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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Ying Du Pu Cheng School of Computer and Information Engineering Henan University Kaifeng China Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China School of Software Henan University Kaifeng China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

Geographic information system (GIS)-document workflows are formed by combining workflow and GIS, and have the capabilities of geographic data processing, analysis, and visualization. They are widely used in areas with “integration of map and document.” An increasing number of complex business processes have great demands for business logic control and geographic data processing. Therefore, we established the framework of GIS - document workflow system in order to face the complex business processes and large geographic data processing processes.

关键词： Process control data visualization data processing Faces Geographic information systems Business Software engineering

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Access control of blockchain based on dual-policy attribute-based encryption

Access control of blockchain based on dual-policy attribute-...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Daojun Han Jinyu Chen Lei Zhang Yatian Shen Xueheng Wang Yihua Gao Institute of Data and Knowledge Engineering School of Computer and Information Engineering Henan University Kaifeng China Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Henan University Kaifeng China

In scenarios where multiple parties such as the Internet of Things and Supply Chains participate in data sharing and computing, when accessing data, users not only need to accept the forward access control of the data owner, but also needs to perform reverse access control on the data, so as to realize two-way access control. In the traditional blockchain, all users can participate in accounting and view transaction data, and only protect user privacy through “pseudo-anonymity”. The access rights of different users cannot be distinguished, which cannot meet the user's two-way access control needs. However, most of the existing blockchain-based access control schemes are one-way access control, which cannot meet the needs of users for two-way access control in scenarios such as the Internet of Things and Supply Chains. Therefore, it is particularly important to design a two-way access control mechanism suitable for application in the blockchain. On this basis, this paper proposes a dual strategy attribute-based encryption (ABE) scheme for distributed outsourcing. This scheme combines two existing schemes, ciphertext-policy ABE and key-policy ABE, and proposes two access structures and a structure of attribute sets. The primary access structure and the secondary attributes are stored in the ciphertext, and the secondary access structure and the primary attributes are stored in the user's private key. Only when the primary attribute set satisfies the primary access structure and the secondary attribute set satisfies the secondary access structure can the user unlock the ciphertext. This scheme has no single authorization center; instead, blockchain nodes jointly participate in authorization. In addition, the proposed scheme outsources the encryption and decryption of the ciphertext to blockchain nodes to reduce the computing pressure on users and can adapt to the decentralized environment of the blockchain and provide users with two-way access control services. Finally

关键词： Authorization data privacy High performance computing Conferences Supply chains Blockchain Permission

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Relays Selection Algorithm of Collaborative Communication Network on Condition of Channel Statistic Information Error

Relays Selection Algorithm of Collaborative Communication Ne...

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IEEE International Conference on Signal processing, Communications and Computing (ICSPCC)

作者： Yong Zhang Junwei Li Kunlin Song Yong Jin Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng PR China School of Information and Electronics Beijing Institute of Technology Beijing PR China

ISBN: (数字)9781728172026

ISBN: (纸本)9781728172033

To date, an original method has been proposed for regional collaborative relays and relays selection based in cognitive radio networks. Considering the different fading characteristics between users and relays in communication links, the regional collaborative relays are introduced to optimize the allocation of powers through selecting available relays. Moreover, the ℓ0-norm usually is replaced with ℓl-norm which is used as the closet convex approximation. Therefore, the neoteric NP-hard optimal problem can be relaxed as a tractable convex optimization problem. Therefore, a computationally efficient and near-optimal solution is obtained by an iteratively re-weighted algorithm. Simulations show that the proposed algorithm satisfied the predetermined service levels at relatively small excess transmission power in collaborative relay network scenarios.

关键词： Relays Collaboration Interference Signal to noise ratio Array signal processing Transforms Channel estimation

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EXISTENCE AND CONTROLLABILITY FOR NONLINEAR FRACTIONAL CONTROL SYSTEMS WITH DAMPING IN HILBERT SPACES

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Acta Mathematica Scientia 2019年第1期39卷 229-242页

作者： Xiuwen LI Zhenhai LIU Jing LI Chris TISDELL School of Science Nanjing University of Sciences and Technology Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Hunan Province Key Laboratory of Mathematical Modelling and Analysis in Engineering Department of Mathematics and Statistics Changsha University of Science and Technology Faculty of Science The University of New South Wales UNSW

In this paper, we are concerned with the existence of mild solution and controllability for a class of nonlinear fractional control systems with damping in Hilbert *** first step is to give the representation of mild solution for this control system by utilizing the general method of Laplace transform and the theory of(α, γ)-regularized families of operators. Next, we study the solvability and controllability of nonlinear fractional control systems with damping under some suitable sufficient conditions. Finally, two examples are given to illustrate the theory.

