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24th IEEE/ACIS International Conference on computer and Information Science, ICIS 2024

作者： Liapis, Charalampos M. Kyritsis, Konstantinos Perikos, Isidoros Paraskevas, Michael University of Patras Computer Technology Institute & Press 'Diophantus' Mathematics Dept. Patras26504 Greece University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece University of Patras Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press 'Diophantus' Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350376647

The Greek School Network (GSN) provides support to students, teachers, and school units in secondary education across Greece. Handling numerous user queries manually can be challenging, necessitating the development of an automated system for accurate categorization of these queries. This paper presents a comparative study of various transformer-based models for multi-class text categorization of Greek language queries submitted to the GSN helpdesk. We introduce a new experimental balanced dataset and extract vector representations from eleven transformer-based models. These representations are evaluated using ten classic machine learning classifiers. Our findings highlight the superior performance of the Multilingual E5 Text Embeddings model, particularly when paired with the extreme gradient-boosting classifier. This combination demonstrates a clear advantage in accurately categorizing user queries, paving the way for more efficient automated helpdesk systems. © 2024 IEEE.

关键词： Contrastive Learning

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A Sweeping Process Control Problem Subject To Mixed Constraints 22

A Sweeping Process Control Problem Subject To Mixed Constrai...

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22nd IFAC World Congress

作者： Cortez, Karla L. Khalil, Nathalie T. Solís, Julio E. Department of Mathematics Universidad Autónoma Metropolitana-Iztapalapa Mexico Department of Electrical and Computer Engineering University of Porto Portugal

ISBN: (纸本)9781713872344

In this study, we investigate optimal control problems that involve sweeping processes with a drift term and mixed inequality constraints. Our goal is to establish necessary optimality conditions for these problems. We address the challenges that arise due to the combination of sweeping processes and inequality mixed constraints in two contexts: regular and non-regular. This requires working with different types of multipliers, such as finite positive Radon measures for the sweeping term and integrable functions for regular mixed constraints. For non-regular mixed constraints, the multipliers correspond to purely finitely additive set functions. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： necessary optimality conditions optimal control theory regular and non-regular mixed constraints sweeping process

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Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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computer Modeling in engineering & Sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2025年第4期143卷 967-1008页

作者： Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar Computer Science Department University of M’silaIchebiliaM’sila28000Algeria Computer ScienceDepartment Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridjBordj BouArreridj34000Algeria Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Faculty of Mathematics Otto-von-Guericke UniversityMagdeburg39016Germany University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Electrical and Computer Engineering Shahid Beheshti UniversityTehran14399Iran DTU AI and Data Science Hub(DAIDASH) Duy Tan UniversityDa Nang550000Vietnam

Multi-objective optimization is critical for problem-solving in engineering,economics,and *** study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct *** approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto *** comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume *** paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关键词： Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance

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2025 IEEE Conference on Secure and Trustworthy Machine Learning, SaTML 2025

作者： Vithana, Sajani Cadambe, Viveck R. Calmon, Flavio P. Jeong, Haewon School of Engineering and Applied Sciences Harvard University United States School of Electrical and Computer Engineering Georgia Institute of Technology United States University of California Department of Electrical and Computer Engineering Santa Barbara United States

ISBN: (纸本)9798331517113

Differentially private distributed mean estimation (DP-DME) is a fundamental building block in privacy-preserving federated learning, where a central server estimates the mean of d-dimensional vectors held by n users while ensuring (ϵ, δ - DP. Local differential privacy (LDP) and distributed DP with secure aggregation (SA) are the most common notions of DP used in DP-DME settings with an untrusted server. LDP provides strong resilience to dropouts, colluding users, and adversarial attacks, but suffers from poor utility. In contrast, SA-based DP-DME achieves an O(n) utility gain over LDP in DME, but requires increased communication and computation overheads and complex multi-round protocols to handle dropouts and attacks. In this work, we present a generalized framework for DP-DME, that captures LDP and SA-based mechanisms as extreme cases. Our framework provides a foundation for developing and analyzing a variety of DP-DME protocols that leverage correlated privacy mechanisms across users. To this end, we propose CorDP-DME, a novel DP-DME mechanism based on the correlated Gaussian mechanism, that spans the gap between DME with LDP and distributed DP. We prove that CorDP-DME offers a favorable balance between utility and resilience to dropout and collusion. We provide an information-theoretic analysis of CorDP-DME, and derive theoretical guarantees for utility under any given privacy parameters and dropout/colluding user thresholds. Our results demonstrate that (anti) correlated Gaussian DP mechanisms can significantly improve utility in mean estimation tasks compared to LDP - even in adversarial settings - while maintaining better resilience to dropouts and attacks compared to distributed DP. © 2025 IEEE.

