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3rd EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2022

作者： Valarmathi, B. Gupta, N. Srinivasa Santhi, K. Chellatamilan, T. Kavitha, A. Raahil, Armaan Padmavathy, N. Department of Software and Systems Engineering School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Analytics School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore India Department of Information Technology School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031289743

In this study, machine learning (ML) techniques are employed to predict used car prices. Several features are used to calculate the price of used cars, but in this paper, we find efficient ways to find the most precise car prices. Despite the fact that there are websites offering this service, they could not employ the most precise prediction system. It is also possible to predict a used car's true market value using a variety of models and techniques. It's important to understand their genuine market value before buying or selling. Both buyers and sellers will be benefitted from these accurate predictions. Support Vector regression, Random Forest regression, and CatBoost regression techniques are used in the proposed system. In the existing method [13], mean absolute error for decision tree regression was 0.6711, which was the least among other algorithms like Linear regression, Lasso regression, Ridge regression, Bayesian Ridge regression, and etc., they used. In the proposed system, mean absolute error (MAE) for Support Vector regression, CatBoost regression and Random Forest regression techniques are 0.1459, 0.1371 and 0.1284 respectively. The prices of second hand/used cars are predicted using the CatBoost regression, Support Vector regression, and Random Forest regression techniques. The accuracy of these algorithms are 86.28%, 85.40% and 87.16%. Among these three algorithms, Random Forest regression gives the least MAE of 0.1317 and the highest accuracy of 87.16%. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Forecasting

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Contextual Multi-Armed Bandit based Beam Allocation in mmWave V2X communication under Blockage

Contextual Multi-Armed Bandit based Beam Allocation in mmWav...

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IEEE Conference on Vehicular Technology (VTC)

作者： Arturo Medina Cassillas Abdulkadir Kose Haeyoung Lee Chuan Heng Foh Chee Yen Leow Department of Engineering King’s College London London UK Department of Computer Engineering Abdullah Gul University Kayseri Turkey School of Physics Engineering and Computer Science University of Hertfordshire Hatfield UK 5GIC & 6GIC Institute for Communication Systems (ICS) University of Surrey Guildford UK Wireless Communication Centre Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia

Due to its low latency and high data rates support, mmWave communication has been an important player for vehicular communication. However, this carries some disadvantages such as lower transmission distances and inability to transmit through obstacles. This work presents a Contextual Multi-Armed Bandit Algorithm based beam selection to improve connection stability in next generation communications for vehicular networks. The algorithm, through machine learning (ML), learns about the mobility contexts of the vehicles (location and route) and helps the base station make decisions on which of its beam sectors will provide connection to a vehicle. In addition, the proposed algorithm also smartly extends, via relay vehicles, beam coverage to outage vehicles which are either in NLOS condition due to blockages or not served any available beam. Through a set of experiments on the city map, the effectiveness of the algorithm is demonstrated, and the best possible solution is presented.

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Iot Based Smart Assistant Cane For The Visually Impaired

Iot Based Smart Assistant Cane For The Visually Impaired

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International Conference on communication, Computing and Internet of Things (IC3IoT)

作者： A Harini C Buvana M Harshini S Keerthana D Prabhu S K Umamaheswaran Department of Electronics and Communication Engineering Sri Sairam Engineering College Chennai Tamil Nadu Department of Information Technology Sri Sairam Engineering College Chennai Tamil Nadu Department of Artificial intelligence and Data Science Sri Sairam Engineering College Chennai Tamil Nadu Department of Computer Science and Business Systems Sri Sairam Engineering College Chennai Tamil Nadu Department of Mathematics Sri Sairam Engineering College Chennai Tamil Nadu

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

This paper presents the design and implementation of a Smart Cane for the visually impaired individuals, incorporating several sensors and features to improve their mobility and safety. The device includes an ultrasonic sensor for obstacle detection, an MPU-6050 device for detecting falls and tilts, a GPS module for navigation, an RTC module for medicine reminders, and a fitness tracking module for monitoring health parameters. Additionally, a Bluetooth headset with a microphone is provided to communicate with the voice assistant in noisy areas. The Smart Cane triggers a buzzer for help and sends a notification to the caretaker in case of a fall or crash. The device is powered by a LIPO battery and is designed to improve the quality of life of visually impaired individuals by providing them with enhanced mobility and safety features.

