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An efficient framework for evaluating the usability of academic websites: Calibration, validation, analysis, and methods

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Neutrosophic Sets and Systems 2023年 53卷 179-201页

作者： Eldrandaly, Basma K. Ali, Ahmed A. Chakrabortty, Ripon K. Abdel-Basset, Mohamed Faculty of Computers and Informatics Zagazig University Ash Sharqia Governorate Zagazig44519 Egypt School of Engineering and Information Technology University of New South Wales Canberra Australia

The success of an organization nowadays is heavily dependent on the usability of its website. Offering educational content and services online is becoming more commonplace in the higher education sector. University websites serve a wide range of users, like students, faculty, parents, staff, etc. Hence, the website must address the different needs of these users while maintaining good usability. Good usability makes it easier for users to find what they are looking for, understand how to use the website, and navigate through the content. This helps improve user satisfaction and engagement with the website, which can lead to increased productivity and better outcomes. Therefore, usability testing and analysis is the unspoken metric for success. Understanding the many factors contributing to the usability of academic websites is a multi-criteria decision-making (MCDM) topic. In this paper, we propose a framework for evaluating the usability of academic websites using the Entropy and Weighted Aggregated Sum Product Assessment (WASPAS) MCDM methods under type-2 neutrosophic sets. The entropy method is used to compute the objective weights of four main criteria contributing to the usability of academic websites, namely (Content, Organization, Presentation and Interaction, and Trustworthiness), with 31 sub-criteria. The WASPAS method is then used to rank five Egyptian university websites and select the best one in terms of usability. This framework will help designers understand the important criteria to consider while designing for university websites in addition to providing them with a usability evaluation method tailored to university websites. © 2023,Neutrosophic Sets and Systems. All Rights Reserved.

关键词： Decision making

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Improving Diabetes Mellitus Diagnosis Performance Using DBSCAN Case-Based Reasoning and Clustering Approaches 10

Improving Diabetes Mellitus Diagnosis Performance Using DBSC...

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10th IEEE Information technology International Seminar, ITIS 2024

作者： Heriyani, Dina Yulina Sulistyorini, Dewi Irawan, Buntoro Purnomo, Agus Sidiq Yasin, Iskandar Kurniawan, V. Reza Bayu Universitas Sarjanawiyata Tamansiswa Faculty of Engineering Department of Informatics Yogyakarta Indonesia Universitas Sarjanawiyata Tamansiswa Faculty of Engineering Department of Civil Engineering Yogyakarta Indonesia Universitas Mercu Buana Yogyakarta Faculty of Information Technology Department of Informatics Yogyakarta Indonesia Universitas Sarjanawiyata Tamansiswa Faculty of Engineering Department of Industrial Engineering Yogyakarta Indonesia

ISBN: (纸本)9798331521295

Diabetes Mellitus (DM) is a chronic disease whose prevalence continues to increase throughout the world, including in Indonesia. The limited number of medical personnel and the large amount of health data that must be managed require technology that can help the diagnosis process faster and more accurately. In this study, a Case-Based Reasoning (CBR) system was developed which was optimized with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method to improve the performance of Diabetes Mellitus diagnosis. CBR works by utilizing previous cases to solve new cases, while DBSCAN is used to group large and irregular medical data. This grouping process reduces the complexity of searching for relevant cases, thereby increasing the efficiency of diagnosis. The test results show that the proposed system is able to increase the accuracy of diagnosis by up to 93%, with a shorter case encounter time compared to other methods. The accuracy value was obtained from the results of the diagnosis test using case data of 30 diabetes mellitus patients. The innovation in this study is the development of a CBR-DBSCAN-based diagnostic system in the health system to support medical personnel in providing a fast and accurate diagnosis. © 2024 IEEE.

关键词： Case-Based Reasoning (CBR) clustering DBSCAN Diabetes Mellitus medical diagnosis

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Automatic Deployment to Kubernetes Cluster by Applying a New Learning Tool and Learning Processes 10

Automatic Deployment to Kubernetes Cluster by Applying a New...

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10th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Golis, Tomáš Dakić, Pavle Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 4 Slovakia Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia

The rapid growth and widespread adoption of containerization technologies, such as Docker, and the increasing popularity of Kubernetes as a container orchestration platform have significantly shaped the landscape of modern software development and deployment. Containers have created a paradigm shift in application packaging, offering a consistent and portable environment across diverse infrastructure setups. Meanwhile, Kubernetes has emerged as the dominant choice for managing containerized applications at scale, providing features such as automated scaling, load balancing, and fault tolerance. However, despite the numerous advantages containers and Kubernetes offer, deploying applications to a Kubernetes cluster often poses challenges due to the steep learning curve and complex configuration requirements. To address these challenges, this paper aims to introduce a comprehensive learning tool that automates and simplifies the deployment process on Kubernetes clusters. © 2023 Copyright for this paper by its authors.

