WorldWideScience

Sample records for automatic vehicle detection and identification systems

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

    Science.gov (United States)

    2012-12-01

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

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

    Directory of Open Access Journals (Sweden)

    О. В. Шишкін

    2013-07-01

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

  3. Roadway System Assessment Using Bluetooth-Based Automatic Vehicle Identification Travel Time Data

    OpenAIRE

    Day, Christopher M.; Brennan, Thomas M.; Hainen, Alexander M.; Remias, Stephen M.; Bullock, Darcy M.

    2012-01-01

    This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection systems. This includes considerations in the physical setup of the collection system as well as the interpretation of the data. An extended discussion is provided, with examples, demonstrating data techniques for converting the raw data into more concise metrics and views. Examples of statistical before-after tests are also provided. A series of case studies were ...

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

    Directory of Open Access Journals (Sweden)

    Hideo Araki

    2006-12-01

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

  5. Estimating spatial travel times using automatic vehicle identification data

    Science.gov (United States)

    2001-01-01

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

  6. Automatic system for localization and recognition of vehicle plate numbers

    OpenAIRE

    Vázquez, N.; Nakano, M.; Pérez-Meana, H.

    2003-01-01

    This paper proposes a vehicle numbers plate identification system, which extracts the characters features of a plate from a captured image by a digital camera. Then identify the symbols of the number plate using a multilayer neural network. The proposed recognition system consists of two processes: The training process and the recognition process. During the training process, a database is created using 310 vehicular plate images. Then using this database a multilayer neural network is traine...

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

    Science.gov (United States)

    Serrão, Carlos

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

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

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

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

  9. Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

    Science.gov (United States)

    Pace, Paul W.; Sutherland, John

    2001-10-01

    This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

  10. 2012 United States Automatic Identification System Database

    Data.gov (United States)

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

  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. 2009 United States Automatic Identification System Database

    Data.gov (United States)

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

  13. 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...

  14. 2011 United States Automatic Identification System Database

    Data.gov (United States)

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

  15. 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.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Rocco Furferi

    2013-05-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  19. Tracking of nuclear shipments with automatic vehicle location systems

    International Nuclear Information System (INIS)

    Colhoun, C.J.K.

    1989-01-01

    A complete Automatic Vehicle Location System (AVL) consists of three main elements: (1) the location sensor in the vehicle, this device constantly determines the coordinates of the vehicles position; (2) the radio link between vehicle and central base; (3) the data processing and display in the central base. For all three elements there are several solutions. The optimal combination of the different techniques depends on the requirements of the special application

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  3. Chemical detection, identification, and analysis system

    International Nuclear Information System (INIS)

    Morel, R.S.; Gonzales, D.; Mniszewski, S.

    1990-01-01

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

  4. 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...

  5. The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia

    Science.gov (United States)

    Kao, Meng-Chun; Ting, Chien-Kun; Kuo, Wen-Chuan

    2018-02-01

    Incorrect placement of the needle causes medical complications in the epidural block, such as dural puncture or spinal cord injury. This study proposes a system which combines an optical coherence tomography (OCT) imaging probe with an automatic identification (AI) system to objectively identify the position of the epidural needle tip. The automatic identification system uses three features as image parameters to distinguish the different tissue by three classifiers. Finally, we found that the support vector machine (SVM) classifier has highest accuracy, specificity, and sensitivity, which reached to 95%, 98%, and 92%, respectively.

  6. Autonomous system for pathogen detection and identification

    International Nuclear Information System (INIS)

    Belgrader, P.; Benett, W.; Langlois, R.; Long, G.; Mariella, R.; Milanovich, F.; Miles, R.; Nelson, W.; Venkateswaran, K.

    1998-01-01

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

    Science.gov (United States)

    1978-12-01

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

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

    KAUST Repository

    Mousa, Mustafa

    2017-12-06

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

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

    KAUST Repository

    Mousa, Mustafa; Sharma, Kapil; Claudel, Christian G.

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Directory of Open Access Journals (Sweden)

    X. Liu

    2017-09-01

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

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

    Science.gov (United States)

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

    2016-04-28

    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.

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

    International Nuclear Information System (INIS)

    Guillot, L.; Reboli, A.

    2009-01-01

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

  14. 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.

  15. Obstacle detection system for underground mining vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, P.; Polotski, V.; Piotte, M.; Melamed, F. [Ecole Polytechnique de Montreal, Montreal, PQ (Canada)

    1998-01-01

    A device for detecting obstacles by autonomous vehicles navigating in mine drifts is described. The device is based upon structured lighting and the extraction of relevant features from images of obstacles. The system uses image profile changes, ground and wall irregularities, disturbances of the vehicle`s trajectory, and impaired visibility to detect obstacles, rather than explicit three-dimensional scene reconstruction. 7 refs., 5 figs.

  16. Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images.

    Science.gov (United States)

    Jani, Shyam S; Low, Daniel A; Lamb, James M

    2015-01-01

    To develop an automated system that detects patient identification and positioning errors between 3-dimensional computed tomography (CT) and kilovoltage CT planning images. Planning kilovoltage CT images were collected for head and neck (H&N), pelvis, and spine treatments with corresponding 3-dimensional cone beam CT and megavoltage CT setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. For positioning errors, setup and planning images were misaligned by 1 to 5 cm in the 6 anatomical directions for H&N and pelvis patients. Spinal misalignments were simulated by misaligning to adjacent vertebral bodies. Image pairs were assessed using commonly used image similarity metrics as well as custom-designed metrics. Linear discriminant analysis classification models were trained and tested on the imaging datasets, and misclassification error (MCE), sensitivity, and specificity parameters were estimated using 10-fold cross-validation. For patient identification, our workflow produced MCE estimates of 0.66%, 1.67%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivity and specificity ranged from 97.5% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 95.4% and 97.7%. MCEs for 1-cm H&N/pelvis misalignments were 1.3%/5.1% and 9.1%/8.6% for TomoTherapy and TrueBeam images, respectively. Two-centimeter MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. MCEs for vertebral body misalignments were 4.8% and 3.6% for TomoTherapy and TrueBeam images, respectively. Patient identification and gross misalignment errors can be robustly and automatically detected using 3-dimensional setup images of different energies across 3 commonly treated anatomical sites. Copyright © 2015 American Society for Radiation Oncology. Published by

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

    Science.gov (United States)

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

    2017-07-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

  19. Automatic system for detecting pornographic images

    Science.gov (United States)

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

    2002-09-01

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

  20. Low ground clearance vehicle detection and warning.

    Science.gov (United States)

    2015-06-01

    A Low Ground Clearance Vehicle Detection : System (LGCVDS) determines if a commercial : motor vehicle can successfully clear a highwayrail : grade crossing and notifies the driver when : his or her vehicle cannot safely traverse the : crossing. That ...

  1. Automatic supervision and fault detection of PV systems based on power losses analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chouder, A.; Silvestre, S. [Electronic Engineering Department, Universitat Politecnica de Catalunya, C/Jordi Girona 1-3, Campus Nord UPC, 08034 Barcelona (Spain)

    2010-10-15

    In this work, we present a new automatic supervision and fault detection procedure for PV systems, based on the power losses analysis. This automatic supervision system has been developed in Matlab and Simulink environment. It includes parameter extraction techniques to calculate main PV system parameters from monitoring data in real conditions of work, taking into account the environmental irradiance and module temperature evolution, allowing simulation of the PV system behaviour in real time. The automatic supervision method analyses the output power losses, presents in the DC side of the PV generator, capture losses. Two new power losses indicators are defined: thermal capture losses (L{sub ct}) and miscellaneous capture losses (L{sub cm}). The processing of these indicators allows the supervision system to generate a faulty signal as indicator of fault detection in the PV system operation. Two new indicators of the deviation of the DC variables respect to the simulated ones have been also defined. These indicators are the current and voltage ratios: R{sub C} and R{sub V}. Analysing both, the faulty signal and the current/voltage ratios, the type of fault can be identified. The automatic supervision system has been successfully tested experimentally. (author)

  2. Automatic supervision and fault detection of PV systems based on power losses analysis

    International Nuclear Information System (INIS)

    Chouder, A.; Silvestre, S.

    2010-01-01

    In this work, we present a new automatic supervision and fault detection procedure for PV systems, based on the power losses analysis. This automatic supervision system has been developed in Matlab and Simulink environment. It includes parameter extraction techniques to calculate main PV system parameters from monitoring data in real conditions of work, taking into account the environmental irradiance and module temperature evolution, allowing simulation of the PV system behaviour in real time. The automatic supervision method analyses the output power losses, presents in the DC side of the PV generator, capture losses. Two new power losses indicators are defined: thermal capture losses (L ct ) and miscellaneous capture losses (L cm ). The processing of these indicators allows the supervision system to generate a faulty signal as indicator of fault detection in the PV system operation. Two new indicators of the deviation of the DC variables respect to the simulated ones have been also defined. These indicators are the current and voltage ratios: R C and R V . Analysing both, the faulty signal and the current/voltage ratios, the type of fault can be identified. The automatic supervision system has been successfully tested experimentally.

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

    Science.gov (United States)

    2016-04-01

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

  4. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Automatic Transmitter Identification System (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter...

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

    KAUST Repository

    Giesbrecht, Gordon G.; Percher, Michael; Brunet, Pierre; Richard, Yanik; Alexander, Marion; Bellemare, Alixandra; Rawal, Yash; Amassian, Aram; Mcdonald, Gerren

    2017-01-01

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

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

    KAUST Repository

    Giesbrecht, Gordon G.

    2017-07-12

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

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

    Directory of Open Access Journals (Sweden)

    Yousra M Abbas

    2015-08-01

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

  8. Development of a wireless protection against imitation system for identification and control of vehicle access

    Directory of Open Access Journals (Sweden)

    Aleksei A. Gavrishev

    2018-03-01

    Full Text Available This article deals with wireless systems for identification and control of vehicle access to protected objects. Known systems are considered. As a result, it has been established that one of the most promising approaches to identifying and controlling vehicle access to protected objects is the use of systems based on the "friend or foe" principle. Among these systems, there are "one-directional" and "bedirectional" identification and access control systems. "Bidirectional" systems are more preferable for questions of identification and access control. However, at present, these systems should have a reduced probability of recognizing the structure of the request and response signals because the potential attacker can easily perform unauthorized access to the radio channel of the system. On this basis, developed a wireless system identification and control vehicle access to protected objects based on the principle of "friend or foe", featuring increased protection from unauthorized access and jamming through the use of rewritable drives chaotic sequences. In addition, it’s proposed to use to identify the vehicle's RFID tag containing additional information about it. Are some specifications of the developed system (the possible frequency range of the request-response signals, the communication range, data rate, the size of the transmitted data, guidelines for choosing RFID. Also, with the help of fuzzy logic, was made the security assessment from unauthorized access request-response signals based on the system of "friend or foe", which are transferred via radio channel, developed systems and analogues. The security assessment of the developed system shows an adequate degree of protection against complex threats (view, spoofing, interception and jamming of traffic in comparison with known systems of this class. Among the main advantages of the developed system it’s necessary to mention increased security from unauthorized access and jamming

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

    Science.gov (United States)

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

    2017-03-01

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

  10. Event storm detection and identification in communication systems

    International Nuclear Information System (INIS)

    Albaghdadi, Mouayad; Briley, Bruce; Evens, Martha

    2006-01-01

    Event storms are the manifestation of an important class of abnormal behaviors in communication systems. They occur when a large number of nodes throughout the system generate a set of events within a small period of time. It is essential for network management systems to detect every event storm and identify its cause, in order to prevent and repair potential system faults. This paper presents a set of techniques for the effective detection and identification of event storms in communication systems. First, we introduce a new algorithm to synchronize events to a single node in the system. Second, the system's event log is modeled as a normally distributed random process. This is achieved by using data analysis techniques to explore and then model the statistical behavior of the event log. Third, event storm detection is proposed using a simple test statistic combined with an exponential smoothing technique to overcome the non-stationary behavior of event logs. Fourth, the system is divided into non-overlapping regions to locate the main contributing regions of a storm. We show that this technique provides us with a method for event storm identification. Finally, experimental results from a commercially deployed multimedia communication system that uses these techniques demonstrate their effectiveness

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

    Directory of Open Access Journals (Sweden)

    Pragyaditya Das.

    2015-08-01

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

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

    OpenAIRE

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

    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 ...

  13. AUTOMATIC RECOGNITION OF CORONAL TYPE II RADIO BURSTS: THE AUTOMATED RADIO BURST IDENTIFICATION SYSTEM METHOD AND FIRST OBSERVATIONS

    International Nuclear Information System (INIS)

    Lobzin, Vasili V.; Cairns, Iver H.; Robinson, Peter A.; Steward, Graham; Patterson, Garth

    2010-01-01

    Major space weather events such as solar flares and coronal mass ejections are usually accompanied by solar radio bursts, which can potentially be used for real-time space weather forecasts. Type II radio bursts are produced near the local plasma frequency and its harmonic by fast electrons accelerated by a shock wave moving through the corona and solar wind with a typical speed of ∼1000 km s -1 . The coronal bursts have dynamic spectra with frequency gradually falling with time and durations of several minutes. This Letter presents a new method developed to detect type II coronal radio bursts automatically and describes its implementation in an extended Automated Radio Burst Identification System (ARBIS 2). Preliminary tests of the method with spectra obtained in 2002 show that the performance of the current implementation is quite high, ∼80%, while the probability of false positives is reasonably low, with one false positive per 100-200 hr for high solar activity and less than one false event per 10000 hr for low solar activity periods. The first automatically detected coronal type II radio burst is also presented.

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

    Directory of Open Access Journals (Sweden)

    Rostam Golmohamadi

    2014-04-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Rosenkranz

    1984-01-01

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

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

    Science.gov (United States)

    2018-02-01

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

  17. Development of automatic flaw detection systems for magnetic particle examination

    International Nuclear Information System (INIS)

    Shirai, T.; Kimura, J.; Amako, T.

    1988-01-01

    Utilizing a video camera and an image processor, development was carried out on automatic flaw detection and discrimination techniques for the purpose of achieving automated magnetic particle examination. Following this, fluorescent wet magnetic particle examination systems for blade roots and rotor grooves of turbine rotors and the non-fluorescent dry magnetic particle examination system for butt welds, were developed. This paper describes these automatic magnetic particle examination (MT) systems and the functional test results

  18. Development of an Automatic Identification System Autonomous Positioning System

    Directory of Open Access Journals (Sweden)

    Qing Hu

    2015-11-01

    Full Text Available In order to overcome the vulnerability of the global navigation satellite system (GNSS and provide robust position, navigation and time (PNT information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS is presented in the paper. The principle of the AIS autonomous positioning system (AAPS is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China. Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts.

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

    Science.gov (United States)

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

    2018-01-01

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

  20. Automatic patient respiration failure detection system with wireless transmission

    Science.gov (United States)

    Dimeff, J.; Pope, J. M.

    1968-01-01

    Automatic respiration failure detection system detects respiration failure in patients with a surgically implanted tracheostomy tube, and actuates an audible and/or visual alarm. The system incorporates a miniature radio transmitter so that the patient is unencumbered by wires yet can be monitored from a remote location.

  1. 33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

    Science.gov (United States)

    2010-07-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  3. 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.

  4. 46 CFR 161.002-10 - Automatic fire detecting system control unit.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting system control unit. 161.002-10...-10 Automatic fire detecting system control unit. (a) General. The fire detecting system control unit... and the battery to be charged. (h) Automatic fire detecting system, battery charging and control—(1...

  5. In-vehicle stereo vision system for identification of traffic conflicts between bus and pedestrian

    Directory of Open Access Journals (Sweden)

    Salvatore Cafiso

    2017-02-01

    Full Text Available The traffic conflict technique (TCT was developed as “surrogate measure of road safety” to identify near-crash events by using measures of the spatial and temporal proximity of road users. Traditionally applications of TCT focus on a specific site by the way of manually or automated supervision. Nowadays the development of in-vehicle (IV technologies provides new opportunities for monitoring driver behavior and interaction with other road users directly into the traffic stream. In the paper a stereo vision and GPS system for traffic conflict investigation is presented for detecting conflicts between vehicle and pedestrian. The system is able to acquire geo-referenced sequences of stereo frames that are used to provide real time information related to conflict occurrence and severity. As case study, an urban bus was equipped with a prototype of the system and a trial in the city of Catania (Italy was carried out analyzing conflicts with pedestrian crossing in front of the bus. Experimental results pointed out the potentialities of the system for collection of data that can be used to get suitable traffic conflict measures. Specifically, a risk index of the conflict between pedestrians and vehicles is proposed to classify collision probability and severity using data collected by the system. This information may be used to develop in-vehicle warning systems and urban network risk assessment.

  6. Automatic detection of patient identification and positioning errors in radiotherapy treatment using 3D setup images

    OpenAIRE

    Jani, Shyam

    2015-01-01

    The success of modern radiotherapy treatment depends on the correct alignment of the radiation beams with the target region in the patient. In the conventional paradigm of image-guided radiation therapy, 2D or 3D setup images are taken immediately prior to treatment and are used by radiation therapy technologists to localize the patient to the same position as defined from the reference planning CT dataset. However, numerous reports in the literature have described errors during this step, wh...

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

    International Nuclear Information System (INIS)

    Clark, R.K.

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

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

    Directory of Open Access Journals (Sweden)

    Chun-Chieh Wang

    2014-02-01

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

  9. Vehicle fault diagnostics and management system

    Science.gov (United States)

    Gopal, Jagadeesh; Gowthamsachin

    2017-11-01

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

  10. Automatic Emergence Detection in Complex Systems

    Directory of Open Access Journals (Sweden)

    Eugene Santos

    2017-01-01

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

  11. 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.

  12. System for Detecting Vehicle Features from Low Quality Data

    Directory of Open Access Journals (Sweden)

    Marcin Dominik Bugdol

    2018-02-01

    Full Text Available The paper presents a system that recognizes the make, colour and type of the vehicle. The classification has been performed using low quality data from real-traffic measurement devices. For detecting vehicles’ specific features three methods have been developed. They employ several image and signal recognition techniques, e.g. Mamdani Fuzzy Inference System for colour recognition or Scale Invariant Features Transform for make identification. The obtained results are very promising, especially because only on-site equipment, not dedicated for such application, has been employed. In case of car type, the proposed system has better performance than commonly used inductive loops. Extensive information about the vehicle can be used in many fields of Intelligent Transport Systems, especially for traffic supervision.

