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2023 International Conference on Smart-Green Technology in Electrical and Information Systems, ICSGTEIS 2023

作者： Sulaksono, Juli Dwi Girinatari, Ida Ayu Sudarma, Made Alit Swarmardika, Ida Bagus Udayana University Engineering Science Doctoral Program Indonesia

ISBN: (纸本)9798350382822

Deaf people are people who are unable to communicate with spoken language. Deaf people communicate with the Indonesian Sign System or commonly known as SIBI. In fact, deaf people often communicate and socialize with normal people, but not all normal people understand and understand SIBI. We as researchers want to provide a way out so that deaf people can convey information to normal people, who do not understand SIBI. The input of this research is SIBI movement which is saved in Video format, then the video is processed with the LSTM algorithm. Video The results of the processing are in the form of classified words, the output of this research is in the form of text. The word data set in this study consisted of 3 words, each word contained 30 data sets. The level of accuracy of this study when recognizing words in SIBI that do not hit the face is 100%. © 2023 IEEE.

关键词： Long short-term memory

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Classification of Multivariate Time Series Signals Using Self-Supervised Representation Learning for Condition Monitoring 30

Classification of Multivariate Time Series Signals Using Sel...

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30th International Symposium on Semiconductor Manufacturing, ISSM 2024

作者： Sumiya, Koichi Arima, Sumika University of Tsukuba Doctoral Program in Policy and Planning Sciences Tsukuba Japan University of Tsukuba Institute of Systems and Information Engineering Tsukuba Japan

ISBN: (纸本)9798331510589

In the analysis of real-world data, two significant challenges often arise: high-dimensional signals and their temporal interactions. To address these issues and identify transitions in process conditions through end-to-end learning, we propose a self-supervised representation learning framework that conceptualizes signals as images. This straightforward approach classifies imaged signals as time-specific conditions by maximizing mutual information within a domain-specific feature space. We applied this methodology to two labeled open datasets and one unlabeled real-world process dataset, yielding promising results. © 2024 IEEE.

关键词： Self-supervised learning

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Development of A Deep Learning Hybrid Model for Classification of Plastic Waste Objects in the Coastal Environment

Development of A Deep Learning Hybrid Model for Classificati...

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

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

ISBN: (纸本)9798331513320

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. © 2025 IEEE.

关键词： Convolutional neural networks

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Shape Effects on Shear Behavior of Superdisk Systems Studied by Level Set Discrete Element Method 6th

Shape Effects on Shear Behavior of Superdisk Systems Studied...

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6th International Conference on Advances in Civil engineering, ICACE 2022

作者： Jiang, Haoran Kawamoto, Reid Matsushima, Takashi Doctoral Program in Engineering Mechanics and Energy University of Tsukuba Tsukuba Japan Independent Scholar Tsukuba Japan Department of Engineering Mechanics and Energy University of Tsukuba Tsukuba Japan

ISBN: (纸本)9789819938254

This paper investigates the shear behavior of superdisk particles using the 2D level set discrete element method (LS-DEM). Specifically, dense samples of various superdisk shapes (blockiness in [2, 4]) were prepared through isotropic compression tests, and the prepared samples were then subjected to simple shear tests under different shearing speeds. We find the following. Firstly, it is observed that the final compression state is strongly influenced by the particle shapes. Larger surface blockiness leads to more ordered packing structures, resulting in higher solid fractions and mean coordination numbers in larger values of n. Secondly, the quasi-static shear response shows significant differences for different values of n. The stress ratios q/p and solid fractions in the peak and critical state increase monotonically with all blockiness values explored. Finally, the study tests the constitutive rheological model of steady flows, and the findings indicate that (Forumala presented). relations can be well captured by power-law functions for all samples. Furthermore, the fitted exponents are found to be nearly independent of the shape of the samples. The results of this study provide deeper insights into the particle shape effects on granular materials. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Numerical methods

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Establishing Utilization Decision Criteria for Open-Source Software Projects Based on Issue Resolution Time Evaluation 18

Establishing Utilization Decision Criteria for Open-Source S...

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18th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025

作者： Inoue, Keisuke Tsuda, Kazuhiko University of Tsukuba Doctoral Program in Risk and Resilience Engineering Tsukuba Japan University of Tsukuba Faculty of Business Sciences Tsukuba Japan

ISBN: (纸本)9798331534677

In the face of growing demand for high-quality software solutions at reduced costs and development times, the use of open-source software (OSS) has become increasingly prevalent. This study evaluates the speed of OSS support activities - an essential quality factor for OSS users - and proposes a method for early-stage evaluation based on issue resolution time. We analyzed 100 popular OSS projects hosted on GitHub, collecting data on issue creation and completion dates. The results indicate a correlation coefficient of 0.587 between 30 and 180 days of observation, aligning with previous findings on OSS support continuity. Notably, a satisfactory correlation of 0.525 was achieved at just 21 days, suggesting that organizations can assess OSS support speed earlier and potentially accelerate their decision-making process. Our findings provide a practical criterion for evaluating the speed of OSS support activities, which may help organizations adopt OSS with greater confidence and enhance productivity in software-related projects. Future research will expand these criteria by exploring additional factors affecting issue resolution time, such as project scale and corporate support. © 2025 IEEE.

