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66th International Symposium ELMAR, ELMAR 2024

作者： Benja, Borna Mijic, David Vranjes, Mario Grbic, Ratko TTTech Auto Central and Eastern Europe Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Osijek Croatia

ISBN: (纸本)9798350375411

The majority of traffic accidents are caused by human error. To counteract that, Advanced Driver-Assistance Systems (ADAS) are being developed and installed in vehicles. One of those systems is the Lane Keeping Assist System (LKAS), which helps to keep the vehicle centered in the corresponding lane. The problem of calculating a steering angle that is to be applied to the steering wheel to keep the vehicle in the corresponding lane is called steering angle prediction (SAP). In this paper, a novel SAP neural network (NN) architecture is presented. It is based on Shifted Windows (Swin) Transformer architecture and uses an image from the vehicle's front-view camera to predict the steering angle. Two new datasets for the training and testing of the NN were created. The datasets consist of the vehicle's front-view camera images and the corresponding steering wheel angles from two different autonomous driving simulators, CARLA and MetaDrive. A variety of weather and road conditions are present in the datasets, including clear, rainy, and cloudy weather and two-, four-, and six-lane roads with various road markings (white and yellow, solid and dashed lines). The presented SAP solution has shown promising results on created test sets and in simulated test environments. © 2024 IEEE.

关键词： Advanced driver assistance systems

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Comparative Study of Single-Input and Dual-Input PSS in Multi-machine System 32nd

Comparative Study of Single-Input and Dual-Input PSS in Mult...

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Košorog, Tomislav Mehmedović, Muharem Marić, Predrag Kljajić, Ružica Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2B Osijek Croatia

ISBN: (纸本)9783031514937

To meet growing demand for electricity, power systems are operating near their operating limits. Due to technical limitations, the transmission lines are close to their transmission capacity and with different dynamic characteristics interaction can occur between the parts of a single power system or between interconnected power systems. Such interactions can result in low-frequency oscillations that further limit the transmission capacity of the system. Low-frequency oscillations can be reduced by increasing the damping torque of the synchronous generators. The most efficient way to increase damping torque is to implement power system stabilizers in the generator excitation circuit. In this paper, single-input and dual-input PSS are implemented in IEEE 14-Bus test system and their influence on the small-signal stability is compared. PSS location is determined by participation analysis, while tuning of the PSS is performed using the pole placement method. For the different tuning parameters, the system performance was analyzed in both time-domain and S-domain for single-input and dual-input PSSs implementations. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electric power system interconnection

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Opening Doors and Drawers by a UR5 Robot with Force Control 1

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Dukić, Jana Vulić, Lukrecia Šimundić, Valentin Pejić, Petra Cupec, Robert Faculty of Electrical Engineering Computer Science and Information Technology Osijek J. J. Strossmayer University of Osijek Osijek Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

Robots capable of automatically opening and closing articulated objects such as doors and drawers have broad potential applications in households, healthcare facilities, and industrial environments. Drawers can be opened and closed by pulling or pushing along the axis of translation, while doors can be opened by rotating around the axis of rotation. When a robot’s motion path deviates from the ideal trajectory required for opening and closing, its action can cause various damages due to excessive lateral forces. In this paper, we address the problem of force control in robotic manipulation of doors and drawers. The goal of force control is to minimize lateral forces when opening and closing doors and drawers. At the same time, position control is performed in the direction of the ideal trajectory. A force-torque sensor attached to a robot can monitor all forces in 3D space. We conduct experiments on opening and closing the doors and drawers using a UR5 robot with and without force control, and analyze the force response while monitoring the success of the actions performed. With this study, we provide insight into the usefulness of force control in opening and closing doors and drawers by a robot. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Trajectories

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COVID-19 Classification from X-Ray Images:An Approach to Implement Federated Learning on Decentralized Dataset

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computers, Materials & Continua 2023年第5期75卷 3883-3901页

