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1st International Conference on Quantum Communications, Networking, and Computing, QCNC 2024

作者： Ju, Keyi Qin, Xiaoqi Zhong, Hui Zhang, Xinyue Pan, Miao Liu, Baoling State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China University of Houston Department of Electrical and Computer Engineering HoustonTX77204 United States Kennesaw State University Department of Computer Science MariettaGA30060 United States

ISBN: (纸本)9798350366778

Quantum computing changes the way of solving complex problems and handling vast datasets. The introduction of quantum search algorithms, notably Grover's algorithm, addresses the inefficiencies of classical search methods in handling vast datasets by offering substantial speed improvements. However, an inherent aspect of quantum searches is their failure probability. This paper aims to explore the relationship between the failure probability in Grover's algorithm and the privacy guarantees of differential privacy (DP). We further investigate the impact of several quantum circuit parameters, including the number of shots, the number of solutions within the dataset, and circuit noise levels, on this failure probability. Our analysis demonstrates the indirect connection between these quantum circuit elements and the privacy guarantees of DP. Through Monte Carlo simulations, we offer an in-depth analysis that paves the way for secure and faster data querying methods. © 2024 IEEE.

关键词： Differential privacy

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Chip-scale spontaneous quasi-phase matched second harmonic generation in a micro-racetrack resonator

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science China(Physics,Mechanics & Astronomy) 2023年第8期66卷 66-74页

作者： Tingge Yuan Jiangwei Wu Yi'an Liu Xiongshuo Yan Haowei Jiang Hao Li Zhaokang Liang Qiang Lin Yuping Chen Xianfeng Chen State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy.Shanghai Jiao Tong UniversityShanghai 200240China Collaborative Innovation Center of Light Manipulations and Applications Shandong Normal UniversityJinan 250358China Department of Electrical and Computer Engineering University of RochesterNew York 14627USA

In this paper,we demonstrate efficient spontaneous quasi-phase matched(SQPM)second harmonic generation(SHG)in a microracetrack resonator on X-cut thin film lithium *** approach does not involve poling,but exploits the anisotropy of the crystals to allow the phase-matching condition to be fulfilled spontaneously as the TE-polarized light circulates in a specifically designed racetrack *** experiment,normalized on-chip conversion efficiencies of 1.01×10-4/W and 0.43×10-4/W are achieved by 37th-order and 111th-order SQPM,*** configurable SQPM will benefit the application of nonlinear frequency conversion and quantum source generation in chip-scale integrated photonics compatible with standard CMOS fabrication processes.

关键词： lithium niobate on insulator quasi-phase matching second harmonic generation

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Improving Multiple Sclerosis Disease Prediction Using Hybrid Deep Learning Model

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computers, Materials & Continua 2024年第10期81卷 643-661页

作者： Stephen Ojo Moez Krichen Meznah A.Alamro Alaeddine Mihoub Gabriel Avelino Sampedro Jaroslava Kniezova Department of Electrical and Computer Engineering College of EngineeringAnderson UniversityAndersonSC 29621USA Faculty of Computing and Information Al-Baha UniversityAl-Baha65528Saudi Arabia ReDCAD Laboratory University of SfaxSfax3038Tunisia Department of Information Technology College of Computer&Information SciencePrincess Nourah Bint Abdul Rahman UniversityRiyadh11564Saudi Arabia Department of Management Information Systems College of Business and EconomicsQassim UniversityP.O.Box 6640Buraidah51452Saudi Arabia School of Management and Information Technology De La Salle-College of Saint BenildeManila1004Philippines Department of Information Management and Business Systems Faculty of ManagementComenius University BratislavaBratislava 2582005Slovakia

