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detection system</title> <meta name="description" content="Search results for: obstacle detection system"> <meta name="keywords" content="obstacle detection system"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="obstacle detection system"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 20175</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: obstacle detection system</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20175</span> Study and Construction on Signalling System during Reverse Motion Due to Obstacle</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20M.%20Yasir%20Arafat">S. M. Yasir Arafat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Driving models are needed by many researchers to improve traffic safety and to advance autonomous vehicle design. To be most useful, a driving model must state specifically what information is needed and how it is processed. So we developed an “Obstacle Avoidance and Detection Autonomous Car” based on sensor application. The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. Based on a developed model of brakes operation, the controller of braking system operation has been designed. It has a task to enable solution to the problem of the better controlling of braking system operation in a more accurate way then it was the case now a day. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automobile" title="automobile">automobile</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle" title=" obstacle"> obstacle</a>, <a href="https://publications.waset.org/abstracts/search?q=safety" title=" safety"> safety</a>, <a href="https://publications.waset.org/abstracts/search?q=sensing" title=" sensing"> sensing</a> </p> <a href="https://publications.waset.org/abstracts/32977/study-and-construction-on-signalling-system-during-reverse-motion-due-to-obstacle" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32977.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">364</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20174</span> Alternative Approach to the Machine Vision System Operating for Solving Industrial Control Issue</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Nikitenko">M. S. Nikitenko</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20A.%20Kizilov"> S. A. Kizilov</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Y.%20Khudonogov"> D. Y. Khudonogov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20vision" title="machine vision">machine vision</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20vision%20operating%20system" title=" machine vision operating system"> machine vision operating system</a>, <a href="https://publications.waset.org/abstracts/search?q=light%20markers" title=" light markers"> light markers</a>, <a href="https://publications.waset.org/abstracts/search?q=measuring%20capability" title=" measuring capability"> measuring capability</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20detection%20system" title=" obstacle detection system"> obstacle detection system</a>, <a href="https://publications.waset.org/abstracts/search?q=autonomous%20transport" title=" autonomous transport"> autonomous transport</a> </p> <a href="https://publications.waset.org/abstracts/159442/alternative-approach-to-the-machine-vision-system-operating-for-solving-industrial-control-issue" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159442.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">114</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20173</span> Obstacle Classification Method Based on 2D LIDAR Database</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Moohyun%20Lee">Moohyun Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Soojung%20Hur"> Soojung Hur</a>, <a href="https://publications.waset.org/abstracts/search?q=Yongwan%20Park"> Yongwan Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=obstacle" title="obstacle">obstacle</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=database" title=" database"> database</a>, <a href="https://publications.waset.org/abstracts/search?q=LIDAR" title=" LIDAR"> LIDAR</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=intensity" title=" intensity"> intensity</a> </p> <a href="https://publications.waset.org/abstracts/11838/obstacle-classification-method-based-on-2d-lidar-database" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11838.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20172</span> Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with Evaluation on a Ground Truth</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hatem%20Hajri">Hatem Hajri</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed-Cherif%20Rahal"> Mohamed-Cherif Rahal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ground%20truth" title="ground truth">ground truth</a>, <a href="https://publications.waset.org/abstracts/search?q=Hungarian%20algorithm" title=" Hungarian algorithm"> Hungarian algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=lidar%20Radar%20data%20fusion" title=" lidar Radar data fusion"> lidar Radar data fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20nearest%20neighbor%20filter" title=" global nearest neighbor filter"> global nearest neighbor filter</a> </p> <a href="https://publications.waset.org/abstracts/95451/real-time-lidar-and-radar-high-level-fusion-for-obstacle-detection-and-tracking-with-evaluation-on-a-ground-truth" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95451.