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A metasurface-based light-to-microwave transmitter for hybrid wireless communications

Light(science & Applications) 2022年第6期11卷 1139-1148页

作者： Xin Ge Zhang Ya Lun Sun Bingcheng Zhu Wei Xiang Jiang Qian Yu Han Wei Tian Cheng-Wei Qiu Zaichen Zhang Tie Jun Cui State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University210096 NanjingChina National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University210096 NanjingChina Frontiers Science Center for Mobile Information Communication and Security Southeast University210096 NanjingChina Purple Mountain Laboratories 211111 NanjingChina Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

Signal conversion plays an important role in many applications such as communication,sensing,and *** signal conversion between optical and microwave frequencies is a crucial step to construct hybrid communication systems that combine both optical and microwave wireless technologies to achieve better features,which are highly desirable in the future wireless ***,such a signal conversion process typically requires a complicated relay to perform multiple operations,which will consume additional hardware/time/energy ***,we report a light-to-microwave transmitter based on the time-varying and programmable metasurface integrated with a high-speed photoelectric detection circuit into a *** a transmitter can convert a light intensity signal to two microwave binary frequency shift keying signals by using the dispersion characteristics of the metasurface to implement the frequency division *** illustrate the metasurface-based transmitter,a hybrid wireless communication system that allows dual-channel data transmissions in a light-to-microwave link is demonstrated,and the experimental results show that two different videos can be transmitted and received simultaneously and *** metasurface-enabled signal conversion solution may enrich the functionalities of metasurfaces,and could also stimulate new information-oriented applications.

关键词： microwave surface light

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A Review on the need of Clustering Techniques Used for Wireless Sensor Networks 2

A Review on the need of Clustering Techniques Used for Wirel...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Bharany, Salil Rehman, Ateeq Ur Tariq Sadiq, M. Farrukh, Muhammad Alharbi, Meshal Hussain, Amjad Issa, Ghassan F. CET and Technology Department Amritsar India Government College University Department of Electrical Engineering Lahore Pakistan University of Brighton School of Architecture & Engineering United Kingdom Minhaj University Department of Computer Science Lahore Pakistan Prince Sattam Bin Abdulaziz University College of Computer Engineering and Sciences Department of Computer Science Alkharj11942 Saudi Arabia School of Computer Science NCBA&E Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan Skyline University College School of Information Technology Sharjah United Arab Emirates

ISBN: (纸本)9798350335644

Wireless sensor networks have been implemented in various software to help gather and analyze data from the physical world. Wireless sensor networks are networks of multiple tiny sensors powered by low-energy batteries (WSNs). WSN lifetime is a critical factor. This is because, after WSNs have been deployed in a given application, the inaccessibility of the sensing nodes makes it impossible to recharge or replace the power source that is limited in energy. Until recently, WSNs were thought to be the same. All the network nodes have the same power, processing speed, and operational capacity. However, scientists have developed heterogeneous WSNs, in which the properties of individual nodes may vary, to extend the lifespan of networks. In order to extend a network's helpful life, energy-efficient protocols must be designed. Even though WSN has its own problems, it has brought a fresh perspective to studying real-time intelligent systems. WSN (Wireless Sensor Network) has gained significant popularity in the recent years, owing to its vast applications in real-time scenarios, such as disaster management, pollution monitoring, temperature monitoring, traffic monitoring, transport monitoring, healthcare monitoring, battlefield monitoring, and border security surveillance, to name a few. Numerous sensor nodes are employed in these applications. They are typically placed in the sensing field, where they automatically transfer data to the base station (BS) through energy transmission (i.e., battery in the sensor). In WSN, clustering is one method for optimizing power consumption at the sensor node. The sensor nodes are grouped and given a leader when they undergo clustering. This study overviews various WSN clustering algorithms, each categorized according to various clustering properties. © 2023 IEEE.

