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A Fully Distributed Approach to Optimal Energy Scheduling of Users and Generators Considering a Novel Combined Neurodynamic Algorithm in Smart Grid

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IEEE/CAA Journal of Automatica Sinica 2021年第7期8卷 1325-1335页

作者： Chentao Xu Xing He the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China

A fully distributed microgrid system model is presented in this *** the user side,two types of load and plug-in electric vehicles are considered to schedule energy for more *** charging and discharging states of the electric vehicles are represented by the zero-one variables with more *** solve the nonconvex optimization problem of the users,a novel neurodynamic algorithm which combines the neural network algorithm with the differential evolution algorithm is designed and its convergence speed is faster.A distributed algorithm with a new approach to deal with the inequality constraints is used to solve the convex optimization problem of the generators which can protect their *** results and comparative experiments show that the model and algorithms are effective.

关键词： Differential evolution algorithm distributed algorithm electric vehicle neural network zero-one variable.

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UNRAVELING THE ENIGMA OF DOUBLE DESCENT: AN IN-DEPTH ANALYSIS THROUGH THE LENS OF LEARNED FEATURE SPACE 12

UNRAVELING THE ENIGMA OF DOUBLE DESCENT: AN IN-DEPTH ANALYSI...

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12th International Conference on Learning Representations, ICLR 2024

作者： Gu, Yufei Zheng, Xiaoqing Aste, Tomaso School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing China Department of Computer Science University College London United Kingdom

Double descent presents a counter-intuitive aspect within the machine learning domain, and researchers have observed its manifestation in various models and tasks. While some theoretical explanations have been proposed for this phenomenon in specific contexts, an accepted theory for its occurring mechanism in deep learning remains yet to be established. In this study, we revisit the phenomenon of double descent and demonstrate that the presence of noisy data strongly influences its occurrence. By comprehensively analysing the feature space of learned representations, we unveil that double descent arises in imperfect models trained with noisy data. We argue that while small and intermediate models before the interpolation threshold follow the traditional bias-variance trade-off, over-parameterized models interpolate noisy samples among robust data thus acquiring the capability to separate the information from the noise. The source code is available at https://***/Yufei-Gu-451/double_descent_***. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Economic and social effects

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Research on Tibetan-Chinese Neural Machine Translation Integrating Statistical Method 6

Research on Tibetan-Chinese Neural Machine Translation Integ...

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6th International Conference on Machine Learning and Natural Language processing, MLNLP 2023

作者： Zhou, Maoxian The Computer College of Qinghai Normal University Qinghai Xining810016 China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Qinghai Xining810008 China Qinghai Engineering and Technology Research Center for Tibetan Information Processing Qinghai Xining810008 China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Xining810008 China

ISBN: (纸本)9798400709241

In recent years, with the emergence of deep learning methods, Neural Machine Translation has become a new research direction of machine translation. Due to the scarcity of digital resources in Tibetan, there is only a small-scale Tibetan-Chinese bilingual parallel corpus to train translation models. In the case of insufficient resources, the performance of Neural Machine Translation decreases significantly. In this regard, considering that the word alignment results in Tibetan-Chinese Statistical Machine Translation are better, and the alignment information in Tibetan-Chinese Neural Machine Translation model is significantly different from that in Tibetan-Chinese Statistical Machine Translation, this paper proposes a Tibetan-Chinese Neural Machine Translation method that integrates statistical methods. We using Statistical Machine Translation method to generate word alignment information of Tibetan-Chinese parallel corpus to supervise the training process of Tibetan-Chinese Neural Machine Translation model to make the model achieve more accurate translation and alignment effect. Experimental results show that this method can effectively improve translation quality in low resource environment. © 2023 ACM.

关键词： Neural machine translation

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Text Guided Road Marking Point Cloud Completion 6

Text Guided Road Marking Point Cloud Completion

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6th International Conference on Next Generation Data-Driven Networks, NGDN 2024

作者： He, Xu Xu, Qihong Luo, Huan Fuzhou University College of Computer and Data Science Fuzhou China Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

ISBN: (纸本)9798350388374

With the continuous development of intelligent transportation technologies such as autonomous driving and navigation, accurate perception of road markings becomes crucial. However, due to limitations in sensor perspectives and obstacles blocking the view, the scanned point cloud of road markings is often incomplete, potentially leading to erroneous decisions in intelligent transportation systems. Therefore, it becomes imperative to recover complete road markings from these incomplete point clouds. This paper proposes a text-guided road marking completion method, which integrates text information with point cloud data using attention mechanisms. By leveraging text information to guide the network in completing road marking point clouds, the proposed method aims to enhance the perception accuracy and completeness of road markings. Experimental validation on road marking datasets demonstrates the effectiveness and feasibility of the proposed approach. © 2024 IEEE.

