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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering network, TEPEN 2023

作者： Chochliouros, Ioannis Kourtis, Michail-Alexandros Xilouris, George Tavernier, Wouter Spiliopoulou, Anastasia Zaharis, Zaharias Lazaridis, Pavlos S.A. Fixed Network R&D Programs Section Maroussi-Athens15122 Greece National Center for Scientific Research "Demokritos" Agia Paraskevi15341 Greece IMEC-Department of Information Technology Ghent University Ghent9000 Belgium School of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece School of Computing and Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom

ISBN: (纸本)9783031494123

In this work, based on the framework of the ongoing OASEES EU-funded project, we have discussed the concept of a Decentralized Autonomous Organization (DAO) that operates on a blockchain and governed by smart contracts. Then we have focused upon the description of a specific use case related to high mast inspection of telecommunications infrastructures. OASEES intends to integrate the DAO paradigm for the self-organized operation of a drone swarm, which will rely on the tight consolidation of the networking (e.g., 5G/B5G) and edge acceleration technologies (e.g., Spiking Neural networks). We have introduced this use case and also discussed current state-of-the-art together with existing limitations. In addition, we have identified intended scenarios of use and proposed specific requirements for conformance to the corresponding project architecture. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Drones

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Multiplex measures for higher-order networks

arXiv

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arXiv 2024年

作者： Lotito, Quintino Francesco Montresor, Alberto Battiston, Federico Department of Information Engineering and Computer Science University of Trento via Sommarive 9 Trento38123 Italy Department of Network and Data Science Central European University Vienna1100 Austria

A wide variety of complex systems are characterized by interactions of different types involving varying numbers of units. Multiplex hypergraphs serve as a tool to describe such structures, capturing distinct types of higher-order interactions among a collection of units. In this work, we introduce a comprehensive set of measures to describe structural connectivity patterns in multiplex hypergraphs, considering scales from node and hyperedge levels to the system’s mesoscale. We validate our measures with three real-world datasets: scientific co-authorship in physics, movie collaborations, and high school interactions. This validation reveals new collaboration patterns, identifies trends within and across movie subfields, and provides insights into daily interaction dynamics. Our framework aims to offer a more nuanced characterization of real-world systems marked by both multiplex and higher-order interactions. Copyright © 2024, The Authors. All rights reserved.

关键词： Large scale systems

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Reliability of Automatic computer Vision-Based Assessment of Orofacial Kinematics for Telehealth Applications

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Digital Biomarkers 2022年第2期6卷 71-82页

作者： Simmatis, Leif Barnett, Carolina Marzouqah, Reeman Taati, Babak Boulos, Mark Yunusova, Yana Department of Speech-Language Pathology University of Toronto TorontoON Canada KITE-Toronto Rehabilitation Institute University Health Network TorontoON Canada Institute of Health Policy Management and Evaluation University of Toronto TorontoON Canada Division of Neurology Department of Medicine University of Toronto TorontoON Canada University Health Network TorontoON Canada Department of Computer Science University of Toronto TorontoON Canada Institute of Biomedical Engineering University of Toronto TorontoON Canada Sunnybrook Health Sciences Centre TorontoON Canada

Introduction: Telehealth/remote assessment using readily available 2D mobile cameras and deep learning-based analyses is rapidly becoming a viable option for detecting orofacial and speech impairments associated with neurological and neurodegenerative disease during telehealth practice. However, the psychometric properties (e.g., internal consistency and reliability) of kinematics obtained from these systems have not been established, which is a crucial next step before their clinical usability is established. Methods: Participants were assessed in lab using a 3 dimensional (3D)-capable camera and at home using a readily-available 2D camera in a tablet. Orofacial kinematics was estimated from videos using a deep facial landmark tracking model. Kinematic features quantified the clinically relevant constructs of velocity, range of motion, and lateralization. In lab, all participants performed the same oromotor task. At home, participants were split into two groups that each performed a variant of the in-lab task. We quantified within-assessment consistency (Cronbach's α), reliability (intraclass correlation coefficient [ICC]), and fitted linear mixed-effects models to at-home data to capture individual-/task-dependent longitudinal trajectories. Results: Both in lab and at home, Cronbach's α was typically high (>0.80) and ICCs were often good (>0.70). The linear mixed-effect models that best fit the longitudinal data were those that accounted for individual- or task-dependent effects. Discussion: Remotely gathered orofacial kinematics were as internally consistent and reliable as those gathered in a controlled laboratory setting using a high-performance 3D-capable camera and could additionally capture individual- or task-dependent changes over time. These results highlight the potential of remote assessment tools as digital biomarkers of disease status and progression and demonstrate their suitability for novel telehealth applications. © 2022

