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arXiv 2023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 Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Department of Computer Science National Chengchi University Taipei11605 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

Forged content shared widely on social media platforms is a major social problem that requires increased regulation and poses new challenges to the research community. The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous work on detecting AI-generated fake videos only utilizes visual modality or audio modality. While there are some methods in the literature that exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multi-modal datasets of deepfake videos involving acoustic and visual manipulations. Moreover, these existing methods are mostly based on CNN and suffer from low detection accuracy. Inspired by the recent success of Transformer in various fields, to address the challenges posed by deepfake technology, in this paper, we propose an Audio-Visual Transformer-based Ensemble Network (AVTENet) framework that considers both acoustic manipulation and visual manipulation to achieve effective video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multi-modal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that our best model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. © 2023, CC BY.

关键词： Statistical tests

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Fault Diagnosis of Wind Energy Conversion Systems Using Gaussian Process Regression-based Multi-Class Random Forest

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IFAC-PapersOnLine 2022年第6期55卷 127-132页

作者： Majdi Mansouri Radhia Fezai Mohamed Trabelsi Hajji Mansour Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematics and Sciences Prince Sultan University Riyadh 11586 Saudi Arabia Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electronic and Communications Engineering Department Kuwait College of Science and Technology P. O. Box 27235 Kuwait Higher Institute of Applied Science and Technology of Kasserine University of Kairouan PO Box 471 1200 Kasserine Tunisia Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

This work proposes a new fault diagnosis approach for a wind energy conversion (WEC) system. The proposed technique merges the benefits of feature extraction based on Gaussian Process Regression (GPR) and Multi-Class Random Forest (MCRF)-based fault classification where instances are classified into one or more classes. In the developed GPR-MCRF approach, the nonlinear statistical features including the mean vector M GPR and the variance matrix C GPR are computed using the GPR model with aim of extracting the most relevant features from the WEC system. Then, these features are introduced to the RF classifier for classification and diagnosis purposes. Therefore, the application of the GPR-MCRF technique for WEC systems aims to enhance the use of the classical raw data-based MCRF and diagnosis accuracy. Three kinds of faults (wear-out, open-circuit, and short-circuit faults) are considered in this work. Different case studies are investigated in order to illustrate the effectiveness and robustness of the developed technique compared to the state-of-the-art methods. The obtained results show that the the developed GPR-MCRF technique is an effective feature extraction and fault diagnosis technique for WEC systems.

关键词： Random Forest (RF) Multi-Class Gaussian Process Regression (GPR) Fault Diagnosis Wind Energy Conversion Systems

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Application of Deep Artificial Neural Network to Model Characteristic Fluctuation of Multi-Channel Gate-All-Around Silicon Nanosheet and Nanofin MOSFETs Induced by Random Nanosized Metal Grains

Application of Deep Artificial Neural Network to Model Chara...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Sagarika Dash Yiming Li Wen-Li Sung Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Center for mm Wave Smart Radar System and Technologies National Yang-Ming Chiao Tung University Hsinchu Taiwan

In this work, we propose a deep artificial neural network (D-ANN) to estimate the work function fluctuation (WKF) on 4-channel stacked gate-all-around (GAA) silicon (Si) nanosheet (NS) and nanofin (NF) MOSFET devices for the first time. The 2-layered simple deep model can well predict the transfer characteristics for both NS/NF FET with a large number of (128) input features, utilizing considerably lesser (1100 samples) data uniformly. The resultant model is evaluated by the $\mathrm{R}^{2}$ score and RMSE to witness its competency and the average error is $< 4\%$ . We do also discuss the circuit simulation possibility by applying the ANN approach.

关键词： Semiconductor device modeling MOSFET Gallium arsenide Artificial neural networks Predictive models Logic gates Silicon

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Guava Trees Disease Monitoring Using the Integration of Machine Learning and Predictive Analytics 3

Guava Trees Disease Monitoring Using the Integration of Mach...

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3rd Novel Intelligent and Leading Emerging Sciences Conference, NILES 2021

作者： Elsayed, Mahmoud Hassan, Nourhan Maher, Marina Waleed, Nouran Reda, Rehab Eldin, Haitham Sharaf Mostafa, Hassan The American University of Cairo Mechatronics Department Egypt Nile University Giza12677 Egypt Communication Engineering Alexandria University Egypt Biomedical Engineering Cairo University Egypt Tanta University Egypt Cairo University Faculty of Science Biophysics Department Egypt Cairo University Electronics and Electrical Communications Engineering Department Giza Egypt University of Science and technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology October Gardens 6th of October Giza12578 Egypt

