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Super Compact UWB Monopole Antenna for Small IoT Devices

computers, Materials & Continua 2022年第11期73卷 2785-2799页

作者： Ahmed Jamal Abdullah Al-Gburi Zahriladha Zakaria Merih Palandoken Imran Mohd Ibrahim A.A.Althuwayb Sarosh Ahmad Samir Salem Al-Bawri Department of Electronics and Computer Engineering(FKEKK) Center for Telecommunication Research and Innovation(CeTRI)Universiti Teknikal Malaysia Melaka(UTeM)Durian Tungal76100Malaysia Department of Electrical and Electronics Engineering Izmir Katip Celebi UniversityIzmir35620Turkey Electrical Engineering Department Jouf UniversitySakaka72388AljoufKingdom of Saudi Arabia Universidad Carloa III de Madrid Leganes28911MadridSpain Space Science Centre Climate Change InstituteUniversiti Kebangsaan Malaysia(UKM)Bangi43600Malaysia

This article introduces a novel,ultrawideband(UWB)planar monopole antenna printed on Roger RT/5880 substrate in a compact size for small Internet of Things(IoT)*** total electrical dimensions of the proposed compact UWB antenna are 0.19λo×0.215λo×0.0196λo with the overall physical sizes of 15 mm×17 mm×1.548 mm at the lower resonance frequency of 3.8 *** planar monopole antenna is fed through the linearly tapered microstrip line on a partially structured ground plane to achieve optimum impedance matching for UWB *** proposed compact UWB antenna has an operation bandwidth of 9.53 GHz from 3.026 GHz up to 12.556 GHz at−10 dB return loss with a fractional bandwidth(FBW)of about 122%.The numerically computed and experimentally measured results agree well in between.A detailed time-domain analysis is additionally accomplished to verify the radiation efficiency of the proposed antenna design for the ultra-wideband signal *** fabricated prototype of a compact UWB antenna exhibits an omnidirectional radiation pattern with the low peak measured gain required of 2.55 dBi at 10 GHz and promising radiation efficiency of 90%.The proposed compact planar antenna has technical potential to be utilized in UWB and IoT applications.

关键词： Internet of things(IoT) ultra-wideband(UWB)application compact UWB monopole antenna

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Performance Evaluation of Coherent MIMO Radar Assisted with Space-Time Coding 9

Performance Evaluation of Coherent MIMO Radar Assisted with ...

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9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Barakat, Mohammed Elmogtaba Saeed, Rashid A. Barakat, Mohammed Edam, Salaheldin Khalifa, Othman O. Sudan University of Science and Technology School of Electronics Engineering Khartoum Sudan Taif University College of Computers and Information Technology Department of Computer Engineering P.O. Box 11099 Taif21944 Saudi Arabia International Islamic University Malaysia Dept. of Electrical and Computer Engineering Malaysia Libyan Center for Engineering Research and Information Technology Bani Waleed Libya

ISBN: (纸本)9798350325218

Using multiple-input multiple-output (MIMO) technology has revolutionized the radar field by providing higher resolution, improved target detection, and reduced interference. However, interrupting signals can significantly degrade the Performance of MIMO radar systems to transmit and receive signals simultaneously;MIMO radar systems employ multiple antennas at the transmitter and receiver. This allows for improved spatial resolution and increased target detection capabilities. However, MIMO radar systems are susceptible to fading and interference, degrading performance. STC is a technique to mitigate these effects by transmitting multiple signals simultaneously from different antennas. This article evaluates the performance of space-time coding (STC) with coherent multiple-input multiple-output (MIMO) radar. The paper investigates the impact of STC on the radar system's detection and estimation capabilities in various scenarios, including target detection in cluttered environments and target tracking in the presence of interference. The simulation results demonstrate that STC can significantly improve the radar system's performance by reducing interference effects and increasing the signal-to-noise ratio. Furthermore, the study shows that different STC schemes have varying degrees of effectiveness depending on the specific scenario. Overall, this research provides valuable insights into the potential benefits of using STC with coherent MIMO radar for various applications. © 2023 IEEE.

