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

作者： Ming, Na Fan, Shuzhen Zhang, Xingyu Chen, Xiaohan Cong, Zhenhua Liu, Zhaojun Guo, Quanxin Guo, Liyuan Jiao, Binzhe Yuan, Jiasheng Wang, Kaiyu Liu, Naichang Center for Optics Research and Engineering Key Laboratory of Laser and Infrared System Ministry of Education Shandong University Qingdao266237 China School of Information Science and Engineering Shandong Provincial Key Laboratory of Laser Technology and Application Shandong University Qingdao266237 China

Highly sensitive terahertz frequency upconversion detection was demonstrated with a KTiOAsO4 crystal. The detectable THz frequency ranges were 3.6-3.9, 4.2-4.4, and 4.8-5.0 THz. The minimum detectable terahertz energy...

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A Novel Quadcopter Drone Simulation Platform Based on Mixed Reality 43

A Novel Quadcopter Drone Simulation Platform Based on Mixed ...

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43rd Chinese Control Conference, CCC 2024

作者： Huang, Jian Zhao, Jun Chen, Xiaohua Sichuan University of Science and Engineering Yibin644000 China Sichuan Key Laboratory of Artificial Intelligence Yibin644000 China Chongqing Weiminghui Information Technology Company Chongqing401320 China

ISBN: (纸本)9789887581581

Virtual simulations are characterized by repeatability and the allowance for experimentation and training without real risks. The increasing importance of virtual simulation in teaching and engineering has made it a research hotspot. The main motivation of this paper is the application of mixed reality technology to virtual simulation. A quadcopter drone simulation platform based on mixed reality for the simulation of quadcopter drones is designed in this article. The development of the platform is based on Unity. After the 3D model of the quadcopter drone is created, the file is imported into Unity and used as a prefabricated body. The flight control of this quadcopter drone is based on a discrete kinematics model where MATLAB is used as the controlling end to make the quadcopter drone fly along a reference trajectory. It is proposed in this article to use Vuforia to scan and model the flight environment using its designated 3D modeling equipment, which will reduce the collision blind spots of quadcopter drones during simulated flight. A simulated flight of a quadcopter drone in mixed reality can be realized by deploying the application to HoloLens2 through Visual Studio. This simulation device is portable and provides an immersive experience, but the collision interaction experience of real aircraft flight is not reduced at all, and the risk of damage to real machines can also be reduced. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： MATLAB

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A simulation research method for data injection attacks on DC microgrids

A simulation research method for data injection attacks on D...

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2024 China Automation Congress, CAC 2024

作者： Hou, Yunhui Liu, Mengxiang Shen, Na National Key Laboratory of Transient Physics Nanjing University of Science and Technology Nanjing China Department of Automatic Control and Systems Engineering University of Sheffield Western Bank Sheffield United Kingdom

ISBN: (纸本)9798350368604

By using Typhoon HIL simulator, a simulation research method of data injection attack against secondary control DC microgrid is established, which reveals the important influence of the attack function on the effectiveness and covertness of the attack. Firstly, a decentralized four-node DC microgrid system using TCP/IP Modbus protocol for communication is built in Typhoon HIL simulator, then, a microgrid security testing experimental platform based on the man-in-the-middle attack as a network attack method is built in Kali Linux system, which can carry out timed single- and multilinks data injection attacks and replay attack on the above four-node DC microgrid. The paper designs a variety of data injection attack schemes to study the impact of data injection attacks on voltage and current control in this DC microgrid, including single-link attack, multi-link composite attack, and replay attack using different attack functions. By controlling the main parameters of the attack function, the amplitude of the fluctuation of the output voltage generated by the attack can be controlled, which can produce a more covert and effective attack effect. © 2024 IEEE.

关键词： DC microgrids False data injection attack Man-in-the-middle attack Power grid cyber security Replay attack

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A variable structure model of neurons’ application in computer vision

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Multimedia Tools and Applications 2025年 1-11页

作者： Sridi, Alaeddine Attia, Mouna Bouallegue, Kais Electronics and Micro-Electronics Laboratory Faculty of Sciences of Monastir University of Monastir Monastir Tunisia The Higher Institute of Computer Science and Communication Technologies of Hammam Sousse University of Sousse Sousse Tunisia Laboratory of Computer Science Parallelism and Intelligent Communicating Systems Faculty of Sciences of Tunisia University of Tunis ELManar Tunis Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia

