyuki

    2007-06-01

    Based on an automatic feedback adjustment of an additional parameter of a dynamical system, we propose a strategy for controlling periodic orbits of desired periods in chaotic dynamics and tracking them toward the set of unstable periodic orbits embedded within the original chaotic attractor. The method does not require information on the system to be controlled, nor on any reference states for the targets, and it overcomes some of the difficulties encountered by other techniques. Assessments of the method's effectiveness and robustness are given by means of the application of the technique to the stabilization of unstable periodic orbits in both discrete- and continuous-time systems.

  1. System identification of a small low-cost unmanned aerial vehicle using flight data from low-cost sensors

    Science.gov (United States)

    Hoffer, Nathan Von

    Remote sensing has traditionally been done with satellites and manned aircraft. While. these methods can yield useful scientificc data, satellites and manned aircraft have limitations in data frequency, process time, and real time re-tasking. Small low-cost unmanned aerial vehicles (UAVs) provide greater possibilities for personal scientic research than traditional remote sensing platforms. Precision aerial data requires an accurate vehicle dynamics model for controller development, robust flight characteristics, and fault tolerance. One method of developing a model is system identification (system ID). In this thesis system ID of a small low-cost fixed-wing T-tail UAV is conducted. The linerized longitudinal equations of motion are derived from first principles. Foundations of Recursive Least Squares (RLS) are presented along with RLS with an Error Filtering Online Learning scheme (EFOL). Sensors, data collection, data consistency checking, and data processing are described. Batch least squares (BLS) and BLS with EFOL are used to identify aerodynamic coecoefficients of the UAV. Results of these two methods with flight data are discussed.

  2. 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.

  3. 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.

  4. Comparison of automatic control systems

    Science.gov (United States)

    Oppelt, W

    1941-01-01

    This report deals with a reciprocal comparison of an automatic pressure control, an automatic rpm control, an automatic temperature control, and an automatic directional control. It shows the difference between the "faultproof" regulator and the actual regulator which is subject to faults, and develops this difference as far as possible in a parallel manner with regard to the control systems under consideration. Such as analysis affords, particularly in its extension to the faults of the actual regulator, a deep insight into the mechanism of the regulator process.

  5. Fault detection and isolation for a full-scale railway vehicle suspension with multiple Kalman filters

    Science.gov (United States)

    Jesussek, Mathias; Ellermann, Katrin

    2014-12-01

    Reliability and dependability in complex mechanical systems can be improved by fault detection and isolation (FDI) methods. These techniques are key elements for maintenance on demand, which could decrease service cost and time significantly. This paper addresses FDI for a railway vehicle: the mechanical model is described as a multibody system, which is excited randomly due to track irregularities. Various parameters, like masses, spring- and damper-characteristics, influence the dynamics of the vehicle. Often, the exact values of the parameters are unknown and might even change over time. Some of these changes are considered critical with respect to the operation of the system and they require immediate maintenance. The aim of this work is to detect faults in the suspension system of the vehicle. A Kalman filter is used in order to estimate the states. To detect and isolate faults the detection error is minimised with multiple Kalman filters. A full-scale train model with nonlinear wheel/rail contact serves as an example for the described techniques. Numerical results for different test cases are presented. The analysis shows that for the given system it is possible not only to detect a failure of the suspension system from the system's dynamic response, but also to distinguish clearly between different possible causes for the changes in the dynamical behaviour.

  6. DESIGN AND DEVELOP A COMPUTER AIDED DESIGN FOR AUTOMATIC EXUDATES DETECTION FOR DIABETIC RETINOPATHY SCREENING

    Directory of Open Access Journals (Sweden)

    C. A. SATHIYAMOORTHY

    2016-04-01

    Full Text Available Diabetic Retinopathy is a severe and widely spread eye disease which can lead to blindness. One of the main symptoms for vision loss is Exudates and it could be prevented by applying an early screening process. In the Existing systems, a Fuzzy C-Means Clustering technique is used for detecting the exudates for analyzation. The main objective of this paper is, to improve the efficiency of the Exudates detection in diabetic retinopathy images. To do this, a three Stage – [TS] approach is introduced for detecting and extracting the exudates automatically from the retinal images for screening the Diabetic retinopathy. TS functions on the image in three levels such as Pre-processing the image, enhancing the image and detecting the Exudates accurately. After successful detection, the detected exudates are classified using GLCM method for finding the accuracy. The TS approach is experimented using MATLAB software and the performance evaluation can be proved by comparing the results with the existing approach’s result and with the hand-drawn ground truths images from the expert ophthalmologist.

  7. Automatic Palette Identification of Colored Graphics

    Science.gov (United States)

    Lacroix, Vinciane

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

  8. 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…

  9. 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.

  10. A Subspace Identification Method for Detecting Abnormal Behavior in HVAC Systems

    Directory of Open Access Journals (Sweden)

    Dimitris Sklavounos

    2015-01-01

    Full Text Available A method for the detection of abnormal behavior in HVAC systems is presented. The method combines deterministic subspace identification for each zone independently to create a system model that produces the anticipated zone’s temperature and the sequential test CUSUM algorithm to detect drifts of the rate of change of the difference between the real and the anticipated measurements. Simulation results regarding the detection of infiltration heat losses and the detection of exogenous heat gains such as fire demonstrate the effectiveness of the proposed method.

  11. 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.

  12. AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles

    Science.gov (United States)

    Wang, X. Sean; Lee, Byung Suk; Sadjadi, Firooz

    2006-05-01

    Advances in sensor technology and image processing have made it possible to equip unmanned aerial vehicles (UAVs) with economical, high-resolution, energy-efficient sensors. Despite the improvements, current UAVs lack autonomous and collaborative operation capabilities, due to limited bandwidth and limited on-board image processing abilities. The situation, however, is changing. In the next generation of UAVs, much image processing can be carried out onboard and communication bandwidth problem will improve. More importantly, with more processing power, collaborative operations among a team of autonomous UAVs can provide more intelligent event detection capabilities. In this paper, we present ideas for developing a system enabling target recognitions by collaborative operations of autonomous UAVs. UAVs are configured in three stages: manufacturing, mission planning, and deployment. Different sets of information are needed at different stages, and the resulting outcome is an optimized event detection code deployed onto a UAV. The envisioned system architecture and the contemplated methodology, together with problems to be addressed, are presented.

