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Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and informatics

作者： Charalampos M. Liapis Isidoros Perikos Konstantinos Kyritsis Vaggelis Kapoulas Michael Paraskevas Department of Mathematics University of Patras Patras Greece and Computer Technology Institute and Press Diophantus Patras Greece Computer Engineering and Informatics Department University of Patras Patras Greece and Computer Technology Institute and Press Diophantus Patras Greece Electrical and Computer Engineering University of the Peloponnese Patras Greece Computer Technology Institute and Press Diophantus Patras Greece Electrical and Computer Engineering University of the Peloponnese Patras Greece and Computer Technology Institute and Press Diophantus Patras Greece

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Help! I need somebody. A Mapping Study about Expert Identification in Software Development 23

Help! I need somebody. A Mapping Study about Expert Identifi...

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37th Brazilian Symposium on Software Engineering, SBES 2023, held in conjunction with the Brazilian Conference on Software: Theory and Practice, CBSoft 2023

作者： Braga, Carlos Santos Jr, Paulo Barcellos, Monalessa Computer Science Department Federal University of Espírito Santo ES Vitoria Brazil Leds Research Department of Informatics Federal Institute of Education Science and Technology of Espírito Santo ES Serra Brazil

ISBN: (纸本)9798400707872

Context: Software development is a knowledge-intensive activity, and its success in an organization relies deeply on knowledge sharing. Knowledge management challenges are often increased in agile environments, which involve a lot of tacit knowledge, commonly acquired through experiences and hard to be made explicit. Therefore, knowledge sharing among practitioners is crucial. However, identifying suitable experts to share specific knowledge is not trivial. It involves not only discovering the individuals with the desired knowledge but also considering other factors that may improve the expert responsiveness, such as social connections and availability. Objective: Considering the important role experts play in knowledge sharing, we decided to investigate approaches that help identify experts that can share knowledge in software development. Our goal is to provide a panorama of the existing approaches and shine a light on research opportunities. Method: We carried out a systematic literature mapping and analyzed 17 publications. Results: The results show that most approaches have relied on code repositories as a source of evidence for identifying experts and, consequently, focus on supporting developers and aiding in the codification activity. Additionally, expert identification has been mostly automated, and factors beyond possessing the desired knowledge have often been disregarded. Conclusion: Although there are several expert identification approaches, there has been a lack of concern with factors that influence reaching the most suitable expert for a specific situation (e.g., considering the characteristics of the person seeking knowledge). Moreover, there is a need for deeper reflection on how to better explore different artifacts as sources of expert evidence and how to combine them to improve expert identification. © 2023 ACM.

关键词： Knowledge management

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HealthAir: A Crowdsourcing mHealth Platform for Air Pollution Effects on Citizens Health Status

HealthAir: A Crowdsourcing mHealth Platform for Air Pollutio...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Ioannis Katsidimas Sotiris Nikoletseas Stefanos H. Panagiotou Christina Spyropoulou Computer Engineering and Informatics Department University of Patras Greece Computer Technology Institute and Press “Diophantus” (CTI) Greece

Crowdsourcing systems offer numerous advantages for acquiring data, which can contribute to the development of modern concepts such as Smart Cities. Air quality in urban areas has been identified as a crucial theme and requirement, towards ideal city of the future that can be adapted upon its citizens' needs and comfort. Thus, besides the sensing infrastructure, a complementary system must be implemented in order to enable the public authority and municipality awareness over citizens' personalised and subjective input, in a cost efficient way that can be easily upscaled. In this work, we present HealthAir, an mHealth application alongside its subsystems (namely a web application and a smartwatch version), that aims to increase and complement the sensing capacity of a Smart City, with respect to the air quality-wise health of the citizens. This is achieved based on questionnaires and surveys approved by the health community, and services and features that implement a bidirectional interaction between the system and the users. Finally, users' data and air quality measurements from a third party platform are combined and presented for the case study realization and demonstration.

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Online Handwritten Recognition for Alphabet Writing Practice 4

Online Handwritten Recognition for Alphabet Writing Practice

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Santiari, Ni Putu Linda Rahayuda, I Gede Surya Institute of Technology and Business STIKOM Bali Information System Study Program Faculty of Informatics and Computer Denpasar Indonesia Informatics Study Program Faculty of Math and Natural Sciences Udayana University Mangupura Indonesia

ISBN: (纸本)9781665453950

Learning to write in children requires the child's habit of using a pencil to write on paper. The manual method has drawbacks such as the use of a lot of paper when children have to study harder to keep repeating the exercises and also cannot be done online remotely. In addition to this, writing exercises on the touchscreen can also train children to be more skilled at using the touchscreen. To overcome these problems, the author will discuss the use of handwriting recognition technology to practice writing capital letters (A-H), where the technology will be built on a web-based basis. The recognition algorithm used is K-NN. Testing the use of the website was carried out at Tunas Mekar Sari Kindergarten, Denpasar. The identification number and result will be stored on the web server. Based on the experiment, it was found that from 80 image data, the K-NN algorithm succeeded in providing accurate recognition results on 60 image data, and obtained an accuracy of 78.75%. © 2022 IEEE.

