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12th International Conference on Physics and Its Applications, ICOPIA 2024

作者： Siswanto Qulub, Fitriyatul Junico, Vallery Ofelia Viannco Physics Program Study Faculty Science and Technology Universitas Airlangga Surabaya Indonesia Biomedical Engineering Program Study Faculty Science and Technology Universitas Airlangga Surabaya Indonesia

Cutaneous Lupus Erythematosus (CLE) is a form of lupus that affects the skin and is highly sensitive to ultraviolet (UV) light. UV-B. in particular. can trigger inflammation and apoptosis in CLE patients. making a sunscreen with effective UVB protection crucial. This study evaluates the effectiveness of zinc oxide (ZnO) and titanium dioxide (TiO2) nanoparticles in sunscreen. ZnO and TiO2 nanoparticles were prepared using the High Energy Milling method. resulting in particle sizes of 7.77 nm and 4.44 nm. respectively. The creams containing these nanoparticles were tested for physical stability and UV protection. Results showed that the creams were physically stable and provided good UV protection. with ZnO and TiO2 nanoparticles making up 12.60% of the total cream ingredients. resulting in the highest SPF (Sun Protection Factor) value of 62.0 ± 1.37. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： TiO2 nanoparticles

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Variable Length Multi-Objective Whale Optimization for Trust Aware Data Gathering in Wireless Sensor Network

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IEEE Access 2025年 13卷 32100-32121页

作者： Saad, Mohammed Ayad Jaafar, Rosmina Chellappan, Kalaivani Faculty of Engineering and Built Environment Department of Electrical Electronics and System Engineering Selangor Bangi43600 Malaysia Al-Kitab University Department of Medical Instrumentations Technique Engineering Kirkuk36001 Iraq Universitas Airlangga Biomedical Engineering Study Program Faculty of Science and Technology Surabaya60115 Indonesia

Efficient data collection in wireless sensor networks (WSNs) is crucial. While traditional approaches rely on stationary data sinks, the use of mobile sinks, like unmanned aerial vehicles (UAVs), has shown promise in enhancing data-gathering capabilities. However, existing methods often overlook the importance of trust, leaving the network susceptible to malicious or faulty nodes. To address this issue, we propose a novel trust-aware data-gathering algorithm, Variable Length Multi-Objective Whale Optimization Data Gathering (VLMOWO-DG). Our algorithm simultaneously optimizes energy consumption, delay, and trust while employing mobile sinks to collect data from sensor nodes. By considering trust as a key performance metric, we improve data reliability and security. The VLMOWO-DG algorithm introduces flexibility through variable-length solution representation and application-oriented operators, allowing for efficient exploration of the solution space. Simulation results demonstrate that our proposed algorithm significantly outperforms established benchmarks, NSGA-II and NSGA-III, in terms of domination and hypervolume. This leads to a remarkable improvement of 200% in data gathering performance. © 2015 The Authors.

关键词： Data collection

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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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Machine Learning-Based Prediction of Corrosion Inhibition Efficiency of Expired Pharmaceuticals: Model Development and Application

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Journal of Bio- and Tribo-Corrosion 2025年第1期11卷 1-12页

作者： Putra, Dzaki Asari Surya Ardyansyah, Nibras Bahy Putranto, Nicholaus Verdhy Trisnapradika, Gustina Alfa Akrom, Muhamad Rustad, Supriadi Dipojono, Hermawan Kresno Maezono, Ryo Faculty of Computer Science Study Program in Informatics Engineering Universitas Dian Nuswantoro Semarang50131 Indonesia Research Center for Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung40132 Indonesia School of Information Science Japan Advanced Institute of Science and Technology Ishikawa923-1292 Japan

Corrosion poses a significant challenge in industries due to material degradation and high maintenance costs, making effective inhibitors essential. Recent studies suggest expired pharmaceuticals as alternative corrosion inhibitors, but identifying the most efficient compounds can be time-consuming. This study applies machine learning models, particularly Gradient Boosting Regressor (GBR), to predict corrosion inhibition efficiency (CIE). The developed model is integrated into a web-based application, enabling real-time, accurate CIE predictions. Results show GBR as the more precise model for predicting CIE, with low error rates. The streamlit-based web application offers a user-friendly platform, facilitating quick identification of suitable inhibitors. It is flexible, supporting analysis beyond corrosion inhibitors, and significantly enhances the efficiency of the evaluation process. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Offsets Reconstruction Method for Clock Skew Measurement Over High-Jitter Communication