The neuron doctrine defines the neuron as the basic unit of the nervous system, which drives the dynamic behavior of our organs. This has led to neurons becoming the focus of modern neuroscience research and to the rise of neurocomputing, in which we try to digitally simulate human behavior. The goal being to better understand the human nervous system and gain more control over neuron-related diseases, helping doctors establish faster and more reliable medical diagnoses. In this context, we aim to simulate eye diseases and vision problems by convolving input images using a new class of neural networks based on a variable structure model of neurons presented in [1]. In this work, we focus on recreating the common convolution filters as a first step. This is the first time in neurocomputing literature that dendritic neurons have been used for dynamic convolution kernels generation and eye diseases simulation. We start with a presentation of our upgrades to the model’s flexibility and accuracy. Then, we propose a novel kernel generator algorithm to convolve the input images. Finally, we show its promising results in creating the outline, pixelization, and night convolution kernels, as well as control some metrics, including brightness and data retention. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Neurons

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Image Captioning with Reinforcement Learning 2

Image Captioning with Reinforcement Learning

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2nd IEEE International Conference on Computer Vision and Machine Intelligence, CVMI 2023

作者： Verma, Anand Agarwal, Saurabh Arya, K.V. Petrlik, Ivan Esparza, Roberto Rodriguez, Ciro ABV-IIITM Gwalior Department of Information Technology Madhya Pradesh 474015 India ABV-Indian Institute of Information Technology and Management Multimedia and Information Security Research Group Department of Computer Science and Engineering Gwalior474015 India National University Federico Villarreal Faculty of Industrial and Systems Engineering Lima Peru National University Mayor de San Marcos Faculty of Systems Engineering and Informatics Peru

ISBN: (纸本)9798350305142

Image captioning involves generating a natural language description that accurately represents the content and context of an image. To achieve this, image captioning utilises various machine learning techniques and fields, such as computer vision and natural language processing. In the field of image captioning, a lot of advances have been made with encoder-decoder models and reinforcement learning algorithms. However, there are still problems of imbalance between testing and training, as reinforcement learning only handles single comparator metrics such as CIDEr, SPICE, and BLEU and could not perform better in multiple metrics at once. Which is why a lack of diversity can be seen in generated captions. This idea proposes a general technique for collaborative updating that can bridge the gap between evaluation measures and test metrics to produce captions that are more human-like. To increase the precision of image captions, the approach involves using a compiled reward system that considers multiple evaluation metrics to compare the generated sentence with the provided sentences. We will evaluate the model's performance and the reward updating process on standard datasets like MS COCO. © 2023 IEEE.

关键词： Reinforcement learning

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Analysis and Control for Synchronization of Coupled Reaction-Diffusion Neural Networks with Multistate Couplings Subject to Recoverable Attacks 13

Analysis and Control for Synchronization of Coupled Reaction...

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13th IEEE International Conference on CYBER technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Zhao, Xin-Yu Ren, Shun-Yan Wang, Jin-Liang School of Computer Science and Technology Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tianjin300387 China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan611731 China

ISBN: (纸本)9798350315196

This paper addresses the synchronization for coupled reaction-diffusion neural networks (CRNNs) with multi-state couplings suffering attacks. By utilizing the Kronecker product, a network synchronization criterion is formulated. Moreover, since networks suffering attacks may not be synchronized in some circumstances, a simple controller is also developed. Finally, the effectiveness of the devised control schemes is verified through a numerical example. © 2023 IEEE.

关键词： Synchronization

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Neuro-symbolic artificial intelligence: a survey

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Neural Computing and Applications 2024年第21期36卷 12809-12844页

作者： Bhuyan, Bikram Pratim Ramdane-Cherif, Amar Tomar, Ravi Singh, T.P. LISV Laboratory University of Paris Saclay 10-12 Avenue of Europe Velizy78140 France School of Computer Science University of Petroleum and Energy Studies Uttarakhand Bidholi Dehradun248006 India Persistent Systems Pune Mumbai411016 India School of Computer Science Engineering and Technology Bennett University Greater Noida201306 India

The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop AI systems with more human-like reasoning capabilities by combining symbolic reasoning with connectionist learning. We survey the literature on neuro-symbolic AI during the last two decades, including books, monographs, review papers, contribution pieces, opinion articles, foundational workshops/talks, and related PhD theses. Four main features of neuro-symbolic AI are discussed, including representation, learning, reasoning, and decision-making. Finally, we discuss the many applications of neuro-symbolic AI, including question answering, robotics, computer vision, healthcare, and more. Scalability, explainability, and ethical considerations are also covered, as well as other difficulties and limits of neuro-symbolic AI. This study summarizes the current state of the art in neuro-symbolic artificial intelligence. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Machine learning

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A Dual-Band Dual-Polarized Antenna With High Aperture Reuse Efficiency and Large Frequency Ratio for Modern Wireless Communications

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IEEE Antennas and Wireless Propagation Letters 2024年第1期23卷 14-18页

