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Topological Dirac-vortex microcavity laser for robust on-chip optoelectronics

Light(science & Applications) 2024年第4期13卷 591-592页

作者： Yuanpeng Wu Zetian Mi Department of Electrical Engineering and Computer Science University of Michigan1301 Beal AvenueAnn ArborMI 48109USA

Dirac-vortex microcavity laser based on InAs/InGaAs quantum dots have been experimentally realized on silicon *** topological laser features a large spectral range and high robustness against variations such as cavity... 详细信息

关键词： laser optoelectronics cavity

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SFI-Swin: symmetric face inpainting with swin transformer by distinctly learning face components distributions

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Multimedia Tools and Applications 2024年第17期84卷 1-15页

作者： Givkashi, MohammadHossein Naderi, MohammadReza Karimi, Nader Shirani, Shahram Samavi, Shadrokh Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Department of Electrical and Computer Engineering McMaster University HamiltonL8S 4L8 Canada Computer Science Department Seattle University Seattle98122 United States

Image inpainting consists of filling holes or missing parts of an image. Inpainting face images with symmetric characteristics is more challenging than inpainting a natural scene. None of the powerful existing models can fill out the missing parts of an image while considering the symmetry and homogeneity of the picture. Moreover, the metrics that assess a repaired face image quality cannot measure the preservation of symmetry between the rebuilt and existing parts of a face. In this paper, we intend to solve the symmetry problem in the face inpainting task by using multiple discriminators that check each face organ’s reality separately and a transformer-based network. We also propose "symmetry concentration score" as a new metric for measuring the symmetry of a repaired face image. The quantitative and qualitative results show the superiority of our proposed method compared to some of the recently proposed algorithms in terms of the reality, symmetry, and homogeneity of the inpainted parts. The code for the proposed method is available at https://***/mohammadrezanaderi4/SFI-Swin. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep learning

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An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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computer Modeling in engineering & sciences 2024年第8期140卷 1689-1710页

作者： Md.Abdur Rahim Fahmid Al Farid Abu Saleh Musa Miah Arpa Kar Puza Md.Nur Alam Md.Najmul Hossain Sarina Mansor Hezerul Abdul Karim Department of Computer Science and Engineering Pabna University of Science and TechnologyPabna6600Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Department of Computer Science and Engineering Bangladesh Army University of Science and TechnologySaidpur5311Bangladesh Department of Mathematics Pabna University of Science and TechnologyPabna6600Bangladesh Department of Electrical Electronic and Communication EngineeringPabnaUniversity of Science and TechnologyPabna6600Bangladesh Department of Electrical and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde

关键词： Bengali handwriting(BHW) person identification convolutional neural network(CNN) BiLSTM

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A Neural-Reinforcement-Learning-Based Guaranteed Cost Control for Perturbed Tracking Systems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 3205-3217页

作者： Zhong, Xiangnan Ni, Zhen Florida Atlantic University Department of Electrical Engineering and Computer Science Boca RatonFL33431 United States

Artificial intelligence (AI)-based learning control plays a critical role in the evolution of intelligent control, particularly for complex network systems. Traditional intelligent control methods assume the agent can learn from safe data in the tasks. However, many application scenarios exist perturbations caused by noise and/or malicious attack, which make the received data unreliable and may cause the failure of the learning process. In this article, we focus on developing an intelligent guaranteed cost control method for nonlinear tracking systems subject to unknown matched and mismatched perturbations. By developing appropriate cost functions for the nominal plants, we transform the robust tracking control problem into a stabilization design for both kinds of perturbations. The explicit proofs are provided to show the equivalence of the transformation for these two situations respectively. Then, the neural-reinforcement-learning-based algorithm with guaranteed cost control is developed to learn the cost functions and optimal control laws adaptively. The designed method can also guarantee the boundedness of a given cost function. Three simulation studies are provided to demonstrate the effectiveness of the proposed method and also validate the theoretical analysis. © 2020 IEEE.