  13. 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

  14. 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.

  15. 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...

  16. Learning theory and system identification; Gakushu riron to system dotei

    Energy Technology Data Exchange (ETDEWEB)

    Adachi, S. [Utsunomiya Univ. (Japan). Faculty of Engineering

    1998-04-10

    The relationship between learning theory and system identification theory is described. The learning theory is mainly being studied by neural network community, while the system identification theory is mainly being discussed in the community of control system design and failure detection. The relation between the two theories has been studied. In this paper, the relation is explained by focusing on the following two points: (1) The relationship between learning method such as error reverse propagation method and on-line system identification is discussed from the viewpoint of robust estimation. (2) The relationship between PAC (probably approximately correct) learning which is recently attracting the attention among many learning theories and system identification theories is investigated. 33 refs.

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

    Science.gov (United States)

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

    2012-02-01

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

  18. Automatic identification and classification of muscle spasms in long-term EMG recordings.

    Science.gov (United States)

    Winslow, Jeffrey; Martinez, Adriana; Thomas, Christine K

    2015-03-01

    Spinal cord injured (SCI) individuals may be afflicted by spasticity, a condition in which involuntary muscle spasms are common. EMG recordings can be analyzed to quantify this symptom of spasticity but manual identification and classification of spasms are time consuming. Here, an algorithm was created to find and classify spasm events automatically within 24-h recordings of EMG. The algorithm used expert rules and time-frequency techniques to classify spasm events as tonic, unit, or clonus spasms. A companion graphical user interface (GUI) program was also built to verify and correct the results of the automatic algorithm or manually defined events. Eight channel EMG recordings were made from seven different SCI subjects. The algorithm was able to correctly identify an average (±SD) of 94.5 ± 3.6% spasm events and correctly classify 91.6 ± 1.9% of spasm events, with an accuracy of 61.7 ± 16.2%. The accuracy improved to 85.5 ± 5.9% and the false positive rate decreased to 7.1 ± 7.3%, respectively, if noise events between spasms were removed. On average, the algorithm was more than 11 times faster than manual analysis. Use of both the algorithm and the GUI program provide a powerful tool for characterizing muscle spasms in 24-h EMG recordings, information which is important for clinical management of spasticity.

  19. Generalizability and comparison of automatic clinical text de-identification methods and resources.

    Science.gov (United States)

    Ferrández, Óscar; South, Brett R; Shen, Shuying; Friedlin, F Jeff; Samore, Matthew H; Meystre, Stéphane M

    2012-01-01

    In this paper, we present an evaluation of the hybrid best-of-breed automated VHA (Veteran's Health Administration) clinical text de-identification system, nicknamed BoB, developed within the VHA Consortium for Healthcare Informatics Research. We also evaluate two available machine learning-based text de-identifications systems: MIST and HIDE. Two different clinical corpora were used for this evaluation: a manually annotated VHA corpus, and the 2006 i2b2 de-identification challenge corpus. These experiments focus on the generalizability and portability of the classification models across different document sources. BoB demonstrated good recall (92.6%), satisfactorily prioritizing patient privacy, and also achieved competitive precision (83.6%) for preserving subsequent document interpretability. MIST and HIDE reached very competitive results, in most cases with high precision (92.6% and 93.6%), although recall was sometimes lower than desired for the most sensitive PHI categories.

  20. 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.

  1. Identification of mycobacterium tuberculosis in sputum smear slide using automatic scanning microscope

    Science.gov (United States)

    Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

    2015-04-01

    Sputum smear observation has an important role in tuberculosis (TB) disease diagnosis, because it needs accurate identification to avoid high errors diagnosis. In development countries, sputum smear slide observation is commonly done with conventional light microscope from Ziehl-Neelsen stained tissue and it doesn't need high cost to maintain the microscope. The clinicians do manual screening process for sputum smear slide which is time consuming and needs highly training to detect the presence of TB bacilli (mycobacterium tuberculosis) accurately, especially for negative slide and slide with less number of TB bacilli. For helping the clinicians, we propose automatic scanning microscope with automatic identification of TB bacilli. The designed system modified the field movement of light microscope with stepper motor which was controlled by microcontroller. Every sputum smear field was captured by camera. After that some image processing techniques were done for the sputum smear images. The color threshold was used for background subtraction with hue canal in HSV color space. Sobel edge detection algorithm was used for TB bacilli image segmentation. We used feature extraction based on shape for bacilli analyzing and then neural network classified TB bacilli or not. The results indicated identification of TB bacilli that we have done worked well and detected TB bacilli accurately in sputum smear slide with normal staining, but not worked well in over staining and less staining tissue slide. However, overall the designed system can help the clinicians in sputum smear observation becomes more easily.

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

    OpenAIRE

    Lepen, Nejc

    2014-01-01

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

  3. Image-Based Pothole Detection System for ITS Service and Road Management System

    Directory of Open Access Journals (Sweden)

    Seung-Ki Ryu

    2015-01-01

    Full Text Available Potholes can generate damage such as flat tire and wheel damage, impact and damage of lower vehicle, vehicle collision, and major accidents. Thus, accurately and quickly detecting potholes is one of the important tasks for determining proper strategies in ITS (Intelligent Transportation System service and road management system. Several efforts have been made for developing a technology which can automatically detect and recognize potholes. In this study, a pothole detection method based on two-dimensional (2D images is proposed for improving the existing method and designing a pothole detection system to be applied to ITS service and road management system. For experiments, 2D road images that were collected by a survey vehicle in Korea were used and the performance of the proposed method was compared with that of the existing method for several conditions such as road, recording, and brightness. The results are promising, and the information extracted using the proposed method can be used, not only in determining the preliminary maintenance for a road management system and in taking immediate action for their repair and maintenance, but also in providing alert information of potholes to drivers as one of ITS services.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. Rapid identification and detection of pathogenic Fungi by padlock probes

    NARCIS (Netherlands)

    Tsui, C.K.M.; Wang, B.; Schoen, C.D.; Hamelin, R.C.

