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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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A Proposal of the Improved Method for Measuring Insulation Resistance between a Photovoltaic Module String and the Earth using the Self-biased Method

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IEEJ Transactions on Power and Energy 2025年第1期145卷 13-20页

作者： Kazama, Takuro Kato, Kazuhiko Doctoral Program in Risk and Resilience Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Renewable Energy Research Center National Institute of Advanced Industrial Science and Technology 2-2-9 Machiikedai Koriyama963-0298 Japan

For safe operation of a photovoltaic generating system, an insulation monitoring function, which can immediately detect deterioration of insulation between photovoltaic module strings and the earth, is indispensable. This function requires accurate measurement, low leakage current and suppression of rising voltage against the earth. In this paper, a new insulation monitoring method of photovoltaic module strings is proposed by the improved existing self-biased method that has an inevitable voltage rise under measurement. In this new method, both terminals of photovoltaic module strings are always connected to the ground with appropriate resistors. Theoretical discussion and experiments for this new method showed precise measurement, and acceptable leakage current under various outdoor conditions. In addition, it was confirmed that this method could sufficiently decrease in the voltage rise compared with the existing self-biased method. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Photovoltaics

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Photovoltaic Fault Detection in Remote Areas Using Fuzzy-Based Multiple Linear Regression (FMLR)

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International Journal of Advanced Computer science and Applications 2025年第4期16卷 243-249页

作者： Ardianto, Feby Ermatita, Ermatita Sofijan, Armin Doctoral Program in Engineering Science Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Faculty of Engineering Universitas Sriwijaya Palembang Indonesia

This research focused on developing and implementing a fault detection model for photovoltaic (PV) systems in remote areas, utilizing a Fuzzy-Based Multiple Linear Regression (FMLR) approach. The study aimed to address the challenges of monitoring PV systems in locations with limited access to conventional power grids and technical resources. The fault detection system integrated environmental parameters such as solar radiation, temperature, wind speed, and rainfall, alongside PV system parameters like panel voltage, current, battery voltage, and inverter performance. Data collection and preprocessing were conducted over a specified period to identify operational patterns under both normal and faulty conditions, ensuring data accuracy through cleaning, normalization, and categorization. The research was conducted in Pandan Arang Village, Kandis District, Ogan Ilir Regency, South Sumatera, Indonesia, contributing to the improvement of reliability and sustainability of renewable energy sources in isolated communities. The total number of data points for 276 rows with 6 attributes each was 1656 records. The MLR model was developed to predict the output power of the PV system, while fuzzy logic was employed to handle uncertainties in the data, offering a more flexible and adaptive decision-making process. The system applied fuzzy rules to determine the charging status (P3), categorizing it into Optimal Charging, Adjusted Charging, Charging Delay, or Fault Alert. The model was tested with real-time data, and its performance was validated through comparison with manual inspections. The results showed that the FMLR-based fault detection system effectively identified faults and optimized the performance of the PV system, making it suitable for remote areas in South Sumatera. © (2025), (science and Information Organization). All Rights Reserved.

关键词： Multiple linear regression

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An Improved Modified Jaya Optimization Algorithm: Application to the Solution of Nonlinear Equation Systems 4th

An Improved Modified Jaya Optimization Algorithm: Applicatio...

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4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Silva, Bruno Guerreiro Lopes, Luiz Doctoral Program in Informatics Engineering University of Madeira Madeira Island Funchal Portugal Regional Secretariat for Education Science and Technology Regional Government of Madeira Funchal Portugal Faculty of Exact Sciences and Engineering University of Madeira Madeira Island Funchal9020-105 Portugal

ISBN: (纸本)9783031812408

Population-based metaheuristic algorithms have been used to solve challenging optimization problems, and numerous modifications to make these algorithms more efficient have been proposed. Jaya is one of these algorithms that has been modified and utilized to solve many hard optimization problems. One such modification to the original algorithm is the Modified Jaya (MJAYA) algorithm, which, like Jaya, uses information about the best and worst candidate solutions to determine the population’s search direction, thereby limiting and focusing the search. Recent research has demonstrated that the MJAYA algorithm is not effective at solving systems of nonlinear equations transformed into equivalent nonlinear optimization problems. Systems of nonlinear equations are probably the most difficult class of numerical mathematics problems to solve, which justifies the use of metaheuristic approaches in their resolution. This paper proposes a new population-based optimization algorithm, the Improved Modified Jaya (IM-Jaya) algorithm, which, despite being a generic metaheuristic optimization algorithm, is here used to solve systems of nonlinear equations. The proposed algorithm strikes a better balance between global exploration and local exploitation, allowing for a broader and more exhaustive exploration of the search space as well as a more efficient local search in its most promising regions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optimization algorithms

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GPU Acceleration of the Enhanced Jaya Optimization Algorithm for Solving Large Systems of Nonlinear Equations 4th

GPU Acceleration of the Enhanced Jaya Optimization Algorit...

