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Mediterranean Conference on Embedded Computing (MECO)

作者： Abdelrahman Saeed Ayman Tawfik Hassan Mostafa Ahmed Hussein Khalil Electronics and Communications Engineering Department Cairo University Giza Egypt Department of Electrical and Computer Engineering Ajman University United Arab Emirates (UAE) University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza Egypt

Convolutional Neural Networks (CNN) have drawn the attention of researchers in the medical imaging field. Many researchers have exploited CNN for breast cancer detection. This study provides an Internet of Things (IoT) friendly implementation of CNN for breast cancer detection. To achieve faster time to Market, Deep-learning Processing Unit (DPU) on Field programmable Gate Array (FPGA) is adopted for the CNN hardware implementation. CNN inference on the proposed system achieves a 1.6x speed-up factor and 91.5% reduction in energy consumption compared to the conventional general-purpose multi-core Central Processing Unit (CPU).

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Immediate Effects of Vergence Exercises Using Automatic Dual Rotational Risley Prisms on Accommodative Lag and Facility

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Ophthalmology and Therapy 2023年第6期12卷 3361-3372页

作者： Huang, Shuan-Yu Su, Hui-Rong Hu, Yun-Shao Lee, Chi-Hung Tsai, Ming-Shan Yeh, Shang-Min Chen, Ya-Yu Tsai, Tzu-Hsun Department of Optometry Central Taiwan University of Science and Technology Taichung 402 Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung 407 Taiwan Department of Optometry Chung Shan Medical University Taichung 402 Taiwan Department of Electrical Engineering Feng Chia University Taichung 407 Taiwan Department of Electrophysics National Chiayi University Chiayi 600 Taiwan Department of Optometry Da-Yeh University Changhua 515 Taiwan Department of Ophthalmology National Taiwan University Hospital Hsin-Chu Branch Hsin-Chu Taiwan Department of Ophthalmology National Taiwan University Hospital Taipei City 100225 Taiwan

Introduction: This study evaluated novel automatic dual rotational Risley prisms (ADRRPs) as a vergence exercise tool for patients with myopia to improve accommodative lag and accommodative facility. Methods: Participants with myopia aged 20–24 years were recruited. After vergence exercises with prisms (treatment group) or plano lenses (control group) using ADRRPs for 10 min, measurements were taken using an open-field autorefractor (Grand Seiko WAM-5500) at viewing distances of 0.4 m and 6.0 m. We measured accommodative facility using a ± 2.00 D accommodative flipper. Results: A total of 56 participants (treatment group, 39;control group, 17) performed vergence exercises using ADRRPs. Participants in the treatment group showed improvements in accommodative lag at a 0.4 m viewing distance, with measurements of 0.57 D (right eye;OD) and 0.53 D (left eye;OS) and 0.21 D (OD) and 0.27 D (OS) before and after the exercises, respectively (p < 0.001). Over-refractions using an open-field autorefractor with spherical equivalent contact lenses at a 6.0 m viewing distance were − 0.01 ± 0.30 D (OD) and 0.03 ± 0.34 D (OS) and 0.15 ± 0.32 D (OD) and 0.19 ± 0.28 D (OS) before and after the exercises, respectively (difference + 0.16 D;p < 0.001). Accommodative facility values before and after exercises were 14.88 ± 3.36 and 15.59 ± 3.60 cpm, respectively (p < 0.01). No significant differences in accommodative lag, relaxation, and accommodative facility before and after exercise were observed in the control group. Conclusions: Using ADRRPs in vergence exercises can improve accommodative lag, accommodative facility, and accommodative relaxation in adults with myopia. Further research to evaluate persistent and long-term effects is needed. © 2023, The Author(s).

关键词： Accommodative facility Accommodative lag Automatic dual rotational Risley prisms (ADRRPs) Vergence exercise

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Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices Induced by Random Interface Traps

Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices ...

