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SSRN 2024年

作者： Halim, Winda Puspasari, Maya Arlini Prasetyo, Ridwan Aji Budi Ardiansyah, Yusuf Huda, Listiani Nurul Lahay, Idham Halid Lady, Lovely Didin, Fatin Saffanah Mahachandra, Manik Iridiastadi, Hardianto Department of Industrial Engineering and Management Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Industrial Engineering Program Study Faculty of Engineering Universitas Kristen Maranatha Bandung Indonesia Department of Industrial Engineering Faculty of Engineering Universitas Indonesia Indonesia Departemet of Psychology Faculty of Social and Political Sciences Brawijaya University Indonesia Department of Industrial Engineering Faculty of Engineering Universitas Sumatera Utara Indonesia Department of Industrial Engineering Faculty of Engineering Universitas Negeri Gorontalo Indonesia Industrial Engineering Departement University of Sultan Ageng Tirtayasa Indonesia Departement of Industrial Engineering Faculty of Industrial Technology Institut Teknologi Sumatera South Lampung Indonesia Industrial Engineering Department Engineering Faculty Diponegoro University Central Java Semarang Indonesia

In Indonesia, motorcycle is the most popular form of transportation because of their convenience and economical. Motorcycles dominate more than 85% of vehicles on the road. Ironically, the number of motorcycle-related accidents rise and now account for about 73% of all traffic accidents. Aim of this research is to understand motorcyclist behavior, other road user, and related traffic conditions. The Naturalistic Driving study (NDS) method is used to gather data. A camera was mounted to participant’s motorcycle to capture their driving behaviors and traffic condition. The participants of this study were drawn from 6 cities across 3 major islands in Indonesia. There were 79 participants with a total journey distance approximately 1036 km and a journey duration nearly 40 hours. The video recordings were then observed by observers in each city to determine the safety critical events (SCE). There was no significant difference in the number of SCEs that occur in each city, but there was a significant difference when it comes to the causes of SCEs. This research found that the largest number of violations (30-80%) occur due to factors related to other road user, such as near crash with other road users when overtaking vehicles in front of them, other road users from the opposite direction driving in the wrong lane/side or lane used by the driver, or near crash with other road users who suddenly change lanes in front of them. In this research, it was also found that the number of SCEs that occurred was not affected by the distance and driving duration. This study supports previous research that the main cause of violations is human error. However, the occurrence of SCE is not only caused by the driver himself but through this research it is found that other road users are a critical factor. © 2024, The Authors. All rights reserved.

关键词： Motorcycles

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Verification of the Inactivation Effect of Near-UV LEDs using a Pulsed Lighting System on Staphylococcus aureus

Verification of the Inactivation Effect of Near-UV LEDs usin...

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Sustainable Smart Lighting World Conference & Expo (LS18), IEEE

作者： Hiroki Nomura Seiji Kihara Akinori Zukeran Jun Sawai Takayuki Misu Graduate School of Engineering Master's Degree Program in Electrical and Electronic Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan Department of Electrical and Electronic Engineering Faculty of Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan Department of Nutrition and Life Science Faculty of Health and Medical Sciences Kanagawa Institute of Technology Atsugi Kanagawa Japan

ISBN: (数字)9798331540197

ISBN: (纸本)9798331540203

The purpose of this study is to investigate the disinfection effect of Near-UV LED light, which is pulsed using PWM control, on Staphylococcus aureus. To evaluate the disinfection effect of Near-UV LED light, three types of Near-UV LEDs with wavelengths of 395 nm, 385 nm, and 365 nm were installed within a sealed space inside an incubator and energized with a forward current of 1000 mA and a forward voltage of 3.6 V, and the disinfection rate under each type of light was assessed. Additionally, the disinfection effect was evaluated when the same three types of Near-UV LEDs were pulsed with a 50% duty cycle. As a result, 100% disinfection was achieved with 365 nm Near-UV LED direct-current irradiation for 120 seconds, and a 93% disinfection rate was obtained with pulsed irradiation for 150 seconds.