关键词： Navigation Personal voice assistants Sensor phenomena and characterization Safety Telecommunication computing Noise measurement Intelligent sensors

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The Reliability of Information Sources: Student Perceptions and Educational Opportunities

The Reliability of Information Sources: Student Perceptions ...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Anita Mihalovicsne Kollar Jozsef Katona Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

The modern digital age demands the skills to be able to assess information. In the current world, access to information and knowledge is abundant from different sources. Indeed, high-quality data are much needed in education and professional development, as the quality and accuracy of information directly influence the process of learning and decision-making. The study aims to investigate the perceptions of computer science students at the University of Dunaújváros related to the credibility of diverse information sources. Within a questionnaire, on a voluntary answer basis, 68 students took part, 59 males and nine females. This work is aimed at assessing the degree to which the surveyed students evaluate information sources based on a five-point Likert scale. The data shows that students find print books and textbooks as the most reliable sources; social media are the least reliable. The study also supports the importance of source credibility evaluation, for which lateral reading techniques and AI-based news source credibility identification systems can be helpful. These findings suggest the necessity of bettering the educational approaches to foster better source criticism skills in the students, especially for online content and social media. The study generally contributes to understanding the information society and helps prepare students to obtain and use reliable and accurate information in their future careers. Using AI-based tools and systems can then further support these educational efforts with robust mechanisms to evaluate information credibility in an ever more complex digital landscape.

关键词： Economics Power engineering Accuracy Social networking (online) Engineering profession Education Reliability engineering Information filters Information age Reliability

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Enhancing Monkeypox diagnosis and explanation through modified transfer learning, vision transformers, and federated learning

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Informatics in Medicine Unlocked 2024年 45卷

作者： Ahsan, Md Manjurul Alam, Tasfiq E. Haque, Mohd Ariful Ali, Md Shahin Rifat, Rakib Hossain Nafi, Abdullah Al Nomaan Hossain, Md Maruf Islam, Md Khairul Department of Industrial and Systems Engineering University of Oklahoma Norman 73019 OK United States Department of Cyber-Physical Systems Clark Atlanta University Atlanta 30314 GA United States Department of Biomedical Engineering Islamic University Kushtia 7003 Bangladesh Department of Computer Science and Engineering BRAC University Dhaka 1212 Bangladesh Department of Information and Communication Technology Islamic University Kushtia 7003 Bangladesh

The Monkeypox outbreak has emerged as a pressing global health challenge, evidenced by rising cases across nations. Individuals afflicted exhibit diverse dermatological symptoms that risk further transmission via contamination. Our study assessed the efficacy of three modified transfer learning models (M-VGG16, M-ResNet50, M-ResNet101) alongside vision transformers (ViT) across four investigations. We achieved high accuracy in discriminating Monkeypox cases, with M-VGG16 achieving 88%, 76%, and 77% accuracy in Studies One, Two and Four and M-ResNet50 achieving 89% in Study Three. To comprehend triggers for Monkeypox onset, we utilized Local Interpretable Model-Agnostic Explanations (LIME) to explain predictions visually. LIME alignments underscored our models' high accuracy, correlating with segmented identification of infected regions. Further, we implemented Federated Learning on decentralized data to evaluate generalization capabilities. Blending established deep learning with emerging decentralized learning and explanation techniques is vital in improving predictive accuracy and elucidating Monkeypox intricacies amid the persisting global outbreak. Our study emphasizes the continued relevance of pioneering techniques while introducing new approaches to address this major health challenge. © 2024 The Authors

关键词： Disease diagnosis Image segmentation LIME Transfer learning Vision transformer

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Design of a Sensor Measuring Station for Pasture Parameters Remote Monitoring 4

Design of a Sensor Measuring Station for Pasture Parameters ...

