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2023 International Conference on Computer Science, Information Technology and Engineering, ICCoSITE 2023

作者： Nugraha, Dian Oktaviati, Risna Faizah, Safira Ahmed, Falah Y. H. Jakarta Global University Informatics Engineering Depok Indonesia Sohar University Faculty of Computing and IT Sohar Oman

ISBN: (纸本)9798350320954

The Sars-CoV-2 pandemic resulted in limited space for the public to interact and carry out their daily routines. The limited space available forces everyone to be more creative in meeting their daily needs. With currently developing technology, new information ecosystems have been developed to address problems especially in critical fields such as health, the economy and education. Artificial intelligence is now very commonly implemented in various fields, Decision Support Systems (DSS) are AI which are often found in most systems that are widely used. Many studies have been conducted using DSS. However, only a few are focused on overcoming the support system for the pandemic that has occurred since late 2019. Most of these DSS methods use outranking methods for multi-criteria parameters owned by users who require wise decisions to be decided. The outranking method has been developed in this article with the aim of obtaining a self-diagnosis system for patients with covid types of Alpha (B.1.17), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1 529) this detection system was developed using Electre and Promethee methods. Both methods utilize outranking to obtain detection results based on multi-criteria decisions of the symptoms experienced by the patient. From the system that has been developed, it is obtained data that is quite promising for the implementation of this outranking system, namely for both systems to obtain an accuracy of approximately 90% and more. This data indicates that the role of artificial intelligence, especially the decision system, is a method that is reliable enough to be implemented in MCDM (Multi-Criteria Decision Making). © 2023 IEEE.

关键词： Coronavirus

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Technology Usage for Education: Polytechnic Deaf or Hard-of-Hearing Student 6

Technology Usage for Education: Polytechnic Deaf or Hard-of-...

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6th IEEE Symposium on Computers and informatics, ISCI 2024

作者： Rahim, Rini Hafzah Abdul Nizam, Dinna Nina Mohd Naim, Nur Faraha Mohd Baharum, Aslina Universiti Malaysia Sabah User Experience Group Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Sunway University Computing and Information System School of Engineering and Technology Selangor Malaysia

ISBN: (纸本)9798350353853

This article investigates the application of technology to enhance education for polytechnic deaf or hard-of-hearing (DHH) students. Polytechnic institutions play a crucial role in preparing students for diverse careers through hands-on, practical education. However, DHH students face unique challenges in accessing and fully participating in polytechnic programs. To provide a diverse approach, the technology focusing on visual technology, such as Augmented Reality and Virtual Reality, incorporates crucial components suitable for DHH visual learning modalities. The study uses a mixed-method approach, integrating questionnaires, interviews, and observational data to discover more about DHH lecturers' and students' preferred learning methods. 77 DHH Sijil Khas Operasi Katering student from selected three Polytechnic and Community Colleges gave their feedback from questionnaires, and five lecturers were interviewed to get a clearer picture of the current usage of technology among DHH students at polytechnic and community college. Results of the lecturer's interview suggest that DHH students need visual aids, communication tools, and focus-enhancing resources to help them learn effectively, especially in cooking classes where understanding kitchen equipment and safety is crucial to prevent injuries. Meanwhile, results from DHH students' questionnaires show students' interest and prefer to use technology, with 88% agreeing to use technology such as Games, AR, VR and AR Games for their teaching and learning process and to make their learning process more interesting, fun and enjoyable. Integrating the use of technology and information technology as part of the approach of teaching aids to deaf students is hoped to help them to understand better, focus and have more fun in learning. © 2024 IEEE.

关键词： Augmented reality

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Crop Yield Forecasting Based on Echo State Network Tuned by Crayfish Optimization Algorithm 2

Crop Yield Forecasting Based on Echo State Network Tuned by ...

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2nd IEEE International Conference on Contemporary computing and Communications, InC4 2024

作者： Bacanin, Nebojsa Jovanovic, Luka Djordjevic, Marko Petrovic, Aleksandar Zivkovic, Tamara Zivkovic, Miodrag Antonijevic, Milos Singidunum University Faculty of Informatics and Computing Belgrade Serbia Singidunum University Faculty of Technical Sciences Belgrade Serbia School of Electrical Engineering University of Belgrade Belgrade Serbia

ISBN: (纸本)9798350383652

The agriculture sector, once reliant only on external inputs for increased yields, faces repercussions of diminished natural systems and significant environmental impact. High-precision agriculture aims to curb excessive usage of fertilizers and pesticides while prioritizing sustainability. Modern technologies can shape decisions toward the betterment of soil health, plant protection, and yield enhancement. Predictive models employing machine learning aid farmers in crop performance estimation, disease detection, soil health assessment, and yield prediction among others. These insights inform field operations, logistics, and contract negotiations. Leveraging machinery data, weather data, and drone imagery using machine learning can help us refine farming practices. Recurrent neural networks (RNN) can aid in various farming challenges like plant stress detection and irrigation. Yet, challenges persist in optimizing hyperparameters, a task we tackled using the nature-inspired crayfish optimization algorithm (COA) adapted to tune echo state networks (ESN) for multivariate time series forecasting of crop yield. This study demonstrates the utility of machine learning in agriculture, enabling yield assessment for improved sustainability. © 2024 IEEE.