关键词： CI/CD Container orchestration Docker image Kubernetes

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Complete DouDizhu Agents: Bid Learning from Pretrained Cardplay 5

Complete DouDizhu Agents: Bid Learning from Pretrained Cardp...

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5th Annual IEEE Conference on Games, CoG 2023

作者： Li, Chuanfa Troillet, Lucien Kiminori, Matsuzaki Kochi University of Technology Graduate School of Engineering Kami Japan Kochi University of Technology School of Informatics Kami Japan

ISBN: (纸本)9798350322774

DouDizhu is a challenging game that includes aspects of both competition and cooperation. In this game, players start by bidding based on their hand cards. They then follow by a round of cardplay in which the goal is to empty one's hand of cards first. So far, other teams have elected to mainly concentrate on the cardplay phase in which agents such as DouZero and PerfectDou have recently achieved top performances. In this paper, we focus on bidding as it is a key component that greatly influences the starting states of the cardplay phase. We train bidding agents with an algorithm similar to DouZero and use PerfectDou for the cardplay phase. We then compare our agent to win-rate based and cheating agents. Our trained agent beat the win-rate agents. © 2023 IEEE.

关键词： Reinforcement learning

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Development of an Autograding System for Weld Bead Surface Quality using Feature Extraction and Mahalanobis-Taguchi System

Development of an Autograding System for Weld Bead Surface Q...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Harudin, Nolia Norizhar, Muhammad Azfar Hazim Marlan, Zulkifli Marlah Selamat, Farah Elida Binti Dept. of Mechanical Engineering Selangor Malaysia Razak Faculty of Technology and Informatics Kuala Lumpur Malaysia

ISBN: (纸本)9798350347050

Autograding systems are becoming more prevalent to address the challenges inherent in teaching and learning assessment. Over the past few decades, technological advancements have increased image processing techniques, including pattern recognition research. The Mahalanobis-Taguchi System (MTS) is a technique for assessing system performance by analyzing multivariate data to make quantitative choices via the development of a multivariate measurement scale. This study intends to develop a grading tool that combines a feature extraction technique with MTS theory, which instructors will utilize at the UNITEN Manufacturing Processes Laboratory to assess the quality of weld bead surface work prepared by UNITEN students. The Mahalanobis Distance (MD) will distinguish between normal and abnormal extracted image patterns from workpieces and transform them into a measurable scale. The samples defined better grading with lower MD. A jig was developed to collect consistent and accurate image data for the image-capturing process. The results showed that out of 10 test samples, 2 samples were classified as normal with a grading range between 75% to 82%. Another sample was classified as gray regions, with grading ranges between 65% and 74%. The remaining 6 samples were classified as abnormal, with a grading range between 40% to 64%. An autograding tool for evaluating welding surface quality utilizing MD scales was established. © 2023 IEEE.

关键词： Grading

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Job Resumes Recommendation using Integration of Fuzzy Discernibility Matrix Feature Selection and Convolutional Neural Network Multi-label Text Classification

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第13期49卷 49-58页

作者： Hayami, Regiolina Yusoff, Nooraini Daud, Kauthar Mohd Fatma, Yulia Department of Informatics Engineering Faculty Computer Science Universitas Muhammadiyah Riau Indonesia Faculty of Data Science and Computing Universiti Malaysia Kelantan 16100 Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and Technology Universiti Kebangsaan Malaysia 43600 Malaysia

The manual analysis of job resumes poses specific challenges, including the time-intensive process and the high likelihood of human error, emphasizing the need for automation in content-based recommendations. Recent advancements in deep learning, particularly Convolutional Neural Networks (CNN) for Multi-label Text Classification (MLTC), offer a promising solution for addressing these challenges through artificial intelligence. While CNN is renowned for its robust feature extraction capabilities, it faces specific challenges such as managing high-dimensional data and poor data interpretability. To address these limitations, this study employs the Fuzzy Discernibility Matrix (FDM) feature selection technique to determine the relevance of skills for each job vacancy. FDM assigns weights to the features of each job category and ranks their relevance based on the highest scores, which are then utilized in the MLTC CNN model. The integration of FDM and MLTC CNN serves as the foundation for generating content-based recommendations derived from key features in job resumes. This study produces a content-based job recommendation system that displays the top three job categories, accompanied by explanations of the skills supporting each selected category. These recommendations also consider cosine similarity values between analyzed items and the integrated results of FDM and MLTC CNN. The application of FDM for feature weighting has been proven to enhance multi-label text classification outcomes by providing better insights during the feature selection process. With a recall of 97.26%, precision of 94.81%, and accuracy of 98.58%, the MLTC model integrating FDM feature selection and CNN demonstrates robust performance characteristics in content-based job recommendation tasks. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Convolutional neural networks

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LQR and Pole Placement Controllers with Integral Action Design Technique and Performance Analysis for Control of Temperature Field in Continuous Casting Process 24

LQR and Pole Placement Controllers with Integral Action Desi...

