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2021 Research, Invention, and Innovation Congress: Innovation Electricals and electronics, RI2C 2021

作者： Chudpooti, Nonchanutt Sangpet, Patchadaporn Duangrit, Nattapong Akkaraekthalin, Prayoot Robertson, Ian D. Somjit, Nutapong King Mongkut's University of Technology North Bangkok Facutly of Appied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Deparment of Electrical and Computer Engineering Bangkok Thailand Rajamangala University of Technology Lanna Faculty of Engineering Chiangmai Thailand University of Leeds School of Electronic and Electrical Engineering Leeds United Kingdom

ISBN: (纸本)9781665403009

This paper presents a 3D-printed hemispherical lens integrated with flower-shaped stub antenna for liquid-mixture characterization. The proposed lens antenna is designed, fabricated, and integrated with the ultra-wideband planar antenna. A high impact polystyrene (HIPs) is selected to design the 3D-printed lens antenna by using the fused deposition modelling (FDM) technique, due to low loss 3D-printed material. The optimum the dimensions of the lens antenna are obtained by using the 3D EM Simulation CST Studio, which is used to investigate the performance of the antenna, e.g., gain, radiation pattern and reflection coefficient. To discriminate the liquid content in ethanol-water mixture, the level of the transmission coefficient (S21) is detected. The proposed sensor system offers various preferable features, e.g., non-destructive method and non-contact measurement. Five samples, e.g., 60%, 65%, 70%, 75%, and 80% ethanol in the ethanol-water mixtures, are measured and performed to generate the extraction model. The proposed sensor also offers other advantages, e.g., real-time monitoring and no life-cycle limitation. © 2021 IEEE.

关键词： Liquids

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An Enhanced Deep Super-Resolution Generative Adversarial Network Approach for Skin Disease Image Regeneration and Assessment

An Enhanced Deep Super-Resolution Generative Adversarial Net...

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electronic engineering (ICEEM), International Conference on

作者： Ibrahim Abd El-Fattah Taha E. Taha Walid El-Shafai Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department Electronics and Electrical Communications Engineering Alexandria Higher Institute of Engineering and Technology (AIET) Alexandria Egypt Computer Science Department Security Engineering Lab Prince Sultan University Riyadh Saudi Arabia

Skin cancer is a critical medical concern, posing significant challenges in accurate diagnosis. Algorithmic approaches have seen remarkable advancements across various occupations, including skin disease assessment. This study introduces a distinctive Improved Deep Super-Resolution Generative Adversarial Network (I_DSUR-GAN) methodology for regenerating low-resolution (LOR) skin disease images into super-resolution (SUR) format. Additionally, a modified SUR-dataset inspired by HAM10000 is presented for skin disease applications. The proposed approach incorporates a novel loss function design to provide supplementary information, facilitating the creation of high-quality SUR images. Experimental results demonstrate that our method outperforms existing approaches on the HAM10000 dataset. A comprehensive evaluation and employing sensitive metrics is conducted to assess the effectiveness, training periods, and memory requirements of the proposed framework. The outcomes reveal that the suggested model excels in restoring and identifying hue and texture compared to conventional and earlier models.

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LiNbO3/Si-Hybrid Slot-Waveguide Electro-Optical Modulator Designs for 1550 nm 26

LiNbO3/Si-Hybrid Slot-Waveguide Electro-Optical Modulator De...

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26th Microoptics Conference, MOC 2021

作者： Mercier, Thomas M. Charlton, Martin D. B. Tomita, Isao University Of Southampton Faculty Of Physical Science Engineering Sustainable Electronic Technologies Department Of Electronics And Computer Science SO17 1BJ United Kingdom National Institute Of Technology Gifu College Department Of Electrical And Computer Engineering Gifu501-0495 Japan

ISBN: (纸本)9784863487758

We investigate the performances of two slot-waveguide modulator designs using optical and electrical simulations. The proposed designs utilize high confinement Si slot waveguides in combination with LiNbO3 (LN). This allows for efficient modulation due to the strong Pockels effect of the LN and the strong electric field of the slot-waveguide. © 2021 Japan Society of Applied Physics.

