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International Scientific Conference on Power and Electrical engineering of Riga Technical University (RTUCON)

作者： Egīls Dzelzītis Pēteris Apse-Apsītis Edijs Luņģis RTU Institute of Heat Gas and Water Technology Riga Latvia RTU Institute of Industrial Electronics Electrical Engineering and Energy Riga Latvia Faculty Of Computer Science Information Tehnology And Energy RTU Riga Latvia

The task of the energy management system is to create conditions for maximizing the efficiency of electricity and heat consumption in RTU buildings, while ensuring a comfortable indoor climate and enabling continuous ... 详细信息

ISBN: (数字)9798350365771

ISBN: (纸本)9798350365788

关键词： Energy consumption Costs Three-dimensional displays ISO Standards Machine learning Digital twins Energy management systems Monitoring Meteorology Resistance heating

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Network-based Control of Epidemic via Flattening the Infection Curve: High-Clustered vs. Low-Clustered Social Networks

arXiv

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arXiv 2023年

作者： Doostmohammadian, Mohammadreza Rabiee, Hamid R. Faculty of Mechanical Engineering Semnan University Semnan Iran School of Electrical Engineering Aalto University Espoo Finland ICT Innovation Center Advanced Information and Communication Technology Research Center Department of Computer Engineering Sharif University of Technology Tehran Iran

Recent studies in network science and control have shown a meaningful relationship between the epidemic processes (e.g., COVID-19 spread) and some network properties. This paper studies how such network properties, namely clustering coefficient and centrality measures (or node influence metrics), affect the spread of viruses and the growth of epidemics over scale-free networks. The results can be used to target individuals (the nodes in the network) to flatten the infection curve. This so-called flattening of the infection curve is to reduce the health service costs and burden to the authorities/governments. Our Monte-Carlo simulation results show that clustered networks are, in general, easier to flatten the infection curve, i.e., with the same connectivity and the same number of isolated individuals they result in more flattened curves. Moreover, distance-based centrality measures, which target the nodes based on their average network distance to other nodes (and not the node degrees), are better choices for targeting individuals for isolation/vaccination. © 2023, CC BY.

关键词： Monte Carlo methods

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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Robotics, engineering, Science, and technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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Deep learning model for efficient traffic forecasting in intelligent transportation systems

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Neural Computing and Applications 2024年 1-14页

作者： Khan, Shakir Alghayadh, Faisal Yousef Ahanger, Tariq Ahamed Soni, Mukesh Viriyasitavat, Wattana Berdieva, Uguloy Byeon, Haewon Riyadh Saudi Arabia University Centre for Research and Development Department of Computer Science and Engineering Chandigarh University Mohali140413 India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Management Information Systems CoBA Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Pune India Dr. D. Y. Patil School of Science and Technology Tathawade Pune India Chulalongkorn Business School Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand The Department of Tax and Taxation Tashkent Institute of Finance Tashkent Uzbekistan Department of Digital Anti-Aging Healthcare Inje University Gimhae50834 Korea Republic of

In this paper, a novel intelligent transportation framework called graph convolutional neural network for distributed machine learning (GCN-DML) is presented. Its primary application is traffic forecasting in large-scale, dynamically-evolving traffic scenarios. One unique method in traffic forecasting, called GCN-DML, is that it allows user data to be processed locally on edge devices, removing the requirement to send all data to CS (CS). Designed specifically for edge computing, this distributed machine learning framework makes it easier to train neural networks on a variety of edge devices. In addition to protecting user privacy, this method reduces the difficulties related to centralised neural network training, minimises communication delays, lowers data transfer quantities, and improves overall data processing efficiency. GCN-LSTM, the composite graph convolutional networks used in this framework, combine edge-enhanced attention mechanisms with the feature transmission capabilities of graph convolutional neural networks to effectively handle the challenging task of traffic forecasting. Even as the number of cars in the network rises, they perform exceptionally well at quickly extracting and sending interaction information between vehicles, while preserving high prediction accuracy and low time complexity. The versatility of GCN-DML is extended to a range of traffic forecasting application scenarios, whereby edge devices can adjust the kind and scale of the neural network according to available compute and storage resources, all without sacrificing performance. The usefulness of GCN-DML in traffic forecasting is demonstrated by experimental evaluations on the NGSIM public dataset, where it outperforms other models with better computation time and prediction performance. It obtains noteworthy F1 scores of 0.9473, 0.9557, and 0.9391, respectively, for recall, precision, and precision. Even when there is an increase in the number of cars, the accuracy remains high,

关键词： Convolutional neural networks

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One-Click Total Bacterial Quantification: An All-in-One Automatic Microfluidic Platform for Simple Liquid Food Samples

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IEEE Sensors Journal 2025年第12期25卷 22667-22676页