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

    Science.gov (United States)

    2014-08-01

    Firewall Louisville QM 65.206.28.x NAIS Site Controller PC RS232 Serial cable TV32 Computer Cmd Center Serial splitter SAAB R40 AIS Base Station...172.17.14.6 Rack mount computer AIS Radio Interface Ethernet Switch 192.168.0.x Firewall Cable Modem 192.168.0.1 VTS Accred. Boundary serial connection...Automatic Identification System ( AIS ) Transmit Testing in Louisville Phase 2 Distribution Statement A: Approved for public release

  14. 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.

  15. System for automatic detection of lung nodules exhibiting growth

    Science.gov (United States)

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

    2004-05-01

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

  16. 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.

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

    DEFF Research Database (Denmark)

    Zecchino, Antonio; Knezovic, Katarina; Marinelli, Mattia

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Shousong Han

    2017-01-01

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

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

    Science.gov (United States)

    Nikolic, Dejan; Stojkovic, Nikola; Lekic, Nikola

    2018-04-09

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

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

    Directory of Open Access Journals (Sweden)

    K. O. Soroka

    2017-06-01

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

  1. Development of a system for automatic detection of pellet failures

    International Nuclear Information System (INIS)

    Lavagnino, C.E.

    1996-01-01

    Nowadays, the failure controls in UO 2 pellets for Atucha and Embalse reactors are performed visually. In this work it is presented the first stage of the development of a system that allows an automatic approach to the task. For this purpose, the problem has been subdivided in three jobs: choosing the illumination environment, finding the algorithm that detects failures with user-defined tolerance and engineering the mechanic system that supports the desired manipulations of the pellets. In this paper, the former two are developed. a) Finding the illumination conditions that allow subtracting the failure from the normal element surface, knowing, in first place, the cylindrical characteristics of it and, as a consequence, the differences in the light reflection direction and, in second place, the texture differences in relation to the rectification type of the pellet. b) Writing a fast and simple algorithm that allows the identification of the failure following the production specifications. Examples of the developed algorithm are shown. (author). 4 refs

  2. Automatic Water Sensor Window Opening System

    KAUST Repository

    Percher, Michael

    2013-01-01

    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.

  3. 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.

  4. 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

  5. Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

    Science.gov (United States)

    Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

    2014-01-01

    EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM

  6. 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.

  7. Automatic detection, tracking and sensor integration

    Science.gov (United States)

    Trunk, G. V.

    1988-06-01

    This report surveys the state of the art of automatic detection, tracking, and sensor integration. In the area of detection, various noncoherent integrators such as the moving window integrator, feedback integrator, two-pole filter, binary integrator, and batch processor are discussed. Next, the three techniques for controlling false alarms, adapting thresholds, nonparametric detectors, and clutter maps are presented. In the area of tracking, a general outline is given of a track-while-scan system, and then a discussion is presented of the file system, contact-entry logic, coordinate systems, tracking filters, maneuver-following logic, tracking initiating, track-drop logic, and correlation procedures. Finally, in the area of multisensor integration the problems of colocated-radar integration, multisite-radar integration, radar-IFF integration, and radar-DF bearing strobe integration are treated.

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

    DEFF Research Database (Denmark)

    2013-01-01

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

  9. 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.

  10. Fully automatic AI-based leak detection system

    Energy Technology Data Exchange (ETDEWEB)

    Tylman, Wojciech; Kolczynski, Jakub [Dept. of Microelectronics and Computer Science, Technical University of Lodz in Poland, ul. Wolczanska 221/223, Lodz (Poland); Anders, George J. [Kinectrics Inc., 800 Kipling Ave., Toronto, Ontario M8Z 6C4 (Canada)

    2010-09-15

    This paper presents a fully automatic system intended to detect leaks of dielectric fluid in underground high-pressure, fluid-filled (HPFF) cables. The system combines a number of artificial intelligence (AI) and data processing techniques to achieve high detection capabilities for various rates of leaks, including leaks as small as 15 l per hour. The system achieves this level of precision mainly thanks to a novel auto-tuning procedure, enabling learning of the Bayesian network - the decision-making component of the system - using simulated leaks of various rates. Significant new developments extending the capabilities of the original leak detection system described in and form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed. (author)

  11. Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

    Science.gov (United States)

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

    2018-03-01

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

  12. 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.

  13. Los Alamos Scientific Laboratory electronic vehicle identification system

    International Nuclear Information System (INIS)

    Landt, J.A.; Bobbett, R.E.; Koelle, A.R.; Salazar, P.H.

    1980-01-01

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

  14. 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.

  15. 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

  16. Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares.

    Science.gov (United States)

    Van De Gucht, Tim; Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen; Saeys, Wouter

    2017-10-08

    Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate.

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

    Directory of Open Access Journals (Sweden)

    V. Arunachalam

    2012-08-01

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

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

    Science.gov (United States)

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

    2014-04-01

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

  19. Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

    Science.gov (United States)

    Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

    2018-01-01

    Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  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 ROAD GAP DETECTION USING FUZZY INFERENCE SYSTEM

    Directory of Open Access Journals (Sweden)

    S. Hashemi

    2012-09-01

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

  2. Automatic Road Gap Detection Using Fuzzy Inference System

    Science.gov (United States)

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

    2011-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Baofeng Wang

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    Sang-Il Oh

    2017-01-01

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

  8. Automatic identification in mining

    Energy Technology Data Exchange (ETDEWEB)

    Puckett, D; Patrick, C [Mine Computers and Electronics Inc., Morehead, KY (United States)

    1998-06-01

    The feasibility of monitoring the locations and vital statistics of equipment and personnel in surface and underground mining operations has increased with advancements in radio frequency identification (RFID) technology. This paper addresses the use of RFID technology, which is relatively new to the mining industry, to track surface equipment in mine pits, loading points and processing facilities. Specific applications are discussed, including both simplified and complex truck tracking systems and an automatic pit ticket system. This paper concludes with a discussion of the future possibilities of using RFID technology in mining including monitoring heart and respiration rates, body temperatures and exertion levels; monitoring repetitious movements for the study of work habits; and logging air quality via personnel sensors. 10 refs., 5 figs.

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

    Science.gov (United States)

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

    2017-10-01

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

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

    Science.gov (United States)

    2017-01-01

    elevation at the time of vessel movement and calculating the tidal dependence (TD) parameter to 23 U.S. port areas for the years 2012– 2014. Tidal prediction...tank vessel traffic in studied locations. Results include relevant tide range and elevation threshold observations for each year and location studied...Factors .............................................................................................................................. vi 1 Introduction

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

    Directory of Open Access Journals (Sweden)

    Sergio Frugoni

    2008-03-01

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

  12. 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.

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

    Science.gov (United States)

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

    2013-11-01

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

  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. 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.

  16. Improvement and development of automatic detection techniques

    International Nuclear Information System (INIS)

    Yamada, Kiyomi; Takai, Setsuo; Togashi, Chikako; Itami, Jun

    2000-01-01

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

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

    Science.gov (United States)

    2009-02-01

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

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

    NARCIS (Netherlands)

    Creusen, I.M.; Hazelhoff, L.; With, de P.H.N.; Said, A.; Guleryuz, O.G.; Stevenson, R.L.

    2012-01-01

    The availability of large-scale databases containing street-level panoramic images offers the possibility to perform semi-automatic surveying of real-world objects such as traffic signs. These inventories can be performed significantly more efficiently than using conventional methods. Governmental

  19. 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

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

    Science.gov (United States)

    Grymin, David J.

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

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Nicole van Klink

    2017-01-01

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

  3. Development of an automatic human duress detection system

    International Nuclear Information System (INIS)

    Greene, E.R.; Davis, J.G.; Tuttle, W.C.

    1979-01-01

    A method for automatically detecting duress in security personnel utilizes real-time assessment of physiological data (heart rate) to evaluate psychological stress. Using body-worn tape recorders, field data have been collected on 22 Albuquerque police officers (20 male, 2 female) to determine actual heart rate responses in both routine and life-threatening situations. Off-line computer analysis has been applied to the data to determine the speed and reliability with which an alarm could be triggered. Alarm algorithms relating field responses to laboratory collected baseline responses have been developed

  4. Robotic vehicle uses acoustic sensors for voice detection and diagnostics

    Science.gov (United States)

    Young, Stuart H.; Scanlon, Michael V.

    2000-07-01

    An acoustic sensor array that cues an imaging system on a small tele- operated robotic vehicle was used to detect human voice and activity inside a building. The advantage of acoustic sensors is that it is a non-line of sight (NLOS) sensing technology that can augment traditional LOS sensors such as visible and IR cameras. Acoustic energy emitted from a target, such as from a person, weapon, or radio, will travel through walls and smoke, around corners, and down corridors, whereas these obstructions would cripple an imaging detection system. The hardware developed and tested used an array of eight microphones to detect the loudest direction and automatically setter a camera's pan/tilt toward the noise centroid. This type of system has applicability for counter sniper applications, building clearing, and search/rescue. Data presented will be time-frequency representations showing voice detected within rooms and down hallways at various ranges. Another benefit of acoustics is that it provides the tele-operator some situational awareness clues via low-bandwidth transmission of raw audio data for the operator to interpret with either headphones or through time-frequency analysis. This data can be useful to recognize familiar sounds that might indicate the presence of personnel, such as talking, equipment, movement noise, etc. The same array also detects the sounds of the robot it is mounted on, and can be useful for engine diagnostics and trouble shooting, or for self-noise emanations for stealthy travel. Data presented will characterize vehicle self noise over various surfaces such as tiles, carpets, pavement, sidewalk, and grass. Vehicle diagnostic sounds will indicate a slipping clutch and repeated unexpected application of emergency braking mechanism.

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

    Science.gov (United States)

    Sa, Qila; Wang, Zhihui

    2018-03-01

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

  6. 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.

  7. Automatic Encoding and Language Detection in the GSDL

    Directory of Open Access Journals (Sweden)

    Otakar Pinkas

    2014-10-01

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

  8. 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.

  9. 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%.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2017-05-01

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

  12. Usage of aids monitoring in automatic braking systems of modern cars

    Directory of Open Access Journals (Sweden)

    Dembitskyi V.

    2016-08-01

    Full Text Available Increased safety can be carried out at the expense the installation on vehicles of automatic braking systems, that monitor the traffic situation and the actions of the driver. In this paper considered the advantages and disadvantages of automatic braking systems, were analyzed modern tracking tools that are used in automatic braking systems. Based on the statistical data on accidents, are set the main dangers, that the automatic braking system will be reduced. In order to ensure the accuracy of information conducted research for determination of optimal combination of different sensors that provide an adequate perception of road conditions. The tracking system should be equipped with a combination of sensors, which in the case of detection of an obstacle or dangers of signal is transmitted to the information processing system and decision making. Information from the monitoring system should include data for the identification of the object, its condition, the speed.

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2017-10-15

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

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

    Directory of Open Access Journals (Sweden)

    ThetKoKo

    2015-07-01

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

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

    Czech Academy of Sciences Publication Activity Database

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

    2016-01-01

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

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

    Science.gov (United States)

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

    1993-01-01

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

  18. Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

    Science.gov (United States)

    Hübl, Johannes; McArdell, Brian W.; Walter, Fabian

    2018-01-01

    The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. PMID:29789449

  19. Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

    Directory of Open Access Journals (Sweden)

    Andreas Schimmel

    2018-05-01

    Full Text Available The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz, several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio.

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

    Directory of Open Access Journals (Sweden)

    Shaorong XIE

    2014-02-01

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

  1. Molecular-Based Identification and Detection of Salmonella in Food Production Systems: Current Perspectives.

    Science.gov (United States)

    Ricke, Steven C; Kim, Sun Ae; Shi, Zhaohao; Park, Si Hong

    2018-04-19

    Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies has greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  2. Detecting accuracy of flaws by manual and automatic ultrasonic inspections

    International Nuclear Information System (INIS)

    Iida, K.

    1988-01-01

    As the final stage work in the nine year project on proving tests of the ultrasonic inspection technique applied to the ISI of LWR plants, automatic ultrasonic inspection tests were carried out on EDM notches, surface fatigue cracks, weld defects and stress corrosion cracks, which were deliberately introduced in full size structural components simulating a 1,100 MWe BWR. Investigated items are the performance of a newly assembled automatic inspection apparatus, detection limit of flaws, detection resolution of adjacent collinear or parallel EDM notches, detection reproducibility and detection accuracy. The manual ultrasonic inspection of the same flaws as inspected by the automatic ultrasonic inspection was also carried out in order to have comparative data. This paper reports how it was confirmed that the automatic ultrasonic inspection is much superior to the manual inspection in the flaw detection rate and in the detection reproducibility

  3. Fault detection and identification in missile system guidance and control: a filtering approach

    Science.gov (United States)

    Padgett, Mary Lou; Evers, Johnny; Karplus, Walter J.

    1996-03-01

    Real-world applications of computational intelligence can enhance the fault detection and identification capabilities of a missile guidance and control system. A simulation of a bank-to- turn missile demonstrates that actuator failure may cause the missile to roll and miss the target. Failure of one fin actuator can be detected using a filter and depicting the filter output as fuzzy numbers. The properties and limitations of artificial neural networks fed by these fuzzy numbers are explored. A suite of networks is constructed to (1) detect a fault and (2) determine which fin (if any) failed. Both the zero order moment term and the fin rate term show changes during actuator failure. Simulations address the following questions: (1) How bad does the actuator failure have to be for detection to occur, (2) How bad does the actuator failure have to be for fault detection and isolation to occur, (3) are both zero order moment and fine rate terms needed. A suite of target trajectories are simulated, and properties and limitations of the approach reported. In some cases, detection of the failed actuator occurs within 0.1 second, and isolation of the failure occurs 0.1 after that. Suggestions for further research are offered.

  4. 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

  5. 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

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

    Science.gov (United States)

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

    2018-02-01

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

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

    NARCIS (Netherlands)

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

    2010-01-01

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

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

    OpenAIRE

    Atacak, Ismail; Erdogdu, Ertugrul

    2017-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-02-10

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-06-15

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

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

    International Nuclear Information System (INIS)

    Qiu, J; Yang, D

    2015-01-01

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

  12. Automatic Adviser on Mobile Objects Status Identification and Classification

    Science.gov (United States)

    Shabelnikov, A. N.; Liabakh, N. N.; Gibner, Ya M.; Saryan, A. S.

    2018-05-01

    A mobile object status identification task is defined within the image discrimination theory. It is proposed to classify objects into three classes: object operation status; its maintenance is required and object should be removed from the production process. Two methods were developed to construct the separating boundaries between the designated classes: a) using statistical information on the research objects executed movement, b) basing on regulatory documents and expert commentary. Automatic Adviser operation simulation and the operation results analysis complex were synthesized. Research results are commented using a specific example of cuts rolling from the hump yard. The work was supported by Russian Fundamental Research Fund, project No. 17-20-01040.

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

    Directory of Open Access Journals (Sweden)

    Swarup Suresh Kulkarni

    2017-07-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

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

    2016-02-19

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

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

    Directory of Open Access Journals (Sweden)

    Zutao Zhang

    2016-02-01

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

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

    International Nuclear Information System (INIS)

    Parlos, A.G.; Muthusami, J.; Atiya, A.F.

    1994-01-01

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

  18. Multi-Perspective Vehicle Detection and Tracking

    DEFF Research Database (Denmark)

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

    2016-01-01

    this dataset is introduced along with its challenges and evaluation metrics. A vision-based multi-perspective dataset is presented, containing a full panoramic view from a moving platform driving on U.S. highways capturing 2704x1440 resolution images at 12 frames per second. The dataset serves multiple......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....

  19. Classification of busses and lorries in an automatic road toll system

    OpenAIRE

    Jarl, Adam

    2003-01-01

    An automatic road toll system enables the passing vehicles to change lanes and no stop is needed for payment. Because of different weight of personal cars, busses, lorries (trucks) and other vehicles, they affect the road in different ways. It is of interest to categorize the vehicles into different classes depending of their weight so that the right fee can be set. An automatic road toll system developed by Combitech Traffic Systems AB (now Kapsch TrafficCom AB), Joenkoping, Sweden, classifi...

  20. 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).

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

    Directory of Open Access Journals (Sweden)

    F.

    2012-04-01

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

  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

    they are responsive or unresponsive based on what is in their best interest at the time. Media and privacy groups get their power from controversy ; the...of potential suspect identification. To do so, the thesis examines all systems’ basic capabilities, privacy issues or concerns, best practices...systems’ basic capabilities, privacy issues or concerns, best practices, possible areas for improvement, and policy considerations. Since the

  3. An overload behavior detection system for engineering transport vehicles based on deep learning

    Science.gov (United States)

    Zhou, Libo; Wu, Gang

    2018-04-01

    This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

  4. Identity verification using computer vision for automatic garage door opening

    NARCIS (Netherlands)

    Wijnhoven, R.G.J.; With, de P.H.N.

    2011-01-01

    We present a novel system for automatic identification of vehicles as part of an intelligent access control system for a garage entrance. Using a camera in the door, cars are detected and matched to the database of authenticated cars. Once a car is detected, License Plate Recognition (LPR) is

  5. Vehicle rollover risk and electronic stability control systems.

    Science.gov (United States)

    MacLennan, P A; Marshall, T; Griffin, R; Purcell, M; McGwin, G; Rue, L W

    2008-06-01

    Electronic stability control (ESC) systems were developed to reduce motor vehicle collisions (MVCs) caused by loss of control. Introduced in Europe in 1995 and in the USA in 1996, ESC is designed to improve vehicle lateral stability by electronically detecting and automatically assisting drivers in unfavorable situations. To examine the relationship between vehicle rollover risk and presence of ESC using a large national database of MVCs. A retrospective cohort study for the period 1995 through 2006 was carried out using data obtained from the National Automotive Sampling System General Estimates System. All passenger cars and sport utility vehicles (SUVs)/vans of model year 1996 and later were eligible. Vehicle ESC (unavailable, optional, standard) was determined on the basis of make, model, and model year. Risk ratios (RRs) and 95% CIs were calculated to compare rollover risk by vehicle ESC group. For all crashes, vehicles equipped with standard ESC had decreased risk of rollover (RR = 0.62, 95% CI 0.50 to 0.77) compared with vehicles with ESC unavailable. The association was consistent for single-vehicle MVCs (RR = 0.61, 95% CI 0.46 to 0.82); passenger cars had decreased rollover risk (RR = 0.77, 95% CI 0.52 to 1.12), but SUVs/vans had a more dramatically decreased risk (RR = 0.40, 95% CI 0.26 to 0.61). This study supports previous results showing ESC to be effective in reducing the risk of rollover. ESC is more effective in SUVs/vans for rollovers related to single-vehicle MVCs.