关键词： Target tracking

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research on Biomimetic Design Methods for Humanoid Robot Thigh

Research on Biomimetic Design Methods for Humanoid Robot Thi...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Nie, Daming Xie, Anhuan Kong, Lingyu Zhang, Yu Zheng, Gang Fu, Yili Gu, Jason Zhejiang Laboratory Intelligent Robot Research Center Hangzhou311100 China Zhejiang University of Science and Technology School of Mechanical and Energy Engineering Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxB3M 1A2 Canada

ISBN: (纸本)9798350325706

Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human's longest and strongest bone - the femur - as an example, it is consist of two characteristic layers, i.e. the substantia compacta and the substantia spongiosd. This article innovatively imitates the structural characteristics of human femur, the thigh of humanoid robot is designed in form of "variable thickness shell + variable density lattice". The thickness of shell and the density of lattice are adjusted by the initial stress distribution individually. Results show that the weight of shell and lattice of the thigh structure can be reduced by 20% under reasonable mapping relationship of "stress - shell thickness"and "stress - lattice rod diameter", while the structural stiffness meets the application requirements. Finally, the limiting factors of the "variable thickness shell + variable density lattice"structure designing approach are analyzed, and potential measures for optimizing the design method of the humanoid robot thigh in the future are described. © 2023 IEEE.

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A Hybrid EEG-EMG Framework for Humanoid Control using Deep Learning Transformers

A Hybrid EEG-EMG Framework for Humanoid Control using Deep L...

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IEEE International Conference on robotics and Biomimetics

作者： Parthan Olikkal Branesh M. Pillai Jackrit Suthakorn Habib Ali Ramana Vinjamuri Department of Computer Science and Electrical Engineering Vinjamuri lab University of Maryland Baltimore County Baltimore MD USA Center for Biomedical and Robotics Technology Mahidol University Salaya Nakorm Pathom Thailand

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Brain-computer interfaces (BCIs) offer promising solutions for upper limb rehabilitation. Despite advancements in deep learning, traditional models for motor rehabilitation using electroencephalography (EEG) or electromyography (EMG) to control assistive devices require enhancement. This study aims to enhance motor control capabilities by integrating EEG and EMG signals using a Transformer-based deep learning model. Ten able-bodies subjects performed center-out tasks on a low-cost upper limb rehabilitation table, capturing 2D kinematic data, EEG, and EMG signals simultaneously. The tasks varied in complexity across four levels. Preprocessed EEG and EMG signals were fused and given as input to the proposed model, which was evaluated using three performance metrics. Results showed that the EEG-EMG combined model achieved 87.27% accuracy across all the four levels. Furthermore, the model's output successfully controlled a humanoid robot to replicate similar movements. These findings highlight the efficacy of combined EEG-EMG data in improving accuracy and performance in BCI applications, advancing assistive technologies and neurorehabilitation interventions.

关键词： Deep learning Accuracy Humanoid robots Brain modeling Transformers Motors Electromyography Electroencephalography Data models Brain-computer interfaces

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Conceptual Design and Simulation of a BCF Swimming Soft Robotic Fish for Deep-Sea

Conceptual Design and Simulation of a BCF Swimming Soft Robo...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhang, Yanyan Ding, Menglong Zhu, Shiqiang Liang, Yiming Bai, Yunhe Xie, Keren Wan, Minhong Gu, Jason Li, Tiefeng Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H4R2 Canada Center for X-mechanics Zhejiang University Hangzhou310027 China Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Department of Engineering Mechanics Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781665481090

This work provides a design of a deep-sea soft robotic fish propelled by the body and/or caudal fin (BCF) mode. The robotic fish consists of a bionic fish head and a BCF propulsion body. To enhance the swimming performance of the first soft robot fish in the deep sea, the design combines the advantages of high efficiency in BCF propulsion with the large deformation angle of dielectric elastomers (DE) flexible joints. The connection of the bionic fish head and BCF is cast in one piece of silicone to achieve deep-sea pressure self-adaptation of the soft robotic fish. The swimming performance was simulated using the CFD method, and the BCF propulsion behaviors were analyzed to evaluate the design proposed. The design goal was verified through numerical calculation, and a further enhanced strategy for the thrust ability of the fish was presented as well. This work can provide a low-cost bionic soft robot fish solution for deep-sea exploration. © 2022 IEEE.

