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machine</title> <meta name="description" content="Search results for: machine"> <meta name="keywords" content="machine"> <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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class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="machine"> <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> 2845</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: machine</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2815</span> A Comparative Study of Series-Connected Two-Motor Drive Fed by a Single Inverter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Djahbar">A. Djahbar</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Bounadja"> E. Bounadja</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Zegaoui"> A. Zegaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Allouache"> H. Allouache</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, vector control of a series-connected two-machine drive system fed by a single inverter (CSI/VSI) is presented. The two stator windings of both machines are connected in series while the rotors may be connected to different loads, are called series-connected two-machine drive. Appropriate phase transposition is introduced while connecting the series stator winding to obtain decoupled control the two-machines. The dynamic decoupling of each machine from the group is obtained using the vector control algorithm. The independent control is demonstrated by analyzing the characteristics of torque and speed of each machine obtained via simulation under vector control scheme. The viability of the control techniques is proved using analytically and simulation approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drives" title="drives">drives</a>, <a href="https://publications.waset.org/abstracts/search?q=inverter" title=" inverter"> inverter</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-phase%20induction%20machine" title=" multi-phase induction machine"> multi-phase induction machine</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20control" title=" vector control"> vector control</a> </p> <a href="https://publications.waset.org/abstracts/42943/a-comparative-study-of-series-connected-two-motor-drive-fed-by-a-single-inverter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42943.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">480</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">2814</span> Failure Analysis and Fatigue Life Estimation of a Shaft of a Rotary Draw Bending Machine </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Engel">B. Engel</a>, <a href="https://publications.waset.org/abstracts/search?q=Sara%20Salman%20Hassan%20Al-Maeeni"> Sara Salman Hassan Al-Maeeni </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human consumption of the Earth's resources increases the need for a sustainable development as an important ecological, social, and economic theme. Re-engineering of machine tools, in terms of design and failure analysis, is defined as steps performed on an obsolete machine to return it to a new machine with the warranty that matches the customer requirement. To understand the future fatigue behavior of the used machine components, it is important to investigate the possible causes of machine parts failure through design, surface, and material inspections. In this study, the failure modes of the shaft of the rotary draw bending machine are inspected. Furthermore, stress and deflection analysis of the shaft subjected to combined torsion and bending loads are carried out by an analytical method and compared with a finite element analysis method. The theoretical fatigue strength, correction factors, and fatigue life sustained by the shaft before damaged are estimated by creating a stress-cycle (S-N) diagram. In conclusion, it is seen that the shaft can work in the second life, but it needs some surface treatments to increase the reliability and fatigue life. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=failure%20analysis" title="failure analysis">failure analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=fatigue%20life" title=" fatigue life"> fatigue life</a>, <a href="https://publications.waset.org/abstracts/search?q=FEM%20analysis" title=" FEM analysis"> FEM analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=shaft" title=" shaft"> shaft</a>, <a href="https://publications.waset.org/abstracts/search?q=stress%20analysis" title=" stress analysis"> stress analysis</a> </p> <a href="https://publications.waset.org/abstracts/79871/failure-analysis-and-fatigue-life-estimation-of-a-shaft-of-a-rotary-draw-bending-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79871.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">301</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">2813</span> Synchronous Generator in Case Voltage Sags for Different Loads</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benalia%20Nadia">Benalia Nadia</a>, <a href="https://publications.waset.org/abstracts/search?q=Bensiali%20Nadia"> Bensiali Nadia</a>, <a href="https://publications.waset.org/abstracts/search?q=Zezouri%20Noura"> Zezouri Noura </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper studies the effects of voltage sags, both symmetrical and unsymmetrical, on the three-phase Synchronous Machine (SM) when powering an isolate load or infinite bus bar. The vast majority of the electrical power generation systems in the world is consist of synchronous generators coupled to the electrical network though a transformer. Voltage sags on SM cause speed variations, current and torque peaks and hence may cause tripping and equipment damage. The consequences of voltage sags in the machine behavior depends on different factors such as its magnitude (or depth), duration , the parameters of the machine and also the size of load. In this study, we consider the machine feeds an infinite bus bar in the first and the isolate load using symmetric and asymmetric defaults to see the behavior of the machine in both case the simulation have been used on SIMULINK MATLAB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=power%20quality" title="power quality">power quality</a>, <a href="https://publications.waset.org/abstracts/search?q=voltage%20sag" title=" voltage sag"> voltage sag</a>, <a href="https://publications.waset.org/abstracts/search?q=synchronous%20generator" title=" synchronous generator"> synchronous generator</a>, <a href="https://publications.waset.org/abstracts/search?q=infinite%20system" title=" infinite system"> infinite system</a> </p> <a href="https://publications.waset.org/abstracts/21583/synchronous-generator-in-case-voltage-sags-for-different-loads" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21583.