关键词： Kinematics

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Complex Pythagorean Fuzzy Decision-Based Approach for Developing English Translation of the Scripture-Based Multiclustering Algorithms

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International Journal of Information Technology and Decision Making 2025年第2期24卷 473-533页

作者： Ahmed, Mohammed A. Zaidan, A.A. Qahtan, Sarah Alsattar, Hassan A. Zaidan, B.B. Mourad, Nahia Baharin, Hanif Kou, Gang Yatim, Khaironi Institute of IR 4.0 Universiti Kebangsaan Malaysia Bangi43600 Malaysia Network Engineering Department College of Engineering Al-Iraqia University Al Adhmia-Haiba Khaton Baghdad10053 Iraq SP Jain School of Global Management Lidcombe SydneyNSW2141 Australia Information Technology Unit College of Health and Medical Technology-Baghdad Middle Technical University Baghdad Iraq Research Center Mazaya University College Nasiriyah Iraq MEU Research Unit Middle East University Amman Jordan Faculty of Engineering and IT British University in Dubai Dubai United Arab Emirates School of Business Administration Faculty of Business Administration Southwestern University of Finance and Economics Chengdu611130 China Computer and Information Sciences Faculty of Sciences and Information Technology Universiti Teknologi PETRONAS Seri Iskandar32610 Malaysia

The English Translation of the Quran Tafsir (ETQT) is essential to understanding and interpreting Allah's words. Clustering is a common text mining technique for eliciting meaningful knowledge from a text collection. It is commonly used when the selected datasets lack typical ground truths. To the best of our knowledge, no study has evaluated and benchmarked ETQTs to select the most comprehensive and appropriate one. The process of evaluating and benchmarking ETQTs falls under the multicriteria decision-making (MCDM) problem because of different issues, namely, multiple internal clustering validation criteria, data variation, and trade-offs between different criteria. The fuzzy decision by opinion score method (FDOSM) is one of the most recommended MCDM ranking methods in the literature to address the said issues. FDOSM has been extended under different fuzzy set (FS) environments to address issues of uncertainty and vagueness caused by expert feedback subjectivity. Although prior versions of FDOSM improved the uncertainty and vagueness issues, they remain open issues. Therefore, this paper extended FDOSM into the complex Pythagorean fuzzy decision by opinion score method (CPFDOSM) to evaluate and benchmark ETQTs. The proposed method consists of two main phases. The first phase formulates decision-matrix-based cluster algorithms and internal cluster validation criteria. The second phase (CPFDOSM development) prioritizes ETQTs and selects the optimum one. Data generation is performed on five different cluster algorithms and six internal cluster validation criteria using 16 ETQTs based on three decision-makers (DMs). Results show the following: (1) 6.25% of the individual decision-making results are identical among the three DMs, whereas 93.75% (n = 15/16) are different when I = 0.5 and I = 2. When I = 0.5. In addition, T7 has consistent ranks (Rank=16) across all DMs, whereas T14 has consistent ranks (Rank=1) across all DMs when I = 1. (2) The results of the group de

关键词： Clustering algorithms

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STAF: Sinusoidal Trainable Activation Functions for Implicit Neural Representation

arXiv

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arXiv 2025年

作者： Morsali, Alireza Vaez, MohammadJavad Soltani, Hossein Kazerouni, Amirhossein Taati, Babak Mohammad-Noori, Morteza Department of Electrical Engineering McGill University Canada School of Mathematics Statistics and Computer Science University of Tehran Iran Department of Computer Science University of Toronto Canada Vector Institute Canada KITE Research Institute University Health Network Canada

