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13th International Conference on software and computer Applications, ICSCA 2024

作者： Steinert, Patrick Wagenpfeil, Stefan Frommholz, Ingo Hemmje, Matthias L. University Of Hagen Faculty Of Mathematics And Computer Science Hagen Germany Pfh Private University Of Applied Sciences Faculty Of Business Computing And Software Engineering Göttingen Germany University Of Wolverhampton School Of Mathematics And Computer Science Wolverhampton United Kingdom

ISBN: (纸本)9798400708329

This paper addresses the challenges in integrating Metaverse Recordings in Multimedia Information Retrieval as a new type of multimedia. Specifically, we describe the characteristics of video content and explain the key differences of a metaverse to other videos. We present a specialized process to analyze and index Metaverse Recordings. We demonstrate that existing techniques can be used for metaverse-specific retrieval, but need content-specific adaptions. Furthermore, we evaluate a prototypical implementation based on the proposed methods with respect to the impact on the retrieval process. © 2024 Owner/Author.

关键词： Multimedia systems

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Considerations in Prioritizing for Efficiently Refactoring the Data Clumps Model Smell: A Preliminary Study 19

Considerations in Prioritizing for Efficiently Refactoring t...

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19th International Conference on Evaluation of Novel Approaches to software engineering, ENASE 2024

作者： Baumgartner, Nils Iyenghar, Padma Pulvermüller, Elke Software Engineering Research Group School of Mathematics/Computer Science/Physics Osnabrück University Osnabrück49090 Germany innotec GmbH Hornbergstrasse 45 Filderstadt70794 Germany Faculty of Engineering and Computer Science HS Osnabrueck Osnabrück49009 Germany

ISBN: (纸本)9789897586965

This paper delves into the importance of addressing the data clumps model smell, emphasizing the need for prioritizing them before refactoring. Qualitative and quantitative criteria for identifying data clumps are outlined, accompanied by a systematic, simple but effective approach involving a weighted attribute system with threshold-based priority assignment. The paper concludes with an experimental evaluation of the proposed method, offering insights into critical areas for developers and contributing to improved code maintenance practices and overall quality. The approach presented provides a practical guide for enhancing software system quality and sustainability. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： software design

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The Emergence of IIoT and its Cyber Security Issues in Critical Information Infrastructure 21

The Emergence of IIoT and its Cyber Security Issues in Criti...

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21st European Conference on Cyber Warfare and Security, ECCWS 2022

作者： Bhaiyat, Humairaa Yacoob Sithungu, Siphesihle Philezwini Academy of Computer Science and Software Engineering Faculty of Science University of Johannesburg South Africa

ISBN: (纸本)9781914587405

The emergence of the Industrial Internet of Things (IIoT) can transform and improve industrial domain processes. This is achieved by IIoT’s ability to collect and process vast amounts of data using technology such as sensors. IIoT capabilities can improve the manufacturing processes of these sectors and contribute to the improved functioning of critical information infrastructure. In addition, current trends - such as the Fourth Industrial Revolution (4IR) - use IIoT to realise specific goals. While the emergence of IIoT systems does introduce many benefits, such as improved efficiency and sustainability, it can also introduce security concerns. These security concerns pose a significant threat to the industrial domain, including critical information infrastructures. The resulting threats emphasise the need to implement solutions to secure IIoT systems. The paper aims to discuss the emergence of IIoT and its cyber security issues within the context of critical information infrastructure. The research paper follows a theoretical research methodology to provide an improved understanding of the emergence of IIoT and its cyber security issues in critical information infrastructure. The paper contains an exhaustive discussion of what is IIoT. A discussion on where IIoT fits within the context of critical information infrastructure and its impact on 4IR is also highlighted in the paper. Due to the many vulnerabilities that IIoT systems can contain, the paper also discusses security concerns surrounding the emergence of IIoT. The security concerns make IIoT systems attractive targets for cyberattacks. Therefore, different approaches that can be applied to secure IIoT systems is also provided. Since IIoT capabilities can impact the critical information infrastructure of businesses and nations, the authors’ stance on how IIoT systems could transform the current understanding of critical information infrastructure is also discussed. © 2022 Curran Associates Inc.. All rights r

关键词： Internet of things

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A New Cybersecurity Approach Enhanced by xAI-Derived Rules to Improve Network Intrusion Detection and SIEM

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computers, Materials & Continua 2025年第5期83卷 1607-1621页

作者： Federica Uccello Marek Pawlicki Salvatore D'Antonio RafałKozik MichałChoras Centro Direzionale Department of EngineeringUniversity of Naples‘Parthenope’Isola C4Napoli80133Italy Department of Computer and Information Science Software and SystemsLinköping UniversityLinköping58183Sweden ITTI Sp.z o.o. Pozna´n61-612Poland Faculty of Telecommunications Computer Science and Electrical EngineeringBydgoszcz University of Science and TechnologyBydgoszcz85-796Poland