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">679</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">2812</span> A Strategy of Direct Power Control for PWM Rectifier Reducing Ripple in Instantaneous Power</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=T.%20Mohammed%20Chikouche">T. Mohammed Chikouche</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Hartani"> K. Hartani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on the analysis of basic direct torque control, a parallel master slave for four in-wheel permanent magnet synchronous motors (PMSM) fed by two three phase inverters used in electric vehicle is proposed in this paper. A conventional system with multi-inverter and multi-machine comprises a three phase inverter for each machine to be controlled. Another approach consists in using only one three-phase inverter to supply several permanent magnet synchronous machines. A modified direct torque control (DTC) algorithm is used for the control of the bi-machine traction system. Simulation results show that the proposed control strategy is well adapted for the synchronism of this system and provide good speed tracking performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electric%20vehicle" title="electric vehicle">electric vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-machine%20single-inverter%20system" title=" multi-machine single-inverter system"> multi-machine single-inverter system</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-machine%20multi-inverter%20control" title=" multi-machine multi-inverter control"> multi-machine multi-inverter control</a>, <a href="https://publications.waset.org/abstracts/search?q=in-wheel%20motor" title=" in-wheel motor"> in-wheel motor</a>, <a href="https://publications.waset.org/abstracts/search?q=master-slave%20control" title=" master-slave control"> master-slave control</a> </p> <a href="https://publications.waset.org/abstracts/87696/a-strategy-of-direct-power-control-for-pwm-rectifier-reducing-ripple-in-instantaneous-power" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87696.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">221</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">2811</span> Development of Fake News Model Using Machine Learning through Natural Language Processing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sajjad%20Ahmed">Sajjad Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Knut%20Hinkelmann"> Knut Hinkelmann</a>, <a href="https://publications.waset.org/abstracts/search?q=Flavio%20Corradini"> Flavio Corradini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fake%20news%20detection" title="fake news detection">fake news detection</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</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=classification%20techniques." title=" classification techniques. "> classification techniques. </a> </p> <a href="https://publications.waset.org/abstracts/127894/development-of-fake-news-model-using-machine-learning-through-natural-language-processing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127894.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">167</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">2810</span> Empowering a New Frontier in Heart Disease Detection: Unleashing Quantum Machine Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sadia%20Nasrin%20Tisha">Sadia Nasrin Tisha</a>, <a href="https://publications.waset.org/abstracts/search?q=Mushfika%20Sharmin%20Rahman"> Mushfika Sharmin Rahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Javier%20Orduz"> Javier Orduz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20machine%20learning" title="quantum machine learning">quantum machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a>, <a href="https://publications.waset.org/abstracts/search?q=QSVM" title=" QSVM"> QSVM</a>, <a href="https://publications.waset.org/abstracts/search?q=matrix%20product%20state" title=" matrix product state"> matrix product state</a> </p> <a href="https://publications.waset.org/abstracts/171382/empowering-a-new-frontier-in-heart-disease-detection-unleashing-quantum-machine-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171382.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">94</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">2809</span> On Control of Asynchronous Sequential Machines with Switching Capability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jung-Min%20Yang">Jung-Min Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Corrective control enables us to change the stable state behavior of an asynchronous sequential machine without modifying inner logic of the machine. This paper addresses corrective control for asynchronous machines with switching capability. The considered asynchronous machine consists of a set of different submachines and switches to each machine according to a constant switching sequence. The control goal is to design a corrective controller such that the closed-loop system can match the behavior of a reference model. The reachability of the switched asynchronous machine is described by a logic calculation of the reachability of submachines. The design procedure of the proposed corrective controller is outlined, and the applicability of the proposed scheme is validated in an example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=switched%20asynchronous%20sequential%20machines" title="switched asynchronous sequential machines">switched asynchronous sequential machines</a>, <a href="https://publications.waset.org/abstracts/search?q=corrective%20control" title=" corrective control"> corrective control</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20feedback" title=" state feedback"> state feedback</a>, <a href="https://publications.waset.org/abstracts/search?q=switching%20sequences" title=" switching sequences"> switching sequences</a> </p> <a href="https://publications.waset.org/abstracts/14853/on-control-of-asynchronous-sequential-machines-with-switching-capability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14853.