关键词： Road and street markings

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Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification

Knowledge-Data Fusion Based Source-Free Semi-Supervised Doma...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Peng, Ruimin An, Jiayu Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781665410205

Electroencephalogram (EEG)-based seizure sub-type classification enhances clinical diagnosis efficiency. Source-free semi-supervised domain adaptation (SF-SSDA), which transfers a pre-trained model to a new dataset with no source data and limited labeled target data, can be used for privacy-preserving seizure subtype classification. This paper considers two challenges in SF-SSDA for EEG-based seizure subtype classification: 1) How to effectively fuse both raw EEG data and expert knowledge in classifier design? 2) How to align the source and target domain distributions for SF-SSDA? We propose a Knowledge-Data Fusion based SF-SSDA approach, KDF-MutuaISHOT, for EEG-based seizure subtype classification. In source model training, KDF uses Jensen-Shannon Diver-gence to facilitate mutual learning between a feature-driven Decision Tree-based model and a data-driven Transformer-based model. To adapt KDF to a new target dataset, an SF-SSDA algorithm, MutualSHOT, is developed, which features a consistency-based pseudo-label selection strategy. Experiments on the public TUSZ and CHSZ datasets demonstrated that KDF-MutualSHOT outperformed other supervised and source-free domain adaptation approaches in cross-subject seizure subtype classification. © 2024 IEEE.

关键词： Self-supervised learning

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Tailoring lithium intercalation pathway in 2D van der Waals heterostructure for high-speed edge-contacted floating-gate transistor and artificial synapses

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InfoMat 2024年第10期6卷 53-64页

作者： Jun Yu Jiawei Fu Hongcheng Ruan Han Wang Yimeng Yu Jinpeng Wang Yuhui He Jinsong Wu Fuwei Zhuge Ying Ma Tianyou Zhai State Key Laboratory of Materials Processing and Die and Mould Technology School of Material Science and EngineeringHuazhong University of Science and Technology(HUST)Wuhanthe People's Republic of China Hubei Yangtze Memory Laboratory School of Integrated CircuitsHuazhong University of Science and Technology(HUST)Wuhanthe People's Republic of China School of Information Engineering Zhongnan University of Economics and LawWuhanthe People's Republic of China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Nanostructure Research CenterWuhan University of TechnologyWuhanthe People's Republic of China Optics Valley Laboratory Hubeithe People's Republic of China

Local phase transition in transition metal dichalcogenides (TMDCs) by lithiumintercalation enables the fabrication of high-quality contact interfaces in twodimensional(2D) electronic devices. However, controlling the intercalation oflithium is hitherto challenging in vertically stacked van der Waalsheterostructures (vdWHs) due to the random diffusion of lithium ions in thehetero-interface, which hinders their application for contact engineering of 2DvdWHs devices. Herein, a strategy to restrict the lithium intercalation pathwayin vdWHs is developed by using surface-permeation assisted intercalationwhile sealing all edges, based on which a high-performance edge-contact MoS_(2)vdWHs floating-gate transistor is demonstrated. Our method avoids intercalationfrom edges that are prone to be random but intentionally promotes lithiumintercalation from the top surface. The derived MoS_(2) floating-gatetransistor exhibits improved interface quality and significantly reduced subthresholdswing (SS) from >600 to 100 mV dec^(–1). In addition, ultrafast program/erase performance together with well-distinguished 32 memory statesare demonstrated, making it a promising candidate for low-power artificialsynapses. The study on controlling the lithium intercalation pathways in 2DvdWHs offers a viable route toward high-performance 2D electronics for memoryand neuromorphic computing purposes.

关键词： 2D vdW heterostructure high-speed floating-gate transistor interlayer lithium intercalation engineering phase-engineered contact

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CNN channel pruning via gradient integration and knowledge distillation 17

CNN channel pruning via gradient integration and knowledge d...

