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Intrinsically patterned corrals in monolayer Ag_(5)Se_(2) and selective molecular co-adsorption

Nano Research 2022年第7期15卷 6730-6735页

作者： Jianchen Lu Shiru Song Shuai Zhang Yang Song Yun Cao Zhenyu Wang Li Huang Hongliang Lu Yu-Yang Zhang Sokrates T.Pantelides Shixuan Du Xiao Lin Hong-Jun Gao Institute of Physics&University of Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100190China Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science Vanderbilt UniversityNashvilleTN 37235USA CAS Center for Excellence in Topological Quantum Computation Chinese Academy of SciencesBeijing 100190China Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunmingYunnan 650093China

Functionalized two-dimensional(2D)materials play an important role in both fundamental sciences and practical *** construction and precise control of patterns at the atomic-scale are necessary for selective and multiple *** we report the fabrication of monolayer pentasilver diselenide(Ag_(5)Se_(2)),a new type of intrinsically patterned 2D material,by direct selenization of a Ag(111)*** atomic arrangement is determined by a combination of scanning tunneling microscopy(STM),low-energy electron diffraction(LEED),and density-functional-theory(DFT)***-scale STM images exhibit a quasi-periodic pattern of stoichiometric triangular domains with a side length of~15 nm and apical *** boundaries between triangular domains are *** of different molecules on the patterned Ag_(5)Se_(2) exhibits selective adsorption *** molecules preferentially adsorb on the boundaries,while tetracyanoquinodimethane(TCNQ)molecules adsorb both on the boundaries and the triangular *** co-depositing pentacene and TCNQ molecules,we successfully construct molecular corrals with pentacene on the boundaries encircling TCNQ molecules on the triangular *** realization of epitaxial large-scale and high-quality,monolayer Ag_(5)Se_(2) extends the family of intrinsically patterned 2D materials and provides a paradigm for dual functionalization of 2D materials.

关键词： two-dimensional materials dual functionalization scanning tunneling microscope epitaxial growth Ag_(5)Se_(2)monolayer

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Worst-Case Integrity Attacks and Resilient State Estimation With Partially Secured Measurements

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IEEE Transactions on Control of Network Systems 2025年第2期12卷 1769-1779页

作者： Zhou, Jing Shang, Jun Chen, Tongwen University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China

This paper examines the problem of optimal deception attacks against state estimation with partially secured measurements, where smart sensors transmit innovation sequences to the remote end for information fusion. Due to resource limitations or defensive countermeasures, the adversary can only modify data packets transmitted through unreliable channels. Meanwhile, the attack should be synthesized with sophistication to deceive an anomaly detector. To investigate the vulnerabilities of such estimation systems without feedback links and enhance security performance, the optimal attack policy is derived by formulating and explicitly solving a convex optimization problem, with the goal of maximizing the sum of estimation errors. Subsequently, a novel attack detection and resilient state estimation algorithm is proposed to ensure an acceptable level of estimation accuracy. The theoretical performance metrics, including false alarm rates for the proposed detector, are provided. Finally, the effectiveness of the results is confirmed through numerical examples. © 2014 IEEE.

关键词： Optimal detection

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Localization for V2X communication with noisy distance measurement

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International Journal of Intelligent Networks 2023年第1期4卷 355-360页

作者： Javed, Iram Tang, Xianlun Saleem, Muhammad Asim Javed, Ashir Zia, Muhammad Azam Shoukat, Ijaz Ali School of Computer Science and Technology Chongqing University of Posts and Telecommunications China Center of Excellence in Artificial Intelligence Machine Learning and Smart Grid Technology Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Aging Research Center Karolinska Institutet Stockholm171 65 Sweden Department of Computer Science University of Agriculture Faisalabad Pakistan Riphah College of Computing Riphah International University Faisalabad Campus Pakistan

