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2024 IEEE International Conference on computing, ICOCO 2024

作者： Kadir, Tuty Asmawaty Abdul Xuan, Desmond Yap Wen Nazri, Siti NurAishah Faculty of Computing Center of Artificial Intelligence and Data Science Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Malaysia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan Malaysia

ISBN: (纸本)9798331530303

This article presents the development and evaluation of "Flood," a 3D simulation game designed to enhance public awareness of flood safety measures. The game features two distinct phases: the Pre-flood phase, where players prepare for impending flood conditions, and the Evacuation phase, where they must navigate various hazards to reach safety. By utilizing the Unity platform, "Flood" immerses players in realistic scenarios that promote learning through engagement. Results from a survey of 20 participants indicate that the game successfully simulates flood situations, with 80% of respondents affirming its effectiveness in conveying essential flood awareness. The majority of players reported learning crucial safety measures, such as avoiding power lines and preparing emergency bags. Furthermore, feedback highlighted high levels of engagement, with 70% rating the game at the highest level of interest. ©2024 IEEE.

关键词： Disasters

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Development of an Enhanced Quality Score Calculation Method for Accurate Assessment of Hotel Quality 5

Development of an Enhanced Quality Score Calculation Method ...

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5th International Conference on Advancements in computing, ICAC 2023

作者： Athurugiriya, A. A. A. Gaweshini Sumathipala, Prasanna Hemachandra, K.M. Tharindu Anupa Sri Lanka Institute of Information Technology Faculty of Computing Department of Data Science Malabe Sri Lanka

ISBN: (纸本)9798350358131

In this research paper, an enhanced hotel quality scoring method (EHQSM), is presented as a revolutionary way to analyze hotel quality. The EHQSM combines sentiment analysis, HOLSERV Plus dimensions classification, and amenity scores to deliver a more thorough review. The study generates an overall sentiment score by doing sentiment analysis on reviews categorized into HOLSERV Plus dimensions then thoughtfully averaging it using dimensionspecific weights collected from a survey. The availability of necessary amenities is considered when calculating the amenity score. The novel feature of this approach is how the amenity score, and sentiment score are carefully combined and efficiently weighted using values from the survey. The result is an improved quality score that accurately and thoroughly describes the quality of hotel services. With the goal of facilitating informed decisions for both hotel owners and attentive tourists, this technique establishes an updated standard for the evaluation of hospitality quality. © 2023 IEEE.

关键词： Sentiment analysis

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Enhancing Hotel Customer Satisfaction Assessment with Semantic Search-based Scoring 5

Enhancing Hotel Customer Satisfaction Assessment with Semant...

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5th International Conference on Advancements in computing, ICAC 2023

作者： Hemachandra, K.M Tharindu Anupa Sumathipala, Prasanna Athurugiriya, A.A.A Gaweshini Sri Lanka Institute of Information Technology Department of Data Science Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

Within the hospitality sector, ensuring customer satisfaction takes precedence, particularly in economies such as Sri Lanka, where tourism serves as a vital growth catalyst. Interestingly, disparities often arise between customer ratings and their written evaluations. This study presents an innovative strategy that utilizes semantic search techniques to extract comprehensive insights from customer feedback, leading to the development of a robust hotel scoring system. By exploring intricate emotions via advanced linguistic analysis, this method reveals underlying cues that conventional metrics often overlook. The method's effectiveness is validated through a comparative study with established hotel ratings. This advancement not only refines precise customer satisfaction assessment for hotels but also bears strategic significance for countries aiming to fortify their tourism sectors. In this era centered around data, this research provides a pivotal standpoint for optimizing hospitality evaluation, thereby enriching guest experiences, and guiding well-informed operational choices. © 2023 IEEE.

关键词： Sentiment analysis

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Determining environmental indicators related to the propagation of contagious diseases and health issues: A Systematic Literature Review 18

Determining environmental indicators related to the propagat...

