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

作者： Imran Djafar Indrabayu Syafruddin Syarif Doctoral Program of Electrical Engineering Department Hasanuddin University Dipa Makassar University Makassar Indonesia Department of Informatics Hasanuddin University Makassar Indonesia Department of Electrical Engineering Hasanuddin University Makassar Indonesia

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

Plastic, glass, metal, and wood waste has become a global scourge and nightmare to the marine environment and the development of the coastal areas. This paper aims at developing a hybrid model of deep learning technique using Convolutional Neural Networks (CNN) and Vision transformers (ViT) in the performance of detecting underwater waste materials. The model is designed with the use of transfer learning and high-resolution imaging sourced from underwater drones to help overcome the challenges of underwater work such as poor visibility and insufficient ambient light. The local features are extracted using CNNs and the global spatial relationships of the images are attended to by the ViTs. The results achieved a waste detection accuracy rate of about 90%, which is effective even in difficult environmental conditions. The concept is for a waste management system where drones or underwater robotics systems can assist automated waste management, waste treatment processes, and aid marine renovation activities.

关键词： Waste management Deep learning Transfer learning Sea measurements Metals Glass Feature extraction Transformers Convolutional neural networks Drones

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Key factors affecting people's willingness to participate in water resource protection in the agricultural Ba River Basin – in the highlands of Vietnam

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Journal of Water and Climate Change 2025年第4期16卷 1225-1237页

作者： Anh, Nguyen Tuan Can, Le Duy Schmalz, Britta Luu, Tran Le Doctoral Training Program in Sustainable Urban Development Vietnamese-German University Vanh Dai 4 Quarter 4Binh Duong Province Ben Cat Viet Nam Nong Lam University of Ho Chi Minh City Gia Lai Campus Gia Lai Viet Nam Department of Mechatronics and Sensor Systems Technology Vietnamese-German University Vanh Dai 4 Quarter 4 Thoi Hoa Ward Binh Duong Province Ben Cat Viet Nam Engineering Hydrology and Water Management Technical University of Darmstadt Darmstadt Germany Master Program in Water Technology Reuse and Management Vietnamese-German University Vanh Dai 4 Quarter 4 Thoi Hoa Ward Binh Duong Province Ben Cat Viet Nam

Willingness to participate (WP) in community-based management depends on various factors such as a sense of community, perceptions, beliefs, and demographic characteristics. This study first evaluates the WP of locals (n = 100) in water management in the Ba River Basin – Highlands of Vietnam, where ethnic minority groups are living and working in the agricultural sector. The multivariable linear regression model is applied to explain WP through the factors including the sense of community (SC), dependance on river water (DW), perceptions of current water resource management (PW), level of income (IN), gender (GE), education levels (ED), and place of residence (PR). The results showed that the final regression model explains 67.9% of the variation in WP levels (R2 = 0.679, p 0.05) in this model. Sense of community and perceptions greatly influence community participation. To boost willingness, periodic training and campaigns are needed. Additionally, improving legal frameworks can encourage greater community involvement in water management programs. © 2025 The Authors.

关键词： Multiple linear regression

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Development of a hanging pendulum thrust stand for pulsed plasma thrusters

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Acta Astronautica 2025年 234卷 368-386页

作者： Yueh-Heng Li Wai-Cheng Lien Sheng-Wen Liu Institute of Space Systems Engineering National Cheng Kung University Tainan 70101 Taiwan Department of Aeronautics and Astronautics National Cheng Kung University Tainan 70101 Taiwan International Doctoral Degree Program on Energy Engineering National Cheng Kung University Tainan 70101 Taiwan

Thrust stands are essential tools for evaluating the performance of propulsion systems, including Hall effect thrusters, ion thrusters, and pulsed plasma thrusters (PPTs). Our thrust stand supports a prototype weighing up to 0.8 kg and measures impulses from 150 to 550 μN s. It generates voltage oscillations with peaks between 5 mV and 35 mV, which, combined with NI voltage modules, minimizes weight constraints on the propulsion system while maintaining accurate measurements under low thrust-to-weight conditions. This design introduces a novel approach compared to conventional torsional thrust stands. By aligning the propulsion system's center of mass with the pendulum arm, we eliminate the need for spring torque. Instead, gravitational torque provides the necessary equivalent spring constant for damping. The eddy-current damper, featuring a copper plate, doubles as both a damping mechanism and a counterweight, allowing adjustments for different propulsion system weights. Unlike elastic pivots, this design avoids performance degradation from material fatigue or thermal effects. Challenges in the current system include non-linear spring and damping coefficients caused by PPT power cables and pulse-width errors during calibration. Future improvements will consist of cable feed-throughs to isolate vibrations without introducing unwanted coefficients. Additionally, the improvement aims to optimize the impulse generator's power supply to eliminate calibration errors caused by high-voltage pulse-width fluctuations.