Mobile sensor network localization is a growing research topic after IEEE 802.15.4 specified the procedure of low-rate wireless personal area networks (LR-WPANs), which further helps localize vehicles in the automobile industry. This paper presents a new localization scheme based on flying anchors deployed in vehicular infrastructure. The mobile anchor nodes follow a random C-shaped trajectory. A global positioning system (GPS) is attached to each anchor node, transmitting beacons with ID and location to all other vehicles in a network. Distance calculation is facilitated through link quality induction, employing the centroid method to compute localization error. Mobile anchor localization, particularly when employing a C-shaped trajectory commonly adopted by various topologies, consistently yields optimal positioning outcomes. However, this approach can be susceptible to the impact of noisy measurements, potentially reducing overall localization performance. To overcome this problem, we proposed a framework based on extended Kalman filtering (EKF), which is used to refine the coordinates of the vehicles. To compute the lower bounding of the vehicular node, an analytical framework is also proposed to enhance the localization error accuracy. Simulation results show that the EKF framework provides better positioning accuracy compared to the existing C-shaped solution, irrespective of noise statistics, topology selection, and anchor node density. With the help of the Extended Kalman Filter (EKF) framework, we achieved a comprehensive localization error of 0.99 m, accompanied by a standard deviation of 0.47. © 2023 The Authors

关键词： Extended Kalman filters

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Efficient Resource Allocation in Vehicular Networks Using Embedding-Enhanced MAPPO 10

Efficient Resource Allocation in Vehicular Networks Using Em...

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10th IEEE Smart World Congress, SWC 2024

作者： Qiu, Wen Shao, Xun Zhao, Wei Masui, Hiroshi Kitami Institute of Technology Information and Communication Engineering Hokkaido Japan Toyohashi University of Technology Department of Electrical and Electronic Information Engineering Toyohashi Japan Anhui University of Technology School of Computer Science and Technology Anhui China Kitami Institute of Technology Information Processing Center Hokkaido Japan

ISBN: (纸本)9798331520861

With the swift advancement of automotive technology, the need for efficient allocation of resources in V2V (vehicle-to-vehicle) communications has grown significantly. However, the dynamic nature of channels in vehicular networks introduces considerable uncertainty in resource allocation. This research presents a novel approach to addressing these challenges by utilizing multi-agent deep reinforcement learning (MADRL). By leveraging shared resource blocks (RBs) for V2V and vehicle-to-infrastructure (V2I) communications, our approach minimizes interference with V2I links and ensures optimal V2V performance. Unlike traditional methods that select actions sequentially, our approach treats every V2V link as an agent and simultaneously determines all agents' actions to improve coordination and efficiency. To accelerate the training of the multi-agent critic network, we integrate an embedding module to simplify and compress the network input dimensions. Through the use of our embedding multi-agent proximal policy optimization (E-MAPPO) algorithm, the agents collaboratively optimize their transmission strategies to efficiently share spectrum with V2I links. Simulation results show that our method greatly minimizes interference with V2I links while meeting the stringent latency and reliability requirements of V 2 V communications, surpassing baseline approaches. © 2024 IEEE.

关键词： Deep reinforcement learning

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A CNN-BiLSTM and KNN based missing data imputation for wind power generation forecasting 6

A CNN-BiLSTM and KNN based missing data imputation for wind ...

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6th IEEE International electrical and Energy Conference, CIEEC 2023

作者： Wang, Chaohong Ren, Bowen Li, Xiaozhu Chen, Laijun Qinghai University Department of Computer Technology and Applications Xining China Industry Research Center Xining China Tsinghua University Department of Electrical Engineering and Applied Electronics Technology Beijing China

ISBN: (纸本)9798350346671

A missing data imputation method combined with the KNN (K-nearest Neighbors) and BiLSTM (Bi-directional Long Short-Term Memory) is proposed to catering the solve challenges of noise interference and large variance. In this method, Firstly, the influence of dimensions on wind power is analyzed by the correlation coefficient of Pearson. And the information is extracted by the CNN (Convolutional Neural Networks) model. At the same time, the BiLSTM model exploits the ability to learn the internal representation of time series data. Then the missing data are imputed one by one by the CNN-BiLSTM model and the KNN model respectively. Finally, the final dataset is composed of these imputation values. The numerical simulation is carried out based on the actual data, the result shows that the combining model has a better imputation effect and its R2 increases by 0.02. © 2023 IEEE.

