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4th International Informatics and software engineering Conference, IISEC 2023

作者： Idushan, K.A.S. Dilshan, P.G.T. Jayasundera, P.S. Madhushan, K.L.B. Krishara, Jenny Wijendra, Dinuka Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350318036

This research aims to develop a comprehensive system for Sinhala Sign Language (SSL) that includes a learning system, dynamic sign detection, audio/video to sign conversion, and vocal training. SSL plays a crucial role in facilitating communication for individuals who are deaf or hard of hearing in Sri Lanka. The learning system provides a platform for learning SSL and includes a text-To-sign language interpreter. The dynamic sign detection system uses computer vision techniques to identify and interpret dynamic signs accurately. The audio/video to sign conversion system bridges the gap between spoken language and SSL by converting auditory information into visual representations. The vocal training system focuses on enhancing the vocal skills of cochlear implanted children. This research contributes to the development of effective communication and language skills for SSL users. © 2023 IEEE.

关键词： Learning systems

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Adapting Pedagogical Frameworks to Online Learning: Simulating the Tutor Role with LLMs and the QUILT Model 6

Adapting Pedagogical Frameworks to Online Learning: Simulati...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Madhubhashana, Sandaru Ranhinda, Vibhashana Jayakody, Dineth Shavinda, Lakmuthu Nawarathne, Malithi Haddela, Prasanna Sri Lanka Institute of Information Technology Dept. of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

This paper presents SoloScholar, a novel asynchronous online learning platform designed to deliver personalized education to large undergraduate student groups by integrating established pedagogical frameworks with Large Language Models (LLMs). Leveraging Bloom's Revised Taxonomy, learners are categorized into beginner, intermediate, and advanced levels to personalize the educational content. The platform employs the Questioning and Understanding to Improve Learning and Thinking (QUILT) model to structure tutorial sessions and simulate the teaching role of a tutor at a Higher Education Institute (HEI). To generate contextually relevant and cognitively appropriate questions, carefully crafted prompts are fed into LLMs, synthesizing information from reliable knowledge sources. The efficacy of SoloScholar was evaluated through a dual assessment approach: a technical evaluation using the Retrieval Augmented Generation Assessment (RAGAS) framework and a human evaluation involving academic experts. The technical evaluation demonstrated high scores in answer relevancy and context utilization across all learning levels. Similarly, quantitative responses from academic experts indicated strong satisfaction with the quality and appropriateness of the generated content. The findings underscore the potential of integrating LLMs with pedagogical models to enhance personalization in online education. SoloScholar effectively addresses challenges associated with large-group teaching by providing adaptive learning experiences that cater to diverse cognitive needs. © 2024 IEEE.

关键词： Contrastive Learning

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Comparative Models of Price Estimation Using Multiple Linear Regression and Random Forest Methods

Comparative Models of Price Estimation Using Multiple Linear...

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2023 International Conference on Computer Science, information Technology and engineering, ICCoSITE 2023

作者： Crosss Sihombing, Denny Jean Othernima, Desi C. Manurung, Jonson Sagala, Jijon Raphita Atma Jaya Catholic University of Indonesia Faculty of Engineering Dept. Information System Jakarta Indonesia STMIK Pelita Nusantara Dept. Software Engineering Medan Indonesia STMIK Pelita Nusantara Dept. Information Technology Medan Indonesia

ISBN: (纸本)9798350320954

The house is one of the essential humans needs as a place to gather and do activities with family, and shelter, as well as a means of investment. The growth rate of people's demand for housing, especially houses in an area, is influenced by the rate of population growth in that area. Some regions in Indonesia with a reasonably high population growth rate are Jakarta, Bogor, Depok, Tangerang, and Bekasi (Jabodetabek). On the other hand, property entrepreneurs must be able to project house prices because businesses engaged in the property sector are currently very competitive. This study aims to model and compare several machine learning methods to estimate house prices in Jabodetabek based on facilities, year of construction, location, land and building area, number of rooms, condition of house construction, and legality documents. This modeling uses Multiple Linear Regression and Random Forest methods. The results of the modeling evaluation where the Random Forest model has an accuracy rate of 95.6%, while the Multiple Linear Regression model has an accuracy rate of 75%. © 2023 IEEE.

