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sub-tasks</title> <meta name="description" content="Search results for: sub-tasks"> <meta name="keywords" content="sub-tasks"> <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 class="d-block d-lg-none navbar-toggler ml-auto" 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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="sub-tasks"> <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> 4</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: sub-tasks</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Analyze the Effect of TETRA, Terrestrial Trunked Radio, Signal on the Health of People Working in the Gas Refinery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Bagher%20Heidari">Mohammad Bagher Heidari</a>, <a href="https://publications.waset.org/abstracts/search?q=Hefzollah%20Mohammadian"> Hefzollah Mohammadian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> TETRA (Terrestrial Trunked Radio) is a digital radio communication standard, which has been implemented in several different parts of the gas refinery ninth (phase 12th) by South Pars Gas Complex. Studies on possible impacts on the users' health considering different exposure conditions are missing. Objectives: To investigate possible acute effects of electromagnetic 铿乪lds (EMF) of two different levels of TETRA hand-held transmitter signals on cognitive function and well-being in healthy young males. Methods: In the present double-blind cross-over study possible effects of short-term (2.5 h) EMF exposure of handset-like signals of TETRA (450 - 470 MHz) were studied in 30 healthy male participants (mean 卤 SD: 25.4 卤2.6 years). Individuals were tested on nine study days, on which they were exposed to three different exposure conditions (Sham, TETRA 1.5 W/kg and TETRA 10.0 W/kg) in a randomly assigned and balanced order. Participants were tested in the afternoon at a 铿亁ed timeframe. Results: Attention remained unchanged in two out of three tasks. In the working memory, signi铿乧ant changes were observed in two out of four subtasks. Signi铿乧ant results were found in 5 out of 35 tested parameters, four of them led to an improvement in performance. Mood, well-being and subjective somatic complaints were not affected by TETRA exposure. Conclusions: The results of the present study do not indicate a negative impact of a short-term EMF- effect of TETRA on cognitive function and well-being in healthy young men. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=TETRA%20%28terrestrial%20trunked%20radio%29" title="TETRA (terrestrial trunked radio)">TETRA (terrestrial trunked radio)</a>, <a href="https://publications.waset.org/abstracts/search?q=electromagnetic%20fields%20%28EMF%29" title=" electromagnetic fields (EMF)"> electromagnetic fields (EMF)</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20telecommunication%20health%20research%20%28MTHR%29" title=" mobile telecommunication health research (MTHR)"> mobile telecommunication health research (MTHR)</a>, <a href="https://publications.waset.org/abstracts/search?q=antenna" title=" antenna"> antenna</a> </p> <a href="https://publications.waset.org/abstracts/41821/analyze-the-effect-of-tetra-terrestrial-trunked-radio-signal-on-the-health-of-people-working-in-the-gas-refinery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41821.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">296</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">3</span> Optimizing Parallel Computing Systems: A Java-Based Approach to Modeling and Performance Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maher%20Ali%20Rusho">Maher Ali Rusho</a>, <a href="https://publications.waset.org/abstracts/search?q=Sudipta%20Halder"> Sudipta Halder</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of the study is to develop optimal solutions for models of parallel computing systems using the Java language. During the study, programmes were written for the examined models of parallel computing systems. The result of the parallel sorting code is the output of a sorted array of random numbers. When processing data in parallel, the time spent on processing and the first elements of the list of squared numbers are displayed. When processing requests asynchronously, processing completion messages are displayed for each task with a slight delay. The main results include the development of optimisation methods for algorithms and processes, such as the division of tasks into subtasks, the use of non-blocking algorithms, effective memory management, and load balancing, as well as the construction of diagrams and comparison of these methods by characteristics, including descriptions, implementation examples, and advantages. In addition, various specialised libraries were analysed to improve the performance and scalability of the models. The results of the work performed showed a substantial improvement in response time, bandwidth, and resource efficiency in parallel computing systems. Scalability and load analysis assessments were conducted, demonstrating how the system responds to an increase in data volume or the number of threads. Profiling tools were used to analyse performance in detail and identify bottlenecks in models, which improved the architecture and implementation of parallel computing systems. The obtained results emphasise the importance of choosing the right methods and tools for optimising parallel computing systems, which can substantially improve their performance and efficiency. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithm%20optimisation" title="algorithm optimisation">algorithm optimisation</a>, <a href="https://publications.waset.org/abstracts/search?q=memory%20management" title=" memory management"> memory management</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20balancing" title=" load balancing"> load balancing</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20profiling" title=" performance profiling"> performance profiling</a>, <a href="https://publications.waset.org/abstracts/search?q=asynchronous%20programming." title=" asynchronous programming."> asynchronous programming.</a> </p> <a href="https://publications.waset.org/abstracts/192978/optimizing-parallel-computing-systems-a-java-based-approach-to-modeling-and-performance-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192978.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">12</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">2</span> Hybrid Method for Smart Suggestions in Conversations for Online Marketplaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yasamin%20Rahimi">Yasamin Rahimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Kamandi"> Ali Kamandi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abbas%20Hoseini"> Abbas Hoseini</a>, <a href="https://publications.waset.org/abstracts/search?q=Hesam%20Haddad"> Hesam Haddad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller鈥檚 messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=smart%20reply" title="smart reply">smart reply</a>, <a href="https://publications.waset.org/abstracts/search?q=spell%20checker" title=" spell checker"> spell checker</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title=" information retrieval"> information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=intent%20detection" title=" intent detection"> intent detection</a>, <a href="https://publications.waset.org/abstracts/search?q=question%20answering" title=" question answering"> question answering</a> </p> <a href="https://publications.waset.org/abstracts/138668/hybrid-method-for-smart-suggestions-in-conversations-for-online-marketplaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138668.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">187</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">1</span> Small Scale Mobile Robot Auto-Parking Using Deep Learning, Image Processing, and Kinematics-Based Target Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mingxin%20Li">Mingxin Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Liya%20Ni"> Liya Ni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot鈥檚 height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20parking" title="autonomous parking">autonomous parking</a>, <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20network" title=" convolutional neural network"> convolutional neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=kinematics-based%20prediction" title=" kinematics-based prediction"> kinematics-based prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer%20learning" title=" transfer learning"> transfer learning</a> </p> <a href="https://publications.waset.org/abstracts/131979/small-scale-mobile-robot-auto-parking-using-deep-learning-image-processing-and-kinematics-based-target-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131979.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">132</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a 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