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A semantic and emotion-based dual latent variable generation model for a dialogue system

CAAI Transactions on Intelligence Technology 2023年第2期8卷 319-330页

作者： Ming Yan Xingrui Lou Chien Aun Chan Yan Wang Wei Jiang State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijingChina School of Information and Communications Engineering Communication University of ChinaBeijingChina Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijingChina Department of Electrical and Electronic Engineering The University of MelbourneMelbourneVictoriaAustralia School of Data Science and Intelligent Media Communication University of ChinaBeijingChina

With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human *** emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate ***,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the *** propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional *** from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer ***,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and *** content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features ***,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the *** results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.

关键词： conditional variational autoencoder dual latent space emotional responses latent variable generation

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A Simple Open-loop Soft Startup Method Based on Operation Mode Analysis for LCC Converters Used in High-voltage DC Power Supply

A Simple Open-loop Soft Startup Method Based on Operation Mo...

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International Conference on Power Electronics and Motion control (IPEMC)

作者： Kai Zhang Hanyu Liu Kai Sun Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

LCC converters incorporate the stray parameters of high frequency transformer and are commonly employed as the initial stage of high-voltage DC power supplies, enhancing both efficiency and power density. However, the significant overshoot that occurs during the startup phase of high-voltage DC power supply poses considerable difficulties for the circuit. In this article, a simple open-loop soft startup control method is proposed: First, the operation mode analysis method is used to accurately solve the time-domain model of the LCC converter under different duty cycles in continuous current mode (CCM). Second, an open-loop variable duty cycle soft startup control strategy from the energy transmitted view is derived. Finally, soft startup process corresponding to different startup time requirements are verified on a 200V/20kV experimental prototype.

关键词： Analytical models Power system measurements Power supplies Prototypes High-voltage techniques Power electronics High-frequency transformers

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Fuzzy-Cycle: Visible to Infrared Ship Image Translation Based on CycleGAN 6

Fuzzy-Cycle: Visible to Infrared Ship Image Translation Base...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： He, Long Yu, Yue Liu, Chang Sun, Yangyang Jiang, Feng Hu, Xiaoning Pan, Chengwei Dong, Xiwang School of Artificial Intelli-gence Beihang University Beijing China Beijing Institute of Control and Electronic Technology Beijing China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University School of Artificial Intelligence Institute of Unmanned System Beijing China

ISBN: (纸本)9798350356618

Detecting targets in infrared ship images is crucial for various applications, such as maritime rescue and ship inspection. Training contemporary mainstream detection and segmentation models, however, requires large-scale, high-quality infrared ship image datasets. In open-world maritime confrontation scenarios, the complex and variable environment, scarcity of target ships, and limited acquisition conditions make it challenging to construct high-quality infrared ship image datasets. To address this issue, this paper proposes an unpaired visible-infrared ship image translation model based on CycleGAN, named Fuzzy-Cycle. The model introduces a fuzzy cycle loss to encourage the model to learn feature mapping rules between different domains while minimizing attention to unnecessary features. Additionally, the method employs U-Net as the generator network to retain shallow image features during upsampling and selects PatchGAN as the discriminator network, embedding Haar wavelet transform to enhance the discriminator's ability to analyze image frequency domain features. Experiments on the VAIS dataset demonstrate that the proposed algorithm outperforms mainstream unpaired image transfer models, showing excellent performance in the task of visible-infrared ship image translation. Furthermore, zero-shot image translation experiments on the HRSC2016 dataset prove the generalizability and reliability of the proposed method. © 2024 IEEE.

关键词： Wavelet transforms

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Indefinite metacavities coupled to a mirror:bound states in the continuum with anomalous resonance scaling

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Photonics Research 2024年第3期12卷 598-607页

作者： QIANG ZHANG PEIXIANG LI ZHIYUAN GU SHAODING LIU ZEJUN DUAN College of Electronic Information and Optical Engineering Taiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China

Indefinite metacavities(IMCs)made of hyperbolic metamaterials show great advantages in terms of extremely small mode volume due to large wave vectors endowed by the unique hyperbolic ***,quality(Q)factors of IMCs are limited by Ohmic loss of metals and radiative loss of leaked *** the fact that Ohmic loss of metals is inevitable in IMCs,the radiative loss can be further suppressed by leakage *** we propose a mirror coupled IMC structure which is able to operate at Fabry–Pérot bound states in the continuum(BICs)while the hyperbolic nature of IMCs is *** the BIC point,the radiative loss of magnetic dipolar cavity modes in IMCs is completely absent,resulting in a considerably increased Q factor(>90).Deviating from the BIC point,perfect absorption bands(>0.99)along with a strong near-field intensity enhancement(>1.8×10^(4))appear when the condition of critical coupling is almost *** proposed BICs are robust to the geometry and material composition of IMCs and anomalous scaling law of resonance is verified during the tuning of optical *** also demonstrate that the Purcell effect of the structure can be significantly improved under BIC and quasi-BIC regimes due to the further enhanced Q factor to mode volume *** results provide a new train of thought to design ultra-small optical nanocavities that may find many applications benefitting from strong light–matter interactions.