关键词： Differential privacy distributed mean estimation noise correlation

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Coupled effects of surface elasticity, couple stresses, and adhesion in nanocontact mechanics

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applied mathematics and Mechanics(English Edition) 2025年第07期46卷 1237-1260页

作者： Youxue BAN Xinyao YANG Q.X.LI Changwen MI Jiangsu Key Laboratory of Mechanical Analysis for Infrastructure and Advanced Equipment School of Civil Engineering Southeast University Department of Applied Mathematics Xi'an Jiaotong Liverpool University Department of Mathematics and Computer Science Fisk University

This paper investigates the adhesive nanocontact behavior of an elastic halfplane indented by a rigid cylindrical indenter, incorporating the simultaneous effects of surface elasticity, couple stresses, and adhesion. The free surface of the half-plane is modeled by the Steigmann-Ogden surface elasticity theory, while the bulk material behavior is described by the classical couple-stress elasticity theory. The adhesion at the contact interface is characterized by the Maugis-Dugdale(MD) adhesive contact model. Building on the fundamental nonclassical Flamant solution, the governing equations and boundary conditions of the nanocontact problem are reformulated into a system of triple integral equations. These equations are solved numerically by the Gauss-Chebyshev quadratures in combination with an iterative algorithm. The validation against the existing literature confirms the accuracy and robustness of the proposed solution methodology. Comprehensive parametric studies are performed to elucidate the critical roles of surface elasticity and couple stresses in adhesive nanocontact. The numerical results provide insights into the complex interactions among surface, couple-stress, and adhesive effects. Specifically, the interplay between the surface and adhesive effects is predominantly competitive, while the interaction between the couple stresses and adhesion exhibits an intricate *** findings highlight the necessity of simultaneously considering surface elasticity, couple stresses, and adhesion in nanoindentation analyses to achieve accurate predictions of material responses.

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Constant-Loop Dominators for Single-Path Code Optimization 21

Constant-Loop Dominators for Single-Path Code Optimization

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21st International Workshop on Worst-Case Execution Time Analysis, WCET 2023

作者： Maroun, Emad Jacob Schoeberl, Martin Puschner, Peter Institute of Computer Engineering TU Wien Vienna Austria Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

ISBN: (纸本)9783959772938

Single-path code is a code generation technique specifically designed for real-time systems. It guarantees that programs execute the same instruction sequence regardless of runtime conditions. Single-path code uses loop bounds to ensure all loops iterate a fixed number of times equal to their upper loop bound. When the lower and upper bounds are equal, the loop must iterate the same number of times, which we call a constant loop. In this paper, we present the constant-loop dominance relation on control-flow graphs. It is a variation of the traditional dominance relation that considers constant loops to find basic blocks that are always executed the same number of times. Using this relation, we present an optimization that reduces the code needed to manage single-path code. Our evaluation shows significant performance improvements, with one example of up to 90%, with mostly minor effects on code size. © Emad Jacob Maroun, Martin Schoeberl, and Peter Puschner.

关键词： Real time systems

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Fuzzy Intelligence Inventory Decision Optimization Model of Sustainability and Green Technologies for Mixed Uncertainties of Carbon Emission 9

Fuzzy Intelligence Inventory Decision Optimization Model of ...

