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Science Bulletin 2025年第8期 1264-1274页

作者：李政通张嘉汉张静燕鹏杨涛杨超林鹏孟陶陶安盟周英棠徐兴涛 The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentState Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai University Electronic-Photonic Smart Sensing Device R&D Team Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal ProcessingSchool of Electronic Information EngineeringInner Mongolia University Ningbo Key Laboratory of Green Petrochemical Carbon Emission Reduction Technology and Equipment Zhejiang Institute of Tianjin University Department of Mechanical Engineering The University of Tokyo Marine Science and Technology College Zhejiang Ocean University College of Material Science and Engineering Nanjing Forestry University

Modulating the macro/nanoarchitecture of evaporators to effectively harness diverse renewable energy sources is of paramount importance for optimizing the performance of solar-driven interfacial *** by the geometric structure of a windmill,we designed an innovative solar evaporator that expertly harnesses both strong and weak *** the purification of heavy metal wastewater,the maximum evaporation rate can reach 4.95 kg m-2h-1under one sun irradiation by introducing an ultralow wind flow (0.1 m s-1),yielding an evaporation rate that is twice that of traditional ***,the gradual deposition of inorganic salt sediments on the evaporator surface is clearly *** address this issue,we present several innovative proof-of-concept cascade treatments that significantly extend the evaporator’s operational *** innovative design and exceptional performance of this solar evaporator open avenues for advancements in sustainable water treatment,energy generation,and environmental remediation.

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Distance Guided Generative Adversarial Network for Explainable Binary Classifications

arXiv

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arXiv 2023年

作者： Xiong, Xiangyu Sun, Yue Liu, Xiaohong Ke, Wei Lam, Chan-Tong Chen, Jiangang Jiang, Mingfeng Wang, Mingwei Xie, Hui Tong, Tong Gao, Qinquan Chen, Hao Tan, Tao Faculty of Applied Sciences Macao Polytechnic University Macao999078 China for Computer Science Shanghai Jiao Tong University Shanghai200240 China Shanghai Key Laboratory of Multidimensional Information Processing School of Communication & Electronic Engineering East China Normal University Shanghai200241 China Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation Ministry of Education Shanghai201203 China School of Computer Sciecnes and Techonology Zhejiang Sci-Tech University Zhejiang Hangzhou310018 China Department of Cardiology Affiliated Hospital of Hangzhou Normal University Hangzhou Institute of Cardiovascular Diseases Hangzhou Normal University Hangzhou310015 China Department of Radiation Oncology Affiliated Hospital [Clinical College Xiangnan University Hunan Chenzhou423000 China College of Physics and Information Engineering Fuzhou University Fuzhou350108 China Department of Mathware Jiangsu JITRI Sioux Technologies Company Ltd Suzhou215000 China

Despite the potential benefits of data augmentation for mitigating the data insufficiency, traditional augmentation methods primarily rely on the prior intra-domain knowledge. On the other hand, advanced generative adversarial networks (GANs) generate inter-domain samples with limited variety. These previous methods make limited contributions to describing the decision boundaries for binary classification. In this paper, we propose a distance guided GAN (DisGAN) which controls the variation degrees of generated samples in the hyperplane space. Specifically, we instantiate the idea of DisGAN by combining two ways. The first way is vertical distance GAN (VerDisGAN) where the inter-domain generation is conditioned on the vertical distances. The second way is horizontal distance GAN (HorDisGAN) where the intra-domain generation is conditioned on the horizontal distances. Furthermore, VerDisGAN can produce the class-specific regions by mapping the source images to the hyperplane. Experimental results show that DisGAN consistently outperforms the GAN-based augmentation methods with explainable binary classification. The proposed method can apply to different classification architectures and has potential to extend to multi-class classification. We provide the code in https://***/yXiangXiong/DisGAN. Copyright © 2023, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Advanced geometry surface coding for dynamic point cloud compression

arXiv

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arXiv 2021年

作者： Xiong, Jian Gao, Hao Wang, Miaohui Li, Hongliang Ngan, King Ngi Lin, Weisi College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing210003 China School of Computer Science and Cyberspace Security Hainan University China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

