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HighTech and Innovation Journal 2025年第1期6卷 67-80页

作者： Latubessy, Anastasya Wardoyo, Retantyo Musdholifah, Aina Kusrohmaniah, Sri Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Informatics Engineering Faculty of Engineering Universitas Muria Kudus Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Psychology Faculty of Psychology Universitas Gadjah Mada Yogyakarta55281 Indonesia

Fine Tuning Attribute Weighted Naïve Bayes (FTAWNB) is a reliable modified Naïve Bayes model. Even though it is able to provide high accuracy on ordinal data, this model is sensitive to outliers. To improve the performance of FTAWNB, this research modified the Partial Instances Reduction (PIR) technique to make the FTAWNB more adaptive to outliers. Nevertheless, in contrast to the original PIR technique, which substitutes missing values for data values deemed outliers, the PIR technique suggested in this study replaces data values deemed outliers using a Naïve Bayes weighting approach. The attribute values from the outlier data are replaced with the highest probability values for the attributes in the actual class. This PIR technique is referred to as modified PIR. The FTAWNB model with modified PIR has been evaluated using the Gaming Disorder dataset. Replacing the four attributes with the least amount of information resulted in accuracy gains of 99.74%, an increase of 1.53% over the FTAWNB model. The experimental result shows that adding the modified PIR technique to the FTAWNB model can handle the outlier in the data, proving it by increasing the performance in terms of accuracy, precision, and recall without pruning the dataset used. © 2025, Ital Publication. All rights reserved.

关键词： Attribute Weighted Classification Fine-Tune Gaming Disorder Instances Reduction Naïve Bayes

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Rule-Based Dialect of Tulang Bawang Stemmer

Rule-Based Dialect of Tulang Bawang Stemmer

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2025 International Conference on Advancement in Data science, E-learning and Information System, ICADEIS 2025

作者： Abidin, Zaenal Junaidi, Akmal Wamiliana Lumbanraja, Favorisen Rosyking Kurniasari, Dian Borman, Rohmat Indra Doctoral Program of Mathematics and Natural Sciences Universitas Lampung Bandar Lampung Indonesia Universitas Lampung Department of Computer Science Bandar Lampung Indonesia Universitas Lampung Department of Mathematics Bandar Lampung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandar Lampung Indonesia

ISBN: (纸本)9798331513320

Stemming, an essential procedure in natural language processing (NLP), diminishes words to their base forms, facilitating tasks such as information retrieval and sentiment analysis. Although stemming techniques for highresource languages are well-developed, numerous low-resource languages, including dialect of Tulang Bawang, suffer from inadequate solutions owing to a scarcity of linguistic data and resources. Existing systems, including rule-based stemmers, have demonstrated efficacy in processing low-resource languages such as Indonesian and Javanese by utilizing established morphological rules. Nonetheless, these methods encounter considerable obstacles, such as restricted adaptability, inability to accommodate unusual root structures, and excessive dependence on fixed rules that might result in over- or understemming. Rule-based methodologies frequently misidentify roots when faced with intricate affixes or unconventional word forms. We introduce an improved rule-based Tulang Bawang Stemmer aimed at overcoming these constraints by enhancing current linguistic rules and integrating new patterns specific to the language's morphology. Assessed on 500 test samples and 200 independent test samples, our improved stemmer attained gold standard evaluation metrics of 96.2% and 94%, respectively, surpassing prior implementations in both precision and generalization. The findings demonstrate the potential of enhanced rule-based techniques to improving NLP for lowresource languages. Improved stemming performance enables better downstream applications, promotes more efficient text analysis, and advances research in underrepresented languages. © 2025 IEEE.

关键词： Linguistics

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Advances in 3D fusion of multimodal medical images: 3D reconstruction of bone, muscle, and ligament structures under load from radiographs and magnetic resonance imaging

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Research on Biomedical Engineering 2025年第1期41卷 1-35页

作者： da Silva, Daniel S. Astolfi, Rodrigo S. Jagatheesaperumal, Senthil K. Selvaraj, Priyadharsini Russel, Newlin Shebiah de Albuquerque, Victor Hugo C. Post-Graduation Program of Medical Surgical Sciences Federal University of Ceara CE Fortaleza60455-970 Brazil Department of Teleinformatics Engineering Federal University of Ceara CE Fortaleza60455-970 Brazil Department of Electronics and Communication Engineering Mepco Schlenk Engineering College TN Sivakasi626005 India Department of Computer Science and Engineering Mepco Schlenk Engineering College TN Sivakasi626005 India