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">171</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20171</span> Beyond the Beep: Optimizing Flight Controller Performance for Reliable Ultrasonic Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raunak%20Munjal">Raunak Munjal</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Akif%20Ali"> Mohammad Akif Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Prithiv%20Raj"> Prithiv Raj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigates the relative effectiveness of various flight controllers for drone obstacle avoidance. To assess ultrasonic sensors' performance in real-time obstacle detection, they are integrated with ESP32 and Arduino Nano controllers. The study determines which controller is most effective for this particular application by analyzing important parameters such as accuracy (mean absolute error), standard deviation, and mean distance range. Furthermore, the study explores the possibility of incorporating state-driven algorithms into the Arduino Nano configuration to potentially improve obstacle detection performance. The results offer significant perspectives for enhancing sensor integration, choosing the best flight controller for obstacle avoidance, and maybe enhancing drones' general environmental navigation ability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ultrasonic%20distance%20measurement" title="ultrasonic distance measurement">ultrasonic distance measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=accuracy%20and%20consistency" title=" accuracy and consistency"> accuracy and consistency</a>, <a href="https://publications.waset.org/abstracts/search?q=flight%20controller%20comparisons" title=" flight controller comparisons"> flight controller comparisons</a>, <a href="https://publications.waset.org/abstracts/search?q=ESP32%20vs%20arduino%20nano" title=" ESP32 vs arduino nano"> ESP32 vs arduino nano</a> </p> <a href="https://publications.waset.org/abstracts/183773/beyond-the-beep-optimizing-flight-controller-performance-for-reliable-ultrasonic-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/183773.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">58</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20170</span> Numerical Study of Heat Transfer and Laminar Flow over a Backward Facing Step with and without Obstacle</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hussein%20Togun">Hussein Togun</a>, <a href="https://publications.waset.org/abstracts/search?q=Tuqa%20Abdulrazzaq"> Tuqa Abdulrazzaq</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20N.%20Kazi"> S. N. Kazi</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Badarudin"> A. Badarudin</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20K.%20A.%20Ariffin"> M. K. A. Ariffin</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20N.%20M.%20Zubir"> M. N. M. Zubir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Heat transfer and laminar fluid flow over backward facing step with and without obstacle numerically studied in this paper. The finite volume method adopted to solve continuity, momentum and energy equations in two dimensions. Backward facing step without obstacle and with different dimension of obstacle were presented. The step height and expansion ratio of channel were 4.8mm and 2 respectively, the range of Reynolds number varied from 75 to 225, constant heat flux subjected on downstream of wall was 2000W/m2, and length of obstacle was 1.5, 3, and 4.5mm with width 1.5mm. The separation length noticed increase with increase Reynolds number and height of obstacle. The result shows increase of heat transfer coefficient for backward facing step with obstacle in compared to those without obstacle. The maximum enhancement of heat transfer observed at 4.5mm of height obstacle due to increase recirculation flow after the obstacle in addition that at backward. Streamline of velocity showing the increase of recirculation region with used obstacle in compared without obstacle and highest recirculation region observed at obstacle height 4.5mm. The amount of enhancement heat transfer was varied between 3-5% compared to backward without obstacle. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=separation%20flow" title="separation flow">separation flow</a>, <a href="https://publications.waset.org/abstracts/search?q=backward%20facing%20step" title=" backward facing step"> backward facing step</a>, <a href="https://publications.waset.org/abstracts/search?q=heat%20transfer" title=" heat transfer"> heat transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=laminar%20flow" title=" laminar flow"> laminar flow</a> </p> <a href="https://publications.waset.org/abstracts/5254/numerical-study-of-heat-transfer-and-laminar-flow-over-a-backward-facing-step-with-and-without-obstacle" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5254.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">469</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20169</span> Model of Obstacle Avoidance on Hard Disk Drive Manufacturing with Distance Constraint </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rawinun%20Praserttaweelap">Rawinun Praserttaweelap</a>, <a href="https://publications.waset.org/abstracts/search?q=Somyot%20Kiatwanidvilai"> Somyot Kiatwanidvilai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obstacle avoidance is the one key for the robot system in unknown environment. The robots should be able to know their position and safety region. This research starts on the path planning which are SLAM and AMCL in ROS system. In addition, the best parameters of the obstacle avoidance function are required. In situation on Hard Disk Drive Manufacturing, the distance between robots and obstacles are very serious due to the manufacturing constraint. The simulations are accomplished by the SLAM and AMCL with adaptive velocity and safety region calculation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title="obstacle avoidance">obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=OA" title=" OA"> OA</a>, <a href="https://publications.waset.org/abstracts/search?q=Simultaneous%20Localization%20and%20Mapping" title=" Simultaneous Localization and Mapping"> Simultaneous Localization and Mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=SLAM" title=" SLAM"> SLAM</a>, <a href="https://publications.waset.org/abstracts/search?q=Adaptive%20Monte%20Carlo%20Localization" title=" Adaptive Monte Carlo Localization"> Adaptive Monte Carlo Localization</a>, <a href="https://publications.waset.org/abstracts/search?q=AMCL" title=" AMCL"> AMCL</a>, <a href="https://publications.waset.org/abstracts/search?q=KLD%20sampling" title=" KLD sampling"> KLD sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=KLD" title=" KLD"> KLD</a> </p> <a href="https://publications.waset.org/abstracts/87279/model-of-obstacle-avoidance-on-hard-disk-drive-manufacturing-with-distance-constraint" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87279.