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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Cui, Laizhong Acharya, Sudipta Mishra, Sumit Pan, Yi Huang, Joshua Zhexue Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Queen's University School of Computing ON Canada Indian Institute of Information Technology Department of Cse Assam Guwahati India Chinese Academy of Sciences Shenzhen Institute of Advanced Technology China

ISBN: (纸本)9798350322279

Dimensionality reduction through feature selection becomes inevitable to overcome the problem of the Curse of dimensionality. In this article, we propose a feature (gene) selection method for high dimensional gene expression (GE) data through a Multi-objective optimization-based Multi-view Co-Clustering algorithm (named MMCo-Clus). A thorough comparative analysis with existing feature selection algorithms using external/internal evaluation metrics supports our proposed method's potency. © 2023 IEEE.

关键词： Clustering algorithms

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Crafting Tomorrow's Trends with Automated Precision, Efficiency, and Faultless Excellence in Apparel Industry for Medium Scale Businesses

Crafting Tomorrow's Trends with Automated Precision, Efficie...

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Advancements in Computing (ICAC), International Conference on

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

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

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.

关键词： Industries Performance evaluation Transforms Production Manuals Machine learning Market research Maintenance Optimization Predictive maintenance

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DRL-Based Time-Varying Workload Scheduling With Priority and Resource Awareness

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2838-2852页

作者： Liu, Qifeng Fan, Qilin Zhang, Xu Li, Xiuhua Wang, Kai Xiong, Qingyu Chongqing University School of Big Data and Software Engineering Chongqing400044 China Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing400044 China Nanjing University School of Electronic Science and Engineering Nanjing210023 China Haihe Laboratory of Information Technology Application Innovation Tianjin300072 China Harbin Institute of Technology School of Computer Science and Technology Weihai264209 China Shandong Key Laboratory of Industrial Network Security Weihai264209 China

With the proliferation of cloud services and the continuous growth in enterprises' demand for dynamic multi-dimensional resources, the implementation of effective strategy for time-varying workload scheduling has become increasingly significant. In this paper, we propose a deep reinforcement learning (DRL)-based method for time-varying workload scheduling, aiming to allocate resources efficiently across servers in the cluster. Specifically, we integrate a classifier and queue scorer to construct a priority queue that exploits temporal resource utilization patterns across different workload classes. Then, we design parallel graph attention layers to capture the dimensional features and temporal dynamics of cloud server cluster. Moreover, we propose a DRL algorithm to generate scheduling strategies that can adapt to dynamic environments. Validation on real-world traces from Google cluster demonstrates that our method outperforms existing approaches in key metrics of cloud server cluster management. © 2004-2012 IEEE.

关键词： Cloud platforms

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Sri Potha: A Voice-Based Sinhala Document Maker

Sri Potha: A Voice-Based Sinhala Document Maker

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Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： D. I De Silva D. S. P. Piyadali M. G. S. Dilrukshi Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka

This study discusses the development of a web application aimed at facilitating Sinhala document creation, with a specific emphasis on Sinhala voice-to-text conversion and the handling of Sinhala commands through vocal input. Leveraging machine learning techniques, including convolutional neural networks and Natural Language Processing, the application's core features were established. Extensive research was conducted to tailor the application's content to the needs of its primary users, ensuring maximum effectiveness. The user-friendly interfaces of the web application are designed for clarity, simplicity, and consistency. The primary objective of this research is to comprehensively analyze the implementation of Sinhala voice-to-text conversion and Sinhala command handling systems. These systems are primarily designed to benefit diverse users, including journalists, content writers, and differently abled individuals with verbal abilities, by enhancing the efficiency of creating Sinhala documents. Through a detailed exploration of the research methodology, this study offers insight into the development process of the web-based system. The outcomes of the linguistic model training, presented within the study, reveal achievements and advancements that address the limitations inherent in existing solutions. Key findings from this research demonstrate the successful functionality of the Sinhala voice-to-text converter and the efficacy of the Sinhala command handler. The voice-to-text conversion system achieved an impressive accuracy rate of over 80%, while the Sinhala command handler exhibited an accuracy of approximately 80%. Moreover, this research envisions potential applications that extend beyond document creation. The technology showcased in the web application holds promise for broader language-based applications, impacting education, accessibility, and communication across the native Sinhala-speaking community in Sri Lanka. In summary, this research showcases th

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An Intelligent Platform for Cricket Technique and Performance Improvement

An Intelligent Platform for Cricket Technique and Performanc...

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Advancements in Computing (ICAC), International Conference on

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

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

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.

关键词： Training Deep learning Accuracy Prevention and mitigation Focusing Real-time systems Injuries Recommender systems Random forests Next generation networking

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computer Communication and Artificial Intelligence (CCAI), International Conference on

作者： Thamindu Gamage Charith Jayasingha Chathurika Dombepola Dinuka Wijendra Kaushalya Premarathne Jenny Krishara Department of Computer Science & Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350362763

ISBN: (纸本)9798350362770

The research employs a novel integration of image processing and deep learning technologies to improve the diagnostics of age-related retinal diseases, namely Diabetic Macular Edema (DME), Choroidal Neovascularization (CNV), Age-Related Macular Degeneration (ARMD), and Diabetic Retinopathy (DR). It presents an advanced architecture that seeks to enhance the accessibility and effectiveness of diagnostic processes worldwide, in addition to automating the identification of these disorders using a variety of datasets from well-known sites like Kaggle and leveraging the capabilities of state-of-the-art programs like TensorFlow and Microsoft Azure. To obtain a high degree of accuracy in early disease identification, the methodology combines custom and pre-trained deep learning models in a hybrid approach. The preliminary findings highlight the capacity of the approach to considerably reduce the probability of visual impairment using early intervention. The research is a multifaceted effort to improve the infrastructure of global eye healthcare by developing diagnostic technologies that are scalable, dependable, and easy to use.

