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2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2022

作者： Mathew, Joseph George, Sudhish N. Control and Instrumentation Group Centre for Development of Advanced Computing Thiruvananthapuram India National Institute of Technology Calicut Department of Electronics and Communication Engineering Kozhikode India

ISBN: (纸本)9781665449403

An infrared thermal imaging system can screen large groups of people quickly, non-intrusively and with a high level of confidence in spotting febrile subjects. A thermal imaging system must identify individuals with a body core temperature above 38°C to effectively do this. Conventionally, this is per-formed using thermal imaging cameras in the Long Wave Infra Red (LWIR) region. But the issue with most of these systems is that it fails to read the temperature at the inner eye canthi, which is the ideal location on the face for fever detection. This is owing to the lack of distinguishing features that are available on a thermal image. Hence, in this paper, an attempt is made to read the temperature at the inner eye canthus by first detecting the eye region by running the Viola - Jones Haar Cascade algorithm over the visible images, in a popular synchronized visible and thermal face dataset. Subsequently, this identified region of interest in the visible image is registered against its corresponding thermal image using the ORB algorithm to locate the eye canthus area on the thermal image. Experimental results analysed in this paper proves that a read out of the temperature at this pixel location can be a sufficiently accurate estimate of the core body temperature of the subject being screened. © 2022 IEEE.

关键词： Image registration

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Proposal of security architecture in 5G mobile network with DDoS attack detection 7

Proposal of security architecture in 5G mobile network with ...

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7th International Conference on Smart and Sustainable Technologies, SpliTech 2022

作者： Gojic, Jovan Radakovic, Danijel University of East Sarajevo Faculty of Transport and Traffic Engineering Doboj Bosnia and Herzegovina University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Novi Sad Serbia

ISBN: (纸本)9789532901160

Software-Defined Networking or SDN (Software-Defined Networking) is a technology for software control and management of the network in order to improve its properties. Unlike classic network management technologies, which are complex and decentralized, SDN technology is a much more flexible and simple system. The new architecture may be vulnerable to several attacks leading to resource depletion and preventing the SDN controller from providing support to legitimate users. One such attack is the Distributed Denial of Service (DDoS), which is on the rise today. We suggest Modified-DDoSNet, a system for detecting DDoS attacks in the SDN environment. A model based on Deep Learning (DL) techniques will be implemented, combining a Recurrent Neural Network (RNN) with an Autoencoder. The proposed model, which was first trained to detect attacks, was implemented in the security architecture of the SDN network, as a new component. The security architecture of the SDN network contains a total of 13 components, each of which represents an individual part of the architecture, where the first component is the RNN - autoencoder. The model itself, which is the first component, was trained in the CICDDoS2019 dataset. It has high reliability for attack detection, which increases the security of the SDN network architecture. © 2022 University of Split, FESB.

关键词： Recurrent neural networks

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Energy Aware Metaheuristic Optimization with Location Aided Routing Protocol for MANET

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Computers, Materials & Continua 2022年第4期71卷 1567-1580页

作者： E.Ahila Devi K.C.Ramya K.Sathesh Kumar Sultan Ahmad Seifedine Kadry Hyung Ju Park Byeong-Gwon Kang Department of Instrumentation and Control Engineering St.Joseph’s College of EngineeringChennai600119India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India School of Computing Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Applied Data Science Noroff University CollegeKristiansand4612Norway Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

A mobile ad hoc network(MANET)involves a group of wireless mobile nodes which create an impermanent network with no central authority and *** nodes in the MANET are highly mobile and it results in adequate network topology,link loss,and increase the re-initialization of the route discovery *** planning in MANET is a multi-hop communication process due to the restricted transmission range of the *** aided routing(LAR)is one of the effective routing protocols in MANET which suffers from the issue of high energy *** few research works have focused on resolving energy consumption problem in LAR,energy efficiency still remains a major design *** this aspect,this study introduces an energy aware metaheuristic optimization with LAR(EAMO-LAR)protocol for *** EAMO-LAR protocol makes use of manta ray foraging optimization algorithm(MRFO)to help the searching process for the individual solution to be passed to the LAR *** fitness value of the created solutions is determined next to pass the solutions to the objective *** MRFO algorithm is incorporated into the LAR protocol in the EAMO-LAR protocol to reduce the desired energy *** ensure the improved routing efficiency of the proposed EAMO-LAR protocol,a series of simulations take *** resultant experimental values pointed out the supreme outcome of the EAMO-LAR protocol over the recently compared *** resultant values demonstrated that the EAMO-LAR protocol has accomplished effectual results over the other existing techniques.

关键词： MANET routing lar protocol energy efficiency mrfo algorithm metaheuristics

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Adaptive Neuro Fuzzy Inference Systems Based Maximum Power Point Tracking for a Photovoltaic System Connected to a Grid 3rd

Adaptive Neuro Fuzzy Inference Systems Based Maximum Power P...

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3rd International Conference on control, Instrumentation and Mechatronics engineering, CIM 2022

作者： Mohammed, Karam Khairullah Buyamin, Salinda Mekhilef, Saad Rosmin, Norzanah Shamsudin, Mohamad Amir Control and Mechatronics Engineering Department School of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru81310 Malaysia School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia

ISBN: (纸本)9789811939228

This paper presented an adaptive neuro fuzzy inference system (ANFIS) for photovoltaic (PV) connected to the grid system for fast and precise maximum power point tracking (MPPT) in various weather conditions. Due to the high cost of sensors and the inaccuracy of irradiance readings, this study suggested an ANFIS approach for tracking maximum power without irradiance and voltage sensors. Instead, it relied on an equation to estimate the irradiance value. The generated power by PV is converted to the grid via a voltage source converter (VSC). MATLAB/SIMULINK has been used to simulate the proposed controller. As per simulation results, the proposed method was shown to be effective in all of the tested cases. A comparison with particle swarm optimization algorithm (PSO) and Perturb and Observe (P&O) has been provided to assess the efficacy of the proposed method. The results demonstrated the efficacy of the proposed technique by providing a rapid and precise tracking in 0.02 s with high efficiency. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy systems

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Evaluation of Ethernet Subsystem for Domain controller in Autonomous Vehicles

Evaluation of Ethernet Subsystem for Domain Controller in Au...

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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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