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6th International Conference on Advancements in Computing, ICAC 2024

作者： Hiruni Herath, H.M. Jayaweera, J.M.M.G. Jayasinghe, J.M.Y. Randeni, K.M.T.D. Amarasena, Nelum Chathuranga Rathnayake, Samadhi Chandanathilaka, S.N. Sri Lankan Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lankan Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

In the evolving landscape of Sri Lanka's apparel industry, the predominance of manual methods in the pre-production phase necessitates innovative technological interventions to enhance efficiency. This research explores the complexities of garment production, addressing critical challenges such as machine breakdowns, maintenance, and workforce management. By employing advanced technologies such as image recognition, loT devices, and machine learning, this study aims to transform pre-production decision-making, optimize sewing machine performance, implement predictive maintenance strategies, and refine workforce optimization. These initiatives, driven by domain expertise and cutting-edge methodologies, not only aim to bridge existing gaps in the industry but also pave the way for significant advancements, ensuring a future characterized by precision, efficiency, and operational excellence. © 2024 IEEE.

关键词： Predictive maintenance

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Sentiment Analysis In Uzbek Texts In The Restaurant Field 3

Sentiment Analysis In Uzbek Texts In The Restaurant Field

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3rd IEEE International Conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Kumushoy, Niyazmetova Farogat, Yusupova Ogabek, Sobirov Urgench Branch of Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi Department of Software Engineering Urgench Uzbekistan Urgench State University Department of Computer Science Urgench Uzbekistan

ISBN: (纸本)9798331516321

Sentiment analysis plays a crucial role in natural language processing, particularly in evaluating user comments and extracting valuable insights for classification tasks. This analysis can significantly impact customer satisfaction and influence a company's future development. In our study, we focused on feedback from restaurants in Tashkent, collected via Google Maps. We constructed a dataset that reflects user sentiments and applied logistic regression models for analysis. Through our evaluation, we found that proper preprocessing steps, such as stemming-especially important for agglutinative languages like Uzbek-greatly enhance model performance. These steps help in reducing words to their root forms, allowing the model to better understand the underlying sentiments. Our best-performing model achieved an impressive accuracy of 91%, demonstrating the effectiveness of our approach. The results highlight the importance of sentiment analysis in the restaurant industry, providing actionable insights that can help businesses improve their services and customer experiences. By leveraging user feedback, companies can make informed decisions that foster growth and enhance customer loyalty. Overall, our research underscores the potential of sentiment analysis in driving business success through careful data handling and analysis techniques. © 2024 IEEE.

关键词： Customer satisfaction

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Online Container Scheduling for Data-intensive Applications in Serverless Edge Computing 42

Online Container Scheduling for Data-intensive Applications ...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Shang, Xiaojun Mao, Yingling Liu, Yu Huang, Yaodong Liu, Zhenhua Yang, Yuanyuan Stony Brook University Department of Electrical and Computer Engineering United States Shenzhen University College of Computer Science and Software Engineering Shenzhen China Stony Brook University Department of Applied Mathematics and Statistics United States

ISBN: (纸本)9798350334142

Introducing the emerging serverless paradigm into edge computing could avoid over- and under-provisioning of limited edge resources and make complex edge resource management transparent to application developers, which largely facilitates the cost-effectiveness, portability, and short time-to-market of edge applications. However, the computation/data dispersion and device/network heterogeneity of edge environments prevent current serverless computing platforms from acclimating to the network edge. In this paper, we address such challenges by formulating a container placement and data flow routing problem, which fully considers the heterogeneity of edge networks and the overhead of operating serverless platforms on resource-limited edge servers. We design an online algorithm to solve the problem. We further show its local optimum for each arriving container and prove its theoretical guarantee to the optimal offline solution. We also conduct extensive simulations based on practical experiment results to show the advantages of the proposed algorithm over existing baselines. © 2023 IEEE.

关键词： Edge computing

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Internet of Things (IoT) Authentication and Integrity Model using MBTSKHF One Time Password (OTP) 22

Internet of Things (IoT) Authentication and Integrity Model ...

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Proceedings of the 11th International Conference on software and Information engineering

作者： Sara El-Sayed Khater Basheer Abd Elfattah Youssef Salwa El-Gamal Department of Software Engineering Department of Software Engineering Egypt and Department of Software Engineering Cairo University Egypt Department of Computer Science Department of Computer Science Egypt and Department of Computer Science Cairo Egypt Department of Computer Science Egypt and Department of Computer Science Cairo University Egypt

ISBN: (纸本)9781450397063

The Internet of Things is a network of physical objects like sensors, actuators, and software. The purpose of connecting is to exchange data with other objects and systems over the internet, enabling us to enhance data collection, minimize human efforts, save time, and make decisions. Secure that network is the most important IoT challenge, so we use ways to securely access all objects in the IoT network that are known with IoT authentication. Most of the attacks come from plain security problems, for example, the weakness of passwords, these techniques have some disadvantages; Password depends on user memory, and most people use default password which is vulnerable to attacks. This paper compares different IoT authentication schemes. Also, present an analysis of the different generation One Time Password (OTP) schemes like Lamport OTP, Elliptic Curve, and HOTP. The paper provides a simple light model using OTP-based MBTS KHF (Moataz, Basheer, Tarek, Salwa keyed hashing function). our model achieves high-level security with a very shorter key size and solves key size and key store problems than the other algorithms. Also, the paper model prevents users from initializing multiple connections for authentication to prevent attackers from guessing OTP.