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4th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Valov, Nikolay Evstaiev, Boris Mladenova, Tsvetelina Valova, Irena Kadirova, Seher Markov, Nikolay Stoycheva, Svetoslava Atanasova, Tatiana Varlyakov, Ivan University of Ruse Angel Kanchev Department of Automatics and Mechatronics Ruse Bulgaria University of Ruse Angel Kanchev Department of Electronics Ruse Bulgaria University of Ruse Department of Computer Systems and Technologies Ruse Bulgaria Research Institute of Mountain Stockbreeding and Agriculture Agricultural Academy Troyan Bulgaria Institute of Information and Communication Technologies Bulgarian Academy of Science Modeling and Optimization Department Sofia Bulgaria Trakia University Department of Morphology Physiology and Nutrition of Animals Stara Zagora Bulgaria

ISBN: (纸本)9781665468350

This paper presents an approach for designing a specific meteo measurement station for remote and fully automatic monitoring of pastures and meadows. The station measurement soil parameters: temperature, moisture, electrical conductivity, pH, content of nitrogen, phosphorus, potassium and air parameters - temperature, humidity, atmospheric pressure. These parameters together with timestamp are sending to data server using LoRaWAN interface. With the help of proposed system and artificial intelligence it is possible to refine the necessary actions to take care of the terrain, predict the amount and quality of the produce by analysing the different parameters of the field, monitoring the atmospheric conditions etc. © 2022 IEEE.

关键词： Microcontrollers

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Detection of terahertz radiation using topological graphene micro-nanoribbon structures with transverse plasmonic resonant cavities

arXiv

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arXiv 2024年

作者： Ryzhii, V. Tang, C. Otsuji, T. Ryzhii, M. Shur, M.S. Research Institute of Electrical Communication Tohoku University Sendai980-8577 Japan Frontier Research Institute for Interdisciplinary Sciences Tohoku University Sendai980-8578 Japan School of Computer Science and Engineering University of Aizu Aizu-Wakamatsu965-8580 Japan Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

The lateral interdigital array of the graphene microribbons (GMRs) on the h-BN substrate connected by narrow graphene nanoribbon (GNR) bridges serves as an efficient detector of terahertz (THz) radiation. The detection is enabled by the nonlinear GNR elements providing the rectification of the THz signals. The excitation of plasmonic waves along the GMRs (transverse plasmonic oscillations) by impinging THz radiation can lead to a strong resonant amplification of the rectified signal current and substantial enhancement of the detector response. The GMR arrays with the GNR bridges can be formed by the perforation of uniform graphene layers. © 2024, CC BY.

关键词： Terahertz waves

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PerMTL: A Multi-Task Learning Framework for Skilled Human Performance Assessment

PerMTL: A Multi-Task Learning Framework for Skilled Human Pe...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Indrajeet Ghosh Avijoy Chakma Sreenivasan Ramasamy Ramamurthy Nirmalya Roy Nicholas Waytowich Department of Information Systems University of Maryland Baltimore County Center for Real-Time Distributed Sensing and Autonomy (CARDS) University of Maryland Baltimore County Department of Computer Science Bowie State University DEVCOM Army Research Laboratory United States

Intelligent and complex human motion analysis can help design the next generation IoT and AR/VR systems for automated human performance assessment. Such an automated system can help advocate the interpretability and translatability of complex human motions, intelligent motion feedback, and fine-grained motion skill assessment to design next-generation interactive human-machine teaming systems. Motivated by this, we design a wearable sensing framework for assessing the players’ performance and consider a live badminton game as our use case. Generally, the players on the field try to improve their performance by focusing on fast and synchronous coordination of their limbs’ reflex actions to have the ideal body postures to perform the desired shot. Learning the minute dissimilarities and distinctive traits from each limb of the players simultaneously can help assess the players’ performance and specific skillsets during a game. This paper proposes a multi-task learning framework, PerMTL to learn the shared features from each player’s limb. The PerMTL comprises a task-specific regressor output layer that helps to determine the dissimilarities and distinctive traits between the player’s limbs for collective inference in a body sensor network (BSN) environment. We evaluate the PerMTL framework using publicly available Badminton Activity Recognition (BAR) and Daily and Sports Activities (DSA) datasets. Empirical results indicate that PerMTL achieves R 2 Score of ≈ 82% in predicting the players’ performance.