ISBN: (纸本)9781665421577

The increase in population, food demand, and the pollution levels of the environment are considered major problems of this era. For these reasons, the traditional ways of farming are no longer suitable for early and accurate detection of biotic stress. Recently, precision agriculture has been extensively used as a potential solution for the aforementioned problems using high resolution optical sensors and data analysis methods that are able to cope with the resolution, size and complexity of the signals from these sensors. In this paper, several methods of machine learning have been utilized in order to study pests, their types, population, and agricultural conditions in terms of soil and climate for some crops such as potatoes, guava, and cotton, which are among the main Egyptian crops. In the process of obtaining a suitable estimate of insects population affecting each of the aforementioned crops, a hardware model control, based on the results provided by the predictive analysis, an estimate of the electromagnetic force is applied to the cultivated areas to get rid of the pests as well as giving a background to farmers about the possibility of infecting a crop such as Potato with Late Blight, according to climatic conditions. © 2021 IEEE.

关键词： Model predictive control

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Analysis of Negative Capacitance MOSFETs Characteristic with Spacer

Analysis of Negative Capacitance MOSFETs Characteristic with...

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2020 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2020

作者： Lee, Yu-Chun Kola, Sekhar Reddy Chen, Chieh-Yang Chuang, Min-Hui Li, Yiming Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Institute of Communications Engineering Eecs International Graduate Program Department of Electrical and Computer Engineering Center for MmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd Hsinchu300 Taiwan

ISBN: (纸本)9781728142326

In this work, our study comprises of design and investigation on negative capacitance (NC), metal-oxide-semiconductor (MOS) field effects transistors (MOSFETs) with spacer and source/drain (S/D) overlap engineering. The scope of the work is to boost the performance and high-energy efficiency of the studied NC-MOSFETs by using the ferro electric material (FE). The NC-MOSFETs with the spacer technology can achieve the admirable Ion/Ioff ratio and subthreshold swing (SS), compared with planar MOSFETs. It makes device scaling possible by eliminating the short channel effect (SCE). We further estimated the effect of FE thickness and spacer, which are another critical parameter of obtaining better electrical characteristics and reducing SS. © 2020 IEEE.

关键词： Capacitance

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Scaling Limitations of Line TFETs at Sub-8-nm Technology Node

Scaling Limitations of Line TFETs at Sub-8-nm Technology Nod...

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2020 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2020

作者： Thoti, Narasimhulu Li, Yiming Kola, Sekhar Reddy Parallel and Scientific Computing Laboratory Eecs International Graduate Program Institute of Communications Engineering Department of Electrical and Computer Engineering Center for MmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd Hsinchu300 Taiwan

ISBN: (纸本)9781728142326

The scope of the work is to investigate limitations in device scaling by identifying various parameters of short channel effects (SCEs) in current challenging geometries of the line tunnel field effect transistors (TFETs). Key factors of the considered device, such as the doping and the thickness (tn) of n-epitaxial region, and source-to-drain length (LSDeff) scaling cannot be tuned anymore to boost the device characteristics for the sub-8-nm technology node. The main results of this study indicates that the engineering acceptable performance are achieved at a low doping of 5 1018 cm-3, an optimal tn as low (about 0.5 nm), and a LSDeff greater than 12.5 nm. Hence, the line TFETs below sub-8-nm faces serious bottleneck of scaling and cannot be further scaled with the conventional scaling rule at all. © 2020 IEEE.

关键词： Tunnel field effect transistors

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Blue micro-LED with a red/green blended polymer film for 3.5-Gbps visible light communication employing adaptive SNR-Flattening Algorithm

Next Nanotechnology

引用

Next Nanotechnology 2024年 5卷

作者： Ho, Pin-Wei Cheng, Chih-Hsien Liao, Yu-Sheng Chi, Yu-Chieh Sadhu, Annada Sankar Matsumoto, Atsushi Akahane, Kouichi Chen, Li-Yin Kuo, Hao-Chung Lin, Gong-Ru Graduate Institute of Photonics and Optoelectronics and Department of Electrical Engineering National Taiwan University Taipei 106319 Taiwan National Institute of Information and Communications Technology Koganei Tokyo 184-8795 Japan SANWAY OPTOELECTRONICS TECH. CORP New Taipei City 235601 Taiwan Department of Photonics Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 30010 Taiwan International Ph.D. Program in Photonics (UST) College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 30010 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei 11492 Taiwan NTU-Tektronix Joint Research Center Tektronix Inc. and National Taiwan University Taipei 106319 Taiwan