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18th Iberian Conference on Information Systems and Technologies, CISTI 2023

作者： Portillo, Janeth Dominguez Peralta, Laura M. Rodriguez Sampaio, Paulo N. M. Nunes, Eldman De Oliveira Faculty of Information Technologies and Data Science Mexico Graduate Program in Computing and Systems Bahia Salvador Brazil

ISBN: (纸本)9789893347928

The environmental indicators provide significant information in order to describe the state of a phenomenon, environment or area [1]. This paper addresses the indicators present in the air and their relationship in the accommodation and transmission of viruses, as well as how these environmental indicators can lead to health problems. Therefore, the main goal of this work is to review the scientific contributions in the literature in order to determine and select the potential environmental indicators present in indoor environments which have an impact on the health of people who work and live within these spaces. For this purpose, we carried out a Systematic Literature Review (SLR) related to environmental monitoring, COVID-19, Internet of things, air pollution and environmental indicators within indoor spaces. This SLR allowed us to identify indicators that according to their level of presence can represent a high risk for people's health. Therefore, the process of planning, conducting and reporting the Systematic Literature Review enabled us not only to identify some environmental indicators, but also their corresponding monitoring advantages and disadvantages, and multiple perspectives and approaches of each contribution in the literature. Further on, this study will be the basis for the proposal of an automatic and intelligent platform based on Internet of Things for monitoring indoor environments in order to detect high risk levels for the contamination of contagious diseases. © 2023 ITMA.

关键词： COVID-19

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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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Shrinkage Estimation for Location and Scale Parameters of Logistic Distribution Under Record Values

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Annals of data science 2024年第4期11卷 1209-1224页

作者： Gupta, Shubham Vishwakarma, Gajendra K. Elsawah, A.M. Department of Mathematics & amp Computing Indian Institute of Technology Dhanbad826004 India Department of Statistics and Data Science Faculty of Science and Technology Beijing Normal University-Hong Kong Baptist University United International College Zhuhai519087 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai519087 China Department of Mathematics Faculty of Science Zagazig University Zagazig44519 Egypt

Logistic distribution (LogDis) is frequently used in many different applications, such as logistic regression, logit models, classification, neural networks, physical sciences, sports modeling, finance and health and disease studies. For instance, the distribution function of the LogDis has the same functional form as the derivative of the Fermi function that can be used to set the relative weight of various electron energies in their contributions to electron transport. The LogDis has wider tails than a normal distribution (NorDis), so it is more consistent with the underlying data and provides better insight into the likelihood of extreme events. For this reason the United States Chess Federation has switched its formula for calculating chess ratings from the NorDis to the LogDis. The outcomes of many real-life experiments are sequences of record-breaking data sets, where only observations that exceed (or only those that fall below) the current extreme value are recorded. The practice demonstrated that the widely used estimators of the scale and location parameters of logistic record values, such as the best linear unbiased estimators (BLUEs), have some defects. This paper investigates the shrinkage estimators of the location and scale parameters for logistic record values using prior information about their BLUEs. Theoretical and computational justifications for the accuracy and precision of the proposed shrinkage estimators are investigated via their bias and mean square error (MSE), which provide sufficient conditions for improving the proposed shrinkage estimators to get unbiased estimators with minimum MSE. The performance of the proposed shrinkage estimators is compared with the performances of the BLUEs. The results demonstrate that the resulting shrinkage estimators are shown to be remarkably efficient. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Mean square error

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Improving the Cost of Updates in Virtual Knowledge Graphs

Improving the Cost of Updates in Virtual Knowledge Graphs

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2024 Joint Ontology Workshops - Episode X: The Tukker Zomer of Ontology, and Satellite Events, JOWO 2024

作者： Wandji, Romuald Esdras Calvanese, Diego Department of Computing Science Umeå Universitet Umeå Sweden Research Centre for Knowledge and Data Faculty of Engineering Free University of Bozen-Bolzano Bolzano Italy

Virtual Knowledge Graph (VKG) is known as a data integration paradigm used to efficiently manage the heterogeneity of richly structured data that is common inside several organizations, in inter-organizational settings, and more openly on the Web. Although such a paradigm continues to gain importance in both foundational and applied research, updates in VKG systems remain an open challenge that has received less attention. Yet, a solution to such a problem would be of great importance, as it would allow VKG systems to be full-fledged, thus allowing end-users to fully manage source data through the lens of the ontology they are exposed to. This research aims to propose a comprehensive framework for instance-level updates in VKGs, where updates posed over the ontology have to be translated into source-level updates and, more importantly, how the side effects related to the propagation of ontology-based updates to the underlying data source can be minimized. © 2024 Copyright for this paper by its authors.