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9th International Conference on Information Management, ICIM 2023

作者： Anand, M. Clement Joe Moorthy, C. Balakrishna Sivamani, S. Indrakumar, S. Kalaiarasi, K. Barhoi, Amir Department of Mathematics Karnataka Bengaluru India University of Technology & Applied Sciences Electrical Engineering Section Department of Engineering Salalah211 Oman Kongu Engineering College Department of Mathematics Tamil Nadu Erode India Department of Mathematics Tamil Nadu Tiruchirappalli India Duliajan College Department of Mathematics Assam India

ISBN: (纸本)9798350336382

In many areas, carbon cap-and-trade and carbon offsets are frequent and significant mechanisms for reducing carbon emissions. Furthermore, particular capital investments in green technologies can efficiently cut carbon emissions from corporate activities. However, such capital investments are expensive, and not all businesses/company can afford them. As a result, if all members of a supply chain agree to share facility investments, the supply chain can cut carbon emissions while also increasing profit. This study utilized crisp and fuzzy models to fix perishable products in the production process. The suggested model, for study is solved using python in machine learning. To cut carbon emissions and increase the total value of the supply chain system, we planned to integrate manufacturing, distribution, replenishment, and technology. Several cases are simulated, and the key parameters are subjected to sensitivity analysis. Under various carbon emission rules, the optimal solutions and joint total profit are also compared. Companies should be able to share risks by co-investing and building sustainable supply chains as a part of the future carbon emission control trend. © 2023 IEEE.

关键词： Python

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A Measurement based Predictive Maintenance Algorithm for Rigid-Body Dynamical Systems using Radial Basis Function Approximation and Information Theory 27

A Measurement based Predictive Maintenance Algorithm for Rig...

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27th International Conference on System Theory, Control and Computing, ICSTCC 2023

作者： Ortmann, Jan Ortmann, Mathis Department of Electrical Engineering and Computer Science University of Siegen Germany Department of Mathematics Justus Liebig University of Giessen Germany

ISBN: (纸本)9798350337983

This paper presents new viewpoints to solve predicative maintenance problems for arbitrarily rigid-body mechanical systems. Reliable predictions for changes in physical parameters are highly dependent on system model accuracy. Hence, costs for physical system modeling are expensive and time-consuming. To overcome this problem, we replaced the modeling process with a full measurement based procedure in conjunction with radial basis functions (RBF) approximation to create the system model. Subsequently, information theory is employed to generate a meaningful metric quantity that reports about the changes in physical parameters. A rigid-body mechanical system is used as an example to verify the presented theory. © 2023 IEEE.

关键词： Radial basis function networks

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New Delay Doppler Communication Paradigm in 6G Era:A Survey of Orthogonal Time Frequency Space(OTFS)

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China Communications 2023年第6期20卷 1-25页

作者： Weijie Yuan Shuangyang Li Zhiqiang Wei Yuanhao Cui Jiamo Jiang Haijun Zhang Pingzhi Fan Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhenChina Faculty of Electrical Engineering and Computer Science Technical University of BerlinBerlinGermany School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’anChina Department of Communication Engineering Beijing University of Posts and TelecommunicationsBeijingChina China Academy of Information and Communications Technology BeijingChina School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina School of Information Science and Technology Southwest Jiaotong UniversityChengduChina

In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile *** such conditions,conventional orthogonal frequency division multiplexing(OFDM)modulation,widely employed in cellular and Wi-Fi communication systems,experiences performance degradation due to significant Doppler *** overcome this obstacle,a novel twodimensional(2D)modulation approach,namely orthogonal time frequency space(OTFS),has emerged as a key enabler for future high-mobility use ***,OTFS modulates information within the delay-Doppler(DD)domain,as opposed to the timefrequency(TF)domain utilized by *** offers advantages such as Doppler and delay resilience,reduced signaling latency,a lower peak-to-average ratio(PAPR),and a reduced-complexity *** studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications(ISAC).In this article,we present an in-depth review of OTFS technology in the context of the 6G era,encompassing fundamentals,recent advancements,and future *** objective is to provide a helpful resource for researchers engaged in the field of OTFS.

关键词： OTFS 6G delay-Doppler(DD)domain

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