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25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Gruman, Shayne Kosseim, Leila Laboratory Department of Computer Science and Software Engineering Concordia University MontréalQC Canada

In this paper, we describe our approach to CLEF 2024 Lab 2 CheckThat! Task 1 (Check-worthiness) and Task 2 (Subjectivity), which aims to evaluate how consistent Large Language Models (LLMs) can distinguish between objective truths worth fact checking and subjective opinions. Our approach was based on prompt engineering utilizing Google's pre-trained LLM Gemini. To optimize performance, we including a random subset of the training data in the input prompt while also augmenting the test data through paraphrasing. We achieved and F1 score of 0.564 for Task 1 and 0.445 for Task 2 which ranked us 24th and 14th respectively. This work contributes to understanding the limitation of LLMs and highlights one of their major pitfalls, subjective reasoning. © 2024 Copyright for this paper by its authors.

关键词： Zero-shot learning

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Exploring Soft-Label Training for Implicit Discourse Relation Recognition 5

Exploring Soft-Label Training for Implicit Discourse Relatio...

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5th Workshop on Computational Approaches to Discourse, CODI 2024

作者： Costa, Nelson Filipe Kosseim, Leila Laboratory Department of Computer Science and Software Engineering Concordia University MontréalQC Canada

ISBN: (纸本)9798891760790

This paper proposes a classification model for single label implicit discourse relation recognition trained on soft-label distributions. It follows the PDTB 3.0 framework and it was trained and tested on the DiscoGeM corpus, where it achieves an F1-score of 51.38 on third-level sense classification of implicit discourse relations. We argue that training on soft-label distributions allows the model to better discern between more ambiguous discourse relations. © 2024 Association for Computational Linguistics.

关键词： Classification (of information)

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Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

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computers, Materials & Continua 2023年第6期75卷 5379-5393页

作者： Abida Sharif Imran Sharif Muhammad Asim Saleem Muhammad Attique Khan Majed Alhaisoni Marriam Nawaz Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadPakistan Faculty of Computing Riphah International UniversityFaisalabadPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science UET TaxilaTaxilaPakistan Department of Software Engineering UET TaxilaTaxilaPakistan Software Engineering Department College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942KSA Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

The Internet of Vehicles(IoV)is a networking paradigm related to the intercommunication of vehicles using a *** a dynamic network,one of the key challenges in IoV is traffic management under increasing vehicles to avoid ***,optimal path selection to route traffic between the origin and destination is *** research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network ***,this work proposed a novel use of the Ant Colony Optimization(ACO)algorithm and formulated the path planning optimization problem as an Integer Linear Program(ILP).This integrates the future estimation metric to predict the future arrivals of the vehicles,searching the optimal *** the mobile nature of IOV,fuzzy logic is used for congestion level estimation along with the ACO to determine the optimal *** model results indicate that the suggested scheme outperforms the existing state-of-the-art methods by identifying the shortest and most cost-effective ***,this work strongly supports its use in applications having stringent Quality of Service(QoS)requirements for the vehicles.

关键词： Internet of vehicles internet of things fuzzy logic optimization path planning

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Navigating the Digital Twin Network landscape:A survey on architecture,applications,privacy and security

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High-Confidence Computing 2024年第4期4卷 129-149页

作者： Akshita Maradapu Vera Venkata Sai Chenyu Wang Zhipeng Cai Yingshu Li Department of Computer and Information Sciences Towson UniversityTowson21252USA Department of Software Engineering and Game Development Kennesaw State UniversityMarietta30060USA Department of Computer Science Georgia State UniversityAtlanta30303USA

In recent years,immense developments have occurred in the field of Artificial Intelligence(AI)and the spread of broadband and ubiquitous connectivity *** has led to the development and commercialization of Digital Twin(DT)*** widespread adoption of DT has resulted in a new network paradigm called Digital Twin Networks(DTNs),which orchestrate through the networks of ubiquitous DTs and their corresponding physical *** create virtual twins of physical objects via DT technology and realize the co-evolution between physical and virtual spaces through data processing,computing,and DT *** high volume of user data and the ubiquitous communication systems in DTNs come with their own set of *** most serious issue here is with respect to user data privacy and security because users of most applications are unaware of the data that they are sharing with these platforms and are naive in understanding the implications of the data ***,currently,there is not enough literature that focuses on privacy and security issues in DTN *** this survey,we first provide a clear idea of the components of DTNs and the common metrics used in literature to assess their ***,we offer a standard network model that applies to most DTN applications to provide a better understanding of DTN’s complex and interleaved communications and the respective *** then shed light on the common applications where DTNs have been adapted heavily and the privacy and security issues arising from the *** also provide different privacy and security countermeasures to address the previously mentioned issues in DTNs and list some state-of-the-art tools to mitigate the ***,we provide some open research issues and problems in the field of DTN privacy and security.