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24th International Carpathian Control Conference, ICCC 2023

作者： Zarghoon, Sohaibullah Belavy, Cyril Solvak University of Technology Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Bratislava Slovakia

ISBN: (纸本)9798350310221

This paper presents the design of Linear Quadratic Regulator and Pole Placement controllers with integral action using MATLAB and Simulink for controlling the temperature field in the secondary cooling zone of a continuous casting process. The secondary cooling zone in continuous casting represents a distributed parameter system. During steel production, the type of steel produced changes continuously, necessitating a control system that can respond quickly and flexibly. We compared the performance of the Linear Quadratic Regulator and Pole Placement control techniques for the temperature field in the secondary cooling zone by analyzing the system's response. The simulation results demonstrate that the Linear Quadratic Regulator technique outperforms the Pole Placement technique for the specified system. © 2023 IEEE.

关键词： Continuous casting

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Sentiment Analysis of Cooking Oil Price Policy in Indonesia using Word2Vec Feature Extraction and Bidirectional Long Short Term Memory 10

Sentiment Analysis of Cooking Oil Price Policy in Indonesia ...

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10th International Conference on Advanced informatics: Concept, Theory and Application, ICAICTA 2023

作者： Sugiarto, Dedy Utami, Ema Yaqin, Ainul Raharjo, Suwanto Universitas Trisakti Faculty of Industrial Technology DKI Jakarta Indonesia Universitas Amikom Yogyakarta Master Program of Informatics Engineering Yogyakarta Indonesia Informatics IST AKPRIND Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9798350329919

The policy of the Ministry of Trade of the Republic of Indonesia which sets the highest retail price for cooking oil and then cancels it in early 2022 due to people's complaints about the difficulty of getting cooking oil in the market has received many responses from the public via social media. This study conducts sentiment analysis using Word2Vec and Bidirectional Long Short Term Memory (BLSTM) with the aim of studying the public's response to the removal of the highest retail price policy and effect of both skip-gram (SG) and continuous bag-of-words (CBOW), window size and dimension to the word similarity and accuracy. Data taken via Twitter in March 2022. The data then goes through preprocessing stages, manual labeling by experts, and word embedding using Word2Vec to be further classified using BLSTM. Data labeling produces imbalanced data where the largest is neutral sentiment (53%) followed by negative (27%) and positive (20%). ome of the words such as 'mafia', 'mahal', 'langka', 'tangkap', 'bongkar', and 'mendag' could become the government's attention. The similarity value of the SG model tends to have a higher value than CBOW at a lower word vector dimension. The model that gives the best performance results is the Word2Vec model with 50 dimensions, SG architecture and window size 5. This is shown in the accuracy of 0.71 which is the highest value and only shows slight signs of overfitting. Symptoms of over fitting will be more visible with increasing dimensions. © 2023 IEEE.

关键词： Sentiment analysis

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Simulation and Control of a Continuously Cast Steel Billet in an Induction Furnace∗ 9

Simulation and Control of a Continuously Cast Steel Billet i...

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9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Zarghoon, Sohaibullah Bartalsky, Lukas Belavy, Cyril Institute of Automation Measurement and Applied Informatics Slovak University of Technology Faculty of Mechanical Engineering Bratislava Slovakia

ISBN: (纸本)9798350311402

This paper presents a solution to a problem that Khan Steel Company in Afghanistan encountered in their induction furnace. The motivation for deploying induction heating technology in the industry is outlined, including a description of the current situation. Basic approaches for managing this technology, critical to the industry's success, are also provided. The process of creating an induction heating model using the COMSOL Multiphysics environment is described, with emphasis placed on the importance of starting the machine and determining the system's dynamics once it is in production mode. Finally, an identification and control proposal based on the distributed parameter system is presented, followed by a demonstration of the proposed control system using simulation results. © 2023 IEEE.

关键词： Induction heating

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Financial Sustainability of Automotive Software Compliance and Industry Quality Standards 8th

Financial Sustainability of Automotive Software Compliance ...

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8th International Congress on Information and Communication technology, ICICT 2023

作者： Dakić, Pavle Todorović, Vladimir Vranić, Valentino Faculty of Informatics and Computing Singidunum University Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia Faculty of Business Studies and Law MB University Belgrade Serbia

ISBN: (纸本)9789819930906

Achieving a high level of quality in the AV industry involves understanding the complexity of the production cycle with the constant challenges of applying appropriate standards. The need for compliance based on relevant certificates implies the creation of an environment of trust between manufacturers, component suppliers, and end customers. Research should sublimate the most current standards from various fields related to data protection, security, system sustainability, environmental management, financial sustainability, and business transparency. The success of a complex parts supply system is impossible without a stable approach to IT security. The control of production processes sometimes involves using non-standardized techniques, and one of the applicable ones is work-in-progress (WIP), which describes the use of partially finished raw materials in the stages of obtaining final products. Key points and the contribution of the current study are in getting a better overview of the situation within this area related to standards and the financial problems that can arise due to a lack of understanding of standards compliance. The main limitations within the study itself refer to the consideration of the theoretical foundations that should be used during future research related to the practical part during implementation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

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