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IEEE Conference on Nanotechnology

作者： Sekhar Reddy Kola Min-Hui Chuang Yiming Li Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering Institute of Communications Engineering Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Hsinchu Taiwan

Three-dimensional (3D) bulk fin-typed field effect transistors (FinFETs) have emerged as key devices that can scale down the technology node beyond 22-nm. However, the scaled devices have created new sources of fluctuation inherent in 3D geometry. The interface trap is one such fluctuation that is caused by the trapping and de-trapping of charge carriers and has an adverse effect on device characteristics and variability. In this work, we study impacts of random interface traps (RITs) on electrical characteristic of bulk FinFETs by using a 3D quantum-mechanically corrected device simulation. RIT position effects on short channel effects (SCEs) are examined with physical governed influence to show the major fluctuations. More than 50% reductions of the RITs-induced characteristic fluctuation of the germanium (Ge) devices are observed, compared with Si devices. The Ge ones can reduce SCE variations and exhibit high immunity to RITs.

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Dynamic Radio Map Using Statistical Hypothesis Testing

Dynamic Radio Map Using Statistical Hypothesis Testing

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作者： Katagiri, Keita Sato, Koya Inage, Kei Fujii, Takeo Advanced Wireless and Communication Research Center University of Electro-Communications Tokyo182-8585 Japan Department of Electrical Engineering Tokyo University of Science Tokyo125-8585 Japan Electrical and Electronics Engineering Program Tokyo Metropolitan College of Industrial Technology Tokyo140-0011 Japan

Private fifth-generation mobile communication networks (5G) have garnered considerable attention for providing various communication services. In private 5G systems, such as those employed in smart factories, it is necessary to appropriately manage the interference power among diverse systems because each nonpublic operator deploys a gNodeB in the local area and utilizes a similar allocated frequency. Several researchers have discussed the use of a radio map, which stores the spatial distribution of received signal power values as a tool for managing intra-system interference. Radio maps are typically applied to television white space, where the location of the base station (BS) is fixed and the average value of the received signal power exhibits time-invariant characteristics. However, in private 5G networks, the estimation accuracy using a conventional radio map is lowered because the location of the BS may be changed when the factory is rearranged. In this study, a database server is used to infer a significant difference in the average values of the received signal power by means of Welch's ${t}$ -test;the server then updates the radio map based on the test results. The simulation results indicate that the proposed method can detect changes in the BS location and update the radio map accurately. © 2015 IEEE.

关键词： 5G mobile communication systems

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AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Taiwan International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei11529 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu30013 Taiwan National Chengchi University Department of Computer Science Taipei11605 Taiwan National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu300044 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan

The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utilize visual modality or audio modality. While some methods exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multimodal datasets of deepfake videos involving acoustic and visual manipulations, and are mostly based on convolutional neural networks with low detection accuracy. Considering that human cognition instinctively integrates multisensory information including audio and visual cues to perceive and interpret content and the success of transformer in various fields, this study introduces the audio-visual transformer-based ensemble network (AVTENet). This innovative framework tackles the complexities of deepfake technology by integrating both acoustic and visual manipulations to enhance the accuracy of 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 multimodal 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 the proposed model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. We also compare AVTENet against humans in detecting video forgery. The results show that AVTENet significantly outperforms humans. © 2016 IEEE.

关键词： audio-visual AVTENet Deepfake detection

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Effect of Metal Oxide Layers on the Performance of Polymer Optical Fiber-based Hydrogen Sulfide Sensors

Effect of Metal Oxide Layers on the Performance of Polymer O...

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IEEE/LEOS International Conference on Optical MEMS

作者： Juan D. L. Vargas Alex Dante Regina C. S. B. Allil Ignacio R. Matias Ignacio del Villar Marcelo M. Werneck Photonics and Instrumentation Laboratory (LIF) Nanotechnology Engineering Program Federal University of Rio de Janeiro Rio de Janeiro Brazil International Iberian Nanotechnology Laboratory (INL) Braga Portugal Photonics and Instrumentation Laboratory (LIF) Electrical Engineering Program Federal University of Rio de Janeiro Rio de Janeiro Brazil Electrical Electronic and Communications Engineering Department Public University of Navarre Pamplona Pamplona Spain

This work presents the development of polymer optical fiber (POF) sensors for hydrogen sulfide $(\mathrm{H}_{2}\mathrm{S})$ detection, coated with varying numbers of metal oxide layers. Four sensors with identical structures were fabricated, and their performance was evaluated when exposed to 200 ppm of $\mathrm{H}_{2}\mathrm{S}$ . Increasing the number of $\text{Fe}3\mathrm{O}_{4}$ layers led to a sensitivity enhancement, up to 8 times greater with 21 layers compared to 3 layers. However, sensitivity decreased with more than 21 layers. These findings highlight the importance of optimizing the number of layers to achieve the best performance of an $\mathrm{H}_{2}\mathrm{S}$ sensor.

