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Proceedings of the 2023 12th International Conference on Software and Information Engineering

作者： Amira Olayan Albashir Adel Youssef Mohamed Samir Abou El-Seoud Faculty of Informatics and Computer Science The British University (BUE) Egypt Department of Electronics and Communication Engineering Arab Academy for Science Technology and Maritime Transport Egypt

ISBN: (纸本)9798400708107

Wireless Body Area Networks have severe challenges in energy management to enhance the longevity of the system. Specifically, for a WBAN system that operates by ambient energy sources. The system combines energy scavenging modules integrated into the sensors carried by patients, enabling data transmission to a personal device. Our approach does not rely on previous information as the characteristics of the scavenged and consumed energy are stochastic. To optimize user utility, a formulation of an optimization problem by employing the Grey Wolf Optimization technique (GWO) compared to previous works that used different optimization techniques, to decompose it into three sub-problems: battery management, collecting rate control, and transmission power allocation. To achieve our goals, we apply the GWO to the introduced online resource allocation algorithm that serves two primary purposes: (1) balancing energy scavenging and consumption of network nodes to ensure system stability, and (2) maximizing user utility. Through simulation results, we validate the effectiveness and optimization capabilities of the algorithm while applying a different optimization technique from the previous works maintained.

关键词： Energy management GWO WBAN

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HOMOCLINIC SOLUTIONS OF NONLINEAR LAPLACIAN DIFFERENCE EQUATIONS WITHOUT AMBROSETTI-RABINOWITZ CONDITION

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Acta Mathematica Scientia 2021年第3期41卷 712-718页

作者： Antonella NASTASI Stepan TERSIAN Calogero VETRO University of Palermo Department of Mathematics and Computer ScienceVia Archirafi 3490123PalermoItaly Institute of Mathematics and Informatics Bulgarian Academy of Sciences1113 SofiaBulgaria

The aim of this paper is to establish the existence of at least two non-zero homoclinic solutions for a nonlinear Laplacian difference equation without using AmbrosettiRabinowitz type-conditions. The main tools are mo... 详细信息

关键词： Difference equations homoclinic solutions non-zero solutions (p,q)-Laplacian operator

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KnowSOntoWSR: Web Service Recommendation System Using Semantically Driven QoS Ontology-Based Knowledge-Centred Paradigm 1

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7th International Conference on Internet of Things and Connected Technologies, ICIoTCT 2022

作者： Dhanvardini, R. Deepak, Gerard Priyadarshini, J. Sheeba Santhanavijayan, A. Healthcare Informatics Division Optum UnitedHealth Groups Hyderabad India Department of Computer Science Engineering National Institute of Technology Tiruchirappalli India Department of Data Science Manipal Institute of Technology Bengaluru Bengaluru India Department of Data Science Manipal Academy of Higher Education Manipal India Bangalore India

ISBN: (数字)9789811997198

ISBN: (纸本)9789811997181

Web services have significantly expanded and become a key enabling technology for online data, application and resource sharing. Designing new methods for efficient and reliable web service recommendation has been of tremendous importance with the growing usage and prominence of web services. It would be ideal for a system to suggest online services that are in line with consumers’ preferences without requesting specific query information from them. Quality of Service (QoS) is vital for characterising non-functional aspects of Web services as they become more prevalent and widely used on the World Wide Web. The KnowSOntoWSR framework, which is built on a knowledge-driven and semantically inclined model that adheres to QoS ontology, is proposed in this research. AWS and WebSphere are employed as knowledge tags, and the powerful machine learning classifier XGBoost is applied. The features and recommendations are computed using the Twitter semantic similarity. The proposed framework outperforms the baseline models’ estimates with an accuracy of 95.94% and average F-measure of 95.93%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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SEMU: Singular Value Decomposition for Efficient Machine Unlearning

arXiv

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arXiv 2025年

作者： Sendera, Marcin Struski, Lukasz Ksiazek, Kamil Musiol, Kryspin Tabor, Jacek Rymarczyk, Dawid Faculty of Mathematics and Computer Science Jagiellonian University Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Poland Ardigen SA Poland