关键词： Sensor nodes

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不可逆分析法研究受磁偶极子影响的Ree-Eyring纳米流体流动多相催化作用

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Journal of Central South University 2023年第7期30卷 2324-2339页

作者： Seemab BASHIR Muhammad RAMZAN Seifedine KADRY C Ahamed SALEEL Department of Mathematics Air UniversityIslamabad44000Pakistan Department of Computer Science Bahria UniversityIslamabad44000Pakistan Department of Mathematics and Computer Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Mechanical Engineering College of EngineeringKing Khalid UniversityAsir-Abha61421Saudi Arabia

Ree-Eyring流体是一种非牛顿流体,具有屈服应力和剪切稀化的特点,比如乳剂、浆体和聚合物溶液。根据Ree-Eyring流体的特性,通过考虑不均匀的产热/吸收效应和黏性耗散效应,以及分析传热现象来研究磁偶极子作用下表面拉伸纳米流体的流动... 详细信息

Ree-Eyring流体是一种非牛顿流体,具有屈服应力和剪切稀化的特点,比如乳剂、浆体和聚合物溶液。根据Ree-Eyring流体的特性,通过考虑不均匀的产热/吸收效应和黏性耗散效应,以及分析传热现象来研究磁偶极子作用下表面拉伸纳米流体的流动行为。所建立模型考虑了对流条件下边界表面的熵产生,将偏微分方程组(PDEs)充分变换转换为耦合常微分方程组(ODEs),采用MATLAB bvp4c法进行数值计算,并以图表形式显示计算结果。结果表明,随着Brinkman数的变化,不可逆性产生率激增。此外,当热泳参数最小化时,边界附近的温度降低,而在远离边界处温度上升。表面催化参数减弱了溶质的分布,模型得到了验证。

关键词： Ree-Eyring纳米流体磁偶极子多相催化熵产生

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Signal Quality Prediction for Cognitive Radio Networks using Deep Learning Techniques 15

Signal Quality Prediction for Cognitive Radio Networks using...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dev, Sudhanshu Santhoshkumar, M.P. Goyal, Udita Raja Praveen, K.N. Pathak, Kishor R. Ravivarman, G. Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Computer Science and Engineering Karnataka Bangalore India Vishwakarma Institute of Technology Department of Information Technology Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India

ISBN: (纸本)9798350370249

Cognitive radio networks (CRNs) are getting increasingly famous due to their potential to deliver excessive-bandwidth offerings to numerous users. Despite this, the signal satisfactory of those networks can be fantastically variable and hard to predict, leading to degraded communication. Currently, deep gaining knowledge of strategies had been proposed as a method to improve the capability of CRNs to correctly expect signal first-rate, allowing multiplied device reliability. On this paper, we gift an assessment of present deep gaining knowledge of tactics to be expecting signal excellent in CRNs, focusing at the structure and application of convolutional neural networks (CNNs), recurrent neural networks (RNNs) and deep reinforcement studying (DRL). The overview additionally examines the overall performance of those processes in terms of accuracy, scalability and generalization to new environments. Subsequently, we provide a survey of capability future guidelines for signal first-rate prediction in CRNs using deep getting to know. © 2024 IEEE.

关键词： Deep reinforcement learning

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View DiffGait: View Pyramid Diffusion for Gait Recognition

View DiffGait: View Pyramid Diffusion for Gait Recognition

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International Conference on Automatic Face and Gesture Recognition

作者： Rijun Liao Zhu Li Shuvra S. Bhattacharyya George York Department of Computer Science and Electrical Engineering University of Missouri-Kansas City MO USA Department of Electrical and Computer Engineering and UMIACS University of Maryland College Park MD USA Department of Electrical and Computer Engineering and UAS Research Center US Air Force Academy Colorado Springs CO USA

ISBN: (数字)9798350394948

ISBN: (纸本)9798350394955

View transformation is crucial for gait recognition. Most existing methods use a view transformation models (VTM) or generative models (VAE or GAN) to achieve transformation. These approaches commonly adopt a paradigm of transforming a gait feature from one view to another. However, most existing methods attempt to use a single or multiple, large-view transformation model to directly transform a source view image to the target view image. Such transformations usually suffer from precision problems under large viewpoint variations due to the lack of fine view prediction. To overcome this challenge, we introduce a novel framework, ViewDiffGait, employing a view pyramid structure and diffusion models. ViewDiffGait is formulated as an iterative refinement generation task in a biologically interpretable way, capable of generating more accurate lateral view images from coarse to fine. Unlike the typical diffusion model that directly adds and removes Gaussian noise in the original image, the ViewDiffGait diffusion process involves a view pyramid structure to capture fine view transformations. The diffusion process adds view noise from the pyramid top to the bottom, while the denoising process removes view noise from the pyramid bottom to the top. We conducted extensive experiments on the CASIA-B and OUMVLP datasets, demonstrating that ViewDiffGait can generate more realistic images, remove variations effectively, and lead to high performance in real applications.

