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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Kenjic, Dusan Antic, Marija Bjelica, Milan University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia

ISBN: (纸本)9781665404174

The expansion of the automotive industry is reflected in the expansion of functionalities and services offered by a modern vehicle. In order for all of them to be executed, it is also necessary to increase the number of physical components within the vehicle. As the entire system grows, so does the problem of connecting the entities within it. The efficient simplification of the system is achieved by introducing domain controllers, and separating the physical components based on the functionality they perform, while creating the backbone communication network between domain controllers. Time-critical and other performance requirements, which are driven by the development of autonomous driving, demand the utilization of new standards and solutions for this communication network backbone. One of those solutions is Automotive Ethernet. In this paper, an implementation of the Ethernet subsystem of the domain controller for autonomous vehicles will be presented and evaluated. © 2021 IEEE.

关键词： Automotive industry

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control Strategy based on Frequency Response for a Single-Phase Full- Bridge Series Active Filter 16

Control Strategy based on Frequency Response for a Single-Ph...

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16th Brazilian Power Electronics Conference, COBEP 2021

作者： Curi Busarello, Tiago Davi Automation and Computing Engineering Federal University of Santa Catarina Department of Control Blumenau Brazil

ISBN: (纸本)9781665421294

Series active filters are a mature technology and well covered in the literature. However, they are usually designed for three-phase systems employing control strategies in dq-rotating reference frame. As a result, proportional-integrator controllers are used. However, they are not suited when the system has abnormal conditions. Moreover, with the high penetration of distribution generators, single-phase distribution voltage is being deteriorated. This paper presents a control strategy based on frequency response for a single-phase full bridge series active filter. The series active filter is controlled in voltage mode through a digital lead-lag controller. The controller parameters are obtained by frequency response technique using the k-factor methodology and later discretized via Backward-Euler approximation. The series active filter is tested in a system with nonlinear loads, distortions at the distribution voltage and under disturbance at the DC-link. The proposal was verified under simulation results and under Hardware-in-Loop Typhoon HIL402 with external microcontroller TMS320F28335. Results showed the effectiveness of the proposed control strategy. © 2021 IEEE.

关键词： Active filters

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Exploiting Machine Learning and LSTM for Human Activity Recognition: Using Physiological and Biological Sensor Data from Actigraph

Exploiting Machine Learning and LSTM for Human Activity Reco...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Matthew Oyeleye Tianhua Chen Pan Su Grigoris Antoniou Department of Computer Science School of Computing and Engineering University of Huddersfield UK School of Control and Computer Engineering North China Electric Power University China

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Human activity recognition involves identifying the daily living activities of an individual through the utilization of sensor attributes and intelligent learning algorithms. The identification of intricate human activities proves to be a labo-rious task, given the inherent difficulty of capturing long-term dependencies and extracting efficient features from unprocessed sensor data. For this purpose, this study aims at recognizing and classifying human activities using physiological and biological sensor data generated by Actigraph, as they can accurately measure moderate-to-vigorous intensity physical which is mostly affected by body composition and also better suited for self-monitoring. We examined the effectiveness of these features by applying prevalent machine learning classifiers and long short-term memory (LSTM) networks on recently publicly available data, which includes accelerometer and heart rate recordings. The results from our experiments showed that LSTM models performed better than conventional ML classifiers with the best result achieving an accuracy of 86.5%. The findings also confirms the significance of the heart rate in accurately classifying and identification of human activity more.