In video-based dynamic point cloud compression (V-PCC), 3D point clouds are projected onto 2D images for compressing with the existing video codecs. However, the existing video codecs are originally designed for natural visual signals, and it fails to account for the characteristics of point clouds. Thus, there are still problems in the compression of geometry information generated from the point clouds. Firstly, the distortion model in the existing rate-distortion optimization (RDO) is not consistent with the geometry quality assessment metrics. Secondly, the prediction methods in video codecs fail to account for the fact that the highest depth values of a far layer is greater than or equal to the corresponding lowest depth values of a near layer. This paper proposes an advanced geometry surface coding (AGSC) method for dynamic point clouds (DPC) compression. The proposed method consists of two modules, including an error projection model-based (EPM-based) RDO and an occupancy map-based (OM-based) merge prediction. Firstly, the EPM model is proposed to describe the relationship between the distortion model in the existing video codec and the geometry quality metric. Secondly, the EPM-based RDO method is presented to project the existing distortion model on the plane normal and is simplified to estimate the average normal vectors of coding units (CUs). Finally, we propose the OM-based merge prediction approach, in which the prediction pixels of merge modes are refined based on the occupancy map. Experiments tested on the standard point clouds show that the proposed method achieves an average 9.84% bitrate saving for geometry compression. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal distortion

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Corrigendum to "Hybridization chain reaction circuit controller: CRISPR/Cas12a conversion amplifier for miRNA-21 sensitive detection" [Talanta 266 (2024) 125130]

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Talanta 2024年 269卷 125395页

作者： keyi Long Gaihua Cao Yue Qiu Nannan Yang Jian Che Mei Yang Changjun Hou Danqun Huo Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China. Chongqing University Three Gorges Hospital Chongqing 404000 PR China. Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China. Electronic address: yangmei@***. Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing School of Microelectronics and Communication Engineering Chongqing University Chongqing 400044 PR China. Electronic address: houcj@***. Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China. Electronic address: huodq@***.

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Consistent and Complementary Graph Regularized Multi-view Subspace Clustering

arXiv

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arXiv 2020年

作者： Zheng, Qinghai Zhu, Jihua Li, Zhongyu Pang, Shanmin Wang, Jun Chen, Lei School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University Shanghai200444 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing210023 China

This study investigates the problem of multi-view clustering, where multiple views contain consistent information and each view also includes complementary information. Exploration of all information is crucial for good multi-view clustering. However, most traditional methods blindly or crudely combine multiple views for clustering and are unable to fully exploit the valuable information. Therefore, we propose a method that involves consistent and complementary graph-regularized multi-view subspace clustering (GRMSC), which simultaneously integrates a consistent graph regularizer with a complementary graph regularizer into the objective function. In particular, the consistent graph regularizer learns the intrinsic affinity relationship of data points shared by all views. The complementary graph regularizer investigates the specific information of multiple views. It is noteworthy that the consistent and complementary regularizers are formulated by two different graphs constructed from the first-order proximity and second-order proximity of multiple views, respectively. The objective function is optimized by the augmented Lagrangian multiplier method in order to achieve multi-view clustering. Extensive experiments on six benchmark datasets serve to validate the effectiveness of the proposed method over other state-of-the-art multi-view clustering methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Clustering algorithms

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Corrections to “An Improved Map-Drift Algorithm for Unmanned Aerial Vehicle SAR Imaging”

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IEEE Geoscience and Remote Sensing Letters 2022年 19卷

作者： Yan Huang Feiyang Liu Zhanye Chen Jie Li Wei Hong State Key Laboratory of Millimeter Waves Southeast University Nanjing China Purple Mountain Laboratory Nanjing China Satellite Signal Processing The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China School of Microelectronics and Communication Engineering Chongqing University Chongqing China Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion Chongqing University Chongqing China National Key Laboratory of Radar Signal Processing Xidian University Xi’an China

In the above article [1] , the corresponding authors should be Yan Huang and Jie Li.

关键词： Geoscience and remote sensing Autonomous aerial vehicles Radar polarimetry

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SEBF: A single-chain based extension model of blockchain for fintech 29

SEBF: A single-chain based extension model of blockchain for...

引用

29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Ji, Yimu Gu, Weiheng Chen, Fei Xiao, Xiaoying Sun, Jing Liu, Shangdong He, Jing Li, Yunyao Zhang, Kaixiang Mei, Fen Wu, Fei School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Institue of High Performance Computing and Bigdata Nanjing University of Posts and Telecommunications Nanjing China Nanjing Center of HPC China Nanjing China Jiangsu HPC and Intelligent Processing Engineer Research Center Nanjing China Institute of Information Technology Nanjing University of Finance and Economics Nanjing China School of Software and Electrical Engineering Swinburne University of Technology Hawthorn Australia WeBank Co. Ltd. Shenzhen China College of Automation Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9780999241165

