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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Sun, Yang Wu, Jiayang Li, Yang Ren, Guanghui Tan, Mengxi Xu, Xingyuan Corcoran, Bill Chu, Sai Tak Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Integrated Photonics and Applications Centre School of Engineering RMIT University MelbourneVIC3000 Australia School of Electronic and Information Engineering Beihang University Beijing100191 China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC Australia Department of Physics City University of Hong Kong Hong Kong QXP Technology Inc. Xi'an China INRS - Énergie Matériaux et Télécommunications VarennesQCJ3X 1S2 Canada

ISBN: (纸本)9781957171395

We experimentally implement microcomb-based microwave photonic transversal signal processors and test their accuracy for differentiation, integration, and Hilbert transform. A global picture quantifying the impact of different error sources on the overall performance is provided. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Microwave photonics

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Feedback control in RF photonic transversal filter systems based on optical microcombs

Feedback control in RF photonic transversal filter systems b...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Li, Yang Wu, Jiayang Sun, Yang Ren, Guanghui Tan, Mengxi Xu, Xingyuan Corcoran, Bill Chu, Sai Tak Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Integrated Photonics and Applications Centre School of Engineering RMIT University MelbourneVIC3000 Australia School of Electronic and Information Engineering Beihang University Beijing100191 China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC Australia Department of Physics City University of Hong Kong Hong Kong QXP Technology Inc. Xi'an China INRS - Énergie Matériaux et Télécommunications VarennesQCJ3X 1S2 Canada

ISBN: (纸本)9781957171395

We propose and experimentally demonstrate four different feedback control methods employed in microcomb-based RF photonic transversal filter systems to enhance their accuracy and stability. Detailed characterizations are carried out to compare the performance of different methods. © Optica Publishing Group 2024 © 2024 The Author (s)

关键词： Transversal filters

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Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection

arXiv

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arXiv 2025年

作者： Li, Yong Liu, Menglin Cui, Zhen Ding, Yi Zong, Yuan Zheng, Wenming Shan, Shiguang Guan, Cuntai School of Computer Science and Engineering The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Nanjing210096 China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China School of Artificial Intelligence Beijing Normal University Beijing100875 China Key Laboratory of AI Safety Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Key Laboratory of Child Development and Learning Science of Ministry of Education School of Biological Science and Medical Engineering Nanjing210096 China

Despite the impressive performance of current vision-based facial action unit (AU) detection approaches, they are heavily susceptible to the variations across different domains and the cross-domain AU detection methods are under-explored. In response to this challenge, we propose a decoupled doubly contrastive adaptation (D2CA) approach to learn a purified AU representation that is semantically aligned for the source and target domains. Specifically, we decompose latent representations into AU-relevant and AU-irrelevant components, with the objective of exclusively facilitating adaptation within the AU-relevant subspace. To achieve the feature decoupling, D2CA is trained to disentangle AU and domain factors by assessing the quality of synthesized faces in cross-domain scenarios when either AU or domain attributes are modified. To further strengthen feature decoupling, particularly in scenarios with limited AU data diversity, D2CA employs a doubly contrastive learning mechanism comprising image and feature-level contrastive learning to ensure the quality of synthesized faces and mitigate feature ambiguities. This new framework leads to an automatically learned, dedicated separation of AU-relevant and domain-relevant factors, and it enables intuitive, scale-specific control of the cross-domain facial image synthesis. Extensive experiments demonstrate the efficacy of D2CA in successfully decoupling AU and domain factors, yielding visually pleasing cross-domain synthesized facial images. Meanwhile, D2CA consistently outperforms state-of-the-art cross-domain AU detection approaches, achieving an average F1 score improvement of 6%-14% across various cross-domain scenarios. © 2025, CC BY-NC-SA.

关键词： Contrastive Learning

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An Authenticated Method for a Secure Changing Password

An Authenticated Method for a Secure Changing Password

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Electronic engineering, Information Technology & Education (EEITE), International Conference in

作者： Mostefa Kara Konstantinos Karampidis Laid Kenioua Manolis Karampidis Muath AlShaikh Giorgos Papadourakis Abdelkader Laouid Scientific and Technology Hub of Sidi Abdellah National Higher School of Mathematics Algiers Algeria Department of Electrical and Computer Engineering Hellenic Mediterranean University Crete Greece LIAP Laboratory El Oued University El Oued Algeria Computer Science Department College of Computing and Informatics Saudi Electronic University Riyadh Kingdom of Saudi Arabia

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

Despite their age, passwords are still widely used more than ever. In many cases, it is the solution that best fits the usage scenario. Researchers are proposing innovative designs and methods to support these scenarios. Many systems, especially sensitive ones, need to change the password. Classic systems rely on changing passwords in two stages, the first i s authentication, which usually consists of two or three rounds, and the second is creating a new password (PW), which also consists of two or three rounds. In this paper, a hidden transmission of a new random PW using the previous one is presented, we talk about an authenticated changing of PW. The verifier g enerates half of the new password and sends it to the prover, the prover authenticates the sent message using the old PW and then returns the authentication proof. After checking it, the verifier creates the second half of the PW. The proposed method combines the authentication and change PW processes into one process consisting of 3 rounds. Therefore, the proposal facilitates the process of automatic periodic change of PW between two entities (user, app, system, etc). Analysis and experiments show that our technique is robust, lightweight, and reduces many potential risks in the field.