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4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

ISBN: (纸本)9783031812408

This paper presents a GPU-based parallel implementation of the Enhanced Jaya (EJAYA) algorithm for solving large-scale systems of nonlinear equations. EJAYA is a gradient-free metaheuristic optimization scheme based on the population-based parameter-less Jaya algorithm that has recently been shown to be capable of solving nonlinear equation systems, a class of challenging problems that are difficult to solve by traditional approaches, particularly as systems become larger. The proposed parallel algorithm was implemented using the Julia programming language on a high-performance GeForce RTX 3090 GPU with 10 496 CUDA cores and 24 GB GDDR6X VRAM and was tested using a set of difficult scalable nonlinear equation system problems. The obtained results, with average speedups up to 122.25x, evidenced the capability of the proposed GPU-based parallel algorithm to meet the computational demands of the important class of problems under consideration. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optimization algorithms

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The Influence of Silicon Dioxide as a Fuel Additive in a Diesel Engine Fuelled by Pure Palm Oil 4

The Influence of Silicon Dioxide as a Fuel Additive in a Die...

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4th International Symposium on Advances and Innovation in Mechanical engineering, ISAIME 2023

作者： Prahmana, Rico Aditia Darmanto, Prihadi Setyo Reksowardojo, Iman Kartolaksono Prakoso, Tirto Juangsa, Firman Bagja Doctoral Program of Mechanical Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung40132 Indonesia Program Study of Mechanical Engineering Faculty of Industrial Technology Institut Teknologi Sumatera South Lampung35365 Indonesia Thermal Science and Engineering Research Group Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Department of Chemical Engineering Faculty of Industrial Technology Institut Teknologi Bandung Bandung40132 Indonesia Program Study of Mechanical Engineering Faculty of Industrial Technology Universitas Pertamina Jakarta12220 Indonesia

In the last decade, the Indonesian government has implemented a program to use biodiesel as a substitute for fossil diesel to reduce dependence on fossil fuels. On the other hand, the development of biodiesel as an alternative fuel to replace fossil diesel has several challenges, one of which is the production of biodiesel, which is more complicated and requires a long process. However, the direct use of crude palm oil (CPO) in diesel engines is not recommended because it has many drawbacks. Research recently shows that fuel additives in diesel engines have promising prospects. Therefore, to solve the problem, this study used pure palm oil (PPaO) as the primary fuel, with the addition of silicon oxide (SiO2) as a fuel additive in diesel engines. The results showed that using SiO2 additive in PPaO can increase thermal efficiency by 18.8% at 60% load compared to diesel fuel (DF). Nevertheless, using this fuel increased specific fuel consumption (SFC) by 3.9% on average and increased the opacity by 153% compared to diesel fuel. These results indicate that SiO2 has the potential to be developed as an effective additive to PPaO fuel that can improve the efficiency and performance of diesel engines. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Biodiesel

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Conversion of Agricultural Waste into High-Rank Solid Fuel Through Sequential Wet and Dry Torrefaction Processes

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BioEnergy Research 2025年第1期18卷 1-11页

作者： Efendi, Muhammad Ade Andriansyah Hardianto, Toto Prawisudha, Pandji Juangsa, Firman Bagja Doctoral Program of Mechanical Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Thermal Science and Engineering Research Group Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia

