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Introduction to the Special Issue on Intelligent Models for Security and Resilience in Cyber Physical Systems

computer Modeling in engineering & sciences 2022年第4期131卷 23-26页

作者： Qi Liu Xiaodong Liu Radu Grosu Ching-Nung Yang School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Computing Edinburgh Napier UniversityEdinburgh018373UK Institute of Computer Engineering Vienna University of TechnologyWien1040Austria Department of Computer Science and Information Engineering National Dong Hwa UniversityHualien97401Taiwan

Cyber Physical Systems(CPS)have been appealing in recent years as a result of the rapid emergence of unique hardware and software compositions that create smart,autonomously behaving ***-to-end procedures and new types of user-machine interaction are made possible via the *** the one hand,these CPS applications have the potential to deliver crucial services in a variety of developing application areas,including energy management,healthcare,traffic monitoring,industrial assessment and surveillance.

关键词： CPS hardware services

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Industrial Automation information Analogy for Smart Grid Security

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computers, Materials & Continua 2022年第5期71卷 3985-3999页

作者： Muhammad Asif Ishfaq Ali Shahbaz Ahmad Azeem Irshad Akber Abid Gardezi Fawaz Alassery Habib Hamam Muhammad Shafiq Department of Computer Science National Textile UniversityFaisalabad37610PunjabPakistan Department of Computer Science and Software Engineering International Islamic UniversityIslamabadPakistan Department of Computer Science COMSATS University IslamabadIslamabadPakistan Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Industrial automation or assembly automation is a strictly monitored environment,in which changes occur at a good *** are many types of entities in the focusing environment,and the data generated by these devices is *** addition,because the robustness is achieved by sensing redundant data,the data becomes *** data generating device,whether it is a sensing device or a physical device,streams the data to a higher-level deception device for calculation,so that it can be driven and configured according to the updated *** the emergence of the Industry 4.0 concept that includes a variety of automation technologies,various data is generated through numerous ***,the data generated for industrial automation requires unique information Architecture(IA).IA should be able to satisfy hard real-time constraints to spontaneously change the environment and the instantaneous configuration of all *** understand its applicability,we used an example smart grid *** smart grid system needs an IA to fulfill the communication requirements to report the hard real-time changes in the power immediately following the *** addition,in a smart grid system,it needs to report changes on either side of the system,i.e.,consumers and suppliers configure and reconfigure the system according to the *** this article,we propose an analogy of a physical phenomenon.A point charge is used as a data generating device,the streamline of electric flux is used as a data flow,and the charge distribution on a closed surface is used as a ***,the intensity changes are used in the physical process,e.g.,the smart *** analogy is explained by metaphors,and the structural mapping framework is used for its theoretical *** proposed analogy provides a theoretical basis for the development of such information architectures that can represent data flows,definition changes(deterministic and non-deterministic),events,and i

关键词： Industry 4.0 information architecture industrial automation

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Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali Maqbool Khan Khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

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A High Availability Microservices Architecture Implementation using Saga and Backup Mechanism 10

A High Availability Microservices Architecture Implementatio...

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10th International Conference on Dependable Systems and Their Applications, DSA 2023

作者： Lee, Wen-Tin Song, Ping-Yi Tsai, Ming-Kai Wu, Meng-Hsien Ma, Shang-Pin National Kaohsiung Normal University Department of Software Engineering and Management Kaohsiung Taiwan National Taiwan Ocean University Department of Computer Science and Information Engineering Keelung Taiwan

ISBN: (纸本)9798350304770

In recent years, the proliferation of complex applications has led to the emergence of microservices architecture as the preferred approach for developing largescale applications. Consequently, numerous design patterns for microservice communication have evolved, with service orchestration gaining widespread acceptance as a standard solution in recent *** study delves into design patterns for microservice data consistency and develops the service orchestration library, Anser-Saga. This library enables the creation of backups and restart points of distributed transaction states, ensuring eventual data consistency between microservice endpoints. Furthermore, it guarantees that our orchestrator can store, compensate for, and restart the orchestration process in case of an unexpected failure, ensuring transaction integrity. We conducted experiments involving actual microservice invocations to evaluate the availability and performance of microservices. The findings revealed that the Anser-Saga library demonstrated superior performance compared to the DTM solution. © 2023 IEEE.

