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Heterogeneous-attributes enhancement deep framework for network embedding

Frontiers of Computer Science 2021年第6期15卷 121-131页

作者： Lisheng QIAO Fan ZHANG Xiaohui HUANG Kai LI Enhong CHEN Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of ChinaHefei 230022China National Key Laboratory of Blind Signal Processing Chengdu 610041China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230022China

Network embedding,which targets at learning the vector representation of vertices,has become a crucial issue in network ***,considering the complex structures and heterogeneous attributes in real-world networks,existing methods may fail to handle the inconsistencies between the structure topology and attribute ***,more comprehensive techniques are urgently required to capture the highly non-linear network structure and solve the existing inconsistencies with retaining more *** that end,in this paper,we propose a heterogeneous-attributes enhancement deep framework(HEDF),which could better capture the non-linear structure and associated information in a deep learningway,and effectively combine the structure information of multi-views by the combining *** this line,the inconsistencies will be handled to some extent and more structure information will be preserved through a semi-supervised *** extensive validations on several real-world datasets show that our model could outperform the baselines,especially for the sparse and inconsistent situation with less training data.

关键词： network embedding heterogeneous-attributes deep framework inconsistent

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Design of real-time feedback control of vertical growth rate on EAST

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Nuclear Science and Techniques 2021年第7期32卷 99-107页

作者： Na-Na Bao Yao Huang Bing-Jia Xiao Qi-Ping Yuan Zheng-Ping Luo Yue-Hang Wang Shu-Liang Chen School of Internet Anhui UniversityHefei 230039China Institute of Plasma Physics Chinese Academy of SciencesHefei 230031China National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230039China

Real-time feedback control of vertical growth rate,called gamma control,has been successfully applied to experimental advanced superconducting tokamak(EAST).In this paper,a new gamma control method is proposed to regulate the vertical growth rate,which is an estimator of plasma vertical ***,the gamma controller can be utilized to keep the tokamak plasma away from its unstable *** this work,the main development process includes three steps:(1)real-time implementation of model-based vertical growth rate calculation,taking advantage of GPU parallel computing capability,(2)design of plasma shape response for dynamic shape control using a slight modification to the plasma boundary,and(3)development of a gamma control algorithm integrated into the EAST plasma control system(PCS).The gamma control was experimentally verified in the EAST 2019 experiment *** is shown that the time evolution of the real-time vertical growth rate agrees with the target value,indicating that the real-time vertical growth rate can be regulated by gamma control.

关键词： Experimental advanced superconducting tokamak(EAST) Dynamic shape response Gamma control Vertical growth rate

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Insect Recognition Based on Complex Frequency Domain Transform and Multi-feature Fusion 5

Insect Recognition Based on Complex Frequency Domain Transfo...

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2020 5th International Conference on Intelligent Computing and Signal Processing, ICSP 2020

作者： Bao, Wenxia Qiu, Xiang Huang, Linsheng Liang, Dong Li, Yongluo National Engineering Research Center Agro-Ecological Big Data Analysis and Application Anhui University Anhui Hefei230601 China

The accurate recognition of insects is of great significance for the protection and treatment of crops, vegetables and fruit trees. In order to improve the accuracy of insect images classification at the order level, the insect recognition algorithm based on complex frequency domain transform and multi-feature fusion is proposed in this paper. Firstly, the color features and Histogram of Oriented Gradient features of the insect images were extracted in the spatial domain. Secondly, the multi-scale and multi-directional complex frequency domain transform was performed on the images using the Multi-directional Dual Tree Complex Wavelet Transform. The shape features and texture features were obtained from the low frequency sub-band images. Finally, the spatial domain features and the complex frequency domain features were fused using the Relief-F algorithm, and the Support Vector Machine was used to recognition the insect images at the order level. The results of insect images recognition at nine orders level showed that the proposed method of multi-feature fusion in complex frequency domain and spatial domain can significantly improve the accuracy of insect recognition. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Support vector machines

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Transient transition behaviors of fractional-order simplest chaotic circuit with bi-stable locally-active memristor and its ARM-based implementation

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Chinese Physics B 2021年第12期30卷 88-101页

作者： Zong-Li Yang Dong Liang Da-Wei Ding Yong-Bing Hu Hao Li School of Electronics and Information Engineering Anhui UniversityHefei 230601China National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230601China State Grid Lu’an Electric Power Supply Company Lu’an 237006China

This paper proposes a fractional-order simplest chaotic system using a bi-stable locally-active *** characteristics of the memristor and transient transition behaviors of the proposed system are analyzed,and this circuit is implemented digitally using ARM-based ***,the mathematical model of the memristor is designed,which is nonvolatile,locally-active and ***,the asymptotical stability of the fractional-order memristive chaotic system is investigated and some sufficient conditions of the stability are ***,complex dynamics of the novel system are analyzed using phase diagram,Lyapunov exponential spectrum,bifurcation diagram,basin of attractor,and coexisting bifurcation,coexisting attractors are *** of these results indicate that this simple system contains the abundant dynamic ***,transient transition behaviors of the system are analyzed,and it is found that the behaviors of transient chaotic and transient period transition alternately ***,the hardware implementation of the fractional-order bi-stable locally-active memristive chaotic system using ARM-based STM32F750 is carried out to verify the numerical simulation results.