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17th IEEE International Conference on Signal processing, ICSP 2024

作者： Lian, Suyun Zhao, Yang Cai, Jiajian Pei, Jihong Shenzhen University The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

ISBN: (纸本)9798350387384

With the advancement of artificial intelligence technology, intelligent applications have permeated all aspects of human life, including automatic driving, intelligent security, and face recognition. Convolutional neural networks (CNNs) are essential models for AI, but their complexity increases with more available data. The complex models are unsuitable for edge devices like wearables and smartphones due to high memory and computational requirements. In this paper, the compact model is achieved by pruning some redundant output channels. To effectively measure the validity of the output channels, this paper proposes a channel pruning algorithm based on gradient integration, which combines the gradient of the channel with the model output and the channel's values. This pruning could destroy model accuracy, so knowledge distillation is introduced during fine-tuning to leverage the original model's reasoning ability. Experiments show that our approach improves accuracy by 0.51% while reducing parameters by 30.1% and FLOPs by 26% in the VGG16 model. © 2024 IEEE.

关键词： Convolutional neural networks

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Research on Waxiang Dialect Recognition Based on Wav2vec2.0 Pre-Training and Transfer Learning

Research on Waxiang Dialect Recognition Based on Wav2vec2.0 ...

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2024 International Conference on Computing, Robotics and System Sciences, ICRSS 2024

作者： Deng, Mixuan Tang, Pengju Gao, Yanxia Li, Huixuan Zhen, Guodong Fu, Kaifeng Wu, Xiaotian Huaihua University Huaihua China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua China

ISBN: (纸本)9798331511296

As a unique local dialect, Waxiang dialect carries rich regional culture and historical information. However, with the acceleration of modernization and the increase of population mobility, the inheritance and protection of Waxiang dialect are facing severe challenges. By constructing the 'Xuewatong' APP- Waxiang dialect digital protection platform, based on cloud storage technology, digital resource display, multimedia integration and other technologies, and providing learning resources through big data analysis of user needs, it can effectively promote the digital recording and preservation of Waxiang dialect language resources, and significantly improve the dissemination and educational effect of Waxiang dialect culture, showing the great potential of digital technology in dialect protection. © 2024 IEEE.

关键词： Linguistics

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Spontaneous Recovery in Directed Dynamical Networks

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Engineering 2024年第6期37卷 208-214页

作者： Xueming Liu Xian Yan H.Eugene Stanley School of Artificial Intelligence and Automation&The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems&the Key Laboratory of Image Processing Huazhong University of Science and TechnologyWuhan 430074China Center for Polymer Studies Department of PhysicsBoston UniversityBostonMA 02215USA

Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneously return to normal after a seizure,and traffic flow can become smooth again after a *** studies on the spontaneous recovery of dynamical networks have been limited to undirected ***,most real-world networks are *** fill this gap,we build a model in which nodes may alternately fail and recover,and we develop a theoretical tool to analyze the recovery properties of directed dynamical *** find that the tool can accurately predict the final fraction of active nodes,and the prediction accuracy decreases as the fraction of bidirectional links in the network increases,which emphasizes the importance of directionality in network *** to different initial states,directed dynamical networks may show alternative stable states under the same control parameter,exhibiting hysteresis *** addition,for networks with finite sizes,the fraction of active nodes may jump back and forth between high and low states,mimicking repetitive failure-recovery *** findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

关键词： Network resilience Directed dynamical networks Spontaneous recovery

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Triboelectric nanogenerators for smart agriculture

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InfoMat 2023年第2期5卷 80-119页

作者： Shufen Dai Xunjia Li Chengmei Jiang Jianfeng Ping Yibin Ying Laboratory of Agricultural Information Intelligent Sensing School of Biosystems Engineering and Food ScienceZhejiang UniversityHangzhouPeople's Republic of China Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province HangzhouPeople's Republic of China Key Laboratory of Micro/Nano-Sensing Technology for Biological Information Acquisition ZJU-Hangzhou Global Scientific and Technological Innovation CenterHangzhouPeople's Republic of China

Rapid iterations of sensing,energy,and communication technologies transform traditional agriculture into standardized,intensive,and smart modern ***,the energy supply challenge for the plentiful sensors or other microdevices constraints the extensive application of intelligent technologies in *** nanogenerator(TENG),which efficiently converts mechanical energy into electrical energy through contact electrification and electrostatic induction,is considered a promising way to build next-generation intelligent energy supply *** efficiently harvesting low-frequency mechanical energy from the agricultural environment,including wind,rain,and water flow energy,TENGs can be a strong contender for distributed power for microdevice networks in smart *** addition,highly customizable TENGs can be combined with microdevices in agriculture to enable self-powered agricultural monitoring and production strategy *** deeply exploring the application potential of TENG in agriculture,it is conducive to further promoting unmanned production,refinement,and intelligence of agricultural production and enhancing agriculture's ability to combat natural risks.

关键词： energy harvesting Internet of Things self-powered sensor smart agriculture triboelectric nanogenerator

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