关键词： Thrust stand Electric propulsion Pulsed plasma thruster Impulse measurement methods

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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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A Neuroelectronic Interface with Microstructured Substrates for Spiral Ganglion Neurons Cultured In Vitro: Proof of Concept

Biosensors

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Biosensors 2025年第4期15卷 224-224页

作者： Delipetar, Boris Žarković Krolo, Jelena Bedalov, Ana Kovačić, Damir Department of Physics Faculty of Science University of Split Ruđera Boškovića 33 Split21000 Croatia University of Split Ruđera Boškovića 31 Split21000 Croatia The Doctoral Program in Mechanical Engineering Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture University of Split Ruđera Boškovića 32 Split21000 Croatia The Doctoral Program in Biophysics Faculty of Science University of Split Ruđera Boškovića 33 Split21000 Croatia Bedalov d.o.o for Research Development and Consulting Ulica T. Antunovića 17 Kaštel Sućurac21212 Croatia

In this study, we present a proof-of-concept neuroelectronic interface (NEI) for extracellular stimulation and recording of neurophysiological activity in spiral ganglion neurons (SGNs) cultured in vitro on three-dimensional, micro-patterned substrates with customized microtopographies, integrated within a 196-channel microelectrode array (MEA). This approach enables mechanotaxis-driven neuronal contact guidance, promoting SGN growth and development, which is highly sensitive to artificial in vitro environments. The microtopography geometry was optimized based on our previous studies to enhance SGN alignment and neuron-electrode interactions. The NEI was validated using SGNs dissociated from rat pups in the prehearing period and cultured for seven days in vitro (DIV). We observed viable and proliferative cellular cultures with robust neurophysiological responses in the form of local field potentials (LFPs) resembling action potentials (APs), elicited both spontaneously and through electrical stimulation. These findings provide deeper insights into SGN behavior and neuron-microenvironment interactions, laying the groundwork for further advancements in neuroelectronic systems. © 2025 by the authors.

关键词： Neurons

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Prediction Model for Track Quality Index Categories on the Northern and Southern Railway Lines of Java

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Periodica Polytechnica Transportation engineering 2025年第2期53卷 184-193页

作者： Yudariansyah, Hadi Ismiyati, Ismiyati Narendera, Alfa Doctoral Program of Civil Engineering Faculty of Engineering University of Diponegoro 5–7 Hayam Wuruk street Semarang50241 Indonesia Department of Civil Engineering Faculty of Engineering University of Diponegoro Prof. Sudarto Tembalang Street Semarang50275 Indonesia Department of Civil Engineering Faculty of Engineering Semarang State University E3–4 Kampus Sekaran Gunung Pati Street Semarang50229 Indonesia

Track quality index (TQI) is a quality metric that objectively measures the geometric condition of railway tracks for maintenance planning. The TQI categories serve as the basis for proposed track maintenance. The TQI measured by the EM120 track recording car on Java island currently covers only 78.84% of the 5,634.363 km of railway tracks, indicating that there are still track sections without TQI category values. This study aims to model the maintenance of railway infrastructure based on TQI categories derived from both track recording car results and manual measurements across various sections of railway lines on the northern and southern routes of Java island. The analysis used is based on the standard deviation of railway track geometry, including superelevation, levelling, lining, and track gauge. Factors such as turnouts, bridges, crossings, straight sections, and curves were then classified as predictive factors. Machine learning techniques were adopted, with 80% of the data set randomly used for training and the remaining for testing to generate TQI category predictions. A total of 233,175 TQI data points from 2019–2022 were used to build and validate the model. The results indicate that the multinomial regression model for TQI Categories 1, 2, 3, and 4 is highly accurate, the rest is influenced by other factors. These results imply that the model has an exceptional fit and excellent predictive capability for TQI on the northern and southern railway lines of Java island. © 2025 Budapest University of Technology and Economics. All rights reserved.

关键词： Prediction models

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Variations in casting temperatures effect of re-melted 6061 aluminum alloy on tensile strength

Results in Materials

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Results in Materials 2025年 26卷

作者： Zulfadhli Akhyar, Akhyar Ali, Nurdin Arhami Pahlevi, Muhammad Reza Doctoral Program-School of Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Mechanical Engineering Universitas Syiah Kuala Jln. Syech Abdurrauf No.7 Darussalam Banda Aceh 23111 Indonesia