    2013-01-01

    Fungi are important pathogens of human diseases, as well as to agricultural crop and trees. Molecular diagnostics can detect diseases early, and improve identification accuracy and follow-up disease management. The use of padlock probe is effective to facilitate these detections and pathogen identif

  9. 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.

  10. Portable automatic bioaerosol sampling system for rapid on-site detection of targeted airborne microorganisms.

    Science.gov (United States)

    Usachev, Evgeny V; Pankova, Anna V; Rafailova, Elina A; Pyankov, Oleg V; Agranovski, Igor E

    2012-10-26

    Bioaerosols could cause various severe human and animal diseases and their opportune and qualitative precise detection and control is becoming a significant scientific and technological topic for consideration. Over the last few decades bioaerosol detection has become an important bio-defense related issue. Many types of portable and stationary bioaerosol samplers have been developed and, in some cases, integrated into automated detection systems utilizing various microbiological techniques for analysis of collected microbes. This paper describes a personal sampler used in conjunction with a portable real-time PCR technique. It was found that a single fluorescent dye could be successfully used in multiplex format for qualitative detection of numerous targeted bioaerosols in one PCR tube making the suggested technology a reliable "first alert" device. This approach has been specifically developed and successfully verified for rapid detection of targeted microorganisms by portable PCR devices, which is especially important under field conditions, where the number of microorganisms of interest usually exceeds the number of available PCR reaction tubes. The approach allows detecting targeted microorganisms and triggering some corresponding sanitary and quarantine procedures to localize possible spread of dangerous infections. Following detailed analysis of the sample under controlled laboratory conditions could be used to exactly identify which particular microorganism out of a targeted group has been rapidly detected in the field. It was also found that the personal sampler has a collection efficiency higher than 90% even for small-sized viruses (>20 nm) and stable performance over extended operating periods. In addition, it was found that for microorganisms used in this project (bacteriophages MS2 and T4) elimination of nucleic acids isolation and purification steps during sample preparation does not lead to the system sensitivity reduction, which is extremely

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

    Science.gov (United States)

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

    2015-09-01

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

  12. Automatic and controlled processing in the corticocerebellar system.

    Science.gov (United States)

    Ramnani, Narender

    2014-01-01

    During learning, performance changes often involve a transition from controlled processing in which performance is flexible and responsive to ongoing error feedback, but effortful and slow, to a state in which processing becomes swift and automatic. In this state, performance is unencumbered by the requirement to process feedback, but its insensitivity to feedback reduces its flexibility. Many properties of automatic processing are similar to those that one would expect of forward models, and many have suggested that these may be instantiated in cerebellar circuitry. Since hierarchically organized frontal lobe areas can both send and receive commands, I discuss the possibility that they can act both as controllers and controlled objects and that their behaviors can be independently modeled by forward models in cerebellar circuits. Since areas of the prefrontal cortex contribute to this hierarchically organized system and send outputs to the cerebellar cortex, I suggest that the cerebellum is likely to contribute to the automation of cognitive skills, and to the formation of habitual behavior which is resistant to error feedback. An important prerequisite to these ideas is that cerebellar circuitry should have access to higher order error feedback that signals the success or failure of cognitive processing. I have discussed the pathways through which such feedback could arrive via the inferior olive and the dopamine system. Cerebellar outputs inhibit both the inferior olive and the dopamine system. It is possible that learned representations in the cerebellum use this as a mechanism to suppress the processing of feedback in other parts of the nervous system. Thus, cerebellar processes that control automatic performance may be completed without triggering the engagement of controlled processes by prefrontal mechanisms.

  13. Automatic identification of seismic swarms and other spatio-temporal clustering from catalogs

    Science.gov (United States)

    Nava, F. Alejandro; Glowacka, Ewa

    1994-06-01

    Statistical analysis of seismic catalogs usually requires identification of swarms and foreshocks-main event-aftershocks sequences-a tedious and time-consuming chore. SWaRMSHoW, a simple but versatile QBASIC program for PC, graphically displays on screen catalog epicentral activity, with optional temporal distribution scaling; identifies spatio-temporal hypocentral clusters (SwrSeq) which may be swarms or foreshocks-main event-aftershocks sequences and discriminates between these; and displays SwrSeq locations and limits, and assigns them equivalent magnitudes corresponding to those of single events having seismic energy equal to that of the whole SwrSeq. SWaRMSHoW features optional detailed disk output of swarms and clusters, including origin time, location, constituent events, equivalent magnitudes, and current parameters, that allows easy application of results. Graphic screen display includes optional maps and drawings. Operation can be completely automatic or interactive. Working parameters can be reset at any time during operation. Besides swarm and sequence identification, this program's modeling of the seismicity, scaled in both space and time, is useful for studying many aspects of spatio-temporal seismicity, such as fault activation, migration of activity, quiescence, etc.

  14. 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...

  15. 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.

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

    Institute of Scientific and Technical Information of China (English)

    夏链; 李福根; 韩春明

    2011-01-01

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

  17. 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.

  18. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-08-19

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

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

    Science.gov (United States)

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

    2011-01-01

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

  20. Automatic Target Detection Using Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Ganesan L

    2004-01-01

    Full Text Available Automatic target recognition (ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. This paper presents an algorithm for detecting a specified set of target objects embedded in visual images for an ATR application. The developed algorithm employs a novel technique for automatically detecting man-made and non-man-made single, two, and multitargets from nontarget objects, located within a cluttered environment by evaluating nonoverlapping image blocks, where block-by-block comparison of wavelet cooccurrence feature is done. The results of the proposed algorithm are found to be satisfactory.

  1. Vehicle usage verification system

    NARCIS (Netherlands)

    Scanlon, William G.; McQuiston, Jonathan; Cotton, Simon L.