关键词： fractional calculus bi-stable locally-active memristor transient transition behaviors ARM implementation

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Robust and Trustworthy data Sharing Framework Leveraging On-Chain and Off-Chain Collaboration

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Computers, Materials & Continua 2024年第2期78卷 2159-2179页

作者： Jinyang Yu Xiao Zhang Jinjiang Wang Yuchen Zhang Yulong Shi Linxuan Su Leijie Zeng School of Computer Science Northwestern Polytechnical UniversityXi’an710072China MIIT Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityXi’an710072China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical UniversityXi’an710072China

The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy *** distributed storage systems are hindered by centralized management and lack traceability,while blockchain systems are limited by low capacity and high *** address these challenges,the present study investigates the reliable storage and trustworthy sharing of IoT data,and presents a novel system architecture that integrates on-chain and off-chain data manage *** architecture,integrating blockchain and distributed storage technologies,provides high-capacity,high-performance,traceable,and verifiable data storage and *** on-chain system,built on Hyperledger Fabric,manages metadata,verification data,and permission information of the raw *** off-chain system,implemented using IPFS Cluster,ensures the reliable storage and efficient access to massive files.A collaborative storage server is designed to integrate on-chain and off-chain operation interfaces,facilitating comprehensive data *** provide a unified access interface for user-friendly system *** testing validates the system’s reliability and stable *** proposed approach significantly enhances storage capacity compared to standalone blockchain *** reliability tests consistently yield positive *** average upload and download throughputs of roughly 20 and 30 MB/s,respectively,the system’s throughput surpasses the blockchain system by a factor of 4 to 18.

关键词： On-chain and off-chain collaboration blockchain distributed storage system hyperledger fabric IPFS cluster

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Calculation Method of Lane Saturated Flow Rate Based on Asphalt Material 10

Calculation Method of Lane Saturated Flow Rate Based on Asph...

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10th Annual International Conference on Material Science and Environmental engineering, MSEE 2022

作者： Liang, Zijun Zhan, Xuejuan Wang, Ruihan Li, Yuqi School of Urban Construction and Transportation Hefei University China Anhui Province Transportation Big Data Analysis and Application Engineering Laboratory China

In order to improve the calculation accuracy and popularity of intersection lane saturated flow rate, we propose a calculation method of lane saturated flow ratebased on asphalt material. Firstly, environmentally friendly modified asphalt material is used to pave the intersection lanes to improve the smoothness and friction of the road *** by millisecond level electric alarmvehicle data for measuring basis, using the small time interval method to extract thedata of green light saturated time *** K-means algorithm clustering analysis, the percentage of different time headway clusters after clustering is analyzed, and the average value of time headway of representatives group as saturated time headway, and the saturated flow rate in the measured period is further ***, an example analysis is carried out on the vehicle data of Eshan Road and Huajin South Road in Wuhu City. The saturated flow rate calculated by the proposed method is 1478.68veh/h. Compared with the manual observation method, the relative error is less than 3%, which verified the accuracy and effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Flow rate

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HyperCalm Sketch: One-Pass Mining Periodic Batches in data Streams 39

HyperCalm Sketch: One-Pass Mining Periodic Batches in Data S...

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Liu, Zirui Kong, Chaozhe Yang, Kaicheng Yang, Tong Miao, Ruijie Chen, Qizhi Zhao, Yikai Tu, Yaofeng Cui, Bin Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peng Cheng Laboratory Shenzhen China Zte Corporation China

ISBN: (纸本)9798350322279

Batch is an important pattern in data streams, which refers to a group of identical items that arrive closely. We find that some special batches that arrive periodically are of great value. In this paper, we formally define a new pattern, namely periodic batches. A group of periodic batches refers to several batches of the same item, where these batches arrive periodically. Studying periodic batches is important in many applications, such as caches, financial markets, online advertisements, networks, etc. We propose a one-pass sketching algorithm, namely the HyperCalm sketch, which takes two phases to detect periodic batches in real time. In phase 1, we propose a time-aware Bloom filter, namely HyperBloomFilter (HyperBF), to detect the start of batches. In phase 2, we propose an enhanced top-k algorithm, called Calm Space-Saving (CalmSS), to report top-k periodic batches. We theoretically derive the error bounds for HyperBF and CalmSS. Extensive experiments show HyperCalm outperforms the strawman solutions 4× in term of average relative error and 13.2× in term of speed. We also apply HyperCalm to a cache system and integrate HyperCalm into Apache Flink. All related codes are open-sourced. © 2023 IEEE.