关键词： Radiation effects Power demand Lighting Pulse width modulation Aerospace electronics Light emitting diodes

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Effect of Wire Size and Slot Filling Factor on the Number of Turns Per Pole in Design of SRM

Effect of Wire Size and Slot Filling Factor on the Number of...

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Global Energy Conference (GEC)

作者： Bekir Geçer Öztürk Tosun N. Füsun Oyman Serteller Alper Nabi Akpolat Gülten Kaşoğlu Mechatronics Program Atasehir Adiguzel Vocational School Istanbul Turkey Electrical-Electronic Engineering Marmara University Istanbul Turkey Electrical-Electronics Engineering Faculty of Technology Marmara University Istanbul Turkey Appied Mathematics Faculty of Sciences Marmara University Istanbul Turkey

ISBN: (数字)9798331532611

ISBN: (纸本)9798331532628

As electric vehicles become increasingly important and widely used, the design of every type of electric motor has gained significant attention in both literature and industry. This study provides a detailed analysis of the number of turns in the motor windings, a critical factor in electric motor design. Through comparative analysis, it investigates how wire size and slot filling factor affect the number of windings turns per pole in Switched Reluctance Motors (SRMs). In addition, the study evaluates the effect of the number of turns analysis on motor performance during design optimization using the genetic algorithm tool in Ansys and traditional calculation methods. The optimization was performed with the wire size range between 0.45 and 0.85 mm. As a result, the optimal value with 82% efficiency was obtained with a wire size of 0.81 mm and 312 turns. The lower copper losses, ideal volume, reduced costs, and enhanced efficiency are obtained by determining the optimal number of turns. This research contributes to developing more efficient and cost-effective electric motor designs. Future research could explore various and more effective optimization techniques and current parameters to design SRM and other motors.

关键词： Power system measurements Fill factor (solar cell) Density measurement Windings Switched reluctance motors Electric vehicles Filling Wire Optimization Electric motors

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Machine Learning-based Modulation Format Identification and Optical Performance Monitoring Techniques Implementation

Machine Learning-based Modulation Format Identification and ...

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2021 Advanced Communication Technologies and Signal Processing, ACTS 2021

作者： Devi, Pukhrambam Puspa Vincent Simatupang, Joni Welman National Institute of Technology Silchar Department of Electronics and Communication Engineering Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung40132 Indonesia President University Study Program of Electrical Engineering Bekasi17530 Indonesia

ISBN: (纸本)9781665423373

In this paper, machine learning-based techniques are used to solve and analyze the modulation format recognition problem. The combination of intelligent software and high-performance hardware provides a large scope for innovation in optical networking. Machine learning algorithms can use a large amount of data available from the network monitors to learn and make the network more robust. This is a problem in optical communication that consists of defining the type of digital modulation process in which an electrical signal should be sent. A dataset to represent realistic transmission behaviors was generated using a simulator based on a Gaussian noise model. A multi-layer perceptron was used and tested with different architectures to show that a high level of accuracy is achievable with machine learning. An analysis of the input features was made by using the select K best features method. Finally, an attempt to visualize the data in 2-dimension was made using the Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE) methods to reduce the dimensionality of the input features and see their relationships. © 2021 IEEE.

关键词： Principal component analysis

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Sentiment Analysis of Cooking Oil using Bidirectional Encoder Representations from Transformers 5

Sentiment Analysis of Cooking Oil using Bidirectional Encode...

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5th International Conference on Information and Communications Technology, ICOIACT 2022

作者： Widianto, Mochammad Haldi Heryadi, Yaya Lukas Suparta, Wayan Wibowo, Antoni Bina Nusantara University Computer Science Department Binus Graduate Program - Doctor of Computer Science Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Departement of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (数字)9781665451406

ISBN: (纸本)9781665451406

Recently, cooking oil has been widely discussed on social media. Many people ask how to analyze this phenomenon, one of which is using a sentiment analysis application on Twitter that performs a scientific analysis of the tweets of this media user. This study aims to test the performance of the sentiment analysis algorithm utilizing the Bidirectional Encoder Representations from Transformers (BERT) algorithm from Twitter, which is used to classify the types of tweets processed in 2000 tweets. The study shows the results of the confusion matrix, accuracy, and precision. The study obtained a fairly good accuracy and precision performance of 84%, which occurred at a learning rate of 1e-6 and epoch 5. The author also discusses the factors that affect the performance of BERT, such as;pre-processing, data quantity, and data variation. © 2022 IEEE.