While the capabilities of generative foundational models have advanced rapidly in recent years, methods to prevent harmful and unsafe behaviors remain underdeveloped. Among the pressing challenges in AI safety, machine unlearning (MU) has become increasingly critical to meet upcoming safety regulations. Most existing MU approaches focus on altering the most significant parameters of the model. However, these methods often require fine-tuning substantial portions of the model, resulting in high computational costs and training instabilities, which are typically mitigated by access to the original training dataset. In this work, we address these limitations by leveraging Singular Value Decomposition (SVD) to create a compact, low-dimensional projection that enables the selective forgetting of specific data points. We propose Singular Value Decomposition for Efficient Machine Unlearning (SEMU), a novel approach designed to optimize MU in two key aspects. First, SEMU minimizes the number of model parameters that need to be modified, effectively removing unwanted knowledge while making only minimal changes to the model’s weights. Second, SEMU eliminates the dependency on the original training dataset, preserving the model’s previously acquired knowledge without additional data requirements. © 2025, CC BY.

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Deep Learning Technology using New Media on Traditional Arts and Crafts of Complex Forms 6

Deep Learning Technology using New Media on Traditional Arts...

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6th International Conference on Trends in Electronics and informatics, ICOEI 2022

作者： Pandey, Amit Janga, Vijaykumar Aweke Wako, Desalegn Senbato Genale, Assefa Sundaram, B.Barani Karthika, P. College of Informatics Bule Hora University Bule Hora Ethiopia Bule Hora University Department of Computer Science Ethiopia Kalasalingam Academy of Research and education Krishnankoil India

ISBN: (纸本)9781665483285

In the age of computer technology, new media art Technology has grown rapidly. The technology comprises virtual art, animation, digital art, computer graphics, 3D Art, sound art, video games, robotics, internet art, 3Dpaintings, and 3D printing. The new media art Technology creates a lot of new jobs and also major universities offer courses and graduate programs in this field. The new media art Technology will not affect the traditional arts as critics say. Today there is a need for new media art. Everything has been digitalized by every business the digital media platforms social media video sharing video other internet Technologies for marketing. Digital marketing has replaced marketing techniques to a great extent. In this research article, we are going to study how the new media and deep learning Technology influences traditional arts and crafts in complex forms. For example, ceramic arts and potteries are traditional arts and crafts in complex forms. Ceramic arts and crafts and pottery are popular cultures and heritage symbols in many civilizations. This form of art for handmade traditionally involves a lot of painstaking effort in manufacturing. In this study, we are going to see how the new media art Technology is going to help in creating complex art forms with ease. The new media art Technology makes use of 3D printing technology to carry out this task. Deep learning is referred to as a type of machine learning Technology that uses artificial neural networks layers processing. Thus we found various advantages of new media art in the manufacturing of complex art forms like ceramic art pottery etc. In this research Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) Algorithm is executed to analyze the presentation of the traditional arts and crafts learning with the aid of new media technology. © 2022 IEEE.

关键词： Deep learning

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Algebraic Proof Theory for Infinitary Action Logic

arXiv

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arXiv 2025年

作者： Fussner, Wesley Santschi, Simon Miranda, Borja Sierra Institute of Computer Science of the Czech Academy of Sciences Czech Republic Institute of Mathematics University of Bern Switzerland Institute of Informatics University of Bern Switzerland

We exhibit a uniform method for obtaining (wellfounded and non-wellfounded) cut-free sequent-style proof systems that are sound and complete for various classes of action algebras, i.e., Kleene algebras enriched with meets and residuals. Our method applies to any class of ∗-continuous action algebras that is defined, relative to the class of all ∗-continuous action algebras, by analytic quasiequations. The latter make up an expansive class of conditions encompassing the algebraic analogues of most well-known structural rules. These results are achieved by wedding existing work on non-wellfounded proof theory for action algebras with tools from algebraic proof *** Codes 03F05 (Primary) 03F52, 68Q70 (Secondary) © 2025, CC BY.

