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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Ling Xu Huanhuan Yang Chao Liu Jianhang Shuai Meng Yan Yan Lei Zhou Xu Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education China School of Big Data and Software Engineering Chongqing University Chongqing China College of Computer Science and Technology Zhejiang University Hangzhou China

Searching and reusing existing code from a large scale codebase can largely improve developers' programming efficiency. To support code reuse, early code search models leverage information retrieval (IR) techniques to index a large-scale code corpus and return relevant code according to developers' search query. However, IR-based models fail to capture the semantics in code and query. To tackle this issue, developers applied deep learning (DL) techniques to code search models. However, these models either are too complex to determine an effective method efficiently or learning for semantic correlation between code and query *** bridge the semantic gap between code and query effectively and efficiently, we propose a code search model TabCS (Two-stage Attention-Based model for Code Search) in this study. TabCS extracts code and query information from the code textual features (i.e., method name, API sequence, and tokens), the code structural feature (i.e., abstract syntax tree), and the query feature (i.e., tokens). TabCS performs a two-stage attention net-work structure. The first stage leverages attention mechanisms to extract semantics from code and query considering their semantic gap. The second stage leverages a co-attention mechanism to capture their semantic correlation and learn better code/query representation. We evaluate the performance of TabCS on two existing large-scale datasets with 485k and 542k code snippets, respectively. Experimental results show that TabCS achieves an MRR of 0.57 on Hu et al.'s dataset, outperforming three state-of-the-art models CARLCS-CNN, DeepCS, and UNIF by 18%, 70%, 12%, respectively. Meanwhile, TabCS gains an MRR of 0.54 on Husain et al.'s, outperforming CARLCS-CNN, DeepCS, and UNIF by 32%, 76%, 29%, respectively.

关键词： Deep learning Correlation Semantics Syntactics Programming Feature extraction Information retrieval

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New Algorithm of QoS Constrained Routing for Node Energy Optimization of Edge computing

New Algorithm of QoS Constrained Routing for Node Energy Opt...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor systems (MASS)

作者： Degan Zhang Jinyu Du Ting Zhang Peng Yang Hongrui Fan Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China

ISBN: (数字)9781728198668

ISBN: (纸本)9781728198675

We propose an oriented edge computing nodes energy optimized QoS constrained routing algorithm. The mechanism of this algorithm is to optimize the network energy consumption and extend the network life cycle by creatively combining the edge computing technology to preprocess the original data of the node, accelerating the transmission and processing of effective data, accelerating the algorithm convergence by using the way of automata interacting with the environment and controlling the dormant activation state of the node. Through experimental testing and comparison, this paper gave the Multi-QoS constrained routing algorithm for Edge computing and Node energy optimization algorithm (MQEN), which can meet the requirements of end-to-end delay and reliability service with multi-QoS constraints when significantly reducing network energy consumption.

关键词： Energy consumption Learning automata Quality of service Routing Acceleration Optimization Edge computing

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Advancing low-light image enhancement through deep learning: A comprehensive experimental study

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Knowledge-Based systems 2025年

作者： Muhammad Tahir Rasheed Hufsa Khan Junsong Wang Yan Kang College of Big Data and Internet Shenzhen Technology University Shenzhen 518118 China Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National-Regional Key Technology Engineering Laboratory for Medical Ultrasound National Engineering Laboratory for Big Data System Computing Technology School of Biomedical Engineering Shenzhen University Shenzhen 518060 China College of Electronics and Information Engineering Shenzhen University Shenzhen 518060 China College of Health Science and Environmental Engineering Shenzhen Technology University Shenzhen 518118 China

Low-light photography severely degrades the perceptual quality of images, which adversely affects the performance of computer vision algorithms. Deep learning-based low-light image enhancement (LLIE) methods are dominating in improving the quality of degraded and corrupted images taken in non-optimal lighting conditions. Either the designed methods are evaluated on a limited set of test datasets or they are not evaluated for machine vision applications. A detailed examination of the recent developments, their generalization, and their application to computer vision tasks is required. This experimental review highlights the future trend of recent learning-based LLIE methods through statistical analysis, experimentally analyzing their generalization capability on a wide spectrum of test datasets, examining the effectiveness of LLIE in computer vision applications, and discussing a correlation between them. The test data used for the generality of these methods covers diversified scenes/contents as well as complex degradation in real scenarios. Rich variety of full-reference and no-reference metrics are applied to compare the relative performances. Furthermore, the application of enhancement methods in low-light face detection is also validated to examine the effectiveness of these LLIE methods as a preprocessing step in machine vision tasks. The discussion on correlation of experimental results from the perspective of both human and machine vision in the subsequent part provides broader view of the field. This systematic review concludes with the limitations of enhancement methodologies and unresolved issues.