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

    Indian Academy of Sciences (India)

    with DIARETDB0 and DIARETDB1 datasets using a classifier based on multi- ... developed, the accurate detection of microaneurysm in colour retinal images .... Two dictionary elements of vessel and non-vessel were used in the sparse rep- ..... Images are analyzed from the point of view of its specific microstructures: ridges,.

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

    Science.gov (United States)

    2012-01-01

    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. PMID:22336431

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

    NARCIS (Netherlands)

    Le quang, Thuan; Baldi, S.

    2018-01-01

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

  9. 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

  10. Development of automatic ultrasonic testing system and its application

    International Nuclear Information System (INIS)

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

    1997-01-01

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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Makili, L. [Dpto. Informatica y Automatica - UNED, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain); Dormido-Canto, S., E-mail: sebas@dia.uned.e [Dpto. Informatica y Automatica - UNED, Madrid (Spain); Pastor, I.; Pereira, A. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain); Farias, G. [Dpto. Informatica y Automatica - UNED, Madrid (Spain); Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M.C. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain); Busch, P. [FOM Institut voor PlasmaFysica Rijnhuizen, Nieuwegein (Netherlands)

    2010-07-15

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

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

    International Nuclear Information System (INIS)

    Gaubatz, D.C.

    1996-01-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

  15. 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

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

    OpenAIRE

    Jenie, Y.I.

    2017-01-01

    In the last decade, the commercial values of Unmanned Aerial Vehicles (UAV), defined as devices that are capable of sustainable flights in the atmosphere that do not require to have a human (pilot) on-board, become widely recognized thanks to the advancement of technology in materials, sensors, computation, and telemetry. As UAVs are becoming cheaper and more user-friendly, many companies are motivated to incorporate them in their everyday business, such as for delivery services, journalisms,...

  17. 33 CFR 401.20 - Automatic Identification System.

    Science.gov (United States)

    2010-07-01

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

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

    OpenAIRE

    Lindstrom, Tedric R.

    2014-01-01

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

  19. Automatic EEG spike detection.

    Science.gov (United States)

    Harner, Richard

    2009-10-01

    Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

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

    Science.gov (United States)

    2014-12-01

    digital selective calling EPIRB Emergency Position Indicting Radio Beacon EU European Union FAA Federal Aviation Administration GAO U. S. Government...that has visited a hovering vessel or received merchandise outside the territorial sea. A hovering vessel is defined as a vessel loitering offshore...often with the intent to introduce merchandise into the United States illegally. Departing the United States and transiting international or foreign

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

    Science.gov (United States)

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

    2015-11-01

    Avalanche risk management is strongly related to the ability to identify and timely report the occurrence of snow avalanches. Infrasound has been applied to avalanche research and monitoring for the last 20 years but it never turned into an operational tool to identify clear signals related to avalanches. We present here a method based on the analysis of infrasound signals recorded by a small aperture array in Ischgl (Austria), which provides a significant improvement to overcome this limit. The method is based on array-derived wave parameters, such as back azimuth and apparent velocity. The method defines threshold criteria for automatic avalanche identification by considering avalanches as a moving source of infrasound. We validate the efficiency of the automatic infrasound detection with continuous observations with Doppler radar and we show how the velocity of a snow avalanche in any given path around the array can be efficiently derived. Our results indicate that a proper infrasound array analysis allows a robust, real-time, remote detection of snow avalanches that is able to provide the number and the time of occurrence of snow avalanches occurring all around the array, which represent key information for a proper validation of avalanche forecast models and risk management in a given area.

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

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2012-01-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

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

    Science.gov (United States)

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

    2003-08-01

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

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

    Directory of Open Access Journals (Sweden)

    I.V. Zimchuk

    2017-04-01

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

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

    Science.gov (United States)

    2013-07-01

    DTRA-TR-13-48 Low Power, Room Temperature Systems for the Detection and Identification of Radionuclides from Atmospheric Nuclear Test Approved for...01-C-0071 Radionuclides from Atmospheric Nuclear Tests 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Muren Chu...I IIlIl4eI ilf "tt""f;lk~ l).t::l’e.do)- mllin:: in an n-t~’J𔃻f mlllril.: II!’ ,-kll ~".r’I::!, ..... ·hkh j,-, .:auI,,·d br thP . la-ek f.r ·;IIff

  7. Detection system for the identification of heavy ions

    International Nuclear Information System (INIS)

    Abriola, Daniel H.; Arazi, Andres; Achterberg, Erhard; Capurro, Oscar A.; Fernandez Niello, Jorge O.; Ferrero, Armando M. J.; Liberman, Rosa G.; Marti, Guillermo V.; Pacheco, Alberto J.; Ramirez, Marcelo C.; Testoni, Jorge E.

    1999-01-01

    The TANDAR laboratory has a magnetic spectrometer as one of its detection facilities. This device allows the separation of incident particles according to the relation between their lineal momentum and their charge state. To complete this identification there are two alternatives: 1) A system of three detectors consisting of a multiwire detector, an ionization chamber and scintillators; 2) A segmented anode ionization chamber. (author)

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

    Directory of Open Access Journals (Sweden)

    Ming-Shyan Wang

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-04-01

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

  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, van den P.P.J.

    2009-01-01

    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 measurement

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

    CERN Document Server

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jaehoon Jung

    2016-06-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

  15. Automatic detection and classification of human epicardial atrial unipolar electrograms

    International Nuclear Information System (INIS)

    Dubé, B; Vinet, A; Xiong, F; Yin, Y; LeBlanc, A-R; Pagé, P

    2009-01-01

    This paper describes an unsupervised signal processing method applied to three-channel unipolar electrograms recorded from human atria. These were obtained by epicardial wires sutured on the right and left atria after coronary artery bypass surgery. Atrial (A) and ventricular (V) activations had to be detected and identified on each channel, and gathered across the channels when belonging to the same global event. The algorithm was developed and optimized on a training set of 19 recordings of 5 min. It was assessed on twenty-seven 2 h recordings taken just before the onset of a prolonged atrial fibrillation for a total of 1593697 activations that were validated and classified as normal atrial or ventricular activations (A, V) and premature atrial or ventricular activations (PAA, PVA). 99.93% of the activations were detected, and amongst these, 99.89% of the A and 99.75% of the V activations were correctly labelled. In the subset of the 39705 PAA, 99.83% were detected and 99.3% were correctly classified as A. The false positive rate was 0.37%. In conclusion, a reliable fully automatic detection and classification algorithm was developed that can detect and discriminate A and V activations from atrial recordings. It can provide the time series needed to develop a monitoring system aiming to identify dynamic predictors of forthcoming cardiac events such as postoperative atrial fibrillation

  16. Automatic Adviser on stationary devices status identification and anticipated change

    Science.gov (United States)

    Shabelnikov, A. N.; Liabakh, N. N.; Gibner, Ya M.; Pushkarev, E. A.

    2018-05-01

    A task is defined to synthesize an Automatic Adviser to identify the automation systems stationary devices status using an autoregressive model of changing their key parameters. An applied model type was rationalized and the research objects monitoring process algorithm was developed. A complex of mobile objects status operation simulation and prediction results analysis was proposed. Research results are commented using a specific example of a hump yard compressor station. The work was supported by the Russian Fundamental Research Fund, project No. 17-20-01040.

  17. 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)

  18. Kalman and particle filtering methods for full vehicle and tyre identification

    Science.gov (United States)

    Bogdanski, Karol; Best, Matthew C.

    2018-05-01

    This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators.

  19. Automatic detection and analysis of nuclear plant malfunctions

    International Nuclear Information System (INIS)

    Bruschi, R.; Di Porto, P.; Pallottelli, R.

    1985-01-01

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

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

    CERN Document Server

    2004-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Juan Jesús Castillo Aguilar

    2015-12-01

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

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

    Science.gov (United States)

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

    2015-12-19

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

  3. PLC Based Automatic Multistoried Car Parking System

    OpenAIRE

    Swanand S .Vaze; Rohan S. Mithari

    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...

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

    NARCIS (Netherlands)

    Jenie, Y.I.

    2017-01-01

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

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

    Science.gov (United States)

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

    2016-08-01

    Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    Energy Technology Data Exchange (ETDEWEB)

    Makili, L.; Dormido-Canto, S. [UNED, Madrid (Spain); Vega, J.; Pastor, I.; Pereira, A.; Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M. [Association EuratomCIEMAT para Fusion, Madrid (Spain); Busch, P. [FOM Instituut voor PlasmaFysica Rijnhuizen, Nieuwegein (Netherlands)

    2009-07-01

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

  7. 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

  8. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2009-07-21

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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

    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 6 copies

  12. 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.

  13. Detection and identification of concealed weapons using matrix pencil

    Science.gov (United States)

    Adve, Raviraj S.; Thayaparan, Thayananthan

    2011-06-01

    The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

  14. HARDWARE TROJAN IDENTIFICATION AND DETECTION

    OpenAIRE

    Samer Moein; Fayez Gebali; T. Aaron Gulliver; Abdulrahman Alkandari

    2017-01-01

    ABSTRACT The majority of techniques developed to detect hardware trojans are based on specific attributes. Further, the ad hoc approaches employed to design methods for trojan detection are largely ineffective. Hardware trojans have a number of attributes which can be used to systematically develop detection techniques. Based on this concept, a detailed examination of current trojan detection techniques and the characteristics of existing hardware trojans is presented. This is used to dev...

  15. Development of a Data Acquisition System for Unmanned Aerial Vehicle (UAV) System Identification

    Science.gov (United States)

    Lear, Donald Joseph

    Aircraft system identification techniques are developed for fixed wing Unmanned Aerial Vehicles (UAV). The use of a designed flight experiment with measured system inputs/outputs can be used to derive aircraft stability derivatives. This project set out to develop a methodology to support an experiment to model pitch damping in the longitudinal short-period mode of a UAV. A Central Composite Response Surface Design was formed using angle of attack and power levels as factors to test for the pitching moment coefficient response induced by a multistep pitching maneuver. Selecting a high-quality data acquisition platform was critical to the success of the project. This system was designed to support fixed wing research through the addition of a custom air data vane capable of measuring angle of attack and sideslip, as well as an airspeed sensor. A Pixhawk autopilot system serves as the core and modification of the device firmware allowed for the integration of custom sensors and custom RC channels dedicated to performing system identification maneuvers. Tests were performed on all existing Pixhawk sensors to validate stated uncertainty values. The air data system was calibrated in a low speed wind tunnel and dynamic performance was verified. The assembled system was then installed in a commercially available UAV known as an Air Titan FPV in order to test the Pixhawk's automated flight maneuvers and determine the final performance of each sensor. Flight testing showed all the critical sensors produced acceptable data for further research. The Air Titan FPV airframe was found to be very flexible and did not lend itself well to accurate measurement of inertial properties. This realization prohibited the construction of the required math models for longitudinal dynamics. It is recommended that future projects using the developed methods choose an aircraft with a more rigid airframe.

  16. Development of Regenerative Braking Co-operative Control System for Automatic Transmission-based Hybrid Electric Vehicle using Electronic Wedge Brake

    OpenAIRE

    Ko, Jiweon; Ko, Sungyeon; Bak, Yongsun; Jang, Mijeong; Yoo, Byoungsoo; Cheon, Jaeseung; Kim, Hyunsoo

    2013-01-01

    This research proposes a regenerative braking co-operative control system for the automatic transmission (AT)-based hybrid electric vehicle (HEV). The brake system of the subject HEV consists of the regenerative braking and the electronic wedge brake (EWB) friction braking for the front wheel, and the hydraulic friction braking for the rear wheel. A regenerative braking co-operative control algorithm is suggested for the regenerative braking and friction braking, which distributes the braking...

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

    Science.gov (United States)

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

    2009-02-10

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

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

    DEFF Research Database (Denmark)

    Sun, Zhen

    equation, the ISDE model generally consists of not only a structured deterministic part called drift term, but also a structured random part called diffusion term. The model can describe the system in which the random features are correlated with system states (inputs, outputs) and this relationship can......Interest in nonlinear system identification has grown significantly in recent years. It is much more difficult to develop general results than the concern for linear models since the nonlinear model structures are often much more complicated. As a consequence, the thesis only considers two...... 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...

  19. Automatic acoustic and vibration monitoring system for nuclear power plants

    International Nuclear Information System (INIS)

    Tothmatyas, Istvan; Illenyi, Andras; Kiss, Jozsef; Komaromi, Tibor; Nagy, Istvan; Olchvary, Geza

    1990-01-01

    A diagnostic system for nuclear power plant monitoring is described. Acoustic and vibration diagnostics can be applied to monitor various reactor components and auxiliary equipment including primary circuit machinery, leak detection, integrity of reactor vessel, loose parts monitoring. A noise diagnostic system has been developed for the Paks Nuclear Power Plant, to supervise the vibration state of primary circuit machinery. An automatic data acquisition and processing system is described for digitalizing and analysing diagnostic signals. (R.P.) 3 figs

  20. Performance of arthroscopic irrigation systems assessed with automatic blood detection

    NARCIS (Netherlands)

    Tuijthof, G. J. M.; de Vaal, M. M.; Sierevelt, I. N.; Blankevoort, L.; van der List, M. P. J.

    2011-01-01

    During arthroscopies, bleeding episodes occur as a result of tissue damage. Irrigation systems assist in minimizing these disturbances. The performance of three arthroscopic irrigation systems in clearing bleeding episodes was evaluated objectively. One surgeon performed 99 shoulder arthroscopies

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

    OpenAIRE

    ThetKoKo; ZawMyoTun; Hla Myo Tun

    2015-01-01

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

  2. 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.

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

    Science.gov (United States)

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

    2017-01-20

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

  4. Slip Ratio Estimation and Regenerative Brake Control for Decelerating Electric Vehicles without Detection of Vehicle Velocity and Acceleration

    Science.gov (United States)

    Suzuki, Toru; Fujimoto, Hiroshi

    In slip ratio control systems, it is necessary to detect the vehicle velocity in order to obtain the slip ratio. However, it is very difficult to measure this velocity directly. We have proposed slip ratio estimation and control methods that do not require the vehicle velocity with acceleration. In this paper, the slip ratio estimation and control methods are proposed without detecting the vehicle velocity and acceleration when it is decelerating. We carried out simulations and experiments by using an electric vehicle to verify the effectiveness of the proposed method.

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

    Science.gov (United States)

    McIntosh, Dawn

    2006-01-01

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

  6. 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.

  7. 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.

  8. Automatic control systems engineering

    International Nuclear Information System (INIS)

    Shin, Yun Gi

    2004-01-01

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

  9. Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode

    Directory of Open Access Journals (Sweden)

    Tao Ye

    2018-06-01

    Full Text Available Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net. It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.

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

    Science.gov (United States)

    Zhang, Yongjie; Wang, Jian; Yang, Xin

    2017-08-01

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

  11. Automatic Shadow Detection and Removal from a Single Image.

    Science.gov (United States)

    Khan, Salman H; Bennamoun, Mohammed; Sohel, Ferdous; Togneri, Roberto

    2016-03-01

    We present a framework to automatically detect and remove shadows in real world scenes from a single image. Previous works on shadow detection put a lot of effort in designing shadow variant and invariant hand-crafted features. In contrast, our framework automatically learns the most relevant features in a supervised manner using multiple convolutional deep neural networks (ConvNets). The features are learned at the super-pixel level and along the dominant boundaries in the image. The predicted posteriors based on the learned features are fed to a conditional random field model to generate smooth shadow masks. Using the detected shadow masks, we propose a Bayesian formulation to accurately extract shadow matte and subsequently remove shadows. The Bayesian formulation is based on a novel model which accurately models the shadow generation process in the umbra and penumbra regions. The model parameters are efficiently estimated using an iterative optimization procedure. Our proposed framework consistently performed better than the state-of-the-art on all major shadow databases collected under a variety of conditions.

  12. Parking Space Detection and Trajectory Tracking Control for Vehicle Auto-Parking

    OpenAIRE

    Shiuh-Jer Huang; Yu-Sheng Hsu

    2017-01-01

    On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be u...

  13. 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.

  14. Automated Vehicle Monitoring System

    OpenAIRE

    Wibowo, Agustinus Deddy Arief; Heriansyah, Rudi

    2014-01-01

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

  15. Bus Travel Time Deviation Analysis Using Automatic Vehicle Location Data and Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Xiaolin Gong

    2015-01-01

    Full Text Available To investigate the influences of causes of unreliability and bus schedule recovery phenomenon on microscopic segment-level travel time variance, this study adopts Structural Equation Modeling (SEM to specify, estimate, and measure the theoretical proposed models. The SEM model establishes and verifies hypotheses for interrelationships among travel time deviations, departure delays, segment lengths, dwell times, and number of traffic signals and access connections. The finally accepted model demonstrates excellent fitness. Most of the hypotheses are supported by the sample dataset from bus Automatic Vehicle Location system. The SEM model confirms the bus schedule recovery phenomenon. The departure delays at bus terminals and upstream travel time deviations indeed have negative impacts on travel time fluctuation of buses en route. Meanwhile, the segment length directly and negatively impacts travel time variability and inversely positively contributes to the schedule recovery process; this exogenous variable also indirectly and positively influences travel times through the existence of signalized intersections and access connections. This study offers a rational approach to analyzing travel time deviation feature. The SEM model structure and estimation results facilitate the understanding of bus service performance characteristics and provide several implications for bus service planning, management, and operation.

  16. 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.

  17. 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.