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation 11

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

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

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

ISBN: (纸本)9781665492324

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. © 2022 IEEE.

关键词： Genetic algorithms

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H∞ gain-scheduled dynamic output feedback control with transient performance applied to electrical microgrid

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Journal of the Franklin Institute 2024年第7期361卷

作者： Fuentes, R.M. Lacerda, M.J. Morais, C.F. Oliveira, R.C.L.F. Palma, J.M. Engineering Systems Doctoral Program Faculty of Engineering Universidad de Talca Curicó3340000 Chile Centre for Communications Technology School of Computing and Digital Media London Metropolitan University LondonN7 8DB United Kingdom Pontifical Catholic University of Campinas – PUC-Campinas Polythecnic School Postgraduate Program in Telecommunication Networks Management SP Campinas13086-900 Brazil SP Campinas13083-852 Brazil Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó334000 Chile

This paper introduces an approach for designing gain-scheduled dynamic output feedback controllers for continuous-time Linear Parameter-Varying (LPV) systems. The aim is to improve transient response by incorporating both D-stability and H∞ criteria into the synthesis conditions. We achieve this by employing changes of variables and congruence transformations, which lead to new synthesis conditions expressed as linear matrix inequalities. Additional fine-tuned scalar parameters can be used to enhance further the controller performance in terms of less conservative H∞ guaranteed costs. To assess the effectiveness of our proposed synthesis procedure, we conduct computational experiments in the context of a microinverter-based distributed power generation system. These experiments take into account real-world operational characteristics, providing a comprehensive evaluation of our approach. The results demonstrate that the designed controller effectively ensures the desired closed-loop system behavior, even when dealing with state noise and discretization errors originating from digital implementation. © 2024 The Franklin Institute

关键词： Transient analysis

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

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Telecommunications Conference (ITC-Egypt), International

作者： Rana M. NourEldeen Rahma A. Elshshtawy Omnia A. Elgohary Fatma Alzahraa A. Wahba Marco K. Attia Zeinab B. Abo elazm Mohamed G. Khattap Hend Galal Eldeen Mohamed Ali Hassan Mariam Mostafa Nayra Ibrahim Reem Ramadan Yomna Refaat Mennatallah Khaled Ali Maher Mohamed Abd Elaziz Ahmed Gamal Abdellatif Ibrahim Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez Egypt Biomedical Informatics Faculty of Computer Science and Engineering Galala University Suez Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez Egypt Department of Electronics and Electrical Communications Engineering Air Defense College Alexandria Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %.

关键词： 6G mobile communication Deep learning Multiple sclerosis Accuracy Internet of Medical Things Telecommunications Convolutional neural networks

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Design and exploration of vertically stacked complementary tunneling field-effect transistors

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Applied Physics Express 2024年第1期17卷 014001-014001页

作者： Thoti, Narasimhulu Li, Yiming Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

The purpose of this letter is to study the design and explore vertically stacked complementary tunneling field-effect transistors (CTFETs) using CFET technology for emerging technology nodes. As a prior work, the CTFET’s device-level simulations are implemented and deliberated in strict compliance with the experimental settings. This work comprises the study of physical and DC analyses by scaling the p- to n-CTFET separation (D pn), being a significant factor in CFET/CTFET design for its process difficulty. By utilizing the 50% benefit in footprint, the work is further extended to CTFET static random access memory implementation and characterization with hold/read noise margin analysis. © 2023 The Author(s). Published on behalf of The Japan Society of Applied Physics by IOP Publishing Ltd

关键词： Si-Ge alloys

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