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Multi-level data security program based on quantum key

Journal of computers (Taiwan) 2021年第2期32卷 164-175页

作者： Zhu, De-Xin Li, Xin-Jian An, Ya-Ting Zhou, Jun-Wei Huang, Qi-Yuan Li, Xiao-Hui Wu, Jia-Nan Song, Li-Jun College of Computer Science and Technology Changchun University Changchun130022 China Institute for Interdisciplinary Quantum Information Technology Jilin Engineering Normal University Changchun130022 China Jilin Engineering Laboratory for Quantum Information Technology Jilin Engineering Normal University Changchun130022 China

A multi-level data security program based on quantum key is proposed in this paper aiming to improve the security of documents in computers. Since the generation of quantum keys is secure theoretically, incorporating time phase coded quantum key distribution networks into classical networks in this program provides a practical way to achieve dual-network integration. Moreover, a quantum key utilization strategy of three quantum keys, including onetime- pad, 16-byte key AES-128 algorithm and SM4 algorithm, are employed according to the importance level of the documents based on low quantum key bit rates of commercial optical fibers. Experimental results demonstrate that dual networks can operate steadily and the encryption/decryption for a 10 MB document of the proposed multi-level security device costs less than 10 s. Hence, a high level of protection for data security is realized through the proposed multi-level data security program. © 2021 computer Society of the Republic of China. All rights reserved.

关键词： Optical fibers

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Region-level Contrastive and Consistency Learning for Semi-Supervised Semantic Segmentation

arXiv

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arXiv 2022年

作者： Zhang, Jianrong Wu, Tianyi Ding, Chuanghao Zhao, Hongwei Guo, Guodong College of Computer Science and Technology Jilin University Changchun China Institute of Deep Learning Baidu Research Beijing China National Engineering Laboratory for Deep Learning Technology and Application Beijing China College of Software Jilin University Changchun China The Institute of Deep Learning Baidu Research China

Current semi-supervised semantic segmentation methods mainly focus on designing pixel-level consistency and contrastive regularization. However, pixel-level regularization is sensitive to noise from pixels with incorrect predictions, and pixel-level contrastive regularization has memory and computational cost with O(pixel num2). To address the issues, we propose a novel region-level contrastive and consistency learning framework (RC2L) for semi-supervised semantic segmentation. Specifically, we first propose a Region Mask Contrastive (RMC) loss and a Region Feature Contrastive (RFC) loss to accomplish region-level contrastive property. Furthermore, Region Class Consistency (RCC) loss and Semantic Mask Consistency (SMC) loss are proposed for achieving region-level consistency. Based on the proposed region-level contrastive and consistency regularization, we develop a region-level contrastive and consistency learning framework (RC2L) for semi-supervised semantic segmentation, and evaluate our RC2L on two challenging benchmarks (PASCAL VOC 2012 and Cityscapes), outperforming the state-of-the-art. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Microwave characterization of exotic resonant states in dielectric resonators

Microwave characterization of exotic resonant states in diel...

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Electronic Technology, Communication and Information (ICETCI), IEEE International Conference on

作者： Tong Wu Andrey B. Evlyukhin Vladimir R. Tuz State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering International Center of Future Science Jilin University Changchun China Cluster of Excellence PhoenixD Institute of Quantum Optics Leibniz University Hannover Germany School of Radiophysics Biomedical Electronics and Computer Systems V. N. Karazin Kharkiv National University Kharkiv Ukraine

ISBN: (数字)9798350361643

ISBN: (纸本)9798350361650

In this study, we design a structure consisting of the radial arrangement of several vertically standing dielectric disks (resonators) so that such a ring cluster supports exotic toroidal dipole mode excitation. Subsequently, the characteristics of a system composed of two identical rings with a change in the distance are studied to reveal how to affect the peculiarities of the coupling between two toroidal dipole modes. The manifestation of toroidal dipole coupling is confirmed by checking the extinction cross-section, near-field distributions, and induced toroidal moments obtained from both full-wave numerical simulation and microwave experiments. To experiment, particles are made from commercially available ceramics. During the measurements, standard microwave equipment is used to characterize the toroidal dipole coupling within the frequency band of 1−10 GHz. Since the structure comprises simple dielectric disks without any metallic elements, the proposed designs are hopefully scalable down to the micrometer or nanometer scale considering their practical applications as building blocks in metamaterials operated on the radiation-less exotic toroidal and anapole states.

