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DeCarbon 2025年 8卷

作者： Wang, Zhijie Gong, Cheng Zhang, Cong Zhao, Chenxu Su, Tzu-Sen Li, Haiyun Zhang, Hong State Key Laboratory of Photovoltaic Science and Technology Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Department of Materials Science Fudan University Shanghai 200433 China School of Energy and Mechanical Engineering Jiangxi University of Science and Technology Jiangxi Province Nanchang 330013 China School of Physics and Electronic Information Engineering Henan Polytechnic University Henan Jiaozuo 454000 China Institute of Chemical Sciences and Engineering École Polytechnique Fédérale de Lausanne (EPFL) Lausanne CH-1015 Switzerland Graduate Institute of Energy and Sustainability Tech National Taiwan University of Science and Technology No. 43 Keelung Rd. Sec. 4 Da'an Dist. Taipei City 106335 Taiwan Key Lab of Modern Optical Technologies of Education Ministry of China Soochow University Suzhou 215006 China

Through strategies such as process optimization, solvent selection, and component tuning, the crystallization of perovskite materials has been effectively controlled, enabling perovskite solar cells (PSCs) to achieve over 25 % power conversion efficiency (PCE). However, as PCE continues to improve, interfacial issues within the devices have emerged as critical bottlenecks, hindering further performance enhancements. Recently, interfacial engineering has driven transformative progress, pushing PCEs to nearly 27 %. Building upon these developments, this review first summarizes the pivotal role of interfacial modifications in elevating device performance and then, as a starting point, provides a comprehensive overview of recent advancements in normal, inverted, and tandem structure devices. Finally, based on the current progress of PSCs, preliminary perspectives on future directions are presented. © 2025 The Author(s)

关键词： Defect passivation Device stability Energy level alignment Interfacial engineering Ion migration Perovskite solar cells

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Double JPEG Compression Detection Based on Markov Model 18th

Double JPEG Compression Detection Based on Markov Model

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18th International Workshop on Digital Forensics and Watermarking, IWDW 2019

作者： Wang, Jinwei Huang, Wei Luo, Xiangyang Shi, Yung-Qing Nanjing University of Information Science and Technology Nanjing210044 China Department of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu210044 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China State Key Laboratory of Information Security Institute Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Electrical Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9783030435745

In this paper, a feature based on the Markov model in quaternion discrete cosine transform (QDCT) domain is proposed for double JPEG compression detection. Firstly, a given JPEG image is extracted from blocked images to obtain amplitude and three angles (ψ, φ, and θ). Secondly, when extracting the Markov features, we process the transition probability matrix with the corresponding refinement. Our proposed refinement method not only reduces redundant features, but also makes the acquired features more efficient for detection. Finally, a support vector machine (SVM) is employed for NA-DJPEG compression detection. It is well known that detecting NA-DJPEG compressed images with (Formula Presented) is a challenging task, and when the images with small size (i.e., 64 × 64), the detection will be more difficult. The experimental result indicates that our method can still achieve a high classification accuracy in this case. © 2020, Springer Nature Switzerland AG.

关键词： Support vector machines

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Two-Dimensional Borophene:Properties,Fabrication,and Promising Applications

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Research 2020年第1期2020卷 412-434页

作者： Zhongjian Xie Xiangying Meng Xiangnan Li Weiyuan Liang Weichun Huang Keqiang Chen Jianming Chen Chenyang Xing Meng Qiu Bin Zhang Guohui Nie Ni Xie Xiaobing Yan Han Zhang Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Institute of Microscale Optoelectronics and Otolaryngology Department and Biobank of the First Affiliated HospitalShenzhen Second People’s HospitalHealth Science CenterShenzhen UniversityShenzhen 518060China Shenzhen International Institute for Biomedical Research 518116 ShenzhenGuangdongChina National-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices Key Laboratory of Digital Medical Engineering of Hebei ProvinceCollege of Electron and Information EngineeringHebei UniversityBaoding 071002China Nantong Key Lab of Intelligent and New Energy Materials College of Chemistry and Chemical EngineeringNantong UniversityNantong226019 JiangsuChina Center for Stretchable Electronics and Nanoscale Systems Key Laboratory of Optoelectronic Devices and Systems of Ministry of EducationCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China Key Laboratory of Marine Chemistry Theory and Technology(Ocean University of China) Ministry of EducationQingdao 266100China

