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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Yang, Chang-Ming Wu, Shu-Cing Kao, Rally Liao, Kuo-Cheng Wu, Ze-We Chen, Shih-Hung Chen, Chi-Chun Ming Young Biomedical Corp Miaoli Taiwan National Chin-Yi University of Technology Program Prospective Technology of Electrical Engineering and Computer Science Taichung Taiwan Bonanza Biotechnology Co.Ltd National Chin-Yi University of Technology Dept. of Computer Science and Information Engineering Taichung Taiwan National Chin-Yi University of Technology Dept. of Electronic Engineering Taichung Taiwan

ISBN: (纸本)9798350324136

With the rapid advancement of electronic textiles, the design and integration of connectors have emerged as pivotal challenges. This study emphasizes the development of a connection solution that amalgamates miniaturization, efficiency, and reliability, specifically tailored for Flexible Conductive Silicone Circuits. A diversified connection scheme is proposed, incorporating elements such as snaps, Pogo pins, and conductive hook-and-loop fasteners, thereby achieving an innovative and pragmatic design. Through meticulous manufacturing processes, including the utilization of hot-melt adhesive, PET films, conductive fabric, and other multilayer materials, a connection system with low impedance and commendable conductivity was successfully engineered. Impedance test outcomes have indicated that the resistance at each connection point is less than 0.7 ohms, substantiating its superior electrical properties. In terms of assembly, this research demonstrates the precise interconnection of the controller and conductive fabric circuit, ensured by metal pin technology, leading to connection stability. This solution not only furnishes appropriate connection technology for specific application scenarios but also opens new avenues and directions for connection design within the domain of electronic textiles. © 2024 IEEE.

关键词： Connectors E-Textiles Flexible Conductive Silicone Circuit PET films

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Gate Stack engineering in n-type (-201) β-Ga2O3Transistors

Gate Stack Engineering in n-type (-201) β-Ga2O3Transistors

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2022 IEEE International Conference on Emerging Electronics, ICEE 2022

作者： Khandelwal, Vishal Yuvaraja, Saravanan Wang, Chuanju Chettri, Dhanu Li, Xiaohang Advanced Semiconductor Laboratory Electrical and Computer Engineering Program Cemse Division Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9781665491853

A systematic study of Al2O3 and SiO2/ Al2O3 dielectric on p-Ga2O3 is carried out including the effect of the forming gas annealing. Capacitance-voltage (C-V) curve of the Al2O3/Ga2O3 gate stack shows a large hysteresis and sweep-to-sweep C-V shift compared to SiO2/Al2O3/Ga2O3 case, which suggests SiO2 interlayer reduces the defect density in Al2O3/Ga2O3 gate stack. In addition, forming gas annealing further suppresses the interface and border traps density in both Al2O3/Ga2O3 and SiO2/ Al2O3/Ga2O3 gate stacks. A thin film transistor (TFT) with annealed SiO2/ Al2O3 dielectric has an on-off ratio of 106, a subthreshold swing (SS) of 0.75 V/decade, and a hysteresis width $(\mathrm{V}_{\text{Hy}})$ of 0.5 V compared to an on-off ratio of105, a SS of 1.2 V/decade, and a VHy of 2 V in the controlled TFT with unannealed Al2O3 dielectric. The increased on-off ratio by one order, reduced SS by > 400 mV/decade, and $\mathrm{V}_{\text{Hy}}$ by >1.5 V is attributed to decreased interface and border traps in annealed SiO2/ Al2O3 compared to unannealed Al2O3/Ga2O3 gate stack. Interface trap density is calculated by $\mathbf{V}_{\text{Hy}}$ of the transistor, which showed a five-time reduction in annealed SiO2/ Al2O3/Ga2O3 compared to the unannealed A;2O3/Ga2O3 gate stack. This study suggests that annealed SiO2/ Al2O3 dielectric stack is promising for $\boldsymbol{\upbeta}-\text{Ga}_2 \mathrm{O}_3$ transistors. © 2022 IEEE.

关键词： Gallium compounds

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization 3

Cloud-Native Mobile Application Applied for Law and Regulati...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Al Qausar, Muhammad Juan Heryadi, Yaya Lukas, Lukas Suparta, Wayan Sonata, Ilvico Doctor of Computer Science Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350394559

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process. © 2023 IEEE.

关键词： Cost effectiveness

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Demonstration of Ga2O3trigate transistors on (100) silicon substrates

Demonstration of Ga2O3trigate transistors on (100) silicon s...

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2022 IEEE International Conference on Emerging Electronics, ICEE 2022

作者： Yuvaraja, Saravanan Khandelwal, Vishal Krishna, Shibin Lu, Yi Liu, Zhiyuan Kumar, Mritunjay Chettri, Dhanu Tang, Xiao Garcia, Glen Issac MacIel Liao, Che-Hao Li, Xiaohang Advanced Semiconductor Laboratory Electrical and Computer Engineering Program Cemse Division Thuwa123955- 6900 Saudi Arabia

ISBN: (纸本)9781665491853

In this paper we demonstrated the UWBG Ga2O3 trigate transistors heterogeneously integrated on silicon substrate. This trigate transistor operates in depletion mode having decent Ion/Ioff ratio (105) and high transconductance (1 μS). Followed by the mobility is around 1.2 cm2/V. s. This work suggests that the ultrawide bandgap oxide transistors can be fabricated on various heterogenous substrates to achieve highly integrated, low cost, and robust electronics. © 2022 IEEE.