关键词： Niobium compounds

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PAPR Reduction in MIMO-OFDM using Nonlinear Inertia Weight Factor of Whale Optimization Algorithm

PAPR Reduction in MIMO-OFDM using Nonlinear Inertia Weight F...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Mohammed I. Habelalmateen R Archana Reddy Chetana Reddy N. Nagarjuna Pradeep Kumar S Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Parit Raja Batu Pahat Johor Malaysia Department of Computer Technical Engineering College of Technical Engineering the Islamic University Najaf Iraq School of Computer Science and Artificial Intelligence SR University Telangana India Department of Electronics and Communication Oxford College of Engineering Bangalore Department of CSIT CVR College of Engineering Hyderabad India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India

In the landscape of optimization for mitigating the Peak-to-Average Power Ratio (PAPR) in Multiple-Input Multiple-Output and Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, prevalent techniques like the tone reservation scheme and l-norm Cyclic Algorithm (LNCA) algorithm grapple with inherent challenges linked to computational complexity and iterative algorithm derivation. While strides have been made with models such as Twin Symbol Hybrid Optimization by the premise of Partial Transmit Sequence (TSHO-PTS) and Advanced Switching Differential Evolution (ASDE), persistent concerns related to symbol overlaps and algorithmic limitations underscore the need for further refinement in computational efficiency within OFDM-based communication systems. In response to these challenges, the proposed Nonlinear Inertia Weight Factor within the Whale Optimization Algorithm (NIWF-WOA) emerges as a solution. Comparative analysis against existing methods like LCNA, Modified Dragonfly Optimization algorithm (MDOA), TSHO-PTS, and ASDE reveals the superior performance of NIWF-WOA. Numerical validation affirms its efficacy, with a recorded in Bit Error Rate (BER) of 10 −2.5 , SNR 10 −3.4 and PAPR of . 10 −4.2 , underscoring the substantial improvement achieved by NIWF-WOA in optimizing PAPR reduction for MIMO-OFDM systems.

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Flexible HTTP-based Video Adaptive Streaming for good QoE during sudden bandwidth drops

TechRxiv

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TechRxiv 2022年

作者： Hung, Nguyen Viet Nam, Pham Ngoc Huong, Truong Thu Chien, Trinh Dac Faculty of Information Technology East Asia University of Technology Viet Nam College of Engineering and Computer Science VinUniversity Hanoi Viet Nam School of Electrical and Electronic Engineering Hanoi University of Science and Technology Viet Nam

We have observed a boom in video streaming over the Internet, especially during the Covid-19 pandemic, that could exceed the network resource availability. In addition to upgrading the network infrastructure, finding a way to smartly adapt the streaming system to the network and users’ conditions to satisfy clients’ perceptions is exceptionally critical, too. This paper proposes a new QoE-aware adaptive streaming scheme over HTTP - ABRA - to make flexible adaptations based on the network and the client’s current status. Besides, we propose a technique that can keep the buffer at an average high for more than 10s. We were limiting the phenomena of rebuffering due to unexpected and unpredictable bandwidth changes. The algorithm keeps the quality of subsequent versions’ quality constant even when the average bitrate decreases, increasing the QoE. Experimental results show that our method can improve QoE from 7.86% to 20.41% compared to state-of-the-art methods. ABRA can provide better performance in terms of QoE score in all buffer conditions compared to the existing solutions while maintaining a minimum secured buffer level for the worst case. © 2022, CC BY.

关键词： HTTP

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Adaptive Fuzzy Sliding Mode Control With Logarithmic Sliding Surface for Active Suspension Systems

Adaptive Fuzzy Sliding Mode Control With Logarithmic Sliding...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Andika Aji Wijaya Fitri Yakub Winda Astuti Mahmud Iwan Solihin S. Syafiie Department of Mechanical Engineering University of Business and Technology (UBT) Jeddah Saudi Arabia Department of Electronic Systems Engineering University of Technology Malaysia (UTM) Kuala Lumpur Malaysia Department of Computer Engineering BINUS ASO School of Engineering Automotive and Robotics Program Bina Nusantara University (BINUS) Jakarta Indonesia Department of Mechanical and Mechatronics Engineering UCSI University Kuala Lumpur Malaysia Department of Chemical and Materials Engineering Faculty of Engineering-Rabigh King Abdulaziz University Jeddah Saudi Arabia