Monoelemental two-dimensional(2D)materials(Xenes)aroused a tremendous attention in 2D science owing to their unique properties and extensive ***,one emerging and typical Xene,has been regarded as a promising agent for energy,sensor,and biomedical ***,the production of borophene is still a challenge because bulk boron has rather intricate spatial structures and multiple chemical *** this review,we describe its excellent properties including the optical,electronic,metallic,semiconducting,photoacoustic,and photothermal *** fabrication methods of borophene are also presented including the bottom-up fabrication and the top-down *** the end,the challenges of borophene in the latest applications are presented and perspectives are discussed.

关键词： properties boron Bor

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Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos

arXiv

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arXiv 2021年

作者： Wang, Guangming Zeng, Honghao Wang, Ziliang Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom

Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone splicing based 3D human pose estimation method brings about the problem of cumulative error. In this paper, the concept of virtual bones is proposed to solve such a challenge. The virtual bones are imaginary bones between non-adjacent joints. They do not exist in reality, but they bring new loop constraints for the estimation of 3D human joints. The proposed network in this paper predicts real bones and virtual bones, simultaneously. The final length of real bones is constrained and learned by the loop constructed by the predicted real bones and virtual bones. Besides, the motion constraints of joints in consecutive frames are considered. The consistency between the 2D projected position displacement predicted by the network and the captured real 2D displacement by the camera is proposed as a new projection consistency loss for the learning of 3D human pose. The experiments on the Human3.6M dataset demonstrate the good performance of the proposed method. Ablation studies demonstrate the effectiveness of the proposed inter-frame projection consistency constraints and intra-frame loop constraints. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

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Mapping global lake dynamics reveals the emerging roles of small lakes (October, 10.1038/s41467-022-33239-3, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-12页

作者： Pi, Xuehui Luo, Qiuqi Feng, Lian Xu, Yang Tang, Jing Liang, Xiuyu Ma, Enze Cheng, Ran Fensholt, Rasmus Brandt, Martin Cai, Xiaobin Gibson, Luke Liu, Junguo Zheng, Chunmiao Li, Weifeng Bryan, Brett A. Southern University of Science and Technology School of Environmental Science and Engineering Shenzhen China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790) The University of Hong Kong Department of Urban Planning and Design Hong Kong SAR China (GRID:grid.194645.b) (ISNI:***) The University of Hong Kong Urban Systems Institute Hong Kong SAR China (GRID:grid.194645.b) (ISNI:***) Southern University of Science and Technology School of Environmental Science and Engineering Shenzhen China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790) Southern University of Science and Technology School of Environmental Science and Engineering Shenzhen China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790) University of Copenhagen Department of Geosciences and Natural Resource Management Copenhagen Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X) University of Copenhagen Department of Biology Copenhagen Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X) Lund University Department of Physical Geography and Ecosystem Science Lund Sweden (GRID:grid.4514.4) (ISNI:0000 0001 0930 2361) Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790) University of Copenhagen Department of Geosciences and Natural Resource Management Copenhagen Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X) Chinese Academy of Sciences Institute of Geodesy and Geophysics Wuhan China (GRID:grid.9227.e) (ISNI:***) Southern University of Science and Technology School of Environmental Science and Engineering Shenzhen China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790) North China University of Water Resources and Electric Power School of Water Conservancy Zhengzhou China (GRID:grid.412224.3) (ISNI:0000 0004 1759 6955) Southern University of Science and Technology School of Environmental Science and Engineering Shenzhen China (GRID:grid.263