关键词： Heart rate Machine learning Feature extraction Recording Human activity recognition Biosensors Biomedical monitoring

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Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

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Computer Systems Science & engineering 2023年第5期45卷 1469-1482页

作者： Doaa Sami Khafaga Amel Ali Alhussan Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mohamed Saber El-Sayed M.El-kenawy Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electronics and Communications Engineering Department Faculty of EngineeringDelta University for Science and TechnologyMansouraEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Arrhythmia has been classified using a variety of *** of the dynamic nature of electrocardiogram(ECG)data,traditional handcrafted approaches are difficult to execute,making the machine learning(ML)solutions more *** with cardiac arrhythmias can benefit from competent monitoring to save their *** arrhythmia classification and prediction have greatly improved in recent *** are a category of conditions in which the heart's electrical activity is abnormally rapid or *** year,it is one of the main reasons of mortality for both men and women,*** the classification of arrhythmias,this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors(KNN)*** proposed method makes advantage of the UCI repository,which has a 279-attribute high-dimensional cardiac arrhythmia *** proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s *** purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia *** method of comprehensive arrhythmia classification outperforms earlier methods presented in the *** achieved classification accuracy using the proposed approach is 99.8%.

关键词： Feature selection electrocardiogram metaheuristics dipper throated algorithm

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Fatigue Load Prediction of Large Wind Turbine by Big Data and Deep Learning

Fatigue Load Prediction of Large Wind Turbine by Big Data an...

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2023 IEEE International Conference on Electrical, Automation and Computer engineering, ICEACE 2023

作者： Wu, Jiayue Yang, Qinmin Jin, Nanlin Xxi'An Jiaotong-Liverpool University Low Carbon Electrical Power and Energy Technology Suzhou China College of Control Science and Engineering Zhejiang University Hangzhou China Xi'An Jiaotong-Liverpool University Department of Computing Suzhou China

ISBN: (纸本)9798350309614

This paper introduces a fatigue load prediction framework for the nacelle of wind turbines utilizing operational data sourced from the supervisory control and data acquisition (SCADA) system of a Wind Farm. The primary objective revolves around achieving precise fatigue load predictions for the nacelle, forecasting 15 minutes in advance. Firstly, a series of data preprocessing steps were implemented on the wind turbine data procured from the SCADA system to enhance the model's generalization capability and robustness, including 3-Sigma outlier detection, sample point selection, as well as filtering and de-noising techniques. Then, the gate recurrent unit (GRU) was tuned and trained as the optimal model for long time-series forecasting of SCADA parameter channels. Subsequently, the support vector regression (SVR) model, refined with grid search methodology, was employed to establish the intricate relationship between SCADA parameters and fatigue loads. Finally, the predicted SCADA parameter values were fed into the optimized SVR model to derive fatigue load prediction results for wind turbines. Experimental results indicated that the proposed model framework can effectively predict fatigue loads on the nacelle of wind turbines utilizing the SCADA data in real scenarios. © 2023 IEEE.

关键词： GRU SCADA system.fatigue loads SVR wind turbine

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Bitroute SOME/IP: Implementation of a Scalable and Service Oriented Communication Middleware 45

Bitroute SOME/IP: Implementation of a Scalable and Service O...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Vujanic, M. Trifunovic, N. Kastelan, I. Kovacevic, B. University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9789532331035

SOME/IP is a communication protocol introduced in automotive industry to enable Service Oriented Architecture which is not possible using traditional automotive protocols such as CAN or FlexRay. A trend emerging in the last years in the Advanced Driver Assistance Systems (ADAS) is that SOME/IP became one of main communication protocols used for communication between safety and performance ECU devices. Currently in the market, including the open-source solutions, there is a set of different SOME/IP implementations that have different audience and combination of characteristics like high royalty costs, available feature set and software solution maturity. This paper presents the Bitroute SOME/IP, a new implementation of the SOME/IP communication protocol with focus on performance and deployment platform independency and compares it with the open-source solution from The Connected Vehicle Systems Alliance (COVESA). © 2022 Croatian Society MIPRO.

