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Neighborhood Modularization‑based Artificial Bee Colony Algorithm for Disassembly Planning with Operation Attributes

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Chinese Journal of Mechanical engineering 2022年第6期35卷 165-177页

作者： Hongfei Guo Linsheng Zhang Yaping Ren Leilei Meng Zhongwei Zhou Jianqing Li GBA and B&R International Joint Research Center for Smart Logistics School of Intelligent Systems Science and EngineeringInstitute of Physical InternetJinan University(Zhuhai Campus)Zhuhai 519070China School of Computer Science Liaocheng UniversityLiaocheng 252059China Faculty of Information Technology Macao University of Science and TechnologyMacao 999078China

The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource *** is an essential process of remanufacturing end-of-life *** disassembly plans help improve disassembly efficiency and reduce disassembly *** paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are ***,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation ***,a neighborhood modularization-based artificial bee colony algorithm is developed,which contains a modular optimized ***,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.

关键词： End-of-life products Disassembly planning Artificial bee colony Neighborhood modularization

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DeepCNN:Spectro-temporal feature representation for speech emotion recognition

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CAAI Transactions on Intelligence Technology 2023年第2期8卷 401-417页

作者： Nasir Saleem Jiechao Gao Rizwana Irfan Ahmad Almadhor Hafiz Tayyab Rauf Yudong Zhang Seifedine Kadry Department of Electrical Engineering Faculty of Engineering and TechnologyGomal UniversityD.I.KhanPakistan Department of Computer Science University of VirginiaCharlottesvilleVirginiaUSA Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySkaka AljoufSaudi Arabia Centre for Smart Systems AI and CybersecurityStaffordshire UniversityStoke‐on‐TrentUK School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Speech emotion recognition(SER)is an important research problem in human-computer interaction *** representation and extraction of features are significant challenges in SER *** the promising results of recent studies,they generally do not leverage progressive fusion techniques for effective feature representation and increasing receptive *** mitigate this problem,this article proposes DeepCNN,which is a fusion of spectral and temporal features of emotional speech by parallelising convolutional neural networks(CNNs)and a convolution layer-based *** parallel CNNs are applied to extract the spectral features(2D-CNN)and temporal features(1D-CNN)representations.A 2D-convolution layer-based transformer module extracts spectro-temporal features and concatenates them with features from parallel *** learnt low-level concatenated features are then applied to a deep framework of convolutional blocks,which retrieves high-level feature representation and subsequently categorises the emotional states using an attention gated recurrent unit and classification *** fusion technique results in a deeper hierarchical feature representation at a lower computational cost while simultaneously expanding the filter depth and reducing the feature *** Berlin Database of Emotional Speech(EMO-BD)and Interactive Emotional Dyadic Motion Capture(IEMOCAP)datasets are used in experiments to recognise distinct speech *** efficient spectral and temporal feature representation,the proposed SER model achieves 94.2%accuracy for different emotions on the EMO-BD and 81.1%accuracy on the IEMOCAP dataset *** proposed SER system,DeepCNN,outperforms the baseline SER systems in terms of emotion recognition accuracy on the EMO-BD and IEMOCAP datasets.

关键词： decision making deep learning

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A Comparative Analysis of Arabic Text Summarization Techniques: Evaluating Word Frequency, K-Means Clustering, and PageRank Algorithm

A Comparative Analysis of Arabic Text Summarization Techniqu...

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Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), International

作者： Abdelrhman A. Karim Manar A. Ibrahim Mahmoud M. Hosny Abdulrhman H. Ibrahim Reem A. Mohamed Magy Elbanbawy Aya M. Al-Zoghby Khaled Foad Ibrahim Fathy Moawad Artificial Intelligence Engineering Faculty of Computer Science and Engineering New Mansoura University Dakhlia Egypt Artificial Intelligence Science Faculty of Computer Science and Engineering New Mansoura University Dakhlia Egypt Computer and System Department Faculty of Engineering Mansoura University Dakhlia Egypt Faculty of Computer Science and Engineering New Mansoura University Dakhlia Egypt Computer Science Department Faculty of Computers and Artificial Intelligence Damietta University Damietta Egypt Information Systems Faculty of Computers and Artificial Intelligence Benha University Egypt Information Systems Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Department of Artificial Intelligence College of Computer Science and Engineering Taibah University Medina Saudi Arabia