作者： Ali Akbar Siddique S.M.Umar Talha M.Aamir Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Department of Telecommunication Engineering Sir Syed University of Engineering&TechnologyKarachi75300Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The COVID-19 pandemic has devastated our daily lives,leaving horrific repercussions in its *** to its rapid spread,it was quite difficult for medical personnel to diagnose it in such a big *** who test positive for Covid-19 are diagnosed via a nasal PCR *** comparison,polymerase chain reaction(PCR)findings take a few hours to a few *** PCR test is expensive,although the government may bear expenses in certain ***,subsets of the population resist invasive testing like ***,chest X-rays or computerized Vomography(CT)scans are preferred in most cases,and more importantly,they are non-invasive,inexpensive,and provide a faster response *** advances in Artificial Intelligence(AI),in combination with state-of-the-art methods,have allowed for the diagnosis of COVID-19 using chest *** article proposes a method for classifying COVID-19 as positive or negative on a decentralized dataset that is based on the Federated learning *** order to build a progressive global COVID-19 classification model,two edge devices are employed to train the model on their respective localized dataset,and a 3-layered custom Convolutional Neural Network(CNN)model is used in the process of training the model,which can be deployed from the *** two edge devices then communicate their learned parameter and weight to the server,where it aggregates and updates the *** proposed model is trained using an image dataset that can be found on *** are more than 13,000 X-ray images in Kaggle Database collection,from that collection 9000 images of Normal and COVID-19 positive images are *** edge node possesses a different number of images;edge node 1 has 3200 images,while edge node 2 has *** is no association between the datasets of the various nodes that are included in the *** doing it in this manner,each of the nodes will have access to a separate image collection that has no correl

关键词： Artificial intelligence deep learning federated learning COVID-19 decentralized image dataset

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Performance Analysis of the Machine Learning Algorithms for the Early Detection of Breast Carcinoma 2

Performance Analysis of the Machine Learning Algorithms for ...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Vanitha, K. Karpagavalli, S.M. Mahesh, T.R. Ali, A. Althaf Sridhar, T. Anitha, K. Faculty of Engineering Department of Computer Science and Engineering Coimbatore India Al Ameen Engineering College Department of Computer Science and Engg Tamilnadu Erode India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India Madanapalle Institute of Technology & Science Department of Computer Applications Andhra Pradesh India Alliance University Alliance College of Engineering and Design Bangalore India Csi College of Engineering Department of Information Technology Tamilnadu Ooty India

ISBN: (纸本)9798350360523

Breast Carcinoma, generally known as breast cancer, primarily affects women, though men can develop it as well. Because of the existence of breast tissue and exposure to female hormones, notably oestrogen, women are at a higher risk It's critical to diagnose breast tumors early. Several techniques based on machine learning (ML were used in this study to classify breast cancer using a dataset that was made available to the public. F-score, recall, precision, preciseness, and other performance metrics were used to evaluate these ML algorithms. Previous research and experimental findings indicate that Random Forest achieved the highest accuracy, with a remarkable accuracy rate of 99.12%. © 2024 IEEE.

关键词： Hormones

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The Importance of Including Sustainable Development Goals (SDGs) in the Educational Process of Engineers and Electrical Engineers 65

The Importance of Including Sustainable Development Goals (S...

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65th IEEE Annual International Scientific Conference on Power and Electrical engineering of Riga Technical University, RTUCON 2024

作者： Patlins, Antons Institute of Industrial Electronics Electrical Engineering and Energy Riga Technical University Faculty of Computer Science Information Technology and Energy Riga Latvia

ISBN: (纸本)9798350365771

The integration of Sustainable Development Goals (SDGs) into the educational process of engineers and electrical engineers is pivotal for fostering a sustainable future. This paper discusses the significance of embedding SDGs in engineering education and presents methodologies for incorporating these goals into various study subjects. The study explores current trends, proposes innovative pedagogical approaches, and provides practical recommendations for educators and institutions. The outcomes suggest that incorporating SDGs not only enhances the relevance of engineering education but also equips future engineers with the necessary skills and mindset to address global sustainability challenges. © 2024 IEEE.

关键词： Sustainable development goals

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An Intelligent Optimization Technique Of Automatic Speech Recognition For Smart Homes 13

An Intelligent Optimization Technique Of Automatic Speech Re...

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13th International Conference on Research in ComputIng at Feminine, RIF 2024

作者： Aly, Rabab Hamed M. Hussein, Aziza I. The Higher Institute for Management and Information Technology Minya Egypt Electrical and Computer Engineering Department College of Engineering Effat University Jeddah Saudi Arabia Computer Science Department Faculty of Computer Science Nahda University Beni Suef Egypt