关键词： Wind power

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Label-aware Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding

Label-aware Multi-level Contrastive Learning for Cross-lingu...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Liang, Shining Shou, Linjun Pei, Jian Gong, Ming Zuo, Wanli Zuo, Xianglin Jiang, Daxin College of Computer Science and Technology Jilin University China Key laboratory of Symbolic Computation and Knowledge Engineering MOE STCA Microsoft Department of Electrical & Computer Engineering Duke University United States

Despite the great success of spoken language understanding (SLU) in high-resource languages, it remains challenging in low-resource languages mainly due to the lack of labeled training data. The recent multilingual code-switching approach achieves better alignments of model representations across languages by constructing a mixed-language context in zero-shot cross-lingual SLU. However, current code-switching methods are limited to implicit alignment and disregard the inherent semantic structure in SLU, i.e., the hierarchical inclusion of utterances, slots, and words. In this paper, we propose to model the utterance-slot-word structure by a multi-level contrastive learning framework at the utterance, slot, and word levels to facilitate explicit alignment. Novel code-switching schemes are introduced to generate hard negative examples for our contrastive learning framework. Furthermore, we develop a label-aware joint model leveraging label semantics to enhance the implicit alignment and feed to contrastive learning. Our experimental results show that our proposed methods significantly improve the performance compared with the strong baselines on two zero-shot cross-lingual SLU benchmark datasets. © 2022 Association for computational Linguistics.

关键词： Semantics

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Multi-state system reliability:An emerging paradigm for sophisticated engineered systems

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Frontiers of engineering Management 2024年第3期11卷 568-575页

作者： Yu LIU Tangfan XIAHOU Qin ZHANG Liudong XING Hong-Zhong HUANG School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Center for System Reliability and Safety University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical&Computer Engineering University of Massachusetts DartmouthMA 02747USA

1 Introduction Reliability is defined as the probability that a system or component will perform its required function for a specified period of time under specified operating conditions(Ebeling,2019).Traditional reliability theory assumes that both a system and its components have only two possible states in the operation stage,either perfectly functioning or completely ***,as engineered systems become more sophisticated,involving larger sizes,increased functionality,and greater intelligence,and with advancements in sensing technologies,it has been extensively observed that systems and components exhibit multiple distinct states as they deteriorate over *** failure behavior,damage severity,performance capacity,and operational efficiency of the system and components vary among these states(Lisnianski et al.,2018).It,therefore,necessitates the development of advanced reliability theories and methodologies that are capable of characterizing these systems and components with multi-state nature.

关键词： system state specified

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Sub-terahertz transmissive reconfigurable intelligent surface for integrated beam steering and self-OOK-modulation

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Light(Science & Applications) 2025年第1期14卷 131-141页

作者： Dongfang Shen Feng Lan Luyang Wang Tianyang Song Munan Yang Tianyu Hu Yueting Li Xiaolei Nie Jiayao Yang Shixiong Liang Hongxin Zeng Hui-Fang Zhang Pinaki Mazumder Ziqiang Yang Yaxin Zhang Tie Jun Cui Sichuan THz Communication Technology Engineering Research Center School of Electronic Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313000China Zhangjiang Laboratory Shanghai201204China School of Microelectronics Tianjin UniversityTianjin300072China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen518100China Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI48109USA Southeast University Nanjing210096China