关键词： Automotive industry

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An approach towards Model-To-Model Mapping between AUTOSAR and Android systems 45

An approach towards Model-To-Model Mapping between AUTOSAR a...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Zlatkovic, Radomir Cabrilo, Vuk Antic, Marija Kovacevic, Branimir University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9789532331035

Every new generation of modern vehicles aims to provide the customers with a higher level of comfort and entertainment services. Consequently, the burden is placed upon the manufacturers to incorporate ever more complex electronic systems in their products and introduce service-based technologies. To meet these demands, service-oriented architecture (SOA) has become an integral part of the Adaptive AUTOSAR as the industry standard. Also, mobile services and applications are natively supported in the new in-vehicle infotainment systems (IVI) which usually run on the Android operating system. As these fundamentally different technologies are incorporated in the vehicles, the developers are facing the challenge of connecting them and exchanging information between the services running in different domains. Service-oriented architectures usually rely on a model-driven engineering approach to facilitate the development of the applications. However, as the complexity of the system grows, the mapping of various metamodels becomes a challenge, as no single standard is used across all domains in the vehicle. This paper provides a possible solution for mapping the already existing AUTOSAR metamodel to an Android Interface Definition Language (AIDL) metamodel. By applying the proposed mapping, it is possible to build applications that require the cooperation of various domains within the vehicle. © 2022 Croatian Society MIPRO.

关键词： Mapping

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Facial Expression Recognition Model Depending on Optimized Support Vector Machine

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Computers, Materials & Continua 2023年第7期76卷 499-515页

作者： Amel Ali Alhussan Fatma M.Talaat El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Mona Alnaggar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Machine Learning&Information Retrieval Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Robotics and Intelligent Machines Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt

In computer vision,emotion recognition using facial expression images is considered an important research *** learning advances in recent years have aided in attaining improved results in this *** to recent studies,multiple facial expressions may be included in facial photographs representing a particular type of *** is feasible and useful to convert face photos into collections of visual words and carry out global expression *** main contribution of this paper is to propose a facial expression recognitionmodel(FERM)depending on an optimized Support Vector Machine(SVM).To test the performance of the proposed model(FERM),AffectNet is *** uses 1250 emotion-related keywords in six different languages to search three major search engines and get over 1,000,000 facial photos *** FERM is composed of three main phases:(i)the Data preparation phase,(ii)Applying grid search for optimization,and(iii)the categorization *** discriminant analysis(LDA)is used to categorize the data into eight labels(neutral,happy,sad,surprised,fear,disgust,angry,and contempt).Due to using LDA,the performance of categorization via SVM has been obviously *** search is used to find the optimal values for hyperparameters of SVM(C and gamma).The proposed optimized SVM algorithm has achieved an accuracy of 99%and a 98%F1 score.

关键词： Facial expression recognition machine learning linear dis-criminant analysis(LDA) support vector machine(SVM) grid search

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3D Printed Capacitive Displacement/Force Sensor with Different Patterns of Dielectric Layer 30

3D Printed Capacitive Displacement/Force Sensor with Differe...

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30th Telecommunications Forum, TELFOR 2022

作者： Suvara, Dragana Vajda, Kristina Katanic, Miroslav Kisic, Milica Damnjanovic, Mirjana Babkovic, Kalman Faculty of Technical Sciences University of Novi Sad Department of Computing and Control Engineering Novi Sad Serbia Faculty of Technical Sciences University of Novi Sad Department of Power Electronic and Telecommunication Engineering Novi Sad Serbia

ISBN: (数字)9781665472739

ISBN: (纸本)9781665472739

In this paper a simple capacitive sensor for displacement/force measuring is presented. Additive 3D printing technology was used to make the sensor housing and electrodes, while silicone rubber was used for the dielectric layer to ensure good sensitivity to the applied force. Three different patterns of dielectric layers were investigated. During experimental measurements, a change in capacitance was observed depending on the performed displacement in the range of 0.5 mm with 0.1 mm increments. The measured capacitance values and characteristics for all three types of sensors were compared. © 2022 IEEE.

关键词： Capacitive sensors

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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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Computer Systems Science & engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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