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">198</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20168</span> Collision Avoidance Based on Model Predictive Control for Nonlinear Octocopter Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Do%C4%9Fan%20Y%C4%B1ld%C4%B1z">Doğan Yıldız</a>, <a href="https://publications.waset.org/abstracts/search?q=Aydan%20M%C3%BC%C5%9Ferref%20Erkmen"> Aydan Müşerref Erkmen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20predictive%20control" title="model predictive control">model predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20octocopter%20model" title=" nonlinear octocopter model"> nonlinear octocopter model</a>, <a href="https://publications.waset.org/abstracts/search?q=collision%20avoidance" title=" collision avoidance"> collision avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20detection" title=" obstacle detection"> obstacle detection</a> </p> <a href="https://publications.waset.org/abstracts/150063/collision-avoidance-based-on-model-predictive-control-for-nonlinear-octocopter-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150063.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">191</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20167</span> Obstacle Avoidance Using Image-Based Visual Servoing Based on Deep Reinforcement Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tong%20He">Tong He</a>, <a href="https://publications.waset.org/abstracts/search?q=Long%20Chen"> Long Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Irag%20Mantegh"> Irag Mantegh</a>, <a href="https://publications.waset.org/abstracts/search?q=Wen-Fang%20Xie">Wen-Fang Xie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image-based%20visual%20servoing" title="image-based visual servoing">image-based visual servoing</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title=" obstacle avoidance"> obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=tracking%20target%20identification" title=" tracking target identification"> tracking target identification</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20reinforcement%20learning" title=" deep reinforcement learning"> deep reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20potential%20approach" title=" artificial potential approach"> artificial potential approach</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a> </p> <a href="https://publications.waset.org/abstracts/110259/obstacle-avoidance-using-image-based-visual-servoing-based-on-deep-reinforcement-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110259.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20166</span> An Intelligent Nondestructive Testing System of Ultrasonic Infrared Thermal Imaging Based on Embedded Linux</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hao%20Mi">Hao Mi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ming%20Yang"> Ming Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tian-yue%20Yang"> Tian-yue Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=remote%20monitoring" title="remote monitoring">remote monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=non-destructive%20testing" title=" non-destructive testing"> non-destructive testing</a>, <a href="https://publications.waset.org/abstracts/search?q=embedded%20Linux%20system" title=" embedded Linux system"> embedded Linux system</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a> </p> <a href="https://publications.waset.org/abstracts/101979/an-intelligent-nondestructive-testing-system-of-ultrasonic-infrared-thermal-imaging-based-on-embedded-linux" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101979.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">224</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20165</span> Real Time Adaptive Obstacle Avoidance in Dynamic Environments with Different D-S</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Javad%20Mollakazemi">Mohammad Javad Mollakazemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhad%20Asadi"> Farhad Asadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper a real-time obstacle avoidance approach for both autonomous and non-autonomous dynamical systems (DS) is presented. In this approach the original dynamics of the controller which allow us to determine safety margin can be modulated. Different common types of DS increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle especially when robot moves very fast in changeable complex environments. The method is validated by simulation and influence of different autonomous and non-autonomous DS such as important characteristics of limit cycles and unstable DS. Furthermore, the position of different obstacles in complex environment is explained. Finally, the verification of avoidance trajectories is described through different parameters such as safety factor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=limit%20cycles" title="limit cycles">limit cycles</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20dynamical%20system" title=" nonlinear dynamical system"> nonlinear dynamical system</a>, <a href="https://publications.waset.org/abstracts/search?q=real%20time%20obstacle%20avoidance" title=" real time obstacle avoidance"> real time obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=safety%20margin" title=" safety margin"> safety margin</a> </p> <a href="https://publications.waset.org/abstracts/18168/real-time-adaptive-obstacle-avoidance-in-dynamic-environments-with-different-d-s" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18168.