关键词： Architecture

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Unsupervised feature selection via multiple graph fusion and feature weight learning

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science China(information sciences) 2023年第5期66卷 56-72页

作者： Chang TANG Xiao ZHENG Wei ZHANG Xinwang LIU Xinzhong ZHU En ZHU School of Computer Science China University of Geosciences State Key Laboratory for Novel Software Technology Nanjing University School of Computer National University of Defense Technology National Supercomputing Center in Jinan Qilu University of Technology (Shandong Academy of Sciences) College of Mathematics Physics and Information Engineering Zhejiang Normal University

Unsupervised feature selection attempts to select a small number of discriminative features from original high-dimensional data and preserve the intrinsic data structure without using data labels. As an unsupervised learning task, most previous methods often use a coefficient matrix for feature reconstruction or feature projection, and a certain similarity graph is widely utilized to regularize the intrinsic structure preservation of original data in a new feature space. However, a similarity graph with poor quality could inevitably afect the final results. In addition, designing a rational and efective feature reconstruction/projection model is not easy. In this paper, we introduce a novel and efective unsupervised feature selection method via multiple graph fusion and feature weight learning（MGF2WL） to address these issues. Instead of learning the feature coefficient matrix, we directly learn the weights of diferent feature dimensions by introducing a feature weight matrix, and the weighted features are projected into the label space. Aiming to exploit sufficient relation of data samples, we develop a graph fusion term to fuse multiple predefined similarity graphs for learning a unified similarity graph, which is then deployed to regularize the local data structure of original data in a projected label space. Finally, we design a block coordinate descent algorithm with a convergence guarantee to solve the resulting optimization problem. Extensive experiments with sufficient analyses on various datasets are conducted to validate the efficacy of our proposed MGF2WL.

关键词： unsupervised feature selection graph fusion feature weight learning local structure preservation

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Machine Learning-based Multi-path Reliable and Energy-efficient Routing Protocol for Underwater Wireless Sensor Networks 20

Machine Learning-based Multi-path Reliable and Energy-effici...

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20th International Conference on Frontiers of information Technology, FIT 2023

作者： Khan, Zahid Ullah Aman, Muhammad Rahman, Wazir Ur Khan, Faran Jamil, Tooba Hashim, Rifhat Harbin Engineering University College of Underwater Acoustic Engineering Harbin150001 China University of Science and Technology Bannu Department of Software Engineering Pakistan Barani Institute of Information and Technology Department of Computer Science Rawalpindi Pakistan

ISBN: (纸本)9798350395785

The research on applications for Underwater Wireless Sensor Networks (UWSNs) including the investigation of submerged resources, gathering oceanographic data, conducting operational surveillance, and prevention from natural disasters is rapidly increasing. Traditional wireless sensor networks (TWSNs) are distinct from UWSNs. Routing protocols of TWSNs are also distinct from UWSNs routing protocols in terms of energy efficiency. Most of routing protocols have been developed to extract data from the ocean floor to the surface of waters. There are many challenges for indigenous designing of an efficient routing protocol for UWSNs, such as, design of reliable path for forwarding communicating data packets, managing the movement of nodes, configuration of sensor nodes, removing void communicating nodes and increasing the power efficiency of the system. This research focuses on designing a novel Machine learning-based multi-path reliable and energy-efficient routing protocol (M2RE2RP) for UWSNs. It will select an efficient path among the existing communication paths used by sensor nodes, which will ultimately increase the lifespan of the network. The simulation experiment results dictate that the proposed routing model M2RE2RP achieves better performance in terms of network throughput, end-to-end latency, total energy consumption and network lifetime. © 2023 IEEE.

关键词： Routing protocols

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Public integrity verification for data sharing in cloud with asynchronous revocation

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Digital Communications and Networks 2022年第1期8卷 33-43页

作者： Wei Song Yu Wu Yihui Cui Qilie Liu Yuan Shen Zicheng Qiu Jianjun Yao Zhiyong Peng School of Computer Science Wuhan UniversityWuhan430074China b School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing400054China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400054China College of Information Engineering Tarim UniversityAlar CityXinjiang843300China

Cloud data sharing service,which allows a group of people to access and modify the shared data,is one of the most popular and efficient working styles in ***,there is an uprising trend that enterprises tend to move their IT service from local to cloud to ease the management and reduce the *** the new cloud environment,the cloud users require the data integrity verification to inspect the data service at the cloud *** recent studies have focused on this application *** these studies,each user within a group is required to sign a data block created or modified by *** a user is revoked,all the data previously signed by him should be *** the existing research,the resigning process is dependent on the revoked ***,cloud users are *** may exit the system at any time without notifying the system admin and even are revoked due to *** the developers in the cloud-based software development platform,they are voluntary and not strictly controlled by the *** to this feature,cloud users may not always follow the cloud service *** may not participate in generating the resigning key and may even expose their secret keys after being *** the signature is not resigned in time,the subsequent verification will be *** if the secret key is exposed,the shared data will be maliciously modified by the attacker who grasps the ***,forcing a revoked user to participate in the revocation process will lead to efficiency and security *** a result,designing a practical and efficient integrity verification scheme that supports this scenario is highly *** this paper,we identify this challenging problem as the asynchronous revocation,in which the revocation operations(i.e.,re-signing key generation and resigning process)and the user's revocation are *** the revocation operations must be able to be performed without the participation of the revo

关键词： Cloud storage Integrity verification Asynchronous revocation

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Fault-Tolerant Data Aggregation with Error-Checking for Smart Grids

Fault-Tolerant Data Aggregation with Error-Checking for Smar...