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SN Computer Science 2025年第5期6卷 1-14页

作者： Sastra, Nyoman Putra Saputra, Komang Oka Teng, Wei-Chung Study Program of Electrical Engineering Faculty of Engineering Udayana University Jalan Raya Kampus Bukit Jimbaran Bali Badung 80361 Indonesia Department of Computer Science and Information Engineering National Taiwan University of Science and Technology No. 43 Section 4 Keelung Rd Taipei 106 China

Measuring clock skew of devices over a network fully relies on the offsets, the differences between sending and receiving times. Offsets that shape a thick line are the most ideal one as their slope is directly the clock skew sought. When some outliers separate from the thick line due to higher delay jitter, current advanced approaches use the lower bound or the majority of offsets to derive accurate clock skew. However, outliers in offsets that shape parallel dotted lines, reduce the availability of offsets in the lower region, and scatter widely the offsets from their majority zone. These conditions drive the current skew estimation approaches to lose their accuracy. This paper then developed a new method, which reconstructs back the outliers into their origin positions, in order to provide ideal offsets for clock skew measurement. The experimental evaluations have demonstrated that the clock skew accuracy of dotted-lines offsets tampered by outliers was improved from 2.1 to 0.9 ppm by the proposed reconstruction method. For a broader purpose, the reconstruction method has been adjusted to be implemented also on non-dotted-lines offsets. The robustness of the proposed method for this case has also been exhibited by the very ideal reconstructed offsets that shape like a thick line. © The Author(s) 2025.

关键词： Clock skew Delay jitter Dotted lines Hough transform

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Analysis Geomorphic Flood Index in Determining Flood-Prone Areas in East Kalimantan Province, Indonesia

Analysis Geomorphic Flood Index in Determining Flood-Prone A...

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2024 Annual Conference, ASPRS 2024

作者： Virtriana, Riantini Amalia, Annisa Fitri Ihsan, Kalingga Titon Nur Anggraini, Tania Septi Harto, Agung Budi Deliar, Albertus Geospatial Information Science and Technology Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung40132 Indonesia Center for Remote Sensing Bandung Institute of Technology Bandung40132 Indonesia Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung40132 Indonesia Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung40132 Indonesia Universitas Pendidikan Indonesia Bandung40111 Indonesia Center for Spatial Data Infrastructure Bandung Institute of Technology Bandung40132 Indonesia

In 2022, there are 1,524 flood events out of a total of 3,531 disasters occurring in Indonesia. East Kalimantan Province ranked 20th among the 35 provinces in Indonesia with 28 flood occurrences in 2022, resulting in two fatalities. This highlights the urgent need for addressing flood hazard to prevent future casualties. There are some methods that can be used to determine the flood hazard in a region. In this research aims to identify flood-prone areas in East Kalimantan Province and evaluate the effectiveness of different mapping methods. The methodology that compares are the Pairwise Comparison method and Geomorphic Flood Index (GFI). The study's results provide flood-prone area maps of East Kalimantan Province using both methods, recommend the more efficient method for flood-prone area identification, and offer mitigation strategies based on the findings. This research is intended to serve as a reference for selecting the best method for identifying flood-prone areas and for informing policy decisions to mitigate flood impacts in East Kalimantan Province. © Author(s) 2025.

关键词： Hazards

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Interconnected Through Robotic System in English Foreign Language Education 5th

Interconnected Through Robotic System in English Foreign Lan...

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5th International Conference on Advances in Information Communication technology and Computing, AICTC 2024

作者： Muthmainnah, M. de Barros Cardoso, Luís Miguel Oliveira Kaur, Dalwinder Burhamzah, Muftihaturrahmah Aeni, Nur Al Yakin, Ahmad Sharma, Aditi Teacher Training and Education Faculty Indonesian Language Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Portugal Department of Languages and Communication Sciences Polytechnic Institute of Portalegre Portalegre Portugal Manipal Globalnxt University Kuala Lumpur Malaysia English Study Program Universitas Negeri Makassar Makassar Indonesia Teacher Training and Education Faculty Civic Education Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Department of Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International [Deemed University Pune India