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">443</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20164</span> Performance Analysis of Vision-Based Transparent Obstacle Avoidance for Construction Robots</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Siwei%20Chang">Siwei Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Heng%20Li"> Heng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Haitao%20Wu"> Haitao Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Xin%20Fang"> Xin Fang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=construction%20robot" title="construction robot">construction robot</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title=" obstacle avoidance"> obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=transparent%20obstacle" title=" transparent obstacle"> transparent obstacle</a> </p> <a href="https://publications.waset.org/abstracts/165433/performance-analysis-of-vision-based-transparent-obstacle-avoidance-for-construction-robots" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165433.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">80</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20163</span> An Intelligent Transportation System for Safety and Integrated Management of Railway Crossings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Magrini">M. Magrini</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Moroni"> D. Moroni</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Palazzese"> G. Palazzese</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Pieri"> G. Pieri</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Azzarelli"> D. Azzarelli</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Spada"> A. Spada</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Fanucci"> L. Fanucci</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20Salvetti"> O. Salvetti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Intelligent%20Transportation%20Systems%20%28ITS%29" title="Intelligent Transportation Systems (ITS)">Intelligent Transportation Systems (ITS)</a>, <a href="https://publications.waset.org/abstracts/search?q=railway" title=" railway"> railway</a>, <a href="https://publications.waset.org/abstracts/search?q=railroad%20crossing" title=" railroad crossing"> railroad crossing</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20camera%20networks" title=" smart camera networks"> smart camera networks</a>, <a href="https://publications.waset.org/abstracts/search?q=radar%20obstacle%20detection" title=" radar obstacle detection"> radar obstacle detection</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20traffic%20optimization" title=" real-time traffic optimization"> real-time traffic optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=IoT" title=" IoT"> IoT</a>, <a href="https://publications.waset.org/abstracts/search?q=ETSI%20M2M" title=" ETSI M2M"> ETSI M2M</a>, <a href="https://publications.waset.org/abstracts/search?q=transport%20safety" title=" transport safety "> transport safety </a> </p> <a href="https://publications.waset.org/abstracts/25567/an-intelligent-transportation-system-for-safety-and-integrated-management-of-railway-crossings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25567.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">496</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20162</span> Numerical Study on the Effect of Obstacle Structure on Two-Phase Detonation Initiation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ding%20Yu">Ding Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Ge%20Yang"> Ge Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang%20Hong-Tao"> Wang Hong-Tao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming at the detonation performance and detonation wave propagation distance of liquid fuel detonation engine, the kerosene/oxygen-enriched air mixture is chosen as the research object; its detonation initiation and detonation wave propagation process by mild energy input are numerically studied by using Euler-Lagrange method in the present study. The effects of a semicircular obstacle, rectangular obstacle, and triangular obstacle on the detonation characteristic parameters in the detonation tube are compared and analyzed, and the effect of the angle between obstacle and flame propagation direction on flame propagation characteristics and detonation process when the blocking ratio is constant are studied. The results show that the flame propagation velocity decreases with the increase of the angle in the range of 0-90°, and when the angle is 0° which corresponds to the semicircle obstacle gets the highest detonation wave propagation velocity. With the increase of the angle in the range of 0-90°, DDT (Deflagration to detonation transition) distance decreases first and then increases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deflagration%20to%20detonation%20transition" title="deflagration to detonation transition">deflagration to detonation transition</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20simulation" title=" numerical simulation"> numerical simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20structure" title=" obstacle structure"> obstacle structure</a>, <a href="https://publications.waset.org/abstracts/search?q=turbulent%20flame" title=" turbulent flame"> turbulent flame</a> </p> <a href="https://publications.waset.org/abstracts/165628/numerical-study-on-the-effect-of-obstacle-structure-on-two-phase-detonation-initiation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165628.