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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Liu, Shiyang Luo, Jing Zeng, Chao Lei, Ting Yang, Chenguang School of Automation Wuhan University of Technology Wuhan430070 China University of Hamburg Department of Informatics Hamburg22527 Germany School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan430070 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798350300178

Supernumerary robotic limb (SRL) is an intelligent platform for providing assistance to humans at extreme conditions in natural human-robot collaboration (HRC) tasks. However, it is still difficult to control the SRL by using a simple way and to eliminate the cognitive burden placed on the human operator. of the human operator. Learning that the burden on human operators can be reduced by using Learning from Demonstrations (LfD) which learns repetitive teleoperation tasks. Our study introduces a method for teaching SRL that utilizes Dynamic Time Warping in combination with Gaussian Mixture Model and Gaussian Mixture Regression. The proposed mechanism utilizes a DTW algorithm to align and compare motion patterns between the human teacher and the SRL. Then, the GMM algorithm was applied to encode the motion patterns into statistical models. Additionally, these models are used to reate a task model that is applicable in a broad range of situations through the GMR method, which can be utilized to regulate the motion of SRL in real-time. The proposed mechanism is tested in experiments, and the results show that the SRL can accurately replicate the motion patterns with an average error of less than 10% for the HRC tasks. The proposed teaching mechanism has potential applications in fields such as rehabilitation and industrial automation, where the use of SRL can strengthen human capabilities and improve task efficiency. © 2023 IEEE.

关键词： Intelligent robots

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Comparison of Mechanical Properties of PLA-Based Biocomposites Filled with Different Agricultural By-Products 7

Comparison of Mechanical Properties of PLA-Based Biocomposit...

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7th International Conference on Material Strength and Applied Mechanics, MSAM 2024

作者： Jakab, Sándor Kálmán Singh, Tej Lendvai, László Department of Materials Science and Engineering Széchenyi István University GyorH-9026 Hungary Savaria Institute of Technology Faculty of Informatics ELTE Eötvös Loránd University BudapestH-1117 Hungary

ISBN: (纸本)9781643685472

In this study, biopolymer composites were developed using poly(lactic acid) (PLA) as a polymer matrix. Various agricultural by-products, including flax seed meal, rapeseed straw, and mustard seed meal, were added as a reinforcement. The research aimed to provide insight into the valorization of cheap, readily available residues generated in the agricultural industry and assess the mechanical properties of composites prepared using them. The experimental fabrication was conducted by compounding PLA with agro-waste particles in 10 and 20 wt% concentrations. These components were melt mixed with a twin-screw extruder and injection molded into standardized forms. The resulting fabricated composites were tested for tensile and flexural mechanical properties and hardness. Through scanning electron microscopy, images of the natural particles were taken to better understand their structure, geometry, and possible ways of interaction between them and the PLA matrix. The results of quasi-static mechanical tests suggest that using agricultural by-products can effectively improve Young's modulus and flexural modulus of PLA but at the cost of tensile and flexural strength, which decreased with the by-products' introduction. Of the three agro-waste options, rapeseed straw emerged as the superior choice because it only marginally reduced the mechanical strength of the PLA and enhanced its stiffness the most. Hardness was the least affected property, test results showed that the added fillers did not substantially change the polymer matrix's hardness. © The Author(s), 2024.

关键词： Straw

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Drone-Based Public Surveillance Using 3D Point Clouds and Neuro-Fuzzy Classifier

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Computers, Materials & Continua 2025年第3期82卷 4759-4776页

作者： Yawar Abbas Aisha Ahmed Alarfaj Ebtisam Abdullah Alabdulqader Asaad Algarni Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Science and Engineering College of InformaticsKorea UniversitySeoul02841Republic of Korea Cognitive Systems Lab University of BremenBremen28359Germany

Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot ***,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera *** research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)*** first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale *** YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further *** joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are *** features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity ***-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing *** particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.

关键词： Activity recognition geodesic distance pattern recognition neuro fuzzy classifier

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Resilient Routing Table Computation Based on Connectivity Preserving Graph Sequences 42

Resilient Routing Table Computation Based on Connectivity Pr...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Tapolcai, Janos Babarczi, Peter Ho, Pin-Han Ronyai, Lajos Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Telecommunications and Media Informatics BudapestH-1111 Hungary University of Waterloo Deptartment of Electrical and Computer Engineering Canada Institute for Computer Science and Control Eötvös Loránd Research Networkand Department of Algebra Hungary Institute of Mathematics Budapest University of Technology and Economics BudapestH-1111 Hungary

ISBN: (纸本)9798350334142

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences. © 2023 IEEE.

