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Adaptive disentangled target representation for unsupervised domain adaptation in remote sensing segmentation

engineering applications of Artificial Intelligence 2025年 156卷

作者： Runuo Lu Shoubin Dong Jianxin Jia Xusheng Wang Kai Liu Jinsong Chen Shanxin Guo Xiaorou Zheng Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis School of Computer Science and Engineering South China University of Technology Guangzhou 510641 China Department of Photogrammetry and Remote Sensing Finnish Geospatial Research Institute Espoo FI-02150 Finland Center for Geo-Spatial Information Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Shenzhen Engineering Laboratory of Ocean Environmental Big Data Analysis and Application Shenzhen 518055 China

Due to the significant differences between the source and target domains, semantic segmentation models for remote sensing images trained on the source domain often struggle to generalize effectively to new target domains, leading to performance degradation. Most solutions disentangle features into domain-invariant features shared by both domains and domain-specific features unique to each domain, relying primarily on the domain-invariant features for model construction and inference. However, during this process, critical domain-specific features as essential information are often discarded as noise, leading to a reduction in segmentation accuracy. To address these issues, this study proposes an unsupervised domain adaptation, called ChameleonRS 1 . ChameleonRS separates the domain-invariant features and the domain-specific features by disentanglement learning, and introduces a multi-level feature alignment module to enhance the representation of domain-invariant features. More importantly, it aligns predictions based on domain-invariant features with those based on fused invariant and specific features using contrastive learning, effectively capturing target-specific features. This study explores two cross-domain semantic segmentation tasks: (I) Geographic location variation. (II) Geographic location and imaging mode variation. Results show that under setting (I), ChameleonRS outperforms the state-of-the-art method by 4.79% in Intersection over Union (IoU) and 6.51% in the F1 score. Under setting (II), it achieves improvements of 4.46% and 4.82% in IoU and F1 score. Results demonstrate the superiority and adaptability of ChameleonRS under varying geographical and imaging conditions, effectively mitigating the generalization issues caused by distribution differences, and thereby promoting the development and application of remote sensing technologies in practical scenarios.

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Efect of Pre‑stretch Strain at High Temperatures on the Formability of AZ31 Magnesium Alloy Sheets

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Acta Metallurgica Sinica(English Letters) 2023年第1期36卷 48-60页

作者： Yongqiao Li Lifei Wang Xiaohuan Pan Qiang Zhang Guangsheng Huang Bin Xing Weili Cheng Hongxia Wang Kwang Seon Shin College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan 030024China Chongqing Innovation Center of Industrial Big-Data Co.Ltd. National Engineering Laboratory for Industrial Big-Data Application TechnologyChongqing 400707China School of Materials Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China National Engineering Research Center for Magnesium Alloys Chongqing UniversityChongqing 400044China Magnesium Technology Innovation Center School of Materials Science and EngineeringSeoul National UniversitySeoul 881416Republic of Korea

High-temperature pre-stretching experiments were carried out on the AZ31 Mg alloy at 723 K with strain levels of 2.54%,6.48%,10.92%,and 19.2%to alter the microstructure and texture for improving room-temperature *** results showed that the strain-hardening coefcient increased,while the Lankford value *** addition,the Erichsen values of all pre-stretch sheets were enhanced compared with that of the as-received *** maximum Erichsen value increased from 2.38 mm for the as-received sample to 4.03 mm for the 10.92%-stretched sample,corresponding to an improvement of 69.32%.This improvement was mainly attributed to the gradual increase in grain size,and the(0001)basal texture was weakened due to the activated non-basal slip as the high-temperature pre-stretching strain levels *** visco-plastic self-consistent analysis was performed on the as-received and high-temperature pre-stretched *** confrmed the higher activity of the prismatic slip in 10.92%-stretched sample,leading to divergence and weakening of basal texture *** results in an augmentation of the Schmid factor under diferent slip ***,it can be concluded that high-temperature pre-stretching technology provided an efective method to enhance the formability of Mg alloy sheets.

