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International Conference on Inventive computing and Informatics (ICICI)

作者： J. Relin Francis Raj U. Karthikeyan R. Santhana Krishnan G. Vinoth Rajkumar Sincy Elezebeth Kuruvilla Sakthidevi. I Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computing Technologies School of Computing College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication & Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Electronics and Communication Engineering J.P. College of Engineering Thenkasi India Department of Electrical and Electronics Engineering RajaRajeswari College of Engineering Bengaluru India Department of Information Technology Adhiyamaan College of Engineering Hosur India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

Dynamic energy management and carbon footprint mitigation in residential communities are crucial for achieving sustainability goals. This research presents a novel algorithm, termed EnerGAIN, which integrates Bayesian Optimization and Random Forests within an AI and IoT framework. EnerGAIN aims to optimize energy consumption patterns while reducing carbon emissions in residential settings. Simulation analyses were conducted to evaluate the performance of EnerGAIN compared to existing algorithms. Key simulation metrics including energy efficiency, carbon footprint reduction, and predictive accuracy were utilized for comparison. Results demonstrate that EnerGAIN outperforms existing algorithms in terms of energy optimization and carbon footprint reduction, showcasing its effectiveness in promoting sustainable energy practices in residential communities. This research contributes to the advancement of AI and IoT-driven solutions for dynamic energy management and carbon footprint mitigation, offering promising avenues for fostering environmentally conscious behaviors in residential settings.

关键词： Energy consumption Machine learning algorithms Prevention and mitigation Heuristic algorithms Prediction algorithms Energy efficiency Internet of Things

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Formation of Ethane by Activation of Methane on B, N Co-Doped Graphene Surface Decorated by Ir13 Cluster: A First Principle Study

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SSRN 2023年

作者： Damte, Jemal Yimer Hailu, Yohannes Mulugeta Cammarata, Antonio Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Technicka 2 Prague 616627 Czech Republic Department of Chemical Engineering National Taiwan University of Science and Technology Section 4 Keelung Road Da’an District Taipei10607 Taiwan

The most critical processes in designing a potential catalyst for the production of ethane are activating methane and suppressing further dehydrogenation. In the present study, using first- principle calculations, we predict that the BNG-Ir13 cluster can efficiently activate methane and promote the CC coupling reactions. Ir in the BNG-Ir13 cluster's top site is found to be the most stable adsorption site of methane with stable adsorption energy of -0.45 eV. Methane is activated with a low activation energy barrier of 0.16 eV, and the reaction energy is -0.54 eV. It is the most facile step and is thermodynamically favorable, likely to occur at low-temperature conditions. The fourth dehydrogenation step is the rate-determining step, which shows the highest activation energy barrier (1.24 eV) in the methane dehydrogenation process on the BNG- Ir13 cluster. Based on the DFT calculations, selective dehydrogenation of methane and self- coupling reactions of methyl groups formed ethane with a low kinetic barrier assisted by the BNG-Ir13 cluster. Furthermore, hydrogen molecules are likely to form, implying that the BNG- Ir13 cluster is a potential and bi-functional catalyst in selective conversion of methane to ethane and in the production of hydrogen molecules at optimum conditions. © 2023, The Authors. All rights reserved.

关键词： Dehydrogenation

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Editorial:Special Topic on Federated Learning for IoT and Edge computing

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ZTE Communications 2022年第3期20卷 1-2页

作者： PAN Yi CUI Laizhong CAI Zhipeng LI Wei Faculty of Computer Science and Control Engineering at Shenzhen Institute of Advanced Technology Chinese Academy of SciencesChina the Academy of the United Nations Sciences and Technology Organization Ukrainian Academy of Engineering Sciences American Institute for Medical and Biological Engineering Institute of Engineering Technology the College of Computer Science and Software Engineering at Shenzhen University China Department of Computer Science and the College of Business at Georgia State University USA the Center for Distributed and High Performance Computing School of Computer ScienceThe University of Sydney the Australia-China Joint Research Center on Energy Informatics and Demand Response Technologies

Recent years have witnessed the proliferation of Internet of Things(IoT),in which billions of devices are connected to the Internet,generating an overwhelming amount of *** is challenging and infeasible to transfer an... 详细信息

关键词： cloud generating data.

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Influence of Applied Tensile/Compressive Stress on He-Irradiated SiC: Examining Defect Evolution Through Experimental Investigation and DFT Simulations

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SSRN 2024年

作者： Liu, Chun Daghbouj, Nabil Zhang, Chao Wu, Zhongzheng Cheng, Wei Polcar, Tomas Li, Bingsheng School of Materials Science and Engineering Anhui University of Science and Technology Huainan232001 China Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Technická Prague 6216000 Czech Republic State Key Laboratory for Environment Friendly Energy Materials Southwest University of Science and Technology Mianyang621010 China College of Nuclear Science and Technology Beijing Normal University Beijing100875 China

In reactor environments, structural materials experience mechanical strain, and understanding how this strain affects defect generation is crucial for predicting microstructural evolution and damage accumulation. A study on He irradiation into SiC at 750°C (1 x 1017 He/cm2) demonstrated that platelet formation is dependent on strain. Tensile stress promotes platelet growth, while compression slows it down. Density functional theory (DFT) simulations confirmed that under tensile strain, carbon vacancies (Cv) and He atoms have low energy barriers for migration, facilitating platelet growth in line with experimental observations. This research has significant implications for SiC applications in nuclear structural materials, where it is important to avoid tensile strain. However, in the context of semiconductor thin film transfer (Smart-cut), He implantation under tensile stress can be advantageous, as it allows for lower He fluence and reduces the cost of the operation. © 2024, The Authors. All rights reserved.