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">457</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">2808</span> Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vincent%20Liu">Vincent Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diabetes" title="diabetes">diabetes</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=30-day%20readmission" title=" 30-day readmission"> 30-day readmission</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a> </p> <a href="https://publications.waset.org/abstracts/181586/using-greywolf-optimized-machine-learning-algorithms-to-improve-accuracy-for-predicting-hospital-readmission-for-diabetes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181586.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">61</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">2807</span> Artificial Intelligence as a User of Copyrighted Work: Descriptive Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dominika%20Collett">Dominika Collett</a> </p> <p class="card-text"><strong>Abstract:</strong></p> AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=copyright" title="copyright">copyright</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=legal%20use" title=" legal use"> legal use</a>, <a href="https://publications.waset.org/abstracts/search?q=infringement" title=" infringement"> infringement</a>, <a href="https://publications.waset.org/abstracts/search?q=Czech%20law" title=" Czech law"> Czech law</a>, <a href="https://publications.waset.org/abstracts/search?q=EU%20law" title=" EU law"> EU law</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20and%20data%20mining" title=" text and data mining"> text and data mining</a> </p> <a href="https://publications.waset.org/abstracts/117804/artificial-intelligence-as-a-user-of-copyrighted-work-descriptive-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117804.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">123</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">2806</span> Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Norah%20Mohammed%20Alshahrani">Norah Mohammed Alshahrani</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulaziz%20Almaleh"> Abdulaziz Almaleh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autism%20spectrum%20disorder" title="autism spectrum disorder">autism spectrum disorder</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=feature%20selection" title=" feature selection"> feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/151270/using-machine-learning-techniques-for-autism-spectrum-disorder-analysis-and-detection-in-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151270.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">151</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">2805</span> Construction and Evaluation of Soybean Thresher </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oladimeji%20Adetona%20Adeyeye">Oladimeji Adetona Adeyeye</a>, <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20Rotimi%20Sadiku"> Emmanuel Rotimi Sadiku</a>, <a href="https://publications.waset.org/abstracts/search?q=Oluwaseun%20Olayinka%20Adeyeye"> Oluwaseun Olayinka Adeyeye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to resuscitate soybean production and post-harvest processing especially, in term of threshing, there is need to develop an affordable threshing machine which will reduce drudgery associated with manual soybean threshing. Soybean thresher was fabricated and evaluated at Institute of Agricultural Research and Training IAR&T Apata Ibadan. The machine component includes; hopper, threshing unit, shaker, cleaning unit and the seed outlet, all working together to achieve the main objective of threshing and cleaning. TGX1835 - 10E variety was used for evaluation because of its high resistance to pests, rust and pustules. The final moisture content of the used sample was about 15%. The sample was weighed and introduced into the machine. The parameters evaluated includes moisture content, threshing efficiency, cleaning efficiency, machine capacity and speed. The threshing efficiency and capacity are 74% and 65.9kg/hr respectively. All materials used were sourced locally which makes the cost of production of the machine extremely cheaper than the imported soybean thresher. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=efficiency" title="efficiency">efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20capacity" title=" machine capacity"> machine capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=speed" title=" speed"> speed</a>, <a href="https://publications.waset.org/abstracts/search?q=soybean" title=" soybean"> soybean</a>, <a href="https://publications.waset.org/abstracts/search?q=threshing" title=" threshing"> threshing</a> </p> <a href="https://publications.waset.org/abstracts/68036/construction-and-evaluation-of-soybean-thresher" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68036.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">485</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">2804</span> Machine Learning Techniques to Develop Traffic Accident Frequency Prediction Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rodrigo%20Aguiar">Rodrigo Aguiar</a>, <a href="https://publications.waset.org/abstracts/search?q=Adelino%20Ferreira"> Adelino Ferreira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety. <p class="card-text"><strong>Keywords:</strong> <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=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20of%20accidents" title=" frequency of accidents"> frequency of accidents</a>, <a href="https://publications.waset.org/abstracts/search?q=road%20safety" title=" road safety"> road safety</a> </p> <a href="https://publications.waset.org/abstracts/178875/machine-learning-techniques-to-develop-traffic-accident-frequency-prediction-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/178875.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">89</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">2803</span> A Study on Performance Prediction in Early Design Stage of Apartment Housing Using Machine Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seongjun%20Kim">Seongjun Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanghoon%20Shim"> Sanghoon Shim</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinwooung%20Kim"> Jinwooung Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaehwan%20Jung"> Jaehwan Jung</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Ah%20Kim"> Sung-Ah Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=apartment%20housing" title="apartment housing">apartment housing</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=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20prediction" title=" performance prediction"> performance prediction</a> </p> <a href="https://publications.waset.org/abstracts/80644/a-study-on-performance-prediction-in-early-design-stage-of-apartment-housing-using-machine-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80644.