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

    Science.gov (United States)

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

    2017-12-01

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

  19. Automatic correspondence detection in mammogram and breast tomosynthesis images

    Science.gov (United States)

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

    2012-02-01

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

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

    Science.gov (United States)

    Zichner, Ralf; Baumann, Reinhard R.

    2013-05-01

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

  1. 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.

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

    International Nuclear Information System (INIS)

    Basner, Mathias; Müller, Uwe; Elmenhorst, Eva-Maria; Kluge, Götz; Griefahn, Barbara

    2008-01-01

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

  3. Hybrid and Electric Advanced Vehicle Systems Simulation

    Science.gov (United States)

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

    1985-01-01

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

  4. Vehicle systems: coupled and interactive dynamics analysis

    Science.gov (United States)

    Vantsevich, Vladimir V.

    2014-11-01

    This article formulates a new direction in vehicle dynamics, described as coupled and interactive vehicle system dynamics. Formalised procedures and analysis of case studies are presented. An analytical consideration, which explains the physics of coupled system dynamics and its consequences for dynamics of a vehicle, is given for several sets of systems including: (i) driveline and suspension of a 6×6 truck, (ii) a brake mechanism and a limited slip differential of a drive axle and (iii) a 4×4 vehicle steering system and driveline system. The article introduces a formal procedure to turn coupled system dynamics into interactive dynamics of systems. A new research direction in interactive dynamics of an active steering and a hybrid-electric power transmitting unit is presented and analysed to control power distribution between the drive axles of a 4×4 vehicle. A control strategy integrates energy efficiency and lateral dynamics by decoupling dynamics of the two systems thus forming their interactive dynamics.

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

    Science.gov (United States)

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

    2017-08-25

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

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

    International Nuclear Information System (INIS)

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

    2011-01-01

    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 2 -C 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.

  7. 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.

  8. Fundamental problems in fault detection and identification

    DEFF Research Database (Denmark)

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

    1999-01-01

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

  9. Microprocessor controlled system for automatic and semi-automatic syntheses of radiopharmaceuticals

    International Nuclear Information System (INIS)

    Ruth, T.J.; Adam, M.J.; Morris, D.; Jivan, S.

    1986-01-01

    A computer based system has been constructed to control the automatic synthesis of 2-deoxy-2-( 18 F)fluoro-D-glucose and is also being used in the development of an automatic synthesis of L-6-( 18 F)fluorodopa. (author)

  10. 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.

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

    Science.gov (United States)

    2007-05-03

    Navassa Island, and Kingman Reef . 3 Through an agreement with the Republic of the Marshall Islands Government, US actions at USAKA are subject to...tripod (similar to the RE used at the Hosted Sites) 15 RAIDRS Block 10 Final Environmental Assessment Banana R ive r A t l an t i c...operations, wastewater treatment plants , fuel storage tanks, aircraft and ground vehicle refueling and maintenance operations, soil

  12. Differences between automatically detected and steady-state fractional flow reserve.

    Science.gov (United States)

    Härle, Tobias; Meyer, Sven; Vahldiek, Felix; Elsässer, Albrecht

    2016-02-01

    Measurement of fractional flow reserve (FFR) has become a standard diagnostic tool in the catheterization laboratory. FFR evaluation studies were based on pressure recordings during steady-state maximum hyperemia. Commercially available computer systems detect the lowest Pd/Pa ratio automatically, which might not always be measured during steady-state hyperemia. We sought to compare the automatically detected FFR and true steady-state FFR. Pressure measurement traces of 105 coronary lesions from 77 patients with intermediate coronary lesions or multivessel disease were reviewed. In all patients, hyperemia had been achieved by intravenous adenosine administration using a dosage of 140 µg/kg/min. In 42 lesions (40%) automatically detected FFR was lower than true steady-state FFR. Mean bias was 0.009 (standard deviation 0.015, limits of agreement -0.02, 0.037). In 4 lesions (3.8%) both methods lead to different treatment recommendations, in all 4 cases instantaneous wave-free ratio confirmed steady-state FFR. Automatically detected FFR was slightly lower than steady-state FFR in more than one-third of cases. Consequently, interpretation of automatically detected FFR values closely below the cutoff value requires special attention.

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

    Science.gov (United States)

    Jeong, Sangheon; Kang, Seongkoo; Kim, Joongkyu

    2013-07-01

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

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

    NARCIS (Netherlands)

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

    2010-01-01

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

  15. Toward detection of marine vehicles on horizon from buoy camera

    Science.gov (United States)

    Fefilatyev, Sergiy; Goldgof, Dmitry B.; Langebrake, Lawrence

    2007-10-01

    This paper presents a new technique for automatic detection of marine vehicles in open sea from a buoy camera system using computer vision approach. Users of such system include border guards, military, port safety and flow management, sanctuary protection personnel. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them on the subject of presence of marine vehicles. The goal of the system is to detect an approximate window around the ship and prepare the small image for transmission and human evaluation. The proposed computer vision-based algorithm combines horizon detection method with edge detection and post-processing. The dataset of 100 images is used to evaluate the performance of proposed technique. We discuss promising results of ship detection and suggest necessary improvements for achieving better performance.

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

    Science.gov (United States)

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

    2013-11-15

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

  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. Automatic age-related macular degeneration detection and staging

    Science.gov (United States)

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

    2013-03-01

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

  19. SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Jani, S; Low, D; Lamb, J [UCLA, Los Angeles, CA (United States)

    2015-06-15

    Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and

  20. SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

    International Nuclear Information System (INIS)

    Jani, S; Low, D; Lamb, J

    2015-01-01

    Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and

  1. 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

  2. Vehicle Detection and Classification Using Passive Infrared Sensing

    KAUST Repository

    Odat, Enas M.; Mousa, Mustafa; Claudel, Christian

    2015-01-01

    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

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

    International Nuclear Information System (INIS)

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

    2004-01-01

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

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

    Science.gov (United States)

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

    2017-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-15

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

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

    International Nuclear Information System (INIS)

    Perez-Cabre, E; Millan, M S; Javidi, B

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    CHEN Chi

    2018-02-01

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

  8. VIRMS: A VEHICLE INFORMATION AND ROAD MONITORING SYSTEM

    Directory of Open Access Journals (Sweden)

    Fabio Arnéz

    2014-01-01

    Full Text Available Intelligent Transport Systems (ITS are emerging technologies for building collaborative vehicular networks to increase road safety and to improve driver’s experience. Unfortunately these technologies require heavy infrastructure to be deployed inside and outside the vehicle that is difficult to extend. In this article we present VIRMS (Vehicle Information and Road Monitoring System, an ITS that is based on low-cost and small footprint client and server infrastructure that was designed to increase vehicular security and reduce accident rates along highways. The VIRMS remote client device is an on board vehicle electronic device that gathers data from sensors and processes the collected data that is sent to the VIRMS server in order to keep drivers informed with precise context information through the detection and identification of events (accidents, traffic jams, bad weather conditions, etc. along the roads. A prototype running tests on Bolivian highways show that VIRMS can give a technological answer to a real problem where road safety is one of the highest issues and cause of mortality.

  9. Automatic detection and classification of EOL-concrete and resulting recovered products by hyperspectral imaging

    Science.gov (United States)

    Palmieri, Roberta; Bonifazi, Giuseppe; Serranti, Silvia

    2014-05-01

    The recovery of materials from Demolition Waste (DW) represents one of the main target of the recycling industry and the its characterization is important in order to set up efficient sorting and/or quality control systems. End-Of-Life (EOL) concrete materials identification is necessary to maximize DW conversion into useful secondary raw materials, so it is fundamental to develop strategies for the implementation of an automatic recognition system of the recovered products. In this paper, HyperSpectral Imaging (HSI) technique was applied in order to detect DW composition. Hyperspectral images were acquired by a laboratory device equipped with a HSI sensing device working in the near infrared range (1000-1700 nm): NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Acquired spectral data were analyzed adopting the PLS_Toolbox (Version 7.5, Eigenvector Research, Inc.) under Matlab® environment (Version 7.11.1, The Mathworks, Inc.), applying different chemometric methods: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square- Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials, distinguishing recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood, foam, etc.). The developed procedure is cheap, fast and non-destructive: it could be used to make some steps of the recycling process more efficient and less expensive.

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

    Directory of Open Access Journals (Sweden)

    Jianqiang Ren

    2014-01-01

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

  11. Visible and NIR spectral band combination to produce high security ID tags for automatic identification

    Science.gov (United States)

    Pérez-Cabré, Elisabet; Millán, María S.; Javidi, Bahram

    2006-09-01

    Verification of a piece of information and/or authentication of a given object or person are common operations carried out by automatic security systems that can be applied, for instance, to control the entrance to restricted areas, access to public buildings, identification of cardholders, etc. Vulnerability of such security systems may depend on the ease of counterfeiting the information used as a piece of identification for verification and authentication. To protect data against tampering, the signature that identifies an object is usually encrypted to avoid an easy recognition at human sight and an easy reproduction using conventional devices for imaging or scanning. To make counterfeiting even more difficult, we propose to combine data from visible and near infrared (NIR) spectral bands. By doing this, neither the visible content nor the NIR data by theirselves are sufficient to allow the signature recognition and thus, the identification of a given object. Only the appropriate combination of both signals permits a satisfactory authentication. In addition, the resulting signature is encrypted following a fully-phase encryption technique and the obtained complex-amplitude distribution is encoded on an ID tag. Spatial multiplexing of the encrypted signature allows us to build a distortion-invariant ID tag, so that remote authentication can be achieved even if the tag is captured under rotation or at different distances. We also explore the possibility of using partial information of the encrypted signature to simplify the ID tag design.

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

    Directory of Open Access Journals (Sweden)

    Hyungchul Yoon

    2017-09-01

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

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

    NARCIS (Netherlands)

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

    1999-01-01

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

  14. Automatic Identification and Reconstruction of the Right Phrenic Nerve on Computed Tomography

    OpenAIRE

    Bamps, Kobe; Cuypers, Céline; Polmans, Pieter; Claesen, Luc; Koopman, Pieter

    2016-01-01

    An automatic computer algorithm was successfully constructed, enabling identification and reconstruction of the right phrenic nerve on high resolution coronary computed tomography scans. This could lead to a substantial reduction in the incidence of phrenic nerve paralysis during pulmonary vein isolation using ballon techniques.

  15. Automatic Detection of Fake News

    OpenAIRE

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

    2017-01-01

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

  16. Energy optimized automatic public transportation system with a microprocessor in the vehicle

    Energy Technology Data Exchange (ETDEWEB)

    Tchinda, A.

    1980-09-11

    The matter with energy optimizing running is, that the train reaches the final state (target station) from the initial state (original station) in time with consideration of the given safety demands and other limitations and the consumed energy has its minimal value. This principle was extended for a driverless train operation in a sense that the optimization problem was formulated new and solved with regards to extensive secondary conditions as: velocity-dependent train and braking power and motion resistance force, path-dependent maximum velocity of the route and hazardous points. The algorithms for optimal vehicle control were developed by means of E. Bellmann's dynamic programming with regards to the secondary conditions mentioned above.

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

    Directory of Open Access Journals (Sweden)

    Xiaoyun Huang

    2015-09-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  19. 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.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Vlad Turcu

    2012-09-01

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

  2. A Method for Automatic Image Rectification and Stitching for Vehicle Yaw Marks Trajectory Estimation

    Directory of Open Access Journals (Sweden)

    Vidas Žuraulis

    2016-02-01

    Full Text Available The aim of this study has been to propose a new method for automatic rectification and stitching of the images taken on the accident site. The proposed method does not require any measurements to be performed on the accident site and thus it is frsjebalaee of measurement errors. The experimental investigation was performed in order to compare the vehicle trajectory estimation according to the yaw marks in the stitched image and the trajectory, reconstructed using the GPS data. The overall mean error of the trajectory reconstruction, produced by the method proposed in this paper was 0.086 m. It was only 0.18% comparing to the whole trajectory length.

  3. Camouflage, detection and identification of moving targets.

    Science.gov (United States)

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

    2013-05-07

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

  4. Automatic identification of mass spectra

    International Nuclear Information System (INIS)

    Drabloes, F.

    1992-01-01

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

  5. Towards the automatic detection and analysis of sunspot rotation

    Science.gov (United States)

    Brown, Daniel S.; Walker, Andrew P.

    2016-10-01

    Torsional rotation of sunspots have been noted by many authors over the past century. Sunspots have been observed to rotate up to the order of 200 degrees over 8-10 days, and these have often been linked with eruptive behaviour such as solar flares and coronal mass ejections. However, most studies in the literature are case studies or small-number studies which suffer from selection bias. In order to better understand sunspot rotation and its impact on the corona, unbiased large-sample statistical studies are required (including both rotating and non-rotating sunspots). While this can be done manually, a better approach is to automate the detection and analysis of rotating sunspots using robust methods with well characterised uncertainties. The SDO/HMI instrument provide long-duration, high-resolution and high-cadence continuum observations suitable for extracting a large number of examples of rotating sunspots. This presentation will outline the analysis of SDI/HMI data to determine the rotation (and non-rotation) profiles of sunspots for the complete duration of their transit across the solar disk, along with how this can be extended to automatically identify sunspots and initiate their analysis.

  6. 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.

  7. Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring.

    Science.gov (United States)

    Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

    2013-06-17

    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.

  8. Automatic Test Systems Aquisition

    National Research Council Canada - National Science Library

    1994-01-01

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

  9. Safety problems in vehicles with adaptive cruise control system

    Directory of Open Access Journals (Sweden)

    Yadav Arun K.

    2017-06-01

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

  10. 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.

  11. 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.

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

    Science.gov (United States)

    Chen, Hongbin

    2018-03-01

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

  13. Automatic detection and quantitative analysis of cells in the mouse primary motor cortex

    Science.gov (United States)

    Meng, Yunlong; He, Yong; Wu, Jingpeng; Chen, Shangbin; Li, Anan; Gong, Hui

    2014-09-01

    Neuronal cells play very important role on metabolism regulation and mechanism control, so cell number is a fundamental determinant of brain function. Combined suitable cell-labeling approaches with recently proposed three-dimensional optical imaging techniques, whole mouse brain coronal sections can be acquired with 1-μm voxel resolution. We have developed a completely automatic pipeline to perform cell centroids detection, and provided three-dimensional quantitative information of cells in the primary motor cortex of C57BL/6 mouse. It involves four principal steps: i) preprocessing; ii) image binarization; iii) cell centroids extraction and contour segmentation; iv) laminar density estimation. Investigations on the presented method reveal promising detection accuracy in terms of recall and precision, with average recall rate 92.1% and average precision rate 86.2%. We also analyze laminar density distribution of cells from pial surface to corpus callosum from the output vectorizations of detected cell centroids in mouse primary motor cortex, and find significant cellular density distribution variations in different layers. This automatic cell centroids detection approach will be beneficial for fast cell-counting and accurate density estimation, as time-consuming and error-prone manual identification is avoided.

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  15. Towards the Automatic Detection of Pre-Existing Termite Mounds through UAS and Hyperspectral Imagery.

    Science.gov (United States)

    Sandino, Juan; Wooler, Adam; Gonzalez, Felipe

    2017-09-24

    The increased technological developments in Unmanned Aerial Vehicles (UAVs) combined with artificial intelligence and Machine Learning (ML) approaches have opened the possibility of remote sensing of extensive areas of arid lands. In this paper, a novel approach towards the detection of termite mounds with the use of a UAV, hyperspectral imagery, ML and digital image processing is intended. A new pipeline process is proposed to detect termite mounds automatically and to reduce, consequently, detection times. For the classification stage, several ML classification algorithms' outcomes were studied, selecting support vector machines as the best approach for their role in image classification of pre-existing termite mounds. Various test conditions were applied to the proposed algorithm, obtaining an overall accuracy of 68%. Images with satisfactory mound detection proved that the method is "resolution-dependent". These mounds were detected regardless of their rotation and position in the aerial image. However, image distortion reduced the number of detected mounds due to the inclusion of a shape analysis method in the object detection phase, and image resolution is still determinant to obtain accurate results. Hyperspectral imagery demonstrated better capabilities to classify a huge set of materials than implementing traditional segmentation methods on RGB images only.

  16. 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.

  17. Automatic control of a robotic vehicle

    Science.gov (United States)

    Mcreynolds, S. R.

    1976-01-01

    Over the last several years Jet Propulsion Laboratory has been engaged in a project to develop some of the technology required to build a robotic vehicle for exploring planetary surfaces. An overview of hardware and software being developed for this project is given. Particular emphasis is placed on the description of the current design for the Vehicle System required for locomotion and the path planning algorithm.

  18. Development report: Automatic System Test and Calibration (ASTAC) equipment

    Science.gov (United States)

    Thoren, R. J.

    1981-01-01

    A microcomputer based automatic test system was developed for the daily performance monitoring of wind energy system time domain (WEST) analyzer. The test system consists of a microprocessor based controller and hybrid interface unit which are used for inputing prescribed test signals into all WEST subsystems and for monitoring WEST responses to these signals. Performance is compared to theoretically correct performance levels calculated off line on a large general purpose digital computer. Results are displayed on a cathode ray tube or are available from a line printer. Excessive drift and/or lack of repeatability of the high speed analog sections within WEST is easily detected and the malfunctioning hardware identified using this system.

  19. 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.

  20. Particle detection systems and methods

    Science.gov (United States)

    Morris, Christopher L.; Makela, Mark F.

    2010-05-11

    Techniques, apparatus and systems for detecting particles such as muons and neutrons. In one implementation, a particle detection system employs a plurality of drift cells, which can be for example sealed gas-filled drift tubes, arranged on sides of a volume to be scanned to track incoming and outgoing charged particles, such as cosmic ray-produced muons. The drift cells can include a neutron sensitive medium to enable concurrent counting of neutrons. The system can selectively detect devices or materials, such as iron, lead, gold, uranium, plutonium, and/or tungsten, occupying the volume from multiple scattering of the charged particles passing through the volume and can concurrently detect any unshielded neutron sources occupying the volume from neutrons emitted therefrom. If necessary, the drift cells can be used to also detect gamma rays. The system can be employed to inspect occupied vehicles at border crossings for nuclear threat objects.