Lakes are important natural resources and carbon gas emitters and are undergoing rapid changes worldwide in response to climate change and human activities. A detailed global characterization of lakes and their long-term dynamics does not exist, which is however crucial for evaluating the associated impacts on water availability and carbon emissions. Here, we map 3.4 million lakes on a global scale, including their explicit maximum extents and probability-weighted area changes over the past four decades. From the beginning period (1984–1999) to the end (2010–2019), the lake area increased across all six continents analyzed, with a net change of +46,278 km2, and 56% of the expansion was attributed to reservoirs. Interestingly, although small lakes (<1 km2) accounted for just 15% of the global lake area, they dominated the variability in total lake size in half of the global inland lake regions. The identified lake area increase over time led to higher lacustrine carbon emissions, mostly attributed to small lakes. Our findings illustrate the emerging roles of small lakes in regulating not only local inland water variability, but also the global trends of surface water extent and carbon *** are essential components of the hydrological and biogeochemical cycles. Here, Pi et al develop a global lake dataset called GLAKES via high-resolution satellite images and deep learning to examine global lake changes over four decades.

关键词： Hydrology Limnology

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A bi-cooperative parallel evolutionary algorithm for co-scheduling of distributed production and distribution considering shared transportation resources

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computers & Operations Research 2025年 183卷

作者： Zijiang Liu Hongyan Sang Quanke Pan Ling Wang School of Computer Liaocheng University Liaocheng 252059 China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Mechatronic and Engineering and Automation Shanghai University Shanghai 200072 China Department of Automation Tsinghua University Beijing 100084 China

This paper investigates the distributed permutation flowshop co-scheduling problem with sequence-dependent setup times (DPFCSP-SDST). A mixed-integer linear programming model is established to minimize the number of AGVs, the total AGV travel distance, and the makespan. The model is validated using the Gurobi solver. The DPFCSP-SDST contains several coupled sub-problems, including transport task assignment, transport task sequencing, processing task assignment, and processing task sequencing. We make the first attempt to propose a bi-cooperative parallel evolutionary algorithm (BCPEA) for solving such a strong NP-hard problem. The proposed BCPEA integrates a hybrid heuristic initialization and two cooperative strategies: knowledge-and-learning cooperative neighborhood search and parallel cooperative co-evolution. The hybrid heuristic initialization incorporates two initialization strategies that compete to generate a superior initial solution. The knowledge-and-learning cooperative neighborhood search employs a learning mechanism to select from 11 pre-designed neighborhood structures using empirical knowledge, with accelerated evaluation methods designed to speed up the insertion and swapping operations. In the parallel cooperative co-evolutionary algorithm, two multi-thread groups are assigned to be responsible for global and local search, respectively, and both use the iterated greedy algorithm as the optimization engine. Cooperation is achieved through elite information transfer between the multi-thread groups and useful information collection by the host process. Computational experiments demonstrate that the proposed BCPEA exhibits superior effectiveness and efficiency in solving the DPFCSP-SDST, outperforming existing methods.

关键词： Accelerated evaluation Automated guided vehicle Co-scheduling Cooperative co-evolutionary algorithm Parallel processing

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Generative Adversarial Networks for Electroencephalogram Signal Analysis: A Mini Review

Generative Adversarial Networks for Electroencephalogram Sig...

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International Winter Workshop on Brain-computer Interface (BCI)

作者： Junkongshuai Wang Wei Mu Aiping Wang Lu Wang Jiaguan Han Pengchao Wang Lan Niu Jianxiong Bin Lihua Zhang Xiaoyang Kang Shanghai Engineering Research Center of AI & Robotics MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI & Robotics Ministry of Education Institute of AI & Robotics Institute of Meta-Medical Academy for Engineering & Technology Fudan University Shanghai China Ji Hua Laboratory Foshan Guangdong Province China Yiwu Research Institute of Fudan University Chengbei Road Yiwu City Zhejiang China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou China

Brain-computer interface (BCI) technology based on electroencephalography (EEG) signals is growing rapidly and attracting widespread attention. However, due to the EEG acquisition methods, the quality and quantity of EEG signals are not able to be guaranteed. To alleviate the problems caused by the lack of data, in this paper, we introduce the applications of EEG signals using generative adversarial networks (GANs) which have shown great performance in image data augmentation and other time series data and then discuss their performance.