关键词： Recurrent neural networks

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Analysing Zero-Shot Readability-Controlled Sentence Simplification 31

Analysing Zero-Shot Readability-Controlled Sentence Simplifi...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Barayan, Abdullah Camacho-Collados, Jose Alva-Manchego, Fernando School of Computer Science and Informatics Cardiff University United Kingdom Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9798891761964

Readability-controlled text simplification (RCTS) rewrites texts to lower readability levels while preserving their meaning. RCTS models often depend on parallel corpora with readability annotations on both source and target sides. Such datasets are scarce and difficult to curate, especially at the sentence level. To reduce reliance on parallel data, we explore using instruction-tuned large language models for zero-shot RCTS. Through automatic and manual evaluations, we examine: (1) how different types of contextual information affect a model's ability to generate sentences with the desired readability, and (2) the trade-off between achieving target readability and preserving meaning. Results show that all tested models struggle to simplify sentences (especially to the lowest levels) due to models' limitations and characteristics of the source sentences that impede adequate rewriting. Our experiments also highlight the need for better automatic evaluation metrics tailored to RCTS, as standard ones often misinterpret common simplification operations, and inaccurately assess readability and meaning preservation. © 2025 Association for Computational Linguistics.

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Enhancing the security of E-Health services in Bangladesh using blockchain technology

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International Journal of Information Technology (Singapore) 2022年第3期14卷 1179-1185页

作者： Hossain, Chowdhury Akram Mohamed, Mohamad Afendee Zishan, Md. Saniat Rahman Ahasan, Rabiul Sharun, Siti Maryam Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Malaysia

The telemedicine service concept was mainly established to benefit the underprivileged people from rural areas of a country. However, due to the low literacy and awareness rates among rural population of Bangladesh, the service is not much effective. This paper represents a study on the awareness of the rural population of telemedicine service in Bangladesh and few key findings indicate how the awareness could be increased. The research also suggests that utilizing blockchain technology can enhance the data security and privacy. The research reveals some of the findings which can raise the awareness and popularity of telemedicine service among rural population. We have proposed implementation of blockchain technology which can vastly improve the security issue. © 2021, Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Awareness rate Bangladesh rural areas Blockchain E-Health Survey Telemedicine

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Developing a Visual Dashboard to Improve Research Activity Assessment 11

Developing a Visual Dashboard to Improve Research Activity A...

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11th International Conference on Computer, Control, informatics and its Applications, IC3INA 2024

作者： Nur Rahman, Muhammad Zaki Prakasa, Esa Bijaksana, Moch Arif Bachelor of Data Science Faculty of Informatics Telkom University Bandung Indonesia Bandung Indonesia School of Computing Telkom University Bandung Indonesia

ISBN: (纸本)9798331542313

In research institutions, the ability to monitor and analyze publication output is crucial for assessing productivity and achieving strategic goals. This paper presents a dashboard designed to visualize and analyze publication data from a research center of the Indonesian public institution. The dashboard addresses several key questions: (1) whether the current number of publications is on track to meet the institution’s targets, (2) the comparison between journal and proceeding publications, (3) individual researcher productivity, (4) research group productivity, and (5) the collaborative efforts among researchers and groups. By leveraging this tool, stakeholders can gain insights into publication trends and identify areas for improvement. The findings reveal significant trends in publication types and collaboration patterns, offering a comprehensive overview of the institution’s research output. This study contributes to the understanding of research productivity metrics and their implications for strategic planning in academic research. © 2024 IEEE.

关键词： Collaboration Metrics Dashboard Visualization Publication Data Research Productivity

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Outbound Innovation Strategic Plan for Malaysian SMEs in the Software Industry: An Operational Research Framework 8

Outbound Innovation Strategic Plan for Malaysian SMEs in the...

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8th IEEE International Conference on Recent Advances and Innovations in Engineering, ICRAIE 2023

作者： Yussof, Soffri Syed Zainol Abidin, Syed Nasirin Universiti Malaysia Sabah Decision Support Systems Research Group Faculty of Computing and Informatics Labuan Malaysia

ISBN: (纸本)9798350315516

The role of Small and Medium Enterprises (SMEs) in Malaysia plays a significant component in driving the nation's economic growth the present analysis focuses on a limited number of studies investigating SMEs' systematic methods for pursuing outbound innovation strategies. Hence, the focus is to evaluate the imperative need for outbound innovation strategies that can effectively contribute to a comprehensive strategic approach. This study aims to develop a comprehensive operational research framework that will be incorporated into the formulation of the strategic plan the strategic plan will encompass external technology commercialization strategies specifically designed for SMEs the operational research framework comprises three distinct phases. Phase 1 involves conducting semi-structured interviews. Phase 2 focuses on formulating the Outbound Innovation Strategic Plan (OISP). Lastly, Phase 3 entails evaluating the suitability of the OISP the outcome of this research involves the development of an OISP specifically tailored for Malaysian SMEs in the software industry. © 2023 IEEE.

