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Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

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Digital Communications and Networks 2024年第6期10卷 1837-1850页

作者： Uchechukwu Awada Jiankang Zhang Sheng Chen Shuangzhi Li Shouyi Yang School of Software Henan Institute of Science and TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computing and Informatics Bournemouth UniversityPoole BH125BBUK School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China

Recently,several edge deployment types,such as on-premise edge clusters,Unmanned Aerial Vehicles(UAV)-attached edge devices,telecommunication base stations installed with edge clusters,etc.,are being deployed to enable faster response time for latency-sensitive *** fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource *** approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks,inter-dependencies of tasks and edge resource *** approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support,as well as provider ***,we present Edge Colla,which is based on the integration of edge resources running across multi-edge *** Colla leverages learning techniques to intelligently dispatch multidependent tasks,and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize *** experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

关键词： Edge computing Collaborative learning Resource utilization Execution time Edge federation Gang scheduling

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dbSCI:A manually curated database of SARS-CoV-2 inhibitors for COVID-19

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BIOCELL 2023年第2期47卷 367-371页

作者： QIANG WANG GUO ZHAO LONGXIANG XIE XUAN LI XIXI YU QIONGSHAN LI BAOPING ZHENG ZULIPINUER WUSIMAN XIANGQIAN GUO Institute of Biomedical Informatics School of SoftwareBioinformatics CenterHenan Provincial Engineering Center for Tumor Molecular MedicineSchool of Basic Medical SciencesAcademy for Advanced Interdisciplinary StudiesHenan UniversityKaifeng475004China

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)is the pathogen of the ongoing coronavirus disease 2019(COVID-19)global ***,by centralizing published cell-based experiments,clinical trials,and virtual drug screening data from the NCBI PubMed database,we developed a database of SARS-CoV-2 inhibitors for COVID-19,dbSCI,which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-based experiments,81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformatics *** provides four major functions:(1)search the drug target or its inhibitor for SARS-CoV-2,(2)browse target/inhibitor information collected from cell experiments,clinical trials,and virtual drug screenings,(3)download,and(4)submit *** entry in dbSCI contains 18 types of information,including inhibitor/drug name,targeting protein,mechanism of inhibition,experimental technique,experimental sample type,and reference *** summary,dbSCI provides a relatively comprehensive,credible repository for inhibitors/drugs against SARS-CoV-2 and their potential targeting mechanisms and it will be valuable for further studies to control COVID-19.

关键词： SARS-CoV-2 COVID-19 Inhibitors Drugs Database

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Object on Use Case Description: Sequence Diagram Conformance based on Step Performed using Text Pre-Processing on Sipranta Application SRS

Object on Use Case Description: Sequence Diagram Conformance...

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2023 IEEE World AI IoT Congress, AIIoT 2023

作者： Abibi, Muhammad Alfath Priyadi, Yudi Dian Martha, Ati Suci Telkom University Department of Informatics Bandung Indonesia Telkom University Department of Software Engineering Bandung Indonesia Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9798350337617

In the Use Case Diagram, a Step Performed in Tabulation contains an object's explanation flow. A sequence diagram attempts to depict in detail the interaction of objects in a system, the messages or commands sent, and the implementation time. In other words, the Sequence Diagram, like the Use Case Diagram, encapsulates an object's explanation flow in a graphical diagram. The Step Performed and the Sequence Diagram should be related, yet the Step Performed and Sequence Diagram diverge while creating the Sipranta Application SRS. By adopting Text Pre-processing, this research intends to quantify the value of conformance between the Sequence Diagram and the Step Performed in Use Case Description. This study identifies the Step Performed and the Sequence Diagram using 22 documents, 11 of which are Step Performed and 11 of which are Sequence Diagrams. In addition, the Text Analysis process produces two documents with the highest conformity: d1 with d12 of 0.933461. Cohen Cappa Score produces a validation value of 0.29195, which is included in the "Fair Agreement"category. While the reliability results from 2 groups of experts, which is 0.8275, so it is included in the "Substantial agreement"category. The results differ between the two methods, which is 0.536. © 2023 IEEE.