关键词： Conceptual design

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对流水平板上二次混合的三重扩散纳米流体的流体力学和流体磁学对比分析

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Journal of Central South University 2023年第8期30卷 2616-2626页

作者： KHALID Abdulkhaliq M-alharbi HINA Gul MUHAMMAD Ramzan SEIFEDINE Kadry ABDULKAFI Mohammed-saeed Mechanical Engineering Department College of EngineeringUmm Al-Qura UniversityMakkah 24382Sandi Arabia Department of Computer Science Bahria UniversityIslamabad 44000Pakistan Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman 346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Mathematics College of ScienceQassim UniversityBuraydah 51452Saudi Arabia

当两种不同密度和扩散速率的纳米流体混合时,会发生三重扩散和对流现象。本文主要目的是比较对流水平板上二次混合的三重扩散纳米流体的流体力学和流体磁学。文中建立的模型其他新特征考虑了可变导热系数和非线性热辐射热通量。该问题... 详细信息

当两种不同密度和扩散速率的纳米流体混合时,会发生三重扩散和对流现象。本文主要目的是比较对流水平板上二次混合的三重扩散纳米流体的流体力学和流体磁学。文中建立的模型其他新特征考虑了可变导热系数和非线性热辐射热通量。该问题由一组方程组成,借助MATLAB bvp4c包进行求解。为了使参数与相关剖面的影响可视化,给出了图形说明,并利用图表来评估关键参数变化是如何影响相关场及其相应的物理量。通过对盐1和盐2的Dufour参数的多次估计,可以推断出流体流速的波动。验证了流体动力流相对于流体磁流的优势。此外,还将特定情景下已发表的结果与当前研究结果进行了比较。

关键词：三重扩散纳米流体二次混合对流可变导热系数非线性热辐射

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Robot Path Planning via Neural-Network-Driven Prediction

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第3期3卷 451-460页

作者： Wang, Jiankun Liu, Jianbang Chen, Weinan Chi, Wenzheng Meng, Max Q.-H. Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen518055 China The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Hong Kong Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Suzhou215021 China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen518172 China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong999077 Hong Kong

This article presents a novel heuristic method named neural-network-driven prediction (NEED) for robot path planning problems. Different from classical heuristic methods, NEED is not designed for some specific environments, which can be applied to various environments. NEED has an encoder-decoder structure, which consists of three modules: convolutional neural network backbone, spatial pooling module, and decoder module. By learning from a number of successful path planning cases, NEED can learn to analyze the environment structure and predict the promising search region for the new path planning problem. This predicted region serves as a heuristic to guide the search direction of path planning algorithms. A series of simulation experiments are conducted to demonstrate that NEED significantly improves the algorithm performance on solving new path planning problems. Meanwhile, NEED can also be applied to highly dynamic environments since it can output the prediction results at a speed of over 100 Hz on a laptop. © 2020 IEEE.

关键词： Intelligent robots

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An Image Acquisition Scheme for Visual Odometry based on Image Bracketing and Online Attribute Control

An Image Acquisition Scheme for Visual Odometry based on Ima...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shuyang Zhang Jinhao He Bohuan Xue Jin Wu Pengyu Yin Jianhao Jiao Ming Liu Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong SAR China Thrust of Robotics and Autonomous Systems the Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Center for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science University College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Visual odometry (VO) system is challenged by complex illumination environments. Image quality and its consistency in the time domain directly determine feature detection and tracking performance, which further affect the robustness and accuracy of the entire system. In this paper, an image acquisition scheme with image bracketing patterns is proposed. Images with different exposure levels are continuously captured to sufficiently explore the scene under varying illumination. An attribute control method is designed to adjust image exposures within the brackets online. Gaussian process regression fits the relationship between image quality metric and exposure via image synthesis technique. The optimal exposures for the next bracket are obtained directly without attempts to ensure a quick response. Experiments show our acquisition system’s effectiveness and performance improvement for VO tasks in complex illumination scenes.