关键词： Face recognition Gaussian noise Noise reduction Diffusion processes Transforms Gesture recognition Diffusion models

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Mini-InternVL: a flexible-transfer pocket multi-modal model with 5% parameters and 90% performance

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Visual Intelligence 2024年第1期2卷 1-17页

作者： Gao, Zhangwei Chen, Zhe Cui, Erfei Ren, Yiming Wang, Weiyun Zhu, Jinguo Tian, Hao Ye, Shenglong He, Junjun Zhu, Xizhou Lu, Lewei Lu, Tong Qiao, Yu Dai, Jifeng Wang, Wenhai Shanghai AI Laboratory Shanghai 200232 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Computer Science Nanjing University Nanjing 210023 China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen 518055 China School of Computer Science Fudan University Shanghai 200433 China SenseTime Research Shanghai 200233 China Department of Electronic Engineering Tsinghua University Beijing 100084 China Beijing National Research Center for Information Science and Technology Department of Automation Tsinghua University Beijing 100084 China Department of Information Engineering The Chinese University of Hong Kong 999077 Hong Kong

Multi-modal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a wide range of domains. However, the large model scale and associated high computational cost pose significant challenges for training and deploying MLLMs on consumer-grade GPUs or edge devices, thereby hindering their widespread application. In this work, we introduce Mini-InternVL, a series of MLLMs with parameters ranging from 1 billion to 4 billion, which achieves 90% of the performance with only 5% of the parameters. This significant improvement in efficiency and effectiveness makes our models more accessible and applicable in various real-world scenarios. To further promote the adoption of our models, we are developing a unified adaptation framework for Mini-InternVL, which enables our models to transfer and outperform specialized models in downstream tasks, including autonomous driving, medical image processing, and remote sensing. We believe that our models can provide valuable insights and resources to advance the development of efficient and effective MLLMs. © The Author(s) 2024.

关键词： Knowledge distillation Lightweight multi-modal large language model Vision-language model Visual instruction tuning

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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System

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Intelligent Automation & Soft Computing 2023年第11期38卷 169-183页

作者： Laith Abualigah Serdar Ekinci Davut Izci Raed Abu Zitar Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Computer Engineering Batman UniversityBatman72100Turkey MEU Research Unit Middle East UniversityAmmanJordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and *** study proposes a novel approach for designing a fractional order proportional-integral-derivative(FOPID)controller that utilizes a modified elite opposition-based artificial hummingbird algorithm(m-AHA)for optimal parameter *** approach outperforms existing optimization techniques on benchmark functions,and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and *** study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and *** highlight the significance of our findings by demonstrating how our approach can improve the performance,safety,and reliability of autonomous *** study’s contributions are particularly relevant in the context of the growing demand for autonomous vehicles and the need for advanced control techniques to ensure their safe *** research provides a promising avenue for further research and development in this area.

关键词： Cruise control system FOPID controller artificial hummingbird algorithm elite opposition-based learning

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Maximizing Harvested Energy in Natural Energy Powered RF WPT with Nonlinear EH Model

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IEEE Transactions on Wireless Communications 2025年

作者： Zhang, Xiang Xiong, Ke Chen, Wei Fan, Pingyi Gao, Bo Letaief, Khaled Ben Collaborative Innovation Center of Railway Traffic Safety School of Computer Science and Technology Engineering Research Center of Network Management Technology for High Speed Railway Ministry of Education China Beijing Jiaotong University National Engineering Research Center of Advanced Network Technologies Beijing100044 China Department of Electronic Engineering China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China Department of Electrical and Computer Engineering Hong Kong Hong Kong