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20161</span> On the Free-Surface Generated by the Flow over an Obstacle in a Hydraulic Channel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Bouhadef">M. Bouhadef</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Bouzelha-Hammoum"> K. Bouzelha-Hammoum</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Guendouzen-Dabouz"> T. Guendouzen-Dabouz</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Younsi"> A. Younsi</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Zitoun"> T. Zitoun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to report the different experimental studies, conducted in the laboratory, dealing with the flow in the presence of an obstacle lying in a rectangular hydraulic channel. Both subcritical and supercritical regimes are considered. Generally, when considering the theoretical problem of the free-surface flow, in a fluid domain of finite depth, due to the presence of an obstacle, we suppose that the water is an inviscid fluid, which means that there is no sheared velocity profile, but constant upstream. In a hydraulic channel, it is impossible to satisfy this condition. Indeed, water is a viscous fluid and its velocity is null at the bottom. The two configurations are presented, i.e. a flow over an obstacle and a towed obstacle in a resting fluid. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=experiments" title="experiments">experiments</a>, <a href="https://publications.waset.org/abstracts/search?q=free-surface%20flow" title=" free-surface flow"> free-surface flow</a>, <a href="https://publications.waset.org/abstracts/search?q=hydraulic%20channel" title=" hydraulic channel"> hydraulic channel</a>, <a href="https://publications.waset.org/abstracts/search?q=subcritical%20regime" title=" subcritical regime"> subcritical regime</a>, <a href="https://publications.waset.org/abstracts/search?q=supercritical%20flow" title=" supercritical flow"> supercritical flow</a> </p> <a href="https://publications.waset.org/abstracts/75299/on-the-free-surface-generated-by-the-flow-over-an-obstacle-in-a-hydraulic-channel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75299.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">307</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20160</span> Optimization Based Obstacle Avoidance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Dariani">R. Dariani</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Schmidt"> S. Schmidt</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Kasper"> R. Kasper</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on a non-linear single track model which describes the dynamics of vehicle, an optimal path planning strategy is developed. Real time optimization is used to generate reference control values to allow leading the vehicle alongside a calculated lane which is optimal for different objectives such as energy consumption, run time, safety or comfort characteristics. Strict mathematic formulation of the autonomous driving allows taking decision on undefined situation such as lane change or obstacle avoidance. Based on position of the vehicle, lane situation and obstacle position, the optimization problem is reformulated in real-time to avoid the obstacle and any car crash. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20driving" title="autonomous driving">autonomous driving</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title=" obstacle avoidance"> obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title=" path planning"> path planning</a> </p> <a href="https://publications.waset.org/abstracts/13122/optimization-based-obstacle-avoidance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13122.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20159</span> Real-Time Adaptive Obstacle Avoidance with DS Method and the Influence of Dynamic Environments Change on Different DS</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Mahjoub%20Moghadas">Saeed Mahjoub Moghadas</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhad%20Asadi"> Farhad Asadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Shahed%20Torkamandi"> Shahed Torkamandi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Moradi"> Hassan Moradi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmood%20Purgamshidian"> Mahmood Purgamshidian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present real-time obstacle avoidance approach for both autonomous and non-autonomous DS-based controllers and also based on dynamical systems (DS) method. In this approach, we can modulate the original dynamics of the controller and it allows us to determine safety margin and different types of DS to increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle and especially when robot moves very fast in changeable complex environments. The method is validated in simulation and influence of different autonomous and non-autonomous DS such as limit cycles, and unstable DS on this algorithm and also the position of different obstacles in complex environment is explained. Finally, we describe how the avoidance trajectories can be verified through different parameters such as safety factor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=limit%20cycles" title="limit cycles">limit cycles</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20dynamical%20system" title=" nonlinear dynamical system"> nonlinear dynamical system</a>, <a href="https://publications.waset.org/abstracts/search?q=real%20time%20obstacle%20avoidance" title=" real time obstacle avoidance"> real time obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=DS-based%20controllers" title=" DS-based controllers"> DS-based controllers</a> </p> <a href="https://publications.waset.org/abstracts/13882/real-time-adaptive-obstacle-avoidance-with-ds-method-and-the-influence-of-dynamic-environments-change-on-different-ds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13882.