关键词： Graph theory

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Comparative analysis of bacterial contamination in tap and groundwater: A case study on water quality of Quetta City, an arid zone in Pakistan

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Journal of Groundwater science and engineering 2022年第2期10卷 153-165页

作者： Khan Tanzeel Akhtar Malik Muhammad Malghani Gohram Akhtar Rabia Department of Environmental Science Faculty of Life Sciences&InformaticsBalochistan University of Information TechnologyEngineering and Management SciencesQuetta 87300Pakistan Department of Psychology Balochistan University of Information TechnologyEngineering and Management SciencesQuetta 87300Pakistan

Water is an essential element on earth,which provides human a variety of services in domestic use,agriculture,or ***,some serious health risks of drinking water are associated with microbial contamination,particularly with fecal ***,microbial quality assessment is considered to be a necessary component of water quality *** study investigates microbial contamination of water distributary system around the city by comparing groundwater(GW)and tap water(TW)quality in Quetta city.31 GW samples and 31 TW samples were collected in the study area during the months of September,October,and *** coliform test was carried out in laboratory and their average total coliform contamination was *** showed that the TW sample were all contaminated by coliform except for Chiltan town,hence are not considered suitable for drinking without any treatment according to WHO drinking water quality *** average coliform concentrations were 12 in Quetta main city,11.6 in Jinnah town,5.3 in Satallite town,10 in Shahbaz town and 5 in Brewery town(0/100 mL CFU)and the TW samples from the three towns were even more contaminated with *** among the GW,average microbial concentrations were 1.8 in Quetta main city,2 in Satallite town,1.4 in Shahbaz town,and 0.4 in Chiltan town(0/100 mL CFU),respectively,which shows that the contamination is occurring within the water distributary pipeline system when the water flows through the ***,this research will be valuable for researchers and administrative authorities to conduct elaborative studies,and develop new policies to prevent further deterioration of drinking water in the water distribution system by pathogenic microorganisms and ensure safe drinking water to the public of Quetta city.

关键词： Groundwater quality Microbial contamination Coliform bacteria Drinking water quality

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Control System for Operating Modes of Fiber Lead Bending Formers

Control System for Operating Modes of Fiber Lead Bending For...

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2024 Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex, TIRVED 2024

作者： Mansurov, Elnur Yablochnikova, Irina Kerimova, Maya Mansurov, Tofig Yablochnikov, Sergey Azerbaijan Technical University Department of Radio Engineering and Telecommunications Baku Azerbaijan Moscow Technical University of Communications and Informatics Russia Azerbaijan State University of Oil and Industry Department of Power Engineering Baku Azerbaijan Plekhanov Russian University of Economics Moscow Russia National University of Science and Technology MISIS Moscow Russia

ISBN: (纸本)9798331518707

In order to monitor, measure or receive a signal via feedback, it is necessary to branch off a part of the output power of the emitter from the main transmission channel. This branch is used as a control signal intended to control the output power level of the emitter, as well as to separate or combine radiation flows. Based on the analysis, the shortcomings of existing works were identified and a control system for the operating modes of fiber optic bend formers was developed. This system allows for connecting one of the optical transmitting modules with a long wavelength and low attenuation of the fiber optic, extracting information by receiving a signal corresponding to the level of branched radiation, determining the locations and masses of the penetrating object depending on the intensity of the branched radiation and, via the feedback circuit, automatically adjusting the output power level of the emitter. © 2024 IEEE.

关键词： Light transmission

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Analyzing darknet traffic through machine learning and neucube spiking neural networks

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Intelligent and Converged Networks 2024年第4期5卷 265-283页

作者： Iman Akour Mohammad Alauthman Khalid M.O.Nahar Ammar Almomani Brij B.Gupta Information Systems Department College of Computing&InformaticsUniversity of SharjahSharjahUnited Arab Emirates Department of Information Security Faculty of Information TechnologyUniversity of PetraAmman 11196Jordan the Faculty of Computer Studies Arab Open UniversityRiyadh 11681Saudi Arabia Department of Information Technology Al-Huson University CollegeAl-Balqa Applied UniversityIrbid 19117Jordan the Department of Computer Information Science Higher Colleges of TechnologySharjahUnited Arab Emirates the Department of Computer Science and Information Engineering Asia UniversityTaichung 413ChinaSymbiosis Centre for Information TechnologySymbiosis International(Deemed University)Pune 412115India Centre of Inter-disciplinary Research&Innovation University of Petroleum and Energy StudiesDehradun 248007India

The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication *** detection of clandestine darknet traffic is therefore critical yet immensely *** research demonstrates how advanced machine learning and specialized deep learning techniques can significantly enhance darknet traffic analysis to strengthen *** diverse classifiers such as random forest and naïve Bayes with a novel spiking neural network architecture provides a robust foundation for identifying concealed *** on the CIC-Darknet2020 dataset establishes state-of-the-art results with 98%accuracy from the random forest model and 84.31%accuracy from the spiking neural *** pioneering application of artificial intelligence advances the frontiers in analyzing the complex characteristics and behaviours of darknet *** proposed techniques lay the groundwork for improved threat intelligence,real-time monitoring,and resilient cyber defense systems against the evolving landscape of cyber threats.