关键词： Image quality Measurement Image synthesis Lighting Gaussian processes Robustness Time-domain analysis

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The Development of Remotely Operated Underwater Vehicle for Plastic Waste Detection with Raspberry Pi 13

The Development of Remotely Operated Underwater Vehicle for ...

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13th International Physics Seminar 2024, IPS 2024

作者： Delina, M. Taryudi Amin, M.F. Hussaan, A.M. Trismidianto Arifin, F.I. Syah, S.M.I. Physics Department Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta13220 Indonesia Electrical Engineering Department Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta13220 Indonesia Department of Computer Science IQRA University Rd. Shaheed-e-Millat Sindh75500 Pakistan Center of Atmospheric Research and Technology National Research and Innovation Agency Bandung40173 Indonesia

Underwater Plastic waste has had a serious impact on the environment. Unfortunately, Detecting and collecting underwater plastic waste is still a challenge, especially in Indonesia because of its position in the water, and the water turbidity. In previous research, a computer algorithm for detecting underwater plastic waste has been developed with Yolov3. To improve the research, we developed a Remotely Operated Underwater Vehicle (ROUV) with Raspberry Pi through the research and Development (R&D) method. This ROUV is like a submarine that operates in the water and is integrated with a camera and computer algorithm to detect plastic waste. To get close to the real condition, we created an artificial water environment in a pond with various turbidity (from 20 to 200 Nephelometric Turbidity Unit). We use 30 pieces of plastic waste in several colors: white, red, black, and transparent. The plastic waste dipped in the water and was then detected by the ROUV camera. The result shows that the effective threshold for object detection is around 100 Nephelometric Turbidity Unit (NTU). Below 100 NTU, although the number of detected plastic images decreases as the turbidity increases, the visibility and contrast still allow for reasonably good object detection. The average confidence value for detection at turbidity levels below 100 NTU is 77%. At high turbidity conditions, the detection model may require adjustment or retraining with data that reflects those turbidity conditions. © Published under licence by IOP Publishing Ltd.

关键词： Remotely operated vehicles

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3D Facial Expressions through Analysis-by-Neural-Synthesis

3D Facial Expressions through Analysis-by-Neural-Synthesis

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： George Retsinas Panagiotis P. Filntisis Radek Daněček Victoria F. Abrevaya Anastasios Roussos Timo Bolkarr Petros Maragos Institute of Robotics Athena Research Center Maroussi Greece MPI for Intelligent Systems Tübingen Germany Institute of Computer Science (ICS) Foundation for Research & Technology - Hellas (FORTH) Greece School of Electrical & Computer Engineering National Technical University of Athens Greece

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

While existing methods for 3D face reconstruction from in-the-wild images excel at recovering the overall face shape, they commonly miss subtle, extreme, asymmetric, or rarely observed expressions. We improve upon these meth-ods with SMIRK (Spatial Modeling for Image-based Reconstruction of Kinesics), which faithfully reconstructs expres-sive 3D faces from images. We identify two key limitations in existing methods: shortcomings in their self-supervised training formulation, and a lack of expression diversity in the training images. For training, most methods employ differentiable rendering to compare a predicted face mesh with the input image, along with a plethora of additional loss functions. This differentiable rendering loss not only has to provide supervision to optimize for 3D face geom-etry, camera, albedo, and lighting, which is an ill-posed optimization problem, but the domain gap between ren-dering and input image further hinders the learning pro-cess. Instead, SMIRK replaces the differentiable rendering with a neural rendering module that, given the ren-dered predicted mesh geometry, and sparsely sampled pix-els of the input image, generates a face image. As the neural rendering gets color information from sampled im-age pixels, supervising with neural rendering-based reconstruction loss can focus solely on the geometry. Further it enables us to generate images of the input identity with varying expressions while training. These are then utilized as input to the reconstruction model and used as supervision with ground truth geometry. This effectively augments the training data and enhances the generalization for di-verse expressions. Our qualitative, quantitative and partic-ularly our perceptual evaluations demonstrate that SMIRK achieves the new state-of-the art performance on accurate expression reconstruction. For our method's source code, demo video and more, please visit our project webpage: https://***/smirk/.

关键词： Training Geometry Solid modeling Three-dimensional displays Accuracy Face recognition Training data

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