关键词： Knowledge graph

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Enhancing Match Detection Process Using Chi-Square Equation for Improving Type-3 and Type-4 Clones in Java Applications

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International Journal of Advanced Computer science and Applications 2025年第4期16卷 777-784页

作者： Abdullah, Noormaizzattul Akmaliza Mubarak-Ali, Al-Fahim Hamza, Mohd Azwan Mohamad Yaacob, Siti Salwani Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan Malaysia Centre For Artificial Intelligence & Data Science Universiti Malaysia Pahang Al-Sultan Abdullah Lebuh Persiaran Tun Khalil Yaakob Gambang Pahang Kuantan26300 Malaysia

Generic Code Clone Detection (GCCD) is a code clone detection model that use distance measure equation, enabling detection of all types of code clones, naming clone Type-1, Type-2, Type-3 and Type-4 in Java programming language applications. However, the detection process of GCCD did not focus on detecting clones of Type-3 and Type-4. Hence, this paper suggested two experiments to incorporate enhancements to the GCCD in order to improve the detection rate of clone Type-3 and clone Type-4. The implementation of Chi-square distance in the match detection process produced a significant result increase in the experiment specifically on clones Type-3 and Type-4, in comparison with the Euclidean distance in GCCD, which allows the increase of detection rate due to the dissimilarity of the distance measures. Based on the results, the suggested enhancement using Chi-square distance on match detection process outperforms GCCD in terms of improving code clone detection results based on clone Type-3 and Type-4, as the objectives for each experiment are carried, contributes to the research on improving the code clone detection result. © (2025), (science and Information Organization). All rights reserved.

关键词： Java programming language

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LF-ViT: Reducing Spatial Redundancy in Vision Transformer for Efficient Image Recognition 38

LF-ViT: Reducing Spatial Redundancy in Vision Transformer fo...

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38th AAAI Conference on Artificial Intelligence, AAAI 2024

作者： Hu, Youbing Cheng, Yun Lu, Anqi Cao, Zhiqiang Wei, Dawei Liu, Jie Li, Zhijun AIoT Lab Faculty of Computing Harbin Institute of Technology China Swiss Data Science Center Zurich Switzerland School of Cyber Engineering Xidian University China

ISBN: (纸本)1577358872

The Vision Transformer (ViT) excels in accuracy when handling high-resolution images, yet it confronts the challenge of significant spatial redundancy, leading to increased computational and memory requirements. To address this, we present the Localization and Focus Vision Transformer (LF-ViT). This model operates by strategically curtailing computational demands without impinging on performance. In the Localization phase, a reduced-resolution image is processed;if a definitive prediction remains elusive, our pioneering Neighborhood Global Class Attention (NGCA) mechanism is triggered, effectively identifying and spotlighting class-discriminative regions based on initial findings. Subsequently, in the Focus phase, this designated region is used from the original image to enhance recognition. Uniquely, LF-ViT employs consistent parameters across both phases, ensuring seamless end-to-end optimization. Our empirical tests affirm LF-ViT's prowess: it remarkably decreases Deit-S's FLOPs by 63% and concurrently amplifies throughput twofold. Code of this project is at https://***/edgeai1/***. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Image recognition

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Exploring Machine Learning in IoT Smart Home Automation 8

Exploring Machine Learning in IoT Smart Home Automation

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8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023

作者： Waseem, Quadri Wan Din, Wan Isni Sofiah Bin Ab Rahman, Azamuddin Nisar, Kashif Faculty of Computing Pekan Malaysia AnalytiCray Kuala Lumpur55100 Malaysia Swinburne University of Technology Sydney Professional Computing Data Science ParramattaNSW2150 Australia

ISBN: (纸本)9798350310931

The Internet of Things (IoT) has evolved in these years. Various types of organizations, industries, research domains and almost all types of intelligent future applications are utilizing the advantages of IoT. These applications include smart homes, smart cities, smart infrastructure smart communities, smart healthcare, smart agriculture and many more. 'Smart Homes' has emerged as one the latest Internet of Things (IoT) applications known to automate household equipment's using remote or automated functioning from remote locations to improve the quality of life for its inhabitants. For a smart home system to function effectively, the machine learning (ML) implementation must go beyond basic remote control and simple automation. To fully realize its potential and provide homeowners with tremendous and unexpected benefits, more research and development in the fields of machine intelligence and smart home automation are required. In this research work, we aim to traverse ML in IoT smart home automation by classifying the home automation applications. We propose a taxonomy of machine learning (ML) for smart homes based on its application. This research also includes related surveys and literature reviews along with open challenges and issues as well as future directions in detail. © 2023 IEEE.

关键词： Automation

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