关键词： Sequence Diagram Step Performed Text Pre-Processing

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MDIASE-Autoencoder: A Novel Anomaly Detection Method for Increasing the Performance of Credit Card Fraud Detection Models 29

MDIASE-Autoencoder: A Novel Anomaly Detection Method for Inc...

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29th International Conference on Telecommunications, ICT 2023

作者： Putrada, Aji Gautama Ramadhan, Nur Ghaniaviyanto Telkom University Advanced and Creative Networks Research Center Bandung Indonesia Institut Teknologi Telkom Purwokerto Software Engineering Faculty of Informatics Purwokerto Indonesia

ISBN: (纸本)9798350361100

Machine learning has presented diverse solutions for identifying credit card fraud by analyzing datasets with anonymous transactions. However, an unexplored avenue lies in employing autoencoders for anomaly detection in credit card fraud identification. Our research objective is to apply and assess autoencoders to enhance credit card fraud detection through machine learning-based classification methods. The study utilizes the credit card fraud dataset available on Kaggle, applying various preprocessing techniques such as standardization and over-sampling using the Synthetic Minority Oversampling Technique (SMOTE). Subsequently, a 5-layer autoencoder is applied to the modified dataset. A novel metric for evaluating reconstruction errors, Mean Decrease in the Impurity of Absolute and Squared Error (MDIASE), is employed for feature selection in the new dataset, combining mean reduction in impurity (MDI), square error, and absolute error concepts. Finally, we assess the influence of the autoencoder on four classification methods: decision tree, KNN, logistic regression, and MLP. The evaluation metrics used for comparison are AUC maximization and geometric mean (g-mean). The test results demonstrate that the autoencoder enhances the performance of four state-of-the-art models in credit card fraud classification. Mainly, MLP exhibits the most significant improvement, with its AUC increasing from 0.558 without the autoencoder to 0.999 after its implementation. © 2023 IEEE.

关键词： Anomaly detection

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An Architectural Extension for Digital Twin Platforms to Leverage Behavioral ModelsBehaviors 19

An Architectural Extension for Digital Twin Platforms to Lev...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Lehner, Daniel Gil, Santiago Mikkelsen, Peter H. Larsen, Peter G. Wimmer, Manuel CDL-MINT Institute of Business Informatics - Software Engineering Johannes Kepler University Linz Austria Aarhus University Department of Electrical and Computer Engineering Finlandsgade 22 Aarhus8200 Denmark

ISBN: (纸本)9798350320695

To reduce the work effort for developing and managing Digital Twin (DT)-based services, so-called DT platforms have emerged recently. These DT platforms make it easier to collect, store, and manage data from physical devices, but often they do not provide means for running behavioral models or synchronizing these with runtime data from the physical devices. These aspects are however crucial for developing many DT-based services. As a result, the implementation of a DT that uses behavioral models still requires a lot of implementation effort, which hinders the adoption of DTs for many applications, in particular for small and medium-sized enterprises that often do not have the resources to implement such complex systems. In this paper, we propose an extension to existing DT platforms that simplifies the incorporation of behavioral models. We base this extended platform on requirements derived from two particular use case examples that require behavioral modeling to run their DT services. We discuss the interfaces offered by the extended DT platform, demonstrate its applicability and evaluate the implementation and adaptation effort of our proposed solution in comparison to a baseline implementation. Based on the case studies, the evaluation shows that the extended DT platform reduces the implementation effort by 56% and the effort for adapting DT services across DTs by 39%, compared to existing DT platforms. © 2023 IEEE.

关键词： Behavioral research

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Extraction of Activity Diagrams Based on Steps Performed in Use Case Description Using Text Mining (Case Study: SRS Myoffice Application) 2

Extraction of Activity Diagrams Based on Steps Performed in ...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Octavially, Reynaldi Prama Priyadi, Yudi Widowati, Sri Telkom University Department of Informatics Bandung Indonesia Telkom University Department of Software Engineering Bandung Indonesia