关键词： High-temperature deformation Grain growth Magnesium alloys Texture Visco-plastic self-consistent modeling Formability

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A Tutorial on Movable Antennas for Wireless Networks

arXiv

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arXiv 2025年

作者： Zhu, Lipeng Ma, Wenyan Mei, Weidong Zeng, Yong Wu, Qingqing Ning, Boyu Xiao, Zhenyu Shao, Xiaodan Zhang, Jun Zhang, Rui Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Chengdu611731 China National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Electronic and Information Engineering Beihang University Beijing100191 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada State Key Laboratory of CNS/ATM MIIT Key Laboratory of Complex-field Intelligent Sensing Beijing Institute of Technology Beijing100081 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China

Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigatio

关键词： Antenna arrays

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Organometallic-Inorganic Hybrid MXenes with Tunable Superconductivity

arXiv

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arXiv 2025年

作者： Fan, Qi Bo, Tao Guo, Wei Chen, Minghua Tang, Qing Yang, Yicong Li, Mian Chen, Ke Ge, Fangfang Li, Jialu Qiao, Sicong Wang, Changda Song, Li Yu, Lijing Guo, Jinghua Naguib, Michael Chai, Zhifang Huang, Qing Dun, Chaochao Kang, Ning Gogotsi, Yury Liang, Kun Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Key Laboratory of Special Energy Materials and Chemistry Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China University of Chinese Academy of Sciences 19 A Yuquan Rd Shijingshan District Beijing100049 China Qianwan Institute of CNITECH Ningbo315336 China Key Laboratory for the Physics and Chemistry of Nanodevices Department of Electronics Peking University Beijing100871 China Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Synchrotron Radiation Laboratory Key Laboratory of Precision and Intelligent Chemistry School of Nuclear Science and Technology University of Science and Technology of China Hefei230029 China Key Laboratory of Materials and Surface Technology Ministry of Education Sichuan Energy Equipment Intelligent Engineering Research Center School of Materials Science and Engineering Xihua University Chengdu610039 China Department of Physics and Engineering Physics Tulane University New OrleansLA70118 United States Department of Materials Science and Engineering A. J. Drexel Nanomaterials Institute Drexel University PhiladelphiaPA19104 United States

Ti-based two-dimensional transition-metal carbides (MXenes) have attracted attention due to their superior properties and are being explored across various applications1,2. Despite their versatile properties, superconductivity has never been demonstrated, not even predicted, for this important group of 2D materials. In this work, we have introduced an electrochemical intercalation protocol to construct versatile organometallic-inorganic hybrid MXenes and achieved tunable superconductivity in the metallocene-modified layered crystals. Through structural editing of MXene matrix at atomic scale and meticulously modulated intercalation route, Ti3C2Tx intercalated with metallocene species exhibits a superconductive transition temperature (Tc) of 10.2 K. Guest intercalation induced electron filling and strain engineering are responsible for the emerging superconductivity in this intrinsically non-superconducting material. Theoretically, simulated electron-phonon interaction effects further elucidate the nature of the changes in Tc. Furthermore, the Tc of crafted artificial superlattices beyond Ti-based MXenes have been predicted, offering a general strategy for engineering superconductivity and magnetism in layered hybrid materials. Copyright © 2025, The Authors. All rights reserved.

关键词： Electron-phonon interactions

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Lithium-ion Battery Storage Dispatch with Embedded Analytical Cycle Aging Mechanism 6

Lithium-ion Battery Storage Dispatch with Embedded Analytica...

引用

6th International Conference on Power and Energy Technology, ICPET 2024

作者： Long, Yilin Huang, Jingsi Wang, Jianxiao Department of Industrial Engineering and Management Peking University Beijing China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China

ISBN: (纸本)9798350375855

Battery aging is a major hindrance to the advancement of batteries, particularly in their use for deep peaking and auxiliary services in the electricity market. Although existing literature recognizes battery aging in dispatch scenarios, the analysis of aging mechanisms often depends on statistical methods such as the rainflow algorithm, which may result in empirical formulas that do not fully consider the complex coupling mechanisms involved in battery aging. In this paper, we innovatively propose a lithium-ion battery(LIB) storage dispatch model with embedded cycle aging mechanism: Firstly, the essay delves into three primary side reactions responsible for battery degradation: solid electrolyte interphase (SEI) film formation and thickening, lithium precipitation, and active particle cracking. Following this exploration, this paper delineates the impacts of these three side-reaction rates on the electrochemical model parameters. Thirdly, a pioneering model is introduced, which integrates side-reaction rates and furnishes analytical expressions for the non-uniform distributions of primary and side-reaction rates. In conclusion, the battery aging model was employed in simulations to engage in power market arbitrage, enabling a comprehensive study of the battery’s aging pattern over the course of a year. © 2024 IEEE.