关键词： hyperbolic mirror definite

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In-depth analysis of core-shell filaments in nonvolatile NbO_(x) memristive device as an artificial synapse for multifunctional bionic applications

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Science China(Technological Sciences) 2023年第12期66卷 3596-3603页

作者： JIANG Bei KE ShanWu TAO ZiPei JIN YaoYao MENG JiaHao SONG XingJuan XIAO YongYue JIANG Li WANG JinZhao CHEN Yong LI YueBin WEN Xin YE Cong School of Microelectronics Key Laboratory of Intelligent Sensing System and SecurityMinistry of EducationHubei UniversityWuhan 430062China Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and TechnologyWuhan 430074China School of Science Hubei University of TechnologyWuhan 430068China Faculty of Chemical Technology and Engineering West Pomeranian University of Technology in SzczecinSzczecin 71-065Poland

As a key building block of the biological cortex,synapses are powerful information processing units that enable highly complex nonlinear *** realization of artificial synapses with similar capabilities has important implications for building intelligent,neuromorphic ***,we demonstrate an artificial synapse based on NbO_(x) nonvolatile memristor to mimic multifunctional bionic applications such as nociceptor and associative *** experimental characterization with COMSOL simulation,the traditional resistance switching characteristics,which are the decisive factor for the synapse properties are in-depth *** can be proposed that the I-V characteristics of Pt/NbO_(x)/TiN memristor are governed by core-shell filaments consisting of the shell region of sub-stoichiometric Nb_(2)O_(5-δ)and the core of NbO_(2).On the basis of the core-shell filament model,it can be reasonably explained that Ohmic conduction and Poole-Frenkel conduction take turns to dominate the current flowing in the memristive device,leading to the zigzag evolution of current during the operation process of NbO_(x)-based *** simulations of synaptic plasticity,including long-term potentiation/depression(LTP/LTD),paired-pulse facilitation(PPF),and spike-timing-dependent plasticity(STDP),exhibiting that the NbO_(x) can be utilized for an artificial ***,bionic functions such as hyperalgesia and allodynia of a nociceptor and a series of associative learning behaviors in Pavlovian dog experiment are mimicked,illustrating that the Pt/NbO_(x)/TiN have great potential for highly simplified artificial neural network applications.

关键词： memristor core-shell filament synaptic plasticity nociceptor associative learning

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Approximately Invertible Neural Network for Learned Image Compression

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IEEE Transactions on Image Processing 2025年 34卷 3041-3055页

作者： Gao, Yanbo Li, Shuai Fu, Meng Lv, Chong Yang, Zhiyuan Cai, Xun Yuan, Hui Ye, Mao Shandong University School of Software Jinan250100 China Shandong University-WeiHai Research Institute of Industrial Technology Shandong University Weihai264209 China Shandong University School of Control Science and Engineering Jinan250100 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250100 China University of Electronic Science and Technology of China Sichuan Chengdu611731 China

Learned image compression has attracted considerable interests in recent years. An analysis transform and a synthesis transform, which can be regarded as coupled transforms, are used to encode an image to latent feature and decode the feature after quantization to reconstruct the image. Inspired by the success of invertible neural networks in generative modeling, invertible modules can be used to construct the coupled analysis and synthesis transforms. Considering the noise introduced in the feature quantization invalidates the invertible process, this paper proposes an Approximately Invertible Neural Network (A-INN) framework for learned image compression. It formulates the rate-distortion optimization in lossy image compression when using INN with quantization, which differentiates from using INN for generative modelling. Generally speaking, A-INN can be used as the theoretical foundation for any INN based lossy compression method. Based on this formulation, A-INN with a progressive denoising module (PDM) is developed to effectively reduce the quantization noise in the decoding. Moreover, a Cascaded Feature Recovery Module (CFRM) is designed to learn high-dimensional feature recovery from low-dimensional ones to further reduce the noise in feature channel compression. In addition, a Frequency-enhanced Decomposition and Synthesis Module (FDSM) is developed by explicitly enhancing the high-frequency components in an image to address the loss of high-frequency information inherent in neural network based image compression, thereby enhancing the reconstructed image quality. Extensive experiments demonstrate that the proposed A-INN framework achieves better or comparable compression efficiency than the conventional image compression approach and state-of-the-art learned image compression methods. © 1992-2012 IEEE.