The growing sophistication of cyberthreats,among others the Distributed Denial of Service attacks,has exposed limitations in traditional rule-based Security Information and Event Management *** machine learning–based intrusion detection systems can capture complex network behaviours,their“black-box”nature often limits trust and actionable insight for security *** study introduces a novel approach that integrates Explainable Artificial Intelligence—xAI—with the Random Forest classifier to derive human-interpretable rules,thereby enhancing the detection of Distributed Denial of Service(DDoS)*** proposed framework combines traditional static rule formulation with advanced xAI techniques—SHapley Additive exPlanations and Scoped Rules-to extract decision criteria from a fully trained *** methodology was validated on two benchmark datasets,CICIDS2017 and *** rules were evaluated against conventional Security Information and Event Management Systems rules with metrics such as precision,recall,accuracy,balanced accuracy,and Matthews Correlation *** results demonstrate that xAI-derived rules consistently outperform traditional static ***,the most refined xAI-generated rule achieved near-perfect performance with significantly improved detection of DDoS traffic while maintaining high accuracy in classifying benign traffic across both datasets.

关键词： Cybersecurity explainable artificial intelligence intrusion detection system rule-based SIEM distributed denial of service

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PESMOD: Small Moving Object Detection Benchmark Dataset for Moving Cameras 7

PESMOD: Small Moving Object Detection Benchmark Dataset for ...

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7th International Conference on Frontiers of Signal Processing, ICFSP 2022

作者： Delibasoglu, Ibrahim Sakarya University Faculty of Computer and Information Sciences Department of Software Engineering Sakarya Turkey

ISBN: (数字)9781665481588

ISBN: (纸本)9781665481588

This paper presents a new high resolution aerial images dataset in which moving objects are labelled manually. It aims to contribute to the evaluation of the moving object detection methods for moving cameras. The problem of recognizing moving objects from aerial images is one of the important issues in computer vision. The biggest problem in the images taken by Unmanned Aerial Vehicles(UAV) is that the background is constantly variable due to camera movement. There are various datasets to evaluate motion detection methods in the literature. The prepared dataset consists of challenging and high resolution images containing small targets compared to other datasets. The dataset consists of different images such as people walking in nature, people skiing, vehicles driving through the forest, towns and vehicles going on the highway. This study also represents a post-processing method that can be used after background modeling for moving object detection. Experimental studies show that proposed post-processing technique provides a significant increase in precision and F-score metrics. The results of different methods in the literature are compared in detailed for each sequence in the dataset. The dataset and source codes are available at: http://***/mribrahim/PESMOD © 2022 IEEE.

关键词： Drones

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Prediction of Antimicrobial Peptides Using Deep Neural Networks

Prediction of Antimicrobial Peptides Using Deep Neural Netwo...

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16th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2023

作者： Gülsüm Söylemez, Ümmü Yousef, Malik Bakir-Gungor, Burcu Department of Software Engineering Faculty of Engineering Muş Alparslan University Muş Turkey Department of Information Systems Zefat Academic College Zefat13206 Israel Department of Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri Turkey

Antimicrobial peptides (AMPs) are crucial elements of the innate immune system;and they are effective against bacteria that cause several diseases. These peptides are investigated as potential alternatives of antibiotics to treat infections. Since wet lab experiments are expensive and time-consuming, computational methods become crucial in this field. In this study, we suggest a computational technique for AMP prediction using deep neural networks (DNN). We trained a DNN classifier using physicochemical features that include a sequential model;and evaluated the model with 10-fold cross-validation on a benchmark dataset. We compared our method with other machine learning approaches and demonstrated that the method we developed generates higher performance (accuracy: 92%, precision: 92%, recall: 93%, f1: 93%, AUC: 98%). In our experiments, we have realized that there is a strong positive correlation between the ‘Normalized Hydrophobic Moment’ feature and ‘Angle Subtended by the Hydrophobic Residues’ feature;and strong negative correlations between ‘Normalized Hydrophobicity’ feature and ‘Disordered Conformation Propensity’ feature, and between ‘Amphilicity Index’ - ‘Disordered Conformation Propensity’ features. We believe that the approach we proposed could guide further experimental studies and could facilitate the prediction of other types of AMPs having anticancer, antivirus, antiparasitic activities. © 2023 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Deep neural networks

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Automatic Detection of Weapons in Surveillance Cameras Using Efficient-Net

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computers, Materials & Continua 2022年第9期72卷 4615-4630页

作者： Erssa Arif Syed Khuram Shahzad Muhammad Waseem Iqbal Muhammad Arfan Jaffar Abdullah S.Alshahrani Ahmed Alghamdi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Informatics&Systems University of Management&TechnologyLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Faculty of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Department of Computer Science&Artificial Intelligence College of Computer Science&EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia

The conventional Close circuit television(CCTV)cameras-based surveillance and control systems require human resource *** all the criminal activities take place using weapons mostly a handheld gun,revolver,pistol,swords ***,automatic weapons detection is a vital requirement now a *** current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–*** time datasets,from local surveillance department’s test sessions are used for model training and *** consist of local environment images and videos from different type and resolution cameras that minimize the *** research also contributes in the making of Efficient-Net that is experimented and results in a positive *** results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research ***-Net algorithm gives better results than existing *** using Efficient-Net algorithms the accuracy achieved 98.12%when epochs increase as compared to other algorithms.