ISBN: (纸本)9781665465410

In this research, extraction is carried out to change the text on an artifact to be processed through Text Mining to process and analyze the text whose results are validated, using the coefficient equation formula. There is a discrepancy between the flow in the Activity Diagram and the steps performed in the Use Case Description. Based on these problems, this study aims to extract an artifact to find similarities between the Activity Diagram and the actions taken in the Use Case Description and perform text analysis using the Text Mining method to obtain similarities, then validation and reliability are carried out. The extraction process is broken down into several documents according to the artifacts used, for Use Case Description, namely: UC01, UC02, UC03, UC04, and UC05. As for the Activity Diagram, namely: AD1, AD2, AD3, AD4, and AD5. The results obtained from this study are the highest similarity between activity diagrams and use case descriptions in sentences UC04 and AD4 with a total similarity of 0.51394086. The highest similarity between words lies in the words 'request' and 'application' with a complete similarity of 0.9231. Kappa's score with the Gwet's AC1 formula using Python programming is 'Less than the Opportunity Agreement' with a number of -008583, while the questionnaire filled out by the Expert is 'Almost perfect' with a score of 0.92246. © 2022 IEEE.

关键词： Extraction

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Object pest detection method based on lightweight SSD-RA algorithm 11

Object pest detection method based on lightweight SSD-RA alg...

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11th International Conference on Networks, Communication and Computing, ICNCC 2022

作者： Li, Shixuan Peng, Hongxing Yuan, Jingqi Software Engineering Institute of Guangzhou China College of Mathematics and Informatics South China Agricultural University China

ISBN: (纸本)9781450398039

In order to detect the types and quantities of pests in rice fields quickly and accurately, a lightweight target pest detection method SSD-RA based on SSD algorithm is proposed. In order to deal with the problems of high missed detection rate, inaccurate positioning, slow detection speed, large number of model parameters and low accuracy of the detection model, the ResNet feature extraction network was introduced and optimized. The first prediction feature layer of SSD was connected to the Conv3-x module of the ResNet network, and all network layers after the Conv3-x module were dropped. The number of parameters of the model is reduced, so that the model is more lightweight, the detection speed is improved, and the redundant features are reduced to ensure the accuracy of the model. In addition, aiming at the characteristics of small target, the structure of prediction feature layer of SSD algorithm is improved, the number of prediction feature layers is adjusted, and the output of underlying feature Conv2-x is connected to the prediction feature layer. The candidate box of each cell in the new prediction feature layer is 6, which accurately divides the boundaries of large, medium and small target boxes. The experimental results show that the mAP of SSD-RA of the improved algorithm in this paper is 84.1%, which is 23.4 percentage points higher than that of the original SSD model. The reasoning time in CPU and GPU environment is 0.056s and 0.009s, which is 0.101s and 0.005s faster than that of the original SSD model, and the model size is 51.9MB. It is reduced to about 7/100 of the original SSD model. Compared with other models, the mAP of SSD-RA is 7.8 and 4.2 percentage points higher than that of EfficientDet and RFCN, respectively. The SSD-RA model is more effective and faster to detecting insect pests and reduces the missed detection rate. © 2022 ACM.

关键词： Forecasting

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Measurement of Similarity between Use Case Description and Sequence Diagram in software Requirement Specification using Text Analysis for Dtrain Application 2

Measurement of Similarity between Use Case Description and S...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Yanis, Rifqi Zaidan Irsyad Priyadi, Yudi Puspitasari, Shinta Yulia Telkom University Department of Informatics Bandung Indonesia Telkom University Department of Software Engineering Bandung Indonesia

ISBN: (纸本)9781665465410

Dtrain application is built by implementing software documents, one of which is the software Requirement Specification (SRS). In compiling software documents, there is a mismatch between one document element with other elements. Therefore, this study will measure the similarity between the Use Case Description (UCD) on the SRS case study Dtrain with Sequence Diagrams (SD) to determine how similar or compatible the two SRS elements are. This study aims to measure the similarity of UML artifacts between UCD and SD contained in a software development document. The suitability of the two artifacts can be done by analyzing the text in the description (UCD) and object (SD) sections. Based on the results and discussion, this study resulted in the following. First, a study that finds level of similarity between UCD and the SD by comparing the step results performed an extraction on the UCD and the extraction of messages and actors on the SD. Second, there are five use cases in the Dtrain application, so the UCD and SD are each 5. Third, the highest similarity value results are found in SD 1 and SD 5, with a similarity value of 0.712. Fourth, the results of the validation value using algorithm code to get a kappa score of 0.331. Fifth, the results of the validation obtained from results of the expert questionnaire got a value of 0.8905. © 2022 IEEE.