关键词： Image coding

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A Low-complexity Decision Variables Classification Brainstorm Optimization Algorithm

A Low-complexity Decision Variables Classification Brainstor...

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2024 International Conference on Applied Mathematics, Modelling and Statistics Application, AMMSA 2024

作者： Li, Qiyue Qiu, Lipeng Zhou, Aoran Wu, Yali Wang, Ziren Department of Information and Control Engineering Xi'An University of Technolog Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd. Xi'an710016 China

In the complex optimization scenarios of real life, we often need to not only weigh the conflicts between multi-objectives but also face the challenges brought by large-scale decision variables. When the scale of decision variables increases sharply, the search space will expand exponentially, which makes it difficult for the algorithm to traverse the whole search space under limited resources, so that the number of local optimal solutions increases sharply. The so-called 'dimension disaster' appears. To effectively deal with this problem, this paper proposes a large-scale multi-objective brainstorm optimization algorithm (LMaOBSO) based on low complexity decision variable classification method and improved penalty boundary intersection strategy. The algorithm uses a low-complexity tree sorting variable classification method to divide the decision variables into converges and diversity variables quickly. At the same time, the convergent variables are optimized by the improved penalty boundary crossover strategy to solve the problems existing in large-scale optimization problems. © Published under licence by IOP Publishing Ltd.

关键词： Disasters

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A New Island Genetic Algorithm for Path Planning Problems *

A New Island Genetic Algorithm for Path Planning Problems *

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhang, Jinghao Chen, Zhe Li, Ning Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9798350327182

Genetic algorithm (GA) is an effective method for path planning problems. As a powerful variant of GA, island genetic algorithm (IGA) has considerable improvement in performance. In this paper, a new island model of GA is proposed to avoid the premature phenomenon and achieve better efficiency. First, a new method of creating subpopulations is presented based on K-means to expand the searching area for the optima. Meanwhile, recombining subpopulations is proposed as a new strategy to improve the diversity of populations and save computational time. Moreover, a method is designed based on Monte Carlo sampling to handle the uncertainty of maps. Comparative experiments are presented to verify the efficiency of the proposed algorithm. Then, a proper number of samples is found by simulation to balance the accuracy and the time cost of Monte Carlo sampling. © 2023 IEEE.

关键词： Genetic algorithms

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Quantum gyroscopes based on double-mode surface-acoustic-wave cavities

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Physical Review Applied 2024年第1期22卷 014061-014061页

作者： Yuting Zhu Shibei Xue Fangfang Ju Haidong Yuan Department of Automation Key Laboratory of System Control and Information Processing Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 People’s Republic of China School of Physics and Electronics Department of Mechanical and Automation Engineering

Recent progress shows that a surface-acoustic-wave (SAW) cavity can not only induce quantum acoustic dynamics, but can also form optomechanical-like systems. Its operating frequencies in the microwave band make it resistant to the thermal noise of surrounding environments, while its radiation-pressure couplings make it susceptible to weak forces. Based on these advantages, we propose a gyroscope comprising coupled microwave-SAW cavities. In this paper we systematically consider the range, signal-to-noise ratio, and sensitivity, which are the three most important indices to gyroscopes, but only partially considered in existing works. Additionally, we establish the fundamental limits of sensitivity when the quantum input is in the vacuum state and the squeezed vacuum state. We find that squeezing improves sensitivity and can surpass the standard quantum limit. However, this improvement can only reach up to 2/2 even as the squeezed parameter approaches infinity, which is rarely noted in recent works. Finally, we also offer analytical constraints for cooperativity and squeezed parameters. These constraints can be utilized to design gyroscopes based on coupled cavities in experiments.

关键词： Open quantum systems & decoherence Quantum sensing Rotation sensing Coupled oscillators Cavity resonators Homodyne & heterodyne detection Microwave techniques Surface acoustic wave

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Hierarchical reinforcement learning guidance with threat avoidance

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Journal of systems engineering and Electronics 2022年第5期33卷 1173-1185页

作者： LI Bohao WU Yunjie LI Guofei State Key Laboratory of Virtual Reality Technology and System Beihang UniversityBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Science and Technology on Aircraft Control Laboratory Beijing 100191China School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China

The guidance strategy is an extremely critical factor in determining the striking effect of the missile operation.A novel guidance law is presented by exploiting the deep reinforcement learning(DRL)with the hierarchical deep deterministic policy gradient(DDPG)*** reward functions are constructed to minimize the line-of-sight(LOS)angle rate and avoid the threat caused by the opposed *** attenuate the chattering of the acceleration,a hierarchical reinforcement learning structure and an improved reward function with action penalty are put *** simulation results validate that the missile under the proposed method can hit the target successfully and keep away from the threatened areas effectively.

关键词： guidance law deep reinforcement learning(DRL) threat avoidance hierarchical reinforcement learning

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