  1. CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal neutron activated samples

    International Nuclear Information System (INIS)

    Giannini, M.; Oliva, P.R.; Ramorino, C.

    1978-01-01

    A description is given of a computer code which automatically analyses gamma-ray spectra obtained with Ge(Li) detectors. The program contains features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification and calculation of masses and errors. Finally the results obtained with our computer code for a lunar sample are reported and briefly discussed

  2. 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.

  3. Automatic Detection of Electric Power Troubles (ADEPT)

    Science.gov (United States)

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

    1988-11-01

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

  4. Characteristics and design improvement of AP1000 automatic depressurization system

    International Nuclear Information System (INIS)

    Jin Fei

    2012-01-01

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

  5. Sensor Fault Detection and Diagnosis for autonomous vehicles

    Directory of Open Access Journals (Sweden)

    Realpe Miguel

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yong-Yi Fanjiang

    2017-01-01

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

  7. Vehicle systems and payload requirements evaluation. [computer programs for identifying launch vehicle system requirements

    Science.gov (United States)

    Rea, F. G.; Pittenger, J. L.; Conlon, R. J.; Allen, J. D.

    1975-01-01

    Techniques developed for identifying launch vehicle system requirements for NASA automated space missions are discussed. Emphasis is placed on development of computer programs and investigation of astrionics for OSS missions and Scout. The Earth Orbit Mission Program - 1 which performs linear error analysis of launch vehicle dispersions for both vehicle and navigation system factors is described along with the Interactive Graphic Orbit Selection program which allows the user to select orbits which satisfy mission requirements and to evaluate the necessary injection accuracy.

  8. 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,

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Gaurav Ravi

    2016-01-01

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

  11. 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.

  12. Integration of low level and ontology derived features for automatic weapon recognition and identification

    Science.gov (United States)

    Sirakov, Nikolay M.; Suh, Sang; Attardo, Salvatore

    2011-06-01

    This paper presents a further step of a research toward the development of a quick and accurate weapons identification methodology and system. A basic stage of this methodology is the automatic acquisition and updating of weapons ontology as a source of deriving high level weapons information. The present paper outlines the main ideas used to approach the goal. In the next stage, a clustering approach is suggested on the base of hierarchy of concepts. An inherent slot of every node of the proposed ontology is a low level features vector (LLFV), which facilitates the search through the ontology. Part of the LLFV is the information about the object's parts. To partition an object a new approach is presented capable of defining the objects concavities used to mark the end points of weapon parts, considered as convexities. Further an existing matching approach is optimized to determine whether an ontological object matches the objects from an input image. Objects from derived ontological clusters will be considered for the matching process. Image resizing is studied and applied to decrease the runtime of the matching approach and investigate its rotational and scaling invariance. Set of experiments are preformed to validate the theoretical concepts.

  13. Vehicle Theft Identification and Intimation Using GSM & IOT

    Science.gov (United States)

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

    2017-11-01

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

  14. Design of an Automatic Forward and Back Collision Avoidance System for Automobiles

    Directory of Open Access Journals (Sweden)

    Tasneem Sanjana

    2018-01-01

    Full Text Available This paper is the extended reflection of work originally presented in conference of Electrical, Computer and Communication Engineering (ECCE-CUET 2017, entitled “Automated Anti Collision System for Automobiles”. Automated collision avoidance system is a trending technology of science in automobile engineering. The aim of this paper is to design a system which will prevent collision from the front as well as the back for automobiles. This paper gives an overview of secure and smooth journey of car (vehicles as well as the certainty of human life. This system is controlled by microcontroller ATMEGA32. Two Sharp distance sensors are used to detect object within the danger range where one is for front detection and other is for back detection. A crystal oscillator is used to produce the oscillation and generates the clock pulse of the microcontroller. An LCD and a GLCD are used to give information about the safe distance for front and rear respectively, and a buzzer is used as alarm. An actuator is used as automatic brake and inside the actuator there is a motor driver that runs the actuator. For coding “microC PRO for PIC” is used and “Proteus Design Suite Version 8 Software” is used for simulation.

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

    Science.gov (United States)

    Parhad, Ashutosh

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

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

    International Nuclear Information System (INIS)

    Caffrey, A.J.; Hartwell, J.K.; Krebs, K.M.; McLaughlin, G.D.

    1998-01-01

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

  17. Vehicle Remote Health Monitoring and Prognostic Maintenance System

    Directory of Open Access Journals (Sweden)

    Uferah Shafi

    2018-01-01

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

  18. Automatic Management of Parallel and Distributed System Resources

    Science.gov (United States)

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

    1990-01-01

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

  19. Automatic Conflict Detection on Contracts

    Science.gov (United States)

    Fenech, Stephen; Pace, Gordon J.; Schneider, Gerardo

    Many software applications are based on collaborating, yet competing, agents or virtual organisations exchanging services. Contracts, expressing obligations, permissions and prohibitions of the different actors, can be used to protect the interests of the organisations engaged in such service exchange. However, the potentially dynamic composition of services with different contracts, and the combination of service contracts with local contracts can give rise to unexpected conflicts, exposing the need for automatic techniques for contract analysis. In this paper we look at automatic analysis techniques for contracts written in the contract language mathcal{CL}. We present a trace semantics of mathcal{CL} suitable for conflict analysis, and a decision procedure for detecting conflicts (together with its proof of soundness, completeness and termination). We also discuss its implementation and look into the applications of the contract analysis approach we present. These techniques are applied to a small case study of an airline check-in desk.

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

    International Nuclear Information System (INIS)

    Severin, V.P.

    2007-01-01

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

  1. 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.

  2. THE IQMULUS URBAN SHOWCASE: AUTOMATIC TREE CLASSIFICATION AND IDENTIFICATION IN HUGE MOBILE MAPPING POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    J. Böhm

    2016-06-01

    Full Text Available 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.

  3. Presentation of the results of a Bayesian automatic event detection and localization program to human analysts

    Science.gov (United States)

    Kushida, N.; Kebede, F.; Feitio, P.; Le Bras, R.

    2016-12-01

    The Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) has been developing and testing NET-VISA (Arora et al., 2013), a Bayesian automatic event detection and localization program, and evaluating its performance in a realistic operational mode. In our preliminary testing at the CTBTO, NET-VISA shows better performance than its currently operating automatic localization program. However, given CTBTO's role and its international context, a new technology should be introduced cautiously when it replaces a key piece of the automatic processing. We integrated the results of NET-VISA into the Analyst Review Station, extensively used by the analysts so that they can check the accuracy and robustness of the Bayesian approach. We expect the workload of the analysts to be reduced because of the better performance of NET-VISA in finding missed events and getting a more complete set of stations than the current system which has been operating for nearly twenty years. The results of a series of tests indicate that the expectations born from the automatic tests, which show an overall overlap improvement of 11%, meaning that the missed events rate is cut by 42%, hold for the integrated interactive module as well. New events are found by analysts, which qualify for the CTBTO Reviewed Event Bulletin, beyond the ones analyzed through the standard procedures. Arora, N., Russell, S., and Sudderth, E., NET-VISA: Network Processing Vertically Integrated Seismic Analysis, 2013, Bull. Seismol. Soc. Am., 103, 709-729.

  4. 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.

  5. 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.

  6. 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.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Tian Xue Jun

    2016-01-01

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

  9. 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.

  10. Comparison Of Semi-Automatic And Automatic Slick Detection Algorithms For Jiyeh Power Station Oil Spill, Lebanon

    Science.gov (United States)

    Osmanoglu, B.; Ozkan, C.; Sunar, F.

    2013-10-01

    After air strikes on July 14 and 15, 2006 the Jiyeh Power Station started leaking oil into the eastern Mediterranean Sea. The power station is located about 30 km south of Beirut and the slick covered about 170 km of coastline threatening the neighboring countries Turkey and Cyprus. Due to the ongoing conflict between Israel and Lebanon, cleaning efforts could not start immediately resulting in 12 000 to 15 000 tons of fuel oil leaking into the sea. In this paper we compare results from automatic and semi-automatic slick detection algorithms. The automatic detection method combines the probabilities calculated for each pixel from each image to obtain a joint probability, minimizing the adverse effects of atmosphere on oil spill detection. The method can readily utilize X-, C- and L-band data where available. Furthermore wind and wave speed observations can be used for a more accurate analysis. For this study, we utilize Envisat ASAR ScanSAR data. A probability map is generated based on the radar backscatter, effect of wind and dampening value. The semi-automatic algorithm is based on supervised classification. As a classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) classifier is used since it is more flexible and efficient than conventional maximum likelihood classifier for multisource and multi-temporal data. The learning algorithm for ANN MLP is chosen as the Levenberg-Marquardt (LM). Training and test data for supervised classification are composed from the textural information created from SAR images. This approach is semiautomatic because tuning the parameters of classifier and composing training data need a human interaction. We point out the similarities and differences between the two methods and their results as well as underlining their advantages and disadvantages. Due to the lack of ground truth data, we compare obtained results to each other, as well as other published oil slick area assessments.

  11. 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...

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-15

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

  14. A framework for automatic feature extraction from airborne light detection and ranging data

    Science.gov (United States)

    Yan, Jianhua

    Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly

  15. THE AUTOMATIC LIGHTENING LOCATION SYSTEM AND ITS ...

    African Journals Online (AJOL)

    ES Obe

    systems. The implications of the lightening location system for the Nigerian electric power system are also highlighted. ... system (the LLP type) is currently operating in may countries .... (iii) Real time lightning maps will aid service restoration.

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

    Science.gov (United States)

    Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

    2011-11-01

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

  17. Automatic Detection and Classification of Audio Events for Road Surveillance Applications

    Directory of Open Access Journals (Sweden)

    Noor Almaadeed

    2018-06-01

    Full Text Available This work investigates the problem of detecting hazardous events on roads by designing an audio surveillance system that automatically detects perilous situations such as car crashes and tire skidding. In recent years, research has shown several visual surveillance systems that have been proposed for road monitoring to detect accidents with an aim to improve safety procedures in emergency cases. However, the visual information alone cannot detect certain events such as car crashes and tire skidding, especially under adverse and visually cluttered weather conditions such as snowfall, rain, and fog. Consequently, the incorporation of microphones and audio event detectors based on audio processing can significantly enhance the detection accuracy of such surveillance systems. This paper proposes to combine time-domain, frequency-domain, and joint time-frequency features extracted from a class of quadratic time-frequency distributions (QTFDs to detect events on roads through audio analysis and processing. Experiments were carried out using a publicly available dataset. The experimental results conform the effectiveness of the proposed approach for detecting hazardous events on roads as demonstrated by 7% improvement of accuracy rate when compared against methods that use individual temporal and spectral features.

  18. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

    Science.gov (United States)

    Hernández Suárez, Marcos; Astray Dopazo, Gonzalo; Larios López, Dina; Espinosa, Francisco

    2015-01-01

    There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA) or Factor Analysis (FA) have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID) algorithm and Artificial Neural Network (ANN) models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain). Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID) tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness between 44 and 100

  19. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID and Artificial Neural Network Models (ANNs.

    Directory of Open Access Journals (Sweden)

    Marcos Hernández Suárez

    Full Text Available There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA or Factor Analysis (FA have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID algorithm and Artificial Neural Network (ANN models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain. Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness

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

    KAUST Repository

    Pietroy, David; Gereige, Issam; Gourgon, Cé cile

    2013-01-01

    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

  1. 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.

  2. 41 CFR 102-34.85 - What motor vehicles require motor vehicle identification?

    Science.gov (United States)

    2010-07-01

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

  3. The new generation of detection and identification equipment

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kemal Akyol

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2018-04-30

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

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

    Science.gov (United States)

    Ramsey, J. E., Jr.

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

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

    Science.gov (United States)

    Craig, J.; Yerazunis, S. W.

    1978-01-01

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

  9. Automatic RST-based system for a rapid detection of man-made disasters

    Science.gov (United States)

    Tramutoli, Valerio; Corrado, Rosita; Filizzola, Carolina; Livia Grimaldi, Caterina Sara; Mazzeo, Giuseppe; Marchese, Francesco; Pergola, Nicola

    2010-05-01

    Man-made disasters may cause injuries to citizens and damages to critical infrastructures. When it is not possible to prevent or foresee such disasters it is hoped at least to rapidly detect the accident in order to intervene as soon as possible to minimize damages. In this context, the combination of a Robust Satellite Technique (RST), able to identify for sure actual (i.e. no false alarm) accidents, and satellite sensors with high temporal resolution seems to assure both a reliable and a timely detection of abrupt Thermal Infrared (TIR) transients related to dangerous explosions. A processing chain, based on the RST approach, has been developed in the framework of the GMOSS and G-MOSAIC projects by DIFA-UNIBAS team, suitable for automatically identify on MSG-SEVIRI images harmful events. Maps of thermal anomalies are generated every 15 minutes (i.e. SEVIRI temporal repetition rate) over a selected area together with kml files (containing information on latitude and longitude of "thermally" anomalous SEVIRI pixel centre, time of image acquisition, relative intensity of anomalies, etc.) for a rapid visualization of the accident position even on Google Earth. Results achieved in the cases of gas pipelines recently exploded or attacked in Russia and in Iraq will be presented in this work.

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

    OpenAIRE

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

    2008-01-01

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

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

    NARCIS (Netherlands)

    Dong, J.; van Driel, W.D.; Zhang, G.Q.

    2011-01-01

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

  12. Automatic identification of tuberculosis mycobacterium

    Directory of Open Access Journals (Sweden)

    Cicero Ferreira Fernandes Costa Filho

    Full Text Available Introduction According to the Global TB control report of 2013, “Tuberculosis (TB remains a major global health problem. In 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease. Two main sputum smear microscopy techniques are used for TB diagnosis: Fluorescence microscopy and conventional microscopy. Fluorescence microscopy is a more expensive diagnostic method because of the high costs of the microscopy unit and its maintenance. Therefore, conventional microscopy is more appropriate for use in developing countries. Methods This paper presents a new method for detecting tuberculosis bacillus in conventional sputum smear microscopy. The method consists of two main steps, bacillus segmentation and post-processing. In the first step, the scalar selection technique was used to select input variables for the segmentation classifiers from four color spaces. Thirty features were used, including the subtractions of the color components of different color spaces. In the post-processing step, three filters were used to separate bacilli from artifact: a size filter, a geometric filter and a Rule-based filter that uses the components of the RGB color space. Results In bacillus identification, an overall sensitivity of 96.80% and an error rate of 3.38% were obtained. An image database with 120-sputum-smear microscopy slices of 12 patients with objects marked as bacillus, agglomerated bacillus and artifact was generated and is now available online. Conclusions The best results were obtained with a support vector machine in bacillus segmentation associated with the application of the three post-processing filters.

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

    Science.gov (United States)

    Broersen, Tom; Peters, Ravi; Ledoux, Hugo

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-05-02

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

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

    Directory of Open Access Journals (Sweden)

    Dang-Nhac Lu

    2018-03-01

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

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

    Science.gov (United States)

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

    2018-03-29

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

  17. Capacitive system detects and locates fluid leaks

    Science.gov (United States)

    1966-01-01

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

  18. 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

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

    Science.gov (United States)

    2010-12-01

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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. An automatic system to study sperm motility and energetics

    OpenAIRE

    Shi, LZ; Nascimento, JM; Chandsawangbhuwana, C; Botvinick, EL; Berns, MW

    2008-01-01

    An integrated robotic laser and microscope system has been developed to automatically analyze individual sperm motility and energetics. The custom-designed optical system directs near-infrared laser light into an inverted microscope to create a single-point 3-D gradient laser trap at the focal spot of the microscope objective. A two-level computer structure is described that quantifies the sperm motility (in terms of swimming speed and swimming force) and energetics (measuring mid-piece membr...

  5. Vehicle Detection and Classification Using Passive Infrared Sensing

    KAUST Repository

    Odat, Enas M.

    2015-10-19

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

  6. Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

    Science.gov (United States)

    Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

    2007-11-01

    Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-01-15

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

  8. Design And Analysis Of Doppler Radar-Based Vehicle Speed Detection

    Directory of Open Access Journals (Sweden)

    Su Myat Paing

    2015-08-01

    Full Text Available The most unwanted thing to happen to a road user is road accident. Most of the fatal accidents occur due to over speeding. Faster vehicles are more prone to accident than the slower one. Among the various methods for detecting speed of the vehicle object detection systems based on Radar have been replaced for about a century for various purposes like detection of aircrafts spacecraft ships navigation reading weather formations and terrain mapping. The essential feature in adaptive vehicle activated sign systems is the accurate measurement of a vehicles velocity. The velocities of the vehicles are acquired from a continuous wave Doppler radar. A very low amount of power is consumed in this system and only batteries can use to operate. The system works on the principle of Doppler Effect by detecting the Doppler shift in microwaves reflected from a moving object. Since the output of the sensor is sinusoidal wave with very small amplitude and needs to be amplified with the help of the amplifier before further processing. The purpose to calculate and display the speed on LCD is performed by the microcontroller.

  9. Non-Invasive Detection of Respiration and Heart Rate with a Vehicle Seat Sensor.

    Science.gov (United States)

    Wusk, Grace; Gabler, Hampton

    2018-05-08

    This study demonstrates the feasibility of using a seat sensor designed for occupant classification from a production passenger vehicle to measure an occupant’s respiration rate (RR) and heart rate (HR) in a laboratory setting. Relaying occupant vital signs after a crash could improve emergency response by adding a direct measure of the occupant state to an Advanced Automatic Collision Notification (AACN) system. Data was collected from eleven participants with body weights ranging from 42 to 91 kg using a Ford Mustang passenger seat and seat sensor. Using a ballistocardiography (BCG) approach, the data was processed by time domain filtering and frequency domain analysis using the fast Fourier transform to yield RR and HR in a 1-min sliding window. Resting rates over the 30-min data collection and continuous RR and HR signals were compared to laboratory physiological instruments using the Bland-Altman approach. Differences between the seat sensor and reference sensor were within 5 breaths per minute for resting RR and within 15 beats per minute for resting HR. The time series comparisons for RR and HR were promising with the frequency analysis technique outperforming the peak detection technique. However, future work is necessary for more accurate and reliable real-time monitoring of RR and HR outside the laboratory setting.