关键词： Time series analysis Generative adversarial networks Electroencephalography Brain-computer interfaces Signal analysis

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Efficient Random Subspace Decision Forests with A Simple Probability Dimensionality Setting Scheme

SSRN

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SSRN 2022年

作者： Wang, Quan Wang, Fei Li, Zhongheng Jiang, Peilin Ren, Fuji Nie, Feiping Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi Xi’an710049 China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing100094 China School of Software Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China Northwestern Polytechnical University Shaanxi Xi’an710072 China

The random subspace concept is widely used in decision forests. However, there is not a reasonable approach to specify the appropriate number of randomly selected features. Previous random subspace decision forests simply specify the random subspace dimensionality d s to a preset function value such as [log 2 d ] or [√ d ] where d is the number of the total feature dimensions. Actually, this preset value may be a relatively poor choice for high dimensional data sets. In this paper, a novel framework named Efficient Random Subspace decision forest (ERS) is proposed which pays attention to how to set the random subspace dimensionality for each decision tree of decision forests. Specifically, a simple discrete uniform distribution is employed to set with probability the number of randomly selected features for each tree in random subspace decision forests. The proposed Half Range Discrete Uniform distribution-based Varied Dimensionality setting (HRDUVD) method removes the hesitation of how to preset an appropriate d s for different data sets but also results in good enough classification performance along with relatively short running time. Plenty of experiments on public benchmark data sets have demonstrated the effectiveness and the efficiency of the proposed ERS. © 2022, The Authors. All rights reserved.

关键词： Decision trees

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An efficient framework for sentence similarity inspired by quantum computing

An efficient framework for sentence similarity inspired by q...

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IEEE International Conference on Big Knowledge (ICBK)

作者： Yan Yu Dong Qiu Ruiteng Yan School of computer science and technology Chongqing University of Posts and Telecommunications Nan'an Chongqing P.R. China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Nan'an Chongqing P.R. China

ISBN: (纸本)9781665438599

Accurately extracting the semantic information and the syntactic structure of sentences is important in natural language processing. Existing methods mainly combine the dependency tree to deep learning with complex computation time to achieve enough semantic information. It is essential to obtain sufficient semantic information and syntactic structures without any prior knowledge excepting word2vec. This paper proposes a model on sentence representation inspired by quantum entanglement using the tensor product to entangle both two consecutive notional words and words with depen-dencies. Inspired by quantum entanglement coefficients, we construct two different entanglement coefficients to weight the different semantic contributions of words with different relations. Finally, the proposed model is applied to SICK_train to verify their performances. The experimental results show that the provided methods achieve perfect results.

关键词： Dimensionality reduction Deep learning Tensors Quantum computing Quantum entanglement Computational modeling Semantics

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A DC-Ka-Band 7-Bit Passive Attenuator with Capacitive-Compensation-Based Bandwidth Extension Technique in 55-nm CMOS

A DC-Ka-Band 7-Bit Passive Attenuator with Capacitive-Compen...

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作者： Zhang, Zijiang Li, Nayu Gao, Huiyan Li, Min Wang, Shaogang Kuan, Yen-Cheng Song, Chunyi Yu, Xiaopeng Gu, Qun Jane Xu, Zhiwei Ocean College Institute of Marine Electronics and Intelligent Systems Zhejiang University Zhoushan China College of Information Science and Electronic Engineering Institute of VLSI Design Zhejiang University Hangzhou China Department of Electrical and Computer Engineering University of California at Davis DavisCA United States Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of Education Zhoushan316021 China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhoushan316021 China International College of Semiconductor Technology National Chiao Tung University Hsinchu30010 Taiwan

This article presents a 7-bit wideband passive attenuator with low insertion loss (IL) and high attenuation accuracy in 55-nm CMOS technology. The $\pi $ -type and bridge-T-type attenuation units utilize an effective capacitive compensation technique, whose bandwidth extension mechanism is detailed in a single-unit pole-zero analysis. The matching-induced performance deterioration is investigated to minimize amplitude and phase errors at the chip level. The fabricated attenuator demonstrates a 32.4-dB attenuation range with a 0.255-dB resolution and a 3.5-8.4-dB IL from dc to 32 GHz. The measured root-mean-square (rms) amplitude and phase errors are below 0.32 dB and 5.33°, respectively. The attenuator occupies a 0.054-mm2 core area and consumes negligible power. © 1963-2012 IEEE.

关键词： Insertion losses

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