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Metasurfaces with high-Q resonances governed by topological edge state

Optics letters 2022年第7期47卷 1822-1825页

作者： Zhidong Gu Jiaxin Chen Bofeng Gao Wei Wu Zhenyu Zhao Wei Cai Xinzheng Zhang Mengxin Ren Jingjun Xu The Key Laboratory of Weak-Light Nonlinear Photonics Ministry of Education School of Physics and TEDA Applied Physics Institute Nankai University Tianjin 300071 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin 300308 China Department of Physics Shanghai Normal University Shanghai 200234 China e-mail: weicai@*** e-mail: jjxu@***

Achieving high-quality (Q)-factor resonances in metasurfaces is essential for various applications, including nano-lasers, nonlinear optics, and quantum optics. In this work, we propose a high-Q metasurface using a topological strategy: constructing the metasurface by stacking two conjugated nanopillar arrays with different topological invariants. Our study shows that a topological edge state steadily appears at the interfaces of the nanopillars, and a sharp transmission resonance with a Q-factor of more than 1000 can be obtained. The sensing application of such high-Q topological metasurface is also demonstrated, whose figure of merit reaches approximately 145. The proposed strategy and underlying theory can open up new avenues to realize ultrasharp resonances, which can promote numerous potential applications, such as biosensing, optical modulation, and slow-light devices.

关键词： Electromagnetically induced transparency Nonlinear optics Optical systems Quantum optics Refractive index Resonance

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TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework

arXiv

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arXiv 2023年

作者： Zhao, Yang Yang, Jiaxi Wang, Wenbo Yang, Helin Niyato, Dusit 2 Fusionopolis Way Innovis #08-04 Singapore138634 Singapore Shenzhen Institute for Advanced Study School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Mechanical and Electrical Engineering Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology Kunming650050 China Department of Information and Communication Engineering Xiamen University Xiamen361005 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

Industrial systems require reliable predictive maintenance strategies to enhance operational efficiency and reduce downtime. Existing studies rely on heuristic models which may struggle to capture complex temporal dependencies. This paper introduces an integrated framework that leverages the capabilities of the Transformer and Deep Reinforcement Learning (DRL) algorithms to optimize system maintenance actions. Our approach employs the Transformer model to effectively capture complex temporal patterns in IoT sensor data, thus accurately predicting the Remaining Useful Life (RUL) of equipment. Additionally, the DRL component of our framework provides cost-effective and timely maintenance recommendations. Numerous experiments conducted on the NASA C-MPASS dataset demonstrate that our approach has a performance similar to the ground-truth results and could be obviously better than the baseline methods in terms of RUL prediction accuracy as the time cycle increases. Additionally, experimental results demonstrate the effectiveness of optimizing maintenance actions. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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EDOLAB: An Open-Source Platform for Education and Experimentation with Evolutionary Dynamic Optimization Algorithms

arXiv

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arXiv 2023年

作者： Peng, Mai Yazdani, Delaram She, Zeneng Yazdani, Danial Luo, Wenjian Li, Changhe Branke, Juergen Nguyen, Trung Thanh Gandomi, Amir H. Yang, Shengxiang Jin, Yaochu Yao, Xin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Research Institute Faculty of Engineering and Technology Liverpool John Moores University United Kingdom School of Computer Science and Technology Harbin Institute of Technology China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies School of Computer Science and Technology Harbin Institute of Technology Peng Cheng Laboratory China School of Artificial Intelligence Anhui University of Sciences & Technology China Information Systems Management and Analytics in Warwick Business School University of Warwick United Kingdom Faculty of Engineering & Information Technology University of Technology Sydney Australia Obuda University Hungary School of Computer Science and Informatics De Montfort University United Kingdom Department of Artificial Intelligence School of Engineering Westlake University China School of Computer Science University of Birmingham United Kingdom

Many real-world optimization problems exhibit dynamic characteristics, posing significant challenges for traditional optimization techniques. Evolutionary Dynamic Optimization Algorithms (EDOAs) are designed to address these challenges effectively. However, in existing literature, the reported results for a given EDOA can vary significantly. This inconsistency often arises because the source codes for many EDOAs, which are typically complex, have not been made publicly available, leading to error-prone re-implementations. To support researchers in conducting experiments and comparing their algorithms with various EDOAs, we have developed an open-source MATLAB platform called the Evolutionary Dynamic Optimization laboratory (EDOLAB). This platform not only facilitates research but also includes an educational module designed for instructional purposes. The education module allows users to observe: a) a 2-dimensional problem space and its morphological changes following each environmental change, b) the behaviors of individuals over time, and c) how the EDOA responds to environmental changes and tracks the moving optimum. The current version of EDOLAB features 25 EDOAs and four fully parametric benchmark generators. © 2023, CC BY-NC-SA.

关键词： Optimization algorithms

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A Novel eemd-based privacy preserving approach for top-k snps query in genome-wide association studies 6

A Novel eemd-based privacy preserving approach for top-k snp...