关键词： Cost functions

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Fault-tolerant properties of scale-free linear protocols for synchronization of homogeneous multi-agent systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 4194-4201页

作者： Stoorvogel, Anton A. Saberi, Ali Liu, Zhenwei University of Twente Department of Electrical Engineering Mathematics and Computer Science P.O. Box 217 Enschede Netherlands Washington State University School of Electrical Engineering and Computer Science PullmanWA99164 United States Northeastern University College of Information Science and Engineering Shenyang110819 China

Originally, protocols were designed for multi-agent systems (MAS) using information about the network which might not be available. Recently, there has been a focus on scale-free synchronization where the protocol is designed without any prior information about the network. As long as the network contains a directed spanning tree, a scale-free protocol guarantees that the network achieves synchronization. If there is no directed spanning tree then synchronization cannot be achieved. But what happens when these scale-free protocols are applied to such a network where the directed spanning tree no longer exists? This paper establishes that the network decomposes into a number of basic bicomponents which achieves synchronization among all nodes in this basic bicomponent. On the other hand, nodes which are not part of any basic bicomponent converge to a weighted average of the synchronized trajectories of the basic bicomponents. The weights are independent of the initial conditions and are independent of the designed protocol. © 1963-2012 IEEE.

关键词： Synchronization

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A New Approach to Determine Feasible Operating Region of Unbalanced Distribution Networks with Distributed Photovoltaics

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IEEE Transactions on Power Delivery 2025年第3期40卷 1493-1504页

作者： Prasad, Manorath Rather, Zakir Hussain Razzaghi, Reza Doolla, Suryanarayana Indian Institute of Technology Bombay Department of Energy Science and Engineering Mumbai India Monash University Department of Electrical and Computer Systems Engineering Melbourne Australia

Amidst rising distributed generation and its potential role in grid management, this article presents a new realistic approach to determine the operational space and flexibility potential of an unbalanced active distribution network. The feasible operating region of an active distribution network is constituted by its range of active-reactive power exchanges with the bulk power system without breaching network constraints. This study explores the potential of highly penetrated single- and three-phase distributed photovoltaics and voltage-sensitive loads to determine the feasible operating region at different operating points. The cumulative response of Volt-Var controlled distributed photovoltaics and voltage-sensitive loads determines the power flow at the bulk power system-active distribution network interconnection, ensuring feasibility with respect to voltage magnitude and unbalance constraints. Further, the correspondence of feasible operating region with the tap-settings of substation transformer enables a novel feature to traverse throughout the available operating region and facilitate bulk power system-active distribution network power coordination. Additionally, a nodal sensitivity-based adjustable Volt-Var control scheme is proposed for distributed photovoltaics, improving the feasible operating region. The proposed strategy is validated on bulk power systemactive distribution network integrated test system. Bulk power system: IEEE-9 bus system-Active distribution network: (highly unbalanced IEEE-13 bus distribution system (medium voltage) + modified CIGRE low voltage system). © 1986-2012 IEEE.

关键词： Power distribution networks

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A Novel Tensor Decomposition-Based Efficient Detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 487-501页

作者： Nianyin Zeng Xinyu Li Peishu Wu Han Li Xin Luo Department of Instrumental and Electrical Engineering Xiamen UniversityXiamen 361005China IEEE College of Computer and Information Science Southwest UniversityChongqing 400715China

Unmanned aerial vehicles(UAVs) have gained significant attention in practical applications, especially the low-altitude aerial(LAA) object detection imposes stringent requirements on recognition accuracy and computational resources. In this paper, the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net) is proposed,where the TT-format TD(tensor decomposition) and equalweighted response-based KD(knowledge distillation) methods are designed to minimize redundant parameters while ensuring comparable performance. Moreover, some robust network structures are developed, including the small object detection head and the dual-domain attention mechanism, which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features. Considering the imbalance of bounding box regression samples and the inaccuracy of regression geometric factors, the focal and efficient IoU(intersection of union) loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy. The proposed TDKD-Net is comprehensively evaluated through extensive experiments, and the results have demonstrated the effectiveness and superiority of the developed methods in comparison to other advanced detection algorithms, which also present high generalization and strong robustness. As a resource-efficient precise network, the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net, which provides useful insights on handling imbalanced issues and realizing domain adaptation.

