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11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021

作者： Shao, Chang Zhao, Qi Shi, Yuhui Jiang, Jing Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Faculty of Engineering and Information Technology University of Technology Sydney Ultimo Australia School of Computer Science and Technology University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9783030720612

Dynamic multi-objective optimization (DMO) has recently attracted increasing interest. Suitable benchmark problems are crucial for evaluating the performance of DMO solvers. However, most of the existing DMO benchmarks mainly focus on Pareto-optimal solutions (PS) varying on the hyperplane, which may produce some unexpected bias for algorithmic analysis. Furthermore, they do not comprehensively consider the general time-linkage property, yet which is commonly observed in real-world applications. To alleviate these two issues, we designed a generalized test suite (GTS) for DMO with the following two advantages over previous existing benchmarks: 1) the PS can change on the hypersurface over time, to better compare the tracking ability of different DMO solvers;2) the general time-linkage feature is included to systemically investigate the algorithmic robustness in the dynamic environment. Experimental results on five representative DMO algorithms demonstrated the proposed GTS can efficiently discriminate the performance of DMO algorithms and is more general than existing benchmarks. © 2021, Springer Nature Switzerland AG.

关键词： Pareto principle

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Mining fuzzy local periodic activity pattern for Smart home applications

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Knowledge-Based Systems 2024年 293卷

作者： Iqbal, Mohammad Prayitno, Adila Sekarrati Dwi Pao, Hsing-Kuo Mukhlash, Imam Department of Mathematics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Sukolilo East Java Surabaya60111 Indonesia Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei106 Taiwan

Perceiving resident movements from ubiquitous sensor devices can aid health and safety management in smart home environment. One can find resident movement patterns to get notification about what should be aware of to prepare for possible accidents. The goal of this work is to propose a method to search for periodic residents’ activity patterns given smart home applications. Specifically, the proposed method is aimed to capture fuzzy local periodic activity patterns (FLPAP) from the smart home data. A FLPAP is an activity pattern that periodically occurs for a particular duration in fuzzy time intervals. We construct an algorithm to help to find the FLPAP called Fuzzy Local Periodic Activity Pattern Miner (FLoPMiner). On the side, a parameter called k-scale period is well-chosen to reorganize the data to make it suitable for the need of periodic activity pattern mining. The proposed method was demonstrated for its effectiveness on a public smart home dataset. After all, we successfully retrieved periodic resident activity patterns, which can be applied to self-health management systems, especially when focusing on a precise scale period. Overall, the proposed method shows descent pattern representation against the state-of-the-art methods of the same category. © 2024 Elsevier B.V.

关键词： Automation

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Subjective weight determination methods in multi-criteria decision-making: a systematic review

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Procedia computer science 2024年 246卷 5396-5407页

作者： Bartłomiej Kizielewicz Tomasz Tomczyk Michał Gandor Wojciech Sałabun National Institute of Telecommunications National Research Institute ul. Szachowa 1 04-894 Warsaw Poland Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 31-155 Krakow Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. żołnierska 49 71-210 Szczecin Poland

The determination of weights is a critical step in Multi-Criteria Decision-Making (MCDM) processes, and subjective methods play a significant role in this area. This paper provides a comprehensive review of subjective weight determination methodologies, focusing primarily on sources from the Scopus database. Through a systematic literature review, this study analyzes 33,434 publications related to subjective weight determination, providing insights into the trends, advancements, and applications of these methodologies. The review underscores the importance of expert knowledge in contemporary decision-making and suggests potential areas for future research, including the integration of subjective methods with emerging technologies and the development of more robust and consistent weighting frameworks. This paper aims to serve as a valuable resource for researchers and practitioners in the field of MCDM, offering a detailed overview of the current state of subjective weight determination methods and their practical implications.