Myelin damage and a wide range of symptoms are caused by the immune system targeting the central nervous system in Multiple Sclerosis(MS),a chronic autoimmune neurological *** disrupts signals between the brain and body,causing symptoms including tiredness,muscle weakness,and difficulty with memory and *** methods for detecting MS are less precise and time-consuming,which is a major gap in addressing this *** gap has motivated the investigation of new methods to improve MS detection consistency and *** paper proposed a novel approach named FAD consisting of Deep Neural Network(DNN)fused with an Artificial Neural Network(ANN)to detect MS with more efficiency and accuracy,utilizing regularization and combat *** use gene expression data for MS research in the GEO GSE17048 *** dataset is preprocessed by performing encoding,standardization using min-max-scaler,and feature selection using Recursive Feature Elimination with Cross-Validation(RFECV)to optimize and refine the ***,for experimenting with the dataset,another deep-learning hybrid model is integrated with different ML models,including Random Forest(RF),Gradient Boosting(GB),XGBoost(XGB),K-Nearest Neighbors(KNN)and Decision Tree(DT).Results reveal that FAD performed exceptionally well on the dataset,which was evident with an accuracy of 96.55%and an F1-score of 96.71%.The use of the proposed FAD approach helps in achieving remarkable results with better accuracy than previous studies.

关键词： Multi Sclerosis(MS) machine learning deep learning artificial neural network healthcare

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Wireless Federated Learning Over Resource-Constrained Networks: Digital Versus Analog Transmissions

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IEEE Transactions on Wireless Communications 2024年第10期23卷 14020-14036页

作者： Yao, Jiacheng Xu, Wei Yang, Zhaohui You, Xiaohu Bennis, Mehdi Poor, H. Vincent Southeast University Nanjing210096 China Zhejiang Laboratory Hangzhou311121 China The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Center for Wireless Communications Oulu University Oulu90014 Finland The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

To enable wireless federated learning (FL) in communication resource-constrained networks, two communication schemes, i.e., digital and analog ones, are effective solutions. In this paper, we quantitatively compare these two techniques, highlighting their essential differences as well as respectively suitable scenarios. We first examine both digital and analog transmission schemes, together with a unified and fair comparison framework under imbalanced device sampling, strict latency targets, and transmit power constraints. A universal convergence analysis under various imperfections is established for evaluating the performance of FL over wireless networks. These analytical results reveal that the fundamental difference between the digital and analog communications lies in whether communication and computation are jointly designed or not. The digital scheme decouples the communication design from FL computing tasks, making it difficult to support uplink transmission from massive devices with limited bandwidth and hence the performance is mainly communication-limited. In contrast, the analog communication allows over-the-air computation (AirComp) and achieves better spectrum utilization. However, the computation-oriented analog transmission reduces power efficiency, and its performance is sensitive to computation errors from imperfect channel state information (CSI). Furthermore, device sampling for both schemes are optimized and differences in sampling optimization are analyzed. Numerical results verify the theoretical analysis and affirm the superior performance of the sampling optimization. © 2002-2012 IEEE.

关键词： Channel state information

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Reduced-Complexity Approach for Opacity Enforcement Based on Extended Insertion Functions with Limited Insertion Events 20

Reduced-Complexity Approach for Opacity Enforcement Based on...

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20th IEEE International Conference on Networking, Sensing and Control, ICNSC 2023

作者： Li, Xiaoyan Hadjicostis, Christoforos N. Li, Zhiwu North University of China School of Information and Communication Engineering Taiyuan China University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Macau University of Science and Technology Institute of Systems Engineering China

ISBN: (纸本)9798350369502

Opacity is a security and privacy property that guarantees predefined secret behavior of a cyber-physical system will not be inferred with certainty by a malicious entity. If a system is opacity-violating, extended insertion functions that insert fake symbols can be implemented to enforce opacity. By constricting the ways in which the fake symbols are inserted, this paper addresses opacity enforcement under the framework of finite state automata using extended insertion functions under event insertion constraints and limited insertion events constraints, i.e., only a limited number of symbols in a specified set can be inserted before and after an actual system output. The notion of (kb,ka)-EIC-enforceability is proposed to describe how to enforce opacity via extended insertion functions in the presence of both event insertion constraints and limited insertion events constraints. A necessary and sufficient condition to check (kb,ka)-EIC-enforceability is derived by constructing an appropriate verifier. © 2023 IEEE.