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RCGA-Net: An Improved Multi-hybrid Attention Mechanism Network in Biomedical Image Segmentation

RCGA-Net: An Improved Multi-hybrid Attention Mechanism Netwo...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Xiao, Feng Shen, Cong Chen, Yu Yang, Tian Chen, Shengyong Liao, Zhijun Tang, Jijun Tianjin University of Technology School of Computer Science and Engineering Tianjin China Engineering Research Center of Learning-Based Intelligent System Ministry of Education Tianjin China School of Basic Medical Sciences Fujian Medical University Fujian Fuzhou China College of Intelligence and Computing Tianjin University Tianjin China Key Laboratory of Systems Bioengineering Ministry of Education Tianjin China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Department of Computer Science and Engineering University of South Carolina ColumbiaSC United States

ISBN: (纸本)9781665401265

Drawing support from an effective Medical Image Segmentation (MIS) is conducive to a substantial diagnostic basis for the physicians to identify the focus lesion in the patient body and give the subsequent clinical assessment of the patient status. Although various works have tried the challenging quantitative analysis problem, it is still difficult to conduct precise automatic segmentation, especially the soft tissue organs. In this decade, with the increased amount of available datasets, deep learning-based networks have achieved remarkable performance in image processing. Inspired by the state-of-the-art deep learning works, in this paper, we propose an end-to-end multi-layer network named RCGA-Net. It consists of an encoder-decoder backbone that integrates a coordinate attention mechanism based on space and channel and a global context extraction module to highlight more valuable information. To evaluate the performance of RCGA-Net, we apply it to different kinds of clinical and experimental MIS tasks to testify its generalization ability. Extensive experiments represent that our schema has taken the outperform or compatible results among the comparison methods group. Specifically, the numeric result of RCGA-Net on the pulmonary dataset has achieved a 99.12% optimum F1-score. © 2021 IEEE.

关键词： Diagnosis

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New Method of MSCA for Edge computing

New Method of MSCA for Edge Computing

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IEEE International Conference on Smart Internet of Things (SmartIoT)

作者： De-gan Zhang Hao-li Zhu Ting Zhang Jia-xu Wang Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Tianjin China Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education Tianjin

ISBN: (数字)9781728165141

ISBN: (纸本)9781728165158

By innovative use of edge computing technology to construct a node data cache model and step-by-step calculation of node channel separation, a multi-strategy channel allocation algorithm (MSCA) for edge computing is proposed. The mechanism of this algorithm is to use edge computing technology to pre-store the data in the nodes in the multicast tree and calculate the channel separation between the nodes, and then select the transmission channel number of the node with the least interference to avoid mutual interference between node information transmissions. Through experimental tests and comparisons, the MSCA algorithm for edge computing presented in this paper can minimize channel interference and overall network energy consumption while satisfying throughput and end-to-end delay.

关键词： Edge computing Interference Computational modeling Delays Peer-to-peer computing Channel allocation Protocols

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Superconductivity in pressurized trilayer La4Ni3O10-δ single crystals

arXiv

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arXiv 2023年

作者： Zhu, Yinghao Peng, Di Zhang, Enkang Pan, Bingying Chen, Xu Chen, Lixing Ren, Huifen Liu, Feiyang Hao, Yiqing Li, Nana Xing, Zhenfang Lan, Fujun Han, Jiyuan Wang, Junjie Jia, Donghan Wo, Hongliang Gu, Yiqing Gu, Yimeng Ji, Li Wang, Wenbin Gou, Huiyang Shen, Yao Ying, Tianping Chen, Xiaolong Yang, Wenge Cao, Huibo Zheng, Changlin Zeng, Qiaoshi Guo, Jiangang Zhao, Jun State Key Laboratory of Surface Physics Department of Physics Fudan University Shanghai200433 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Shanghai201203 China College of Physics and Optoelectronic Engineering Ocean University of China Shandong Qingdao266100 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Neutron Scattering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Center for High Pressure Science and Technology Advanced Research Shanghai201203 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China Center for High Pressure Science and Technology Advanced Research Beijing100094 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Institute of Nanoelectronics and Quantum Computing Fudan University Shanghai200433 China Shanghai Branch Hefei National Laboratory Shanghai201315 China