关键词： Subjective weighting AHP BWM DEMATEL MCDM MCDA Mutli-criteria

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Text steganography in webometrics

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International Journal of information technology (Singapore) 2021年第2期13卷 621-635页

作者： Yaghobi, Shabnam Rahber Sajedi, Hedieh Faculty of Computer and Information Technology Engineering Qazvin Branch Islamic Azad University Qazvin Iran Department of Computer Science School of Mathematics Statistics and Computer Science College of Science University of Tehran Tehran 14155-6455 Iran

In the age of technology and science advancement, even powerful governments are not immune from hackers and spies’ influence. Their most important and sensitive information is always being heard and subject to disclosure. Steganography is one of the main ways to improve security and data protection when transferring data over the Web. Steganography’s primary purpose is to convey messages in communication channels through text, image, audio, and video. From the above media, the text files usually use less memory for storage. Text-based steganography methods can be used in Web page texts and plain texts. In Web, the possibility of broadcasting texts (e.g., HTML codes and Hashtags in Social networks) with and without hidden information is the same. It means that the provided steganography system has high security and a Web pages’ viewer cannot realize what hidden information has been transmitted. To hide text, one can refer to the various methods, such as blank space, feature repetition, and the arrangement of elements on Web pages. In these methods, the secret message is hidden using the Web pages’ properties in the code or in the content. In this research, to increase the security of Persian messages transmitting on the networks, some text steganography methods are proposed. Experiments show the performance of the proposed methods. © 2021, Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Persian texts Steganography Web pages

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An In-Silico Technique: Prediction of Unknown Protein Structure from Sequences by Homology 23

An In-Silico Technique: Prediction of Unknown Protein Struct...

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23rd International Arab Conference on information technology, ACIT 2022

作者： Faisal, Wafa Eltaveb, Hana Hassan, Mohammed Ibrahim, Nusiba Sudan University of Science and Technology Faculty of Computer Science and Information Technology Khartoum Sudan National University Biomedical Research Institute National University Khartoum Sudan 7Vision Training and Development Center Department of Biology and Bioinformatics' Khartoum Sudan

ISBN: (纸本)9798350320244

The structural characterization of protein sequences is one of the most common problems in biology. This task is usually facilitated by the accurate Three-Dimensional (3-D) structure of the protein. This paper was carried out to investigate and compare the most suitable software online tools for homology modeling of protein structure by obtaining few samples of proteins. Different length, known and unknown (3-D) proteins structures of bacteria, and viruses were obtained from Uniprot which do not have a Protein Data Bank Identifier (PDB ID). This paper used several tools, such CPHmodels-3.2, Phyre2, Swiss-Model, (PS)2-v2, and Robetta, for predicting, comparison and model generation, where CPHmodels-3.2 and Phyre2 Server, gave relatively better values. Proteins (3-D) structure was evaluated using PROSESS Server and the better evaluation to proteins structure was for the Phyre2 software online tool. © 2022 IEEE.

关键词： Forecasting

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Balls and Universal Space in GFO

Balls and Universal Space in GFO

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Joint Ontology Workshops 2023, Episode IX: The Quebec Summer of Ontology, JOWO 2023

作者： Hanle, Bärbel Loebe, Frank Burek, Patryk Herre, Heinrich Leipzig University Computer Science Institute Augustusplatz 10 Leipzig04109 Germany ScaDS.AI Dresden/Leipzig Leipzig University Humboldtstrasse 25 Leipzig04105 Germany Faculty of Computer Science Polish-Japanese Academy of Information Technology ul. Koszykowa 86 Warsaw02-008 Poland Haertelstrasse 16-18 Leipzig04107 Germany