关键词： Detection algorithms machine learning machine vision video surveillance

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Towards agile collaborative multi-view modeling with inconsistency tolerance

Towards agile collaborative multi-view modeling with inconsi...

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2024 Symposium on software Technologies: Applications and Foundations, STAF 2024 Workshops: 2nd International Workshop on Agile Model-Driven engineering, AgileMDE 2024, 1st Large Language Models for Model-Driven engineering Workshop, AgileMDE 2024 and 4th International Workshop on Model-Driven engineering for Smart Internet-of-Things Systems, MeSS 2024

作者： Shahvari, Yaser Sharbaf, Mohammadreza Rahimi, Shekoufeh Kolahdouz Tehrani, Sobhan Yassipour MDSE Research Group Department of Software Engineering University of Isfahan Isfahan Iran School of Arts University of Roehampton London United Kingdom Computer Science Department Faculty of Engineering University College London London United Kingdom

Model-driven engineering (MDE) copes with the complexity of software development by using the principles of separation of concerns and automatic transformation. In MDE, stakeholders from diverse domains collaborate concurrently on different models to quickly analyze, design, and generate complex software-intensive systems. To adopt an agile development approach in MDE, an inconsistency tolerance framework is needed. This framework postpones the resolution phase for incompatibilities caused by online cooperation, allowing temporary incompatibilities to be automatically fixed while requiring resolution only for the remaining conflicts at the appropriate time. In this paper, we propose a general framework for identifying and diagnosing inconsistencies, making decisions regarding inconsistency tolerance or intervention for resolution, and outlining tolerance strategies in agile systems modeled as multi-views. Our framework comprises three primary phases: detection, analysis, and tolerance. It is designed to identify inconsistencies in multi-view models, which are inherently more complex than single-view models. The tolerance phase employs strategies to tolerate inconsistencies, enhancing the flexibility of the agile development approach for collaborative multi-view modeling. © 2024 Copyright for this paper by its authors.

关键词： software design

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UML and NFR-framework based method for the analysis of the requirements of an information system

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International Journal of Information Technology (Singapore) 2023年第1期15卷 411-422页

作者： Arif, Mohd. Mohammad, Chaudhary Wali Sadiq, Mohd. Computer Science and Technology Research Group Department of Applied Sciences and Humanities Faculty of Engineering and Technology Jamia Millia Islamia A Central University New Delhi 110025 India Software Engineering Lab Computer Engineering Section UPFET Jamia Millia Islamia A Central University New Delhi 110025 India

software requirements are the expectation of stakeholders which are identified and modeled by various requirements elicitation and modeling techniques like traditional methods, goal oriented methods, and unified modeling language (UML), etc. The identified software requirements are broadly classified into functional requirements (FRs) and non-functional requirements (NFRs). Based on our literature review, we found that most of the focus in the area of software engineering is on the analysis of FRs as compared to NFRs. For the successful development of any information system both FRs and NFRs should be considered equally during the elicitation and modeling process;and ignoring NFRs may lead to failure of software. Therefore, to address this issue, we developed a method for the analysis of both FRs and NFRs so that a successful software product can be developed by a software company. In the proposed method, FRs are modeled by UML use-case diagram, class-diagram, and activity diagram. The NFRs are analyzed using NFR-framework;and NFR propagation rules have been derived from the requirements of an information system. In this framework, fuzzy based approach has been used to analyze the contribution links of softgoal interdependency graph. The applicability of the proposed method is discussed by using FRs and NFRs of library information system. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Functional requirements Library information system Non-functional requirements software requirements UML

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Weighted Multi-modal Sign Language Recognition

Weighted Multi-modal Sign Language Recognition

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Edmond Liu Jong Yoon Lim Bruce MacDonald Ho Seok Ahn Department of Electrical Computer and Software Engineering Faculty of Engineering University of Auckland New Zealand

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Multiple modalities can boost accuracy in the difficult task of Sign Language Recognition (SLR), however, each modality does not necessarily contribute the same quality of information. Current multi-modal approaches assign the same importance weightings to each modality, or set weightings based on unproven heuristics. This paper takes a systematic approach to find the optimal weights by performing grid search. Firstly, we create a multi-modal version of the RGB only WLASL100 data with additional hand crop and skeletal pose modalities. Secondly, we create a 3D CNN based weighted multi-modal sign language network (WMSLRnet). Finally, we run various grid searches to find the optimal weightings for each modality. We show that very minor adjustments in the weightings can have major effects on the final SLR accuracy. On WLASL100, we significantly outperform previous networks of similar design, and achieve high accuracy in SLR without highly complex pre-training schemes or extra data.

关键词： Sign language Accuracy Three-dimensional displays Systematics Crops Assistive technologies Robots

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