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SSRN 2025年

作者： Su, Wenzhi Zhang, Mengyu Zhang, Chuancheng Zou, Yong Liu, Wenpeng Ding, Shoujun School of Microelectronics and Data Science Anhui University of Technology Anhui Maanshan243002 China Anhui Provincial Joint Key Laboratory of Disciplines for Industrial Big Data Analysis and Intelligent Decision Anhui Maanshan243002 China Anhui Hefei230031 China

Upconversion (UC) fluorescence intensity ratio (FIR) technology has emerged as a promising approach for optical thermometry due to its ability to provide non-contact, high-precision temperature measurements. Unlike conventional UC phosphor-based systems, single-crystal UC materials offer enhanced responsiveness and sensitivity for thermal detection, thanks to their structural stability and superior thermal conductivity. In this study, we successfully synthesized an Yb3+, Ho3+:NaBi(MoO4)2 (NBM) single crystal with exceptional optical quality using the Czochralski (Cz) growth technique. Comprehensive structural characterization was carried out using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM). The results confirmed that Yb3+, Ho3+:NBM crystallizes in a tetragonal structure with the space group I41/a. The emission of different visible light colors under various excitation wavelengths was found to be due to the multiphonon relaxation process. Systematic analysis of power-dependent up-conversion emission spectra conclusively showed that the green and red up-conversion emissions arise from two-photon excitation processes. Moreover, temperature-dependent spectral evolution in the range of 300-500 K was quantitatively analyzed, allowing the calculation of both absolute sensitivity (Sa) and relative sensitivity (Sᵣ) parameters to evaluate the material's optical thermometric performance. These findings highlight the promising potential of Yb3+, Ho3+:NBM single crystal for developing high-performance optical thermometry devices. © 2025, The Authors. All rights reserved.

关键词： Single crystals

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Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition

arXiv

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arXiv 2025年

作者： Yang, Siyuan Lu, Shilin Wang, Shizheng Er, Meng Hwa Zheng, Zengwei Kot, Alex C. School of Electrical and Electronic Engineering Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Institute of Microelectronics Chinese Academy of Sciences China Department of Computer Science and Computing Zhejiang University City College China

This paper explores the promising interplay between spiking neural networks (SNNs) and event-based cameras for privacy-preserving human action recognition (HAR). The unique feature of event cameras in capturing only the outlines of motion, combined with SNNs’ proficiency in processing spatiotemporal data through spikes, establishes a highly synergistic compatibility for event-based HAR. Previous studies, however, have been limited by SNNs’ ability to process long-term temporal information, essential for precise HAR. In this paper, we introduce two novel frameworks to address this: temporal segment-based SNN (TS-SNN) and 3D convolutional SNN (3D-SNN). The TS-SNN extracts long-term temporal information by dividing actions into shorter segments, while the 3D-SNN replaces 2D spatial elements with 3D components to facilitate the transmission of temporal information. To promote further research in event-based HAR, we create a dataset, FallingDetection-CeleX, collected using the high-resolution CeleX-V event camera (1280 × 800), comprising 7 distinct actions. Extensive experimental results show that our proposed frameworks surpass state-of-the-art SNN methods on our newly collected dataset and three other neuromorphic datasets, showcasing their effectiveness in handling long-range temporal information for event-based HAR. Copyright © 2025, The Authors. All rights reserved.

关键词： Spatio-temporal data

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Phantom Events: Demystifying the Issues of Log Forgery in Blockchain

arXiv

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arXiv 2025年

作者： Liu, Yixuan Dong, Yuxin Liu, Ye Luo, Xiapu Li, Yi College of Computing and Data Science Nanyang Technological University Singapore School of Software and Microelectronics Peking University Beijing China School of Computing and Information Systems Singapore Management University Singapore Department of Computing The Hong Kong Polytechnic University Hong Kong

With the rapid development of blockchain technology, transaction logs play a central role in various applications, including decentralized exchanges, wallets, cross-chain bridges, and other third-party services. However, these logs, particularly those based on smart contract events, are highly susceptible to manipulation and forgery, creating substantial security risks across the ecosystem. To address this issue, we present the first in-depth security analysis of transaction log forgery in EVM-based blockchains, a phenomenon we term Phantom Events. We systematically model five types of attacks and propose a tool designed to detect event forgery vulnerabilities in smart contracts. Our evaluation demonstrates that our approach outperforms existing tools in identifying potential phantom events. Furthermore, we have successfully identified real-world instances for all five types of attacks across multiple decentralized applications. Finally, we call on community developers to take proactive steps to address these critical security vulnerabilities. Copyright © 2025, The Authors. All rights reserved.