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2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Wang, Congcong Wang, Chen Shen, Jian Vijayakumar, Pandi Bhuiyan, Zakirul Alam School of Software Nanjing University of Information Science & Technology Nanjing210044 China School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China University College of Engineering Tindivanam Department of Computer Science and Engineering Tamilnadu 604001 India Fordham University Department of Computer and Information Sciences NY10458 United States

ISBN: (纸本)9798350304602

With the rapid development of smart grid technology, a new challenge has been brought about by the massive data generated from distributed devices. Data aggregation technology plays a crucial role in smart grid schemes, in terms of energy data statistics and resource allocation. However, achieving fast error-checking and improving device fault-tolerance are still open issues in the smart grid data aggregation. To address these issues, this paper proposes an error-tolerant data aggregation scheme integrated with error-checking mechanisms. The scheme proposes a tree-based aggregation structure, facilitating swift error-checking of data. We combine masking values with user anonymity in the ElGamal cryptographic scheme to ensure the security of sensitive data and resist collusion attacks. Both theoretical and experimental analyses demonstrate that this scheme enables a lightweight, secure data aggregation, ensuring enhanced reliability and error-checking. © 2023 IEEE.

关键词： Fault tolerance

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Success Factors of Enterprise Resource Planning: A State-of-the-Art Mini Review

Success Factors of Enterprise Resource Planning: A State-of-...

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2024 International Conference on Artificial Intelligence, Metaverse and Cybersecurity, ICAMAC 2024

作者： BaniMustafa, Ahmed Bulkrock, Olla Faculty of Computer Information Science Higher Colleges of Technology Abu Dhabi United Arab Emirates Software Engineering Department Princess Sumaya University for Technology Amman Jordan

ISBN: (纸本)9798350353488

Enterprise Resource Planning Systems (ERP) are vital for today’s businesses. However, the successful implementation of ERP systems faces several challenges, which can determine its success or failure. This paper provides a brief state-of-the-art review of the success factors of ERP implementation using various applications that span different contexts. The paper discusses and compares the aims defined and the techniques applied in these studies, as well as the data used and the results obtained from each of these studies. This review paper reviews published work to tackle these challenges, covering the literature published in 2020-2023. A special effort was also made to focus on high-quality papers published in top journals with high-impact factors and indexed in Scopus and Web of science. The review process is repeatable, as special keywords were used to search the literature using publishers’ databases and three specialized tools. The paper concludes by discussing the future of the successful implementation of ERP systems. The paper argues that ERP systems will continue to have a major impact on the success of today’s businesses. Therefore, they must carefully consider various factors that influence their successful implementation. © 2024 IEEE.

关键词： information use

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Sand Cat Swarm Optimization with Deep Transfer Learning for Skin Cancer Classification

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computer Systems science & engineering 2023年第11期47卷 2079-2095页

作者： C.S.S.Anupama Saud Yonbawi G.Jose Moses E.Laxmi Lydia Seifedine Kadry Jungeun Kim Department of Electronics and Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Computer Science and Engineering University Institute of Engineering and Technology(UIET)Guru Nanak UniversityHyderabadIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Skin cancer is one of the most dangerous *** of the high melanoma death rate,skin cancer is divided into non-melanoma and *** dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin ***,pathology and biopsy examinations are required for cancer *** studies have formulated computer-based systems for detecting skin cancer from skin lesion *** recent advancements in hardware and software technologies,deep learning(DL)has developed as a potential technique for feature ***,this study develops a new sand cat swarm optimization with a deep transfer learning method for skin cancer detection and classification(SCSODTL-SCC)*** major intention of the SCSODTL-SCC model lies in the recognition and classification of different types of skin cancer on dermoscopic ***,Dull razor approach-related hair removal and median filtering-based noise elimination are ***,the U2Net segmentation approach is employed for detecting infected lesion regions in dermoscopic ***,the NASNetLarge-based feature extractor with a hybrid deep belief network(DBN)model is used for ***,the classification performance can be improved by the SCSO algorithm for the hyperparameter tuning process,showing the novelty of the *** simulation values of the SCSODTL-SCC model are scrutinized on the benchmark skin lesion *** comparative results assured that the SCSODTL-SCC model had shown maximum skin cancer classification performance in different measures.

关键词： Deep learning skin cancer dermoscopic images sand cat swarm optimization machine learning

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