ISBN: (数字)9798350367775

ISBN: (纸本)9798350367782

This study explores methods to efficiently summarize extensive Arabic texts, addressing the growing need to condense large volumes of content across various fields. Three primary techniques are evaluated: Word Frequency Analysis, K-means Clustering based on Sentence Proximity, and the PageRank Algorithm. The research finds the PageRank Algorithm to be the most effective, delivering higher compression ratios while maintaining strong recall and precision metrics. In particular, the PageRank method achieved the highest compression ratio of 0.562 while maintaining a population standard deviation of 2.0, compared to other techniques. Evaluation metrics such as population standard deviation, F1 score, and compression ratio support these findings. The study also examines advanced approaches like fuzzy logic-based methods, transformers, and multi-document summarization, aiming to enhance Arabic text summarization.

关键词： Measurement Clustering algorithms Text summarization Ubiquitous computing Transformers Information retrieval Data mining Standards

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A requirement analysis method for the design of the upgradable product-service system 33

A requirement analysis method for the design of the upgradab...

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33rd CIRP Design Conference

作者： Wang, Hanfei Mitake, Yuya Tsutsui, Yusuke Alfarisi, Salman Shimomura, Yoshiki Faculty of Systems Design Tokyo Metropolitan University Asahigaoka 6-6 Hino-shi Tokyo191-0065 Japan Human Augmentation Research Center National Institute of Advanced Industrial Science and Technology Chiba277-0882 Japan Faculty of Computer Science and Systems Engineering Okayama Prefectural University Okayama719-1197 Japan

For extending the life cycle of products and satisfying the further requirement of customers, product-service system (PSS), an integration of products and services is considered as a promising solution. However, for PSS design, customers' expectations on the purchased product could be changed due to the development of technology and fashion. For this reason, the life of value might be exhausted before the real life of a product. Although there are some existing upgrade plans or maintenance plans for PSS design, it is found to be risky for PSS firms to provide the mentioned plans that are threatened by various uncertain events. Thus, to achieve an upgradable PSS, it is extremely essential to propose a method to identify the requirement for upgradability based on the perspective of customers. To achieve this aim, this paper has developed a method includes four steps. In step one, a set of definitions is provided to clarify the upgradability of PSS. In step 2, this study utilizes a PEST-OT matrix to analyze the driver of the future development. Step3 uses a persona-based explorative scenario building method to identify the characteristic of targeted customer and build a scenario of interaction between customer and PSS in a future scenario. Step 4 provides a requirement transformation method to transform the requirement into receiver state parameter (RSP). After that, the RSP is transformed into detailed product characteristics (PChs) and service characteristics (SChs). To verify the effectiveness, a case study of shared furniture is used. The result of the case study shows this method could work effectively in a Business-to-Customer business. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Life cycle

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A Novel Multiobjective Fireworks Algorithm and Its Applications to Imbalanced Distance Minimization Problems

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1476-1489页

作者： Shoufei Han Kun Zhu MengChu Zhou Xiaojing Liu Haoyue Liu Yusuf Al-Turki Abdullah Abusorrah College of Computer Science and Technology Nanjing University of Aeronautics and Astronauticsand also with the Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjing 211106China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand also with the K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions *** this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision *** first extend a latest single-objective fireworks algorithm to handle *** we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special ***,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization *** results show that the proposed algorithm is superior to compared algorithms in solving ***,its runtime is less than its peers'.

关键词： Adaptive strategy fireworks algorithm multimodal multiobjective optimization problems(MMOP)

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Comparing microbial communities in mucilage and seawater samples: Metagenomic insights into mucilage formation in the Marmara Sea

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Environmental science and Pollution Research 2024年第48期31卷 58363-58374页

作者： Gundogdu, Aycan Nalbantoglu, Ozkan Ufuk Karis, Gizem Sarikaya, Ilknur Erdogan, Meryem Nisa Hora, Mehmet Aslan, Herdem Department of Microbiology and Clinical Microbiology Faculty of Medicine Erciyes University Kayseri Turkey Erciyes University Melikgazi Kayseri38280 Turkey Department of Computer Engineering Faculty of Engineering Erciyes University Kayseri Turkey Department of Molecular Biology and Genetics Gevher Nesibe Genome and Stem Cell Institute Erciyes University Kayseri Turkey Department of Bioinformatics Systems Biology Institute of Health Sciences Erciyes University Kayseri Turkey Enbiosis Biotechnology Istanbul Turkey Department of Biology Faculty of Science Canakkale Onsekiz Mart University Canakkale Turkey