关键词： existence controllability fractional control systems damping regularized resolvent family

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analysis of the Causes of Cyanobacteria Bloom:A Review

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Journal of Resources and Ecology 2020年第4期11卷 405-413页

作者： ZHOU Bing CAI Xiaoli WANG Sen YANG Xinxin Key Laboratory of Analysis and Processing of Big Data Kaifeng 475004HenanChina School of Computer and Information Engineering Henan UniversityKaifeng 475004HenanChina School of Information Management Wuhan UniversityWuhan 430072China

Among water blooms,cyanobacteria bloom occurs over the widest range and is much more harmful than other *** occurrence in inland water bodies is affected by many factors,such as meteorology,hydrology,and human ***,the study of the causes of cyanobacterial bloom has become a major focus of *** China Knowledge Network Journal database contains 143 papers from China and abroad from the years 2004 to 2019 that are relevant to the study of cyanobacteria *** begin by analyzing keywords in these studies and creating a keyword distribution map which indicates the factors related to the *** on parameters such as the frequency of words appearing in the text,the full text of each of the 143 papers is analyzed to form a word cloud created by a program written in Python *** irrelevant terms are eliminated,the word cloud map can reveal potential factors that were not identified by keywords *** completing this macro analysis,we examined approximately 100 related papers from the China Knowledge Network Journal database and Web of Science database published from 2014 to ***,we summarize the main reasons for the outbreak of water *** factors causing blooms can be divided into natural factors and human *** the natural factors are illumination,water temperature and nutrient salt *** human factors are generally related to large-scale water conservancy *** paper analyzes and summarizes these factors,and provides a reference to aid in the prevention and treatment of algal *** information in the paper has a certain practical significance for the protection of water environments.

关键词： algae bloom eutrophication literature measurement temperature

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Adaptive Deployment of UAV-Aided Networks Based on Hybrid Deep Reinforcement Learning

Adaptive Deployment of UAV-Aided Networks Based on Hybrid De...

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IEEE Conference on Vehicular Technology (VTC)

作者： Xiaoyong Ma Shuting Hu Danyang Zhou Yi Zhou Ning Lu School of Computer and Information Engineering Henan University Kaifeng China International Joint Research Laboratory for Cooperative Vehicular Networks of Henan Henan China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng PR China Queen’s University Kingston Ontario Canada

ISBN: (数字)9781728194844

ISBN: (纸本)9781728194851

Unmanned aerial vehicles (UAVs) can be used as air base stations to provide fast wireless connections for ground users. Due to their constraints on both mobility and energy consumption, a key problem is how to deploy UAVs adaptively in a geographic area with changing traffic demand of mobile users, while meeting the aforemetioned constraints. In this paper, we propose an adaptive deployment strategy for UAV-aided networks based on hybrid deep reinforcement learning, where a UAV can adjust its movement direction and distance to serve users who move randomly in the target area. Through hybrid deep reinforcement learning, UAVs can be trained offline to obtain the global state information and learn a completely distributed control strategy, with which each UAV only needs to take actions based on its observed state in the real deployment to be fully adaptive. Moreover, in order to improve the speed and effect of learning, we improve hybrid reinforcement learning, by adding genetic algorithms and TD-error-based resampling optimization mechanism. Simulation results show that the hybrid deep reinforcement learning algorithm has better efficiency and robustness in multi-UAV control, and has better performance in terms of coverage, energy consumption and average throughput, by which average throughput can be increased by 20% to 60%.

关键词： Energy consumption Adaptive systems Simulation Reinforcement learning Throughput Unmanned aerial vehicles Optimization

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An improved method of algal-bloom discrimination in Taihu Lake using Sentinel-1A data 6

An improved method of algal-bloom discrimination in Taihu La...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Wu, Lin Sun, Mengwei Min, Lin Zhao, Jianhui Li, Ning Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China

ISBN: (纸本)9781728129129

The algal bloom is a prominent manifestation of water pollution. Synthetic aperture radar (SAR) shows an advantage in water monitoring due to its characteristic of all-time and all-weather. The water regions where algae gather present dark in SAR image. However, dark regions may also be caused by other factors, such as low wind. This paper proposes an improved algal bloom discrimination method based on Artificial Neural Network (ANN) to recognize the dark regions of algal bloom. Taihu Lake is chosen as the research area in this study because of its serious bloom in recent years. By means of quasi-synchronous optical images, the dark region database of SAR images labeled algal bloom and non-algal bloom are obtained. Then the segmentation algorithm and region growing algorithm are used to acquire the feature from dark regions, and divided into training feature set and testing feature set. Finally, the training and testing feature set are used for ANN-based discrimination model construction and verification. According the experimental results, the overall accuracy reaches 80%, which indicates that ANN model has a good applicability in algal bloom recognition of SAR image. © 2019 IEEE.