The pursuit of discovering new high-temperature superconductors that diverge from the copper-based paradigm1-3 carries profound implications for elucidating mechanisms behind superconductivity and may also enable new applications4-8. Here, our investigation reveals that application of pressure effectively suppresses the spin and charge order in trilayer nickelate La4Ni3O10-δ single crystals, leading to the emergence of superconductivity with a maximum critical temperature (Tc) of around 30 K at 69.0 GPa. The DC susceptibility measurements confirm a substantial diamagnetic response below Tc, indicating the presence of bulk superconductivity with a volume fraction exceeding 80%. In the normal state, we observe a "strange metal" behavior, characterized by a linear temperature-dependent resistance extending up to 300 K. Furthermore, the layer-dependent superconductivity observed hints at a unique interlayer coupling mechanism specific to nickelates, setting them apart from cuprates in this regard. Our findings provide crucial insights into the fundamental mechanisms underpinning superconductivity, while also introducing a new material platform to explore the intricate interplay between the spin/charge order, flat band structures, interlayer coupling, strange metal behavior and high-temperature superconductivity. © 2023, CC BY-NC-ND.

关键词： Single crystals

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Spatiotemporal variation of mortality burden attributable to heatwaves in China,1979–2020

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Science Bulletin 2022年第13期67卷 1340-1344,M0004页

作者： Huiqi Chen Liang Zhao Wei Dong Liangliang Cheng Wenjia Cai Jun Yang Junzhe Bao Xin-Zhong Liang Shakoor Hajat Peng Gong Wannian Liang Cunrui Huang School of Public Health Sun Yat-sen UniversityGuangzhou 510080China Shanghai Key Laboratory of Meteorology and Health Shanghai Meteorological ServiceShanghai 200030China The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Meteorological Disaster Ministry of Education&Joint International Research Laboratory of Climate and Environment Change&Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China Department of Earth System Science Tsinghua UniversityBeijing 100084China Institute for Environmental and Climate Research Jinan UniversityGuangzhou 510632China School of Public Health Zhengzhou UniversityZhengzhou 450001China Earth System Science Interdisciplinary Center&Department of Atmospheric and Oceanic Science University of MarylandCollege Park MD 20742USA Department of Epidemiology and Population Health London School of Hygiene and Tropical MedicineLondon WC1E 7HTUK Department of Earth Sciences the University of Hong KongHong Kong 999077China Vanke School of Public Health Tsinghua UniversityBeijing 100084China Institute of Healthy China Tsinghua UniversityBeijing 100084China

热浪通过增加死亡和发病风险导致巨大的公共卫生负担.而在气候变暖与社会经济发展相交织的风险下,中国人群所面临的热浪导致的健康负担的时间演变规律、空间分布特征及其驱动因素仍然存在大量空白.本研究应用基于事件的归因损失评估方... 详细信息

热浪通过增加死亡和发病风险导致巨大的公共卫生负担.而在气候变暖与社会经济发展相交织的风险下,中国人群所面临的热浪导致的健康负担的时间演变规律、空间分布特征及其驱动因素仍然存在大量空白.本研究应用基于事件的归因损失评估方法定量评估了过去40年格点水平的每日热浪归因死亡人数.研究发现,热浪相关死亡人数具有快速增长、非线性和极端性的特征,40年间增加了4倍,2010年代年均归因死亡人数达15500人.归因死亡负担还呈现强烈的区域异质性,华东和华中地区负担更重.随着时间的推移,中国可归因死亡人数上升的主要影响因素是增加的热浪发生频率,其次是人口增长和老龄化.这项工作为民众提供了更为直观的高温健康危害信息,同时为制定有针对性的气候变化适应措施提供重要信息.