  10. Increasing accuracy of vehicle detection from conventional vehicle detectors - counts, speeds, classification, and travel time.

    Science.gov (United States)

    2014-09-01

    Vehicle classification is an important traffic parameter for transportation planning and infrastructure : management. Length-based vehicle classification from dual loop detectors is among the lowest cost : technologies commonly used for collecting th...

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

    Science.gov (United States)

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

    2017-12-04

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

  12. 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.

  13. Detection of vehicle parts based on Faster R-CNN and relative position information

    Science.gov (United States)

    Zhang, Mingwen; Sang, Nong; Chen, Youbin; Gao, Changxin; Wang, Yongzhong

    2018-03-01

    Detection and recognition of vehicles are two essential tasks in intelligent transportation system (ITS). Currently, a prevalent method is to detect vehicle body, logo or license plate at first, and then recognize them. So the detection task is the most basic, but also the most important work. Besides the logo and license plate, some other parts, such as vehicle face, lamp, windshield and rearview mirror, are also key parts which can reflect the characteristics of vehicle and be used to improve the accuracy of recognition task. In this paper, the detection of vehicle parts is studied, and the work is novel. We choose Faster R-CNN as the basic algorithm, and take the local area of an image where vehicle body locates as input, then can get multiple bounding boxes with their own scores. If the box with maximum score is chosen as final result directly, it is often not the best one, especially for small objects. This paper presents a method which corrects original score with relative position information between two parts. Then we choose the box with maximum comprehensive score as the final result. Compared with original output strategy, the proposed method performs better.

  14. 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.

  15. 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.

  16. Chemometric strategy for automatic chromatographic peak detection and background drift correction in chromatographic data.

    Science.gov (United States)

    Yu, Yong-Jie; Xia, Qiao-Ling; Wang, Sheng; Wang, Bing; Xie, Fu-Wei; Zhang, Xiao-Bing; Ma, Yun-Ming; Wu, Hai-Long

    2014-09-12

    Peak detection and background drift correction (BDC) are the key stages in using chemometric methods to analyze chromatographic fingerprints of complex samples. This study developed a novel chemometric strategy for simultaneous automatic chromatographic peak detection and BDC. A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data. A local curve-fitting strategy was then employed for BDC. Simulated and real liquid chromatographic data were designed with various kinds of background drift and degree of overlapped chromatographic peaks to verify the performance of the proposed strategy. The underlying chromatographic peaks can be automatically detected and reasonably integrated by this strategy. Meanwhile, chromatograms with BDC can be precisely obtained. The proposed method was used to analyze a complex gas chromatography dataset that monitored quality changes in plant extracts during storage procedure. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. The new generation of detection and identification equipment; Nouvelle generation de materiel de detection et d' identification

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, F.; Guerin, M.; Fort, Ph. [Mirion technologies, division HPH, BPI - 13113 Lamanon (France)

    2009-07-01

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

  18. 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.

  19. Automatic detection and classification of breast tumors in ultrasonic images using texture and morphological features.

    Science.gov (United States)

    Su, Yanni; Wang, Yuanyuan; Jiao, Jing; Guo, Yi

    2011-01-01

    Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of interest (ROI), segmentation and classification of breast tumor is proposed without any manual intervention. By incorporating local features of texture and position, a ROI is firstly detected using a self-organizing map neural network. Then a modified Normalized Cut approach considering the weighted neighborhood gray values is proposed to partition the ROI into clusters and get the initial boundary. In addition, a regional-fitting active contour model is used to adjust the few inaccurate initial boundaries for the final segmentation. Finally, three textures and five morphologic features are extracted from each breast tumor; whereby a highly efficient Affinity Propagation clustering is used to fulfill the malignancy and benign classification for an existing database without any training process. The proposed system is validated by 132 cases (67 benignancies and 65 malignancies) with its performance compared to traditional methods such as level set segmentation, artificial neural network classifiers, and so forth. Experiment results show that the proposed system, which needs no training procedure or manual interference, performs best in detection and classification of ultrasonic breast tumors, while having the lowest computation complexity.

  20. 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 ...

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

    Directory of Open Access Journals (Sweden)

    N. Zarrinpanjeh

    2017-09-01

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

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

    Science.gov (United States)

    Zarrinpanjeh, N.; Dadrassjavan, F.

    2017-09-01

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

  3. 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.

  4. Systems and methods for vehicle speed management

    Science.gov (United States)

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

    2016-03-01

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

  5. Exploiting ensemble learning for automatic cataract detection and grading.

    Science.gov (United States)

    Yang, Ji-Jiang; Li, Jianqiang; Shen, Ruifang; Zeng, Yang; He, Jian; Bi, Jing; Li, Yong; Zhang, Qinyan; Peng, Lihui; Wang, Qing

    2016-02-01

    Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs. To date, studies reported in the literature utilize a single learning model for retinal image classification in grading cataract severity. We present an ensemble learning based approach as a means to improving diagnostic accuracy. Three independent feature sets, i.e., wavelet-, sketch-, and texture-based features, are extracted from each fundus image. For each feature set, two base learning models, i.e., Support Vector Machine and Back Propagation Neural Network, are built. Then, the ensemble methods, majority voting and stacking, are investigated to combine the multiple base learning models for final fundus image classification. Empirical experiments are conducted for cataract detection (two-class task, i.e., cataract or non-cataractous) and cataract grading (four-class task, i.e., non-cataractous, mild, moderate or severe) tasks. The best performance of the ensemble classifier is 93.2% and 84.5% in terms of the correct classification rates for cataract detection and grading tasks, respectively. The results demonstrate that the ensemble classifier outperforms the single learning model significantly, which also illustrates the effectiveness of the proposed approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  6. Automatic Detection of Terminology Evolution

    Science.gov (United States)

    Tahmasebi, Nina

    As archives contain documents that span over a long period of time, the language used to create these documents and the language used for querying the archive can differ. This difference is due to evolution in both terminology and semantics and will cause a significant number of relevant documents being omitted. A static solution is to use query expansion based on explicit knowledge banks such as thesauri or ontologies. However as we are able to archive resources with more varied terminology, it will be infeasible to use only explicit knowledge for this purpose. There exist only few or no thesauri covering very domain specific terminologies or slang as used in blogs etc. In this Ph.D. thesis we focus on automatically detecting terminology evolution in a completely unsupervised manner as described in this technical paper.

  7. 46 CFR 112.01-10 - Automatic emergency lighting and power system.

    Science.gov (United States)

    2010-10-01

    ... 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 in... 46 Shipping 4 2010-10-01 2010-10-01 false Automatic emergency lighting and power system. 112.01-10...

  8. 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.

  9. Usefulness of Cone-Beam Computed Tomography and Automatic Vessel Detection Software in Emergency Transarterial Embolization

    Energy Technology Data Exchange (ETDEWEB)

    Carrafiello, Gianpaolo, E-mail: gcarraf@gmail.com; Ierardi, Anna Maria, E-mail: amierardi@yahoo.it; Duka, Ejona, E-mail: ejonaduka@hotmail.com [Insubria University, Department of Radiology, Interventional Radiology (Italy); Radaelli, Alessandro, E-mail: alessandro.radaelli@philips.com [Philips Healthcare (Netherlands); Floridi, Chiara, E-mail: chiara.floridi@gmail.com [Insubria University, Department of Radiology, Interventional Radiology (Italy); Bacuzzi, Alessandro, E-mail: alessandro.bacuzzi@ospedale.varese.it [University of Insubria, Anaesthesia and Palliative Care (Italy); Bucourt, Maximilian de, E-mail: maximilian.de-bucourt@charite.de [Charité - University Medicine Berlin, Department of Radiology (Germany); Marchi, Giuseppe De, E-mail: giuseppedemarchi@email.it [Insubria University, Department of Radiology, Interventional Radiology (Italy)

    2016-04-15

    BackgroundThis study was designed to evaluate the utility of dual phase cone beam computed tomography (DP-CBCT) and automatic vessel detection (AVD) software to guide transarterial embolization (TAE) of angiographically challenging arterial bleedings in emergency settings.MethodsTwenty patients with an arterial bleeding at computed tomography angiography and an inconclusive identification of the bleeding vessel at the initial 2D angiographic series were included. Accuracy of DP-CBCT and AVD software were defined as the ability to detect the bleeding site and the culprit arterial bleeder, respectively. Technical success was defined as the correct positioning of the microcatheter using AVD software. Clinical success was defined as the successful embolization. Total volume of iodinated contrast medium and overall procedure time were registered.ResultsThe bleeding site was not detected by initial angiogram in 20 % of cases, while impossibility to identify the bleeding vessel was the reason for inclusion in the remaining cases. The bleeding site was detected by DP-CBCT in 19 of 20 (95 %) patients; in one case CBCT-CT fusion was required. AVD software identified the culprit arterial branch in 18 of 20 (90 %) cases. In two cases, vessel tracking required manual marking of the candidate arterial bleeder. Technical success was 95 %. Successful embolization was achieved in all patients. Mean contrast volume injected for each patient was 77.5 ml, and mean overall procedural time was 50 min.ConclusionsC-arm CBCT and AVD software during TAE of angiographically challenging arterial bleedings is feasible and may facilitate successful embolization. Staff training in CBCT imaging and software manipulation is necessary.

  10. 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.

  11. The Commercial Vehicle Information Systems and Network program, 2012.

    Science.gov (United States)

    2014-03-01

    The Commercial Vehicle Information Systems and : Networks (CVISN) program supports that safety : mission by providing grant funds to States for: : Improving safety and productivity of motor : carriers, commercial motor vehicles : (CMVs), and thei...

  12. Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

    Directory of Open Access Journals (Sweden)

    Maíla de Lima Claro

    2016-08-01

    Full Text Available The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classiffication of images in glaucomatous or not. We obtained results of 93% accuracy.

  13. 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.

  14. [Detection of Brucella with an automatic hemoculture system: Bact/Alert].

    Science.gov (United States)

    Casas, J; Partal, Y; Llosá, J; Leiva, J; Navarro, J M; de la Rosa, M

    1994-12-01

    The ability of in vitro and in vivo detection of Brucella spp. with the Bact/Alert system was studied. Three strains of Brucella melitensis and two of Brucella abortus were used. Different dilutions of the five strains were performed in trypticase soy broth (TSB), achieving concentrations of 1 cfu/ml, 5 cfu/ml, 10 cfu/ml and 100 cfu/ml. Ten ml of each dilution and strain were inoculated into 5 aerobic bottles Bact/Alert and 5 biphasic Hemóline bottles. Furthermore, over a 9 month period, 8,216 bottles of Bact/Alert bottles from hospitalized patients and from the emergency department were processed in the authors' laboratory. The mean detection time for Brucella growth was from 2 to 3 days with the Bact/Alert system, and 14 days in the biphasic bottles. Former bottles processed in the authors' laboratory, 11 aerobic bottles belonged to 5 patients in whom brucelosis was confirmed by bloodculture. The Bact/Alert system detected Brucella melitensis in only on bottle at 2.9 days of incubation. In 7 bottles Bact/Alert detected B. melitensis by a blind pass of these bottles at 10 to 20 days of incubation. These results suggest that the Bact/Alert system does not totally solve the diagnosis of brucellosis. Blind passes of the bloodcultures are required.

  15. 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.

  16. Ground Vehicle System Integration (GVSI) and Design Optimization Model

    National Research Council Canada - National Science Library

    Horton, William

    1996-01-01

    This report documents the Ground Vehicle System Integration (GVSI) and Design Optimization Model GVSI is a top-level analysis tool designed to support engineering tradeoff studies and vehicle design optimization efforts...

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

    International Nuclear Information System (INIS)

    Dupeyrat, Benoit

    1981-01-01

    This report deals with the acoustical-phonetic step of the automatic recognition of the speech. The parameters used are the extrema of the acoustical signal (coded in amplitude and duration). This coding method, the properties of which are described, is simple and well adapted to a digital processing. The quality and the intelligibility of the coded signal after reconstruction are particularly satisfactory. An experiment for the automatic recognition of isolated words has been carried using this coding system. We have designed a filtering algorithm operating on the parameters of the coding. Thus the characteristics of the formants can be derived under certain conditions which are discussed. Using these characteristics the identification of a large part of the phonemes for a given speaker was achieved. Carrying on the studies has required the development of a particular methodology of real time processing which allowed immediate evaluation of the improvement of the programs. Such processing on temporal coding of the acoustical signal is extremely powerful and could represent, used in connection with other methods an efficient tool for the automatic processing of the speech.(author) [fr

  18. 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.

  19. 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.

  20. 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.

  1. Automatic identification of temporal sequences in chewing sounds

    NARCIS (Netherlands)

    Amft, O.D.; Kusserow, M.; Tröster, G.

    2007-01-01

    Chewing is an essential part of food intake. The analysis and detection of food patterns is an important component of an automatic dietary monitoring system. However chewing is a time-variable process depending on food properties. We present an automated methodology to extract sub-sequences of

  2. Automatic Payroll Deposit System.

    Science.gov (United States)

    Davidson, D. B.

    1979-01-01

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

  3. Automatic continuous monitoring system for dangerous sites and cargoes

    International Nuclear Information System (INIS)

    Smirnov, S.N.

    2009-01-01

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

  4. 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.

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

    International Nuclear Information System (INIS)

    Lu Wei; Nystrom, Michelle M.; Parikh, Parag J.; Fooshee, David R.; Hubenschmidt, James P.; Bradley, Jeffrey D.; Low, Daniel A.

    2006-01-01

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

  6. Generic detection and identification of pospiviroids.

    Science.gov (United States)

    Olivier, Thibaut; Demonty, Elisabeth; Fauche, Frédéric; Steyer, Stéphan

    2014-08-01

    A multiplex one-step RT-PCR aiming at detecting all pospiviroids known to be harmful to cultivated plants has been developed. Specificity, sensitivity, selectivity, repeatability and reproducibility of this test have been assessed in order to fulfill the recommendations of the EPPO standard PM7/98 and provide routine detection laboratories with a cost-effective, easy-to-use and robust pospiviroid detection test. To further understand the epidemiology and ease the management of pospiviroid outbreaks, this RT-PCR diagnostic test can be followed by direct sequencing of the amplicons to identify and characterize the detected pospiviroid isolates.

  7. Automatic centroid detection and surface measurement with a digital Shack–Hartmann wavefront sensor

    International Nuclear Information System (INIS)

    Yin, Xiaoming; Zhao, Liping; Li, Xiang; Fang, Zhongping

    2010-01-01

    With the breakthrough of manufacturing technologies, the measurement of surface profiles is becoming a big issue. A Shack–Hartmann wavefront sensor (SHWS) provides a promising technology for non-contact surface measurement with a number of advantages over interferometry. The SHWS splits the incident wavefront into many subsections and transfers the distorted wavefront detection into the centroid measurement. So the accuracy of the centroid measurement determines the accuracy of the SHWS. In this paper, we have presented a new centroid measurement algorithm based on an adaptive thresholding and dynamic windowing method by utilizing image-processing techniques. Based on this centroid detection method, we have developed a digital SHWS system which can automatically detect centroids of focal spots, reconstruct the wavefront and measure the 3D profile of the surface. The system has been tested with various simulated and real surfaces such as flat surfaces, spherical and aspherical surfaces as well as deformable surfaces. The experimental results demonstrate that the system has good accuracy, repeatability and immunity to optical misalignment. The system is also suitable for on-line applications of surface measurement

  8. Automatic Sensor-Fault Detection System for Comprehensive Structural Health Monitoring System

    National Research Council Canada - National Science Library

    Chan, Hian-Leng; Zhang, Chang; Qing, Peter X; Ooi, Teng K; Marotta, Steve A

    2005-01-01

    Structural health monitoring systems are viewed as viable means to reduce life-cycle costs, increase structural reliability, and extend the operational hours for a wide variety of composite structures...

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

    International Nuclear Information System (INIS)

    German, U.; Levinson, S.; Pelled, O.; Shemesh, Y.; Assido, H.

    1997-01-01

    An alpha and beta counting system - FAG*, for planchette samples is operated at the Health Physics department's laboratory of the NRCN. The original operation mode of the system was based on manual tasks handled by the FHT1 100 electronics. An option for a basic computer keyboard operation was available too. A computer with an appropriate I/O card was connected to the system and a new operating program was developed which enables full automatic control of the various components. The program includes activity calculations and statistical checks as well as data management. A bar-code laser system for sample number reading was integrated into the Alpha-Beta automatic counting system. The sample identification by means of an attached bar-code label enables unmistakable and reliable attribution of results to the counted sample. authors)

  10. 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.

  11. 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.

  12. Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

    Science.gov (United States)

    Giménez, Estela; Gay, Marina; Vilaseca, Marta

    2017-01-30

    Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. 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.

  14. Usage of aids monitoring in automatic braking systems of modern cars

    OpenAIRE

    Dembitskyi V.; Mazylyuk P.; Sitovskyi O.

    2016-01-01

    Increased safety can be carried out at the expense the installation on vehicles of automatic braking systems, that monitor the traffic situation and the actions of the driver. In this paper considered the advantages and disadvantages of automatic braking systems, were analyzed modern tracking tools that are used in automatic braking systems. Based on the statistical data on accidents, are set the main dangers, that the automatic braking system will be reduced. In order to ensure the acc...

  15. Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Min-Yin Liu

    2017-05-01

    Full Text Available Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz measured by electroencephalography (EEG mostly during non-rapid eye movement (NREM stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1 the lack of common benchmark databases, and (2 the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA, the Strength Pareto Evolutionary Algorithm (SPEA2, to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT, and two Hilbert-Huang transform (HHT based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726–0.737.

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

    International Nuclear Information System (INIS)

    Wormanns, Dag; Fiebich, Martin; Saidi, Mustafa; Diederich, Stefan; Heindel, Walter

    2002-01-01

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

  17. [Development of a Computer-aided Diagnosis System to Distinguish between Benign and Malignant Mammary Tumors in Dynamic Magnetic Resonance Images: Automatic Detection of the Position with the Strongest Washout Effect in the Tumor].