    2012-01-01

    EN)A computer-implemented system for verifying vehicle usage comprising a server capable of communication with a plurality of clients across a communications network. Each client is provided in a respective vehicle and with a respective global positioning system (GPS) by which the client can determi

  2. System design of electronic vehicles and components

    OpenAIRE

    Смолій, Вікторія Миколаївна

    2015-01-01

    The oscillation mechanical and thermal mathematical models of electronic vehicles that allow to take into account properties and cooperation of making model elements of replacement and design oscillation stability of PCBS and components in the conditions of technological process of their production are worked out

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

    Institute of Scientific and Technical Information of China (English)

    李林; 强秀华; 邹斌

    2012-01-01

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

  4. 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.

  5. 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 ISA ...

  6. 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

  7. 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-...

  8. 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.

  9. An automatic speech recognition system with speaker-independent identification support

    Science.gov (United States)

    Caranica, Alexandru; Burileanu, Corneliu

    2015-02-01

    The novelty of this work relies on the application of an open source research software toolkit (CMU Sphinx) to train, build and evaluate a speech recognition system, with speaker-independent support, for voice-controlled hardware applications. Moreover, we propose to use the trained acoustic model to successfully decode offline voice commands on embedded hardware, such as an ARMv6 low-cost SoC, Raspberry PI. This type of single-board computer, mainly used for educational and research activities, can serve as a proof-of-concept software and hardware stack for low cost voice automation systems.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. HYBRID VEHICLE CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    V. Dvadnenko

    2016-06-01

    Full Text Available The hybrid vehicle control system includes a start–stop system for an internal combustion engine. The system works in a hybrid mode and normal vehicle operation. To simplify the start–stop system, there were user new possibilities of a hybrid car, which appeared after the conversion. Results of the circuit design of the proposed system of basic blocks are analyzed.

  15. 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.

  16. 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.

  17. Automatic and Controlled Attention Processes in Auditory Detection.

    Science.gov (United States)

    1981-02-01

    Research (Code 458) ...WKo. PAGE Arlington, Virginia 22217 _1 14 MONITORING AGENCY NAME 6 AODRESS(if dlN.UI be. C6w.lbojf Oee) IS. SECURITY CLASS. (of...o Ig aemep ad *sN I0p WoolF USI .. ) attention, dichotic listening, individual diff*erences, time-sharing, memory search, visual search, auditory...Charles V. Hutchins Code N-711 Naval Air Systems Command Hq NAVTRAEQUIPCEN A IR-34OF Orlando , FL 32813 Navy Department Washington, DC 20361 Chief of Naval

  18. Accurate Localization of Communicant Vehicles using GPS and Vision Systems

    Directory of Open Access Journals (Sweden)

    Georges CHALLITA

    2009-07-01

    Full Text Available The new generation of ADAS systems based on cooperation between vehicles can offer serious perspectives to the road security. The inter-vehicle cooperation is made possible thanks to the revolution in the wireless mobile ad hoc network. In this paper, we will develop a system that will minimize the imprecision of the GPS used to car tracking, based on the data given by the GPS which means the coordinates and speed in addition to the use of the vision data that will be collected from the loading system in the vehicle (camera and processor. Localization information can be exchanged between the vehicles through a wireless communication device. The creation of the system must adopt the Monte Carlo Method or what we call a particle filter for the treatment of the GPS data and vision data. An experimental study of this system is performed on our fleet of experimental communicating vehicles.

  19. Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion.

    Science.gov (United States)

    Ljungblad, Jonas; Hök, Bertil; Allalou, Amin; Pettersson, Håkan

    2017-04-03

    The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlighting the necessary conditions for large scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the DADSS (driver alcohol detection system for safety) program aiming at massive deployment of alcohol sensing systems which could potentially save thousands of American lives annually. The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction. Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol

  20. 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.

  1. 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.

  2. 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...

  3. 14 CFR 25.672 - Stability augmentation and automatic and power-operated systems.

    Science.gov (United States)

    2010-01-01

    ... power-operated systems. 25.672 Section 25.672 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Construction Control Systems § 25.672 Stability augmentation and automatic and power-operated systems. If the functioning of stability augmentation or other automatic or power-operated systems is necessary to...

  4. 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.

  5. Design and Analysis of Automatic Car Park System with Capacity Control

    Directory of Open Access Journals (Sweden)

    Musa Mohammed Gujja

    2015-08-01

    Full Text Available :The need for an automatic car park gate system has been in increase in recent times following the economic situation in present days. The circuit is aimed at eliminating manual operation of a car park. It incorporate the use of LM741 op-amp and CD4017 decade counter for controlling the number of vehicle that can have access to the parking premises and the circuit is fixed close to the gate with the sensor tragically located where it can sense the presence of a car. The light dependent resistor (LDR senses both entrance and exit of the cars and this followed the maximum of three cars in the case of this design. As a monitoring and control system, when you comes close to the gate the light dependent resistor senses an incoming car which allows the gate to open automatically and closed when done. This process is same for outgoing cars. This module make use of an optical sensor, whose resistance changes with the intensity of light (Horowitz, 1980 the type use is ORP12 and it has a dark resistance of 10MΩ. When light rays are focused on the light dependent resistor (LDR, the resistance becomes very low (0-500Ω but when the rays are interrupted, the increases to its dark resistance (Huiyu, 2010. The variable resistor is used to vary the sensitivity of the light dependent resistor. It is otherwise called dark activated sensor. For the design two conditions are considered. First, when light rays are focused on the ORP12, and second, when the rays are being interrupted. The counter registers and displays the number of vehicle crossing the gate (both entrance and exit and allows maximum of three cars. Once the maximum is reached, the gate entrance remains closed and inaccessible, until another vehicle leaves the park. The car park system comprises of the sensor unit, trigger circuitry, display unit (switching unit and the power supply unit.

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

    Science.gov (United States)

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

    2012-06-01

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

  7. Automatic object recognition and change detection of urban trees

    NARCIS (Netherlands)

    Van der Sande, C.J.