作者： Yang, Ping Liang, Baihui Yuan, Haojun Zheng, Junmei Zou, Tinglang Xin, Pengfei Yan, Xinxin Wu, Jinlei Luo, Zhiquan Jin, Qinghui Gao, Wanlei Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China Healthy & Intelligent Kitchen Engineering Research Center of Zhejiang Province Zhejiang Ningbo315336 China Zhejiang Fashion Institute of Technology Mechanical and Electrical Engineering School Zhejiang Ningbo315211 China Ningbo Polytechnic Zhejiang Ningbo315800 China Chinese Academy of Sciences State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Shanghai200050 China

Food safety detection is essential for disease prevention and public health protection. However, current bacterial detection technologies generally face challenges including complex operation, long detection cycles, and large sample requirements. While ATP bioluminescence technology offers rapid, sensitive microbial quantification, traditional processes remain inefficient. To address these challenges, this study developed a fully automated integrated ATP bioluminescence bacterial quantification platform. The system integrates a microfluidic chip, automatic sample injection module, and real-time luminescence analysis photoelectric module, achieving an end-to-end workflow of mixing, on-chip reaction, analysis, and cleaning, eliminating manual intervention and improving convenience and efficiency. Chip’s advanced structures ensure high mixing efficiency of 98.9%, significantly reducing required sample volume and cost. With detection time under 10 minutes, experimental validation demonstrated excellent inter-batch consistency and repeatability (RSD 2 = 0.9995), and detection limit of 4.86 pM. For Vibrio parahaemolyticus, the system achieved a detection range of 102 to 108 CFU/mL (R2 = 0.996). In spiked Coca-Cola samples, the system maintained excellent anti-interference ability and accuracy (R2 = 0.941), with standard curve slopes differing by only 11.3% from PBS buffer. This portable platform with high sensitivity, stability, and repeatability is suitable for field testing of water and simple liquid foods.. In the future, by integrating specific bacterial capture technology and sample pretreatment modules, the system is expected to extend to more complex matrix sample detection, further enhancing its application value in food safety. © 2001-2012 IEEE.

关键词： Microfluidic chips

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The Child Factor in Child-Robot Interaction: Discovering the Impact of Developmental Stage and Individual Characteristics

arXiv

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arXiv 2024年

作者： Rudenko, Irina Rudenko, Andrey Lilienthal, Achim J. Arras, Kai O. Bruno, Barbara Freiburg im Breisgau Germany Robert Bosch GmbH Corporate Research Stuttgart Germany Germany Örebro University Sweden Faculty of Computer Science Electrical Engineering and Information Technology University of Stuttgart Germany Germany

Social robots, owing to their embodied physical presence in human spaces and the ability to directly interact with the users and their environment, have a great potential to support children in various activities in education, healthcare and daily life. Child-Robot Interaction (CRI), as any domain involving children, inevitably faces the major challenge of designing generalized strategies to work with unique, turbulent and very diverse individuals. Addressing this challenging endeavor requires to combine the standpoint of the robot-centered perspective, i.e. what robots technically can and are best positioned to do, with that of the child-centered perspective, i.e. what children may gain from the robot and how the robot should act to best support them in reaching the goals of the interaction. This article aims to help researchers bridge the two perspectives and proposes to address the development of CRI scenarios with insights from child psychology and child development theories. To that end, we review the outcomes of the CRI studies, outline common trends and challenges, and identify two key factors from child psychology that impact child-robot interactions, especially in a long-term perspective: developmental stage and individual characteristics. For both of them we discuss prospective experiment designs which support building naturally engaging and sustainable interactions. © 2024, CC BY.

关键词： Machine design

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Moving Towards Nano-Devices in the Context of Smart Bio-Tech Wearables

Moving Towards Nano-Devices in the Context of Smart Bio-Tech...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Ranganathaswamy M K Vaibhav Srivastav Deeksha Choudhary Department of Mechanical Engineeirng Faculty of Engineering and Technology JAIN (Deemed to be University) Bangalore India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Maharishi School of Engineeing & Technology Maharishi University of Information Technology Uttar Pradesh India

Because of the development of wireless capabilities, the network and, in specific, data centers have become a significant problem in our everyday lives. In order to maximize miniaturization and lower the opportunity burden among this equipment, the Network of Things (IoT) attempts to incorporate sensor and actuators into commonplace things. The idea is to use wireless and satellite networks to link these parts to the Internet, producing hard numbers that can then be saved and processed later. The Internet and pcs all provide innovative elements, but Interface TV (iTV) mixes conventional TV with a comparable level of involvement. With the advancement of Smart tvs, computational capability has been added to the device, enabling it to provide services beyond the norm, execute programmes, and realise its networking potential. This study proposes a methodology that comprises and unifies an IoT platform, a genuine tv Streaming show, and a network of wireless sensors. It includes everything from wireless sensor network implementation and transmission to web content accessibility guidelines and finished products through a genuine interactive television application. Hard data provision has now been trialled in a housing area with the goal of enhancing residents' life experiences. Additionally, it combines the potential for using this data to build procedures aimed at lowering energy consumption, enhancing longevity, and promoting the effective use of already available resources. For any implementation with comparable features, the conceptual approach serves as the foundation.