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">481</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">2802</span> Design and Construction of a Maize Dehusking Machine for Small and Medium-Scale Farmers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Francis%20Ojo%20Ologunagba">Francis Ojo Ologunagba</a>, <a href="https://publications.waset.org/abstracts/search?q=Monday%20Olatunbosun%20Ale"> Monday Olatunbosun Ale</a>, <a href="https://publications.waset.org/abstracts/search?q=Lewis%20A.%20Olutayo"> Lewis A. Olutayo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The economic successes of commercial development of agricultural product processing depend upon the adaptability of each processing stage to mechanization. In maize processing, one of its post-harvest operations that is still facing a major challenge is dehusking. Therefore, a maize dehusking machine that could replace the prevalent traditional method of dehusking maize in developing countries, especially Nigeria was designed, constructed and tested at the Department of Agricultural and Bio-Environmental Engineering Technology, Rufus Giwa Polytechnic, Owo. The basic features of the machine are feeding unit (hopper), housing frame, dehusking unit, drive mechanism and discharge outlets. The machine was tested with maize of 50mm average diameter at 13% moisture content and 2.5mm machine roller clearance. Test results showed appreciable performance with the dehusking efficiency of 92% and throughput capacity of 200 Kg/hr at a machine speed of 400rpm. The estimated production cost of the machine at the time of construction is forty-five thousand, one hundred and eighty nairas (₦45,180) excluding the cost of the electric motor. It is therefore recommended for small and medium-scale maize farmers and processors in Nigeria. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=construction" title="construction">construction</a>, <a href="https://publications.waset.org/abstracts/search?q=dehusking" title=" dehusking"> dehusking</a>, <a href="https://publications.waset.org/abstracts/search?q=design" title=" design"> design</a>, <a href="https://publications.waset.org/abstracts/search?q=efficiency" title=" efficiency"> efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=maize" title=" maize"> maize</a> </p> <a href="https://publications.waset.org/abstracts/84517/design-and-construction-of-a-maize-dehusking-machine-for-small-and-medium-scale-farmers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84517.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">323</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">2801</span> Statistical Comparison of Machine and Manual Translation: A Corpus-Based Study of Gone with the Wind </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yanmeng%20Liu">Yanmeng Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article analyzes and compares the linguistic differences between machine translation and manual translation, through a case study of the book Gone with the Wind. As an important carrier of human feeling and thinking, the literature translation poses a huge difficulty for machine translation, and it is supposed to expose distinct translation features apart from manual translation. In order to display linguistic features objectively, tentative uses of computerized and statistical evidence to the systematic investigation of large scale translation corpora by using quantitative methods have been deployed. This study compiles bilingual corpus with four versions of Chinese translations of the book Gone with the Wind, namely, Piao by Chunhai Fan, Piao by Huairen Huang, translations by Google Translation and Baidu Translation. After processing the corpus with the software of Stanford Segmenter, Stanford Postagger, and AntConc, etc., the study analyzes linguistic data and answers the following questions: 1. How does the machine translation differ from manual translation linguistically? 2. Why do these deviances happen? This paper combines translation study with the knowledge of corpus linguistics, and concretes divergent linguistic dimensions in translated text analysis, in order to present linguistic deviances in manual and machine translation. Consequently, this study provides a more accurate and more fine-grained understanding of machine translation products, and it also proposes several suggestions for machine translation development in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corpus-based%20analysis" title="corpus-based analysis">corpus-based analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=linguistic%20deviances" title=" linguistic deviances"> linguistic deviances</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20translation" title=" machine translation"> machine translation</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20evidence" title=" statistical evidence"> statistical evidence</a> </p> <a href="https://publications.waset.org/abstracts/109650/statistical-comparison-of-machine-and-manual-translation-a-corpus-based-study-of-gone-with-the-wind" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109650.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">144</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">2800</span> Development of a Robot Assisted Centrifugal Casting Machine for Manufacturing Multi-Layer Journal Bearing and High-Tech Machine Components</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Syed%20Ali%20Molla">Mohammad Syed Ali Molla</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Azim"> Mohammed Azim</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Esharuzzaman"> Mohammad Esharuzzaman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Centrifugal-casting machine is used in manufacturing special machine components like multi-layer journal bearing used in all internal combustion engine, steam, gas turbine and air craft turboengine where isotropic properties and high precisions are desired. Moreover, this machine can be used in manufacturing thin wall hightech machine components like cylinder liners and piston rings of IC engine and other machine parts like sleeves, and bushes. Heavy-duty machine component like railway