关键词： Commerce

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Abnormal Clustering and Cross Slicing Transformer for Insect Fine-Grained Image Classification 2

Abnormal Clustering and Cross Slicing Transformer for Insect...

引用

2nd International Conference on Algorithm, Image Processing and Machine Vision, AIPMV 2024

作者： Mei, Aokun Huo, Hua Big Data and Computing Intelligence Engineering Technology Research Center School of Information Engineering Henan University of Science and Technology Big Data Analysis Laboratory of Henan Medical Luoyang471023 China

ISBN: (纸本)9798350390254

Insect fine-grained image classification is an application scenario in fine-grained image classification. It not only has the characteristics of small inter-class differences and large intra-class differences, but also has the difficulty that some categories have multiple life-stage forms, which makes the general fine-grained image classification model difficult to play a role in insect scenes. To this end, based on the Vision Transformer, we design a fine-grained classification network for insect images based on abnormal clustering and cross slicing, called ACCS-Trans. In the first stage of the model, we use segmentation and clustering operations to distinguish the special morphology of insects in those few-shot life stages. The model can avoid the interference of few-sample abnormal morphology on the class feature extraction of the current class during training. The second stage is the cross slicing module, which uses the anchor box of the image sample segmentation region in the first stage to cut the original sample image to form the main target image, which is used as the information supplement area of the original image. Finally, the image is divided into doubling patch groups by two vertical patch operations. In the third stage, we concatenate the multiplication patch group and input it into the Vision Transformer network for class feature extraction. We fully experiment with ACCS-Trans on two insect image datasets. Compared with the current mainstream fine-grained image classification models, ACCS- Trans achieves state-of-the-art effects on both datasets, and we do ablation experiments for each module. The effect of each module on our ACCS- Trans is analyzed. The excellent performance of our ACCS- Trans in insect scenes is verified in these experiments, these provide new ideas for the task of fine-grained classification of insect images. © 2024 IEEE.

关键词： Image segmentation

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A neural kernel framework for relation extraction

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Expert Systems with applications 2025年 286卷

作者： Kai Wang Yanping Chen Weizhe Yang Ruizhang Huang Yongbin Qin Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and Technology Guizhou University PR China State Key Laboratory of Public Big Data Guizhou University PR China

Relation extraction (RE) poses significant challenges due to the complexity of identifying semantic relationships between overlapping entity pairs within sentences. Traditional kernel-based methods effectively leverage instance-level similarities but heavily depend on manually designed kernel functions, requiring substantial domain expertise and limiting their flexibility. On the other hand, neural network approaches excel at automatically learning abstract feature representations but typically neglect critical instance-specific information, potentially missing valuable relational details during inference. These limitations motivate the exploration of a hybrid approach that effectively integrates the strengths of traditional kernels with the representational power of neural networks. In this paper, we propose a neural kernel framework designed to bridge this critical gap. The proposed framework employs neural kernels, whose parameters are initialized based on task-specific objectives and optimized through neural training procedures, enabling adaptive learning of similarity measures without relying on handcrafted kernel functions. By maintaining instance-level details through annotated training examples, neural kernels create discriminative, flexible decision boundaries tailored specifically to the relation extraction task. We further develop three complementary neural kernel components, instance kernel, description kernel, and cluster kernel, to show the advantages of kernel substitution. Extensive experiments on the ACE 2005, SemEval 2010, and CoNLL 2004 datasets demonstrate that our neural kernel framework significantly outperforms existing state-of-the-art methods, achieving F1-scores of 88.11 %, 91.08 %, and 98.63 %, respectively.