关键词： Additional Keywords and Phrases • Internet of Things • One Time Password • Authentication • Security • Cryptography • Hash Key Function • Data Integrity

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A Multimodal Method for Semi-Biometric Information Based User Identification in AR and VR Applications

A Multimodal Method for Semi-Biometric Information Based Use...

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IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Han Li Ke Lyu Owen Dossett Xianglong Feng Department of Computer Science and Software Engineering Miami University Oxford

ISBN: (数字)9798350367942

ISBN: (纸本)9798350367959

Virtual Reality (VR) and Augmented Reality (AR) have witnessed a surge in popularity, revolutionizing various industries and enhancing user experiences. As these technologies continue to evolve, ensuring secure user identification becomes increasingly important. However, existing identification methods often come with vulnerabilities or require costly hardware implementations. To address these challenges, we propose a novel semi-biometric information-based user identification approach leveraging multimodal techniques. By analyzing the user’s viewing patterns and gaze behavior in the runtime, we can accurately identify individuals. This approach offers a promising solution for seamless user identification in VR and AR applications, without compromising on user experience or requiring expensive hardware modifications. To verify the efficiency of our proposed algorithm, we test our algorithm using a public dataset, the result of which shows a high classification accuracy. Additionally, beyond traditional evaluation metrics, we perform a transferability test, demonstrating the adaptability of our solution to new scenarios with robust generality.

关键词： Accuracy Runtime Neural networks Streaming media Hardware User experience Real-time systems Classification algorithms Security Surges

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An Intelligent Platform for Cricket Technique and Performance Improvement 6

An Intelligent Platform for Cricket Technique and Performanc...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Madushan, Anjana Fernando, Priyantha Mahendra, Hesara Kottage, Nowen Kasthuriarachchi, Sanvitha Rajapaksha, Samantha Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331517878

In cricket training, preventing injuries and developing skills are of utmost importance, especially concerning the school cricketers. This research presents a web application, 'CricBoost' which would serve to address all these vital issues through a multifaceted strategy. This study offers batsman pose accuracy assessment and correction using MediaPipe and Random Forest algorithm, Analysis of bowling and grip using MediaPipe, VGG16 and Gradient Boost models for classification and Shap for providing suggestions on the optimal methods, Suggestion of Shot selection for Batsman, where YOLOv8 and OpenCV are applied to ball pitch analysis and the player is given suggestions about the right shot to take, and cricket drill recommendation system focused on targeted skill improvement of players. CricBoost will deliver a unique combination that will increase players' technical skills, strategic intelligence, and performance while simultaneously focusing on injury prevention by teaching correct techniques. © 2024 IEEE.

关键词： Cricket (Sports)

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software Defect Prediction Using Ensemble Technique 9

Software Defect Prediction Using Ensemble Technique

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Wicaksono, Pandu Arisaputra, Panji Yunanda, Rezky Kristian, Willy Mujhid, Almuzhidul School of Computer Science Bina Nusantara University Software Engineering Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

software defect prediction is the methodical process of identifying code segments that are likely to have problems. This is done by analyzing software metrics and using categorization algorithms. This work introduces an alternate approach that utilizes ensemble learning techniques to improve the effectiveness of fault detection models. The models utilized in this study are CodeGPT and CodeBERT, both of which are transformer-based deep learning models that can extract code features from source code. The models are trained using the PROMISE dataset, which consists of Java projects that have been labeled with defects. The test results show that using ensemble learning methods can improve the accuracy, precision, recall, and F1 score of a single model by around 1-3%. This study contributes to the progress of software dependability and quality by utilizing advanced software fault prediction algorithms. © 2024 IEEE.

关键词： Prediction models

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Enhancement of Depth Map through Weighted Combination of Guided Image Filters in Shape-From-Focus 2

Enhancement of Depth Map through Weighted Combination of Gui...