Purpose: Foot and ankle pathologies are among the most prevalent conditions within the human locomotor system. Imaging examinations are crucial for diagnosing, treating, and achieving satisfactory functional outcomes for these conditions. However, conventional imaging exams often fail to capture all the necessary details for precise analysis, necessitating the use of multiple imaging modalities to evaluate bones, ligaments, cartilage, and other structures. Objective: This research aims to explore computational technologies and algorithms for 3D reconstruction and fusion of foot and ankle images, alongside the analysis, segmentation, classification, and evaluation techniques applied to these images. Methods: The study investigates different computational approaches for 3D reconstruction and multimodal image fusion, integrating X-ray and MRI data. Advanced segmentation and classification techniques are applied to enhance the precision of structural assessment. Additionally, we assess the availability and quality of databases for training and validating these models. Results: Our findings highlight a significant gap in research concerning these specific applications, as well as a shortage of suitable databases for 3D reconstruction and fusion of images from X-rays and MRI. Conclusion: The study emphasizes the need for dedicated datasets and further research to develop effective computational solutions for multimodal foot and ankle imaging. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical Engineering 2025.

关键词： Magnetic resonance imaging

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A Performance Study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis

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Procedia computer science 2025年 253卷 84-93页

作者： Anak Agung Ayu Putri Ardyanti Zhiqiang Xie Andrea Stevens Karnyoto Bens Pardamean Ni Made Estiyanti School of Computer Science and Technology Harbin University of Science and Technology Harbin 150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Doctoral School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, computer science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions.

关键词： integrated scheduling assembly job shop scheduling heuristic algorithm genetic algorithm bibliometric analysis

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Rule-Based Dialect of Tulang Bawang Stemmer

Rule-Based Dialect of Tulang Bawang Stemmer

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Advancement in Data science, E-learning and Information Systems (ICADEIS), International Conference on

作者： Zaenal Abidin Akmal Junaidi Wamiliana Favorisen Rosyking Lumbanraja Dian Kurniasari Rohmat Indra Borman Doctoral Program of Mathematics and Natural Sciences Universitas Lampung Bandar Lampung Indonesia Department of Computer Science Universitas Lampung Bandar Lampung Indonesia Department of Mathematics Universitas Lampung Bandar Lampung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandar Lampung Indonesia

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

关键词： Measurement Sentiment analysis Text analysis Electronic learning Morphology Linguistics Data science Information retrieval Machine translation Information systems

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Damage-Free Neutral Beam Etching for Gate Recess in E-mode AlGaN/GaN HEMTs

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第5期46卷 705-708页

作者： Chen, Yi-Ho Chu, Fu-Chuan Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Solid State Devices Section Electronic System Research Division National Chung-Shan Institute of Science and Technology Taoyuan325 Taiwan Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science international graduate program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Recess gate etching is a critical technique for achieving enhancement-mode (E-mode) AlGaN/GaN high-electron mobility transistors (HEMTs) because the interface is susceptible to the etching damage. This study fabricates recess gates using the neutral beam etching (NBE) technique. By adjusting the aperture thickness in the NBE apparatus, we simulate both NB-mode and plasma-mode etching. The electrical characteristics of E-mode HEMTs fabricated using these two modes are analyzed and compared through DC, noise, and pulsed IV measurements. The results demonstrate that NB-recessed HEMTs exhibit superior performance. © 2025 IEEE.

关键词： Aluminum gallium nitride

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Design of a Framework Based on MCDM and Data Analytics for Improving the Inventory Management of Supplies for Clinical Studies: A Case Study in a Research Center of a High Complexity Clinic 26th

Design of a Framework Based on MCDM and Data Analytics for I...

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26th International Conference on Human-computer Interaction, HCII 2024

作者： Jiménez-Delgado, Genett Isabel Aslan, Imran Hernández-Palma, Hugo Orozco Bohorquez, Mario Acosta Ortega, Felipe Plazas-Alvarado, Jonny Jiménez-Coronado, Angélica Roncallo-Pichon, Alberto Morales-Espinosa, Roberto Department of Industrial Engineering Institución Universitaria de Barranquilla IUB Barranquilla Colombia Faculty of Health Sciences Bingöl University Bingöl12000 Turkey Faculty of Engineering Industrial Engineering Program Corporación Universitaria Iberoamericana IBERO Bogotá Colombia Department of Computer Science and Electronics Universidad de la Costa CUC Barranquilla Colombia Faculty of Economic Accounting and Administrative Sciences Business Administration Program Fundación Universitaria de Popayan Popayan Colombia Bogotá Colombia Department of Business Transformation - Business Administration Program Corporación Unificada Nacional de Educación Superior – CUN Bogotá Colombia Faculty of Economic Administrative and Accounting Sciences. Accounting Program Corporación Universitaria Americana Barranquilla Colombia International Business Program Fundación Universitaria CEIPA Barranquilla Colombia