    Science.gov (United States)

    Miyazaki, Yoshiaki; Tabata, Nobuyuki; Taroura, Tomomi; Shinozaki, Kenji; Kubo, Yuichiro; Tokunaga, Eriko; Taguchi, Kenichi

    We propose a computer-aided diagnostic (CAD) system that uses time-intensity curves to distinguish between benign and malignant mammary tumors. Many malignant tumors show a washout pattern in time-intensity curves. Therefore, we designed a program that automatically detects the position with the strongest washout effect using the technique, such as the subtraction technique, which extracts only the washout area in the tumor, and by scanning data in 2×2 pixel region of interest (ROI). Operation of this independently developed program was verified using a phantom system that simulated tumors. In three cases of malignant tumors, the washout pattern detection rate in images with manually set ROI was ≤6%, whereas the detection rate with our novel method was 100%. In one case of a benign tumor, when the same method was used, we checked that there was no washout effect and detected the persistent pattern. Thus, the distinction between benign and malignant tumors using our method was completely consistent with the pathological diagnoses made. Our novel method is therefore effective for differentiating between benign and malignant mammary tumors in dynamic magnetic resonance images.

  18. Detection and 3d Modelling of Vehicles from Terrestrial Stereo Image Pairs

    Science.gov (United States)

    Coenen, M.; Rottensteiner, F.; Heipke, C.

    2017-05-01

    The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, obtained from a moving vehicle. Processing every stereo pair individually, our approach is divided into two subsequent steps: the vehicle detection and the modelling step. For the detection, we make use of the 3D stereo information and incorporate geometric assumptions on vehicle inherent properties in a firstly applied generic 3D object detection. By combining our generic detection approach with a state of the art vehicle detector, we are able to achieve satisfying detection results with values for completeness and correctness up to more than 86%. By fitting an object specific vehicle model into the vehicle detections, we are able to reconstruct the vehicles in 3D and to derive pose estimations as well as shape parameters for each vehicle. To deal with the intra-class variability of vehicles, we make use of a deformable 3D active shape model learned from 3D CAD vehicle data in our model fitting approach. While we achieve encouraging values up to 67.2% for correct position estimations, we are facing larger problems concerning the orientation estimation. The evaluation is done by using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012).

  19. Design and Implementation of an Emergency Vehicle Signal Preemption System Based on Cooperative Vehicle-Infrastructure Technology

    OpenAIRE

    Yinsong Wang; Zhizhou Wu; Xiaoguang Yang; Luoyi Huang

    2013-01-01

    Emergency vehicle is an important part of traffic flow. The efficiency, reliability, and safety of emergency vehicle operations dropped due to increasing traffic congestion. With the advancement of the wireless communication technologies and the development of the vehicle-to-vehicle (v2v) and vehicle-to-infrastructure (v2i) systems, called Cooperative Vehicle-Infrastructure System (CVIS), there is an opportunity to provide appropriate traffic signal preemption for emergency vehicle based on r...

  20. Exporting automatic vehicle SNM monitoring technology

    International Nuclear Information System (INIS)

    York, R.L.; Fehlau, P.E.; Close, D.A.

    1995-01-01

    Controlling the transportation of nuclear materials is still one of the most effective nuclear proliferation barriers. The recent increase of global nuclear material proliferation has expanded the application of vehicle monitor technology to prevent the diversion of special nuclear material across international borders. To satisfy this new application, a high-sensitivity vehicle monitor, which is easy to install and capable of operating in high-traffic areas, is required. A study of a new detector configuration for a drive-through vehicle monitor is discussed in this paper

  1. Improving the safety and protective automatic actions of the CMS electromagnetic calorimeter detector control system

    CERN Document Server

    Jimenez Estupinan, Raul; Cirkovic, Predrag; Di Calafiori, Diogo Raphael; Dissertori, Guenther; Djambazov, Lubomir; Jovanovic, Dragoslav; Lustermann, Werner; Milenovic, Predrag; Zelepoukine, Serguei

    2017-01-01

    The CMS ECAL Detector Control System (DCS) features several monitoring mechanisms able to react and perform automatic actions based on pre-defined action matrices. The DCS is capable of early detection of anomalies inside the ECAL and on its off-detector support systems, triggering automatic actions to mitigate the impact of these events and preventing them from escalating to the safety system. The treatment of such events by the DCS allows for a faster recovery process, better understanding of the development of issues, and in most cases, actions with higher granularity than the safety system. This paper presents the details of the DCS automatic action mechanisms, as well as their evolution based on several years of CMS ECAL operations.

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

    Directory of Open Access Journals (Sweden)

    Seung-Ki Ryu

    2015-01-01

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

  3. 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.

  4. 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.

  5. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    International Nuclear Information System (INIS)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing

    2016-01-01

    Purpose: Radiation treatment planning involves a complex workflow that has multiple potential points of vulnerability. This study utilizes an incident reporting system to identify the origination and detection points of near-miss errors, in order to guide their departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or applied a near-miss risk index (NMRI) to gauge severity. Methods: From 3/2012 to 3/2014, 1897 incidents were analyzed from a departmental incident learning system. All incidents were prospectively reviewed weekly by a multidisciplinary team and assigned a NMRI score ranging from 0 to 4 reflecting potential harm to the patient (no potential harm to potential critical harm). Incidents were classified by point of incident origination and detection based on a 103-step workflow. The individual steps were divided among nine broad workflow categories (patient assessment, imaging for radiation therapy (RT) planning, treatment planning, pretreatment plan review, treatment delivery, on-treatment quality management, post-treatment completion, equipment/software quality management, and other). The average NMRI scores of incidents originating or detected within each broad workflow area were calculated. Additionally, out of 103 individual process steps, 35 were classified as safety barriers, the process steps whose primary function is to catch errors. The safety barriers which most frequently detected incidents were identified and analyzed. Finally, the distance between event origination and detection was explored by grouping events by the number of broad workflow area events passed through before detection, and average NMRI scores were compared. Results: Near-miss incidents most commonly originated within treatment planning (33%). However, the incidents with the highest average NMRI scores originated during imaging for RT planning (NMRI = 2.0, average NMRI of all events = 1.5), specifically

  6. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    Energy Technology Data Exchange (ETDEWEB)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing, E-mail: jzeng13@uw.edu [Department of Radiation Oncology, University of Washington Medical Center, 1959 NE Pacific Street, Campus Box 356043, Seattle, Washington 98195 (United States)

    2016-05-15

    Purpose: Radiation treatment planning involves a complex workflow that has multiple potential points of vulnerability. This study utilizes an incident reporting system to identify the origination and detection points of near-miss errors, in order to guide their departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or applied a near-miss risk index (NMRI) to gauge severity. Methods: From 3/2012 to 3/2014, 1897 incidents were analyzed from a departmental incident learning system. All incidents were prospectively reviewed weekly by a multidisciplinary team and assigned a NMRI score ranging from 0 to 4 reflecting potential harm to the patient (no potential harm to potential critical harm). Incidents were classified by point of incident origination and detection based on a 103-step workflow. The individual steps were divided among nine broad workflow categories (patient assessment, imaging for radiation therapy (RT) planning, treatment planning, pretreatment plan review, treatment delivery, on-treatment quality management, post-treatment completion, equipment/software quality management, and other). The average NMRI scores of incidents originating or detected within each broad workflow area were calculated. Additionally, out of 103 individual process steps, 35 were classified as safety barriers, the process steps whose primary function is to catch errors. The safety barriers which most frequently detected incidents were identified and analyzed. Finally, the distance between event origination and detection was explored by grouping events by the number of broad workflow area events passed through before detection, and average NMRI scores were compared. Results: Near-miss incidents most commonly originated within treatment planning (33%). However, the incidents with the highest average NMRI scores originated during imaging for RT planning (NMRI = 2.0, average NMRI of all events = 1.5), specifically

  7. Automatic contact in DYNA3D for vehicle crashworthiness

    International Nuclear Information System (INIS)

    Whirley, R.G.; Engelmann, B.E.

    1994-01-01

    This paper presents a new formulation for the automatic definition and treatment of mechanical contact in explicit, nonlinear, finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. The authors have used a new four-step automatic contact algorithm. Key aspects of the proposed method include (1) automatic identification of adjacent and opposite surfaces in the global search phase, and (2) the use of a smoothly varying surface normal that allows a consistent treatment of shell intersection and corner contact conditions without ad hoc rules. Three examples are given to illustrate the performance of the newly proposed algorithm in the public DYNA3D code

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

    International Nuclear Information System (INIS)

    Brunnett, C.J.; Ioannou, B.N.

    1976-01-01

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

  9. Performance evaluation of three automated identification systems in detecting carbapenem-resistant Enterobacteriaceae.

    Science.gov (United States)

    He, Qingwen; Chen, Weiyuan; Huang, Liya; Lin, Qili; Zhang, Jingling; Liu, Rui; Li, Bin

    2016-06-21

    Carbapenem-resistant Enterobacteriaceae (CRE) is prevalent around the world. Rapid and accurate detection of CRE is urgently needed to provide effective treatment. Automated identification systems have been widely used in clinical microbiology laboratories for rapid and high-efficient identification of pathogenic bacteria. However, critical evaluation and comparison are needed to determine the specificity and accuracy of different systems. The aim of this study was to evaluate the performance of three commonly used automated identification systems on the detection of CRE. A total of 81 non-repetitive clinical CRE isolates were collected from August 2011 to August 2012 in a Chinese university hospital, and all the isolates were confirmed to be resistant to carbapenems by the agar dilution method. The potential presence of carbapenemase genotypes of the 81 isolates was detected by PCR and sequencing. Using 81 clinical CRE isolates, we evaluated and compared the performance of three automated identification systems, MicroScan WalkAway 96 Plus, Phoenix 100, and Vitek 2 Compact, which are commonly used in China. To identify CRE, the comparator methodology was agar dilution method, while the PCR and sequencing was the comparator one to identify CPE. PCR and sequencing analysis showed that 48 of the 81 CRE isolates carried carbapenemase genes, including 23 (28.4 %) IMP-4, 14 (17.3 %) IMP-8, 5 (6.2 %) NDM-1, and 8 (9.9 %) KPC-2. Notably, one Klebsiella pneumoniae isolate produced both IMP-4 and NDM-1. One Klebsiella oxytoca isolate produced both KPC-2 and IMP-8. Of the 81 clinical CRE isolates, 56 (69.1 %), 33 (40.7 %) and 77 (95.1 %) were identified as CRE by MicroScan WalkAway 96 Plus, Phoenix 100, and Vitek 2 Compact, respectively. The sensitivities/specificities of MicroScan WalkAway, Phoenix 100 and Vitek 2 were 93.8/42.4 %, 54.2/66.7 %, and 75.0/36.4 %, respectively. The MicroScan WalkAway and Viteck2 systems are more reliable in clinical identification of

  10. Microarrays for Universal Detection and Identification of Phytoplasmas

    DEFF Research Database (Denmark)

    Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

    2013-01-01

    Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...... and differentiate all types of phytoplasmas in one assay. The present protocol describes a microarray-based method for identification of phytoplasmas to 16Sr group level....

  11. Structural Acoustic UXO Detection and Identification in Marine Environments

    Science.gov (United States)

    2016-05-01

    a thick steel wall, is cylindrical, and has an aspect ratio of about 5:1. Further, the interior water can support acoustic waves as does the epoxy...FINAL REPORT Structural Acoustic UXO Detection and Identification in Marine Environments SERDP Project MR-2103 MAY 2016 B. H...NUMBER Structural Acoustic UXO Detection and Identification in Marine Environments- Final report for Follow-on Work- MR-2103 Sb. GRANT NUMBER Sc

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

    Directory of Open Access Journals (Sweden)

    Jianjun Hu

    2016-08-01

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

  13. 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.

  14. Electronic Toll And Traffic Management Systems, National Cooperative Highway Research Program Synthesis

    Science.gov (United States)

    1993-01-01

    ELECTRONIC TOLL COLLECTION OR ETC AND TRAFFIC MANAGEMENT OR ETTM, AUTOMATIC VEHICLE IDENTIFICATION OR AVI : ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT (ETTM) SYSTEMS ARE NOT A FUTURISTIC DREAM, THEY ARE OPERATING OR ARE BEING TESTED TODAY I...

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

    International Nuclear Information System (INIS)

    Qian Defeng; Guo Pingwen; Jiang Shan; Zhang Lei; Yang Lijun; Xiong Chuansheng; Liu Deheng; Chen Weijie; He Biao; Wang Wei

    1999-01-01

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

  16. 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.

  17. Performance evaluation and design of flight vehicle control systems

    CERN Document Server

    Falangas, Eric T

    2015-01-01

    This book will help students, control engineers and flight dynamics analysts to model and conduct sophisticated and systemic analyses of early flight vehicle designs controlled with multiple types of effectors and to design and evaluate new vehicle concepts in terms of satisfying mission and performance goals. Performance Evaluation and Design of Flight Vehicle Control Systems begins by creating a dynamic model of a generic flight vehicle that includes a range of elements from airplanes and launch vehicles to re-entry vehicles and spacecraft. The models may include dynamic effects dealing with structural flexibility, as well as dynamic coupling between structures and actuators, propellant sloshing, and aeroelasticity, and they are typically used for control analysis and design. The book shows how to efficiently combine different types of effectors together, such as aero-surfaces, TVC, throttling engines and RCS, to operate as a system by developing a mixing logic atrix. Methods of trimming a vehicle controll...

  18. A SIMULATION ENVIRONMENT FOR AUTOMATIC NIGHT DRIVING AND VISUAL CONTROL

    OpenAIRE

    Arroyo Rubio, Fernando

    2012-01-01

    This project consists on developing an automatic night driving system in a simulation environment. The simulator I have used is TORCS. TORCS is an Open Source car racing simulator written in C++. It is used as an ordinary car racing game, as a IA racing game and as a research platform. The goal of this thesis is to implement an automatic driving system to control the car under night conditions using computer vision. A camera is implemented inside the vehicle and it will detect the reflective ...

  19. 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 (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.

  20. Development of a system for automatic detection of pellet failures; Desarrollo de un sistema para deteccion automatica de fallas en pastillas

    Energy Technology Data Exchange (ETDEWEB)

    Lavagnino, C E [Comision Nacional de Energia Atomica, San Martin (Argentina). Unidad de Actividad Combustibles Nucleares

    1997-12-31

    Nowadays, the failure controls in UO{sub 2} pellets for Atucha and Embalse reactors are performed visually. In this work it is presented the first stage of the development of a system that allows an automatic approach to the task. For this purpose, the problem has been subdivided in three jobs: choosing the illumination environment, finding the algorithm that detects failures with user-defined tolerance and engineering the mechanic system that supports the desired manipulations of the pellets. In this paper, the former two are developed. a) Finding the illumination conditions that allow subtracting the failure from the normal element surface, knowing, in first place, the cylindrical characteristics of it and, as a consequence, the differences in the light reflection direction and, in second place, the texture differences in relation to the rectification type of the pellet. b) Writing a fast and simple algorithm that allows the identification of the failure following the production specifications. Examples of the developed algorithm are shown. (author). 4 refs.

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  3. Detection of clinical mastitis with sensor data from automatic milking systems is improved by using decision-tree induction.

    Science.gov (United States)

    Kamphuis, C; Mollenhorst, H; Heesterbeek, J A P; Hogeveen, H

    2010-08-01

    The objective was to develop and validate a clinical mastitis (CM) detection model by means of decision-tree induction. For farmers milking with an automatic milking system (AMS), it is desirable that the detection model has a high level of sensitivity (Se), especially for more severe cases of CM, at a very high specificity (Sp). In addition, an alert for CM should be generated preferably at the quarter milking (QM) at which the CM infection is visible for the first time. Data were collected from 9 Dutch dairy herds milking automatically during a 2.5-yr period. Data included sensor data (electrical conductivity, color, and yield) at the QM level and visual observations of quarters with CM recorded by the farmers. Visual observations of quarters with CM were combined with sensor data of the most recent automatic milking recorded for that same quarter, within a 24-h time window before the visual assessment time. Sensor data of 3.5 million QM were collected, of which 348 QM were combined with a CM observation. Data were divided into a training set, including two-thirds of all data, and a test set. Cows in the training set were not included in the test set and vice versa. A decision-tree model was trained using only clear examples of healthy (n=24,717) or diseased (n=243) QM. The model was tested on 105 QM with CM and a random sample of 50,000 QM without CM. While keeping the Se at a level comparable to that of models currently used by AMS, the decision-tree model was able to decrease the number of false-positive alerts by more than 50%. At an Sp of 99%, 40% of the CM cases were detected. Sixty-four percent of the severe CM cases were detected and only 12.5% of the CM that were scored as watery milk. The Se increased considerably from 40% to 66.7% when the time window increased from less than 24h before the CM observation, to a time window from 24h before to 24h after the CM observation. Even at very wide time windows, however, it was impossible to reach an Se of 100

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

    Science.gov (United States)

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

    2016-01-01

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

  5. 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.

  6. 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,

  7. 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

  8. Efficient and automatic image reduction framework for space debris detection based on GPU technology

    Science.gov (United States)

    Diprima, Francesco; Santoni, Fabio; Piergentili, Fabrizio; Fortunato, Vito; Abbattista, Cristoforo; Amoruso, Leonardo

    2018-04-01

    In the last years, the increasing number of space debris has triggered the need of a distributed monitoring system for the prevention of possible space collisions. Space surveillance based on ground telescope allows the monitoring of the traffic of the Resident Space Objects (RSOs) in the Earth orbit. This space debris surveillance has several applications such as orbit prediction and conjunction assessment. In this paper is proposed an optimized and performance-oriented pipeline for sources extraction intended to the automatic detection of space debris in optical data. The detection method is based on the morphological operations and Hough Transform for lines. Near real-time detection is obtained using General Purpose computing on Graphics Processing Units (GPGPU). The high degree of processing parallelism provided by GPGPU allows to split data analysis over thousands of threads in order to process big datasets with a limited computational time. The implementation has been tested on a large and heterogeneous images data set, containing both imaging satellites from different orbit ranges and multiple observation modes (i.e. sidereal and object tracking). These images were taken during an observation campaign performed from the EQUO (EQUatorial Observatory) observatory settled at the Broglio Space Center (BSC) in Kenya, which is part of the ASI-Sapienza Agreement.