关键词： Multiple linear regression

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AI-Powered IT Project Management: Analyzing the Effectiveness of Advanced Project Management Tools to Ensure Project Efficiency

AI-Powered IT Project Management: Analyzing the Effectivenes...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Das, Jiban Krisna Elegbe, Ifeoluwa Coffie, Lord Khadka, Rojeena Chen, Lei Ji, Yiming Georgia Southern University Dept. of Information Technology StatesboroGA United States College of Computing and Software Engineering Kennesaw State University United States

ISBN: (纸本)9798331504847

The integration of Artificial Intelligence (AI) into project management has significantly transformed traditional methodologies, particularly within the information Technology (IT) sector. This study investigates the effectiveness of AI-powered tools, specifically Asana, Jira, and *** to improve project management efficiency through automation, resource optimization, and decision-making processes. Using a systematic literature review and quantitative analysis, the research highlights the capabilities and limitations of these tools in the management of complex IT projects. The study findings reveal that AI-powered platforms facilitate real-time tracking, predictive analytics and dynamic resource allocation, which collectively contribute to reduced project timelines and improved outcomes. However, challenges such as data quality, integration complexities, and the need for skilled personnel remain prevalent. The study was summarized with strategic recommendations for organizations to incorporate automation, leverage predictive analytics, and improve data integrity, thus maximizing the benefits of AI in project management. This research underscores the critical role of AI in modernizing project management practices, which ultimately leads to increased productivity and project success rates in the IT domain. © 2025 IEEE.

关键词： Project management

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Methodology for Creating Annotated Datasets of Biological Objects in Microscopic Images 5

Methodology for Creating Annotated Datasets of Biological Ob...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Kovalenko, Sergii Kovalenko, Svitlana Kutsenko, Alexander Godlevskyi, Mykhailo Severin, Valery Kovalenko, Anton Dept. of System Analysis and Information-Analytical Technologies National Technical University "KhPI" Kharkiv Ukraine Dept. of Software Engineering and Management Intelligent Technologies National Technical University "KhPI" Kharkiv Ukraine

ISBN: (纸本)9798350384499

The study presents a methodology for automatically creating an annotated dataset for further use in training neural networks. The method is based on the Crisp-DM framework and consists of 6 stages: business understanding, data understanding, data preparation, modeling, evaluation, deployment, which has been modified due to the specifics of computer vision tasks. As a modeling method, the k-means method is proposed, which is applied to the normalized area and average color data of a given object. The approach is tested for creating an annotated dataset for recognizing and localizing cells of different types in blood smear images. The output is a dataframe with the columns file_name, xmin, ymin, xmax, ymax, type, area, which represent the file name, the coordinates of the upper left and lower right points of the bounding boxes, the cell type, and its area. Using these parameters and image processing libraries it is easy to add bounding boxes to the original images. The resulting annotated dataset is analyzed. Metrics were calculated and a loss matrix was constructed. All calculations were performed using the Python programming language and the Pandas, numpy, openCV, and matplotlib libraries. ©2024 IEEE.

关键词： Image segmentation

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Suitable and Style-Consistent Multi-Texture Recommendation for Cartoon Illustrations

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ACM Transactions on Multimedia Computing, Communications and Applications 2024年第7期20卷 1-26页

作者： Wu, Huisi Wang, Zhaoze Li, Yifan Liu, Xueting Lee, Tong-Yee College of Computer Science and Software Engineering Shenzhen University No. 3688 Nanhai Road Nanshan District Guangdong Shenzhen518060 China Dept. of Computer Science and Information Engineering National Cheng-Kung University No. 1 University Road Tainan70101 Taiwan

Texture plays an important role in cartoon illustrations to display object materials and enrich visual experiences. Unfortunately, manually designing and drawing an appropriate texture is not easy even for proficient artists, let alone novice or amateur people. While there exist tons of textures on the Internet, it is not easy to pick an appropriate one using traditional text-based search engines. Although several texture pickers have been proposed, they still require the users to browse the textures by themselves, which is still labor-intensive and time-consuming. In this article, an automatic texture recommendation system is proposed for recommending multiple textures to replace a set of user-specified regions in a cartoon illustration with visually pleasant look. Two measurements, the suitability measurement and the style-consistency measurement, are proposed to make sure that the recommended textures are suitable for cartoon illustration and at the same time mutually consistent in style. The suitability is measured based on the synthesizability, cartoonity, and region fitness of textures. The style-consistency is predicted using a learning-based solution since it is subjective to judge whether two textures are consistent in style. An optimization problem is formulated and solved via the genetic algorithm. Our method is validated on various cartoon illustrations, and convincing results are obtained. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Textures

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Design of a Smart and Green Industry 4.0 Architecture 24

Design of a Smart and Green Industry 4.0 Architecture

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24th International Arab Conference on information Technology, ACIT 2023

作者： Hamdan, Khaled Kazar, Okba College of It Uaeu Dept. of Computer Science and Software Engineering United Arab Emirates College of It Uaeu Dept. of Information Systems & Security United Arab Emirates

ISBN: (纸本)9798350384307

The industrial sector has entered a phase of profound change which sees digital technologies being integrated into the heart of industrial processes. This fourth industrial era gives birth to a new generation of factory called 'Digital Factory', 'Industry 4.0'. This industrial change is the result of the integration of new digital technologies into manufacturing processes and the optimization of energy consumption. The commitment to the environment is also a key and success factor of Industry 4.0 and green in particular the reduction of carbon emissions and pollution. This is how smart green industry try to take in charge the problem of energy consumption and to reduce the Co2 pollution. The goal of this paper is to present the new model of smart green industry using distributed artificial intelligence based on multi-agent system (MAS). The motivation to use the intelligent approach based on MAS is based on the similarity between the fundamental concepts of the cyber-physical system and those contained in the architecture and operation of MAS such as communication, coordination, decision and cooperation. © 2023 IEEE.