关键词： Websites

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An Efficient AI Based Approach for Multimedia Traffic Management in Wireless Network 4

An Efficient AI Based Approach for Multimedia Traffic Manage...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Abdullahi, Akibu Mahmoud Usmani, Muhammad Hamza Sheikh, Md Amin Ullah Asirvatham, David Muzzaffar, Saira Chowdhury, Sohini School of Computing and Informatics Albukhary International University Kedah Alor Setar Malaysia School of Computer Science Taylor's University Malaysia School of Computer Science Taylor's University Faculty of Innovation and Technology Subang Jaya Malaysia Lovely Professional University Division of Research and Development Phagwara144411 India KKR KSR Institute of Technology and Sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

This paper deals with the AI based monitoring system called AI Monitoring System (AIMS), which allows to integrate media traffic in the Wireless networks. h In addition to that, every node in the network can obtain a view about the neighbour node transmission and it can also perform the task before sending the traffic. First, it judges the values of SNR ratio and next is the Queue limit of the receiving. AIMS aims at making sure that every node knows all the digitized information of the chosen brand or node. Besides distributional and conditional statistical model, the proposed Bay Estimator Model is used to analyse the signal to noise ratio and choose a path to route the Multimedia traffic. Through developing the recursive analysis matrix, we can figure out the effectiveness of our process. In doing so we will be able to set the default buffer size as well as the guard time thereby maintaining the quality of the service, Multipath adaptability for resilience and also minimize the packet loss ratio. © 2024 IEEE.

关键词： Quality of service

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Classification of SEMG Signal Based Hand Movements by Using Support Vector Machine 6

Classification of SEMG Signal Based Hand Movements by Using ...

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6th IEEE Symposium on computers and informatics, ISCI 2024

作者： Zahra, Syeda Rabail Ismail, Sadia Ali, Muhammad Danish Khan, Muhammad Amir Darus, Mohamad Yusof Mazhar, Tahseen Gomal University Institute of Computing & Information Technology Dera Ismail Khan Pakistan University Islamabad Computer Science Comsats Abbottabad Pakistan Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Shah Alam40450 Malaysia Virtual University of Pakistan Department of Computer Science Pakistan

ISBN: (纸本)9798350353853

This paper explores the application of Surface Electromyography (SEMG) for hand movement classification using machine learning techniques. SEMG signals play a crucial role in sports medicine, rehabilitation, prosthesis control, and medical diagnosis. The study addresses a multi-class problem, extending the dataset with limited prior exploration. Nine features from SEMG signal's time domain are extracted, including Maximum Amplitude, Root Mean Square, Slope Sign Change, Variance, Simple Square Integral, Zero Crossing, Waveform Length, and Willison Amplitude. Linear Discriminant Analysis is employed for dimensionality reduction as a feature selection technique. The proposed algorithm achieves an overall classification accuracy of 72% for the classification of six different hand movements performed by five healthy subjects using Support Vector Machines. This research contributes to the advancement of SEMG-based hand movement classification in various practical applications. © 2024 IEEE.

关键词： Dimensionality reduction

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Recent Trends and Challenges in Assistive Applications for Sinhala-Speaking Adults with Dyslexia: A Decade in Review

Recent Trends and Challenges in Assistive Applications for S...

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Advanced Research in Computing (ICARC), International Conference on

作者： Peshala Perera Deshan Sumanathilaka School of Computing Informatics Institute of Technology Colombo Sri Lanka School of Mathematics and Computer Science Swansea University United Kingdom

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

This paper discusses assistive technologies developed for Sinhala-speaking dyslexics, focusing on the challenges they face and how existing tools attempt to address them. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, this review analyzed research publications from 2015 to 2024, highlighting topics such as phonetic processing, text normalization, and error detection. Of the 85 initially reviewed, 32 were included in the meta-analysis to represent major challenges posed by the lack of annotated datasets and Natural Language Processing (NLP) resources tailored to the cognitive and linguistic needs of the adult patient population. This review points out the need for the extension of low-resource language toolkits and proper integration of assistive NLP applications. The study concludes that while significant progress has been made, a collaborative, interdisciplinary approach is crucial to improving literacy, independence, and social participation for Sinhala-speaking adults with dyslexia.