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This paper introduces a hybrid control strategy that integrates the unique features of natural logarithm sliding mode control (lnSMC) and fuzzy logic systems. The lnSMC control approach ensures that the vibration amplitude remains within a bound, as determined by the parameters of the lnSMC switching function. Furthermore, the fuzzy logic system is employed to approximate the nonlinearities and uncertainties inherent in the suspension system components, such as the spring and damper. The stability of the closed-loop system is analyzed using the Lyapunov stability theorem, guaranteeing convergence within a finite time. To validate the effectiveness of the proposed controller, a simulation study was carried out using a quarter-car suspension model, considering the system’s nonlinearities, parameter uncertainties, and various external disturbances. The results indicate that the proposed controller significantly improves ride comfort while maintaining suspension deflection and road holding within critical safety limits.

关键词： Fuzzy logic Vibrations Uncertain systems Uncertainty Roads Switches Stability analysis Vehicle dynamics Springs Sliding mode control

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Communication-Efficient Federated Learning in Channel Constrained Internet of Things

Communication-Efficient Federated Learning in Channel Constr...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Tao Hu Xinran Zhang Zheng Chang Fengye Hu Timo Hämäläinen School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyvaskyla Jyvaskyla Finland College of Communication Engineering Jilin University Changchun China

ISBN: (纸本)9781665435413

Federated learning (FL) is able to utilize the computing capability and maintain the privacy of the end devices by collecting and aggregating the locally trained learning model parameters while keeping the local personal data. As the most widely-used FL framework,Jederated averaging (FedAvg) suffers an expensive communication cost especially when there are large amounts of devices involving the FL process. Moreover, when considering asynchronous FL, the slowest device becomes the bottleneck for the cask effect and determines the overall latency. In this work, we propose a communication-efficient federated learning framework with partial model aggregation (CE-FedPA) algorithm to utilize compression strategy and weighted device selection, which can significantly reduce the size of uploaded data and decrease the communication time. We perform a series of experiments on the MNIST/CIFAR-10 datasets, in both lID and non-lID data settings. We compare the communication time of different aggregation schemes, in terms of iteration rounds and target accuracy. Simulation results demonstrate that the uploading time of the proposed scheme is up to 4.3 times shorter than other existing ones. Experiments on an end - to-end FL framework also verify the communication efficiency of CE-FedPA in a real-world setting.

关键词： Performance evaluation Training Data privacy Costs Federated learning Simulation Data integrity

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AoI-Aware Spectrum and Power Allocation for High-Speed Railway Networks

AoI-Aware Spectrum and Power Allocation for High-Speed Railw...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Difei Jia Fengye Hu Zhuang Ling Zhi Mao Zheng Chang Timo Hämäläinen College of Communication Engineering Jilin University School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland

ISBN: (纸本)9781665450867

This paper studies a high-speed railway (HSR) network, where train-to-infrastructure (T2I) and train-to-train (T2T) transmissions co-exist. First, we analyze the age of information (AoI) of the T2T link to capture the freshness of data. Then, with the objective to maximize the sum data rate of T2I links, we formulate a resource allocation optimization problem subject to the data rate constraint of T2I links and the average AoI constraint of T2T links. Since the formulated problem has coupled optimizing variables and non-convex structure, we propose an AoI-aware spectrum and power allocation (AoI-ASPA) scheme to address it. In the proposed scheme, the optimization problem is decomposed into a power allocation subproblem and a spectrum allocation subproblem, and solved in two steps. For the power allocation subproblem, the optimal power allocation solution for each spectrum reusing pair is derived in an algebraic method. For the spectrum allocation subproblem, we transform it into a weighted bipartite matching problem and solve it by using the Kuhn-Munkres (KM) method. Simulation results verify the effectiveness of our proposed scheme.

关键词： Wireless communication Simulation Quality of service Transforms Interference Signal processing Rail transportation

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High-Resolution Optical Imaging Incorporated Non-Destructive Morphological Boundary Detection of Fruit Disorders: A Pilot Study

High-Resolution Optical Imaging Incorporated Non-Destructive...