引用

6th IEEE International Conference on control science and Systems Engineering, ICCSSE 2020

作者： Xiaoyun, He Hao, Guo Hongsong, Chen Global Energy Interconnection Research Institute Co Ltd State Grid Key Laboratory of Information Network Security Beijing China University of Science and Technology Beijing School of Computer Communication Engineering Beijing China

ISBN: (纸本)9781728198460

Genome-wide association studies (GWAS) have been a popular method for querying Top-k most significant sets of singe-nucleotide polymorphism locations (SNPs) to discover the genetic factors of diseases. Doctors have been increasing interest to in querying SNPs that significantly associated to diseases. However, the queries and GWAS data share service bring great privacy breach risk to the patients. In traditional Laplace privacy preserving mechanism, privacy budget \varepsilonis different to be determined, the Laplace noise is added to original data only once, which causes randomness and potential security risk to privacy protection. A novel approach is proposed to implement the differential privacy preserving for Top-k SNPs query in GWAS. Ensemble Empirical Mode Decomposition(EEMD) is a noise-Assisted data analysis method, it is firstly proposed to be used as noise-Adding approach in privacy protection mechanism. In the EEMD approach, random white noise will be added into the SNPs querying results for many times. Moreover, the parameters of added white noise can be precisely controlled to achieve better effect. PriSTRAT software tool was redeveloped to evaluate EEMD-based privacy preserving approach, the dataset was generated by PLINK tools. Experimental results show that EEMD-based privacy preserving approach has achieved higher accuracy than Laplace mechanism under the same noise-Adding strength. The novel approach could be used to realize differential privacy preserving for Top-k SNPs query in GWAS to achieve the balance between privacy preserving and query accuracy. © 2020 IEEE.

关键词： Empirical mode decomposition

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Radar Sea Clutter Modeling and Reconstruction Based on Statistical Singularity Power Spectrum

Radar Sea Clutter Modeling and Reconstruction Based on Stati...

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Gang Xiong Baigang Huang Science and Technology on Communication Information Security Control Lab. Jiaxing China Shanghai Key Lab. for Intelligent Sensing and Recognition SJTU Shanghai China Science and Technology on Communication Information Security Control Laboratory No.36 Research Institute of CETC Jiaxing China

ISBN: (数字)9781728168968

ISBN: (纸本)9781728168975

In this paper, the radar clutter reconstruction model based on singularity power spectrum (SPS) and instantaneous singularity exponent (ISE) is proposed. The proposed ISE-SPS model consists of power measure channel and dimension measure channel. The multi-scale wavelet coefficients are estimated based on the coupling of the two channels to reconstruct the radar sea clutter. Experiment based on the Ice Multi-parameter Imaging X-Band (IPIX) indicates that the proposed model behaves better than the N-partitioned random multiplicative model (NRMM), with about 32% increment in terms of correlation coefficient and normalized MSE of MFS and SPS.

关键词： Power measurement Radar clutter Sea measurements Radar imaging Clutter Image reconstruction Wavelet coefficients

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Research on the Construction of a Novel Cyberspace security Ecosystem

引用

Engineering 2018年第1期4卷 47-52页

作者： Xiao-Niu Yang Wei Wang Xiao-Feng Xu Guo-Rong Pang Chun-Lei Zhang Science and Technology on Communication Information Security Control Laboratory Jiaxing Zhejiang 314033 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianfin 300300 China

Given the challenges facing the cyberspace of the nation, this paper presents the tripartite theory of cyberspace, based on the status quo of cyberspace. Corresponding strategies and a research architecture are proposed for common public networks （C space）, secure classified networks （S space）, and key infras- tructure networks （K space）, based on their individual characteristics. The features and security require- ments of these networks are then discussed. Taking C space as an example, we introduce the SMCRC （which stands for ＂situation awareness, monitoring and management, cooperative defense, response and recovery, and countermeasures and traceback＂） loop for constructing a cyberspace security ecosys- tem. Following a discussion on its characteristics and information exchange, our analysis focuses on the critical technologies of the SMCRC loop. To obtain more insight into national cyberspace security, special attention should be paid to global sensing and precise mapping, continuous detection and active manage- ment, cross-domain cooperation and systematic defense, autonomous response and rapid processing, and accurate traceback and countermeasure deterrence.

关键词： Cyberspace security ecosystem SMCRC loop Tripartite theory of cyberspace

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引用

International Conference on Computer and communications (ICCC)

作者： Yifan Xie Wenan Zhou Huamiao Hu Zhicheng Lu Mengyuan Wu School of Computer Science Beijing University of Posts and Telecommunications Beijing China Science and Technology on Communication Information Security Control Laboratory Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Code similarity detection is one of the important means to maintain the healthy development of the software eco-environment. Early code similarity detection method is mainly based on the code attribute measurement technology, this method can quickly detect more obvious similar parts on small-scale code datasets, but when faced with large-scale datasets or code segments with similar syntax and semantics, the detection performance is not effective. The new code similarity detection technology based on tree-structure representation and machine learning can adapt to different data changes, thus providing new solutions. This paper proposes a new detection method that combines the abstract syntax tree (AST) structure and unsupervised clustering, this new method can improve the detection efficiency of code clustering analysis, because it not only considers the syntax and semantic information of the code, but also reduces the workload of code data preprocessing through unsupervised clustering.