关键词： Silicon carbide

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Terrain prickliness: Theoretical grounds for high complexity viewsheds 11

Terrain prickliness: Theoretical grounds for high complexity...

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11th International Conference on Geographic Information science - Part II, GIscience 2021

作者： Acharyya, Ankush Jallu, Ramesh K. Löffler, Maarten Meijer, Gert G.T. Saumell, Maria Silveira, Rodrigo I. Staals, Frank Czech Academy of Sciences Institute of Computer Science Prague Czech Republic Deptartment of Information and Computing Sciences Utrecht University Netherlands Academy of ICT and Creative Technologies NHL Stenden University of Applied Sciences Netherlands Department of Theoretical Computer Science Faculty of Information Technology Czech Technical University in Prague Czech Republic Department of Mathematics Universitat Politècnica de Catalunya Barcelona Spain Department of Information and Computing Sciences Utrecht University Netherlands

ISBN: (纸本)9783959772082

An important task in terrain analysis is computing viewsheds. A viewshed is the union of all the parts of the terrain that are visible from a given viewpoint or set of viewpoints. The complexity of a viewshed can vary significantly depending on the terrain topography and the viewpoint position. In this work we study a new topographic attribute, the prickliness, that measures the number of local maxima in a terrain from all possible angles of view. We show that the prickliness effectively captures the potential of terrains to have high complexity viewsheds. We present near-optimal algorithms to compute it for TIN terrains, and efficient approximate algorithms for raster DEMs. We validate the usefulness of the prickliness attribute with experiments in a large set of real terrains. © Ankush Acharyya, Ramesh K. Jallu, Maarten Löffler, Gert G.T. Meijer, Maria Saumell, Rodrigo I. Silveira, and Frank Staals;licensed under Creative Commons License CC-BY 4.0

关键词： Landforms

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Data analysis using neural networks and Kohonen maps in a comparative perspective

Data analysis using neural networks and Kohonen maps in a co...

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Innovative computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Ksenia Degtyareva Aleksey Borodulin Tatiana Soloveva Vladimir Nelyub Vladislav Kukartsev Department of Information Economic System Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Informatics Artificial Intelligence and Control Systems Faculty Bauman Moscow State Technical University Moscow Russia Department of Systems Analysis and Operations Research Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow Russia

This paper discusses two powerful methods of data analysis, neural networks and self-organising Kohonen maps. The main emphasis is on the importance of correct data preparation before analysis. Their impact on the accuracy and quality of research results is analysed. The paper provides deep insight into the effective application of these techniques in various data analysis scenarios.

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COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

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Computers, Materials & Continua 2021年第7期68卷 391-407页

作者： Aqib Ali Wali Khan Mashwani Samreen Naeem Muhammad Irfan Uddin Wiyada Kumam Poom Kumam Hussam Alrabaiah Farrukh Jamal Christophe Chesneau Department of Computer Science Concordia College BahawalpurBahawalpur63100Pakistan Department of Computer Science&IT Glim Institute of Modern StudiesBahawalpur63100Pakistan Institute of Numerical Sciences Kohat University of Science&TechnologyKohat26000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Program in Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiThanyaburi12110Thailand Departments of Mathematics Faculty of ScienceCenter of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research LaboratoryRoom SCL 802 Fixed Point LaboratoryScience Laboratory BuildingKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand Department of Medical Research China Medical University HospitalTaichung40402Taiwan College of Engineering Al Ain UniversityAl Ain64141United Arab Emirates Department of Mathematics Tafila Technical UniversityTafila66110Jordan Department of Statistics The Islamia University of BahawalpurBahawalpur63100Pakistan 11Department of MathematicsUniversitéde CaenLMNOCaen14032France

The purpose of this research is the segmentation of lungs computed tomography(CT)scan for the diagnosis of COVID-19 by using machine learning *** dataset contains data from patients who are prone to the *** contains three types of lungs CT images(Normal,Pneumonia,and COVID-19)collected from two different sources;the first one is the Radiology department of Nishtar Hospital Multan and Civil Hospital Bahawalpur,Pakistan,and the second one is a publicly free available medical imaging database known as *** the preprocessing,a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest(ROIs)and acquire 52 hybrid statistical features for each ***,12 optimized statistical features are selected via the chi-square feature reduction *** the classification,five machine learning classifiers named as deep learning J4,multilayer perceptron,support vector machine,random forest,and naive Bayes are deployed to optimize the hybrid statistical features *** is observed that the deep learning J4 has promising results(sensitivity and specificity:0.987;accuracy:98.67%)among all the deployed *** a complementary study,a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.