The variation in casting temperature influences the solidification rate of aluminum alloys, which in turn affects the tensile properties of the metal. This experiment aims to investigate the effect of four different casting temperatures on the tensile strength of remelted 6061 aluminum alloy. Cast samples were prepared using a square steel mold, and tensile test specimens were machined according to standard tensile tests. The mold was preheated to 220 °C to prevent thermal shock due to temperature differences between the melt and the mold. The casting temperature variations used for the melt were 700, 750, 800, and 850 °C. Ultimate tensile strength (UTS) shows slight fluctuations with changes in casting temperature, decreasing to approximately 160 MPa at 800 °C before recovering at 850 °C, but these variations are not statistically significant. Yield strength remains relatively stable across the temperature range, with minor fluctuations suggesting minimal effect from casting temperature. Young's modulus increases significantly at 750 °C but decreases slightly at 800 °C, indicating moderate sensitivity to casting conditions while maintaining relatively consistent values overall. The relationship between casting temperature and cooling rate is non-linear, with the cooling rate decreasing to a minimum at 800 °C before rising again. The casting temperature has minimal impact on the tensile strength, yield strength, and Young's modulus of remelted Al 6061 alloy, as indicated by the slight fluctuations in these properties across the tested temperature range. © 2025 The Authors

关键词： Casting temperature Re-melt of 6061 alloy Tensile Yield stress

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Technology-Enhanced Learning for User Security Awareness Using AI-based Naive RAG: A Design and Prototype

Technology-Enhanced Learning for User Security Awareness Usi...

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

作者： I Putu Agus Eka Pratama I Made Oka Widyantara Linawati Nyoman Gunantara Sinung Suakanto Eka Tresna Irawan Doctoral Program of Engineering Sciences Faculty of Engineering Udayana University Badung Bali Indonesia dept. of Electrical Engineering Faculty of Engineering Udayana University Badung Bali Indonesia dept. of Information System Telkom University Bandung West Java Indonesia Mayar International Pte. Ltd. Singapore

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

The increasing use of Information Technology (IT) in all areas of life, followed by increasing cybersecurity threats on the user side, makes cybersecurity awareness among users an obligation that must be met. Several solutions currently available (guides, discussion forums, workshops) have not been able to provide good results and are lacking in terms of user engagement, adaptability, and optimizing available resources, so technology-based learning is needed, especially AI. This paper introduces the design and prototype of an AI-based learning system, especially with the Naive Retrieval-Augmented Generation (Naive RAG) method with three steps, including Retrieval, Augmented, and Generation. The system combines contextual user questions and answers with internal and domain knowledge systems to explain cybersecurity awareness to users dynamically and personally. The prototype that has been developed is then tested using the Black Box Testing method to evaluate functionality and usability. The test results show that the functionality of the system built has run well with a percentage of success of 100%, so it can be used as a technologybased learning medium for education and learning of user security awareness.

关键词： Electronic learning Retrieval augmented generation Knowledge based systems Prototypes Learning (artificial intelligence) Computer security Usability Information technology Testing Information systems

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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

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.

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

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Cigarette butt filter as membrane material with tannic acid and FeCl₃ additives for improve antifouling properties

Case Studies in Chemical and Environmental Engineering

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Case Studies in Chemical and Environmental engineering 2025年 11卷

作者： Luthfiana, Anisa Mulyati, Sri Arahman, Nasrul Bilad, Muhammad Roil Aulia, Muhammad Prayogie Doctoral Program School of Engineering Science Universitas Syiah Kuala Banda Aceh Indonesia Department of Chemical Engineering Universitas Syiah Kuala Banda Aceh Indonesia Department of Chemical and Process Engineering Faculty of Integrated Technologies Universiti Brunei Darussalam Bandar Seri Begawan Brunei Darussalam Department of Chemical Science and Engineering Kobe University Kobe Japan

Membrane fouling remains a critical challenge in wastewater treatment, particularly in applications involving oil-water emulsions. This study addresses this issue by fabricating antifouling membranes from repurposed cigarette filter waste, modified with tannic acid and FeCl₃ (ferric chloride) coatings. These modifications enhance membrane hydrophilicity, antifouling properties, flux recovery, and selectivity through an environmentally friendly approach. The membranes were prepared using the non-solvent induced phase separation (NIPS) method and subsequently coated through vacuum filtration. Key performance metrics included pure water flux, oil emulsion selectivity, and antifouling properties. The antifouling mechanism was attributed to the hydrophilic and protective layers formed by the tannic acid and FeCl₃ modifications, which reduced fouling and improved flux recovery. Characterization revealed that the tannic acid and FeCl₃ modifications created a hydrophilic layer with uniform pore distribution, leading to an oil rejection rate of up to 97 % and an increased flux recovery ratio of 85 %, compared to 65 % in unmodified membranes. The results highlight the potential of waste-derived membranes as a sustainable alternative for industrial wastewater treatment, aligning with the principles of circular economy and green chemistry. Future work should explore long-term stability, surface charge effects, and optimization of additive concentrations to enhance performance and antifouling efficiency further. © 2025 The Authors

关键词： Antifouling membrane Cigarette filter waste FeCl3 Oil-water emulsion tannic acid

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