wheel can also be prepared by centrifugal casting. A lot of technological developments are required in casting process for production of good casted machine body and machine parts. Usually defects like blowholes, surface roughness, chilled surface etc. are found in sand casted machine parts. But these can be removed by centrifugal casting machine using rotating metallic die. Moreover, die rotation, its temperature control, and good pouring practice can contribute to the quality of casting because of the fact that the soundness of a casting in large part depends upon how the metal enters into the mold or dies and solidifies. Poor pouring practice leads to variety of casting defects such as temperature loss, low quality casting, excessive turbulence, over pouring etc. Besides these, handling of molten metal is very unsecured and dangerous for the workers. In order to get rid of all these problems, the need of an automatic pouring device arises. In this research work, a robot assisted pouring device and a centrifugal casting machine are designed, developed constructed and tested experimentally which are found to work satisfactorily. The robot assisted pouring device is further modified and developed for using it in actual metal casting process. Lot of settings and tests are required to control the system and ultimately it can be used in automation of centrifugal casting machine to produce high-tech machine parts with desired precision. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bearing" title="bearing">bearing</a>, <a href="https://publications.waset.org/abstracts/search?q=centrifugal%20casting" title=" centrifugal casting"> centrifugal casting</a>, <a href="https://publications.waset.org/abstracts/search?q=cylinder%20liners" title=" cylinder liners"> cylinder liners</a>, <a href="https://publications.waset.org/abstracts/search?q=robot" title=" robot"> robot</a> </p> <a href="https://publications.waset.org/abstracts/40197/development-of-a-robot-assisted-centrifugal-casting-machine-for-manufacturing-multi-layer-journal-bearing-and-high-tech-machine-components" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40197.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">414</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">2799</span> Knowledge Required for Avoiding Lexical Errors at Machine Translation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yukiko%20Sasaki%20Alam">Yukiko Sasaki Alam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research aims at finding out the causes that led to wrong lexical selections in machine translation (MT) rather than categorizing lexical errors, which has been a main practice in error analysis. By manually examining and analyzing lexical errors outputted by a MT system, it suggests what knowledge would help the system reduce lexical errors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20translation" title="machine translation">machine translation</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20analysis" title=" error analysis"> error analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=lexical%20errors" title=" lexical errors"> lexical errors</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation" title=" evaluation"> evaluation</a> </p> <a href="https://publications.waset.org/abstracts/63451/knowledge-required-for-avoiding-lexical-errors-at-machine-translation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63451.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">337</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">2798</span> Electroencephalogram Based Alzheimer Disease Classification using Machine and Deep Learning Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carlos%20Roncero-Parra">Carlos Roncero-Parra</a>, <a href="https://publications.waset.org/abstracts/search?q=Alfonso%20Parre%C3%B1o-Torres"> Alfonso Parreño-Torres</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorge%20Mateo%20Sotos"> Jorge Mateo Sotos</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandro%20L.%20Borja"> Alejandro L. Borja</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alzheimer" title="alzheimer">alzheimer</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=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a> </p> <a href="https://publications.waset.org/abstracts/165522/electroencephalogram-based-alzheimer-disease-classification-using-machine-and-deep-learning-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165522.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">126</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">2797</span> A Machine Learning Decision Support Framework for Industrial Engineering Purposes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anli%20Du%20Preez">Anli Du Preez</a>, <a href="https://publications.waset.org/abstracts/search?q=James%20Bekker"> James Bekker</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Data%20analytics" title="Data analytics">Data analytics</a>, <a href="https://publications.waset.org/abstracts/search?q=Industrial%20engineering" title=" Industrial engineering"> Industrial engineering</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=Value%20creation" title=" Value creation"> Value creation</a> </p> <a href="https://publications.waset.org/abstracts/116912/a-machine-learning-decision-support-framework-for-industrial-engineering-purposes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116912.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">168</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">2796</span> Evaluating the Implementation of Machine Learning Techniques in the South African Built Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peter%20Adekunle">Peter Adekunle</a>, <a href="https://publications.waset.org/abstracts/search?q=Clinton%20Aigbavboa"> Clinton Aigbavboa</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthew%20Ikuabe"> Matthew Ikuabe</a>, <a href="https://publications.waset.org/abstracts/search?q=Opeoluwa%20Akinradewo"> Opeoluwa Akinradewo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The future of machine learning (ML) in building may seem like a distant idea that will take decades to materialize, but it is actually far closer than previously believed. In reality, the built environment has been progressively increasing interest in machine learning. Although it could appear to be a very technical, impersonal approach, it can really make things more personable. Instead of eliminating humans out of the equation, machine learning allows