关键词： Scalability Games Multitasking Robustness Sensors Task analysis Motion analysis

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Optimal Bandwidth Utilization Techniques for IoT Device Networks using Edge Computing

Optimal Bandwidth Utilization Techniques for IoT Device Netw...

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Innovation in Technology (ASIANCON), Asian Conference on

作者： Dankan Gowda V G. Vijayakumar J. Chandrasekar Shekhar R KDV Prasad Senthil Kumar C Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka Department of Information Technology V.S.B. Engineering College Karur Tamilnadu India Department of Social Work ( Aided) Madras School of Social Work Chennai Tamilnadu India Department of Computer Science and Engineering Alliance University Bangalore Karnataka India Symbiosis Institute of Business Management Hyderabad Symbiosis International (Deemed University) Pune India Department of Information Technology School of Computer Science Engineering & Information Systems Vellore Institute of Technology Vellore India

ISBN: (数字)9798350354218

ISBN: (纸本)9798350354225

The IoT devices have persisted on growing at a very fast pace and this has proven very challenging in managing the network bandwidth. This paper spins the new concept of increasing the IoT networks bandwidth by adopting the edge computing strategies. It also offers data processing near the sources which reduces the load on the central servers and cuts down data transfer requirements. The usage of the Dynamic Bandwidth Allocation algorithm in the proposed method also enhances the priority of the imperative data and scales up the transmission rates according to the network status. The number of data units achieve higher values, the latency is less and overall, better results have been obtained for the total network performance. Consequently, the results obtained presented pathways through which the bandwidth challenge in IoT could be addressed by means of edge computing to enhance IoT capacity in the corresponding surroundings.

关键词： Performance evaluation Technological innovation Costs Heuristic algorithms Bandwidth Channel allocation Dynamic scheduling Internet of Things Time factors Edge computing

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Enhancing the Throughput of Device-to-Device communication in Cellular systems Using Non-Orthogonal Transmission

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IEEE Access 2024年 12卷 112290-112307页

作者： Chu-Tung Liu Hsuan-Jung Su Hsien-Bo Tseng Jhe-Yi Lin Wei-Hsiang Wang Alan Shenghan Tsai Yasuhiro Takano Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan MediaTek Inc. Hsinchu Taiwan Realtek Semiconductor Corp. Hsinchu Taiwan Department of Electrical and Computer Engineering University of Maryland College Park MD USA *** Inc. Sunnyvale CA USA Department of Information Systems Engineering Chitose Institute of Science and Technology Hokkaido Chitose Japan

Device-to-Device (D2D) communications facilitate direct data exchange between two devices, bypassing the necessity of routing through a central base station. This proximity-based communication offers advantages such as high data rates, low latency, reduced power consumption, and efficient frequency reuse. In the cellular spectrum, D2D operations encompass overlay D2D and underlay D2D. Overlay D2D allocates orthogonal radio resources to D2D and cellular users, resulting in inefficient frequency reuse. On the other hand, underlay D2D shares the same radio resources among D2D and cellular users, necessitating centralized coordination and extensive exchanges of channel and traffic information for effective interference management. To address the limitations of overlay and underlay D2D, we introduce a scheme that allows D2D users to simultaneously and non-orthogonally transmit both D2D and cellular signals. This approach resembles underlay D2D in terms of high frequency reuse but eliminates the need for centralized interference management. In this paper, we investigate various system design aspects based on this scheme, including power allocation, multiple-antenna extension, scheduling constraints, and different interference cancellation techniques. Incorporating a coordinated scheduling method, the proposed scheme enhances the sum rate of a conventional multiple-antenna overlay D2D system by 2.14 times, with only a negligible impact on the cellular communication rate. Furthermore, the proposed scheme improves the sum rate by up to 87% within conventional underlay D2D systems, all without the need for additional centralized coordination.

关键词： Device-to-device communication Resource management Interference cancellation Cellular networks Spectral efficiency Precoding Throughput MIMO communication

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