关键词： Attention mechanism knowledge distillation(KD) object detection tensor decomposition(TD) unmanned aerial vehicles(UAVs)

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Multidimensional image morphing-fast image-based rendering of open 3D and VR environments

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虚拟现实与智能硬件(中英文) 2025年第2期7卷 155-172页

作者： Simon SEIBT Bastian KUTH Bartosz von Rymon LIPINSKI Thomas CHANG Marc Erich LATOSCHIK Game Tech Laboratory Faculty of Computer ScienceNuremberg Institute of TechnologyNuremberg 90489Germany Department of Electrical Engineering and Computer Science Coburg University of Applied Sciences and ArtsCoburg 96450Germany Human-Computer Interaction Group Institute of Computer ScienceUniversity of WuerzburgWuerzburg 97074Germany

Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and ***,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains *** This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and ***,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image *** this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of *** rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image *** detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in *** addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light *** Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,*** achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering *** Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR ***,the handling of morphing artifacts in the parallax image regions remains a topic for future resea

关键词： computer graphics 3D real-time rendering computer vision Image morphing Virtual reality

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iLIAC: An approach of identifying dissimilar groups on unstructured numerical image dataset using improved agglomerative clustering technique

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Multimedia Tools and Applications 2024年第39期83卷 86359-86381页

作者： S, Sreedhar Kumar Ahmed, Syed Thouheed Fathima, Afifa Salsabil Mathivanan, Sandeep Kumar Jayagopal, Prabhu Saif, Abdu Gupta, Sachin Kumar Sinha, Garima Department of Computer Science and Engineering School of Engineering and Technology CMR University Karnataka Bengaluru India Department of Electrical Engineering Indian Institute of Technology Hyderabad Telangana Kandi India School of Computer Science and Engineering REVA University Bangalore India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Communication and Computer Engineering Faculty of Engineering and IT Taiz University Taiz Yemen Katra India Department of Computer Science Engineering Jain University Bangalore India

Unstructured Numerical Image Dataset Separation (UNIDS) method employing an enhanced unsupervised clustering technique. The objective is to delineate an optimal number of distinct groups within the input grayscale (G-S) image content, utilizing the improved limited iteration agglomerative clustering (iLIAC) clustering technique for the separation and enhancement of picture elements. The UNIDS method is structured into two primary stages: partitioning and validation. In the partitioning stage, the UNIDS method identifies an appropriate number of discrete clusters within the grayscale image using the iLIAC technique, eliminating the need for predetermined procedures. Subsequently, the method evaluates the similarity and deviation among data elements within the same group in the resultant image dataset. Additionally, it assesses the proximity and inters severance among clusters in the outcome of the image dataset through the partitioning process. Empirical results indicate that the UNIDS system excels in the spontaneous identification of an optimal number of discrete clusters within the input G-S image. The system demonstrates superior thickness, reduced deviation among data elements within the same cluster, increased inter-separation, and diminished inter-closeness between cluster elements. Furthermore, empirical analysis establishes the superior performance of the UNIDS approach compared to existing clustering techniques. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Iterative methods

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BAAP-FIoT: Blockchain Assisted Authentication Protocol for Fog-enabled Internet of Things Environment

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IEEE Internet of Things Journal 2025年第11期12卷 15681-15696页

作者： Ponnuru, Raveendra Babu Kumar, Sathish A.P. Azab, Mohamed Alavalapati, Goutham Reddy Virginia Tech Virginia Military Institute and Computer Science Department of Computer and Information Science BlacksburgVA United States Cleveland State University Department of Electrical Engineering and Computer Science ClevelandOH44115 United States Virginia Military Institute Department of Computer Science and Information Sciences LexingtonVA24450 United States University of Illinois Springfield One University Plaza Department of Computer Science SpringfieldIL62703 United States

The proliferation of Internet of Things (IoT) devices across multiple domains has heralded an era of unprecedented connectivity and data exchange. Fog computing enhances edge-network processing, enabling real-time data analysis and prompt responses. However, ensuring secure and trustworthy communication among these devices remains a paramount concern. In fog-enabled IoT environments, securing communication among users,IoT devices, gateways, and fog nodes is of paramount importance to prevent unauthorized access and ensure data integrity and confidentiality. Additionally, users can control and deliver instructions to IoT devices remotely. Hence, we propose a blockchain-assisted authentication protocol tailored specifically for fog-enabled IoT environments to verify the user's identity prior to accessing the IoT devices. The proposed protocol leverages cutting-edge crypto primitives like elliptic curve cryptography, hash functions, and blockchain to establish secure communication between users and IoT devices. Furthermore, we evaluate the proposed scheme through formal (scyther) and informal analysis, demonstrating its efficacy in mitigating well-known attacks. On the other hand, the proposed protocol exhibits robustness against relevant protocols in terms of communication and computational aspects, as well as reliability for real-world fog-enabled IoT applications. © 2014 IEEE.

关键词： Authentication Protocol

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