ISBN: (纸本)9789819761050

Robots have become increasingly important in a variety of life domains as a result of the rapid advancement of technology. Additionally, robots are employed in education as teaching assistants in science, art, and language courses. This research aims to explore the potential of robotic systems as a multipurpose tool for increasing cultural awareness, language proficiency, and communicative competence in the GenAI era. Language games, conversation simulations, and real-time feedback mechanisms are just a few examples of interactive scenarios enabled by virtual robot systems or tutor robots that enable immersive language experiences that go beyond the limitations of conventional schooling. This research contributes knowledge that explores how AI can be used to personalize language teaching according to the needs and learning styles of each student in higher education. The total population of undergraduate students involved in this research was 350 for the 2023 academic year, with 24 students selected purposefully based on sample characteristics from this group who were exposed to using AI for one semester. The research method used is a mix method with quantitative analysis of the results of surveys and interviews with students who are known to have given positive responses and proposes a comprehensive strategy for using AI robot technology in EFL classrooms, which can significantly improve effective learning outcomes. The survey results also show that if educators have a solid understanding of the relationship between linguistic acquisition and technological advances, they will be better prepared to design engaging, individualized lessons that prepare their students to use the language effectively in real-world contexts. The robot-assisted language learning (RALL) approach used in this study, with the integration of robots in the classroom, has the potential to change the way people learn languages to make it more interesting, fun, and motivating, increase engagement

关键词： Students

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Challenging body shaming with grading techniques in the fashion industry

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Social Sciences and Humanities Open 2025年 11卷

作者： Supadmi Irianti, Agus Hery Marniati Wiana, Winwin Nafiah, Annisau Department of Culinary and Fashion Education Faculty of Engineering Universitas Negeri Malang Malang Indonesia Fashion Technology Education Study Program Faculty of Engineering State University of Surabaya Surabaya Indonesia Fashion Education Study Program Faculty of Engineering and Industry Education Universitas Pendidikan Indonesia Bandung Indonesia

Body shaming remains a prevalent concern in the fashion business, as conventional beauty standards sometimes exclude persons with varied body shapes. This study investigates the effect of pattern grading and motif grading approaches on reducing body shaming, particularly in the context of batik shirt production. The research highlights how various grading systems improve garment fit and cater to a broader range of body shapes, thereby challenging body shaming and promoting body inclusivity. The research examines the impact of grading methods on tailors' engagement, skill level, and self-assurance, showing that these methods enhance garment quality and empower industry professionals. This study employed a mixed-method approach, combining the creation of graded batik shirt prototypes with quantitative analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM). The research indicates that motif grading maintains the traditional validity of batik designs while facilitating size modifications. Tailors expressed strong interest in adopting grading techniques, and the study proposes inclusive design solutions that effectively address body shaming in a traditional manner. The results suggest that integrating grading methodologies into fashion processes can foster a more inclusive and diverse business. Suggestions are offered for fashion designers, educational institutions, and companies to promote the implementation of grading techniques that accommodate body variation. This research identifies future research opportunities, such as incorporating technology in grading and formulating design methods to mitigate body shaming in the fashion industry. © 2025 The Authors

关键词： Batik shirts Body inclusivity Body shaming Motif grading Pattern grading

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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Optimization of biomass-fueled vertical corn drying: Efficiency, energy balance, and sustainability

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Results in engineering 2025年 26卷

作者： Sukmawaty, Sukmawaty Syahrul, Syahrul Amuddin, Amuddin Rahmi, Sri Helmayana Syahrul, Ahmad Ibrahim Agricultural Engineering Study Program Faculty of Food Technology and Agroindustry University of Mataram Mataram83125 Indonesia Mechanical Engineering Department Engineering Faculty University of Mataram Mataram83125 Indonesia

This study investigates the thermal performance and energy efficiency of a biomass-fueled vertical dryer utilizing candlenut shell biomass for corn drying. The objective is to evaluate drying behavior under continuous and discontinuous operation modes at different temperature settings. A custom-built dryer was developed and tested at 45 °C, 50 °C, and 55 °C, and energy input, drying time, and efficiency were recorded. Statistical analyses, including paired t-tests, were conducted to examine the significance of operational differences. Results show that continuous drying at 50 °C and 55 °C significantly improves drying efficiency, reaching above 66 %, and reduces drying time compared to discontinuous modes. Candlenut shells performed well as a renewable fuel, offering stable combustion and minimal ash production, outperforming traditional fuels such as rice husks and corn cobs in similar drying conditions. Energy analyses indicated balanced energy use, while future work should address post-drying quality characteristics and automation. These findings suggest that candlenut shells are a viable, sustainable alternative for efficient post-harvest thermal processing, particularly in rural agro-industrial settings. © 2025 The Authors

关键词： Energy utilization

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