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2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang-Ming Chiao Tung University Parallel and Scientific Computing Laboratory Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Electrical Engineering and Computer Science International Graduate Program Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Department of Electrical Engineering and Computer Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300 Taiwan Center for mmWave Smart Radar System and Technologies National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300 Taiwan

ISBN: (纸本)9781665409230

In this paper, for the first time, deep learning (DL) based artificial neural network (ANN) is applied to model the effects of various random variations: work function fluctuation, random dopant fluctuation, and interface trap fluctuation, on gate-all-around silicon nanosheet MOSFETs. The number of fluctuations for each source variation is used as input features and their effects on devices of interest are studied qualitatively and quantitatively. The key figures of merit (FoM) are also extracted accurately from the transfer characteristics, which shows the competency of the ANN model in the domain of device modeling. © 2022 IEEE.

关键词： Nanosheets

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Adaptive and Fair Deployment Approach to Balance Offload Traffic in Multi-UAV Cellular Networks

arXiv

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arXiv 2022年

作者： Lai, Chuan-Chi Bhola Tsai, Ang-Hsun Wang, Li-Chun The Department of Information Engineering and Computer Science Feng Chia University Taichung40724 Taiwan The Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu30010 Taiwan The Department of Communications Engineering Feng Chia University Taichung40724 Taiwan The Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan

Unmanned aerial vehicle-aided communication (UAB-BS) is a promising solution to establish rapid wireless connectivity in sudden/temporary crowded events because of its more flexibility and mobility features than conventional ground base station (GBS). Because of these benefits, UAV-BSs can easily be deployed at high altitudes to provide more line of sight (LoS) links than GBS. Therefore, users on the ground can obtain more reliable wireless channels. In practice, the mobile nature of the ground user can create uneven user density at different times and spaces. This phenomenon leads to unbalanced user associations among UAV-BSs and may cause frequent UAV-BS overload. We propose a three-dimensional adaptive and fair deployment approach to solve this problem. The proposed approach can jointly optimize the altitude and transmission power of UAV-BS to offload the traffic from overloaded UAV-BSs. The simulation results show that the network performance improves by 37.71% in total capacity, 37.48% in total energy efficiency and 16.12% in the Jain fairness index compared to the straightforward greedy approach. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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An Enhanced System for Wrong-Way Driving Vehicle Detection with Road Boundary Detection Algorithm

An Enhanced System for Wrong-Way Driving Vehicle Detection w...

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2022 International Conference on Industry Sciences and computer Science Innovation, iSCSi 2022

作者： Suttiponpisarn, Pintusorn Charnsripinyo, Chalermpol Usanavasin, Sasiporn Nakahara, Hiro TAIST Tokyo Tech ICTES Program Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathum Thani Thailand School of ICT Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand Dept. of Information and Communications Engineering Tokyo Institute of Technology Tokyo Japan

Driving in the wrong direction is one of the main reasons that cause road accidents in Thailand. To efficiently detect wrong direction driving vehicles, we proposed a system that can track those moving vehicles from CCTVs using deep learning and image processing techniques. Our proposed system is composed of two main algorithms: Road Lane Boundary detection from CCTV algorithm (RLB-CCTV) and Majority-Based Correct Direction Detection algorithm (MBCDD). In this paper, we introduced the RLB-CCTV algorithm and the enhanced version of MBCDD algorithms for detecting road boundaries and wrong-direction driving vehicles. Based on our experiments, our system can identify the road lane boundary and track vehicles driving in the wrong direction on each lane with an accuracy of 96.61%. © 2022 Elsevier B.V.. All rights reserved.

关键词： Hough transforms

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Performance comparison of InGaN-based 40–80 μm micro-LEDs fabricated with and without plasma etching

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Materials Today Advances 2024年 22卷

作者： Lo, Yu-Yun Chen, Yi-Ho Hsu, Yun-Cheng Lee, Tzu-Yi Hung, Yu-Ying Kao, Yu-Cheng Zan, Hsiao-Wen Wuu, Dong- Sing Kuo, Hao-Chung Samukawa, Seiji Horng, Ray-Hua Institute of Electronics National Yang Ming Chiao Tung University 1001 University Road Hsinchu30010 Taiwan Department of Photonics College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan

The fabrication of InGaN-based blue 4✕4 array micro-LEDs (μLEDs) with 40 μm ✕40 μm chip size and 2✕2 array μLEDs with 80 μm ✕80 μm chip size etching by the inductive coupled plasma reactive ion etching (ICPRIE) and defect-free neutral beam etching (NBE) processes was studied in this work. In μLEDs of this size, the influence of defects formation in the sidewalls on EQE was evaluated. There was almost no difference in EQE between μLEDs array etched by the NBE process no matter 40 μm ✕40 μm and 80 μm ✕80 μm, but the dependence was observed in the ICPRIE. Even with this size, it was found that the size effect of EQE is smaller than that in case of using ICPRIE for defect-free neutral beam etching. This impact is substantial since μLED predominantly operated at low current density, around 1–5 A/cm2. Consequently, the reduction of defect density, encompassing both internal and sidewall defects, becomes imperative even in 40–80 μm InGaN-based μLEDs. This not only improves the overall efficiency of μLEDs but also fortifies the brightness stability of μLED displays if process etching by NBE. It was also found that the etching shape had an influence on EQE. It could be attributed to fact that the etching profile angle of NBE was more vertical than that of ICPRIE. Because the different angles of the mesa resulted in different light intensity. The μLEDs emitting with a wavelength of 450 nm, the light extraction efficiency and intensity at a mesa angle 58° of NBE etching μLEDs was about 8% lower than those of an angle (38°) of ICPRIE etching μLEDs by simulation. © The Authors

关键词： Light emitting diodes

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Noise-Robust Deep Spiking Neural Networks with Temporal Information 21

Noise-Robust Deep Spiking Neural Networks with Temporal Info...

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Proceedings of the 58th Annual ACM/IEEE Design Automation Conference

作者： Seongsik Park Dongjin Lee Sungroh Yoon Department of Electrical and Computer Engineering Seoul National University Seoul South Korea and Institute of New Media and Communications Seoul National University Seoul South Korea Department of Electrical and Computer Engineering Seoul National University Seoul South Korea Department of Electrical and Computer Engineering Seoul National University Seoul South Korea and Institute of New Media and Communications Seoul National University Seoul South Korea and ASRI and Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul South Korea

ISBN: (纸本)9781665432740

Spiking neural networks (SNNs) have emerged as energy-efficient neural networks with temporal information. SNNs have shown a superior efficiency on neuromorphic devices, but the devices are susceptible to noise, which hinders them from being applied in real-world applications. Several studies have increased noise robustness, but most of them considered neither deep SNNs nor temporal information. In this paper, we investigate the effect of noise on deep SNNs with various neural coding methods and present a noise-robust deep SNN with temporal information. With the proposed methods, we have achieved a deep SNN that is efficient and robust to spike deletion and jitter.

关键词： neural coding

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Quality Improvements in the Electrical Design of Typical DC-DC Electronic Power Converter for High-Voltage Applications

Quality Improvements in the Electrical Design of Typical DC-...

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International Conference on engineering and Emerging Technologies (ICEET)

作者： King Harold A. Recto Miguel T. Escoto Noel B. Hernandez Department of Electronics Computer and Communications Engineering Ateneo de Manila University Quezon City Philippines Electrical and Electronics Engineering Institute University of the Philippines Diliman Quezon City Philippines Post-doctoral Program in Quality Management of the Graduate School Centro Escolar University Manila Philippines

ISBN: (纸本)9781665491075

The green transition has brought about a worldwide-shift to the use of renewables as alternative energy sources. Because of this, high voltage DC has been a field of interest in power electronics due to its capability in efficiently transmitting power to reach remote areas. Typical DC-DC electronic power converter design has the capability of boosting voltage level to a certain extent but not enough for high-voltage applications. Using the DMAIC Approach of the Six Sigma, quality improvements in the design was proposed to stabilize operating frequency, bring up the output voltage from 100 VDC to 4,000 VDC and provide at least 10% margin of error in the apparent power measured at the output side to offset inherent losses in the electrical design. These proposed quality improvements were sustained by designing a control circuit that would ensure the attainment of the parameters set in the Define Phase of the DMAIC Approach. The result of the study is a practical 12 VDC to 4,000 VDC boost converter design that has incorporated all the proposed quality improvements.