作者： Zhao, Yue Ge, Lei Gu, Hui Chen, Shi Chang Chung, Ming-An Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen518060 China Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Hangzhou Dianzi University Key Laboratory of Rf Circuits and Systems of the Ministry of Education of China Microelectronic Cad Center Hangzhou310018 China National Taipei University of Technology Department of Electronic Engineering Taipei10608 Taiwan

In this letter, a microwave dense dielectric patch antenna and a millimeter-wave (MMW) Fabry-Perot cavity (FPC) antenna are first combined to implement a dual-band dual-polarized antenna with high aperture reuse efficiency and large frequency ratio. In the proposed design, a piece of high-permittivity dielectric and a metallic patch are adopted as not only the radiators of the microwave antenna but also the partially reflective surface and ground plane of the MMW FPC. Furthermore, for performance improvement, the high-permittivity dielectric is sharpened to widen the FPC gain bandwidth, a neutralization line is used to enhance the polarization isolation, and two small capacitive disks are employed to improve the channel isolation. As a demonstration, the proposed antenna is designed at 3.5 and 27 GHz. A prototype is fabricated and achieves 20% bandwidth (VSWR 30 dB) with 8 dBi gain in the low band, 22% bandwidth (VSWR24 dB) with 19.9 dBi gain in the high band, and channel isolation higher than 40 dB. © 2002-2011 IEEE.

关键词： Microwave antennas

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Report for ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment and Management Committee Fourth Machine Learning in Geotechnics Dialogue on “Machine Learning Supremacy Projects”: 5 December 2023, Okayama Convention Center, Okayama, Japan

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Georisk 2024年第1期18卷 304-313页

作者： Leung, Andy Y.F. Phoon, Kok-Kwang Xiao, Te Shuku, Takayuki Ching, Jianye Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong Information Systems Technology and Design/Architecture and Sustainable Design Singapore University of Technology and Design Singapore Singapore Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong Okayama University Okayama Japan Department of Civil Engineering National Taiwan University Taipei Taiwan

The ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment Management Committee Fourth Machine Learning (ML) in Geotechnics Dialogue was held at the Okayama Convention Center on 5 December 2023. The dialogue focused on “machine learning supremacy projects”, which involve the use of novel ML techniques to analyse emerging data, potentially bringing disruptive value to transform research and practice. The discussions centred around four real-world projects covering tunnelling, pile foundations, and geophysical investigation, to showcase the latest developments and implementations of ML, exchange views on the associated technical and non-technical challenges, and explore further developments to transform practice on a broader scale. These projects highlight the need for efficient ML techniques to analyse large volumes of real-time data for 3D heterogeneous soil/rock domains, and the benefits of standardising data formats among practitioners and researchers. Meanwhile, as data become valuable assets, there is a need to establish guidelines or protocols to protect data privacy and ensure data trustworthiness while creating incentives for owners to share data. Several recommendations include (1) creating benchmark examples using real data and Class A prediction (i.e. prediction made before the event) exercises from real projects to accelerate research in ML methods and (2) involving regulators in future dialogue and exploring the incorporation of data-driven approaches in design codes to complement traditional methods. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Big data data-centric geotechnics digital transformation emerging data machine learning supremacy projects

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IN-SILICO non-invasive glucose monitoring using patch antenna

IN-SILICO non-invasive glucose monitoring using patch antenn...

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2023 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2023

作者： Sricharani, Goundla Singh, Urvashi Mukherjee, Jayanta Indian Institute of Information Technology Design and Manufacturing Madhya Pradesh Jabalpur India Iit Bombay Integrated Systems Laboratory Department of Electrical Engineering Annex Powai India

ISBN: (纸本)9798350328264

This study compares single and double patch antennas operating at 2.4504 GHz and 2.4508 GHz. The single patch antenna shows good impedance matching (-48.28 dB) and higher gain (7.004 dBi). The double patch antenna has S11= - 39.35 dB but slightly reduced gain (4.198 dBi). Both antennas exhibit alterations in near-field electric and magnetic fields in double patch configuration. The double patch's efficiency is 0.46 (46%), lower than the single patch's 0.906 (90.6%). Consideration of these findings aids in selecting the suitable antenna for specific application needs. Furthermore, we present a sensitivity analysis of antenna performance in the presence of a lateral forearm model representing human tissue with varying dielectric properties of blood. Two scenarios were considered: the hand model placed at 5 mm from the antennas and in direct contact with the antennas. Parametric sweep simulations were performed for the dielectric constant (ϵ) of blood with six values: 58.264, 62.264, 66.264, 70.264, 74.264, and 78.264. S-parameter results, specifically S11 and S21, were analyzed to understand the impact of blood dielectric constant on antenna behavior. © 2023 IEEE.

关键词： and Sensitivity Efficiency Gain Dielectric constant Impedance Patch

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