关键词： environmental impact Industry 4.0 smart and green Industry 4.0

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Quality Obstacles of Distance Learning: Experiences from Students of the University of Benghazi 3

Quality Obstacles of Distance Learning: Experiences from Stu...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer engineering, MI-STA 2023

作者： Suweel, Osamah Sulayman Yahya Maatuk, Abdelsalam M. Abdalla, Mohamed A E Benghazi University Faculty of Information Technology Dept. of Information Systems Benghazi Libya Libyan International Medical University Faculty of Information Technology Benghazi Libya Benghazi University Faculty of Information Technology Dept. of Software Engineering Benghazi Libya

ISBN: (纸本)9798350319897

Adopting distance learning with a high level of quality in universities and educational institutions is a real challenge. Therefore, several studies and organizations have provided different standards to evaluate the quality of long-distance and to measure the obstacles. This study examines the quality obstacles of the long-distance learning techniques applied at the Faculty of information Technology at the University of Benghazi, Libya. The British Quality Assurance Agency (BQAA) standards are utilized and presented as a questionnaire to the students at the faculty. The total participant number is 223 respondents. The study findings show that the students face severe challenges in all categories of the BQAA of technical, social, and organizational obstacles. The level of challenges is represented in the negativity of the response 69.1%, 60.1%, and 59.44% of the determined categories. © 2023 IEEE.

关键词： Quality assurance

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Dynamic View Synthesis of Thin Structures with Short-term Movements from Monocular Videos Using Neural Radiance Fields 25

Dynamic View Synthesis of Thin Structures with Short-term Mo...

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25th International Conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Rajapaksha, Uchitha Laga, Hamid Diepeveen, Dean Bennamoun, Mohammed Sohel, Ferdous School of Information Technology Murdoch University MurdochWA Australia The University of Western Australia Dept. of Computer Science and Software Engineering CrawleyWA Australia

ISBN: (纸本)9798350379037

Learning to generate motions of thin structures such as plant leaves in dynamic view synthesis is challenging. This is because thin structures usually undergo small but fast, non-rigid motions as they interact with air and wind. When given a set of RGB images or videos of a scene with moving thin structures as input, existing methods that map the scene to its corresponding canonical space for rendering novel views fail as the object movements are too subtle compared to the background. Disentangling the objects with thin parts from the background scene is also challenging when the parts show fast and rapid motions. To address these issues, we propose a Neural Radiance Field (NeRF)-based framework that accurately reconstructs thin structures such as leaves and captures their subtle, fast motions. The framework learns the geometry of a scene by mapping the dynamic images to a canonical scene in which the scene remains static. We propose a ray masking network to further decompose the canonical scene into foreground and background, thus enabling the network to focus more on foreground movements. We conducted experiments using a dataset containing thin structures such as leaves and petals, which include image sequences collected by us and one public image sequence. Experiments show superior results compared to existing methods. Video outputs are available at https://***/. © 2024 IEEE.

关键词： Rendering (computer graphics)

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Measures of Organizational Process Performance in the Capability Maturity Model Integration 24

Measures of Organizational Process Performance in the Capabi...

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24th International Arab Conference on information Technology, ACIT 2023

作者： Al-Ghuwairi, Abdel-Rahman Al-Fraihat, Dimah Sharrab, Yousef Kittaneh, Ahmed Ali, Ahmed Alsarhan, Ayoub Alkhalidy, Muhsen The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Dept. of Software Engineering Jordan Isra University Faculty of Information Technology Dept. of Software Engineering Jordan Isra University Faculty of Information Technology Dept. of Artificial Intelligence and Data Science Jordan The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Dept. of Cyber Security Jordan The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Dept. of Information Technology Jordan

ISBN: (纸本)9798350384307

The Capability Maturity Model Integration (CMMI) is widely utilized by organizations to facilitate process improvement. Among its 22 process areas, this paper focuses on the Organizational Process Performance (OPP) area, which assesses the effectiveness of a process. Specifically, this study examines one goal (establishing performance baselines and models) and two practices (establishing quality and process performance objectives and selecting processes within OPP. To measure these practices, the Goal Questions Metrics (GQM) approach is employed. Data was collected using a questionnaire, and the defined measures are validated quantitatively. 250 responses were used for analysis. The results obtained indicate that implementing the defined measures in companies would be beneficial for achieving high-quality processes in OPP and advancing the maturity level of CMMI. © 2023 IEEE.

关键词： Goal Questions Metrics (GQM) software Quality, Organizational Process Performance, Capability Maturity Model Integration, CMMI

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