    2010-01-01

    Monitoring of tree objects is relevant in many current policy issues and relate to the quality of the public space, municipal urban green management, management fees for green areas or Kyoto protocol reporting and all have one thing in common: the need for an up to date tree database. This study, pa

  8. Automatic 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.

  9. 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.

  10. Research on automatic spraying of single-walled carbon nanotubes and detection of spraying effects

    Directory of Open Access Journals (Sweden)

    Jianwen Zhao

    2014-04-01

    Full Text Available Single-walled carbon nanotubes (SWNTs have been introduced as compliant electrodes for dielectric elastomers (DEs due to fault tolerance. To acquire a better electrostrictive strain and longer lifetime, it is essential to obtain a certain and uniform width of the SWNT electrode. To ensure uniform width manually, a small flux and longer time are necessary. Moreover, it is difficult to control the width of the electrode for the randomness of manual spraying. Therefore, a new type of automatic spraying process is presented in this paper. The width and homogeneity of the electrode can be easily controlled by certain parameters of the process. Two methods for detecting the homogeneity of the electrode are introduced in this paper: Measurement of surface resistance and luminosity. The coefficient of variation (CV values detected by the two methods are virtually equal and less than 8%, which shows the feasibility of the detection method and homogeneity of automatic spraying. The speed of automatic spraying is 102 mm2/s, which is higher than that of manual spraying. The spraying process and the method used to detect homogeneity in this paper provide a reference for the relevant processes.

  11. A Hybrid Method for Automatic Anatomical Variant Detection and Segmentation

    NARCIS (Netherlands)

    Lorenz, C.; Hanna, R.; Barschdorf, H.; Klinder, T.; Weber, IF.; Krueger, M.; Doessel, O.

    2012-01-01

    The delineation of anatomical structures in medical images can be achieved in an efficient and robust manner using statistical anatomical organ models, which has been demonstrated for an already considerable set of organs, including the heart. While it is possible to provide models with sufficient s

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

    CERN Document Server

    Kodge, B G

    2011-01-01

    In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.

  17. Design and Realization of Controllable Ultrasonic Fault Detector Automatic Verification System

    Science.gov (United States)

    Sun, Jing-Feng; Liu, Hui-Ying; Guo, Hui-Juan; Shu, Rong; Wei, Kai-Li

    The ultrasonic flaw detection equipment with remote control interface is researched and the automatic verification system is developed. According to use extensible markup language, the building of agreement instruction set and data analysis method database in the system software realizes the controllable designing and solves the diversification of unreleased device interfaces and agreements. By using the signal generator and a fixed attenuator cascading together, a dynamic error compensation method is proposed, completes what the fixed attenuator does in traditional verification and improves the accuracy of verification results. The automatic verification system operating results confirms that the feasibility of the system hardware and software architecture design and the correctness of the analysis method, while changes the status of traditional verification process cumbersome operations, and reduces labor intensity test personnel.

  18. 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.

  19. 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

  20. 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.

  1. Robust automatic detection and removal of fiducial projections in fluoroscopy images: an integrated solution.

    Science.gov (United States)

    Zhang, Xuan; Zheng, Guoyan

    2008-01-01

    Automatic detection and removal of fiducial projections in fluoroscopy images is an essential prerequisite for fluoroscopy-based navigation and image-based 3D-2D registration. This paper presents an integrated solution to fulfill this task. A custom-designed calibration cage with a two-plane pattern of fiducials is utilized in our solution. The cage is attached to the C-arm image intensifier and the projections of the fiducials are automatically detected and removed by an on-line algorithm consisting of following 6 steps: image binarization, connected-component labeling, region classification, adaptive template matching, shape analysis, and fiducial projection removal. A similarity measure which is proposed previously for image-based 3D-2D registration is employed in the adaptive template matching to improve the accuracy of the detection. Shape analysis based on the geometrical constraints satisfied by those fiducials in the calibration cage is used to further improve the robustness of the detection. An image inpainting technique based on the fast marching method for level set applications is used to remove the detected fiducial projections. Our in vitro experiments show on average 4 seconds execution time on a Pentium IV machine, a zero false-detection rate, a miss-detection rate of 1.6+/-2.3%, and a sub-pixel localization error.

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

    Science.gov (United States)

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

    2013-01-01

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

  3. A novel vehicle stationary detection utilizing map matching and IMU sensors.

    Science.gov (United States)

    Amin, Md Syedul; Reaz, Mamun Bin Ibne; Nasir, Salwa Sheikh; Bhuiyan, Mohammad Arif Sobhan; Ali, Mohd Alauddin Mohd

    2014-01-01

    Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.

  4. 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...

  5. 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.

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

    Science.gov (United States)

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

    2015-12-01

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

  7. 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.

  8. Pavement crack identification based on automatic threshold iterative method

    Science.gov (United States)

    Lu, Guofeng; Zhao, Qiancheng; Liao, Jianguo; He, Yongbiao

    2017-01-01

    Crack detection is an important issue in concrete infrastructure. Firstly, the accuracy of crack geometry parameters measurement is directly affected by the extraction accuracy, the same as the accuracy of the detection system. Due to the properties of unpredictability, randomness and irregularity, it is difficult to establish recognition model of crack. Secondly, various image noise, caused by irregular lighting conditions, dark spots, freckles and bump, exerts an influence on the crack detection accuracy. Peak threshold selection method is improved in this paper, and the processing of enhancement, smoothing and denoising is conducted before iterative threshold selection, which can complete the automatic selection of the threshold value in real time and stability.