关键词： Opacity

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Clutter and Ambiguity Reduction Using 3-Dimensional Side-Looking Synthetic Aperture Radar

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Progress In Electromagnetics Research B 2023年 102卷 115-130页

作者： Kelly, Colin D. Dogaru, Traian V. Gallagher, Kyle A. Le, Calvin D. Phelan, Brian R. Narayanan, Ram M. The Department of Electrical Engineering and Computer Science The Pennsylvania State University University Park PA16802 United States The U.S. Army Combat Capabilities Development Command Army Research Laboratory AdelphiMD20783 United States

Advancement in radar component technology has led to a reduction in the size, weight, and power consumption of radar systems. Experimental radar systems can now be integrated onto smaller, maneuverable platforms, such as small unmanned aerial vehicles (sUAVs). Integration onto rotor-based sUAVs enables data collection over novel synthetic apertures which can be optimized for different scenarios. The design, simulation, and experimentation of a light-weight, ultra-wideband synthetic aperture radar (SAR) is presented here that will be used for the detection of obscured surface targets. The approach outlined herein uses 3-dimensional (3-D) imagery to vertically resolve clutter from the target. A vertical-grid aperture is presented which yields vertical resolution. Point spread functions are derived for both linear and vertical-grid apertures. The analytical expressions are verified using simulations. Finally, experimental data is used to form 3-D imagery and demonstrate the importance of vertical resolution in the discrimination between scatterers above the ground, as well as clutter mitigation. © (2023). All Rights Reserved.

关键词： Synthetic aperture radar

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Spotted Hyena Optimizer with Deep Learning Driven Cybersecurity for Social Networks

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computer systems science & engineering 2023年第5期45卷 2033-2047页

作者： Anwer Mustafa Hilal Aisha Hassan Abdalla Hashim Heba G.Mohamed Lubna A.Alharbi Mohamed K.Nour Abdullah Mohamed Ahmed S.Almasoud Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversityTabuk47512Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMecca24382Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityRiyadh12435Saudi Arabia

Recent developments on Internet and social networking have led to the growth of aggressive language and hate *** provocation,abuses,and attacks are widely termed cyberbullying(CB).The massive quantity of user generated content makes it difficult to recognize *** advancements in machine learning(ML),deep learning(DL),and natural language processing(NLP)tools enable to detect and classify CB in social *** this view,this study introduces a spotted hyena optimizer with deep learning driven cybersecurity(SHODLCS)model for *** presented SHODLCS model intends to accomplish cybersecurity from the identification of CB in the *** achieving this,the SHODLCS model involves data pre-processing and TF-IDF based feature *** addition,the cascaded recurrent neural network(CRNN)model is applied for the identification and classification of ***,the SHO algorithm is exploited to optimally tune the hyperparameters involved in the CRNN model and thereby results in enhanced classifier *** experimental validation of the SHODLCS model on the benchmark dataset portrayed the better outcomes of the SHODLCS model over the recent approaches.

关键词： Cybersecurity cyberbullying online social network deep learning spotted hyena optimizer

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IAACS: Image aesthetic assessment through color composition and space formation

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Virtual Reality & Intelligent Hardware 2023年第1期5卷 42-56页

作者： Bailin YANG Changrui ZHU Frederick WBLI Tianxiang WEI Xiaohui LIANG Qingxu WANG School of Computer and Information Engineering Zhejiang Gongshang UniversityHangzhou 310018China Department of Computer Science University of DurhamDH13LEUnited Kingdom College of Intelligence and Computing Tianjin UniversityTianjin 300072China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China

Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.

关键词： Image aesthetic assessment Color composition Space formation Deep learning

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Switching Loss Reduction on Cascaded H-Bridge Converter with Diode Clamped Transformer Grounding Scheme 10

Switching Loss Reduction on Cascaded H-Bridge Converter with...

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10th IEEE Workshop on Wide Bandgap Power Devices and Applications, WiPDA 2023

作者： Gao, Zihan Chen, Ruirui Li, Dingrui Wang, Fred University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350337136

Parasitic capacitance of dc/dc transformers interfacing the cascaded H-Bridge (CHB) converter can introduce extra switching losses. A switching loss reduction method with diode clamped grounding for dc/dc transformers connecting CHB is proposed in this paper. The transformer grounding is connected to diode clamping circuit on the low voltage dc link to partially cancel the voltage charging/discharging the parasitic capacitances. Simulation and test have been demonstrated that the proposed method has reduced 53% of the parasitics induced loss and \sim 6% of the total converter loss in the setup with one simple diode half-bridge clamping circuit added on each converter cell. © 2023 IEEE.

关键词： Diodes

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An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design 13

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Hong, Wenjing Chen, Cheng Zhu, Zexuan Tang, Ke Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9798350308365

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA Design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design. © 2024 IEEE.

关键词： Vaccines

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