关键词： COVID-19 machine learning fuzzy c-mean deep learning J4

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Towards Narrowing the Search in Bounded-Suboptimal Safe Interval Path Planning 14

Towards Narrowing the Search in Bounded-Suboptimal Safe Inte...

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14th International Symposium on Combinatorial Search, SoCS 2021

作者： Rybecky, Tomas Kulich, Miroslav Andreychuk, Anton Yakovlev, Konstantin Department of Cybernetics Faculty of Electrical Engineering Czech Technical University Czech Republic Czech Institute for Informatics Robotics and Cybernetics Czech Technical University Czech Republic Federal Research Center for Computer Science and Control of Russian Academy of Sciences Russia Russia National Research University Higher School of Economics Russia

ISBN: (纸本)9781713834557

Path planning in the presence of dynamic obstacles is challenging as the time dimension has to be considered. A prominent approach to tackle this problem known to be complete and optimal is the A*-based Safe-interval Path Planning (SIPP). Bounded-suboptimal variants of SIPP employing the ideas of Weighted A* (WSIPP) and Focal Search (FocalSIPP) have been introduced recently, trading-off optimality for decreased planning time. In this paper, we revisit FocalSIPP and design several secondary heuristics for Focal Search with the intention to narrow the search in the direction of a preplanned optimal single-agent path not considering dynamic obstacles. The experimental results on various maps show that the designed heuristics generally outperform the hops-to-the-goal heuristic used in the original FocalSIPP and successfully compete with WSIPP as well. Copyright © 2021, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Motion planning

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Multi-method analysis of emotional and affective states

Multi-method analysis of emotional and affective states

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Progress in Applied Electrical Engineering (PAEE)

作者： Adrian Luckiewicz Bogdan Ruszczak Mariusz Pelc Dariusz Mikołajewski Adam Sudoł Barbara Grochowicz Edward J. Gorzelanczyk Patryk Mendon Aleksandra Kawala-Sterniu Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science University of Opole Opole Poland School of Computing and Mathematical Sciences University of Greenwich London UK Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Neuropsychological Research Unit 2nd Clinic of the Psychiatry and Psychiatric Rehabilitation Medical University in Lublin Lublin Poland Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

ISBN: (数字)9798331527563

ISBN: (纸本)9798331527570

This study explores the neurological basis of emotions using a multi-method approach, analysing functional near-infrared spectroscopy (fNIRS) data obtained from a 26-channel device. Author’s primary objective was to examine the brain’s response to tasks that provoke emotional, imagery and affective reactions through the observation of hemodynamic changes in data. By applying data processing methods and techniques, cerebral activations corresponding to different emotional states were shown. This research enriches comprehension of how emotion and imagery tasks are processed by the brain and offers insights into aspects of brain activity during emotionally charged engagements.

关键词： Electrical engineering Brain Data processing Hemodynamics Functional near-infrared spectroscopy

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Eight-Element MIMO Antenna with Closely Spaced Loop Resonators for THz and 6G Systems

Eight-Element MIMO Antenna with Closely Spaced Loop Resonato...

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National Conference on Radio science (NSRC)

作者： Naser Ojaroudi Parchin Ahmed S.I. Amar Sherif A. Khaleel Mohamed S. Soliman Ming Shen School of Computing Engineering & the Built Environment Edinburgh Napier University Edinburgh UK Egyptian Technical Research and Development Centre Cairo Egypt Arab Academy for Science Technology and Maritime Transport Aswan Egypt Department of Electrical Engineering College of Engineering Taif University Taif Saudi Arabia Department of Electrical Engineering Faculty of Energy Engineering Aswan University Aswan Egypt Department of Electronic Systems Aalborg University Aalborg Denmark

ISBN: (数字)9798331535261

ISBN: (纸本)9798331535278

This study proposes an innovative terahertz (THz) MIMO antenna architecture comprising four pairs of loop elements, strategically positioned at the four corners of a low-profile Rogers 5880 substrate with dimensions of $155\times 155\ \mu \mathrm{m}^{2}$ . Each corner integrates closely spaced L-ring/loop resonators, designed to ensure minimal mutual coupling and maintain satisfactory isolation between adjacent elements. The antenna is optimized to operate efficiently within the 4.4–5.2 THz frequency range, offering polarization diversity and enhanced radiation coverage, which are critical for achieving seamless and robust connectivity in high-frequency communication systems. Extensive full-wave simulations have been carried out to evaluate key performance metrics such as gain, efficiency, isolation, and radiation patterns. The results demonstrate the antenna's strong potential for integration into future 6G and THz wireless platforms, where compactness, efficiency, and wide coverage are essential requirements.

关键词： 6G mobile communication Mutual coupling Resonant frequency Terahertz radiation Reliability Resonators Gain Substrates Next generation networking Terahertz communications

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