关键词： Strategic planning

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Image Classification of Occluded and Non-Occluded Cats and Dogs Datasets with Machine Learning

Image Classification of Occluded and Non-Occluded Cats and D...

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2023 IEEE Symposium on Computers and informatics, ISCI 2023

作者： Rumpungan, Jacintha Lucia On, Chin Kim Hijazi, Mohd Hanafi Ahmad Karim, Samsul Ariffin Bin Abdul Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Research Centre Malaysia

ISBN: (纸本)9798350302363

Pet classification performance can be significantly affected by occlusions, such as pillows, hands, blankets, and shadows. Existing research on pet recognition and classification focuses on poses, breeds, and natural scene variations, but there has been limited work on occlusion-based pet classification. This project aims to improve the performance of deep neural networks for pet classification by using data augmentation, transfer learning, and fine-tuning techniques. Two independent datasets of occluded and non-occluded images of cats and dogs are used to evaluate the proposed algorithms. The investigation explores the impact of transfer learning on cat and dog classification using two proposed models: a fine-tuned Convolutional Neural Network (CNN) and a pre-trained VGG16 model. By leveraging advanced techniques such as transfer learning and fine-tuning, this research demonstrates the potential for significantly improving pet image classification performance, especially in scenarios involving occluded images. These findings contribute to the broader field of computer vision and provide valuable insights for further research in pet image analysis and classification. © 2023 IEEE.

关键词： Convolutional neural networks

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Insights into research on blockchain for smart contracts: a bibliometric analysis

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Multimedia Tools and Applications 2024年 1-25页

作者： Singh, Renu Gupta, Ashlesha Mittal, Poonam Faculty of Informatics and Computing J.C. Bose University of Science and Technology YMCA Faridabad India Department of Computer Science & amp Engineering Indraprastha Institute of Information Technology IIIT New Delhi India

Over the past few years, blockchain technology has gained significant attention. This surge in popularity can be attributed to the emergence of cryptocurrencies and the development of smart contracts. Cryptocurrency is a digital currency that eliminates the problem of double spending. Cryptocurrencies like Bitcoin, Ethereum, Litecoin, Stellar, Zcash, Maker, Aave, etc. become popular and are preferred for money transfers. Smart contracts are the next popular technology on the blockchain after cryptocurrency. It can be considered a piece of code that can execute automatically when the predefined conditions are fulfilled. Researchers believe that the potential of blockchain with smart contracts is only in its initial stages and that its true potential has yet to be fully discovered. Hence, an extensive bibliometric analysis is conducted to understand blockchain trends for smart contracts and to give future directions in this field. For this analysis, various steps are followed, starting with formulating the research question, defining the scope of our research, extracting and analyzing data, answering the research question, and finally, drawing a conclusion. This research paper will be fruitful for scholars and researchers, providing an extensive statistical and network analysis of extracted smart contracts publications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Bibliometric analysis Blockchain Crypto contract Scientometrics Scopus Smart contracts VOSViewer

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PowerPlay: Adaptation of Game-Based Learning on Empowering Energy Conservation 22

PowerPlay: Adaptation of Game-Based Learning on Empowering E...

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22nd IEEE Student Conference on Research and Development, SCOReD 2024

作者： Zulkifli, Zuhri Arafah Halim, Faiqah Hafidzah Johari, Nur Farahin Mohd Zaini, Hazrati Mangshor, Nur Nabilah Abu Ishak, Norshahidatul Hasana Samah, Khyrina Airin Fariza Abu Faisal, Muhammad Alif Mohd Universiti Teknikal Malaysia Faculty of Information and Communication Technology Melaka Malaysia Universiti Teknologi MARA College of Computing Informatics and Mathematics Malaysia

ISBN: (纸本)9798331510077

PowerPlay is a game-based learning tool to educate children about energy conservation. It addresses the gap in effective mediums for teaching energy conservation to young learners and the limitations of traditional methods. This study employs the waterfall model methodology to design and implement an interactive educational game. This adaptation features two game modes, EcoFact and EcoGuess, which incorporate educational videos and enjoyment factors to engage children in fun learning about environmental responsibility. This study conducted enjoyment testing following the guidelines from eGameFlow to ensure an engaging and motivating learning experience. Results demonstrate high user engagement and enjoyment levels, validating the game's educational impact. PowerPlay emerges as a promising tool for fostering environmental awareness and responsibility in children through an innovative and enjoyable medium. © 2024 IEEE.

关键词： Energy saving

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