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Fast Solution Method for the Large-scale Unit Commitment Problem with Long-term Storage

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Chinese Journal of Electrical engineering 2023年第3期9卷 39-49页

作者： Bo Li Chunjie Qin Ruotao Yu Wei Dai Mengjun Shen Ziming Ma Jianxiao Wang School of Electrical Engineering Guangxi UniversityNanning 530004China State Grid Sichuan Electric Power Company Chengdu 610041China National Power Dispatching and Control Center State Grid Corporation of ChinaBeijing 100031China National Engineering Laboratory for Big Data Analysis and Applications(Peking University) Beijing 100871China

Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy ***,long-term unit commitment(UC)with LTS involves mixed-integer programming with large-scale coupling constraints between consecutive intervals(state-of-charge(SOC)constraint of LTS,ramping rate,and minimum up/down time constraints of thermal units),resulting in a significant computational ***,an iterative-based fast solution method is proposed to solve the long-term UC with ***,the UC with coupling constraints is split into several sub problems that can be solved in ***,the solutions of the sub problems are adjusted to obtain a feasible solution that satisfies the coupling ***,a decoupling method for long-term time-series coupling constraints is proposed to determine the global optimization of the SOC of the *** price-arbitrage model of the LTS determines the SOC boundary of the LTS for each sub ***,the sub problem with the SOC boundary of the LTS is iteratively solved *** proposed method was verified using a modified IEEE 24-bus *** results showed that the computation time of the unit combination problem can be reduced by 97.8%,with a relative error of 3.62%.

关键词： Constraint splitting long-term storage mix-integer programming unit commitment

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Resilience-oriented Valuation for Energy Storage Amidst Extreme Events

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Chinese Journal of Electrical engineering 2023年第3期9卷 15-25页

作者： Youzhen Wu Jianxiao Wang Yiyang Song Yunyun Xie College of Engineering Peking UniversityBeijing 100871China National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijing 100871China School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China School of Automation Nanjing University of Science and TechnologyNanjing 210094China

In power grids,the frequency is increasing of extreme accidents which have a low probability but high risk such as natural disasters and deliberate *** has sparked discussions on the resilience of power ***-storage systems(ESSs)are critical for enhancing the resilience of power ***,with their mechanism of flexible charging and discharging,adjust energy usage as needed during disasters,thereby mitigating the impact on the grid and enhancing security and ***,in turn,ensures the power system’s stable ***,there is limited systematic research quantifying the economic value of energy storage in resilience ***,a model and methodology were proposed to quantify the value of energy storage systems for enhancing grid resilience during extreme events.A two-stage stochastic optimization mathematical model was *** first stage involves pre-deployment based on day-ahead expectations,and the second stage involves simulating potential failure scenarios through real-time *** the temporal dimension,the energy storage systems with flexible regulation capabilities was used as emergency power sources to reduce occurrences of ***,a novel index was proposed that quantifies the resilience value of energy storage as the economic value of energy storage per unit of capacity,as reflected in the emergency dispatch *** index helps determine the balance between the energy storage investment cost and resilience ***,an IEEE-30 node transmission system was used to verify the feasibility and effectiveness of the proposed *** findings revealed a significant improvement in the resilience value,with a 23.49%increase observed when energy storage systems were implemented compared to the scenario without energy storage *** optimal capacity configurations for the flywheel,lithium-ion batteries,and pumped hydro storage were 10 MW,11 MW,and 12 MW,respectively,highligh

关键词： Energy storage dispatch model power system resilience resilience-oriented valuation two-stage optimization model

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Shaping future low-carbon energy and transportation systems: Digital technologies and applications

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iEnergy 2022年第3期1卷 285-305页

作者： Jie Song Guannan He Jianxiao Wang Pingwen Zhang Department of Industrial Engineering and Management College of EngineeringPeking UniversityBeijing 100871China National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijing 100871China School of Mathematical Sciences Peking Univer-sityBeijing 100871China

Digitalization and decarbonization are projected to be two major trends in the coming *** the already widespread process of digitalization continues to progress,especially in energy and transportation systems,massive data will be produced,and how these data could support and promote decarbonization has become a pressing *** paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure,common mechanisms and algorithms,and system-level impacts,as well as the application of digital technologies to coupled energy and transportation systems with electric *** paper also identifies corresponding challenges and future research directions,such as in the field of blockchain,digital twin,vehicle-to-grid,low-carbon computing,and data security and pri-vacy,especially in the context of integrated energy and transportation systems.

关键词： Digitalization decarbonization energy system transportation system energy and transportation integration.

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