  9. Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  10. 农业自动化喷雾机械标靶害虫自动识别系统的研究%Research on Automatic Identification System of Target Pests in Agricultural Automation Spraying Machine

    Institute of Scientific and Technical Information of China (English)

    张震; 高雄; 陈铁英; 王海超

    2016-01-01

    农业喷雾对象的识别和定位是农业自动化喷雾机械研究中的核心技术之一. 对病虫害甘蓝进行精准喷洒农药,实现病虫害准确自动识别成为关键. 为此,利用机器视觉的欧氏距离甘蓝夜蛾虫害自动识别检测系统,结合由Qualityspec 光谱仪组成的光谱成像系统,对甘蓝正常叶片和遭受甘蓝夜蛾虫害的甘蓝叶片的颜色特征和光谱特征进行分析,并采用机器视觉分割阈值选取中的Otsu算法和自适应波段选择方法提取出了颜色差异的最佳几何阈值和两种叶片的特征波段. 试验结果表明:综合机器视觉和光谱技术能够实现甘蓝夜蛾虫害的自动且准确的识别,准确率可达94%. 因此,建立机器视觉和光谱技术综合识别体系,可为农作物病虫害自动防治喷雾机器人的研制奠定基础,以达到农作物病虫害实时识别和及时治理的目的.%The spray object recognition and localization is one of the core technology of automatic spray mechanization re -search .For precision spraying pesticide plant diseases and insect pests of cabbage , the accurate and automatic identifica-tion of plant diseases and insect pests of cabbage becomes the key .Therefore , using machine vision automatic identifica-tion of the Euclidean distance of cabbage moth pests detection system , combined with spectral imaging system composed of qualityspec spectrometer , Cabbage normal blade and suffer from the cabbage moth pests of cabbage leaf color features and spectral characteristics were analyzed .The best geometric threshold of color difference and characteristic bands of two kinds of leaves were extracted , using the Otsu threshold value image segmentation algorithm and adaptive band selection method.The test results show that the technology compositing image processing with spectrum can realize automatic and accurate identification of Cabbage moth pests , accuracy reaching 94%.Therefore, the establishment of

  11. Automatic GPRS Rainfall Detecting Set Based on P89C669

    Institute of Scientific and Technical Information of China (English)

    Yang,Lei; Wu,Kun

    2005-01-01

    A new kind of remote and automatic GPRS rainfall detecting network system is established and developed. As the main unit of the network system, automatic rainfall detecting set based on P89C669 is used to acquire rainfall information automatically. GPRS station, combined with mobile wireless communication and internet technology is used to achieve the objective of dynamically share and display the meteorological information via internet.

  12. System Identification and Robust Control

    DEFF Research Database (Denmark)

    Tøffner-Clausen, S.

    for mixed real and complex perturbation sets. A novel method, denoted m - K iteration, has been develop to solve the mixed m problem. A general feature of all robust control design methods is the need for specifying not only a nominal model but also some kind of quantification of the uncertainty is, however......, a non-trivial problem which to some extent has been neglected by the theoreticians of robust control. An uncertainty specification has simply been assumed given. One way of obtaining a perturbation model is by physical modelling. Application if the fundamental laws of thermodynamics, mechanics, physics...... estimate frequency domain uncertainty estimates may be obtained. In classical (i.e. Ljungian) system identification, model quality has been assessed under the structure of the model is assumed to be correct. This is, however, often an inadequate assumption in connection with control design. Recently...

  13. Modelling and simulation of vehicle electric power system

    Science.gov (United States)

    Lee, Wootaik; Choi, Daeho; Sunwoo, Myoungho

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

  14. 生物战剂/气溶胶探测和识别系统综述%Detection and Identification System of Biological Aerosols

    Institute of Scientific and Technical Information of China (English)

    杨辉; 宗军君; 薛向锋; 侯智斌

    2015-01-01

    Easy and inexpensive manufacturing of biological weapons ,complicated detection ,expensive protection ,dif‐ficult treating of affected individuals ,selective impact only for people ,animals or plants ,are all factors making an effective defense against biological warfare agents .The aim of this study is to introduce the systems for the detection and identification of biological aerosols containing dangerous bioagents .The basic techniques used for detection and identification of bioagents are described ,including physical ,molecular ,immunochemical ,and other ligand assays .Measuring systems and equipment for the individual techniques are summarized .%生物战剂/武器具有针对性强(人体、动物或植物)、易于制造、廉价、探测困难、防护代价高、感染群体诊治困难等特性,对生物战剂的防御极具挑战性。论文对生物气溶胶/生物战剂探测识别系统的技术路线(如物理、分子、免疫及配合基检验等)、特点和运用情况进行了分析梳理和总结。

  15. 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

  16. Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID) of Penguins.

    Science.gov (United States)

    Afanasyev, Vsevolod; Buldyrev, Sergey V; Dunn, Michael J; Robst, Jeremy; Preston, Mark; Bremner, Steve F; Briggs, Dirk R; Brown, Ruth; Adlard, Stacey; Peat, Helen J

    2015-01-01

    A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus) at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

  17. Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID of Penguins.

    Directory of Open Access Journals (Sweden)

    Vsevolod Afanasyev

    Full Text Available A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

  18. 14 CFR 29.672 - Stability augmentation, automatic, and power-operated systems.

    Science.gov (United States)

    2010-01-01

    ... power-operated systems. 29.672 Section 29.672 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Construction Control Systems § 29.672 Stability augmentation, automatic, and power-operated systems. If the functioning of stability augmentation or other automatic or power-operated system is necessary to...

  19. 14 CFR 27.672 - Stability augmentation, automatic, and power-operated systems.

    Science.gov (United States)

    2010-01-01

    ... power-operated systems. 27.672 Section 27.672 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Construction Control Systems § 27.672 Stability augmentation, automatic, and power-operated systems. If the functioning of stability augmentation or other automatic or power-operated systems is necessary to...

  20. 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.

  1. 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

  2. Channel selection for automatic seizure detection

    DEFF Research Database (Denmark)

    Duun-Henriksen, Jonas; Kjaer, Troels Wesenberg; Madsen, Rasmus Elsborg

    2012-01-01

    of an automatic channel selection method. The characteristics of the seizures are extracted by the use of a wavelet analysis and classified by a support vector machine. The best channel selection method is based upon maximum variance during the seizure. Results: Using only three channels, a seizure detection...

  3. Raft and floating radio frequency identification (RFID) antenna systems for detecting and estimating abundance of PIT-tagged fish in rivers

    Science.gov (United States)

    Fetherman, Eric R.; Avila, Brian W.; Winkelman, Dana L.