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">388</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20158</span> An Architecture for New Generation of Distributed Intrusion Detection System Based on Preventive Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Benmoussa">H. Benmoussa</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20El%20Kalam"> A. A. El Kalam</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ait%20Ouahman"> A. Ait Ouahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Intrusion%20Detection%20System%20%28IDS%29" title="Intrusion Detection System (IDS)">Intrusion Detection System (IDS)</a>, <a href="https://publications.waset.org/abstracts/search?q=preventive%20detection" title=" preventive detection"> preventive detection</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20agents" title=" mobile agents"> mobile agents</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20architecture" title=" distributed architecture"> distributed architecture</a> </p> <a href="https://publications.waset.org/abstracts/18239/an-architecture-for-new-generation-of-distributed-intrusion-detection-system-based-on-preventive-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18239.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">583</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20157</span> Optical Flow Direction Determination for Railway Crossing Occupancy Monitoring</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zdenek%20Silar">Zdenek Silar</a>, <a href="https://publications.waset.org/abstracts/search?q=Martin%20Dobrovolny"> Martin Dobrovolny</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=background%20estimation" title="background estimation">background estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=direction%20of%20optical%20flow" title=" direction of optical flow"> direction of optical flow</a>, <a href="https://publications.waset.org/abstracts/search?q=K-means%20clustering" title=" K-means clustering"> K-means clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=objects%20detection" title=" objects detection"> objects detection</a>, <a href="https://publications.waset.org/abstracts/search?q=railway%20crossing%20monitoring" title=" railway crossing monitoring"> railway crossing monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=velocity%20vectors" title=" velocity vectors"> velocity vectors</a> </p> <a href="https://publications.waset.org/abstracts/1853/optical-flow-direction-determination-for-railway-crossing-occupancy-monitoring" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1853.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">518</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20156</span> Self-Directed-Car on GT Road: Grand Trunk Road</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rameez%20Ahmad">Rameez Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Aqib%20Mehmood"> Aqib Mehmood</a>, <a href="https://publications.waset.org/abstracts/search?q=Imran%20Khan"> Imran Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Self-directed car (SDC) that can drive itself from one fact to another without support from a driver. Certain trust that self-directed car obligate the probable to transform the transportation manufacturing while essentially removing coincidences, and cleaning up the environment. This study realizes the effects that SDC (also called a self-driving, driver or robotic) vehicle travel demands and ride scheme is likely to have. Without the typical obstacles that allows detection of a audio vision based hardware and software construction (It (SDC) and cost benefits, the vehicle technologies, Gold (Generic Obstacle and Lane Detection) to a knowledge-based system to predict their potential and consider the shape, color, or balance) and an organized environment with colored lane patterns, lane position ban. Discovery the problematic consequence of (SDC) on GT (grand trunk road) road and brand the car further effectual. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SDC" title="SDC">SDC</a>, <a href="https://publications.waset.org/abstracts/search?q=gold" title=" gold"> gold</a>, <a href="https://publications.waset.org/abstracts/search?q=GT" title=" GT"> GT</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge-based%20system" title=" knowledge-based system"> knowledge-based system</a> </p> <a href="https://publications.waset.org/abstracts/30033/self-directed-car-on-gt-road-grand-trunk-road" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30033.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">370</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20155</span> Simulation of Obstacle Avoidance for Multiple Autonomous Vehicles in a Dynamic Environment Using Q-Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andreas%20D.%20Jansson">Andreas D. Jansson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20vehicles" title="autonomous vehicles">autonomous vehicles</a>, <a href="https://publications.waset.org/abstracts/search?q=industry%204.0" title=" industry 4.0"> industry 4.0</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20system" title=" multi-agent system"> multi-agent system</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title=" obstacle avoidance"> obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=Q-learning" title=" Q-learning"> Q-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/132508/simulation-of-obstacle-avoidance-for-multiple-autonomous-vehicles-in-a-dynamic-environment-using-q-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132508.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">138</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20154</span> Parking Space Detection and Trajectory Tracking Control for Vehicle Auto-Parking</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shiuh-Jer%20Huang">Shiuh-Jer Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Sheng%20Hsu"> Yu-Sheng Hsu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> 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 used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vehicle%20auto-parking" title="vehicle auto-parking">vehicle auto-parking</a>, <a href="https://publications.waset.org/abstracts/search?q=parking%20space%20detection" title=" parking space detection"> parking space detection</a>, <a href="https://publications.waset.org/abstracts/search?q=parking%20path%20tracking%20control" title=" parking path tracking control"> parking path tracking control</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20fuzzy%20controller" title=" intelligent fuzzy controller"> intelligent fuzzy controller</a> </p> <a href="https://publications.waset.org/abstracts/78571/parking-space-detection-and-trajectory-tracking-control-for-vehicle-auto-parking" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78571.