关键词：社会经济发展气候变化适应区域异质性死亡人数损失评估公共卫生极端性发病风险

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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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AirDIV: Over-the-Air Cloud-Fog Data Integrity Verification Scheme for Industrial Cyber-Physical systems

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IEEE Journal on Selected Areas in Communications 2025年

作者： Zhao, Yao Xiang, Yong Uddin, Md Palash Zhang, Yushu Liu, Lu Liu, Yansong Gao, Longxiang Deakin University School of Information Technology VIC Australia Jiangxi University of Finance and Economics School of Computing and Artificial Intelligence Nanchang330013 China University of Exeter Department of Computer Science Exeter United Kingdom RWTH Aachen University Department of Computer Science Aachen Germany Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Jinan China

Industrial Cyber-Physical systems (ICPSs) have been motivating various Industry 4.0 endeavours, particularly with the integration of fog computing. Cloud-fog data caching paradigms, as supportive elements of ICPSs, have been adopted to cache user data, catering to diverse ICPS requirements such as data sensitivity and reduced access latency. In this hierarchical caching context, ensuring Cloud-Fog Data Integrity (CFDI) is crucial for maintaining the consistent functionality of ICPSs. Existing solutions primarily focus on examining the integrity of data cached solely on either cloud or fog nodes. However, cloud-cached data and fog-cached data are tightly coupled and should be considered simultaneously when checking data integrity. In this work, we introduce an over-the-air CFDI verification scheme, namely AirDIV, with a high accuracy and security guarantee. Instead of aggregating integrity proofs after proof transmission, AirDIV completes proof aggregation and transmission over the air for efficiency improvement. To enhance practicability, we derive adjustable parameters and formulate an optimization problem to minimize over-the-air aggregation errors. Furthermore, with an effective proof generation method, AirDIV can defend against two common attacks, i.e., replay and forge attacks. We provide a theoretical analysis of AirDIV's correctness, accuracy and security, while conducting extensive experiments on both simulated and real platforms to validate its efficiency. © 1983-2012 IEEE.

关键词： Cache memory

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Recent progress of integrated circuits and optoelectronic chips

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Science China(Information Sciences) 2021年第10期64卷 103-135页

作者： Yue HAO Shuiying XIANG Genquan HAN Jincheng ZHANG Xiaohua MA Zhangming ZHU Xingxing GUO Yahui ZHANG Yanan HAN Ziwei SONG Yan LIU Ling YANG Hong ZHOU Jiangyi SHI Wei ZHANG Min XU Weisheng ZHAO Biao PAN Yangqi HUANG Qi LIU Yimao CAI Jian ZHU Xin OU Tiangui YOU Huaqiang WU Bin GAO Zhiyong ZHANG Guoping GUO Yonghua CHEN Yong LIU Xiangfei CHEN Chunlai XUE Xingjun WANG Lixia ZHAO Xihua ZOU Lianshan YAN Ming LI School of Microelectronics Xidian University State Key Laboratory of Integrated Service Networks Xidian University National Integrated Circuit Innovation Center School of Microelectronics Fudan University School of Integrated Circuit Science and Engineering Beihang University China Center for Information Industry Development Frontier Institute of Chip and System Fudan University Institute of Microelectronics Peking University Nanjing Electronic Devices Institute State Key Laboratory of Functional Material for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Institute of Microelectronics Tsinghua University Center for Carbon-based Electronics Department of Electronics Peking University CAS Key Laboratory of Quantum Information University of Science and Technology of China CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Origin Quantum Computing Company Limited Key Laboratory of Flexible Electronics & Institute of Advanced Materials Nanjing Tech University State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China National Laboratory of Solid State Microstructures & College of Engineering and Applied Sciences Nanjing University State Key Laboratory on Integrated Optoelectronics Institute of Semiconductors Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University School of Electrical and Electronic Engineering Tiangong University Center for Information Photonics and Communications School of Information Science and TechnologySouthwest Jiaotong University School of Electronic Electrical and Communication Engineering

Integrated circuits(ICs) and optoelectronic chips are the foundation stones of the modern information society. The IC industry has been driven by the so-called "Moore's law" in the past 60 years, and now has entered the post Moore's law era. In this paper, we review the recent progress of ICs and optoelectronic chips. The research status, technical challenges and development trend of devices, chips and integrated technologies of typical IC and optoelectronic chips are focused on. The main contents include the development law of IC and optoelectronic chip technology, the IC design and processing technology, emerging memory and chip architecture, brain-like chip structure and its mechanism, heterogeneous integration, quantum chip technology, silicon photonics chip technology, integrated microwave photonic chip, and optoelectronic hybrid integrated chip.

关键词： integrated circuit semiconductor science and technology optoelectronic device and chip photonic integrated circuit wide bandgap semiconductors silicon photonics hybrid integration quantum chip integrated microwave photonic photonic neural computing

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