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25 articles for “Simulation Training”

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Research ArticleOpen accessIn the abstractAdaptive Controllers for Permanent Magnet Brushless DC Motor Drive System using Adaptive-Network-based Fuzzy Interference SystemV.M. Varatharaju, Badrilal Mathur, UdhayakumarProblem statement: The tuning methodology for the parameters of adaptive speed controller causes a transient deviation of the response from the set reference following variation in load torque in a permanent-magnet brushless DC (BLDC) motor drive system. Approach: This study develops a mathematical model of the BLDC drive system, firstly. Secondly, discusses a design of the closed loop drive system … …American Journal of Applied Sciences, Vol. 8, Issue 8 · 19 Jul 2011 · 6,941 accessesView PDFCite
Research ArticleOpen accessIn the abstractUtilizing of Big Data and Predictive Analytics Capability in Crisis ManagementMohammad Atwah AL-Ma’aitahThis study investigates the impact of Big Data and Predictive Analytics (BDPA) capability on crisis management in the Greater Amman Municipality (GAM), Jordan. Effective utilization of BDPA is considered in the study to depend upon the five dimensions: Tangible resources, technical skills, management skills, organizational learning and data driven culture. Crisis management is classified into the three stages of crisis … …Journal of Computer Science, Vol. 16, Issue 3 · 9 Mar 2020 · 7,862 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy Method for Online Learning of Bayesian Network ParametersMariana D.C. Lima, Silvia M. NassarIn learning problems, there are situations where training data is not fully available at the learning time. They are incrementally generated by time, defining a type of domain called online that has among its characteristics the possibility of data failure or even missing data. In Bayesian networks, learning is divided into two categories: structure (related to the graph of conditional … …Journal of Computer Science, Vol. 15, Issue 3 · 16 Mar 2019 · 7,498 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,755 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Soft Sensor Modelling of Biomass Concentration during Fermentation using Accurate Incremental Online v-Support Vector Regression Learning AlgorithmBinjie Gu, Feng PanIn order to model real fermentation process, a soft sensor modelling of biomass concentration during fermentation using accurate incremental online ν-Support Vector Regression (ν-SVR) learning algorithm was proposed. Firstly, an accurate incremental online ν-SVR learning algorithm was proposed. This algorithm solved the two complications introduced in the dual problem based on the equivalent formulation of ν-SVR. Moreover, it addressed the … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 8 Aug 2015 · 7,327 accessesView PDFCite
Research ArticleOpen accessIn the abstract3-DIMENSIONAL EAR RECOGNITION BASED ITERATIVE CLOSEST POINT WITH STOCHASTIC CLUSTERING MATCHINGKhamiss Masaoud S. Algabary, Khairuddin Omar, Md Jan NordinEar recognition is a new technology and future trend for personal identification. However, the false detection rate and matching recognition are very challenging due to the ear complex geometry. The Scope of the study is to introduced a combination of Iterative Closest Point (ICP) and Stochastic Clustering Matching (SCM) algorithm for 3D ears matching based on biometrics field with a … …Journal of Computer Science, Vol. 10, Issue 3 · 29 Nov 2013 · 6,812 accessesView PDFCite
Research ArticleOpen accessIn the abstractPreventing Injuries Via Innovative Investigations: Reviewing Dangerous Driving Research MethodsChris S. Dula, Russell Fox, Ashley Dickson et al.Dangerous driving behavior is particularly difficult to study for many reasons. Researchers must be creative to capture meaningful data, but innovative techniques often meet with problems that might be solved through the broader use by others. The researchers generally lack a central location from which to review and choose from past methods. This article reviews the techniques used to study … …Current Research in Psychology, Vol. 3, Issue 1 · 16 Jul 2012 · 7,283 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing an Adaptative Fuzzy-Logic System to Optimize the Performances and the Reduction of Chattering Phenomenon in the Control of Induction MotorM. M. Krishan, L. Barazane, A. KhwaldehProblem statement: Neural networks and fuzzy inference systems are becoming well-recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance. Also, by combining these two features, more versatile and robust models, called “neuro-fuzzy” architectures have been developed. The mo Approach: Motivation behind the use of neuro-fuzzy approaches was based on … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,523 accessesView PDFCite
Research ArticleOpen accessIn the abstractWeighted Semi-Blind Channel Identification by Cross Relation MethodMohamed Tahar Taba, S. FemmamProblem statement: The bandwidth efficiency of many communication systems could be improved if the transmission channel was estimated blindly without resort to training sequences. GMSK was a spectrum-efficient modulation scheme and it was adopted as the modulation standard of GSM systems. Approach: However, because of its phase modulation, Gaussian filtering and partial response signalling properties, Results: The simulation results showed … …American Journal of Applied Sciences, Vol. 6, Issue 6 · 30 Jun 2009 · 6,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractElectricity Load Forecasting based on Framelet Neural Network TechniqueMohammed K. AbdLoad forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This study shows Electricity Load Forecasting modeling based on Framelet Neural Network Technique (FNN) for Baghdad City. Framelet technique is implemented to the time series data, decomposing the data into number of Framelet coefficient signals. The decomposed signals … …American Journal of Applied Sciences, Vol. 6, Issue 5 · 31 May 2009 · 8,274 accessesView PDFCite