Boasting superior flexibility in beam manipulation and a simpler framework than traditional phased arrays,terahertz metasurface-based phased arrays show great promise for 5G-A/6G communication *** with the reflective reconfigurable intelligent surface(reflective RIS),the transmissive RIS(TRIS)offers more feasibility for transceiver multiplexing systems to meet the growing demand for high-performance beam tracking in terahertz communication and radar ***,the terahertz TRIS encounters greater challenges in phase shift,beam efficiency,and complex ***,we propose a sub-terahertz TRIS based on the phase shift via Pancharatnam-Berry(PB)metasurface and self-on-off keying(OOK)modulation via Schottky *** electrically reconfigurable unit cell consists of a column-wise phase resonator and a rectangular *** experimental retrieved equivalent lumped-element circuit model is implemented in joint field-circuit simulations and is validated by experiments.A fabricated prototype demonstrates excellent performance of TRIS with the minimum insertion loss of 2.8 dB for operational states,large bandwidth nearly covering the entire W-band for 1-bit phase shift,deep OOK amplitude modulation of 12 dB,and wide scanning range of±60°with low specular *** further implement an integrated platform combining high-speed beam steering and spatial-light modulation,verifying the point-to-point signal transmissions in different directions using the TRIS *** proposed TRIS with high-performance and cost-effective fabrication makes it a promising solution to terahertz minimalist communication systems,radar,and satellite communication systems.

关键词： reconfigurable reflective resonator

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A Comparative Study of DeepLabCut and Other Open-Source Pupillometry Data Analysis Algorithms – Which to Choose?

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Machine Graphics and Vision 2024年第2期33卷 77-90页

作者： Badkul, Amitesh Mishra, Sonakshi Kommajosyula, Srinivasa P. Department of Electrical & Electronics Engineering Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Department of Pharmacy Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Ph.D. Program in Computer Science The Graduate Center The City University of New York New YorkNY United States

Pupillometry measures pupil size, and several open-source algorithms are available to analyse pupillometry data. However, only a few studies compared these algorithms’ accuracy and computational resources. This study aims to compare the accuracy of computer vision-based algorithms (Swirski, Starburst, PuRe, ElSe, ExCuSe algorithms) and the machine learning algorithm, DeepLabCut, to the double-blinded human examiners (gold-standard). Training of DeepLabCut with different architectures and a variable number of markers (2-9 markers) was done on an open-source dataset. The duration of training was statistically longer for the ResNet152 model compared to the MobileNet model. The pupil diameters in computer vision-based software such as PuRe, Starburst, and Swirski were statistically different from human measurements. MobileNet 2 and 3 marker models were the closest to the human measurements. In conclusion, this work highlights the efficiency of lower marker models based on MobileNet architecture in DeepLabCut, which consumes fewer computational resources and is more accurate. © 2024 Institute of Information technology, Warsaw University of Life Sciences - SGGW. All rights reserved.

关键词： Adversarial machine learning

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Applying Reinforcement Learning to Combine Multiple Swarm-based Algorithms

Applying Reinforcement Learning to Combine Multiple Swarm-ba...

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2023 IEEE Latin American Conference on computational Intelligence, LA-CCI 2023

作者： Lira, Rodrigo Cesar Macedo, Mariana Siqueira, Hugo Valadares Bastos-Filho, Carmelo Computer Engineering Department University of Pernambuco Recife Brazil Center for Collective Learning ANITI University of Toulouse Occitania France Department of Electrical Engineering Federal University of Technology Paraná Brazil

ISBN: (纸本)9798350348071

Swarm intelligence is a very efficient field for the optimization of high-dimensional functions. Nevertheless, choosing the best swarm-based algorithm is still challenging because it requires expertise in the field. Here, we propose to use reinforcement learning to dynamically select the swarm-based techniques to solve a benchmark function based on the current simulation state. First, we created a swarm capable of modifying its metaphor over iteration. Next, we created a reinforcement learning environment to solve benchmark functions. Then, we trained Proximal Policy Optimization to select the well-suited metaheuristic (GWO, GPSO or LPSO) to solve Rastrigin and F3 based on the information retrieved from the simulation. Our proposal reached competitive results in all simulated scenarios. Moreover, we found that the use of GPSO is consistently more efficient at the middle of the convergence and that using GWO is more efficient than using the other selected algorithms at the beginning of the convergence. Future works will bring us more robustness in combining swarm-based techniques while decreasing the computational cost. Thus, we show that reinforcement learning has the potential to overcome the effort of choosing the well-suited metaheuristic for a specific problem. © 2023 IEEE.

关键词： Swarm intelligence

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