关键词： Microwave measurement Couplings Microwave integrated circuits Masers Microwave communication Particle measurements Dielectrics

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Conditional Generative Modeling for Amorphous Multi-Element Materials

arXiv

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arXiv 2025年

作者： Li, Honglin Liu, Chuhao Guo, Yongfeng Luo, Xiaoshan Chen, Yijie Liu, Guangsheng Li, Yu Wang, Ruoyu Wang, Zhenyu Wu, Jianzhuo Ma, Cheng Xie, Zhuohang Lv, Jian Ding, Yufei Zhang, Huabin Luo, Jian Zhong, Zhicheng Li, Mufan Wang, Yanchao Li, Wan-Lu Key Laboratory of Material Simulation Methods and Software Ministry of Education College of Physics Jilin University Changchun China Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California La Jolla San DiegoCA United States Institute of Molecular Engineering Plus College of Chemistry Fuzhou University Fuzhou China College of Chemistry and Molecular Engineering Peking University Beijing China School of Physics Nankai University Tianjin China Institute of Modern Physics Fudan University Shanghai China Program in Materials Science and Engineering University of California La Jolla San DiegoCA United States School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China International Center of Future Science Jilin University Changchun China Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Center for Renewable Energy and Storage Technologies Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Suzhou Lab Suzhou215123 China

Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Amorphization

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CellMirror: Deciphering Cell Populations from Spatial Transcriptomics Data by Interpretable Contrastive Learning

CellMirror: Deciphering Cell Populations from Spatial Transc...

引用

Medical Artificial Intelligence (MedAI), IEEE International Conference on

作者： Junjie Xia Jiangnan Cui Zhenyu Huang Shuangquan Zhang Fang Yao Yijian Zhang Chunman Zuo Department of Applied Mathematics Institute of Artificial Intelligence Donghua University Shanghai China Institute of Artificial Institute Donghua University Shanghai China College of Computer Science and Technology Jilin University Changchun China School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China Affiliated Shenzhen Maternity and Child Healthcare Hospital Institute of Maternal and Child Medicine Southern Medical University Shenzhen China Department of General Surgery Xinhua Hospital Affiliated to Shanghai Jiao Tong University of Medicine Shanghai China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

Spatial transcriptomics (ST) has enabled us elucidating tumor microenvironments, however, the technological limitations without single-cell resolution severely hinder its application. Here, we propose CellMirror, an interpretable contrastive learning model to decipher heterogeneous cell populations in ST data by single-cell RNA-sequencing (scRNA-seq) data. Specifically, CellMirror learns the disentangled shared (representing biological variations in both data) and salient features (specific to ST data) by two contrastive variational encoders, while constructing the relations between genes and features by a shared linear decoder. In various cancer samples, CellMirror outperforms other tools in learning common features for label transfer, and interpretation of features. Particularly, in breast cancer studies, CellMirror detects finer domains in ST data missed by other methods, and is robust to dissect cell populations in ST data using independent scRNA-seq data. These results demonstrate applications of CellMirror in interpreting the complex tumor structure in ST data by integrating scRNA-seq data.