关键词： Open source software

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Review of Hollow Cathode Discharge: Exploring Advanced Design and Optimization

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Journal of Aeronautics, Astronautics and Aviation 2023年第3期55卷 385-414页

作者： Hsieh, Jordan H. Li, Yueh-Heng Department of Aeronautics and Astronautics National Cheng Kung University Tainan70101 Taiwan International Doctoral Degree Program on Energy Engineering National Cheng Kung University Tainan70101 Taiwan

Electric propulsion has seen significant development over the years, resulting in its popularity due to its expanded capabilities in satellite constellation management and orbital transfer vehicles. Hollow cathodes have become an extensively utilized source of electrons for propellant ionization and ion beam neutralization in electric propulsion systems. This paper reviews the hollow cathode discharge and the recent advancements and progress in hollow cathode technology to highlight the key areas that require further research. The classic hollow cathode design, which features an external heater and has been widely used in flight programs, is discussed, followed by a focus on heaterless hollow cathodes, which have recently gained publicity. The critical aspects of low-current and high-current hollow cathode operation, including the emitter material and self-heating mechanisms, are highlighted in this review, each facing unique challenges. Future challenges for hollow cathodes involve creating chemically stable, long-lasting materials with low work function, optimizing the design to reduce ion yield and erosion, and ongoing modeling of cathode operation and plasma instabilities. © 2023 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.

关键词： Cathodes

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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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Gastritis Diagnosis Expert System Using Android-Based Certainty Factor Method 6

Gastritis Diagnosis Expert System Using Android-Based Certai...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Isnanto, R. Rizal Purwanto Windarto, Yudi Eko Setiawan, Annas Diponegoro University Information Systems Doctoral Program Semarang Indonesia Diponegoro University Computer Engineering Department Semarang Indonesia

ISBN: (纸本)9798350358346

In the modern era, an increasing number of diseases are emerging because of human lifestyle choices and bacterial transmission. Gastritis, characterized by inflammation in the stomach lining leading to frequent abdominal pain, is one such ailment. Recognizing the significance of addressing these health issues, there is a need for an expert system application specifically designed for diagnosing gastritis. The primary objective is to disseminate information to the public regarding the early symptoms of gastritis, promoting awareness from a young age. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The diagnostic process employs the Certainty Factor (CF) method to ensure accurate results. By utilizing symptom CF values chosen by the user, the Certainty Factor approach facilitates a diagnosis based on calculations established by medical specialists. The research culminates in the development of an expert system application capable of accurately diagnosing the disease Android based. The accuracy rates for the first, second, and third test cases are reported as 98.848%, 99.8464%, and 99.99115264%, respectively. System testing, conducted through black-box testing, validates the application's functionality, demonstrating a 100% success rate for each component. © 2023 IEEE.

关键词： Expert systems

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Identification of spatial potential flood-prone area using topographic wetness index under the digital elevation model of Kr. Keureuto watershed, North Aceh. 5

Identification of spatial potential flood-prone area using t...

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5th Aceh International Symposium on Civil engineering 2024, AISCE 2024

作者： Rizalihadi, Maimun Meilianda, Ella Yulianur, Alfiansyah Away, Yuwaldi Doctoral Program Post Graduate Program Syiah Kuala University Banda Aceh Indonesia Civil Engineering Department Syiah Kuala University Banda Aceh Indonesia Electro and Computer Engineering Department Syiah Kuala University Banda Aceh Indonesia

Floods are the most frequent disaster events in Lhoksukon, resulting in significant losses and community and environmental damage. Floods are generated by several factors, consisting of hydrometeorological, topographical, geological, soil, and human activities. Topography is a key controlling factor in flood initiation. Topographic analysis for detecting flood susceptibility, especially flood inundation, can be conducted using the TWI. The research aims to identify the potential spatial distribution of flood-prone areas based on TWI and assess the model accuracy using the ROC-AUC method. A case study was conducted in the Kr. Keureuto watershed. of North Aceh. TWI analysis is based on the topography of an area denoted by extracting DEM using GIS to create slope, flow direction, and flow accumulation. Higher TWI values are associated with higher flood susceptibility. The results show that the value of TWI is approximately 1.571-27.147, showing that more than 20% of area are potentially flood inundations with high and very hight rating of flood susceptibility. Furthermore, based on the analysis using field observation flood is obtained the AUC value of 71,60%. It can be concluded that the spatial model of flood-prone using TWI is good and effective for determining flood prone region in the Kr. Keureuto River basin © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Watersheds

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Expert System for Diagnosis of Diphtheria Disease Using Fuzzy Logic 6

Expert System for Diagnosis of Diphtheria Disease Using Fuzz...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Isnanto, R.Rizal Mustafid Prasetijo, Agung Budi Fitria Ali, Safira Isna Diponegoro University Information Systems Doctoral Program Semarang Indonesia Diponegoro University Computer Engineering Department Semarang Indonesia

ISBN: (纸本)9798350358346

Diphtheria is an infectious disease that affects the upper respiratory system and throat, arising suddenly and caused by Corynebacterium diphtheriae. The symptoms of diphtheria such as fever, swollen neck and slimy nose are often interpreted as influenza or laryngitis. Diphtheria is a contagious and deadly disease that requires specialized and rapid treatment and care. In today's technological era, it can be overcome with a system that can diagnose diphtheria like a doctor's diagnosis ability commonly called an expert system. This study describes the application of an expert system to diagnose diphtheria disease. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The method used to process input values is Forward Chaining. Fuzzy Tsukamoto to calculate the input value from the user. The research has been tested with Blackbox testing showing the results that the expert system works well and accuracy testing with 92% results. The results show effectiveness with a satisfactory level of accuracy in detecting diphtheria disease. This research contributes to the development of expert systems in the health sector with a focus on diagnosing diphtheria disease using a fuzzy logic approach. © 2023 IEEE.

关键词： Diagnosis

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