The traditional blockchain has the shortcoming that a single-chain can only deal with one or a few specific data types. The research question of how to make blockchain be able to deal with various data types has not been well studied. In this paper, we propose a single-chain based extension model of blockchain for fintech (SEBF). In the financial environment, we design a four-layer architecture for this model. By employing the external trusted oracle group and a financial regulator agency, a variety types of data can be effectively stored in the blockchain, such that the data type extension based on a single-chain is realized. The experimental results indicate that the proposed model can improve the efficiency of simplified payment verification. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Blockchain

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Target vehicle detection and tracking in surveillance videos based on exponential forgetting and perceptual hash algorithm

Advances in Transportation Studies

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Advances in Transportation Studies 2018年第Special issue期2卷 97-106页

作者： Fan, H.H. Zhu, H.J. School of Computer Engineering Jiangsu University of Technology Changzhou213001 China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Changzhou213001 China

In order to obtain the stable background of a traffic surveillance video, the application scenarios, computational complexity, and results of the Gaussian background model were analyzed. In the background modeling process, many artifacts were generated, making it difficult to reconstruct a highly stable background image. In order to solve this problem, we proposed a background model based on exponential forgetting algorithm. This method satisfies the background reconstruction of complex environment, the computation is small and the background result is pure. To further improve the accuracy of the test, shadows of the vehicle were detected to reduce the error caused on vehicle detection. The perceptual hash algorithm was used to track the target vehicle. The proposed algorithm is verified by different video data. The experimental results show that a good vehicle tracking effect is achieved in a variety of weather conditions. © 2018, Gioacchino Onorati Editore. All rights reserved.

关键词： Vehicles

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Enhancing Device-Free Gesture Recognition Capability of Mobile communication Signals

引用

IEEE Transactions on communications 2025年

作者： Wu, Jingmiao He, Weijie Sun, Kai Huang, Wei Zhang, Haijun Leung, Victor C. M. Inner Mongolia University School of Electronic Information Engineering Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Hohhot010021 China University of Science and Technology at Beijing Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Beijing100083 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Device-free gesture recognition using mobile communication signals is a convenient and efficient technology with broad application prospects in smart homes and human-computer interaction. It utilizes the effect of gestures on surrounding signals to achieve gesture recognition. The cell-specific reference signals (CRS) information can be used to achieve the task in close-range training scenarios. However, when gestures are performed at long-range or in non-training scenarios, the recognition performance will significantly degrade. To enhance device-free gesture recognition capability in arbitrary scenarios, we propose the signal quality enhancement algorithm and the gesture spectrogram construction method to solve this problem. Specifically, we superimpose the CRS information from multiple carriers to improve the gesture signal-to-noise ratio and increase the gesture sensing range. Then, we extract the gesture dynamic components from the CRS information and construct gesture spectrograms to represent scenario-independent gesture motion patterns. Using the gesture spectrogram features, we design a deep network to accomplish the gesture recognition task. We built a prototype system on a software-defined radio platform. Experimental results show that our proposed method can effectively increase the gesture sensing range from 30m² to 228m² and achieve an average recognition accuracy of 82.5% for five types of gestures in arbitrary scenarios. © 1972-2012 IEEE.

关键词： Gesture recognition

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Efficient differentiated storage architecture for large-scale flow tables in openflow networks 21

Efficient differentiated storage architecture for large-scal...

引用

21st IEEE International Conference on High Performance Computing and communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Xiong, Bing Wu, Rengeng Liao, Zhuofan Wang, Jin School of Computer AND Communication Engineering Changsha University of Science AND Technology Changsha410114 China Department of Computer and Information Sciences Temple University Philadelphia19122 United States Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science AND Technology Changsha China

ISBN: (纸本)9781728120584

As a novel network paradigm, Software Defined Networking (SDN) decouples control logic functions from data forwarding devices, and introduces a separate control plane to manipulate underlying switches via southbound interfaces like OpenFlow. However, it leads to large-scale flow tables and poses serious challenges on their storage resources and lookup performance in OpenFlow switches. This paper is thus motivated to propose an efficient differentiated storage architecture for large-scale flow tables in OpenFlow networks. Firstly, we investigate into the impact of wildcards in match fields on packet-in-batch property within a flow based on network traffic locality. Then, packet flows are dynamically distinguished into active ones and idle ones in terms of their short-term states. Subsequently, we store the match fields of active flows and idle flows respectively in TCAM and SRAM, and the content fields of both types of flows in DRAM, to effectively relieve the insufficiency of TCAM capacity. Finally, we evaluate the performance of our proposed flow table storage architecture with real network traffic traces by experiments. The experimental results indicate that our proposed storage architecture obviously outperforms the traditional one applying the elephant/mice flow differentiation method in terms of TCAM hit rates and average flow table access time. © 2019 IEEE.

关键词： Software defined networking

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