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Asynchronous distribution scheme of group quantum keys based on max heap in classical network

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Journal of King Saud University - computer and Information sciences 2025年第4期37卷 1-17页

作者： Zhu, Dexin Zhao, Zilong Zhang, Huanjie Zhou, Zhiqing Li, Yuanbo Zhao, Jian Song, Lijun Zheng, Jun School of Cyberspace Science and Technology Beijing Institute of Technology Beijing 100081 China College of Computer Science and Technology Changchun University Jilin Changchun 130022 China Jilin Engineering Laboratory for Quantum Information Technology Changchun Institute Of Technology Jilin Changchun 130022 China

With the advancement of the information age, various information-based products have become increasingly prevalent, leading to a corresponding rise in the volume of data requiring encrypted transmission. Consequently, secure key distribution has become particularly critical, especially in large-scale communication scenarios. Considering practical limitations such as offline availability and low performance among communication participants, we propose an asynchronous group quantum key distribution scheme based on a max heap structure and blockchain technology within classical networks. In this scheme, quantum keys serve as group communication keys, and the encrypted transmission of quantum keys is facilitated through a max heap constructed according to user information. Specifically, during the initialization phase, users upload relevant information to the Key Distribution Center (KDC), while in the key distribution phase, the blockchain stores encrypted temporary group keys, enabling asynchronous access. The proposed scheme not only reduces performance consumption for users within the group but also leverages the intrinsic properties of the max heap to dynamically balance loads. Moreover, the scheme achieves both forward and backward secrecy and demonstrates favorable performance in terms of storage efficiency and computational cost. © The Author(s) 2025.

关键词： Blockchain Group key distribution Max heap Quantum key

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Adaptive feature fusion and task-dynamic alignment for real-time object detection on edge devices

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Expert Systems with Applications 2025年 290卷

作者： Ding, Yan Wu, Wenjie Zhai, Yunan Zhang, Liyuan Pan, Lin Zhao, Jia School of Computer Technology and Engineering Changchun Institute of Technology Changchun130012 China College of Artificial Intelligence Technology Changchun Institute of Technology Changchun130012 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China Education Examinations Authority of Jilin Province China School of Electronics Engineering and Computer Science Peking University Beijing China

Real-time object detection on resource-constrained edge devices faces a fundamental challenge: balancing high detection accuracy with low computational complexity. Existing models often fail to achieve this balance, limiting their deployment in practical edge computing applications. This paper introduces EdgeSight, an efficient and optimized object detection architecture specifically designed for edge computing environments. EdgeSight integrates several key innovations, including the RepViTBlock in the C2f module to enhance feature extraction while maintaining a compact model size, and the Task-dynamic-aligned Detection Head (TDADH), which uses Deformable ConvNet V2 (DCNv2) to adaptively adjust receptive fields, optimizing both classification and localization tasks. Additionally, EdgeSight employs layer-adaptive magnitude-based pruning (LAMP) for model compression, reducing computational complexity without sacrificing accuracy, and incorporates advanced knowledge distillation techniques, such as Channel-wise Knowledge Distillation (CWD) and Bridging Cross-task Knowledge Distillation (BCKD), to minimize accuracy loss during compression. Experiments across multiple benchmark datasets demonstrate that EdgeSight significantly improves detection accuracy while maintaining low computational complexity and a compact model size, confirming its effectiveness and robustness across diverse real-time edge computing applications, including public safety, autonomous driving, and urban monitoring. © 2025 Elsevier Ltd

关键词： Object detection

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Visually meaningful asymmetric image encryption based on a random devil's vortex phase mask in the gyrator transform domain

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Optics and Lasers in engineering 2025年 194卷

作者： Liu, Yujia Sham, Chiu-Wing Zhang, Fuqi Zhao, Hui Ma, Longyu School of Electrical and Information Engineering Changchun Institute of Technology Changchun130012 China School of Computer Science The University of Auckland Auckland1010 New Zealand College of Communication Engineering Jilin University Jilin Changchun130012 China Changchun Water Conservancy Planning and Research Institute Jilin Changchun130062 China