    2016-01-01

    Portable radio frequency identification (RFID) PIT tag antenna systems are increasingly being used in studies examining aquatic animal movement, survival, and habitat use, and their design flexibility permits application in a wide variety of settings. We describe the construction, use, and performance of two portable floating RFID PIT tag antenna systems designed to detect fish that were unavailable for recapture using stationary antennas or electrofishing. A raft antenna system was designed to detect and locate PIT-tagged fish in relatively long (i.e., ≥10 km) river reaches, and consisted of two antennas: (1) a horizontal antenna (4 × 1.2 m) installed on the bottom of the raft and used to detect fish in shallower river reaches (<1 m), and (2) a vertical antenna (2.7 × 1.2 m) for detecting fish in deeper pools (≥1 m). Detection distances of the horizontal antenna were between 0.7 and 1.0 m, and detection probability was 0.32 ± 0.02 (mean ± SE) in a field test using rocks marked with 32-mm PIT tags. Detection probability of PIT-tagged fish in the Cache la Poudre River, Colorado, using the raft antenna system, which covered 21% of the wetted area, was 0.14 ± 0.14. A shore-deployed floating antenna (14.6 × 0.6 m), which covered 100% of the wetted area, was designed for use by two operators for detecting and locating PIT-tagged fish in shorter (i.e., <2 km) river reaches. Detection distances of the shore-deployed floating antenna were between 0.7 and 0.8 m, and detection probabilities during field deployment in the St. Vrain River exceeded 0.52. The shore-deployed floating antenna was also used to estimate abundance of PIT-tagged fish. Results suggest that the shore-deployed floating antenna could be used as an alternative to estimating abundance using traditional sampling methods such as electrofishing.

  4. Motion coordination and performance analysis of multiple vehicle systems

    Science.gov (United States)

    Sharma, Vikrant

    In this dissertation, issues related to multiple vehicle systems are studied. First, the issue of vehicular congestion is addressed and its effect on the performance of some systems studied. Motion coordination algorithms for some systems of interest are also developed. The issue of vehicular congestion is addressed by characterizing the effect of increasing the number of vehicles, in a bounded region, on the speed of the vehicles. A multiple vehicle routing problem is considered where vehicles are required to stay velocity-dependent distance away from each other to avoid physical collisions. Optimal solutions to the minimum time routing are characterized and are found to increase with the square root of the number of vehicles in the environment, for different distributions of the sources and destinations of the vehicles. The second issue addressed is that of the effect of vehicular congestion on the delay associated with data delivery in wireless networks where vehicles are used to transport data to increase the wireless capacity of the network. Tight bounds on the associated delay are derived. The next problem addressed is that of covering an arbitrary path-connected two dimensional region, using multiple unmanned aerial vehicles, in minimum time. A constant-factor optimal algorithm is presented for any given initial positions of the vehicles inside the environment. The last problem addressed is that of the deployment of an environment monitoring network of mobile sensors to improve the network lifetime and sensing quality. A distributed algorithm is presented that improves the system's performance starting from an initial deployment.

  5. 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.

  6. Nonlinear System Identification and Behavioral Modeling

    CERN Document Server

    Huq, Kazi Mohammed Saidul; Kabir, A F M Sultanul

    2010-01-01

    The problem of determining a mathematical model for an unknown system by observing its input-output data pair is generally referred to as system identification. A behavioral model reproduces the required behavior of the original analyzed system, such as there is a one-to-one correspondence between the behavior of the original system and the simulated system. This paper presents nonlinear system identification and behavioral modeling using a work assignment.

  7. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Baum, Thomas; Dobritz, Martin; Rummeny, Ernst J.; Noel, Peter B. [Technische Universitaet Muenchen, Institut fuer Radiologie, Klinikum rechts der Isar, Muenchen (Germany); Bauer, Jan S. [Technische Universitaet Muenchen, Abteilung fuer Neuroradiologie, Klinikum rechts der Isar, Muenchen (Germany); Klinder, Tobias; Lorenz, Cristian [Philips Research Laboratories, Hamburg (Germany)

    2014-04-15

    To develop a prototype algorithm for automatic spine segmentation in MDCT images and use it to automatically detect osteoporotic vertebral fractures. Cross-sectional routine thoracic and abdominal MDCT images of 71 patients including 8 males and 9 females with 25 osteoporotic vertebral fractures and longitudinal MDCT images of 9 patients with 18 incidental fractures in the follow-up MDCT were retrospectively selected. The spine segmentation algorithm localised and identified the vertebrae T5-L5. Each vertebra was automatically segmented by using corresponding vertebra surface shape models that were adapted to the original images. Anterior, middle, and posterior height of each vertebra was automatically determined; the anterior-posterior ratio (APR) and middle-posterior ratio (MPR) were computed. As the gold standard, radiologists graded vertebral fractures from T5 to L5 according to the Genant classification in consensus. Using ROC analysis to differentiate vertebrae without versus with prevalent fracture, AUC values of 0.84 and 0.83 were obtained for APR and MPR, respectively (p < 0.001). Longitudinal changes in APR and MPR were significantly different between vertebrae without versus with incidental fracture (ΔAPR: -8.5 % ± 8.6 % versus -1.6 % ± 4.2 %, p = 0.002; ΔMPR: -11.4 % ± 7.7 % versus -1.2 % ± 1.6 %, p < 0.001). This prototype algorithm may support radiologists in reporting currently underdiagnosed osteoporotic vertebral fractures so that appropriate therapy can be initiated. circle This spine segmentation algorithm automatically localised, identified, and segmented the vertebrae in MDCT images. (orig.)

  9. 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

  10. 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.

  11. An integrated flow cytometry-based system for real-time, high sensitivity bacterial detection and identification.

    Directory of Open Access Journals (Sweden)

    Dan A Buzatu

    Full Text Available Foodborne illnesses occur in both industrialized and developing countries, and may be increasing due to rapidly evolving food production practices. Yet some primary tools used to assess food safety are decades, if not centuries, old. To improve the time to result for food safety assessment a sensitive flow cytometer based system to detect microbial contamination was developed. By eliminating background fluorescence and improving signal to noise the assays accurately measure bacterial load or specifically identify pathogens. These assays provide results in minutes or, if sensitivity to one cell in a complex matrix is required, after several hours enrichment. Conventional assessments of food safety require 48 to 56 hours. The assays described within are linear over 5 orders of magnitude with results identical to culture plates, and report live and dead microorganisms. This system offers a powerful approach to real-time assessment of food safety, useful for industry self-monitoring and regulatory inspection.