Marine environments are subject to various naturally occurring phenomena, including marine snow and mucilage. In 2021, the rapid emergence of mucilage in the Marmara Sea raised concerns about its environmental impact. This study investigates the microbial communities in mucilage and seawater samples from the Marmara Sea using metagenomic-scale comparative analyses. The results indicate significant differences in microbial composition and diversity, with mucilage samples showing higher levels of polysaccharide biosynthesis-related enzymes. Over 50% of reads in mucilage samples remained unclassified (dark matter), highlighting unknown microbial taxa. Clean seawater was characterized by a higher presence of Euryarchaeota, Proteobacteria, and Rhodothermaeota, while Chlamydiae and Fusobacteria were dominant in mucilage. The study underscores the necessity for comprehensive metagenomic analyses to understand microbial roles in mucilage formation and persistence. Early detection of microbial shifts could serve as a warning system for mucilage outbreaks, aiding in the development of management strategies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Seawater

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Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

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23rd International Conference on Computational science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

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The Empirical Evaluation of Artificial Intelligence-based Techniques for Improving Cyber Security 2

The Empirical Evaluation of Artificial Intelligence-based Te...

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2nd International Conference on Electronics and Renewable systems, ICEARS 2023

作者： Nayak, Chhaya Rao, Chintala Lakshmana Alam, Tanweer Singh, Shalini Islam, Shaziya Maginmani, Umme Habiba Pimpri Chinchwad College of Engineering Pune India School of Law Visakhapatnam India Islamic University of Madinah Faculty of Computer and Information Systems Department of Computer Science Madinah Saudi Arabia Graphic Era Deemed to Be University Department of Ece Uttarakhand Dehradun248002 India Rungta College of Engineering and Technology Bhilai India Secab Institute of Engineering and Technology Department of Computer Science and Engineering Karnataka Vijayapur India

ISBN: (纸本)9798350346640

Artificial intelligence (AI) technologies have been recently developed, and their advantages can be observed in a wide range of domains, from image processing to face detection. AI-based approaches can assist opponents to enhance their attack strategies while also improving cyber protection technologies. The efficiency of AI techniques against cyber security issues are evaluated. Here, the primary data and a quantitative study design approach is used. The information is then obtained from software industry professionals. The sample size for this study is 549 people, and it included confirmatory factor analysis, discriminant validity testing, model fundamental analysis, and hypothesis evaluation. All variables' P-values were found to be statistical, with the exception of intelligent agents, which had no meaningful relationship to AI or cyber security. The main issues were availability, geographical locations, study population, and other related variables. © 2023 IEEE.

关键词： Factor analysis

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia 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 UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Surface Sampling, Vertex Manipulation and Surface Generation Based on WebGL Technologies 7

Surface Sampling, Vertex Manipulation and Surface Generation...

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Runchevski, Danail Rechkoska-Shikoska, Ustijana Salkoski, Rasim University for Information Science and Technology 'St. Paul the Apostle' Faculty of Communication Networks and Security Resen Macedonia University for Information Science and Technology 'St. Paul the Apostle' Faculty of Computer Science and Engineering Ohrid Macedonia University for Information Science and Technology 'St. Paul the Apostle' Faculty of Information Systems Visualisation Multimedia and Animation Ohrid Macedonia

ISBN: (纸本)9798350342154

Surface sampling is a powerful technique used in computer graphics and visualization to gather data from 3D surfaces. Surface sampling is a process of collecting visual and tactile information from real world surfaces to serve as references for artistic creations. It allows artists to study and analyze the intricate details of surfaces, such as the roughness of tree bark, the smoothness of a pebble, or the subtle variations in fabric patterns. By examining surfaces up close, artists gain insights into the nuances that make each surface visually and texturally distinct. The solution we've developed operates seamlessly on both desktop and mobile devices, utilizing the functionalities of widely used web browsers. It eliminates the need for any software installations. Our achievement is founded on fully open-source solutions, allowing users to explore 3D models without any barriers. © 2023 IEEE.

关键词： Web browsers

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