ISBN: (纸本)9783031768088

Inventory management in the health sector, specifically in the pharmaceutical service, represents a high percentage of logistics costs, putting pressure on health institutions to optimize inventory management to guarantee the availability of supplies. On the other hand, different regulations worldwide establish the adoption of mechanisms and policies for adequate inventory management, a situation that in low- and middle-income countries is restricted by resource limitations and the low implementation of robust techniques and methodologies. Different applications of models for inventory management have been identified in the literature, such as optimization models, Lean tools, and multicriteria decision-making methods. However, integrated approaches to optimize demand management, ordering, and controlling pharmaceutical services supplies are still under development. Therefore, the present study proposes a three-phase hybrid approach based on MCDM techniques and data analytics to improve inventory management of the pharmaceutical service in a health research center. The first stage consisted of characterizing the process to identify aspects for improvement. In the second stage, a multicriteria ABC classification model based on F-AHP and TOPSIS was applied to classify laboratory supplies for three selected clinical studies. Furthermore, the appropriate forecasting method was chosen for each clinical study, and a combined model (P model and FEFO model) was applied to establish the reorder point. Then, strategies, mechanisms, and policies were proposed to improve inventory management and redesign the process flow. As the main results, a multicriteria ABC method was obtained to classify laboratory supplies, taking into account Rotation (GW = 0.512), Criticality (GW = 0.286), and Availability (GW = 0.203). On the other hand, through data analysis and regression models, the exponential smoothing model with α = 0.10 was identified as the most convenient forecasting model, as

关键词： Decision making

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Landscape of Biomedical Engineering and Technology in Nigeria: A Perspective

Biomedical Engineering Education

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Biomedical Engineering Education 2025年 1-12页

作者： Oyejide, Ayodele James Abodunrin, Oluwatosin David Atoyebi, Ebenezer Oluwatosin Oni, Bola Idoko, Joy Ene Adeyemi, Ayoade Adetunji Akindele, Goodnews Adedayo, Sadiq Adewale Biomedical Engineering Department Afe Babalola University Ado Ekiti Nigeria Department of Electronics Engineering Kadir Has University Istanbul Turkey UEMF Euromed University of Fes Fès Morocco Department of Biomedical Engineering Federal University of Technology Akure Nigeria Department of Biomedical Engineering Achievers University Owo Nigeria Biomedical Engineering Department University of Ibadan Ibadan Nigeria Department of Computational Science and Engineering Kadir Has University Istanbul Turkey Doctoral School of Computer Science University of Vienna Vienna Austria

Since their introduction into Nigeria in the 1990s, biomedical engineering and technology have played a transformative role in the healthcare industry. This paper presents a perspective on the current landscape of biomedical engineering and technology in Nigeria, beginning with a historical overview and the development of academic and practical aspects of the fields. Emphasis is placed on the dual pathways of academic training and professional practice within the healthcare sector, along with an exploration of local and international collaborations, ongoing initiatives, regulatory frameworks, and the structure of teaching and curricula. Key challenges facing biomedical engineering and technology education and practice are discussed, including funding and staffing. The insights provided in this paper are informed by the authors’ collective experiences, which include participation in industry and healthcare-based internships, as well as international academic exposure in biomedical engineering. Based on these perspectives, both short- and long-term strategies are proposed to address existing challenges. The conclusion posits that sustainable growth in biomedical engineering and technology can be achieved through collaborative efforts among professional bodies, strategic funding initiatives, and a targeted approach to addressing local healthcare needs.

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Indonesian Sign Language System (SIBI) Dataset: Sentences Enhanced by Diverse Facial Expressions for Total Communication

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Data in Brief 2025年

作者： I Dewa Made Bayu Atmaja Darmawan Linawati Gede Sukadarmika Ni Made Ary Esta Dewi Wirastuti Reza Pulungan Doctoral Engineering Department Udayana University Denpasar Indonesia Electrical Engineering Department Udayana University Badung Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

Total communication in sign language is a communication approach that involves several components in conveying information, including hand movements, body movements, lip movements, and facial expressions. Currently, there is no publicly available Indonesian Sign Language (SIBI) dataset. Therefore, researchers must collect their own data. Utilizing diverse datasets can result in partiality when making inferences about the suggested approach. The SIBI dataset was built by involving 10 teachers and 10 hearing-impaired high school students. The SIBI dataset includes basic signs and sign sentences. Basic sign gestures include letters, numbers, and affixes, according to the SIBI online dictionary published by the Indonesian Government. Sentences are created by several teachers using common communication phrases during learning process. Sign language sentences are delivered using total communication, which combines lip movements, body movements, and facial expressions. The same sentence can be delivered with different facial expressions, giving different meanings. This article discusses how a sign sentence is expressed with different facial expressions. In SIBI, word morphology follows the rules of the Indonesian language. Therefore, this paper also explains the morphemic structure of the 40 sentences used as references. The use of the SIBI dataset can be adjusted to certain research parameters. The video dataset can be converted into a series of frames or images as needed for the research. Although audio is not available, the SIBI video data captures lip movements that can be used in lip reading research. The SIBI dataset can facilitate research in computer vision as well as other fields of study related to sign language.

关键词： sign language SIBI hand gestures facial expression total communication video data

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