关键词： darknet traffic machine learning deep learning spiking neural network PCA

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A Study on Mobility Management Schemes in Vehicular Communication 2

A Study on Mobility Management Schemes in Vehicular Communic...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Nugraha, Toha Ardi Ardiyanto, Yudhi Damarjati, Cahya Fachrie, Muhammad Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Information Technology Yogyakarta Indonesia Universitas Teknologi Yogyakarta Faculty of Science and Technology Department of Informatics Yogyakarta Indonesia

ISBN: (纸本)9781665465410

Vehicular communication allows vehicles to communicate with each other without connecting to a centralized infrastructure (i.e., base station). Vehicular communication including Vehicle-to-vehicle and vehicle-to-infrastructure communications also allows for the exchange of information between vehicles, which supports a number of applications, such as intelligent transportation systems and safety management. However, mobility management is a key aspect that has yet to be addressed properly for vehicular communication. Therefore, this paper reviews the existing mobility management and summarizes the resource allocation scheme for vehicular communication. We present a mode selection to maintain the connectivity of vehicular communication. Then, we simulate and discuss the existing mobility management scheme for vehicular communication. © 2022 IEEE.

关键词： Vehicles

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Tele-Rheumatology-Advanced Neural Network Model for Remote Assessment and Management of Rheumatic Conditions 10

Tele-Rheumatology-Advanced Neural Network Model for Remote A...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Aghalya, S. Sarasu, R. Mishra, Nilamadhab Arunachalam, G. Gobinath, D. Naganathan, Suresh Babu Thandullu St. Joseph's College of Engineering Omr Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Spatial Informatics Tamil Nadu Chennai India Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh India Department of Electronics and Communication Engineering Tamil Nadu Namakkal India Rajalakshmi Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

The study presents an advanced neural network model for real-time remote evaluation and treatment of rheumatic diseases using sensor fusion. The model was developed for use in this investigation. The suggested system uses a wide variety of sensing modalities, such as image, motion, and biometric sensors. This is accomplished via artificial intelligence (AI) and the data gleaned from sensors. The neural network, which was trained on a dataset that was both varied and labeled, performs autonomous analyses of input data in order to accurately predict and categorize rheumatic diseases. The integration of the model into remote medical treatment is made easier by the fact that it is run on a Raspberry Pi inside a tele-rheumatology framework. This unique strategy not only improves diagnostic accuracy but also expands rheumatology services to geographically inaccessible or disadvantaged groups. As a result, the landscape of rheumatic healthcare delivery is completely transformed as a result of this new approach. For the purpose of ensuring the ethical use of this revolutionary technology, the procedures for data security and ethical concerns have been given priority. © 2024 IEEE.

关键词： Neural network models

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Efficient Resource Management in IoTs Using Evolutionary and Swarm Intelligence Algorithms 7

Efficient Resource Management in IoTs Using Evolutionary and...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Gupta, Keshav Dev Cengiz, Korhan Awasthi, Charu Ramini, Siva Akash Chatterjee, Shyamapriya Pavithra, M. Poornima College of Engineering Department of Computer Science Engineering Jaipur India University of Fujairah College of Information Technology United Arab Emirates Istinye University Department of Computer Engineering Istanbul Turkey University of Hradec Kralove Faculty of Informatics and Management Department of Information Technologies Hradec Kralove500 03 Czech Republic JSS Academy of Technical Education Department of Information Technology Noida India Andhra Pradesh Amaravati India Narula Institute of Technology Department of Information Technology West Bengal Kolkata India Jansons Institute of Technology Karumathampatti Department of Computer Science and Engineering Coimbatore641659 India

ISBN: (纸本)9798350383065

The proliferation of the Internet of Things (IoT) has ushered in a transformative era of connected devices, emphasizing the critical need for effective resource management. This study introduces an innovative approach that harnesses Evolutionary and Swarm Intelligence algorithms for IoT Task Scheduling, addressing resource optimization challenges. The approach offers superior resource utilization through advanced optimization techniques, reducing energy consumption and enhancing efficiency. Furthermore, it significantly reduces task scheduling execution time, enabling prompt decision-making in dynamic IoT environments. This results in improved task allocation quality, meeting application-specific requirements, and prioritizing critical tasks. Notably, the approach excels in minimizing completion time, making it particularly advantageous for real-time IoT applications. This research contributes to the advancement of IoT resource management, offering an adaptive, efficient, and intelligent solution with broad applicability. In the evolving landscape of IoT, the findings presented here lay a solid foundation for future research and practical implementations, ultimately promoting more responsive, sustainable, and intelligent IoT ecosystems. © 2023 IEEE.

关键词： Swarm intelligence

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