Traditional image encryption methods usually generate noisy ciphertext images, which are vulnerable to targeted analysis by attackers, thus exposing the existence of encrypted information. To solve this problem, this study proposes a visually meaningful asymmetric image encryption method based on the rotation transform domain and random devil's vortex phase mask (RDVPM). The proposed method constructs RDVPM using devil lens function, Fresnel zone plate phase function and vortex phase function, and uses it as the public key of the encryption system. In addition, using visually meaningful images, amplitude and phase truncation techniques are used in the gyrator transform domain to construct an asymmetric encryption system to generate a specific Private key source, effectively improving the efficiency of encryption and decryption while ensuring that the system has a high degree of security. The visually meaningful image is a completely natural image that does not contain the original image information, which effectively improves the security of the encryption system. Numerical simulation results show that under the conditions of multiple test images, the proposed algorithm has high system parameter sensitivity and key sensitivity, and has good statistical characteristics. It has good robustness and security under Gaussian noise, speckle noise and salt and pepper noise attacks, occlusion attacks, chosen plaintext attacks and specific attack conditions. The proposed optical asymmetric encryption method provides a new idea for fast and secure visually meaningful image encryption. © 2025 Elsevier Ltd

关键词： Salt and pepper noise

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Enhancing Li-Ion Battery State of Charge Estimation Via an Adaptive Strong Tracking Extended Kalman Filter with Variable Fading

SSRN

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SSRN 2024年

作者： Wu, Baigong Xu, Guoqi Zhan, Mingjing Xu, Mingqi Zhang, Xiao Cheng, Junjie Shu, Yongdong Cheng, Chen Marine Equipment and Technology Institute Jiangsu University of Science and Technology Jiangsu Province Zhenjiang212003 China College of Automation Jiangsu University of Science and Technology Jiangsu Province Zhenjiang212003 China School of Naval Architecture and Ocean Engineering Jiangsu University of Science and Technology Jiangsu Province Zhenjiang212003 China College of Marine Science and Technology Hainan Tropical Ocean University Hainan Province Sanya572000 China School of Energy and Power Engineering Changchun Institute of Technology Jilin Province Changchun130012 China Nanjing High Precision Marine Equipment Co. Ltd Jiangsu Province Nanjing210000 China

In lithium-ion battery management systems, accurately estimating the State of Charge (SOC) is crucial for ensuring system reliability and safety. Traditional methods like the Extended Kalman Filter (EKF) and its improved variant, the Strong Tracking Extended Kalman Filter (STEKF), face challenges in managing the covariance matrix of observation noise, especially under varying operational conditions. To address these issues, this study introduces an Adaptive Strong Tracking Extended Kalman Filter (ASTEKF). This algorithm employs biased estimation to ensure the positiveness and symmetry of observation noise and dynamically updates the observation noise by comparing the ratio of a priori residuals to theoretical residuals. Additionally, ASTEKF controls the measurement noise within a reasonable range by setting appropriate thresholds based on system state noise and operational outcomes. Evaluation under different temperatures (0°C, 15°C, 25°C) demonstrates that ASTEKF outperforms conventional EKF and STEKF, particularly in terms of accuracy and reliability, marking a significant advancement in battery management system enhancements. © 2024, The Authors. All rights reserved.

关键词： Extended Kalman filters

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A two-stage HV-driven adaptive multi-objective evolutionary algorithm and its application in fixed polarity reed-muller circuits

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Expert Systems with Applications 2025年 288卷

作者： Yang, Lu Wang, Shengsheng Dong, Ruyi Fu, Zihao College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Information and Control Engineering Jilin Institute of Chemical Technology Changchun130012 China

To achieve a balance between convergence and diversity, we proposed a two-stage HV-driven adaptive multi-objective evolutionary algorithm (TSAMEA). TSAMEA employs a sinusoidal decreasing parameter adjustment method to enhance exploration pace in the first stage. An adaptive parameter control mechanism utilizes historical memory pools and an HV-driven degree adjustment strategy to achieve better exploitation in the second stage. Extensive experimental data demonstrate that TSAMEA outperforms nine other compared MOEAs. The component analysis illustrates the efficacy of each component of TSAMEA. In addition, area and power optimization are now the main limitations in chip design, TSAMEA is applied to area and power optimization for Fixed Polarity Reed-Muller (FPRM) logic circuits and perform well, which further verifies the ability of the TSAMEA to solve practical problems. © 2025

关键词： Cellular automata

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