Implicit Neural Representations (INRs) have emerged as a powerful framework for modeling continuous signals. The spectral bias of ReLU-based networks is a well-established limitation, restricting their ability to capture fine-grained details in target signals. While previous works have attempted to mitigate this issue through frequency-based encodings or architectural modifications, these approaches often introduce additional complexity and do not fully address the underlying challenge of learning high-frequency components efficiently. We introduce Sinusoidal Trainable Activation Functions (STAF), designed to directly tackle this limitation by enabling networks to adaptively learn and represent complex signals with higher precision and efficiency. STAF inherently modulates its frequency components, allowing for self-adaptive spectral learning. This capability significantly improves convergence speed and expressivity, making STAF highly effective for both signal representations and inverse problems. Through extensive evaluations, we demonstrate that STAF outperforms state-of-the-art (SOTA) methods in accuracy and reconstruction fidelity with superior Peak Signal-to-Noise Ratio (PSNR). These results establish STAF as a robust solution for overcoming spectral bias and the capacity-convergence gap, making it valuable for computer graphics and related fields. Our codebase is publicly accessible on the https://***/AlirezaMorsali/STAF. © 2025, CC BY.

关键词： Signal to noise ratio

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Implementation of Industrial Automation Sustainable Training in Savannakhet University, Laos 8

Implementation of Industrial Automation Sustainable Training...

引用

Joint 8th International Conference on Digital Arts, Media and Technology and 6th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2023

作者： Georgieva, Tsvetelina Bencheva, Nina Daskalov, Plamen Yahoui, Hamed Khemmarath, Sitha Norasane, Khonesavanh Chanthanouvong, Lamnguen Leaunglith, Youlananh Keovorabouth, Vinai University of Ruse Angel Kanchev Automation and Mechatronics Department Ruse Bulgaria University of Ruse Angel Kanchev Telecommunications Department Ruse Bulgaria Automation &processing Claude Bernard University Lyon 1 Department of Mechanical Engineering Lyon France Savannakhet University Faculty of Engineering Savannakhet Laos Savannakhet University Faculty of Information Technology Technology Computer Network Dept. Savannakhet Laos Savannakhet University Faculty of Information Technology Savannakhet Laos

ISBN: (纸本)9798350396546

The paper presents part of the work fulfilled under the Asean Factori 4.0 Erasmus+ project focused on the implementation of industrial automation in the education in 6 universities from 3 countries in South-East Asia: Thailand, Laos and Cambodia. The implementation of the project tasks, related to increasing the capacity and more precisely to the training of the professors from the Asian Universities is presented. According to the planned activities, professors from the University of Ruse conduct training for teachers from two universities: Chulalongkorn University, Thailand and Savannakhet University, Laos. The phases of training included in the project activities and how many of them have already been implemented are briefly presented. The program and the tasks of the teachers practical training for building the necessary teaching capacity in Savannakhet University and implementation of sustainable training in the field of industrial automation were presented and analyzed. Conclusions and future training of the staff of Asian universities planned under the project are presented in the paper. © 2023 IEEE.

关键词： Personnel training

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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Design and Performance of Resonant Beam Communications - Part I: Quasi-Static Scenario

arXiv

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arXiv 2024年

作者： Li, Dongxu Tian, Yuanming Huang, Chuan Liu, Qingwen Zhou, Shengli Future Network of Intelligence Institute the School of Science and Engineering the Chinese University of Hong Kong Shenzhen518172 China School of Science and Engineering the Future Network of Intelligence Institute the Chinese University of Hong Kong Shenzhen518172 China College of Electronics and Information Engineering Tongji University Shanghai201804 China Department of Electrical and Computer Engineering University of Connecticut StorrsCT06250 United States