关键词： Error analysis

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Adaptive offloading scheme of fine-grained tasks based on reinforcement learning in multi-access edge computing

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Simulation Modelling Practice and Theory 2025年

作者： Jie Li Ge Chen Kansong Chen School of Computer Science and Information Engineering Hubei University Wuhan 430062 China Hubei Key Laboratory of Big Data Intelligent Analysis and Application (Hubei University) Wuhan 430062 China Engineering Research Center of Hubei Province in Intelligent Government Affairs and Application of Artificial Intelligence Wuhan 430062 China Key Laboratory of Intelligent Sensing System and Security (Hubei University) Ministry of Education Wuhan 430062 China

In the context of multi-access edge computing, the constraints on device resources and energy pose a challenge in meeting the requirements of delay-sensitive and high-resource demand tasks. In order to address this issue, this paper puts forth an adaptive offloading decision based on fine-grained task sequencing (AOD-FTS). To enhance task execution efficiency and resource utilization, we design scheduling optimization for subtasks algorithm within the fine-grained task model to optimize the execution order of subtasks and improve subtask parallelism. Additionally, to reduce task delay and energy consumption, we propose an adaptive multi-objective reinforcement learning offloading algorithm based on ordered subtasks, formulated through multi-objective Markov decision processes. The scheme dynamically adjusts optimization preferences according to environmental changes and task completion states to make offloading decisions. Simulation results demonstrate that compared with two benchmark algorithms, the proposed AOD-FTS scheme achieves: (1) higher task completion rates, (2) improved resource utilization efficiency, (3) 81.66% and 51.53% reductions in delay respectively, and (4) 39.72% and 71.36% reductions in energy consumption respectively.

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RGB image and Monochromatic image of hyperspectral image for Identification of apple fungi infection 8

RGB image and Monochromatic image of hyperspectral image for...

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8th International Symposium on Advances in Electrical, Electronics, and Computer engineering, ISAEECE 2023

作者： Lv, Wenbing Chang, Haoyu Zhang, Shengyu Weng, Shizhuang Zheng, Ling National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University 111 Jiulong Road Hefei China

ISBN: (纸本)9781510666290

Detection of apple fungi infection is significant to provide the customized prevention and control strategies and ensure food safety. In this study, an identification method of infection of Botrytis cinerea and Rhizopus stolonifera was developed using the RGB images and monochromatic images (MIs) of effective wavelengths (EWs) of hyperspectral imaging. RGB images converted by CIE 1931 colour matching functions, and MIs of EWs were screened by random frog from hyperspectral images. U-Net combining data splicing strategy was adopted to segment the region of rot (ROR). Network features of RGB images and MIs of EWs of ROR were extracted by VGG16 and adopted to develop the classification models of fungi infection by using SVM, RF and KNN. The fused features of two-type images obtained the better classification, outperforming the other one-type image, and the optimal accuracy in prediction set of 99.25% was gotten from the SVM model. The proposed method provides the accurate detection of apple fungi infection and is beneficial to improve the quality of apple fruit. © 2023 SPIE. All rights reserved.

关键词： Hyperspectral imaging

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WOBTree:a write-optimized B+-tree for non-volatile memory

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Frontiers of Computer Science 2021年第5期15卷 37-51页

作者： Haitao WANG Zhanhuai LI Xiao ZHANG Xiaonan ZHAO Song JIANG School of Computer Science and Engineering Northwestern Polytechnical UniversityXi'An 710072China Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityMinistry of Industry and Information TechnologyXi'An 710072China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’An 710072China Department of Computer Science and Engineering University of Texas at ArlingtonArlingtonTX 76010USA

The emergence of non-volatile memory(NVM)has introduced new opportunities for performance optimizations in existing storage *** better utilize its byte-addressability and near-DRAM performance,NVM can be attached on the memory bus and accessed via load/store memory instructions rather than the conventional block *** this scenario,a cache line(usually 64 bytes)becomes the data transfer unit between volatile and non-volatile ***,the failure-atomicity of write on NVM is the memory bit width(usually 8 bytes).This mismatch between the data transfer unit and the atomicity unit may introduce write amplification and compromise data consistency of node-based data structures such as B+-*** this paper,we propose WOBTree,a Write-Optimized B+-Tree for NVM to address the mismatch problem without expensive *** minimizes the update granularity from a tree node to a much smaller subnode and carefully arranges the write operations in it to ensure crash consistency and reduce write *** results show that compared with previous persistent B+-tree solutions,WOBTree reduces the write amplification by up to 86× and improves write performance by up to 61× while maintaining similar search performance.

关键词： non-volatile memory B+-tree atomic granularity mismatch write amplification performance optimization

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