关键词： Digital Twin Networks Network architecture Privacy and security Federated learning Blockchain Internet of Vehicles 6G Supply chain

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Reflections on Conducting Online Think-Alouds

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ACM Inroads 2023年第2期14卷 26-34页

作者： Imbulpitiya, Asanthika Whalley, Jacqueline Senapathi, Mali Computer Science and Software Engineering Department Auckland University of Technology St Paul StreetCentral Auckland1010 New Zealand

This article presents a protocol for conducting online think-aloud interviews as well as the reflections of the participants and interviewer on this process. The interviewer and participants commenced the interviews in person but then shifted to an online mode partway through the study. Thus, their reflections provide a comparison of the two different modes. These reflections are situated within a study of novice database designers. This computer science context, to some extent, influences both the protocol and the experiences of the study participants. Recommendations based on these experiences are provided for future computer science education researchers interested in using an online mode for conducting think-alouds, and suggestions for the use of aspects of the protocol in teaching are presented. © 2023 ACM.

关键词： Education computing

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A Practical Learning-Based FTL for Memory Constrained Mobile Flash Storage

A Practical Learning-Based FTL for Memory Constrained Mobile...

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2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Du, Zelin Huang, Kecheng Wang, Tianyu Yao, Xin Chen, Renhai Shao, Zili The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong College of Computer Science and Software Engineering Shenzhen University Shenzhen China Huawei Technologies China

ISBN: (纸本)9783982674100

The rapidly growing mobile market is pushing flash storage manufacturers to expand capacity into the terabyte range. However, this presents a significant challenge for mobile storage management: more logical-to-physical page mappings are desired to be efficiently managed and cached while the available caching space is extremely limited. This motivates us to shift toward a new learning-based paradigm: rather than maintaining mappings for individual pages, the learning-based approach can represent mapping relationships for a set of continuous pages. However, to construct linear models, existing methods that either consume the already-limited memory space or reuse flash garbage collection demonstrate poor model construction capabilities or significantly degrade flash performance, making them impractical for real-world use. In this paper, we propose LFTL, a practical, learning-based on-demand flash translation layer design for flash management in mobile devices. In contrast to prior work that centered around gathering sufficient mappings for linear model construction, our key insight is that linear patterns can be extracted and refined by leveraging the orderly, LPA-aligned write stream typical of mobile devices. By doing this, highly accurate linear models can be constructed regardless of the constraints of mobile device's cache limitation. We have implemented a fully functional prototype of LFTL based on FEMU. Our evaluation results show that LFTL is more adaptable to memory-constrained storage devices than state-of-the-art learning-based approaches. © 2025 EDAA.

关键词： flash translation layer learned index Mobile flash storage

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Fortifying Healthcare Data Security in the Cloud:A Comprehensive Examination of the EPM-KEA Encryption Protocol

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computers, Materials & Continua 2024年第5期79卷 3397-3416页

作者： Umi Salma Basha Shashi Kant Gupta Wedad Alawad SeongKi Kim Salil Bharany Computer Science and Information Technology Jazan UniversityJazanSaudi Arabia CSE Eudoxia Research UniversityNew CastleUSA Department of Information Technology College of Computer ScienceQassim UniversityBuraydahSaudi Arabia National Center of Excellence in Software Sangmyung UniversitySeoulKorea Department of Computer Science and Engineering Lovely Professional UniversityPhagwaraPunjabIndia

A new era of data access and management has begun with the use of cloud computing in the healthcare *** the efficiency and scalability that the cloud provides, the security of private patient data is still a majorconcern. Encryption, network security, and adherence to data protection laws are key to ensuring the confidentialityand integrity of healthcare data in the cloud. The computational overhead of encryption technologies could leadto delays in data access and processing rates. To address these challenges, we introduced the Enhanced ParallelMulti-Key Encryption Algorithm (EPM-KEA), aiming to bolster healthcare data security and facilitate the securestorage of critical patient records in the cloud. The data was gathered from two categories Authorization forHospital Admission (AIH) and Authorization for High Complexity *** use Z-score normalization forpreprocessing. The primary goal of implementing encryption techniques is to secure and store massive amountsof data on the cloud. It is feasible that cloud storage alternatives for protecting healthcare data will become morewidely available if security issues can be successfully fixed. As a result of our analysis using specific parametersincluding Execution time (42%), Encryption time (45%), Decryption time (40%), Security level (97%), and Energyconsumption (53%), the system demonstrated favorable performance when compared to the traditional *** suggests that by addressing these security concerns, there is the potential for broader accessibility to cloudstorage solutions for safeguarding healthcare data.