关键词： Energy gap

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The One-vs-Rest Method for a Multilabel Patent Classification Machine Learning Approach using a Regression Model

The One-vs-Rest Method for a Multilabel Patent Classificatio...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Widodo, Slamet Ermatita Setiawan, Deris Pradnyana, I Wayan Widi Universitas Sriwijaya Politeknik Negeri Sriwijaya Faculty of Engineering Department of Computer Engineering Palembang30139 Indonesia University of Sriwijaya Faculty of Engineering Palembang30139 Indonesia University of Pembangunan Nasional Veteran Jakarta Information System Program Jakarta Indonesia

ISBN: (纸本)9798350307306

Redundancy in patent abstracts, that is, the repetition of an International Patent Classification tag or patent class information across documents, poses a challenge in patent classification, which is essential for efficiently managing the growing number of patent documents. This study aims to develop a model to analyze the weights and index values of summary sentences to improve the efficiency and accuracy of patent classification. This model can predict relevant patent data types. Utilizing logistic regression and the one-vs-rest method, this study focuses on the development of models to analyze the weights and index values of summary sentences, with the goal of enhancing the precision and efficiency of patent classification. The main contribution of this research is the creation of predictive models for new patent documents to streamline patent citations based on document type. This study also serves as a reference for evaluating Indonesian patent document classification models, thereby facilitating the patent evaluation process. © 2023 IEEE.

关键词： Efficiency

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The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Pangestu, Gusti Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of computer Science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising. © 2022 IEEE.

关键词： Convolutional neural networks

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A Hybrid Inference Engine to Predict Uncertain Sugar Content for Sugar Industry 9th

A Hybrid Inference Engine to Predict Uncertain Sugar Content...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Asrol, Muhammad Napthaleni Utama, Ditdit Nugeraha Suharjito Harito, Christian Syafrudin, Muhammad Industrial Engineering Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Department of Artificial Intelligence and Data Science Sejong University Seoul05006 Korea Republic of

The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict sugar content by considering uncertainty factors. A hybrid model combining fuzzy subtractive clustering, and a fuzzy inference system is proposed to predict sugar content. The clustering results using silhouette and fuzzy subtractive clustering successfully identified 6 cluster centres from 2225 datasets collected in a sugar industry in East Java Province. The hybrid inference engine model is designed with fuzzy rules derived from the clustered data. Two inference models are developed: triangular and Gaussian fuzzy numbers. The testing results indicate that the hybrid model with triangular fuzzy numbers shows the smallest error with an R2 value of 0.95. This model is possible to applied in the sugar industry for decision makers in improving productivity with taking attention into uncertain factors influencing sugar content. © 2024 The Authors.

关键词： Prediction models

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Grating Coupled Attachment of Optical Fiber Arrays for in situ Photonics Experimentation

Grating Coupled Attachment of Optical Fiber Arrays for in si...

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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Arnold, Kellen P. Slaby, Joel B. Dattilo, Hannah M. Kaylor, C. Alex Schrimpf, Ronald D. Fleetwood, Daniel M. Ralph, Stephen E. Reed, Robert Weiss, Sharon M. Interdisciplinary Materials Science Program Vanderbilt University 2201 West End Ave NashvilleTN37235 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Electrical and Computer Engineering Vanderbilt University 2201 West End Ave NashvilleTN37235 United States

We report a simple, vacuum-compatible fiber attach process for in situ study of grating-coupled photonic devices. The robustness of this technique is demonstrated on grating-coupled waveguides exposed to multiple X-ra... 详细信息

关键词： Photonic devices

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Real-Time Object Detection Performance of YOLOv8 Models for Self-Driving Cars in a Mixed Traffic Environment 2

Real-Time Object Detection Performance of YOLOv8 Models for ...

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2nd International Conference on computer System, Information Technology, and Electrical engineering, COSITE 2023

作者： Afdhal, Afdhal Saddami, Khairun Sugiarto, Sugiarto Fuadi, Zahrul Nasaruddin, Nasaruddin Doctoral Program School of Engineering Universitas Syiah Kuala Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Indonesia Department of Civil Engineering Universitas Syiah Kuala Indonesia Department of Mechanical dan Industrial Engineering Universitas Syiah Kuala Indonesia Indonesia

ISBN: (纸本)9798350343069

Self-driving cars have gained significant attention in recent years. Real-time object detection is a critical component of their perception system. One of the main challenges in developing safe and efficient self-driving cars lies in accurately and in real-time detecting objects in diverse and complex traffic environments. This paper presents the performance evaluation of real-time object detection of YOLOv8 models, a state-of-the-art deep learning framework for self-driving cars in mixed traffic environments. The objective is to assess the extent of YOLOv8's object detection capabilities can be used for self-driving car within complex realworld traffic scenarios. The experimental results show that the accuracy of YOLOv8 during normal daylight scenarios ranges from 0.60 ~ 0.80. In contrast, the accuracy values obtained in night scenarios fall between 0.15 ~ 0.25. Similarly, the FMeasure of YOLOv8 models under daylight conditions ranges from 0.75 ~ 0.87. Conversely, the F-Measure in night conditions falls between 0.27 ~ 0.46. Based on our thorough evaluation results, YOLOv8 has demonstrated its robustness in detecting objects. However, the algorithm requires improvement to effectively handle the challenges of self-driving cars' object detection systems in mixed traffic, such as diverse object classifications, small-scale objects, fast-moving objects, blur, glare, and low-light illumination, particularly in nighttime scenarios. © 2023 IEEE.

关键词： Object detection

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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