people do their real work more efficiently. It is therefore vital to evaluate the factors influencing the implementation and challenges of implementing machine learning techniques in the South African built environment. The study's design was one of a survey. In South Africa, construction workers and professionals were given a total of one hundred fifty (150) questionnaires, of which one hundred and twenty-four (124) were returned and deemed eligible for study. Utilizing percentage, mean item scores, standard deviation, and Kruskal-Wallis, the collected data was analyzed. The results demonstrate that the top factors influencing the adoption of machine learning are knowledge level and a lack of understanding of its potential benefits. While lack of collaboration among stakeholders and lack of tools and services are the key hurdles to the deployment of machine learning within the South African built environment. The study came to the conclusion that ML adoption should be promoted in order to increase safety, productivity, and service quality within the built environment. <p class="card-text"><strong>Keywords:</strong> <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=implementation" title=" implementation"> implementation</a>, <a href="https://publications.waset.org/abstracts/search?q=built%20environment" title=" built environment"> built environment</a>, <a href="https://publications.waset.org/abstracts/search?q=construction%20stakeholders" title=" construction stakeholders"> construction stakeholders</a> </p> <a href="https://publications.waset.org/abstracts/157567/evaluating-the-implementation-of-machine-learning-techniques-in-the-south-african-built-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157567.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 class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2795</span> Instance Selection for MI-Support Vector Machines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amy%20M.%20Kwon">Amy M. Kwon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title="support vector machine">support vector machine</a>, <a href="https://publications.waset.org/abstracts/search?q=Margin" title=" Margin"> Margin</a>, <a href="https://publications.waset.org/abstracts/search?q=Hausdorff%20distance" title=" Hausdorff distance"> Hausdorff distance</a>, <a href="https://publications.waset.org/abstracts/search?q=representation%20selection" title=" representation selection"> representation selection</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple-instance%20learning" title=" multiple-instance learning"> multiple-instance learning</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/186528/instance-selection-for-mi-support-vector-machines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186528.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">34</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">2794</span> Fault Study and Reliability Analysis of Rotative Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guang%20Yang">Guang Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhiwei%20Bai"> Zhiwei Bai</a>, <a href="https://publications.waset.org/abstracts/search?q=Bo%20Sun"> Bo Sun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper analyzes the influence of failure mode and harmfulness of rotative machine according to FMECA (Failure Mode, Effects, and Criticality Analysis) method, and finds out the weak links that affect the reliability of this equipment. Also in this paper, fault tree analysis software is used for quantitative and qualitative analysis, pointing out the main factors of failure of this equipment. Based on the experimental results, this paper puts forward corresponding measures for prevention and improvement, and fundamentally improves the inherent reliability of this rotative machine, providing the basis for the formulation of technical conditions for the safe operation of industrial applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rotative%20machine" title="rotative machine">rotative machine</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20test" title=" reliability test"> reliability test</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20tree%20analysis" title=" fault tree analysis"> fault tree analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=FMECA" title=" FMECA"> FMECA</a> </p> <a href="https://publications.waset.org/abstracts/90886/fault-study-and-reliability-analysis-of-rotative-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90886.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">154</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">2793</span> Development of a French to Yorùbá Machine Translation System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benjamen%20Nathaniel">Benjamen Nathaniel</a>, <a href="https://publications.waset.org/abstracts/search?q=Eludiora%20Safiriyu%20Ijiyemi"> Eludiora Safiriyu Ijiyemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Egume%20Oneme%20Lucky"> Egume Oneme Lucky</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A review on machine translation systems shows that a lot of computational artefacts has been carried out to translate written or spoken texts from a source language to Yorùbá language through Machine Translation systems. However, there are no work on French to Yorùbá language machine translation system; hence, the study investigated the process involved in the translation of French-to-Yorùbá language equivalent with the view to adopting a rule- based MT approach to build a Machine Translation framework from simple sentences administered through questionnaire. Articles and relevant textbooks were reviewed with key speakers of both languages interviewed to find out the processes involved in the translation of French language and their equivalent in Yorùbálanguage simple sentences using home domain terminologies. Achieving this, a model was formulated using phrase grammar structure, re-write rule, parse tree, automata theory- based techniques, designed and implemented respectively with unified modeling language (UML) and python programming language. Analysing the result, it was observed when carrying out the result that, the Machine Translation system performed 18.45% above Experimental Subject Respondent and 2.7% below Linguistics Expert when analysed with word orthography, sentence syntax and semantic correctness of the sentences. And, when compared with Google Machine Translation system, it was noticed that the developed system performed better on lexicons of the target language. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20translation%20%28MT%29" title="machine translation (MT)">machine translation (MT)</a>, <a href="https://publications.waset.org/abstracts/search?q=rule-based" title=" rule-based"> rule-based</a>, <a href="https://publications.waset.org/abstracts/search?q=French%20language" title=" French language"> French language</a>, <a href="https://publications.waset.org/abstracts/search?q=Yoru%60ba%C2%B4%20language" title=" Yoru`ba´ language"> Yoru`ba´ language</a> </p> <a href="https://publications.waset.org/abstracts/181699/development-of-a-french-to-yoruba-machine-translation-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181699.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">77</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">2792</span> A Machine Learning Approach for the Leakage Classification in the Hydraulic Final Test</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christian%20Neunzig">Christian Neunzig</a>, <a href="https://publications.waset.org/abstracts/search?q=Simon%20Fahle"> Simon Fahle</a>, <a href="https://publications.waset.org/abstracts/search?q=J%C3%BCrgen%20Schulz"> Jürgen Schulz</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthias%20M%C3%B6ller"> Matthias Möller</a>, <a href="https://publications.waset.org/abstracts/search?q=Bernd%20Kuhlenk%C3%B6tter"> Bernd Kuhlenkötter</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces. <p class="card-text"><strong>Keywords:</strong> <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=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20quality" title=" predictive quality"> predictive quality</a>, <a href="https://publications.waset.org/abstracts/search?q=hydraulics" title=" hydraulics"> hydraulics</a>, <a href="https://publications.waset.org/abstracts/search?q=supervised%20learning" title=" supervised learning"> supervised learning</a> </p> <a href="https://publications.waset.org/abstracts/143537/a-machine-learning-approach-for-the-leakage-classification-in-the-hydraulic-final-test" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143537.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">213</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">2791</span> Estimation of Synchronous Machine Synchronizing and Damping Torque Coefficients </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20M.%20EL-Naggar">Khaled M. EL-Naggar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation" title=" estimation"> estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=synchronous" title=" synchronous"> synchronous</a>, <a href="https://publications.waset.org/abstracts/search?q=machine" title=" machine"> machine</a>, <a href="https://publications.waset.org/abstracts/search?q=crow%20search" title=" crow search"> crow search</a> </p> <a href="https://publications.waset.org/abstracts/110946/estimation-of-synchronous-machine-synchronizing-and-damping-torque-coefficients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110946.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">140</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">2790</span> Adjustment and Compensation Techniques for the Rotary Axes of Five-axis CNC Machine Tools</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tung-Hui%20Hsu">Tung-Hui Hsu</a>, <a href="https://publications.waset.org/abstracts/search?q=Wen-Yuh%20Jywe"> Wen-Yuh Jywe</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=calibration" title="calibration">calibration</a>, <a href="https://publications.waset.org/abstracts/search?q=compensation" title=" compensation"> compensation</a>, <a href="https://publications.waset.org/abstracts/search?q=rotary%20axis" title=" rotary axis"> rotary axis</a>, <a href="https://publications.waset.org/abstracts/search?q=five-axis%20computer%20numerical%20control%20%28CNC%29%20machine%20tools" title=" five-axis computer numerical control (CNC) machine tools"> five-axis computer numerical control (CNC) machine tools</a>, <a href="https://publications.waset.org/abstracts/search?q=eccentric%20error" title=" eccentric error"> eccentric error</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20calibration%20system" title=" optical calibration system"> optical calibration system</a>, <a href="https://publications.waset.org/abstracts/search?q=ISO%2FCD%2010791-6" title=" ISO/CD 10791-6"> ISO/CD 10791-6</a> </p> <a href="https://publications.waset.org/abstracts/4994/adjustment-and-compensation-techniques-for-the-rotary-axes-of-five-axis-cnc-machine-tools" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4994.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">383</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">2789</span> Feasibility Study of Wireless Communication for the Control and Monitoring of Rotating Electrical Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Ben%20Brahim">S. Ben Brahim</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20H.%20Vuong"> T. H. Vuong</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20David"> J. David</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Bouallegue"> R. Bouallegue</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Pietrzak-David"> M. Pietrzak-David</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electrical machine monitoring is important to protect motor from unexpected problems. Today, using wireless communication for electrical machines is interesting for both real time monitoring and diagnostic purposes. In this paper, we propose a system based on wireless communication IEEE 802.11 to control electrical machine. IEEE 802.11 standard is recommended for this type of applications because it provides a faster connection, better range from the base station, and better security. Therefore, our contribution is to study a new technique to control and monitor the rotating electrical machines (motors, generators) using wireless communication. The reliability of radio channel inside rotating electrical machine is also discussed. Then, the communication protocol, software and hardware design used for the proposed system are presented in detail and the experimental results of our system are illustrated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control" title="control">control</a>, <a href="https://publications.waset.org/abstracts/search?q=DFIM%20machine" title=" DFIM machine"> DFIM machine</a>, <a href="https://publications.waset.org/abstracts/search?q=electromagnetic%20field" title=" electromagnetic field"> electromagnetic field</a>, <a href="https://publications.waset.org/abstracts/search?q=EMC" title=" EMC"> EMC</a>, <a href="https://publications.waset.org/abstracts/search?q=IEEE%20802.11" title=" IEEE 802.11"> IEEE 802.11</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring" title=" monitoring"> monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=rotating%20electrical%20machines" title=" rotating electrical machines"> rotating electrical machines</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20communication" title=" wireless communication"> wireless communication</a> </p> <a href="https://publications.waset.org/abstracts/34526/feasibility-study-of-wireless-communication-for-the-control-and-monitoring-of-rotating-electrical-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34526.