  12. Performance of an Automated-Mixed-Traffic-Vehicle /AMTV/ System. [urban people mover

    Science.gov (United States)

    Peng, T. K. C.; Chon, K.

    1978-01-01

    This study analyzes the operation and evaluates the expected performance of a proposed automatic guideway transit system which uses low-speed Automated Mixed Traffic Vehicles (AMTV's). Vehicle scheduling and headway control policies are evaluated with a transit system simulation model. The effect of mixed-traffic interference on the average vehicle speed is examined with a vehicle-pedestrian interface model. Control parameters regulating vehicle speed are evaluated for safe stopping and passenger comfort.

  13. Comparing seismic tomographic images from automatically- and manually-detected arrival times

    Science.gov (United States)

    Spallarossa, Daniele; Scafidi, Davide; Turino, Chiara; Ferretti, Gabriele; Viganò, Alfio

    2013-04-01

    In this work we compare local earthquake tomographic images obtained using arrival times detected by an automatic picking procedure and by an expert seismologist. For this purpose we select a reference dataset composed of 476 earthquakes occurred in the Trentino region (north-eastern Italy) in the period 1994-2007. Local magnitudes are comprised between 0.8 and 5.3. Original recordings are mainly from the Provincia Autonoma di Trento (PAT), and from other networks operating in the surrounding areas (Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - INOGS; Istituto Nazionale di Geofisica e Vulcanologia - INGV; others available via the European Integrated Data Archive). The automatic picking of P and S phases is performed through a picker engine based on the Akaike information criterion (AIC). In particular, the proposed automatic phase picker includes: (i) envelope calculation, (ii) band-pass filtering, (iii) Akaike information criterion (AIC) detector for both P- and S-arrivals, (iv) checking for impulsive arrivals, (v) evaluation of expected S onset on the basis of a preliminary location derived from the P-arrival times, and (vi) quality assessment. Simultaneously, careful manual inspection by expert seismologists is applied to the same waveform dataset, to obtain manually-repicked phase readings. Both automatic and manual procedures generate a comparable amount of readings (about 6000 P- and 5000 S-phases). These data are used for the determination of two similar 3-D propagation models for the Trentino region, applying the SIMULPS code. In order to quantitatively estimate the difference of these two models we measure their discrepancies in terms of velocity at all grid points. The small differences observed among tomographic results allow us to demonstrate that the automatic picking engine adopted in this test can be used for reprocessing large amount of seismic recordings with the aim of perform a local tomographic study with an accuracy

  14. 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

  15. 33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

    Science.gov (United States)

    2010-07-01

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

  16. Archival Automatic Identification System (AIS) Data for Navigation Project Performance Evaluation

    Science.gov (United States)

    2015-08-01

    and available to USACE practitioners via the MOU mentioned above provides several of these parameters at a cost that is significantly lower than...performance information can be screened for a variety of embedded factors in the context of navigation features, such as inbound or outbound vessels. Vessel...collection, yet AIS data provides triple the data volume for this single transit, with no explicit cost incurred. Each historical data request from

  17. 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.

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

    Science.gov (United States)

    White, Jonathan; Panda, Brajendra

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

  19. Vehicle Detection Based on Visual Saliency and Deep Sparse Convolution Hierarchical Model

    Institute of Scientific and Technical Information of China (English)

    CAI Yingfeng; WANG Hai; CHEN Xiaobo; GAO Li; CHEN Long

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  1. Comparative evaluation of autofocus algorithms for a real-time system for automatic detection of Mycobacterium tuberculosis.

    Science.gov (United States)

    Mateos-Pérez, José María; Redondo, Rafael; Nava, Rodrigo; Valdiviezo, Juan C; Cristóbal, Gabriel; Escalante-Ramírez, Boris; Ruiz-Serrano, María Jesús; Pascau, Javier; Desco, Manuel

    2012-03-01

    Microscopy images must be acquired at the optimal focal plane for the objects of interest in a scene. Although manual focusing is a standard task for a trained observer, automatic systems often fail to properly find the focal plane under different microscope imaging modalities such as bright field microscopy or phase contrast microscopy. This article assesses several autofocus algorithms applied in the study of fluorescence-labeled tuberculosis bacteria. The goal of this work was to find the optimal algorithm in order to build an automatic real-time system for diagnosing sputum smear samples, where both accuracy and computational time are important. We analyzed 13 focusing methods, ranging from well-known algorithms to the most recently proposed functions. We took into consideration criteria that are inherent to the autofocus function, such as accuracy, computational cost, and robustness to noise and to illumination changes. We also analyzed the additional benefit provided by preprocessing techniques based on morphological operators and image projection profiling.

  2. 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.

  3. 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.

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

    Science.gov (United States)

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

    2013-02-01

    Numerous studies have shown that exposure to motor vehicle emissions increases the probability of heart attacks, asthma attacks, and hospital visits among at-risk individuals. However, while many studies have focused on measurements of ambient nanoparticles near highways, they have not focused on specific road-level domains, such as intersections near population centers. At these locations, very intense spikes in particle number concentration have been observed. These spikes have been linked to motor vehicle activity and have the potential to increase exposure dramatically. Characterizing both the contribution and composition of these spikes is critical in developing exposure models and abatement strategies. To determine the contribution of the particle spikes to the ambient number concentration, we implemented wavelet-based algorithms to isolate the particle spikes from measurements taken during the summer and winter of 2009 in Wilmington, Delaware, adjacent to a roadway intersection that approximately 28,000 vehicles pass through daily. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC*; TSI, Inc., St. Paul, MN) and a fast mobility particle sizer (FMPS). The high-frequency portion of the signal, consisting of a