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Efficient Communication and System Model for Delay Minimization in UAV-Assisted IoT Networks

Efficient Communication and System Model for Delay Minimizat...

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Frontier Technologies and Solutions (ICFTS), International Conference on

作者： Sangeetha V N. Janardhana Rao V. Subashini Rajasekhar Manda Amneh Alamleh Shilpa Bhimrao Sahare Department of AI&DS Sri Sai Ram Engineering College Chennai Dept of MBA QIS College of Engineering and Technology Ongole Andhra Pradesh Dept of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai Dept of ECE QIS College of Engineering and Technology Ongole India Department of Computer Science Faculty of Information Technology Zarqa University Jordan University of Business and Technology - UBT Jeddah SA Dept of ME Yeshwantrao Chavan College of Engineering Nagpur India

ISBN: (数字)9798331502768

ISBN: (纸本)9798331502775

An ECSMDM is an efficient Unmanned Aerial Vehicle (UAV) communication and system model that utilizes UAPs as mobile relays to facilitate data transfer across IoT networks. By optimizing the ECSMDM protocol, factors such as packet size and throughput optimization are considered alongside energy efficiency (energy savings) and routing overhead. The purpose of UAVs is to provide a weak direct link between nodes. The Age of information (AoI) metric ensures information is current. The UAV-BS adjusts its position to improve A2G channel connectivity, considering LOS, NLOS factors, and UAV energy usage. ECSMDM surpasses existing protocols like DSVO, OFDC, and IBUR in all aspects of measurement. The ECSMDM protocol achieves the highest packet delivery ratio of 91.07%, indicating superior network reliability, and the highest network throughput of 567.94 Kbps, reflecting better data transmission. It also records the lowest average latency of 116.36ms, which highlights its responsiveness, and the highest energy efficiency of 405.36 joules, indicating significant saving features. ECSMDM has the lowest routing of 312.54 packets, showing reduced network congestion and better performance. The ECSMDM protocol's performance enhancement in UAV-assisted data transmission highlights its potential to enhance network reliability, efficiency, and effectiveness in IoT networks.

关键词： Protocols Throughput Routing Autonomous aerial vehicles Energy efficiency Data models Delays Reliability Relays Optimization

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A Fine-Grained Cross-Chain Spectrum Sharing Mechanism Based on Oracle

A Fine-Grained Cross-Chain Spectrum Sharing Mechanism Based ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Mengjie Cao Qian Wang Xiaojiang Du Juan Fang Bei Gong Mohsen Guizani Faculty of Information Technology Beijing University of Technology Beijing China Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ USA Mohamed Bin Zayed University of Artificial Intelligence United Arab Emirates

The dramatically increased wireless communication needs make non-renewable spectrum resources extremely scarce and costly. Consortium blockchain realizes trusted spectrum sharing among untrusted spectrum owners. Yet, most existing studies ignore spectrum sharing among blockchains, which greatly reduce spectrum utilization. In the paper, we focus on cross-chain spectrum sharing. We propose a Fine-grained Cross-chain Spectrum Sharing mechanism based on Oracle (FCSSO) to realize trusted and efficient cross-chain spectrum transactions. To guarantee benefits of spectrum owners, we design a fine-grained time partition method to decide spectrum renting time in transactions. The method reduces the waste of owners' available spectrum time caused by spectrum handoff. Extensive simulation proves the positive impact of the proposed fine-grained time partition method, and FCSSO outperforms two representative cross-chain mechanisms from two aspects: spectrum owners' benefits and spectrum utilization.

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Cryptocurrency volatility prediction based on price, return and volatility cross-correlation using LSTM

Cryptocurrency volatility prediction based on price, return ...

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International Symposium on Telecommunications, IST

作者： Masoud Omidvari Abarghouie Sasan H. Alizadeh Ahmad Khademzadeh Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Faculty of Information Technology ICT Research Institute (ITRC) Tehran Iran ICT Research Institute (ITRC) Tehran Iran

ISBN: (数字)9798350356250

ISBN: (纸本)9798350356267

The rise of cryptocurrencies as a major economic factor has drawn interest from both individual investors and regulators. This has led researchers to explore new ways to predict cryptocurrency volatility. This research proposes a new approach for more accurately predicting the conditional variance of cryptocurrencies while previous research did not investigate cross-correlation among cryptocurrency mean and volatility landscapes. This research precisely uses a method to select the most relevant features based on the cross-correlation between price, returns, and volatility. Experiments on eight cryptocurrencies that have the largest market capacity from 2018 to 2024 show that this approach is effective. By considering stronger cross-correlation when choosing the data used for volatility prediction using LSTM, the research substantially reduces the error of prediction. The findings of this research can be used to predict the volatility of other cryptocurrencies and the stock markets.

关键词： Analytical models Adaptation models Regulators Accuracy Predictive models Cryptocurrency Telecommunications Stock markets Long short term memory Portfolios

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