关键词： Training Adaptation models Collaboration Phonetics Assistive technologies Dyslexia Natural language processing Complexity theory Text to speech Systematic literature review

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SLayR: Scene Layout Generation with Rectified Flow

arXiv

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arXiv 2024年

作者： Braunstein, Cameron Petekkaya, Hevra Lenssen, Jan Eric Toneva, Mariya Ilg, Eddy Saarland University Saarland Informatics Campus Germany Max Planck Institute for Informatics Saarland Informatics Campus Germany Max Planck Institute for Software Systems Saarland Informatics Campus Germany Computer Vision and Machine Perception Lab University of Technology Nuremberg Germany

We introduce SLayR, Scene Layout Generation with Rectified flow, a novel transformer-based model for text-to-layout generation which can then be paired with existing layout-to-image models to produce images. SLayR addresses a domain in which current text-to-image pipelines struggle: generating scene layouts that are of significant variety and plausibility, when the given prompt is ambiguous and does not provide constraints on the scene. SLayR surpasses existing baselines including LLMs in unconstrained generation, and can generate layouts from an open caption set. To accurately evaluate the layout generation, we introduce a new benchmark suite, including numerical metrics and a carefully designed repeatable human-evaluation procedure that assesses the plausibility and variety of generated images. We show that our method sets a new state of the art for achieving both at the same time, while being at least 3× times smaller in the number of parameters. Copyright © 2024, The Authors. All rights reserved.

关键词： Flow simulation

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Through the Sci-Fi Lens: Exploring Social Media's Influence on Body Image and Bullying Among Adolescents in Boarding Schools 21

Through the Sci-Fi Lens: Exploring Social Media's Influence ...

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21st International Learning and technology Conference, L and T 2024

作者： Mustapha, Jawahir Che Ghazali, Muhammad Azmin Mohamed Abdullah, Munaisyah Sulaiman, Nor Intan Saniah Rahman, Hezlin Aryani Abd Universiti Kuala Lumpur Malaysian Institute of Information Technology Informatics & Analytics Section Kuala Lumpur Malaysia Universiti Kuala Lumpur Malaysian Institute of Information Technology Computer Engineering Tech. Section Kuala Lumpur Malaysia Universiti Kuala Lumpur Malaysian Institute of Information Technology Software Engineering Section Kuala Lumpur Malaysia Universiti Utara Malaysia College of Arts and Science School of Quantitative Sciences Kedah Malaysia Universiti Teknologi Mara Centre of Statistical and Decision Science Studies Faculty of Computer and Mathematical Sciences Selangor Malaysia

ISBN: (纸本)9798350393569

This research investigates the complex relationships between social media, body image, and bullying among adolescent boarding school students, with an emphasis on the Malaysian context. Utilizing science fiction as a conceptual lens, the study presents hypothetical future scenarios to investigate how technological advancements could impact these interconnected issues. The paper seeks to provide nuanced insights into the ethical and policy implications of social media use in boarding schools by drawing on key theories such as Social Comparison Theory, Social-Ecological Model and Uses and Gratifications Theory. Through comparative analysis of hypothetical scenarios, this study aims to provide educators, policymakers, and technologists with a comprehensive understanding of the challenges and opportunities at this intersection. The ultimate objective is to contribute to the ongoing discourse concerning adolescent mental health and to propose actionable strategies for mitigating negative outcomes in the unique context of Malaysian boarding schools. © 2024 IEEE.

关键词： Social networking (online)

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Arthropodia-V1: Biodiversity Dataset for Semantic Segmentation, Quality Estimation, and Observation Extraction 5

Arthropodia-V1: Biodiversity Dataset for Semantic Segmentati...

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5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Ayoob, Mohamed Maul, Tomas Chandesa, Tissa Informatics Institute of Technology School of Computing Colombo Sri Lanka The University of Nottingham Malaysia School of Computer Science Semenyih Malaysia

ISBN: (纸本)9798331530983

This paper introduces a novel biodiversity image dataset named Arthropodia, which focuses on three crucial tasks: image quality estimation, semantic segmentation, and observation extraction (image similarity). Arthropodia is collected from tropical Malaysian forests and encompasses a diverse range of arthropod species captured under various lighting and environmental conditions. We manually annotate the dataset for each task, making it suitable for benchmarking and developing AI models applicable to biodiversity and environmental monitoring. To demonstrate its utility, we present baseline results using state-of-the-art deep learning models for each task. Our findings indicate that Arthropodia serves as a valuable resource for advancing research in the field of biodiversity conservation and ecological studies through automated image processing and analysis. The open-access availability of Arthropodia fosters further contributions from the research community, paving the way for the development of robust and accurate AI solutions for biodiversity monitoring and preservation. © 2025 IEEE.

关键词： Semantic Segmentation

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