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">695</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">2788</span> Park’s Vector Approach to Detect an Inter Turn Stator Fault in a Doubly Fed Induction Machine by a Neural Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amel%20Ourici">Amel Ourici</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An electrical machine failure that is not identified in an initial stage may become catastrophic and it may suffer severe damage. Thus, undetected machine faults may cascade in it failure, which in turn may cause production shutdowns. Such shutdowns are costly in terms of lost production time, maintenance costs, and wasted raw materials. Doubly fed induction generators are used mainly for wind energy conversion in MW power plants. This paper presents a detection of an inter turn stator fault in a doubly fed induction machine whose stator and rotor are supplied by two pulse width modulation (PWM) inverters. The method used in this article to detect this fault, is based on Park’s Vector Approach, using a neural network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=doubly%20fed%20induction%20machine" title="doubly fed induction machine">doubly fed induction machine</a>, <a href="https://publications.waset.org/abstracts/search?q=PWM%20inverter" title=" PWM inverter"> PWM inverter</a>, <a href="https://publications.waset.org/abstracts/search?q=inter%20turn%20stator%20fault" title=" inter turn stator fault"> inter turn stator fault</a>, <a href="https://publications.waset.org/abstracts/search?q=Park%E2%80%99s%20vector%20approach" title=" Park’s vector approach"> Park’s vector 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/21491/parks-vector-approach-to-detect-an-inter-turn-stator-fault-in-a-doubly-fed-induction-machine-by-a-neural-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21491.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">608</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">2787</span> Using Machine Learning to Monitor the Condition of the Cutting Edge during Milling Hardened Steel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pawel%20Twardowski">Pawel Twardowski</a>, <a href="https://publications.waset.org/abstracts/search?q=Maciej%20Tabaszewski"> Maciej Tabaszewski</a>, <a href="https://publications.waset.org/abstracts/search?q=Jakub%20Czy%C5%BCycki"> Jakub Czyżycki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main goal of the work was to use machine learning to predict cutting-edge wear. The research was carried out while milling hardened steel with sintered carbide cutters at various cutting speeds. During the tests, cutting-edge wear was measured, and vibration acceleration signals were also measured. Appropriate measures were determined from the vibration signals and served as input data in the machine-learning process. Two approaches were used in this work. The first one involved a two-state classification of the cutting edge - suitable and unfit for further work. In the second approach, prediction of the cutting-edge state based on vibration signals was used. The obtained research results show that the appropriate use of machine learning algorithms gives excellent results related to monitoring cutting edge during the process. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=milling%20of%20hardened%20steel" title="milling of hardened steel">milling of hardened steel</a>, <a href="https://publications.waset.org/abstracts/search?q=tool%20wear" title=" tool wear"> tool wear</a>, <a href="https://publications.waset.org/abstracts/search?q=vibrations" title=" vibrations"> vibrations</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/185240/using-machine-learning-to-monitor-the-condition-of-the-cutting-edge-during-milling-hardened-steel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185240.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">59</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">2786</span> Evaluation of the Matching Optimization of Human-Machine Interface Matching in the Cab</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yanhua%20Ma">Yanhua Ma</a>, <a href="https://publications.waset.org/abstracts/search?q=Lu%20Zhai"> Lu Zhai</a>, <a href="https://publications.waset.org/abstracts/search?q=Xinchen%20Wang"> Xinchen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongyu%20Liang"> Hongyu Liang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytic%20hierarchy%20process" title="analytic hierarchy process">analytic hierarchy process</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20comprehension%20evaluation%20method" title=" fuzzy comprehension evaluation method"> fuzzy comprehension evaluation method</a>, <a href="https://publications.waset.org/abstracts/search?q=human-machine%20interface" title=" human-machine interface"> human-machine interface</a>, <a href="https://publications.waset.org/abstracts/search?q=matching%20optimization" title=" matching optimization"> matching optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20human%20factor%20analysis" title=" software human factor analysis"> software human factor analysis</a> </p> <a href="https://publications.waset.org/abstracts/131104/evaluation-of-the-matching-optimization-of-human-machine-interface-matching-in-the-cab" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131104.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">156</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=machine&page=1" rel="prev">&lsaquo;</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=machine&page=1">1</a></li> <li class="page-item active"><span class="page-link">2</span></li> <li class="page-item"><a class="page-link" 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