Space, besides time, is one of the most fundamental categories. The top-level ontology General Formal Ontology (GFO) includes a space theory as one of its modules, called GFO-Space. Former work presents axiomatizations in connection with GFO-Space and its core notions of space regions and their boundaries (leading to surfaces, lines and points), together with relations between those space entities. In contrast to standard mathematical and physical theories in space-related applications, among the space entities of GFO there is none yet that covers "all of space" or "all space regions at once", which we call ‘universal space’. In the current paper, we address the problem of introducing the notion of universal space, motivated by aligning the theory more easily with the usual understanding and treatment in standard mathematical modeling. Our approach to its solution sets out from extending GFO-Space by (1) the category of balls, in order to (2) define a metric by recourse to balls. On that basis, we consider constructions of universal space and clarify that notion ontologically against the background of GFO. This procedure is associated with classifications of shapes of space entities and further future work. © 2023 Copyright for this paper by its authors.

关键词： Ontology

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Dynamic Hierarchical Reinforcement Learning Framework for Energy-Efficient 5G Base Stations in Urban Environments

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IEEE Transactions on Mobile Computing 2025年

作者： Xu, Dianlei Su, Xiang Premsankar, Gopika Wang, Huandong Tarkoma, Sasu Hui, Pan University of Helsinki Department of Computer Science Helsinki00014 Finland Department of Electronic Engineering Beijing100084 China University of Helsinki Department of Agricultural Sciences Helsinki00014 Finland Aalto University Department of Information and Communications Engineering Finland University of Oulu Faculty of Information Technology and Electrical Engineering Oulu90014 Finland The Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

The energy consumption of 5G base stations (BSs) is significantly higher than that of 4G BSs, creating challenges for operators due to increased costs and carbon emissions. Existing solutions address this issue by switching off BSs during specific periods or forming cooperation coalitions where some BSs deactivate while others serve users. However, these approaches often rely on fixed geographic configurations, making them unsuitable for urban areas with numerous BSs and mobile users. To tackle these challenges, we propose a hierarchical reinforcement learning (RL) framework for energy conservation in large-scale 5G networks. In the upper-layer, we propose a deep Q-network integrated with a graph convolutional network that dynamically groups BSs into coalitions from a macro perspective. This layer focuses on high-level coalition formation to optimize system-wide energy efficiency by considering the global state of the network. In the lower-layer, we combine attention mechanism with multi-agent RL and graph convolutional networks to design a scalable algorithm that maximizes local energy efficiency through optimizing the cooperation within each coalition. These two layers align global coalition dynamics with local intra-coalition cooperation to achieve system-wide energy optimization. Moreover, we accurately model large-scale urban 5G scenarios leveraging a high-fidelity network simulator, which enables our RL framework to learn from real-world feedback. Extensive experiments conducted with the simulator demonstrate that our proposed framework achieves remarkable energy savings of up to 75.6%, significantly outperforming baseline approaches. These findings highlight the effectiveness and superiority of our hierarchical RL optimization framework in addressing the energy consumption challenges faced by large-scale 5G networks. © 2002-2012 IEEE.

关键词： 5G mobile communication systems

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Enhancing Cancer Classification Through the Development of a Fuzzy Gene Selection-Wrapper Plus Method

Enhancing Cancer Classification Through the Development of a...

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IEEE International Conference on Artificial Intelligence in Engineering and technology (IICAIET)

作者： Mahmood Khalsan Mu Mu Eman Salih Al-shamery Lee Machado Michael Opoku Agyeman Suraj Ajit Advanced Technology Research Group Faculty of Arts Science and Technology The University of Northampton UK Computer Science Department College of Information Technology The University of Babylon Iraq Centre for Physical Activity and Life Science Faculty of Arts Science and Technology The University of Northampton UK

Deep Learning (DL) approaches have made sub-stantial advances in developing classification models in most disciplines, in terms of both accuracy and speed. However, analyzing gene expression data for cancer classification remains challenging due to the nature of the complexity of available datasets, which are characterized by high dimensionality (a small number of samples and a large number of features). We developed a new fuzzy gene selection wrapper plus (FGSWP) to select the most significant genes with the goal of reducing the complexity of cancer classification and the dimensionality of the datasets. FGSWP has shown its efficacy by lowering the number of genes and enhancing classifier model performance. Wrapper techniques are not suitable for use with high-dimensional data, hence fuzzy gene selection is used as the initial phase for reducing the number of genes before utilizing wrapper techniques. The accuracy attained in all datasets used ranged from ${85.3{\%}}$ to 99.3% when FGSWP and Multilayer Perceptron (MLP) were employed together.