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Ahmed, Zubair Shahzad, Ahsan Ali, Usman Department of Computer & Software Engineering Islamabad Pakistan Korea University of Technology and Education School of Computer Science & Engineering Korea Republic of

ISBN: (纸本)9781665498197

Estimation of depth map plays a key role in a number of computer vision applications. Shape from focus is a monocular approach that uses image focus as a cue to reconstruct 3D shapes. In the literature, a variety of guided image filters have been proposed to enhance the depth map individually. Among them, some have excess computational time burden, and some others produce unsatisfactory results. This paper proposed a framework for the enhancement of depth map by using a weighted combination of selected guided filters in shape from focus. The optimized weights are obtained using the particle swarm optimization approach, and the subset of best-performing filters is identified through a sequential forward search method. The experimental results have demonstrated that the proposed framework provides considerably improved depth maps. © 2022 IEEE.

关键词： Particle swarm optimization (PSO)

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Secure Energy Efficiency for ARIS Networks With Deep Learning: Active Beamforming and Position Optimization

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IEEE Transactions on Wireless Communications 2025年第6期24卷 5282-5296页

作者： Wang, Dawei Wang, Zijun Zhao, Hongbo Zhou, Fuhui Alfarraj, Osama Yang, Weichao Mumtaz, Shahid Leung, Victor C. M. Northwestern Polytechnical University School of Electronics and Information Shaanxi Xi’an710072 China Beihang University School of Electronic and Information Engineering Beijing100191 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing210000 China King Saud University Community College Computer Science Department Riyadh11437 Saudi Arabia Nottingham Trent University Department of Computer Science NottinghamNG1 4FQ United Kingdom Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen528060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Incorporating an active reconfigurable intelligent surface on an autonomous aerial vehicles (AAVs), denoted as an aerial reconfigurable intelligent surface (ARIS), introduces a novel dimension for secure transmissions. Given the constraint of limited battery capacity in AAVs, energy management emerges as a key challenge within AAV networks. In response, we propose a secure energy efficiency (SEE) transmission scheme for ARIS networks, where active ARIS is strategically deployed to enhance information security. In addition, a SEE optimal problem is formulated by considering the imperfect wiretap channel state information to optimize the active beamforming vector and the ARIS position. For this non-convex problem, we first reformulate the fractional SEE objective into an equivalent form and subsequently decompose it into two distinct subproblems: optimizing the AAV’s position and designing the active beamforming. For the AAV’s position optimization, we propose a sophisticated deep deterministic policy gradient algorithm that enables the AAV to autonomously determine the optimal ARIS position through a self-learning strategy. Regarding beamforming design, we transform this aspect into a quadratic constrained quadratic programming problem and design an alternating direction multiplier method to optimize the reflection coefficient. Subsequently, an alternating optimization algorithm is proposed to synergistically solve these subproblems. Empirical simulations validate our proposed scheme, indicating an improvement in SEE of up to 47.2%. This significant improvement underscores the efficacy of the proposed ARIS-assisted secure transmission scheme in enhancing both security and energy efficiency in AAV networks. © 2002-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Data-Driven Analysis of software Testing Automation Challenges Using Structural Equation Modeling (SEM) Approach

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IEEE Access 2025年 13卷 96159-96181页

作者： Abrar, Muhammad Faisal Majeed, Muhammad Faran Saqib, Muhammad Alferaidi, Ali Uddin, Raza University of ha'Il College of Computer Science and Engineering 55476 Saudi Arabia Kohsar University Department of Computer Science Punjab Muree Pakistan University of Engineering & Technology Department of Software Engineering Peshawar25000 Pakistan

The adoption of automation in software testing presents challenges that can hinder its effectiveness and scalability. This study systematically investigates these challenges using a multi-phase research approach. First, a Systematic Literature Review (SLR) was conducted to identify 14 Critical Challenges (CCs) in automation adoption. Second, a questionnaire survey of 50 industry experts validated these challenges and examined their interrelationships. Finally, Structural Equation Modeling (SEM) a mathematical and statistical approach was employed to analyze correlations and uncover structural dependencies among the challenges. The SEM analysis identified five latent variables: Human Resource Constraints (HRC), Technological & Process Challenges (TPC), Financial & Resource Constraints (FRC), Security & Reliability Issues (SRI), and Future Adaptability & Scalability (FAS) that significantly influence automation adoption. Hypothesis testing revealed that HRC (-0.32), TPC (-0.45), FRC (-0.41), and SRI (-0.38) negatively impact automation success, whereas FAS (+0.51) plays a pivotal role in enabling successful adoption. Model validation through Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis (EFA) confirmed strong construct reliability and fit indices (RMSEA = 0.043, CFI = 0.95, TLI = 0.92, SRMR = 0.037). The study highlights the need for workforce training, standardized automation processes, cost-effective solutions, and security enhancements. By providing an empirically validated framework, this research contributes to both academia and industry, guiding decision-makers in optimizing automation strategies and improving software testing efficiency. © 2013 IEEE.

关键词： software testing

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