The low calorific value and high risk of ash deposition hinder the use of agricultural biomass waste as furnace fuel. However, torrefaction can upgrade agricultural waste into high-rank solid fuel, making it a viable biomass source. This study develops a multi-process conversion method using sequential wet and dry torrefaction to obtain high-rank solid fuel with high calorific value, low slagging and fouling potential, and efficient process energy. The paper focuses on multi-process conversion, revealing its superior product characteristics compared to single-process torrefaction. The wet torrefaction process (180 °C) was followed by dry torrefaction at various temperatures ranging from 200 to 330 °C (200 °C, 250 °C, 300 °C, 330 °C). Rice straw multi-process conversion results show increasing a calorific value from 13.76 to 16.58 MJ/kg (330 °C), reduction in slagging and fouling potential from 0.21 (low potency) and 0.92 (medium potency) to 0.013 and 0.48 (both low potency). For palm oil empty fruit bunches, the calorific value increased from 17.21 to 26.89 MJ/kg (330 °C), with a reduction in slagging and fouling potential from 0.435 (low potency) and 74.84 (high potency) to 0.251 and 28.85 (low-medium potency), indicating low-medium potency. The Energy Return on Energy Invested (EROEI) for the multi-process conversion exceeds 1, utilizing residual energy from other systems. The multi-process conversion has reduced slagging and fouling potential, significantly increased calorific value, and provided a good energy return on energy investment. Therefore, sequential wet and dry torrefaction is recommended to harness the benefits of both processes.

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Evaluation of HDPE plastic waste as a coarse aggregate substitute in Hot Rolled Sheet-Wearing Course asphalt mixtures 1

Evaluation of HDPE plastic waste as a coarse aggregate subst...

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1st engineering and science International Conference 2024, ESIC 2024

作者： Desriantomy, D. Siantoni, J. Murniati, M. Department of Civil Engineering Faculty of Engineering Universitas Palangka Raya Kampus UPR Tunjung Nyaho Yos Sudarso Street Kotak Pos 2/PLKUP Palangka Raya Central Kalimantan73111 Indonesia Doctoral Program in Environmental Science Postgraduate Program Universitas Palangka Raya Kampus UPR Tunjung Nyaho Yos Sudarso Street Kotak Pos 2/PLKUP Palangka Raya Central Kalimantan73111 Indonesia

Plastic-based goods are commonly used in daily life, but their waste poses significant environmental challenges due to its durability. This study investigates the use of recycled plastic as an artificial coarse aggregate in asphalt mixtures, specifically assessing the effects of High-Density Polyethylene (HDPE) on Hot Rolled Sheet Wearing Course (HRS-WC) mixtures. The objectives are to evaluate the physical properties of the artificial coarse aggregates, identify the optimal asphalt content and Marshall characteristics, and determine the maximum feasible substitution level for these aggregates. A test specimen (briquette) was produced for the Marshall test to assess the mixture properties. Our findings indicate that the maximum allowable substitution of HDPE plastic in HRS-WC mixtures is 42%. With an optimal asphalt content of 7.30%, HDPE substitution levels of 30%, 35%, 40%, 45%, and 50% yielded the highest stability at 45% (1176.696 kg), the highest VMA at 30% (21.250%), and the highest VIM within specifications at 30% (4.998%). The highest VFB value was observed at 45% (88.767%), while the highest Marshall Quotient was at 30% (364.527 kg/mm). The study recommends a maximum HDPE plastic waste substitution level of 40%, highlighting the potential for using HDPE plastic waste in asphalt mixtures to promote more sustainable construction practices. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Aggregates

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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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Lung Cancer Diagnosis Based on Object Detection Technology 14th

Lung Cancer Diagnosis Based on Object Detection Technology

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14th International Conference on Frontier Computing, FC 2024

作者： Xu, Jia-Lang Wang, Pei-Yun Huang, Tzu-Hsuan Hsu, Ying-Lin Huang, Kuo-Yang Chen, Mu-Yen Artificial Intelligence Development Center Changhua Christian Hospital Changhua Taiwan Doctoral Program in Data Science and Industrial Analytics National Chung Hsing University Taichung Taiwan Department of Applied Mathematics and Institute of Statistics National Chung Hsing University Taichung Taiwan Division of Chest Medicine Department of Internal Medicine Changhua Christian Hospital Changhua Taiwan Department of Engineering Science National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9789819623945

With the rise of artificial intelligence, many people nowadays use artificial intelligence to help solve some problems in life, and the medical field is also with the rise of artificial intelligence, many people are slowly applying artificial intelligence to medical images to assist in decision-making, this study proposes a Yolov8 algorithm for object tracking of CT images of lung cancer, which can quickly tell the doctor where the cancer is and what the type of cancer is. The results of this study show that the Box_Loss, Cls_Loss, and Dfl_loss of the Yolov8 algorithm in detecting the location of lung cancer are 1.3689, 0.4552, and 1.5569 in the validation data, respectively, and thus this study suggests that this method can help physicians know the location of the tumor and what kind of tumor it belongs to. Therefore, this study suggests that this method can help physicians know the location of the tumor and the type of tumor. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

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