In the typical radio frequency (RF)-based wireless power transfer (WPT) system, the wireless power station (WPS) connected to the grid transmits energy to charge low-power sensors via radio signals. Such a system may not be green and also difficult to deploy in some special areas including deserts and mountainous areas, because it depends on the grid. To achieve a green RF WPT system design, this paper considers that the WPS is powered by natural energy sources rather than the grid. To explore the maximal total amount of the energy that can be harvested by the sensors, we focus on the offline setting, so similar to many existing works on offline optimization, we assume that the WPS knows prior knowledge about energy arrivals and channel changes, and then formulate an optimization problem to maximize the total harvested energy via optimizing the WPS's time-domain transmit power subject to multiple constraints, including the finite battery capacity at the WPS, the causal relationship between the natural energy harvesting and the WPT, and the transmit power budget of the WPS, where for practicality, the nonlinear energy harvesting (EH) model is also taken into account. To solve this non-convex problem, we first equivalently transform it by using the epigraph reformulation and the variable substitution, and then use the first-order Taylor expansion to get an approximate convex version. Then, we present a successive convex approximation (SCA)-based algorithm to improve the accuracy of the obtained solution for approaching the optimal one. For the special case with a single sensor, we further propose a branch and bound (BB)-based algorithm that is able to get a more accurate solution with lower complexity than the SCA-based one. Numerical results demonstrate that the proposed algorithms are able to achieve the near-global optimal solution. As the average recharge rate increases, compared with the other two baselines, i.e., the greedy power (GP) policy and the constant pow

关键词： Budget control

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Measurement of Synthetic-Dimension Band Structures in Silicon Coupled Ring Resonators 16

Measurement of Synthetic-Dimension Band Structures in Silico...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Zhang, Ruming Li, Liucun Kamata, Mikiya Baba, Toshihiko Ozawa, Tomoki Ota, Yasutomo Iwamoto, Satoshi Research Center for Advanced Science and Technology The University of Tokyo Tokyo153-8904 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan Keio University Department of Applied Physics and Physico-Informatics Yokohama223-8533 Japan

We fabricated integrated silicon coupled-ring resonators and measured photonic band structures for synthetic frequency lattices with different configurations. A phase difference between two modulation signals introduc... 详细信息

ISBN: (纸本)9798350372076

关键词： Silicon photonics

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Ubicon-BP: Towards Ubiquitous, Contactless Blood Pressure Detection Using Smartphone

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IEEE Transactions on Mobile Computing 2025年

作者： Wu, Yuan Bai, Shoudu Hu, Qingyong Wang, Bo Li, Min Hu, Xinrong Chen, Yanjiao Wuhan Textile University School of Computer Science and Artificial Intelligence Engineering Research Center of Hubei Province for Clothing Information Wuhan430200 China Hong Kong University of Science and Technology Department of Computer Science and Engineering China Wuhan University School of Electrical Engineering Wuhan430072 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

Blood pressure (BP) is a critical physiological parameter closely associated with severe diseases such as heart failure and kidney damage. Current methods either require additional or dedicated hardware, or closing touching to the devices, causing discomfort and inconvenience. Therefore, a convenient, contactless BP measurement solution is highly desired. In this work, we present Ubicon-BP, a ubiquitous, device-free, and contactless BP detection application. Ubicon-BP calculates BP based on the pulse transit time (PTT), a key feature that is medically proven correlated with BP. However, using smartphone sensors to contactless calculate PTT is non-trivial since it requires a micro-second level precision for cardiac event detection. To address this issue, we propose leveraging the acoustic sensors in smartphone to detect vibrations caused by heart valve movements, as well as camera sensors to measure finger pulses. To accurately measure heartbeat signal that are susceptible to motion, we first improve the sensing granularity of acoustic signals and then introduce the IQ-MVED model to eliminate motion interference. Furthermore, when recovering pulse signals from video signals, issues such as poor generalization performance arise. Consequently, we propose the TS-CAN and meta-learning models to obtain personalized pulse signals. Finally, we transform the extracted time-frequency features from the recovered heartbeats and pulse signals to the corresponding BP. Comprehensive testing involving 50 subjects reveal a standard deviation error of 4.27mmHg for diastolic pressure and 6.36mmHg for systolic pressure, respectively. © 2025 IEEE. All rights reserved.

关键词： Blood pressure

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