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">244</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20153</span> Securing Web Servers by the Intrusion Detection System (IDS)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yousef%20Farhaoui">Yousef Farhaoui </a> </p> <p class="card-text"><strong>Abstract:</strong></p> An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title="intrusion detection">intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=architectures" title=" architectures"> architectures</a>, <a href="https://publications.waset.org/abstracts/search?q=characteristic" title=" characteristic"> characteristic</a>, <a href="https://publications.waset.org/abstracts/search?q=tools" title=" tools"> tools</a>, <a href="https://publications.waset.org/abstracts/search?q=security" title=" security"> security</a>, <a href="https://publications.waset.org/abstracts/search?q=web%20server" title=" web server"> web server</a> </p> <a href="https://publications.waset.org/abstracts/13346/securing-web-servers-by-the-intrusion-detection-system-ids" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13346.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">418</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20152</span> Efficient Signal Detection Using QRD-M Based on Channel Condition in MIMO-OFDM System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jae-Jeong%20Kim">Jae-Jeong Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ki-Ro%20Kim"> Ki-Ro Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyoung-Kyu%20Song"> Hyoung-Kyu Song</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better trade off between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MIMO-OFDM" title="MIMO-OFDM">MIMO-OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=QRD-M" title=" QRD-M"> QRD-M</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20condition" title=" channel condition"> channel condition</a>, <a href="https://publications.waset.org/abstracts/search?q=BER" title=" BER"> BER</a> </p> <a href="https://publications.waset.org/abstracts/3518/efficient-signal-detection-using-qrd-m-based-on-channel-condition-in-mimo-ofdm-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3518.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">370</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20151</span> Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carlos%20Gordon">Carlos Gordon</a>, <a href="https://publications.waset.org/abstracts/search?q=Patricio%20Encalada"> Patricio Encalada</a>, <a href="https://publications.waset.org/abstracts/search?q=Henry%20Lema"> Henry Lema</a>, <a href="https://publications.waset.org/abstracts/search?q=Diego%20Leon"> Diego Leon</a>, <a href="https://publications.waset.org/abstracts/search?q=Dennis%20Chicaiza"> Dennis Chicaiza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20navigation" title="autonomous navigation">autonomous navigation</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title=" path planning"> path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=robotic%20operative%20system" title=" robotic operative system"> robotic operative system</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20source%20computer%20vision%20library" title=" open source computer vision library"> open source computer vision library</a> </p> <a href="https://publications.waset.org/abstracts/101726/autonomous-kuka-youbot-navigation-based-on-machine-learning-and-path-planning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101726.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">177</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20150</span> Proposed Anticipating Learning Classifier System for Cloud Intrusion Detection (ALCS-CID)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wafa%27%20Slaibi%20Alsharafat">Wafa' Slaibi Alsharafat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IDS" title="IDS">IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title=" cloud computing"> cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=anticipating%20classifier%20system" title=" anticipating classifier system"> anticipating classifier system</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a> </p> <a href="https://publications.waset.org/abstracts/18240/proposed-anticipating-learning-classifier-system-for-cloud-intrusion-detection-alcs-cid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18240.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">474</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20149</span> Drone On-Time Obstacle Avoidance for Static and Dynamic Obstacles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Herath%20M.%20P.%20C.