  9. 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

  10. Studies and Proposals for an Automatic Crystal Control System

    CERN Document Server

    Drobychev, Gleb; Khruschinsky, A A; Korzhik, Mikhail; Missevitch, Oleg; Oriboni, André; Peigneux, Jean-Pierre; Schneegans, Marc

    1997-01-01

    This document presents the status of the studies for an Automatic Crystal Control System ( ACCOS) performed since autumn 1995 for the CMS collaboration. Evaluation of a startstop method for light yield, light uniformity and decay time measurements of PbWO4 crystals is presented, as well as the first results obtained with a compact double-beam spectrophotometer for transverse transmission. Various overall schemes are proposed for an integrated set-up including crystal dimension measurement. The initial financial evaluationperformed is also given.

  11. Automatic Identification of Physical Activity Intensity and Modality from the Fusion of Accelerometry and Heart Rate Data.

    Science.gov (United States)

    García-García, Fernando; Benito, Pedro J; Hernando, María E

    2016-12-07

    Physical activity (PA) is essential to prevent and to treat a variety of chronic diseases. The automated detection and quantification of PA over time empowers lifestyle interventions, facilitating reliable exercise tracking and data-driven counseling. We propose and compare various combinations of machine learning (ML) schemes for the automatic classification of PA from multi-modal data, simultaneously captured by a biaxial accelerometer and a heart rate (HR) monitor. Intensity levels (low / moderate / vigorous) were recognized, as well as for vigorous exercise, its modality (sustained aerobic / resistance / mixed). In total, 178.63 h of data about PA intensity (65.55 % low / 18.96 % moderate / 15.49 % vigorous) and 17.00 h about modality were collected in two experiments: one in free-living conditions, another in a fitness center under controlled protocols. The structure used for automatic classification comprised: a) definition of 42 time-domain signal features, b) dimensionality reduction, c) data clustering, and d) temporal filtering to exploit time redundancy by means of a Hidden Markov Model (HMM). Four dimensionality reduction techniques and four clustering algorithms were studied. In order to cope with class imbalance in the dataset, a custom performance metric was defined to aggregate recognition accuracy, precision and recall. The best scheme, which comprised a projection through Linear Discriminant Analysis (LDA) and k-means clustering, was evaluated in leave-one-subject-out cross-validation; notably outperforming the standard industry procedures for PA intensity classification: score 84.65 %, versus up to 63.60 %. Errors tended to be brief and to appear around transients. The application of ML techniques for pattern identification and temporal filtering allowed to merge accelerometry and HR data in a solid manner, and achieved markedly better recognition performances than the standard methods for PA intensity estimation.

  12. Oocytes Polar Body Detection for Automatic Enucleation

    Directory of Open Access Journals (Sweden)

    Di Chen

    2016-02-01

    Full Text Available Enucleation is a crucial step in cloning. In order to achieve automatic blind enucleation, we should detect the polar body of the oocyte automatically. The conventional polar body detection approaches have low success rate or low efficiency. We propose a polar body detection method based on machine learning in this paper. On one hand, the improved Histogram of Oriented Gradient (HOG algorithm is employed to extract features of polar body images, which will increase success rate. On the other hand, a position prediction method is put forward to narrow the search range of polar body, which will improve efficiency. Experiment results show that the success rate is 96% for various types of polar bodies. Furthermore, the method is applied to an enucleation experiment and improves the degree of automatic enucleation.

  13. Rheticus Displacement: an Automatic Geo-Information Service Platform for Ground Instabilities Detection and Monitoring

    Science.gov (United States)

    Chiaradia, M. T.; Samarelli, S.; Agrimano, L.; Lorusso, A. P.; Nutricato, R.; Nitti, D. O.; Morea, A.; Tijani, K.

    2016-12-01

    Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and a minimum interaction with human operators. This target is achieved by means of programmable components working as different software layers in a modern enterprise system which relies on SOA (service-oriented-architecture) model. Due to its architecture, where every functionality is well defined and encapsulated in a standalone component, Rheticus is potentially highly scalable and distributable allowing different configurations depending on the user needs. Rheticus offers a portfolio of services, ranging from the detection and monitoring of geohazards and infrastructural instabilities, to marine water quality monitoring, wildfires detection or land cover monitoring. In this work, we outline the overall cloud-based platform and focus on the "Rheticus Displacement" service, aimed at providing accurate information to monitor movements occurring across landslide features or structural instabilities that could affect buildings or infrastructures. Using Sentinel-1 (S1) open data images and Multi-Temporal SAR Interferometry techniques (i.e., SPINUA), the service is complementary to traditional survey methods, providing a long-term solution to slope instability monitoring. Rheticus automatically browses and accesses (on a weekly basis) the products of the rolling archive of ESA S1 Scientific Data Hub; S1 data are then handled by a mature running processing chain, which is responsible of producing displacement maps immediately usable to measure with sub-centimetric precision movements of coherent points. Examples are provided, concerning the automatic displacement map generation process, as well as the integration of point and distributed scatterers, the integration of multi-sensors displacement maps (e.g., Sentinel-1 IW and COSMO-SkyMed HIMAGE), the combination of displacement rate maps acquired along both ascending

  14. Automatic Smoker Detection from Telephone Speech Signals

    DEFF Research Database (Denmark)

    Poorjam, Amir Hossein; Hesaraki, Soheila; Safavi, Saeid

    2017-01-01

    This paper proposes an automatic smoking habit detection from spontaneous telephone speech signals. In this method, each utterance is modeled using i-vector and non-negative factor analysis (NFA) frameworks, which yield low-dimensional representation of utterances by applying factor analysis...... method is evaluated on telephone speech signals of speakers whose smoking habits are known drawn from the National Institute of Standards and Technology (NIST) 2008 and 2010 Speaker Recognition Evaluation databases. Experimental results over 1194 utterances show the effectiveness of the proposed approach...... for the automatic smoking habit detection task....

  15. Stakeholders' opinions on a future in-vehicle alcohol detection system for prevention of drunk driving.

    Science.gov (United States)

    Anund, Anna; Antonson, Hans; Ihlström, Jonas

    2015-01-01

    There is a common understanding that driving under the influence of alcohol is associated with higher risk of being involved in crashes with injuries and possible fatalities as the outcome. Various countermeasures have therefore from time to time been taken by the authorities to prevent drunk driving. One of them has been the alcohol interlock. Up to now, interlocks have mainly been used by previously convicted drunk drivers and in the commercial road transport sector, but not in private cars. New technology has today reached a level where broader implementation might be possible. To our knowledge, however, little is known about different stakeholders' opinions of a broader implementation of such systems. In order to increase that knowledge, we conducted a focus group study to collect in-depth thoughts from different stakeholders on this topic. Eight focus groups representing a broad societal span were recruited and conducted for the purpose. The results show that most stakeholders thought that an integrated system for alcohol detection in vehicles might be beneficial in lowering the number of drunk driving crashes. They said that the system would probably mainly prevent driving by people who unintentionally and unknowingly drive under the influence of alcohol. The groups did, however, not regard the system as a final solution to the drunk driving problem, and believed that certain groups, such as criminals and alcoholics, would most likely find a way around the system. Concerns were raised about the risk of increased sleepy driving and driving just under the legal blood alcohol concentration (BAC) limit. The results also indicate that stakeholders preferred a system that provides information on the BAC up to the legal limit, but not for levels above the limit; for those, the system should simply prevent the car from starting. Acceptance of the system depended on the reliability of the system, on its ability to perform fast sampling, and on the analytical process

  16. Object-based detection of vehicles using combined optical and elevation data

    Science.gov (United States)

    Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

    2018-02-01

    The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consists of three consecutive stages: candidate identification, classification, and single vehicle extraction. Unlike in most previous approaches, fusion of both data sources is strongly pursued at all stages. While the first stage utilizes the fact that most man-made objects are rectangular in shape, the second and third stages employ machine learning techniques combined with specific features. The stages are designed to handle multiple sensor input, which results in a significant improvement. A detailed evaluation shows the benefits of our workflow, which includes hand-tailored features; even in comparison with classification approaches based on Convolutional Neural Networks, which are state of the art in computer vision, we could obtain a comparable or superior performance (F1 score of 0.96-0.94).

  17. A new rechargeable intelligent vehicle detection sensor

    International Nuclear Information System (INIS)

    Lin, L; Han, X B; Ding, R; Li, G; Lu, Steven C-Y; Hong, Q

    2005-01-01

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

  18. A new rechargeable intelligent vehicle detection sensor

    Energy Technology Data Exchange (ETDEWEB)

    Lin, L [Inspiring Technology Research Laboratory, Tianjin University, Tianjin 300072 (China); Han, X B [Inspiring Technology Research Laboratory, Tianjin University, Tianjin 300072 (China); Ding, R [Tianjin University of Technology and Education, Tianjin 300222 (China); Li, G [Inspiring Technology Research Laboratory, Tianjin University, Tianjin 300072 (China); Lu, Steven C-Y [Inspiring Technology Research Laboratory, Tianjin University, Tianjin 300072 (China); Hong, Q [Inspiring Technology Research Laboratory, Tianjin University, Tianjin 300072 (China)

    2005-01-01

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

  19. Identification of vehicle components associated with severe thoracic injury in motor vehicle crashes: a CIREN and NASS analysis.

    Science.gov (United States)

    Nirula, R; Pintar, F A

    2008-01-01

    Thoracic trauma secondary to motor vehicle crashes (MVC) continues to be a major cause of morbidity and mortality. Specific vehicle features may increase the risk of severe thoracic injury when striking the occupant. We sought to determine which vehicle contact points were associated with an increased risk of severe thoracic injury in MVC to focus subsequent design modifications necessary to reduce thoracic injury. The National Automotive Sampling System (NASS) databases from 1993 to 2001 and the Crash Injury Research and Engineering Network (CIREN) databases from 1996 to 2004 were analyzed separately using univariate and multivariate logistic regression stratified by restraint use and crash direction. The risk of driver thoracic injury, defined as an abbreviated injury scale (AIS) of score > or =3, was determined as it related to specific points of contact between the vehicle and the driver. The incidence of severe chest injury in NASS and CIREN were 5.5% and 33%, respectively. The steering wheel, door panel, armrest, and seat were identified as contact points associated with an increased risk of severe chest injury. The door panel and arm rest were consistently a frequent cause of severe injury in both the NASS and CIREN data. Several vehicle contact points, including the steering wheel, door panel, armrest and seat are associated with an increased risk of severe thoracic injury when striking the occupant. These elements need to be further investigated to determine which characteristics need to be manipulated in order to reduce thoracic trauma during a crash.

  20. An automatic system to study sperm motility and energetics.

    Science.gov (United States)

    Shi, Linda Z; Nascimento, Jaclyn M; Chandsawangbhuwana, Charlie; Botvinick, Elliot L; Berns, Michael W

    2008-08-01

    An integrated robotic laser and microscope system has been developed to automatically analyze individual sperm motility and energetics. The custom-designed optical system directs near-infrared laser light into an inverted microscope to create a single-point 3-D gradient laser trap at the focal spot of the microscope objective. A two-level computer structure is described that quantifies the sperm motility (in terms of swimming speed and swimming force) and energetics (measuring mid-piece membrane potential) using real-time tracking (done by the upper-level system) and fluorescent ratio imaging (done by the lower-level system). The communication between these two systems is achieved by a gigabit network. The custom-built image processing algorithm identifies the sperm swimming trajectory in real-time using phase contrast images, and then subsequently traps the sperm by automatically moving the microscope stage to relocate the sperm to the laser trap focal plane. Once the sperm is stably trapped (determined by the algorithm), the algorithm can also gradually reduce the laser power by rotating the polarizer in the laser path to measure the trapping power at which the sperm is capable of escaping the trap. To monitor the membrane potential of the mitochondria located in a sperm's mid-piece, the sperm is treated with a ratiometrically-encoded fluorescent probe. The proposed algorithm can relocate the sperm to the center of the ratio imaging camera and the average ratio value can be measured in real-time. The three parameters, sperm escape power, sperm swimming speed and ratio values of the mid-piece membrane potential of individual sperm can be compared with respect to time. This two-level automatic system to study individual sperm motility and energetics has not only increased experimental throughput by an order of magnitude but also has allowed us to monitor sperm energetics prior to and after exposure to the laser trap. This system should have application in both the

  1. 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

    2017-05-29

    The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight 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 Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that 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 (CO 2 ) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO 2 . In the present investigation, alcohol and CO 2 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 CO 2 and alcohol. From the statistical data, the accuracy of breath alcohol

  2. Calculation of climatic reference values and its use for automatic outlier detection in meteorological datasets

    Directory of Open Access Journals (Sweden)

    B. Téllez

    2008-04-01

    Full Text Available The climatic reference values for monthly and annual average air temperature and total precipitation in Catalonia – northeast of Spain – are calculated using a combination of statistical methods and geostatistical techniques of interpolation. In order to estimate the uncertainty of the method, the initial dataset is split into two parts that are, respectively, used for estimation and validation. The resulting maps are then used in the automatic outlier detection in meteorological datasets.

  3. Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration's Adverse Event Reporting System Narratives.

    Science.gov (United States)

    Polepalli Ramesh, Balaji; Belknap, Steven M; Li, Zuofeng; Frid, Nadya; West, Dennis P; Yu, Hong

    2014-06-27

    The Food and Drug Administration's (FDA) Adverse Event Reporting System (FAERS) is a repository of spontaneously-reported adverse drug events (ADEs) for FDA-approved prescription drugs. FAERS reports include both structured reports and unstructured narratives. The narratives often include essential information for evaluation of the severity, causality, and description of ADEs that are not present in the structured data. The timely identification of unknown toxicities of prescription drugs is an important, unsolved problem. The objective of this study was to develop an annotated corpus of FAERS narratives and biomedical named entity tagger to automatically identify ADE related information in the FAERS narratives. We developed an annotation guideline and annotate medication information and adverse event related entities on 122 FAERS narratives comprising approximately 23,000 word tokens. A named entity tagger using supervised machine learning approaches was built for detecting medication information and adverse event entities using various categories of features. The annotated corpus had an agreement of over .9 Cohen's kappa for medication and adverse event entities. The best performing tagger achieves an overall performance of 0.73 F1 score for detection of medication, adverse event and other named entities. In this study, we developed an annotated corpus of FAERS narratives and machine learning based models for automatically extracting medication and adverse event information from the FAERS narratives. Our study is an important step towards enriching the FAERS data for postmarketing pharmacovigilance.

  4. 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.

  5. Classifying Vessels Operating in the South China Sea by Origin with the Automatic Identification System

    Science.gov (United States)

    2018-03-01

    p. 5) means to track voyage and safety related information in real time. Over time, massive amounts of information related to maritime operations... safety related messages from land based stations, navigation aids, and search and rescue (SAR) crews. All AIS messages are intended to encourage open...United States is the South China Sea. Eight countries, China, Taiwan, the Philippines, Brunei, Indonesia, Malaysia , Singapore, and Vietnam

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, Susan R.

    1995-01-01

    An antiskid braking and traction control system for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes one or more sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensors and determining if regenerative antiskid braking control, requiring hydrualic braking control, or requiring traction control are required. The processor then employs a control strategy based on the determined vehicle state and provides command signals to a motor controller to control the operation of the electric traction motor and to a brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative antiskid braking control, hydraulic braking control, and traction control.

  8. Electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, S.R.

    1995-09-12

    An antiskid braking and traction control system for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes one or more sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensors and determining if regenerative antiskid braking control, requiring hydraulic braking control, or requiring traction control are required. The processor then employs a control strategy based on the determined vehicle state and provides command signals to a motor controller to control the operation of the electric traction motor and to a brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative antiskid braking control, hydraulic braking control, and traction control. 10 figs.

  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. Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

    Science.gov (United States)

    Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

    2018-05-01

    Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

  11. Vehicle usage verification system

    NARCIS (Netherlands)

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

    2012-01-01

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

  12. Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

    Science.gov (United States)

    Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

    2015-06-01

    The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

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

    Directory of Open Access Journals (Sweden)

    Hai Guo

    2015-01-01

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

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

    Science.gov (United States)

    2010-01-01

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

  15. 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.

  16. Detection of biosurfactants in Bacillus species: genes and products identification.

    Science.gov (United States)

    Płaza, G; Chojniak, J; Rudnicka, K; Paraszkiewicz, K; Bernat, P

    2015-10-01

    To screen environmental Bacillus strains for detection of genes encoding the enzymes involved in biosurfactant synthesis and to evaluate their products e.g. surfactin, iturin and fengycin. The taxonomic identification of isolated from the environment Bacillus strains was performed by Microgene ID Bacillus panel and GEN III Biolog system. The polymerase chain reaction (PCR) strategy for screening of genes in Bacillus strains was set up. Liquid chromatography-mass spectrometry (LC-MS/MS) method was used for the identification of lipopeptides (LPs). All studied strains exhibited the presence of srfAA gene and produced surfactin mostly as four homologues (C13 to C16). Moreover, in 2 strains (KP7, T'-1) simultaneous co-production of 3 biosurfactants: surfactin, iturin and fengycin was observed. Additionally, it was found out that isolate identified as Bacillus subtilis ssp. subtilis (KP7), beside LPs co-production, synthesizes surfactin with the efficiency much higher than other studied strains (40·2 mg l(-1) ) and with the yield ranging from 0·8 to 8·3 mg l(-1) . We showed that the combined methodology based on PCR and LC-MS/MS technique is an optimal tool for the detection of genes encoding enzymes involved in biosurfactant synthesis as well as their products, e.g. surfactin, iturin and fengycin. This approach improves the screening and the identification of environmental Bacillus co-producing biosurfactants-stimulating and facilitating the development of this area of science. The findings of this work will help to improve screening of biosurfactant producers. Discovery of novel biosurfactants and biosurfactants co-production ability has shed light on their new application fields and for the understanding of their interactions and properties. © 2015 The Society for Applied Microbiology.

  17. CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal-neutron-activated samples

    International Nuclear Information System (INIS)

    Giannini, M.; Oliva, P.R.; Ramorino, M.C.

    1979-01-01

    A computer code that automatically analyzes gamma-ray spectra obtained with Ge(Li) detectors is described. The program contains such features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification, and calculation of masses and errors. Finally, the results obtained with this computer code for a lunar sample are reported and briefly discussed

  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. Vehicle Parameter Identification and its Use in Control for Safe Path Following