The creation of new approaches to the design and configuration of smart buildings relies heavily on AI tools and Machine Learning (ML) algorithms, particularly optimization techniques. The widespread use of electronic devices has sparked a strong desire to incorporate the Internet of Things (IoT) into houses, leading to the development of smart homes. As networked gadgets proliferate rapidly, this phenomenon is characterized by rapid proliferation. In smart buildings, smart cities, smart grids, and smart homes, interconnected electronic devices are becoming more popular. The objective of this paper is to enhance the functionality of home automation systems through the performance of speech recognition using the Bat-Salp Swarm Optimization (BSSO). This paper investigates the notion of (BSSO), a data analysis methodology that facilitates the automated construction of analytical models. The implementation of BSSO provides an enhancement to the feature selection process in speech recognition, providing an approximation solution that improves the accuracy of system decisions. The use of the BSSO technique improves the precision of the voice recognition system and also incorporates an Artificial Neural Network (ANN) for the classification part. The findings substantiated the efficacy of the employed methodology. © 2024 Copyright for this paper by its authors.

关键词： Bat Optimization Algorithm Salp Optimization Algorithm Smart homes Speech recognition

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A Mathematical Model for Analyzing Honeynets and Their Cyber Deception Techniques 27

A Mathematical Model for Analyzing Honeynets and Their Cyber...

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27th International Conference on engineering of Complex computer Systems, ICECCS 2023

作者： Javadpour, Amir Ja'fari, Forough Taleb, Tarik Benzaid, Chafika University of Oulu Faculty of Information Technology and Electrical Engineering Oulu90570 Finland Sharif University of Technology Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350340044

As a way of obtaining useful information about the adversaries behavior with a low rate of false detection, honeypots have made significant advancements in the field of cybersecurity. They are also powerful in wasting the adversaries resources and attracting their attention from other critical assets in the network. A deceptive network with multiple honeypots is called a honeynet. The honeypots in a honeynet aim to cooperate in order to increase their deception power. Professional adversaries utilize strong detection mechanisms to discover the existence of the honeypots in a network. When an adversary finds that a deception mechanism is deployed, it may change their behavior and cause malicious effects on the network. Therefore, a honeynet has to be deceptive enough in order not to be identified. This paper aims to review the techniques that are designed for the honeynets to make them improve their deception performance. The recent related surveys do not focus on the honeynet-specific techniques, and also have no comparison analysis. The main presented techniques in this paper are fully investigated through comparative analysis and simulation scenarios. Some suggestions on the research gap are also provided. The results of this paper can be used by the honeynet developers and researchers to improve their work. © 2023 IEEE.

关键词： Cybersecurity

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Comparative Analysis and Evaluation of Well-being Activity-Infused Fine-Tuned Language Models with Benchmark Models

Comparative Analysis and Evaluation of Well-being Activity-I...

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2025 IEEE Symposium on Computational Intelligence in Health and Medicine, CIHM 2025

作者： Mohammed, Hamza Haruna Kiss, Gabriel Serrano, J. Artur Lindseth, Frank Department of Computer Science Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway Department of Neuromedicine and Movement Science Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9798331508333

Large language models (LLMs) have significantly impacted natural language processing (NLP), healthcare, and beyond fields. LLMs have demonstrated unprecedented abilities to understand and generate human-like text, making them highly valuable for various tasks, including information retrieval, question-answering, and conversational AI. However, as these models are integrated into real-world applications, especially in sensitive domains such as healthcare, it becomes essential to evaluate their performance comprehensively. We present a process for fine-tuning LLMs to incorporate cardiac exercise and corpus of well-being activity, aiming to promote activity health support through NLP-driven applications. Using QLoRA, you can ensure that the model size remains small and reduce overhead while maintaining the high performance of the fine-tuned model. Subsequently, this paper presents a comparative analysis benchmark pipeline to evaluate fine-tuned models with base models on standard benchmark datasets from the healthcare domain. The aim is to evaluate the performance, robustness and accuracy of these models, showing that the fine-tuning process does not degrade the model performance, but improves the performance to some extent in some benchmarks. © 2025 IEEE.

关键词： Nutrition

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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries

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Frontiers of computer Science 2024年第5期18卷 1-10页

作者： Lingling ZHAO Shitao SONG Pengyan WANG Chunyu WANG Junjie WANG Maozu GUO Faculty of Computing Harbin Institute of TechnologyHarbin 150001China School of Electrical Engineering Liaoning University of TechnologyJinzhou 121004China School of Computer Science Northeast Electric Power UniversityJilin 132000China Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China

Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series ***,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be *** address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL *** MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level ***,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL *** experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation *** code and dataset are available at the website of github.

关键词： lithium-ion battery remaining useful life deep learning MLP-Mixer mixture-of-experts

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