%20Jayaweera">Herath M. P. C. Jayaweera</a>, <a href="https://publications.waset.org/abstracts/search?q=Samer%20Hanoun"> Samer Hanoun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Path planning for on-time obstacle avoidance is an essential and challenging task that enables drones to achieve safe operation in any application domain. The level of challenge increases significantly on the obstacle avoidance technique when the drone is following a ground mobile entity (GME). This is mainly due to the change in direction and magnitude of the GME′s velocity in dynamic and unstructured environments. Force field techniques are the most widely used obstacle avoidance methods due to their simplicity, ease of use, and potential to be adopted for three-dimensional dynamic environments. However, the existing force field obstacle avoidance techniques suffer many drawbacks, including their tendency to generate longer routes when the obstacles are sideways of the drone′s route, poor ability to find the shortest flyable path, propensity to fall into local minima, producing a non-smooth path, and high failure rate in the presence of symmetrical obstacles. To overcome these shortcomings, this paper proposes an on-time three-dimensional obstacle avoidance method for drones to effectively and efficiently avoid dynamic and static obstacles in unknown environments while pursuing a GME. This on-time obstacle avoidance technique generates velocity waypoints for its obstacle-free and efficient path based on the shape of the encountered obstacles. This method can be utilized on most types of drones that have basic distance measurement sensors and autopilot-supported flight controllers. The proposed obstacle avoidance technique is validated and evaluated against existing force field methods for different simulation scenarios in Gazebo and ROS-supported PX4-SITL. The simulation results show that the proposed obstacle avoidance technique outperforms the existing force field techniques and is better suited for real-world applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drones" title="drones">drones</a>, <a href="https://publications.waset.org/abstracts/search?q=force%20field%20methods" title=" force field methods"> force field methods</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title=" obstacle avoidance"> obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title=" path planning"> path planning</a> </p> <a href="https://publications.waset.org/abstracts/172301/drone-on-time-obstacle-avoidance-for-static-and-dynamic-obstacles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172301.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">93</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20148</span> Fault Location Detection in Active Distribution System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Rezaeipour">R. Rezaeipour</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20R.%20Mehrabi"> A. R. Mehrabi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fault%20location%20detection" title="fault location detection">fault location detection</a>, <a href="https://publications.waset.org/abstracts/search?q=active%20distribution%20system" title=" active distribution system"> active distribution system</a>, <a href="https://publications.waset.org/abstracts/search?q=micro%20grids" title=" micro grids"> micro grids</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20operators" title=" network operators"> network operators</a> </p> <a href="https://publications.waset.org/abstracts/27086/fault-location-detection-in-active-distribution-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27086.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">788</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20147</span> Rapid Detection System of Airborne Pathogens</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shigenori%20Togashi">Shigenori Togashi</a>, <a href="https://publications.waset.org/abstracts/search?q=Kei%20Takenaka"> Kei Takenaka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We developed new processes which can collect and detect rapidly airborne pathogens such as the avian flu virus for the pandemic prevention. The fluorescence antibody technique is known as one of high-sensitive detection methods for viruses, but this needs up to a few hours to bind sufficient fluorescence dyes to viruses for detection. In this paper, we developed a mist-labeling can detect substitution viruses in a short time to improve the binding rate of fluorescent dyes and substitution viruses by the micro reaction process. Moreover, we developed the rapid detection system with the above 'mist labeling'. The detection system set with a sampling bag collecting patient’s breath and a cartridge can detect automatically pathogens within 10 minutes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=viruses" title="viruses">viruses</a>, <a href="https://publications.waset.org/abstracts/search?q=sampler" title=" sampler"> sampler</a>, <a href="https://publications.waset.org/abstracts/search?q=mist" title=" mist"> mist</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=fluorescent%20dyes" title=" fluorescent dyes"> fluorescent dyes</a>, <a href="https://publications.waset.org/abstracts/search?q=microreaction" title=" microreaction"> microreaction</a> </p> <a href="https://publications.waset.org/abstracts/2700/rapid-detection-system-of-airborne-pathogens" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2700.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">475</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20146</span> Electrical Dault Detection of Photovoltaic System: A Short-Circuit Fault Case</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Moustapha%20H.%20Ibrahim">Moustapha H. Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Dahir%20Abdourahman"> Dahir Abdourahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PV%20system" title="PV system">PV system</a>, <a href="https://publications.waset.org/abstracts/search?q=short-circuit" title=" short-circuit"> short-circuit</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20detection" title=" fault detection"> fault detection</a>, <a href="https://publications.waset.org/abstracts/search?q=modelling" title=" modelling"> modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=MATLAB-Simulink" title=" MATLAB-Simulink"> MATLAB-Simulink</a> </p> <a href="https://publications.waset.org/abstracts/109349/electrical-dault-detection-of-photovoltaic-system-a-short-circuit-fault-case" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109349.pdf" target="_blank" class="btn btn-primary 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