关键词： Algebra

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Secure Blockchain Integration Approach for Knowledge Discovery in Industrial Internet of Things

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the Communications Society 2025年 6卷 4772-4787页

作者： Rohan Tripathi Ritam Rao Vivekananda Bhat K. Abhishek Kumar Pandey Ashok Kumar Das Department of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Department of Computer Science and Engineering College of Informatics Korea University Seoul South Korea

The field of Industrial Internet of Things (IIoT) is now being duly recognized as a revolutionary area in industrial automation. With the budding interest of knowledge discovery that helps the businesses in applying technology on a large scale, researchers are now faced with several major security concerns. Blockchain integration is one of the suggested applications of technology that could help secure the data during transmission, storage, and knowledge discovery. Moreover, by integrating smart contracts, a secure architecture could also assimilate accountability during data exchange. Thus, we propose a four-layer security architecture that isolates IIoT devices from user-oriented layers and maintains a record of all IIoT devices registered in the organization to prevent malicious devices from corrupting the database and discovery process. Further, by choosing proof of authority (PoA), we ensure the fair functioning of the Blockchain nodes. Through proxy re-encryption for clients, PoA consensus for Blockchain nodes, and Whitelist-based access control for IIoT Devices, we ensure the legitimacy of all participating nodes. We also implement a prototype using a private Ethereum network with proof of authority consensus and present the time taken for the entire exchange and the gas (ethereum currency) consumed per exchange by the contracts. Also we implemented the secure knowledge discovery to understand the significance of the developed scheme. The results show that the exchange can be implemented in an IIoT environment and work with a reasonable amount of resource consumption.

关键词： Blockchains Industrial Internet of Things computer architecture Security Knowledge discovery computer science Cloud computing Prototypes Authentication Analytical models

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Decomposition of Differences of Independent and Identically Distributed Random Variables

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Moscow University Computational Mathematics and Cybernetics 2025年第1期49卷 67-72页

作者： Ushakov, V. G. Ushakov, N. G. Department of Computational Mathematics and Cybernetics Moscow State University Moscow Russia Institute of Informatics Problems Federal Research Center ‘‘Computer Science and Control’’ Russian Academy of Sciences Moscow Russia Norwegian University of Science and Technology Trondheim Norway

The authors consider conditions where the distribution of the components of the difference between two independent identically distributed random variables can be uniquely reconstructed with an accuracy of up to a shift and reflection. This uniqueness is essential for solving a number of characterization problems in mathematical statistics. An algorithm for estimating the components is presented for when data are given in a symmetrized form.

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Implementation of a Convolution Algorithm to the Evaluation of Stationary Characteristics of Resource Loss System with Resource-Dependent Service Times 1

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23rd International Conference on Information Technologies and Mathematical Modelling, ITMM 2024

作者： Nazarin, Artem Sopin, Eduard Moscow Russia Institute of Informatics Problems Federal Research Center Computer Science and Control of Russian Academy of Sciences Moscow Russia

ISBN: (数字)9783031883071

ISBN: (纸本)9783031883064

In this paper, a multi-server resource loss system with resource requirement-dependent service times is considered. We develop a convolutional algorithm for the evaluation of the stationary probability distribution and various system characteristics, such as the loss probability and the average volume of occupied resources. In the case study, we calculate these characteristics under the assumption of the Erlang distribution for the service time and several distributions for the resource requirements. We also compare the execution time of the developed convolution algorithm with direct calculations of probabilistic measures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Normal distribution

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Self-Timed Pipeline with Variable Stage Number*

Self-Timed Pipeline with Variable Stage Number*

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Networks, Circuits and Systems (NCS), Seminar on

作者： Igor A. Sokolov Yuri V. Rogdestvenski Yuri A. Stepchenkov Denis Y. Diachenko Yuri G. Diachenko Leonid P. Plekhanov Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia Institute of Informatics Problems Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia

The paper analyzes the problem of improving the self-timed pipeline’s performance. The paper considers possible options for reducing the pipeline latency by decreasing the number of actively operating stages when certain conditions occur, determined by the processed data value or an external signal. One stage bypassing becomes appropriate if it occurs in at least 64% of data processing operations, while two stage bypassing decreases the average pipeline latency if it occurs in 50% of operations.

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