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Various Pre-processing Strategies for Domain-Based Sentiment Analysis of Unbalanced Large-Scale Reviews 6th

Various Pre-processing Strategies for Domain-Based Sentiment...

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6th International Conference on Advanced Intelligent Systems and Informatics, AISI 2020

作者： AL-Ghuribi, Sumaia Mohammed Noah, Shahrul Azman Tiun, Sabrina Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Faculty of Applied Sciences Department of Computer Science Taiz University Taizz Yemen

ISBN: (纸本)9783030586683

User reviews are important resources for many processes such as recommender systems and decision-making programs. Sentiment analysis is one of the processes that is very useful for extracting the valuable information from these reviews. Data preprocessing step is of importance in the sentiment analysis process, in which suitable preprocessing methods are necessary. Most of the available research that study the effect of preprocessing methods focus on balanced small-sized dataset. In this research, we apply different preprocessing methods for building a domain lexicon for unbalanced big-sized reviews. The applied preprocessing methods study the effects of stopwords, negation words and the number of words occurrence. Followed by applying different preprocessing methods to determine the words that have high sentiment orientations in calculating the total review sentiment score. Two main experiments with five cases are tested on the Amazon dataset for the movie domain. The best suitable preprocessing method is then selected for building the domain lexicon as well as calculating the total review sentiment score using the generated lexicon. Finally, we evaluate the proposed lexicon by comparing it with the general-based lexicon. The proposed lexicon outperforms the general lexicon in calculating the total review sentiment score in term of accuracy and F1-measure. Furthermore, the results prove that sentiment words are not restricted to adjectives and adverbs only (as commonly claimed);nouns and verbs also contribute to the sentiment score and thus effects in the sentiment analysis process. Moreover, the results also show that negation words have positive effects in the sentiment analysis process. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sentiment analysis

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RAC-Based One-Stop Professional Course Teaching Model Exploration and Practice - Taking the Course of "Microcomputer Principles and Interface technology" as an Example 6th

RAC-Based One-Stop Professional Course Teaching Model Explor...

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6th International Conference on computer science and Educational Informatization, CSEI 2024

作者： Wan, Xiaorong Li, Yingna Luo, Chuan Li, Chuan You, Jinguo Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Computer Technology Applications Kunming650500 China

ISBN: (纸本)9789819637379

In the context of the country’s requirement for academic disciplines to be aligned and mutually reinforcing with industry chains, innovation chains, and talent chains, the integration of education and industry has become an important direction for the reform of higher education. In response to the iterative demand for edge intelligence in the Intelligent Internet of Things (AIOT), the course "Microcomputer Principles and Interface technology" is deeply integrated with industry and education, establishing a hierarchical model of resource, capability, and commercialization (RAC) layers. It adopts a "one-stop" teaching mainline that starts with microcomputer theory knowledge, relies on hardware development boards, project orientation, competition innovation, and product commercialization training "five points and one line", connects knowledge product channels, integrates ideological and political education in courses, and constructs a multi-dimensional and comprehensive evaluation system to achieve the integration of industry and education from universities to enterprises, classrooms to markets, and from knowledge to products. The innovative teaching mode of this course has achieved significant results in innovative practice. This innovative teaching mode can effectively achieve the knowledge, ability, and quality goals of cultivating new engineering talents, and effectively improve the quality of talent cultivation and teaching. This teaching reform and innovation provide a reference and idea for further exploring the talent cultivation mode of schools and enterprises. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Teaching

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