关键词： Sentiment analysis

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A DfT Technique for electrical Interconnect Testing of Circuit Boards with 3D Stacked SRAM ICs 12

A DfT Technique for Electrical Interconnect Testing of Circu...

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12th IEEE CPMT Symposium Japan, ICSJ 2023

作者： Ikiri, Yuki Yotsuyanagi, Hiroyuki Ali, Fara Ashikin Binti Lu, Shyue-Kung Hashizume, Masaki Graduate School of Advanced Technology and Science Tokushima University Tokushima Japan Graduate School of Technology Industrial and Social Sciences Tokushima University Tokushima Japan Universiti Teknikal Malaysia Melaka Faculty of Electrical and Electronic Engineering Technology Melaka Malaysia National Taiwan Univ. of Science and Technology Department of Electrical Engineering Taiwan Taipei Taiwan The Open University of Japan Tokushima Study Center Tokushima Japan

ISBN: (纸本)9798350325157

A Design-for-test (DfT) technique is proposed in this paper for a test method, by which detecting open defects occurring interconnects between 3D stacked SRAM IC and a printed circuit board and among dies inside them. The test method is based on the supply current that is made flow through an interconnect to be tested. The DfT technique utilizes a built-in current sensor circuit to detect the open defects. It is shown that open defects occurring at interconnects among dies designed by the DfT method in a 3D stacked SRAM IC, and between the IC and a circuit board can be detected by the supply current test method. © 2023 IEEE.

关键词： Static random access storage

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Arabic text sentiment analysis and emotion classification using transformers

Arabic text sentiment analysis and emotion classification us...

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Electronics, Communications, and Computations (JAC-ECC), International Japan-Africa Conference on

作者： Nada Mossad Youssef Mohamed A Fares Ahmed B. Zaky Egypt-Japan University of Science and Technology (E-JUST) Alexandria Egypt The Department of Electrical Engineering The Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University

Sentiment analysis and emotion classification are two crucial components of natural language processing (NLP), which have been widely explored in recent years due to their broad applications. Sentiment analysis aims to identify the polarity of written texts, ranging from positive to negative. Meanwhile, emotion classification is focused on recognizing and categorizing the emotional states expressed in the text. To achieve a deeper understanding of sentiments and emotions, it's essential to utilize models like BERT transformers that can effectively interpret the context. The process begins with data preprocessing, including tokenization and noise removal, followed by fine-tuning techniques to adapt the BERT model to the proposed tasks. We employed the BERT model on four datasets obtained from various sources, including Twitter, news websites, and restaurant reviews, where each dataset represents a distinct Arabic dialect. Our proposed model outperforms commonly used techniques like LSTM and CNN, yielding superior results. Despite the progress made, there are still challenges to overcome, such as dealing with Arabic diacritics, the new Arabic Arabizi, which uses Latin characters, and handling Arabic idioms. Further research is required to address these challenges adequately.

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study of Dispersion Compensation with Dispersion Compensating Fiber in 10 Gbps Single-Mode Fiber

Study of Dispersion Compensation with Dispersion Compensatin...

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2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021

作者： Effendi, Nabila Syadzwina Natali, Yus Apriono, Catur Universitas Indonesia Faculty of Engineering Department of Electrical Engineering Depok Indonesia Akademi Telkom Sandhy Putra Jakarta Telecommunication Engineering Program Jakarta Indonesia