关键词： Renewable energy sources Voltage measurement Power measurement Measurement uncertainty Green products High-voltage techniques Loss measurement

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High School and College Students’ Graph-Interpretation Competence in Scientific and Daily Contexts of Data Visualization

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Science & Education 2022年第3期33卷 1-23页

作者： Binali, Theerapong Chang, Ching-Hwa Chang, Yen-Jung Chang, Hsin-Yi Department of Computer Science and Information Engineering National Taiwan Normal University Taipei City Taiwan Program of Learning Sciences and Institute for Research Excellence in Learning Sciences National Taiwan Normal University Taipei City Taiwan Department of Graphic Arts and Communications National Taiwan Normal University Taipei City Taiwan

This study surveyed 183 college and senior high school students’ graph-interpretation competence in scientific and daily contexts. Specifically, whether students’ graph interpretation in scientific and daily contexts differed across educational levels was investigated. Furthermore, the questions of whether students’ graph interpretation competence in scientific contexts might predict their graph interpretation in daily contexts were explored. Other factors including age and gender were also considered and examined to discern significant factor(s) predicting graph interpretation competence in daily contexts. Results indicated that there were statistically significant differences across educational levels in terms of graph interpretation competence in both scientific and daily contexts. Furthermore, the students’ graph interpretation competence was related between scientific and daily contexts. The important factors predicting students’ graph interpretation in daily contexts include age and graph-interpretation in scientific literacy. Implications are discussed.

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Statistical Analysis of Intrinsic High-Frequency Characteristic Fluctuation of Emerging Silicon Gate-All-Around Nanosheet (NS) MOSFETs at Sub-3-nm Nodes

Statistical Analysis of Intrinsic High-Frequency Characteris...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Sekhar Reddy Kola Yiming Li Min-Hui Chuang Kazuhiko Endo Seiji Samukawa Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Institute of Communications Engineering Department of Electronics and Electrical Engineering Institute of Biomedical Engineering Center for mm Wave Smart Radar System and Technologies National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai Japan National Institute of Advanced Industrial Science and Technology Tsukuba Japan

In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically independent and identically distributed $(iid)$ assumptions on the aforementioned random variables overestimate the variability of high-frequency characteristics, compared with considering all fluctuation factors simultaneously. Notably, the random nanosized metal grains dominates the variations of voltage gain, cut-off frequency, and 3dB frequency because the random work functions strongly alter the channel surface potential.

关键词： MOSFET Fluctuations Statistical analysis Gallium arsenide Cutoff frequency Metals Logic gates

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Unmasking Illusions: Understanding Human Perception of Audiovisual Deepfakes

arXiv

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arXiv 2024年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei11529 Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu300044 Taiwan Department of Computer Science National Chengchi University Taipei11529 Taiwan Department of Electrical Engineering Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Institute of Information Science Academia Sinica Taipei11529 Taiwan

The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the incidence of misinterpretation and is difficult to distinguish from genuine content. Currently, machine learning techniques have been extensively studied for automatically detecting deepfakes. However, human perception has been less explored. Malicious deepfakes could ultimately cause public and social problems. Can we humans correctly perceive the authenticity of the content of the videos we watch? The answer is obviously uncertain;therefore, this paper aims to evaluate the human ability to discern deepfake videos through a subjective study. We present our findings by comparing human observers to five state-of-the-art deepfake detection models. To this end, we used gamification concepts to provide 110 participants (55 native English speakers and 55 non-native English speakers) with a web-based platform where they could access a series of 40 videos (20 real and 20 fake) to determine their authenticity. Each participant performed the experiment twice with the same 40 videos in different random orders. The videos are manually selected from the FakeAVCeleb dataset. We found that all AI models performed significantly better than humans when evaluated on the same 40 videos. The study also reveals that while deception is not impossible, humans tend to overestimate their detection capabilities. Our experimental results may help benchmark human versus machine performance, advance forensics analysis, and enable adaptive countermeasures. © 2024, CC BY.

关键词： Audiovisual

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Understanding Audiovisual Deepfake Detection: Techniques, Challenges, Human Factors and Perceptual Insights

arXiv

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arXiv 2024年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu300044 Taiwan The Department of Computer Science National Chengchi University Taipei11529 Taiwan The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Deep Learning has been successfully applied in diverse fields, and its impact on deepfake detection is no exception. Deepfakes are fake yet realistic synthetic content that can be used deceitfully for political impersonation, phishing, slandering, or spreading misinformation. Despite extensive research on unimodal deepfake detection, identifying complex deepfakes through joint analysis of audio and visual streams remains relatively unexplored. To fill this gap, this survey first provides an overview of audiovisual deepfake generation techniques, applications, and their consequences, and then provides a comprehensive review of state-of-the-art methods that combine audio and visual modalities to enhance detection accuracy, summarizing and critically analyzing their strengths and limitations. Furthermore, we discuss existing open source datasets for a deeper understanding, which can contribute to the research community and provide necessary information to beginners who want to analyze deep learning-based audiovisual methods for video forensics. By bridging the gap between unimodal and multimodal approaches, this paper aims to improve the effectiveness of deepfake detection strategies and guide future research in cybersecurity and media integrity. © 2024, CC BY.

关键词： Audiovisual

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