关键词： Phantoms

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Rotatable Antenna Enabled Wireless Communication: Modeling and Optimization

arXiv

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arXiv 2025年

作者： Zheng, Beixiong Wu, Qingjie Zhang, Rui School of Microelectronics South China University of Technology Guangzhou511442 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

In this paper, we propose a new rotatable antenna (RA) model to improve the performance of wireless communication systems. Different from conventional fixed antennas, the proposed RA system can flexibly alter the three-dimensional (3D) boresight direction of each antenna independently by adjusting its deflection angles to achieve a desired array directional gain pattern. Specifically, we investigate an RA-enabled uplink communication system, where the receive beamforming and the deflection angles of all RAs at the base station (BS) are jointly optimized to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all the users. In the special single-user and free-space propagation setup, the optimal deflection angles of RAs are derived in closed form with the maximum-ratio combining (MRC) beamformer applied at the BS. Moreover, we analyze the asymptotic performance with an infinite number of antennas based on this solution, which theoretically proves that the RA system can achieve a higher array gain as compared to the fixed-antenna system. In the general multi-user and multi-path channel setup, we first propose an alternating optimization (AO) algorithm to alternately optimize the receive beamforming and the deflection angles of RAs in an iterative manner. Then, a two-stage algorithm that solves the formulated problem without the need for iteration is further proposed to reduce computational complexity. Simulation results are provided to validate our analytical results and demonstrate that the proposed RA system can significantly outperform other benchmark schemes. Copyright © 2025, The Authors. All rights reserved.

关键词： Beamforming

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AMCOA: Agent Motion Control With Obstacle Avoidance for Efficient Palm ROI Extraction

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Chen, Junan Fan, Dandan Liang, Xu Zhang, David The Chinese University of Hong Kong School of Data Science Guangdong Shenzhen518055 China Shenzhen Institute of Information Technology School of Microelectronics Guangdong 518055 China The Chinese University of Hong Kong AdBRC Laboratory Shenzhen518172 China Northwestern Polytechnical University School of Software Xi’an710129 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Shenzhen518129 China Harbin Institute of Technology School of Computer Science and Technology Guangdong Shenzhen518055 China

Palm recognition facilitates various real-world applications such as security access control and identity verification. The contactless method of acquiring palm images significantly reduces the risk of bacterial transmission and enhances user friendliness. However, this approach also presents inherent difficulties and challenges. Accurately identifying the region of interest (ROI) is crucial for feature extraction and recognition. The absence of strict guidelines regarding the position and angle of the user’s palm during contactless image acquisition complicates the accurate localization and extraction of the ROI. To address this issue, we propose an innovative ROI extraction method that utilizes agent motion control with obstacle avoidance (AMCOA). The agent dynamically identifies finger valley points (FVPs) while navigating and avoiding obstacles in the image, enabling the effective extraction of both the palmprint and palm vein ROIs based on the positions of two keypoints within the finger valleys. Our method is implemented in a synchronous acquisition system designed for palmprint and palm vein ROIs. We use a sensor module that simultaneously captures the distance, infrared (IR) image, and visible light (VL) image of the hand. The IR image is used to segment the hand area and extract the palm veins ROI, while the VL image aids in the extraction of the palmprint ROI after proper alignment. Experimental results indicate that our proposed method achieves both accurate and efficient ROI extraction. © 1963-2012 IEEE.

关键词： Palmprint recognition

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Dynamically scattering medium-based security-enhanced optical image encryption using orbital angular momentum and deep learning

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Results in Physics 2025年 69卷

作者： Hu, Junbao Mo, Xutao Lei, Yu Huang, Xianshan Wang, Dong Department of Optoelectronic Engineering School of Microelectronics & Data Science Anhui University of Technology Ma'anshan Anhui 243002 China Innovation and Entrepreneurship College Anhui University of Technology Ma'anshan Anhui 243002 China

Scattering medium-based optical image encryption is a practical strategy for information security, but it is challenging to convert speckles caused by scattering into encrypted information. In addition, the security level of the encryption is an issue of concern. Here we propose and demonstrate a potential optical image encryption with high security, in particular using optical orbital angular momentums (OAMs) to carry plaintext information so that encrypted information can be coded and converted into speckles, besides a dynamic diffuser for encryption and a pre-trained convolutional neural network (CNN) model for decryption. The high level of security stems from the use of both the order key (one-to-one correspondence between the labelled OAMs and the speckles) and the model key (unduplicatable pre-trained CNN model). Proof-of-concept experiments to demonstrate the proposed method have been successfully carried out. The image encryption method can open up new prospects for authentication, anti-counterfeiting and encrypted communication. © 2024

关键词： Convolutional neural network Dynamically scattering Optical encryption Orbital angular momentum

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Dual Backbone Multi-Attention Hierarchical Fusion and Feature Enhancement Network for Crowd Counting

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IEEE Transactions on Consumer Electronics 2025年

作者： Zheng, Chunling Gao, Xingyu Chen, Zhenyu Lyu, Lei Shandong Normal University School of Information Science and Engineering Jinan250358 China Chinese Academy of Sciences Institute of Microelectronics Beijing100029 China State Grid Corporation of China Big Data Center Beijing100031 China China Electric Power Research Institute Beijing100192 China