关键词： Neural networks

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Optimizing Convolutional Neural Networks Architecture Using a Modified Particle Swarm Optimization for Image Classification

SSRN

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SSRN 2022年

作者： Elhani, Djenaihi Megherbi, Ahmed Chaouki Zitouni, Athmane Dornaika, Fadi Sbaa, Salim Taleb-Ahmed, Abdelmalik Laboratory of LESIA University of Biskra Algeria Department of Electrical Engineering University of Biskra BP 145 RP Biskra07000 Algeria Laboratory of LI3C University of Biskra Algeria Department of Electrical Engineering University of Biskra BP 145 RP Biskra07000 Algeria Henan University Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China University of the Basque Country UPV/EHU Manuel Lardizabal 1 San Sebastian20018 Spain IKERBASQUE Basque Foundation for Science Bilboa Spain Univ. Polytechnique Hauts-de-France Univ. Lille CNRS Centrale Lille UMR CNRS 8520 ValenciennesF-59313 France

Although the Convolutional Neural Network (CNN) has been shown to be effective in solving image classification tasks, its architecture is often difficult to design (i.e., much tuning is required for optimization) due to the large number of hyperparameters that require careful human intervention to determine their optimal values. In this paper, we propose an approach to create the best CNN design and reduce human intervention during this process. The approach uses an optimization algorithm derived from the particle swarm without velocity (PSWV) equation to significantly reduce the number of iterations to determine the optimal CNN hyperparameters and architecture for a given dataset. A novel strategy for updating a particle swarm without velocity using particle swarm optimization (PSO) with CNNs was developed. In this approach, we adopted the variable-length coding strategy to represent the particles in the population. We proposed an algorithm for a suitable process that allows fast convergence to the best architecture. The proposed algorithm was studied and compared with several recent algorithms in the literature. Experiments on eight benchmark datasets for classification tasks have demonstrated the efficiency and practicality of our approach in finding the best CNN architecture with less human intervention. © 2022, The Authors. All rights reserved.

关键词： Image classification

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Influence of Elevation and Orbit Interpolation on the Accuracy of R-D Location Model

Influence of Elevation and Orbit Interpolation on the Accura...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Minghu Fan Xianyu Zuo Junfeng Tian Key Laboratory of Big Data Analysis and Processing of Henan Province College of Computer Science and Information Engineering Henan University Kaifeng China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

R-D model is the most commonly location model in geometric processing of SAR images. How to improve its location accuracy has been one of the focuses in application. Based on the in-depth analysis of the solving process of R-D equation, two kinds of influencing factors are selected to study. They are elevation and satellite orbit interpolation method. Then, aiming at the pixel location of high-resolution spaceborne SAR images, three kinds of DEM and two orbit interpolation algorithms were studied. The experimental results show that these two kinds of factors mainly affect the location accuracy of range direction, both the horizontal and vertical resolution of elevation have great influence on location accuracy, the quartic polynomial orbit interpolation can meet requirements of high accuracy location, and further improvement of the location accuracy need other auxiliary means.

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Parallel Geometric Correction for Single Spaceborne SAR Image

Parallel Geometric Correction for Single Spaceborne SAR Imag...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

The fast processing of SAR images is of great significance for SAR applications, and parallel computing is the most common solution. The paper studied the parallel computing algorithm for the geometric correction of single spaceborne SAR image, which is based on a classical serial geometric correction algorithm. After fully analyzing the parallel features of the algorithm, a CPU-oriented and a GPU-oriented global parallel correction algorithm were designed. Then, two spaceborne SAR images were used to test the speedup performance of the two algorithms. The experimental results show that the two parallel algorithms can greatly improve the speed of the geometric correction of spaceborne SAR image, and the performance of CPU-oriented parallel algorithm is mainly related to the number of CPU/cores, while the performance of GPU-oriented parallel algorithm is mainly related to the data granularity, and the latter has very high speedup ratio and is an efficient method for geometric correction of spaceborne SAR image.

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