ISBN: (纸本)9781665438650

The industrial revolution was able to solve various social challenges in society, which create a sustainable life and bring people to the uttermost advanced society, Society 5.0. In Society 5.0, a massive amount of data from the sensor will rapidly accumulate in cloud services. It requires enormous bandwidth and high-speed communication than can be achieved by using optical fiber as a transmission media. However, chromatic dispersion will limit the bandwidth and data rate due to pulse broadening, which needs compensation. Among many compensation techniques for optical fiber systems, this research investigates the effects of dispersion compensating fiber (DCF) in a single-mode-fiber (SMF) using a 10 Gbps bit rate at various source power levels. This research considers three different schemes of DCF, i.e., pre-compensation, post-compensation, and symmetrical compensation with NRZ modulation format at transmission distances up to 200 km simulated by using OptiSystem. The results show that the dispersion effect can be compensated by the proposed DCF scheme. Also, the use of amplifiers should be considered to compensate for the high attenuation effect of DCF. The system performance showed that using a three different scheme of DCF could provide a good system performance and reach a transmission distance of 200 km. © 2021 IEEE.

关键词： Single mode fibers

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Predicting Potential Fires in Indonesia by Analyzing VIIRS Night Data during 2018 – 2022

Predicting Potential Fires in Indonesia by Analyzing VIIRS N...

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International Symposium on Grids and Clouds 2023 in conjunction with HEPiX Spring Workshop, ISGC and HEPiX 2023

作者： Suhardiman, Basuki Hermanto, Benni Rio Directorate of Information Technology Institut Teknologi Bandung Jl Ganesha 10 Bandung Indonesia Master’s Program in Computational Science Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl Ganesha 10 Bandung Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia

Forest fires have been detected to occur in Indonesia since 1998. The forest fires mostly resulted from human activities in order to expand their land, especially oil palm lands. Once a land clearing is carried out, it covers areas of tens to hundreds of thousands of hectares. The peak of the forest fires occurred in 2015 when almost half of the world was affected especially by smoke from the fire. In 2011, VIIRS (Visible Infrared Imaging Radiometer Suite) was launched by NOAA (National Oceanic and Atmospheric Administration). In their collected data, there is data on Indonesia issued daily for areas in the islands of Java, Sumatra, Kalimantan, Sulawesi, and the general areas of Indonesia. The VIIRS night data shows the possibility of some burning at night. We need to identify burnings that potentially become fires, which are potentially producing smoke. It is important to observe areas where large-scale forest fires frequently occur, so the authority could do some prevention beforehand. Using existing data released per day per area, we utilize an ANN (Artificial Neural Network) to identify a potential fire. The processes start with data cleaning and processing, Neural Network creation, and finally ANN training and testing. By using the ANN prediction model with the MinMax Scaler, we choose variables Temperature, Radiant Heat Intensity, and Source Footprint. Simulations are made to show the ranges of these variables that predict the possibility of’flame’ status occurring. We conclude that the ANN method can give more accurate results than the existing classification. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Fires

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Implementation of AI-Based Support Vector Machine Algorithm for Fraud Detection in Digital Payment Systems

Implementation of AI-Based Support Vector Machine Algorithm ...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Edy Prayitno Rikie Kartadie Uning Lestari Munengsih Sari Bunga Accounting Information Systems Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Computer Engineering Study Program Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Informatics Study Program Faculty of Science and Information Technology Universitas Akprind Indonesia Yogyakarta Indonesia Department of Computer Engineering Smart City Information Systems Politeknik Negeri Indramayu Indramayu Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The increasing use of digital payment systems has led to a rise in fraudulent activities, presenting a significant challenge in ensuring secure transactions. This research focuses on implementing the Support Vector Machine (SVM) algorithm with a Radial Basis Function (RBF) kernel to detect fraud in digital payment systems. One of the main challenges addressed in this study is the severe class imbalance in the dataset, where fraudulent transactions account for only 0.17% of total transactions. To overcome this, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied to balance the dataset, allowing the model to better recognize fraudulent patterns. The results indicate that the SVM model achieved an accuracy of 99.93%, with a precision of 86.23% and a recall of 75.51%. These results demonstrate that SVM, combined with SMOTE and RBF kernel, is highly effective in detecting fraudulent transactions while minimizing false positives. This research provides a strong foundation for improving fraud detection models in the context of digital payment systems, offering enhanced security and trust for users. Further research could explore hybrid models and real-time data analysis to improve performance.

关键词： Support vector machines Seminars Adaptation models Accuracy Data models Real-time systems Fraud Security Kernel Intelligent systems

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