In recent years, significant progress has been made in crowd counting with the development of convolutional neural networks (CNNs). However, while CNNs excel at extracting local features, their limited receptive fields restrict their ability to model global context. In contrast, Transformers can effectively model long-distance dependencies, but are inferior to CNN in capturing local detail features. Local details and global context information are crucial to handle large-scale changes in crowds. To address this problem, we propose a novel dual backbone network (DBNet) that integrates CNN and Transformer architectures, aiming to capture and aggregate both global semantic information and local detail features at multiple levels. Specifically, the dual backbone structure is designed to extract fine-grained local features while modeling long-range contextual relationships. Additionally, we introduce a multi-attention hierarchical fusion module (MAHF) that integrates global and local features from the two backbones while suppressing background noise. To further enhance accuracy in the presence of multi-scale variations, we also employ a Feature Enhancement Module (FEM), which enables the network to more effectively identify edge features and facilitates more effective multi-scale feature modeling. Extensive experiments on ShanghaiTech, UCF-QNRF, and JHU-Crowd++ datasets demonstrate that DBNet achieves competitive performance, validating the effectiveness of our approach. © 1975-2011 IEEE.

关键词： Convolutional neural networks

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cVTS: A Constrained Voronoi Tree Search Method for High Dimensional Analog Circuit Synthesis 23

cVTS: A Constrained Voronoi Tree Search Method for High Dime...

引用

Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Aidong Zhao Xianan Wang Zixiao Lin Zhaori Bi Xudong Li Changhao Yan Fan Yang Li Shang Dian Zhou Xuan Zeng State Key Laboratory of Integrated Chips and Systems Microelectronics Department Fudan University Shanghai China Department of Electrical Engineering University of Texas at Dallas USA Department of Electrical and Computer Engineering University of California at San Diego USA School of Data Science Fudan University Shanghai China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9798350323481

A constrained Voronoi tree-based domain decomposition method for high-dimensional Bayesian optimization is proposed to solve large scale analog circuit synthesis problems, which can be formulated as high-dimensional heterogeneous black-box optimization. Hierarchical Voronoi tree progressively breaks down the design space into partitions with implicit performance boundaries such that promising regions are efficiently explored. Fast exploitation is ensured in Voronoi nest via local Bayesian optimization with a few observations. A slice-enhanced Gibbs sampling method is proposed to sample acquisition function cMES in irregular polyhedrons with design constraints. Compared with state-of-the-art methods, cVTS achieves significant speed up without loss of accuracy.

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Efficient ILT via Multi-Level Lithography Simulation 23

Efficient ILT via Multi-Level Lithography Simulation

引用

Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Shuyuan Sun Fan Yang Bei Yu Li Shang Xuan Zeng State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China and School of Microelectronics Fudan University Shanghai China Chinese University of Hong Kong Hong Kong China State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China and China and Shanghai Key Laboratory of Data Science School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9798350323481

Inverse Lithography Technology (ILT) is a widely investigated method to improve the yield of chip manufacturing. However, high computational complexity and difficulty in fabricating curvilinear shapes have hindered the widespread adoption of ILT. This paper presents an efficient ILT framework, including a multi-level resolution method for simulation acceleration, a downsampling strategy for mask optimization, and an improved mask binary function to improve mask printability. Experimental results show that the proposed method outperforms state-of-the-art methods with at least a 33.8% reduction in L2 loss and a 15.5% reduction in PVBand.

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An Intelligent Security-Enabled Home Automation System using Internet of Things Environment 3

An Intelligent Security-Enabled Home Automation System using...

引用

3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Karthikeyan, P. Dinesh, M. Akila, A. Veeramuthu, A. Giri, Jayant Al Sherideh, Ala'a Prathyusha Engineering College Department of Eee Tiruvallur Chennai India Saveetha School of Engineering Department of Vlsi Microelectronics Chennai India R.M.K. College of Engineering and Technology Department of Artificial Intelligence and Data Science Tamil Nadu Puduvoyal India Sathyabama Institute of Science and Technology Department of Information Technology Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University College of Information Technology Department of Cyber Security Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331509675

IoT technologies to bolster residential security, safety, and sustainability. By leveraging facial recognition for door access, enhancing fire safety monitoring, and integrating energy harvesting, it aims to create more resilient and eco-friendly residential environments. These innovations offer comprehensive solutions to address evolving challenges and optimize residential living. The proposed research introduces an innovative smart home automation system leveraging IoT technologies and Google Assistant for the voice-controlled operation of household devices. It integrates a comprehensive array of sensors for safety and security monitoring, facilitating real-time alerts for fire outbreaks, unauthorized entry, and environmental anomalies. MQTT enables smooth remote access and management of devices. The research evaluates IoT routing protocols, highlighting ISHAS-IoTs's benefits in efficiency, delivery ratio, and delay. These findings underscore the protocol's potential to enhance IoT network performance and efficiency, contributing to the design of more robust and reliable smart home systems. © 2025 IEEE.

关键词： Smart homes

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