关键词： Clustering methods Semantics Clustering algorithms Machine learning Syntactics Tools Benchmark testing

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Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism

Prediction of exosomal piRNAs based on deep learning for seq...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Yulian Ding Aimin Li Rong Fei Xie Guo Fangxiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

PIWI-interacting RNAs (piRNAs) are a type of small non-coding RNAs which bind with the PIWI proteins to exert biological effects in various regulatory mechanisms. A growing amount of evidence reveals that exosomal piRNAs are potential biomarkers for diagnosis and treatment of complex diseases. Effective methods for the prediction of exosomal piRNAs are the foundation of piRNA functional research. In this study, we propose an end-to-end deep network for identifying exosomal piRNAs based on features learned from natural language processing (NLP) models for sequence embedding with attention mechanism. First, a benchmark dataset is constructed by processing piRNA subcellular localization annotated data and sequence data. Moreover, bagging positive unlabeled learning is applied to get the reliable negative set. Finally, we treat a piRNA sequence as a sentence and its k-mer subsequence as a token. Sequence embedding models with self-attention mechanism is designed to extract features from exosome piRNA sequences, which are used for the prediction task. Compared with three competing methods, our model achieves the best performance and reveals the key factors of exosomal piRNA sequences by the attention mechanism. Our model characterizes exosomal piRNAs and could be beneficial for researchers to investigate exosomal piRNAs’ functions.

关键词： Proteins Location awareness RNA Biological system modeling Predictive models Feature extraction Natural language processing

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A Deep Exploration of BitLocker Encryption and security Analysis

A Deep Exploration of BitLocker Encryption and Security Anal...

引用

International Conference on communication technology (ICCT)

作者： Cheng Tan Lijun Zhang Liang Bao Science and Technology on Communication Security Laboratory Chengdu Key Lab of Information Network Security Ministry of Public Security Shanghai China

ISBN: (数字)9781728181417

ISBN: (纸本)9781728181424

Due to the popularity of Windows system, BitLocker is widely used as a built-in disk encryption tool. As a commercial application, the design of BitLocker has to consider a capability of disaster recovery, which helps a user to recover data stored on encrypted disk when a regular access is not available. In this case, it will inevitably lead to some security risks when using BitLocker. We have a deep exploration of BitLocker encryption mechanism in this paper. We present the decryption method of encrypted VMK in case of system partition encryption and non-system partition encryption, respectively. VMK is the core key in BitLocker, with which the encrypted partition or the entire disk can be further decrypted. As for security analysis on BitLocker, we firstly make a difficulty analysis of brute force cracking on BitLocker keys, and then we analyze a possible threat caused by key theft. Based on this, we propose a few countermeasures about BitLocker usage. Additionally, we give some suggestions about security enhancement of BitLocker encryption.

关键词： Encryption Password Force Partitioning algorithms Universal Serial Bus Hard disks Dictionaries

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Parallel in-memory wireless computing

arXiv

引用

arXiv 2023年

作者： Wang, Cong Ruan, Gong-Jie Yang, Zai-Zheng Yangdong, Xing-Jian Li, Yixiang Wu, Liang Ge, Yingmeng Zhao, Yichen Pan, Chen Wei, Wei Wang, Li-Bo Cheng, Bin Zhang, Zaichen Zhang, Chuan Liang, Shi-Jun Miao, Feng Institute of Brain-inspired Intelligence National Laboratory of Solid State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing China National Mobile Communications Research Laboratory Southeast University Frontiers Science Center for Mobile Information Communication and Security Southeast University Purple Mountain Laboratories Nanjing China Institute of Interdisciplinary Physical Sciences School of Science Nanjing University of Science and Technology Nanjing China Nanjing Drum Tower Hospital The Affiliated Hospital of Nanjing University Medical School Nanjing China

Parallel wireless digital communication with ultralow power consumption is critical for emerging edge technologies such as 5G and Internet of Things. However, the physical separation between digital computing units and analogue transmission units in traditional wireless technology leads to high power consumption. Here we report a parallel in-memory wireless computing scheme. The approach combines in-memory computing with wireless communication using memristive crossbar arrays. We show that the system can be used for the radio transmission of a binary stream of 480 bits with a bit error rate of 0/480. The in-memory wireless computing uses two orders of magnitude less power than conventional technology (based on digital-to-analogue and analogue-to-digital converters). We also show that the approach can be applied to acoustic and optical wireless communications. Copyright © 2023, The Authors. All rights reserved.

关键词： Radio transmission

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