By the semipolar blue single GaN μ-LED and blended Ir(piq)2(acac) + CC-MP5 polymer thin film color converter, a high-speed white-light μ-LED-based system is built up for the applications of short-distance VLC. The characteristics and properties of both devices are analyzed to understand the requirements for transmission and illumination. By selecting the growing orient, the influence of QCSE is reduced in this GaN μ-LED. Meanwhile, possessing the low reflection characteristic, it is beneficial for signal modulation. For the polymer thin film color converter with a lifetime of 7.8 ns, low surface reflection and high conversion efficiency are thought of good properties. Color-converted cool white light has a CCT of around 7000 K and high color accuracy with a CRI of about 90. The APD-combined frequency responses of the GaN μ-LED and GaN μ-LED + polymer are measured as 750 MHz and 600 MHz, respectively. After the optimization by utilizing the adaptive SNR-flattening pre-emphasis algorithm, the transmission performance of the white-light μ-LED is significantly promoted. For NRZ-OOK encoding, a 1.4 Gbps 0.15-m free-space transmission is achieved with a rising time of 656.33 ps, a falling time of 493.32 ps, and a Q-factor of 4.75. Besides, in more advanced data formats, the performance of this white-light μ-LED can be better highlighted. For the same 0.15-m free-space VLC, a high-speed 3 Gbps broadband 8-QAM-OFDM transmission is fulfilled with an EVM of 23.9%, an average SNR of 12.5, and a BER below 3.8 × 10^-3;while to the best of our knowledge, a record 3.5 Gbps BL-DMT transmission is implemented as well. This white-light μ-LED can also be integrated into large-scale arrays for multi-functional VLC applications. © 2024 The Authors

关键词： Adaptive SNR-Flattening algorithm Blue micro-LED Red/Green blended polymer Visible light communication

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation

A Genetic Algorithm to Optimize Cargo Stability in Container...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Chi-Jung Hsieh Kuang-Sung Wu Tin-Yu Wu Fu Jie Tey Yi-Kai Chen Jye Yi Ho Department of Computer Science and Information Engineering National Ilan University Ilan County Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Pingtung County Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781665492331

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method.

关键词： Rollover Transportation industry Roads Stacking Transportation Containers Safety

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Histogram specification by assignment of optimal unique values

arXiv

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arXiv 2021年

作者： Ramos, Vítor S. de Q. Silveira, Luiz Felipe de Q. Silveira Júnior, Luiz Gonzaga Electrical and Computer Engineering Graduate Program Federal University of Rio Grande do Norte Natal Brazil Computer Engineering and Automation Department Federal University of Rio Grande do Norte Natal Brazil Communications Engineering Department Federal University of Rio Grande do Norte Natal Brazil

In this paper, we propose two novel algorithms for histogram specification and quantile transformation of data without local information. These are core techniques that can serve as building blocks for applications that require specifying the sample distribution of a given set of data. Histogram specification is best known for its image enhancement applications, whereas quantile transformation is typically employed in data preprocessing for data normalization. In signal processing, methods often require temporal or spatial information;in data preprocessing, methods work by interpolation or by approximation, drawing from results in computational statistics, and have a trade-off between speed and quality. It is nontrivial to accommodate for cases that do not have local information (e.g., tabular data) while also providing a fast, exact solution. For that, we take up a concept in image processing called group mapping law and propose an extension. The proposed extension allows us to formulate a convex functional where we look for the best approximation between the output unique values and the reference histogram. Then, we apply the ordered assignment solution, a result in optimal transport, to reconstruct the output from the optimal unique values. Two sets of results show the effectiveness of the proposed algorithms when compared to traditional and state-of-the-art methods. The proposed algorithms are fast, exact, and least p-norm optimal. Further, we define the algorithms as generic data processing methods. Thus, contributions from this paper can be easily incorporated in applications spanning many disciplines, especially in applied data science. Copyright © 2021, The Authors. All rights reserved.

关键词： Graphic methods

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Root cause analysis and defect ground effect of EMI problem for power electronics

Root cause analysis and defect ground effect of EMI problem ...

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2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electromagnetic Compatibility, EMC Sapporo/APEMC 2019

作者： Lin, Han-Nien Tseng, Wei-Ding Wu, Cheng-Hau Yeh, Ting-Hao Ho, Tzu-Hao Feng Chia University Department of Communications Engineering Taichung City Taiwan Ansys Taiwan Taiwan Feng Chia University Ph.D. Program of Electrical and Communications Engineering Taichung City Taiwan

ISBN: (纸本)9784885523229

The DC-DC converter is a crucial component of electronic modules or systems, and thus making electromagnetic interference issue essential. Even though power IC manufacturer often provides useful PCB design guidelines, but power electronic engineer sometimes ignores the design rules because of his own application concerned or cost issue. This usually leads the converter to a poor EMI performance in the first time, thus requiring additional engineering resources, greater time to market, as well as higher EMI filter costs to comply with related EMI regulations. In this paper, we'll analyze the root cause of EMI problem on a DC-DC converter module built with single layer-double side PCB, and point out some factors of PCB ground design that will affect the EMI performance. Since there is no complete pair for power-ground plane, the plane resonance issue will not be discussed in this paper. © 2019 The Institute of Electronics, Information and Communication Engineer.

关键词： Power electronics

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