关键词： Design methodology Education Authentication Passwords Proposals

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Exact solution of the longitudinally-graded rectangular plate under mixed instantaneous shock loading

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Waves in Random and Complex Media 2023年

作者： Amari, Abdelfattah Salman, Hayder Mahmood Department of Chemical Engineering College of Engineering King Khalid University Abha Saudi Arabia Research Laboratory of Processes Energetics Environment and Electrical Systems National School of Engineers of Gabes Gabes University Gabes Tunisia Department of Computer Science Al-Turath University College Baghdad Iraq

This study follows a novel path toward analysis of the thermoelastic reaction of the longitudinally-graded graphene-nanoplates enriched composite (LG-GNPEC) rectangular-shaped plates exposed to the mixed-form instantaneous shock. Three-dimensional form of the linear thermoelasticity theory is picked as the base for establishing the governing equations. Lord-Shulman theorem and energy balance relations are employed to determine the time-dependency of the system’s behavior. Due to simply-supported boundary conditions, solving the governing equations through an analytical solution on the bases of Navier’s approach is performed. Accuracy of the applied methods is verified by comparing the obtained results with those presented in the published studies. Results of this research can be directly considered in the analysis of the thermoelastic behavior of the advanced composite materials exposed to the mixed-form thermomechanical shocks. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Graphene

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Maximizing the accuracy of microcomb-based microwave photonic transversal signal processors

Maximizing the accuracy of microcomb-based microwave photoni...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Microwave photonics

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Command filtered and observer-based adaptive neural event-triggered control for fractional-order nonlinear systems with actuator fault

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Communications in Nonlinear Science and Numerical Simulation 2025年 149卷

作者： You, Xingxing Pu, Yifei Zou, Yanli Tang, Zixin Zhao, Tao Dian, Songyi College of Electrical Engineering Sichuan University Chengdu610065 China Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips Guangxi Normal University Guilin541004 China College of Computer Science Sichuan University Chengdu610065 China College of Electronic Engineering Guangxi Normal University Guilin541004 China School of Computing and Artificial Intelligence Southwest University of Finance and Economics Chengdu611130 China

This paper investigates the tracking control problem for the uncertain fractional-order nonlinear systems (FONSs) with unmeasured states and unknown control gain subject to external disturbances and actuator fault, under restricted communication resources. First, the radial basis function neural networks (RBF NNs) are deployed to identify the unknown smooth nonlinear function. Subsequently, a neural network-based state observer is constructed based on this identification to estimate the unknown states of the original FONS. Then, an adaptive neural event-triggered fault-tolerant controller (ANETFTC) is developed by adopting the backstepping method, fractional-order command filter (FOCF) and Lyapunov stability theory. In the event of external disturbances and actuator fault, the designed ANETFTC not only ensures the tracking performance of uncertain FONS so that the tracking error can converge to a neighborhood near the origin but also the observer designed based on this controller can better approximate the original system states. Simulation analysis further verifies the effectiveness and availability of control strategy. © 2025 Elsevier B.V.

关键词： State estimation

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Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

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computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP DDoS attack

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Utterance as A Bridge: Few-shot Joint Learning of Empathy Detection and Empathy Intent Classification

Utterance as A Bridge: Few-shot Joint Learning of Empathy De...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Liting Jiang Di Wu Zhe Li Shuangyong Song Yanbing Li Hao Huang School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Multi-Lingual Information Technology Urumqi China Institute of Artificial Intelligence (TeleAI) China Telecom Corp Ltd Beijing China Department of Electrical and Electronic Engineering Hong Kong Polytechnic University Hong Kong China Department of Electrical Engineering Stanford University USA Joint International Research Laboratory of Silk Road Multilingual Cognitive Computing Urumqi China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Empathy detection (ED) and empathy intent classification (EIC) aim to identify the empathy direction expressed in user utterances and the underlying empathy intent behind them. Previous studies show that facilitating information transfer between tasks can enhance model performance. However, the interaction between ED and EIC in few-shot learning remains underexplored. To this end, we identify the challenges in jointly training ED and EIC in a few-shot setting: establishing effective information transfer between them and improving the model’s generalization capability. We propose a novel model called USB. For information transfer, the interactive module maps empathy and empathy intent labels through utterances to model task correlations. For generalization capability, after capturing empathy and empathy intent representations with an adaptive fusion module, we introduce a multi-level contrastive learning strategy to optimize representations at task and label levels, enhancing generalization. Experimental results on two public datasets show that our model outperforms all baselines.

关键词： Training Bridges Adaptation models Intent recognition Focusing Contrastive learning Signal processing Universal Serial Bus Few shot learning Speech processing

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Robust Fault Estimation for Wind Turbine Pitch and Drive systems

SSRN

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SSRN 2023年

作者： Azizi, Abdesamia Youssef, Tewfik Kouadri, Abdelmalek Mansouri, Majdi Mimouni, Mohamed Fouzi Signals and Systems Laboratory Institute of Electrical and Electronic Engineering University M’Hamed Bougara of Boumerdes Boumerdes35000 Algeria Electrical and Computer Engineering Program Texas A and M University at Qatar Doha23874 Qatar " National School of Engineers of Monastir University of Monastir Monastir5019 Tunisia

In this paper, a novel fault estimator for wind turbine pitch and drive train system is proposed. The main objective is to estimate actuator and sensor faults along with the system states while mitigating the impact of process disturbances and noises. To accomplish this, an augmented state is created by combining the states of the system and faults. Subsequently, an Unknown Input Observer (UIO) is developed to estimate them simultaneously. The UIO matrices are acquired by optimizing a multi-objective function formed by transforming state and fault estimation errors into the frequency domain using a genetic algorithm. Compared with H∞, the proposed technique shows great superiority in accurately estimating various faults of actuators and sensors. © 2023, The Authors. All rights reserved.

关键词： Wind turbines

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