关键词： Extraction

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Structure learning of Bayesian networks using sparrow optimization algorithm

International Journal of Systematic Innovation

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International Journal of Systematic Innovation 2025年第2期9卷 14-25页

作者： Kareem, Shahab Wahhab Awla, Hoshang Qasim Mohammed, Amin Salih Department of Technical Information Systems Engineering Erbil Technical Engineering College Erbil Polytechnic University Erbil Iraq Department of Computer Technical Engineering Al-Qalam University College Kirkuk Iraq Department of Computer Science Faculty of Science Soran University Soran Iraq Department of Software and Informatics Salahaddin University Erbil Iraq

Bayesian networks are powerful analytical models in machine learning, used to represent probabilistic relationships among variables and create learning structures. These networks are made up of parameters that show conditional probabilities and a structure that shows how random variables interact with each other. The structure is shown by a directed acyclic graph. Despite the NP-hard nature of learning Bayesian network structures, there has been significant progress in improving the accuracy of approximation solutions. The main focus is on score-based search strategies, which make use of functions to evaluate network models and identify structures with high scores. This study is significantly focused on structure learning Bayesian networks using the Bayesian Dirichlet equivalent uniform scoring function and metaheuristic search strategies. To this end, this paper presents the sparrow optimization algorithm (SOA), a new metaheuristic algorithm derived from the foraging behavior of sparrows. SOA performs a concurrent optimization in the solution space by simultaneously performing a local and global search that leads to the discovery of near-optimal structures. The results from our experiments on several benchmark datasets show that SOA yields overall better performance than SA and greedy search algorithms. In particular, it is claimed that by applying the proposed approach of SOA, the convergence speed is significantly higher compared with the existing ones;F1 score is 0.35 and 0.05 for the Hamming distance with better results. Given these results, signed operators prove to be very efficient in SOA’s Bayesian network structure learning as a concept, especially for real-world use. © (2024), (Society of Sytematic Innovation). All Rights Reserved.

关键词： Bayesian Network Global and Local Search Search and Score Sparrow Search Optimization Algorithm Structure Learning

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Securing the Silver Surfers: Cybersecurity Awareness Among Older Adults 19

Securing the Silver Surfers: Cybersecurity Awareness Among O...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Ahmad Nawi, Haslinda Sutan Omar, Siti Fatimah Basaruddin, Suzana Info. Science & Computing Department Management and Science University Selangor Malaysia Software Engineering Section UniKL MIIT Kuala Lumpur Malaysia Informatics & Analytics Section UniKL MIIT Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

This research investigates the perceptions of cybersecurity among older adults in Malaysia, aged 60 years and above, who are reliant on technology for basic activities. The data from 331 participants showed that 30.8% were online for 4-8 hours daily, while 3.3% were completely disconnected. Interestingly, more than half of the respondents were unaware of cybersecurity threats, especially malware and ransomware, which put their data in jeopardy. While there is some awareness related to unauthorized access and computer fraud, knowledge gaps remain significant, and effective educational interventions are thus needed. Informal, self-directed learning appears to be a widespread way of acquiring skills in this age group, often supplemented by community workshops and peer networks. Given that almost half of the older adults spend considerable time online, improving their digital skills in tandem with their support systems is an important goal for enhancing their online experiences. It indicates the need for a twin approach: enhancing cybersecurity awareness with specialized educational programs, alongside developing flexible opportunities for informal learning. Educational institutions and relevant policies are encouraged to prioritize building hands-on, specific cybersecurity education for seniors. Also, user interface design considering cybersecurity-related issues can make using the technological environment as user-friendly and secure as possible. These strategies will contribute to creating an inclusive digital society, where older adults are confident and safe in using digital technologies while continuously contributing to their personal and professional development. © 2025 IEEE.

关键词： Economic and social effects

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