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Advancements in Computing (ICAC), International Conference on

作者： Nethmi Tharushi Hakmana Nipun Shantha Kahatapitiya Sasmitha Weerasinghe Deshan Kalupahana Bhagya Nathali Silva Naresh Kumar Ravichandran Daewoon Seong Sangyeob Han Seung Yeol Lee Hee-Young June Mansik Jeon Jeehyun Kim Udaya Wijenayake Ruchire Eranga Wijesinghe Department of Mechanical Engineering Faculty of Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Engineering Faculty of Engineering University of Sri Jayewardenepura Nugegoda Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Center for Excellence in Informatics Electronics & Transmission (CIET) Sri Lanka Institute of Information Technology Malabe Sri Lanka Center for Scientific Instrumentation Korea Basic Science Institute Daejeon Republic of Korea School of Electronic and Electrical Engineering College of IT Engineering Kyungpook National University Daegu Republic of Korea ICT Convergence Research Center Kyungpook National University Daegu Republic of Korea Department of Plant Medicine Kyungpook National University Daegu Republic of Korea Institute of Plant Medicine Kyungpook National University Daegu Republic of Korea Department of Electrical and Electronic Engineering Faculty of Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Plant diseases caused by various pathogens, such as fungi, bacteria, and viruses, lead to significant reductions in crop yield and quality. Early detection of these diseases is critical for preventing their spread and optimizing crop yield. Traditional methods of disease detection, while effective, often involve invasive or time-consuming procedures that may not provide real-time insights. This study investigates the use of Swept-Source Optical Coherence Tomography (SS-OCT) for non-destructive, high-resolution imaging to identify morphological abnormalities in fruit specimens affected by diseases. The research focuses on differentiating healthy regions, healthy boundaries, infected boundaries, and fully infected regions in apples. Using a 1310 nm center wavelength laser, the SS-OCT system captured detailed cross-sectional images of fruit tissue, revealing microstructural changes associated with disease progression. A qualitative assessment of the two-dimensional (2D) OCT images highlighted distinct layers in healthy tissues, noticeable structural deformities, and the merging of microstructural layers in the boundary and infected regions. Quantitative depth-profile analysis of axial-direction A-scan profiles further demonstrated the reduction and merging of intensity peaks correlating with tissue abnormalities in infected fruit specimens. These findings underscore the potential of SS-OCT as an effective tool for early disease detection in agricultural products, providing a means for timely intervention and optimized postharvest management.

关键词： Plant diseases Pathogens Statistical analysis Two-dimensional displays Merging High-resolution imaging Optical imaging Real-time systems Crop yield Diseases

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Generative technology for Human Emotion Recognition: A Scope Review

SSRN

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SSRN 2024年

作者： Ma, Fei Yuan, Yucheng Xie, Yifan Ren, Hongwei Liu, Ivan He, Ying Ren, Fuji Yu, Fei Richard Ni, Shiguang Shenzhen China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Guangzhou China Department of Psychology Faculty of Arts and Sciences Beijing Normal University at Zhuhai Zhuhai China College of Computer Science and Software Engineering Shenzhen University Shenzhen China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

Affective computing stands at the forefront of artificial intelligence (AI), seeking to imbue machines with the ability to comprehend and respond to human emotions. Central to this field is emotion recognition, which endeavors to identify and interpret human emotional states from different modalities, such as speech, facial images, text, and physiological signals. In recent years, important progress has been made in generative models, including Autoencoder, Generative Adversarial Network, Diffusion Model, and Large Language Model. These models, with their powerful data generation capabilities, emerge as pivotal tools in advancing emotion recognition. However, up to now, there remains a paucity of systematic efforts that review generative technology for emotion recognition. This survey aims to bridge the gaps in the existing literature by conducting a comprehensive analysis of over 320 research papers until June 2024. Specifically, this survey will firstly introduce the mathematical principles of different generative models and the commonly used datasets. Subsequently, through a taxonomy, it will provide an in-depth analysis of how generative techniques address emotion recognition based on different modalities in several aspects, including data augmentation, feature extraction, semi-supervised learning, cross-domain, etc. Finally, the review will outline future research directions, emphasizing the potential of generative models to advance the field of emotion recognition and enhance the emotional intelligence of AI systems. © 2024, The Authors. All rights reserved.

关键词： Emotion Recognition

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