This two-part paper studies a point-to-point resonant beam communication (RBCom) system, where two separately deployed retroreflectors are adopted to generate the resonant beam between the transmitter and the receiver, and analyzes the transmission rate of the considered system under both the quasi-static and mobile scenarios. Part I of this paper focuses on the quasi-static scenario where the locations of the transmitter and the receiver are relatively fixed. Specifically, we propose a new information-bearing scheme which adopts a synchronization-based amplitude modulation method to mitigate the echo interference caused by the reflected resonant beam. With this scheme, we show that the quasi-static RBCom channel is equivalent to a Markov channel and can be further simplified as an amplitude-constrained additive white Gaussian noise channel. Moreover, we develop an algorithm that jointly employs the bisection and exhaustive search to maximize its capacity upper and lower bounds. Finally, numerical results validate our analysis. Part II of this paper discusses the performance of the RBCom system under the mobile scenario. Copyright © 2024, The Authors. All rights reserved.

关键词： Transmitters

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Prediction Of Student Education Performance Using Googlenet Comparison With Over Alexnet Algorithm

Prediction Of Student Education Performance Using Googlenet ...

引用

International Conference on Computational and Characterization Techniques in engineering & Sciences (CCTES)

作者： Kotte. Venkata Rama Krishna V Parthipan Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Big Data and Network Security Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

An examination of the degree to which GoogleNet and Alexnet are accurate in predicting the academic success of students is the primary objective of this study. Each of the two groups that make up the program contains ten samples, and there are two groups altogether. For the purpose of determining the sample size, a threshold of 0.05%, a G-power pretest of 80%, and a confidence interval of 95% are utilized. We took into consideration the student education dataset that was available on *** and had a size of 66500. The method that was proposed was found to have an accuracy of 94.63% when compared to the existing system, which has an accuracy of only if. Furthermore, it demonstrates that there is a statistically significant difference between GoogleNet and Alexnet, with a value of p=0.001 (independent sample T test p<0.05) in the prediction of student educational performance using SPSS statistical analysis. When it comes to forecasting the academic success of students, the GoogleNet algorithm is more accurate than the Alexnet algorithm.

关键词： Accuracy Statistical analysis Instruments Education Artificial neural networks Prediction algorithms Forecasting Artificial intelligence

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The Role of Calcium in Non-Invasively Imaging Breast Cancer: An Overview of Current and Modern Imaging Techniques

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Critical Reviews in Biomedical engineering 2023年第5期51卷 43-62页

作者： Simmons, Lyndsay Feng, Lisa Fatemi-Ardekani, Ali Noseworthy, Michael D. Medical Physics and Applied Radiation Sciences McMaster University HamiltonON Canada Mohawk College Institute for Applied Health Sciences HamiltonON Canada Imaging Research Centre St. Joseph’s Healthcare Hamilton 50 Charlton Ave. E HamiltonON Canada Medical Physics Merit Health Southeast Cancer Network Canada Department of Physics Jackson State University United States Department of Electrical and Computer Engineering McMaster University 280 Main Street W. HamiltonON Canada School of Biomedical Engineering McMaster University HamiltonON Canada Department of Radiology McMaster University 1280 Main St. W HamiltonON Canada

The landscape of breast cancer diagnostics has significantly evolved over the past decade. With these changes, it is possible to provide a comprehensive assessment of both benign and malignant breast calcifications. The biochemistry of breast cancer and calcifications are thoroughly examined to describe the potential to characterize better different calcium salts composed of calcium carbonate, calcium oxalate, or calcium hydroxyapatite and their associated prognostic implications. Conventional mammographic imaging techniques are compared to available ones, including breast tomosynthesis and contrast-enhanced mammography. Additional methods in computed tomography and magnetic resonance imaging are discussed. The concept of using magnetic resonance imaging particularly magnetic susceptibility to characterize the biochemical characteristics of calcifications is described. As we know magnetic resonance imaging is safe and there is no ionization radiation. Experimental findings through magnetic resonance susceptibility imaging techniques are discussed to illustrate the potential for integrating this technique to provide a quantitative assessment of magnetic susceptibility. Under the right magnetic resonance imaging conditions, a distinct phase variability was isolated amongst different types of calcium salts. © 2023 by Begell House, Inc.

关键词： Magnetic susceptibility

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