关键词： Deep learning Macular degeneration Accuracy Image processing Refining Retina Ophthalmology

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CodeSafari: A Customized Mobile Solution for Introducing Programming Concepts to Children

CodeSafari: A Customized Mobile Solution for Introducing Pro...

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International Conference on information Technology Research (ICITR)

作者： Fahmi M.F.A. Sanjeevan M.C.M.A. Samanthi E.R. Siriwardana Mihiri Samaraweera Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331511425

ISBN: (纸本)9798331511432

Following the COVID-19 pandemic, Sri Lanka's economy faced significant setbacks, particularly in key sectors such as tea exports, garment manufacturing, and tourism, which experienced severe downturns. However, the IT sector showed resilience amid these challenges, highlighting its potential to drive economic growth. Despite this potential, Sri Lanka has struggled to capitalize fully on global demand for IT services due to a skills gap among Sri Lankan youth compared to their Indian counterparts. India's IT outsourcing industry has thrived partly because of the early involvement of young professionals in open-source projects such as the Android Open Source Project (AOSP), Linux Kernel and React. This trend underscores the importance of foundational programming education to develop competitive technical skills from a young age. To address this gap, authors developed a mobile learning solution CodeSafari, designed to introduce core programming concepts data types, conditional statements, and loops to young Sri Lankan learners. The platform uses Personalized Storytelling and a Customized Kids Assisting System in students' native language, making programming more accessible. Programming training with the app improved test scores for 58 percent of participants. By addressing the skills gap early, this research aims to build a strong IT foundation for Sri Lankan students, positioning them to compete more effectively in the global outsourcing market. These findings underscore the essential role of programming education in fostering economic resilience and preparing a workforce capable of thriving in an evolving technology landscape.

关键词： Training Economics Pandemics Prototypes software Outsourcing Usability Programming profession Testing Resilience

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Revolutionalize Your Learning Experience with EQU ACCESS

Revolutionalize Your Learning Experience with EQU ACCESS

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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Gawsan Raveenthiran Kaanushan Sivarajah Akash Ahamed Mohamed Riyal Vethurja Kugathasan Sanjeevi Chandrasiri Karthiga Rajendran Department of Computer Science & Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

This paper introduces a novel approach aimed at enhancing online education by placing a central focus on students' emotional well-being and improving their learning experiences. The approach integrates four key machine learning technologies: behavioral expression analysis, a personalized chatbot for emotional support, voice stress detection, and visual content description. Through empirical findings, the study illustrates the effectiveness of these methods in bolstering students' emotional well-being and academic performance. By providing a roadmap for the advancement of online education and emotional support, this research holds promise for delivering substantial benefits to learners worldwide. The study showcases notable advancements in online education, reporting a 30% rise in perceived emotional support and a 25% increase in overall satisfaction. The personalized emotional support chatbot achieved an 85% accuracy in addressing students' emotional needs, while voice stress detection boasted a 90% accuracy in identifying anxiety. Additionally, visual content description led to a 20% improvement in comprehension. These findings highlight the approach's potential to elevate both emotional well-being and academic performance in online learners.

关键词： Visualization Electric potential Accuracy Education Anxiety disorders Machine learning Chatbots

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Multi-Path Attention Inverse Discrimination Network for Offline Signature Verification

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Intelligent Automation & Soft Computing 2023年第6期36卷 3057-3071页

作者： Xiaorui Zhang Yingying Wang Wei Sun Qi Cui Xindong Wei School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of WindsorWindsorN9B 3P4Canada School of Teacher Education Nanjing University of Information Science&TechnologyNanjing210044China

Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business ***,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective ***,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass *** challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective *** solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature ***,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature *** addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of *** respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification *** is more helpful to the task of signature authentication in justice and finance.

关键词： Offline signatures biometric verification multi-path discrimination loss attention mechanisms inverse discrimination

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AlgoCert: Adopt Non-transferable NFT for the Issuance and Verification of Educational Certificates using Algorand Blockchain

AlgoCert: Adopt Non-transferable NFT for the Issuance and Ve...

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2022 IEEE Asia-Pacific Conference on computer science and Data engineering, CSDE 2022

作者： Tahlil, Tahlil Gomasta, Sarmistha Sarna Ali, A B M Shawkat Institute of Information Technology University of Dhaka Dhaka Bangladesh Daffodil International University Dept of Software Engineering Dhaka Bangladesh The University of Fiji Dept of Computer Science & Engineering Fiji

ISBN: (纸本)9781665453059

In addition to tanking the economy and society, credential fraud frequently damages the credibility of higher education. As the majority of conventional verification and issuance procedures are arduous, expensive, and obsolete, fraud has proliferated in numerous forms, ranging from paper-based counterfeit certificates to replicas enabled by database manipulation, and has reached exponential quantities. In this paper, the authors propose AlgoCert, a comprehensive credential verification solution that incorporates blockchain, self-sovereign identity (SSI), and decentralized identifier (DID) to introduce a more proficient, attack-resistant system that is user-friendly as well as effective at reducing widespread credential fraud. In addition, AlgoCert leverages stateful smart contracts on the Algorand blockchain and non-transferable non-fungible tokens (NFT), and neither students nor organizations are required to handle credentials in order to use the system. This paper provides a prototype of our solution and detail our attempts to develop a verification service with features, including data security, transcript authentication, and selective data disclosure. © 2022 IEEE.

关键词： Blockchain

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