关键词： Cloud computing healthcare data security enhanced parallel multi-key encryption algorithm(EPM-KEA)

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Optimization of Decentralized Caching with Improved Coded Delivery Under Heterogeneous File Popularity 22

Optimization of Decentralized Caching with Improved Coded De...

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22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Zhang, Siyu Liang, Jiasheng Deng, Yong Lakehead University Department of Software Engineering ON Canada Binghamton University Department of Computer Science New York United States

ISBN: (纸本)9798331508050

This paper considers the design and optimization of decentralized coded caching under heterogeneous file popularity. We propose a decentralized nested coded caching scheme (D-NCCS) that implements an improved nested coded delivery strategy to avoid using zero-padding, a common sub-optimal approach for simplifying the coded delivery under heterogeneous file popularity. We formulate a joint optimization problem to jointly optimize the cache placement and nested coded delivery strategies of the D-NCCS, and develop a successive approximation algorithm to solve the problem. Numerical results demonstrate the close to optimal performance of the optimized D-NCCS. © 2025 IEEE.

关键词： Approximation algorithms

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The role of ChatGPT in sports trauma: a mini review on strengths and limits of open AI application

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Discover Artificial Intelligence 2023年第1期3卷 40页

作者： Hasnain, Muhammad Mehboob, Bilal Imran, Shahid Department of Computer Science Lahore Leads University Lahore54000 Pakistan Department of Software Engineering Superior University Lahore Lahore54000 Pakistan

Purpose: This paper is focused on the role of ChatGPT an artificial intelligence (AI) language model in the area of sports trauma. Sports trauma represents some significant concerns due to its prevalence and impacts. The objective of this study is to present an overview of the literature on how ChatGPT handles information about sports trauma, considering both its strengths and limitations. Methods: A review method is used in this study. Well-known online databases such as PubMed, scienceDirect, Springer and Google Scholar were searched for the relevant studies. In addition, ChatGPT application was accessed to provide the concise information on the research topic. Results: Search strategy resulted in 30 articles on the topic. Among them only seven studies revealed the potential applications of ChatGPT in sports. The other five studies presented the current status on ChatGPT and sports trauma. The results show that ChatGPT generates information on several types of sports trauma that align with the published literature. However, some limitations of ChatGPT are identified such as its tendency to provide general information about sprains and lack of updated statistics on sports trauma. This study also identified some serious concerns such ethical considerations, data privacy and security regarding the ChatGPT application in sports industry. Conclusion: Despite having some limitations, the ChatGPT application has potential to be used in healthcare, and particularly in sports trauma. The implications of this study guide scholars for the development of enhanced AI systems, which are tailored to redress the challenges of sports trauma. © The Author(s) 2023.

关键词： Sports

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Efficient Bit-Plane Based Medical Image Cryptosystem Using Novel and Robust Sine-Cosine Chaotic Map

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computers, Materials & Continua 2025年第4期83卷 917-933页

作者： Zeric Tabekoueng Njitacke Louai A.Maghrabi Musheer Ahmad Turki Althaqafi Department of Electrical and Electronic Engineering College of Technology(COT)University of BueaBueaP.O.Box 63Cameroon Department of Software Engineering College of EngineeringUniversity of Business and TechnologyJeddah22246Saudi Arabia Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India Department of Computer Science School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah22246Saudi Arabia

This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map,which allows us to select optimal parameter configurations for the encryption *** findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors,an essential characteristic for effective *** encryption technique is based on bit-plane decomposition,wherein a plain image is divided into distinct bit *** planes are organized into two matrices:one containing the most significant bit planes and the other housing the least significant *** subsequent phases of chaotic confusion and diffusion utilize these matrices to enhance *** auxiliary matrix is then generated,comprising the combined bit planes that yield the final encrypted *** results demonstrate that our proposed technique achieves a commendable level of security for safeguarding sensitive patient information in medical *** a result,image quality is evaluated using the Structural Similarity Index(SSIM),yielding values close to zero for encrypted images and approaching one for decrypted ***,the entropy values of the encrypted images are near 8,with a Number of Pixel Change Rate(NPCR)and Unified Average Change Intensity(UACI)exceeding 99.50%and 33%,***,quantitative assessments of occlusion attacks,along with comparisons to leading algorithms,validate the integrity and efficacy of our medical image encryption approach.

关键词： Image cryptosystem robust chaos sine-cosine map nonlinear analysis tools medical images

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